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PRODUCT USER MANUAL For Sea Level SLA products
SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001 SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002
SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003 SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004 SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005
WP leader CLS Gilles Larnicol France Issue 31
Contributors Franccediloise Mertz Rosmorduc Vinca Anne Delamarche Gilles Larnicol
MyOcean version scope Version 21
Approval Date 20 July 2012
Project Ndeg FP7-SPACE-2007-1
Work programme topic SPA20071101 - development of upgraded capabilities for existing GMES fast-track services and related (pre)operational services Duration 39 Months
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
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CHANGE RECORD
Issue Date sect Description of change Author Validated by
10 20110101 all First version of document FranccediloiseMertz VincaRosmorducAnne Dela-marche
Gilles Larnicol
11 20110223 all Correction of anomaliesin the format of the file
FranccediloiseMertz VincaRosmorducAnne Dela-marche
Gilles LarnicolGeacuterald Dibar-boure
20 20110901 all Version V2 of MyOceanproducts
FranccediloiseMertz VincaRosmorducAnne Dela-marche
Gilles LarnicolGeacuterald Dibar-boure
21 20111031 all New template FranccediloiseMertz VincaRosmorducAnne Dela-marche
Gilles LarnicolGeacuterald Dibar-boure
22 20120224 all Version V21 FranccediloiseMertz VincaRosmorducAnne Dela-marche
Gilles LarnicolGeacuterald Dibar-boure
30 20120525 all End of Envisat missionand addition of Jason-1 onits geodetic orbit (j1g)
FranccediloiseMertz VincaRosmorducAnne Dela-marche
Gilles LarnicolGeacuterald Dibar-boure
31 20120720 all New version D of Jason-2IGDR
FranccediloiseMertz VincaRosmorducAnne Dela-marche
Gilles LarnicolGeacuterald Dibar-boure
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CONTENTS
I Introduction 11
II Updates in 2011 and 2012 14II1 Version D of input IGDROGDR Jason-2 data for NRT processing (July 30 2012) 14II2 Integration of Jason-1 on its geodetic orbit (May 2012) 14II3 Envisat has stopped sending data (April 2012) 15II4 Integration of the Cryosat2 Mission (February 2012) 16
II41 Generalities about the mission 16II42 Integration in DUACS 17
II5 Addition of Europe and Arctic products (January 2012) 18
IIISSALTODUACS system 20III1 Introduction 20III2 Near Real Time processing steps 22
III21 Input data models and corrections applied 22III22 Acquisition 25III23 Homogenization 26III24 Input data quality control 26III25 Multi-mission cross-calibration 27III26 Product generation 28
III261 Computation of raw SLA 28III262 Cross validation 29III263 Filtering and sub-sampling 29
III27 Quality control 30III271 Final quality Control 30III272 Performance indicators 31
III3 Delayed Time processing steps 32III31 Input data models and corrections applied 32III32 Acquisition 35III33 Homogenization 35III34 Input data quality control 35III35 Multi-mission cross-calibration 36III36 Product generation 37
III361 Computation of raw SLA 37III362 Cross validation 38III363 Filtering and sub-sampling 38
III37 Quality control 39III371 Final quality Control 39
IV MyOcean Products 40IV1 Near Real Time Products 40
IV11 Delay of the products 40IV12 Temporal availibility 40
IV2 Delayed Time Products 40IV21 Delay of the products 41IV22 Temporal availibility 41
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V Description of the product specification 42V1 General information 42
VI Nomenclature of files 47VI1 Nomenclature of files downloaded through the MyOcean Web Portal DirectgetfileService 47
VI11 Nomenclature of the product line 47VI12 Nomenclature of the datasets 48VI13 Nomenclature of the NetCdf files 49
VIIData format 50VII1NetCdf 50VII2Structure and semantic of NetCDF along-track files 51
VIIIHow to download a product 55VIII1Download a product through the MyOcean Web Portal Directgetfile Service 55
IX News and Updates 56IX1 [Duacs] Operational news 56IX2 Updates 56
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LIST OF TABLES
1 Characteristics of the geodetic orbit for Jason-1 since May 7th 2012 142 SSALTODUACS Near-Real Time Input data overview 223 Corrections and models applied in SSALTODUACS NRT products produced from IGDRs 234 Corrections and models applied in SSALTODUACS NRT products produced from OG-
DRsFDGDRs 245 SSALTODUACS Delayed Time Input data overview 326 Corrections and models applied in SSALTODUACS DT products (gtv300) (12) 337 Corrections and models applied in SSALTODUACS DT products (gtv300) (22) 34
LIST OF FIGURES
1 DUACS and AVISO a user-driven altimetry service 112 SSH-MSS for Cryosat-2 with LRM mode only (left) or LRM+pseudo-LRM modes (right) 163 Coverage of the Europe product for Jason-1 Jason-2 and Envisat from August 18th to
September 9th 2011 184 Coverage of the Arctic region with Envisat from October 28th 2011 to January 3rd 2012 195 SSALTODUACS processing sequences 216 Overview of the near real time system data flow management 257 Merging pertinent information from IGDR and OGDR processing 268 Example with the key performance indicator on 20090627 31
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LIST OF ACRONYMS
ATP Along-Track ProductADT Absolute Dynamic TopographyAVISO Archiving Validation and Interpretation of Satellite Oceanographic dataBGLO Biais Grande Longueur drsquoOndeCalVal Calibration - ValidationCERSAT Centre ERS drsquoArchivage et de TraitementCMA Centre Multimission Altimetry centerCORSSH CORrected Sea Surface HeightC2 Cryosat-2DAC Dynamic Atmospheric CorrectionDT Delayed TimeDTU Mean Sea Surface computed by Technical University of DanemarkDUACS Data Unification and Altimeter Combination SystemE1 ERS-1E2 ERS-2EN EnvisatENN Envisat on its non repetitive orbit (since cycle 94)ECMWF European Centre for Medium-range Weather ForecastingENACT ENhanced ocean data Assimilation and Climate predictionG2 Geosat Follow OnGIM Global Ionospheric MapsGDR Geophysical Data Record(s)IERS International Earth Rotation ServiceIGDR Interim Geophysical Data Record(s)J1 Jason-1J1N Jason-1 on its new orbit (since cycle 262)J1G Jason-1 on its geodetic orbit (since May 2012)J2 Jason-2JPL Jet Propulsion LaboratoryLAS Live Access ServerLWE Long Wavelength ErrorsMADT Map of Absolute Dynamic TopgraphyMDT Mean Dynamic TopographyMOE Medium Orbit EphemerisMP Mean ProfileMSLA Map of Sea Level AnomalyMSS Mean Sea SurfaceNRT Near-Real TimeOE Orbit ErrorOER Orbit Error ReductionOpendap Open-source Project for a Network Data Access ProtocolPF Polynom FitPODAAC Physical Oceanography Distributed Active Archive CentrePOE Precise Orbit EphemerisRD Reference DocumentSAD Static Auxiliary Data
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SI Signed IntegerSLA Sea Level AnomalySL TAC Sea Level Thematic Assembly CentreSSALTO Ssalto multimission ground segmentSSH Sea Surface HeightTAC Thematic Assembly CentreTP TopexPoseidonTPN TopexPoseidon on its new orbit (since cycle 369)
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REFERENCES
[1] Andersen O B The DTU10 Gravity filed and Mean sea surface (2010) Second international sympo-sium of the gravity field of the Earth (IGFS2) Fairbanks Alaska
[2] Boy F et al (2011) Cryosat LRM TRK and SAR processing Presented at the 2011 Ocean Sur-face Topography Science Team meeting httpwwwavisooceanobscomfileadmindocumentsOSTST2011oral01_Wednesday
[3] Carrere L F Lyard 2003 Modeling the barotropic response of the global ocean to atmo-spheric wind and pressure forcing- comparisons with observations J Geophys Res 30(6) 1275doi1010292002GL016473
[4] Carrere L 2003 Etude et modeacutelisation de la reacuteponse HF de lrsquooceacutean global aux forccedilagesmeacuteteacuteorologiques PhD thesis Universiteacute Paul Sabatier (Toulouse III France) 318 pp
[5] Cartwright D E R J Tayler 1971 New computations of the tide-generating potential Geophys JR Astr Soc 23 45-74
[6] Cartwright D E A C Edden 1973 Corrected tables of tidal harmonics Geophys J R Astr Soc33 253-264
[7] Following the scientific recommendations from the OSTST meeting (San Diego October 2011) theESA Cryosat Project and the CNES SALP Project have been collaborating to generate these Cryosat-derived L3 and L4 products Level 1B and Level 2 products derived from CNES processors are notdistributed by AVISO as per the CNES ESA agreement
[8] Dibarboure G C Renaudie M-I Pujol S Labroue N Picot 2011 A demonstrationof the potential of Cryosat-2 to contribute to mesoscale observation J Adv Space Resdoi101016jasr201107002 httpdxdoiorg101016jasr201107002
[9] Dibarboure G P Schaeffer P Escudier M-IPujol JF Legeais Y Faugegravere R Morrow JK WillisJ Lambin JP Berthias N Picot 2010 Finding desirable orbit options for the Extension of Lifephase of Jason-1 Submitted to Marine Geodesy
[10] Dibarboure G M-IPujol FBriol PYLe Traon GLarnicol NPicot FMertz P Escudier MAblainCDufau 2010 Jason-2 in DUACS first tandem results and impact on processing and products Sub-mitted in Marine Geodesy
[11] Dibarboure G 2009 Using short scale content of OGDR data improve the Near Real Time productsof SsaltoDuacs oral presentation at Seattle OSTST meeting (pdf)
[12] Dorandeu J M Ablain Y Faugegravere F Mertz B Soussi and P Vincent 2004 Jason-1 global statisti-cal evaluation and performance assessment Calibration and cross-calibration results Marine Geodesy27(3-4) 345-372
[13] Dorandeu J M Ablain P-Y Le Traon 2003 Reducing Cross-Track Geoid Gradient Errors aroundTOPEXPoseidon and Jason-1 Nominal Tracks Application to Calculation of Sea Level AnomaliesJ of Atmosph and Ocean Techn20 1826-1838
[14] Dorandeu J and P-Y Le Traon 1999 Effects of global mean atmospheric pressure variations onmean sea level changes from TOPEXPoseidon J Atmos Oceanic Technol 16 1279-1283
[15] Ducet N P-Y Le Traon and G Reverdin 2000 Global high resolution mapping of ocean circulationfrom TOPEXPoseidon and ERS-1 and -2 J Geophys Res 105 19477-19498
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[16] Egbert Gary D Svetlana Y Erofeeva 2002 Efficient Inverse Modeling of Barotropic Ocean Tides JAtmos Oceanic Technol 19 183-204 doi 1011751520-0426(2002)019lt0183EIMOBOgt20CO2
[17] Gaspar P and F Ogor Estimation and analysis of the Sea State Bias of the ERS-1 altimeter Reportof task B1-B2 of IFREMER Contract n˚ 942426 016C 1994
[18] Gaspar P F Ogor and C Escoubes 1996 Nouvelles calibration et analyse du biais drsquoeacutetat de mer desaltimegravetres TOPEX et POSEIDON Technical note 96018 of CNES Contract 951523 1996
[19] Gaspar P and F Ogor Estimation and analysis of the Sea State Bias of the new ERS-1 and ERS-2altimetric data (OPR version 6) Report of task 2 of IFREMER Contract n˚ 962246 002C 1996
[20] Gaspar P S Labroue and F Ogor 2002 Improving nonparametric estimates of the sea state bias inradar altimeter measurements of seal level J Atmos Oceanic Technology 19 1690-1707
[21] Hernandez F P-Y Le Traon and R Morrow 1995 Mapping mesoscale variability of the AzoresCurrent using TOPEXPOSEIDON and ERS-1 altimetry together with hydrographic and Lagrangianmeasurements Journal of Geophysical Research 100 24995-25006
[22] Hernandez F and P Schaeffer 2000 Altimetric Mean Sea Surfaces and Gravity Anomaly maps inter-comparisons AVI-NT-011-5242-CLS 48 pp CLS Ramonville St Agne
[23] Hernandez F M-H Calvez J Dorandeu Y Faugegravere F Mertz and P Schaeffer 2000 Sur-face Moyenne Oceacuteanique Support scientifique agrave la mission altimeacutetrique Jason-1 et agrave une mis-sion micro-satellite altimeacutetrique Contrat SSALTO 2945 - Lot 2 - A1 Rapport drsquoavancementCLSDOSNT00313 40 pp CLS Ramonville St Agne
[24] Iijima BA IL Harris CM Ho UJ Lindqwiste AJ Mannucci X Pi MJ Reyes LC SparksBD Wilson 1999 Automated daily process for global ionospheric total electron content maps andsatellite ocean altimeter ionospheric calibration based on Global Positioning System data J AtmosSolar-Terrestrial Physics 61 16 1205-1218
[25] Labroue S F Boy N Picot M Urvoy M Ablain First quality assessment of the Cryosat-2 altimetricsystem over ocean J Adv Space Res 2011 doi101016jasr201111018 httpdxdoiorg101016jasr201111018
[26] Labroue S 2007 RA2 ocean and MWR measurement long term monitoring 2007 report for WP3Task 2 - SSB estimation for RA2 altimeter Contract 1729303I-OL CLS-DOS-NT-07-198 53ppCLS Ramonville St Agne
[27] Labroue S P Gaspar J Dorandeu OZ Zanifeacute F Mertz P Vincent and D Choquet 2004 Nonparametric estimates of the sea state bias for Jason-1 radar altimeter Marine Geodesy 27 453-481
[28] Lagerloef GSE GMitchum RLukas and PNiiler 1999 Tropical Pacific near-surface currentsestimated from altimeter wind and drifter data J Geophys Res 104 23313-23326
[29] Le Traon P-Y and F Hernandez 1992 Mapping the oceanic mesoscale circulation validation ofsatellite altimetry using surface drifters J Atmos Oceanic Technol 9 687-698
[30] Le Traon P-Y P Gaspar F Bouyssel and H Makhmara 1995 Using TopexPoseidon data to en-hance ERS-1 data J Atmos Oceanic Technol 12 161-170
[31] Le Traon P-Y F Nadal and N Ducet 1998 An improved mapping method of multisatellite altimeterdata J Atmos Oceanic Technol 15 522-534
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[32] Le Traon P-Y and F Ogor 1998 ERS-12 orbit improvement using TOPEXPOSEIDON the 2 cmchallenge J Geophys Res 103 8045-8057
[33] Le Traon P-Y and G Dibarboure 1999 Mesoscale mapping capabilities of multi-satellite altimetermissions J Atmos Oceanic Technol 16 1208-1223
[34] Le Traon P-Y G Dibarboure and N Ducet 2001 Use of a High-Resolution Model to Analyze theMapping Capabilities of Multiple-Altimeter Missions J Atmos Oceanic Technol 18 1277-1288
[35] Le Traon PY and G Dibarboure 2002 Velocity mapping capabilities of present and future altimetermissions the role of high frequency signals J Atmos Oceanic Technol 19 2077-2088
[36] Le Traon PY Faugegravere Y Hernandez F Dorandeu J Mertz F and M Ablain 2002 Can we mergeGEOSAT Follow-On with TOPEXPOSEIDON and ERS-2 for an improved description of the oceancirculation J Atmos Oceanic Technol 20 889-895
[37] Le Traon PY and G Dibarboure 2004 An Illustration of the Contribution of the TOPEXPoseidon-Jason-1 Tandem Mission to Mesoscale Variability Studies Marine Geodesy 27 (1-2)
[38] Mertz F F Mercier S Labroue N Tran J Dorandeu 2005 ERS-2 OPR data quality assessment Long-term monitoring - particular investigation CLSDOSNT-06001 (pdf)
[39] MSS_CNES_CLS11 was produced by CLS Space Oceanography Division and distributed by Avisowith support from Cnes (urlhttpwwwavisooceanobscom)
[40] Pascual A Y Faugegravere G Larnicol P-Y Le Traon 2006 Improved description of the oceanmesoscale variability by combining four satellite altimeters Geophys Res Lett 33
[41] Pascual A C Boone G Larnicol and P-Y Le Traon 2009 On the quality of Real-Time altimetergridded fields comparison with in-situ data Journ of Atm and Ocean Techn Vol 26(3) pp 556-569DOI 1011752008JTECHO5561
[42] Prandi P M Ablain A Cazenave N Picot 2011 A new estimation of mean sea level in the ArcticOcean from satellite altimetry Submitted to Marine Geodesy
[43] Pujol M-I et al 2009 Three-satellite quality level restored in NRT poster at OSTST meeting (pdf)
[44] Ray R 1999 A Global Ocean Tide model from TOPEXPoseidon Altimetry GOT992 NASA TechMemo NASATM-1999-209478 58 pp Goddard Space Flight Center NASA Greenbelt MD USA
[45] Rio M-H and F Hernandez 2003 A Mean Dynamic Topography computed over the worldocean from altimetry in-situ measurements and a geoid model J Geophys Res 109 C12032doi1010292003JC002226
[46] Rio M-H and F Hernandez 2003 High frequency response of wind-driven currents measured bydrifting buoys and altimetry over the world ocean J Geophys Res 108 39-1
[47] Rio M-H 2003 Combinaison de donneacutees in situ altimeacutetriques et gravimeacutetriques pour lrsquoestimationdrsquoune topographie dynamique moyenne globale Ed CLS PhD Thesis University Paul Sabatier(Toulouse III France) 260pp
[48] Scharroo R and P Visser 1998 Precise orbit determination and gravity field improvement for theERS satellites J Geophys Res 103 8113-8127
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[49] Scharroo R J Lillibridge and WHF Smith 2004 Cross-calibration and long-term monitoring ofthe Microwave Radiometers of ERS Topex GFO Jason-1 and Envisat Marine Geodesy 97
[50] Tran N and E Obligis December 2003 Validation of the use of ENVISAT neural algorithms onERS-2 CLSDOSNT03901
[51] Tran N S Labroue S Philipps E Bronner and N Picot 2010 Overview and Update of the SeaState Bias Corrections for the Jason-2 Jason-1 and TOPEX Missions Marine Geodesy accepted
[52] Vincent P Desai SDDorandeu J Ablain M Soussi B Callahan PS and BJ Haines 2003 Jason-1 Geophysical Performance Evaluation Marine Geodesy 26 167-186
[53] Wahr J W 1985 Deformation of the Earth induced by polar motionJ of Geophys Res (Solid Earth)90 9363-9368
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I INTRODUCTION
MyOcean is a European Network project aiming at monitoring analyzing and forecasting the Ocean Ituses satellite and in-situ data to describe the ocean in 3 dimensions and real time More information can befound on httpwwwmyoceaneuorgThe aim of this document is to describe the products delivered by the Sea Level TAC (Thematic AssemblyCentre) which is one of the five TAC of the MyOcean projectThe data produced in the frame of this TAC are generated by the processing system named DUACS (DataUnification and Altimeter Combination System)DUACS is part of the CNES multi-mission ground segment (SSALTO) It processes data from all altimetermissions Cryosat-2 OSTMJason-2 Jason-1 TopexPoseidon Envisat GFO ERS-1amp2 and even GeosatAt this time (May 25th 2012) DUACS is using three different altimeters in near real time Developed and operated by CLS it started as an European Commission Project (Developing Use Of Altime-try for Climate Studies) funded under the European Commission and the Midi-Pyreacuteneacutees regional councilIt has been integrated to the CNES multi-mission ground segment SSALTO in 2001 and it is maintainedupgraded and operated with funding from CNES with shared costs from EU projectsAt the beginning of 2004 DUACS was redefined as the Data Unification Altimeter Combination System
Figure 1 DUACS and AVISO a user-driven altimetry service
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The products lines described in this user manual are the followingSEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005
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The data provided to users have a global coverage (PL SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001)and regional products are also computed over specific areasMediterranean Sea (PL SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002)and Black Sea (PL SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003)Thanks to updates in 2011 and 2012 (see section II) new regional products are now availableEurope (PL SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004)and Arctic (PL SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005)
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II UPDATES IN 2011 AND 2012
This section describes the updates of the SSALTODUACS Near Real Time system that occurred during2011 and 2012 allowing to add new products (Europe and Arctic) the integration of the Cryosat-2 data inthe system the stopping delivery of Envisat data the addition of Jason-1 data on geodetic orbit (j1g)To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtml
II1 Version D of input IGDROGDR Jason-2 data for NRT processing(July 30 2012)
On July 30 2012 the version of Jason-2 IGDROGDR has changed and is now the D version Somecorrections have thus been updated as detailed in tables 3 and 4
II2 Integration of Jason-1 on its geodetic orbit (May 2012)
An anomaly occured on March 3rd 2012 on the Jason-2 mission (see httpwwwavisooceanobscomfractualitesactualitesindexhtmltx_ttnews[tt_news]=1162amptx_ttnews[backPid]=1399ampcHash=d5baeb645e) On April 23rd CNES began to command the satellite into a nadir ori-entation and after some propulsion anomalies CNES and NASA management through the Joint SteeringGroup have directed the Jason-1 Project to then begin a series of maneuvers to place Jason-1 into a neworbit as defined in table 1 After checking the current orbit carefully the operational team determined thata geodetic mission was still possible It was also decided to preserve all remaining fuel for future stationkeeping maneuvers which is mandatory in a geodetic orbit Core payloads were switched ON on May 4thand after some POSEIDON2 radar (PRF) adjustments the mission was resumed on May 7th at 151248UTCBelow are the characteristics of the new orbit which will be maintained as before within +- 1km controlbox at the Equator
Semi major axis 7702437 kmEccentricity 13 to 28 10-4Altitude equator 13240 kmOrbital period 6730s (1h52rsquo10rdquo)Inclination 66042˚Cycle 406 daysSub cycles 39 - 109 - 475 - 1795
days
Table 1 Characteristics of the geodetic orbit for Jason-1 since May 7th 2012
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For this new phase of the Jason-1 mission (called j1g) the cycle numbering will restart at 500 Off-lineproducts will be produced once a day for the IGDR and every 11 days for the GDRrsquos The integration ofJason-1 data in the DUACS system is available since May 25th 2012
II3 Envisat has stopped sending data (April 2012)
Since April 8th 2012 Envisat has stopped sending data to Earth Esarsquos mission control has worked tore-establish contact with the satellite but there has been no reaction from the satellite Thus Esa has de-clared officially the end of mission for Envisat (see httpwwwesaintesaCPSEM1SXSWT1H_index_0html) Therefore no SL TAC NRT data from Envisat can be released since this date
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II4 Integration of the Cryosat2 Mission (February 2012)
Since February 6th 2012 Cryosat-2 mission has been integrated in the DUACS sytem This mission isdedicated to the observation of the floating sea-ice as well as the continental ice sheets but all data acquiredover ocean are valuable for the observation of oceanic circulation and mesoscale variations This majorchange is the result of the long-standing and fruitful partnership between ESA and CNES and a responseto the request from scientific and operational oceanography users [7] The integration of Cryosat-2 impactsthe delivering of Near real time Sea Level Anomalies (SLA)
II41 Generalities about the mission
A Cryosat-2 Processing Prototype (C2P) (described in Boy et al 2011 [2]) has been developed on CNESside to lay the ground for various SAR processing studies The processing chains ingest Level-0 telemetryfiles distributed by ESA and perform the following steps to generate Sea Level Anomalies (SLA) values foreach altimeter measurements
bull Level-1 Decommutation time-tagging and localization of measurements
bull Level-1b Calculation of instrumental corrections and geophysicalmeteorological corrections
bull Level-2 MLE4 waveforms Retracking and calculation of SLA
The prototype processes data almost continuously over ocean either in Low Resolution Mode (LRM) or inthe DopplerSAR mode processed as pseudo-LRM mode allowing to increase the coverage (figure 2)
Figure 2 SSH-MSS for Cryosat-2 with LRM mode only (left) or LRM+pseudo-LRM modes (right)
Although Cryosat-2 raw SSH can be only corrected with GPS-derived ionospheric correction and ECMWFwet troposphere correction validation activities showed (Labroue et al 2011 [25]) that C2P outputs have anaccuracy roughly equivalent to Envisatrsquos Level 2 products if the latter are processed with the same standards
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II42 Integration in DUACS
The Cryosat-2 data are included in the Near Real time process The chain delivers now (for global coverageMediterranean and Black Seas) along track data from Cryosat-2 (SLAs) Note that the products distributedare of Level-3 and donrsquot replace Level-2 products distributed by agenciesThe details of the processing are given in Dibarboure et al 2011 [8]Here we just give an overview the data are computed with the corrections given in section III21 Thefiltering and sub-sampling of SLAs (section III263) are detailed in [8]
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II5 Addition of Europe and Arctic products (January 2012)
Since the MyOcean V2 two new along-track products are computed in Near Real Time intended foraddressing the needs of data assmilation and validation in regional models
bull Following the TAPAS (Tailored Altimeter Product for Assimilation Systems) initiative launched bySL TAC with all the Modeling and Forecasting Centers (MFCs) the Europe regional products (PLSEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004) have been proposed (figure 3) They areavailable in Near Real Time onlyThey are studied to partly fulfil the needs of the Centers with adapted filtering and resolution Thoseparameters have been tuned in order to provide boundary conditions for the Atlantic assimilationmodels They are different from the ones used for Mediterranean and Black Seas products If you needto study the Mediterranean Sea or the Black Sea yoursquod better use the dedicated products describedabove since the processing parameters have been fitted to be adapted to the dynamics of the ocean inthose regions
Figure 3 Coverage of the Europe product for Jason-1 Jason-2 and Envisat from August 18th to September9th 2011
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bull The Arctic along-track products (PL SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005) coverlatitudes between 45 and 82 degrees (figure 4) They are available in Near Real Time only
Figure 4 Coverage of the Arctic region with Envisat from October 28th 2011 to January 3rd 2012
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III SSALTODUACS SYSTEM
III1 Introduction
This chapter presents the input data used by SSALTODUACS system and an overview of the different pro-cessing steps necessary to produce the output dataSSALTODUACS system is made of two components a Near Real Time one (NRT) and a Delayed Time(DT) oneIn NRT the systemrsquos primary objective is to provide operational applications with directly usable high qual-ity altimeter data from all missions availableIn DT it is to maintain a consistent and user-friendly altimeter database using the state-of-the-art recom-mendations from the altimetry communityFollowing figure gives an overview of DUACS system where processing sequences can be divided into 7main steps
bull acquisition
bull homogenization
bull input data quality control
bull multi-mission cross-calibration
bull product generation
bull merging
bull final quality control
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Figure 5 SSALTODUACS processing sequences
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III2 Near Real Time processing steps
III21 Input data models and corrections applied
To produce SLA in near-real time the DUACS system uses two flows based on the same instrumental mea-surements but with a different quality
bull The IGDR that are the latest high-quality altimeter data produced in near-real-time
bull The OGDR that includes real time data (OSTMJason-2 and Jason-1 OSDR) to complete IGDR Thesefast delivery products do not always benefit from precise orbit determination nor from some exter-nal model-based corrections (Dynamic Atmospheric Correction (DAC) Global Ionospheric Maps(GIM))
Integration of OGDR data and the introduction of Jason-2Jason-1 tandem increased the resilience and pre-cision of the system A better restitution of ocean variability is observed especially in high energetic areas
Altimetric product Source Availability Type of orbit
Jason-2 IGDR CNES ~24h CNES MOE GDR-Cuntil 20120730
CNES MOE GDR-Dsince 20120731
OGDR NOAAEUMETSAT ~3 to 5 h
Jason-1 IGDR CNESNASA ~48 h CNES MOE GDR-Dsince 20120507
OGDR CNESNASA ~3 to 12 h
Envisat IGDR ESACNES not deliveredsince 20120408
CNES MOE GDR-Dsince 20120121
FDGDR ESA not deliveredsince 20120408
Cryosat-2 IGDR-like ESACNES ~48 h CNES MOE GDR-D
not delivered
Table 2 SSALTODUACS Near-Real Time Input data overview
See Figure 6 Overview of the near real time system data flow management
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DUACS 2011 NRT product from IGDR1
j2 j1nj1g enn c2Productstandard ref
version C until20120730 and D after
version C version 21 CPP [2]
Orbit CNES MOE GDR-Cuntil 20120730
GDR-D after
CNES MOE GDR-C forj1n and CNES MOE
GDR-D for j1g
CNES MOE GDR-Dfrom 20120121 to
20120408
CNES MOE GDR-D
Ionopheric bi-frequency altimeter range measurements GIM model for cgt64 (Iijima et al1998[24])Dry tropo Model computed from ECMWF Gaussian grids (new S1 and S2 atm tides applied)Wet tropo-sphere
AMR radiometer(enhancement in coastal
regions since20120730)
JMR radiometer MWR radiometer andcorrected from side
lobes
Model computed fromECMWF Gaussian
grids
DAC MOG2D High Resolution forced with ECMWF pressure and wind fields (S1 and S2 wereexcluded) (Carrere and Lyard 2003[3])+ inverse barometer Filtering temporal window is
un-centered (no data in the future)Ocean tide GOT4v8 (S1 and S2 are included) and TPX 072 [16] for Arctic productsPole tide [Wahr 1985 [53]]Solid earthtide
Elastic response to tidal potential [Cartwright and Tayler 1971[5]] [Cartwright andEdden 1973[6]]
Loading tide GOT4v8 (S1 and S2 are included)Sea statebias
Non parametric SSB[Labroue 2004[27]](with cycles J1 1 to 11
using GDR-B standardsuntil 20120730 andderived from Jason-2
after)
Non parametric SSB[Labroue 2004[27]](with cycles 1 to 21
using GDR-Bstandards)
Non parametric SSB[Labroue 2004[27]](with cycles 41 to 60
using GDR-Bstandards)
Same as Jason-2 SSB
Orbit error Global multi-mission crossover minimization (Le Traon and Ogor1998[32])
Long wave-lengh errors
Optimal Interpolation [Le Traon et al 1998[31]]
Intercalibration Reference from cycle20
Mean pro-file (seeIII261)
Computed with cycles11-353 TP data andwith cycles 11-250J1 data referenced[19931999]
TPNJ1N computedwith cycles 369-479TPN data refer-enced [19931999]J1G No MP can beused instead theMSS_CNES_CLS11[39] is used
No Mean Profilecan be used forEnvisat on its neworbit Instead theMSS_CNES_CLS11[39] is used
No Mean Profilecan be used forCryosat-2 Instead theMSS_CNES_CLS11[39] is used
(1) A flag included in the along-track files indicates the source of the production (OGDRFDGDR orIGDR) If flag=0 the processed data comes from OGDRsFDGDRs if flag=1 the processed data comesfrom IGDRs
Table 3 Corrections and models applied in SSALTODUACS NRT products produced from IGDRs
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
DUACS 2011 NRT product from OGDR or FDGDR2
j2 j1nj1g ennProduct stan-dard ref
version C until 20120730and D after
version C version 21
Orbit Navigator Extrapolated CNES MOEGDR-D since 20120121
Ionopheric From-dual frequency altimeter range measurements From GIM model fromcycle 65 (Iijima et al1998 [24])
Dry troposphere Model computed from ECMWF Gaussian grids (new S1 and S2 atmospherictides are applied)
Wet tropo-sphere
AMR radiometer(enhancement in coastal
regions since 20120730)
JMR radiometer MWR radiometer andcorrected from side lobes
DAC Inverse Barometer forecastedOcean tide GOT4v8 (S1 and S2 are included) and TPX 072 [16] for Arctic productsPole tide [Wahr 1985 [53]]Solid earth tide Elastic response to tidal potential [Cartwright and Tayler 1971[5]]
[Cartwright and Edden 1973[6]]Loading tide GOT4v8 (S1 and S2 are included)Sea state bias Non parametric SSB
[Labroue 2004[27]] (withcycles J1 1 to 11 usingGDR-B standards until20120730 and derivedfrom Jason-2 after)
Non parametric SSB[Labroue 2004[27]](with cycles 1 to 21 usingGDR-B standards)
Non parametric SSB[Labroue 2004[27]](with cycles 41 to 60using GDR-B standards)
Orbit error Specific filtering of long-wavelength signal3
Long wave-lengh errors
Optimal Interpolation [Le Traon et al 1998[31]]
Intercalibration Reference from cycle 20Mean profile(see III261)
Computed with cycles 11-353 TP data and with cy-cles 11-250 J1 data refer-enced [19931999]
TPNJ1N computedwith cycles 369-479TPN data referenced[19931999] J1G NoMP can be used insteadthe MSS_CNES_CLS11[39] is used
No Mean Profile can beused for Envisat on itsnew orbit Instead theMSS_CNES_CLS11 [39]is used
(2) A flag included in the along-track files indicates the source of the production (OGDRFDGDR orIGDR) If flag=0 the processed data comes from OGDRsFDGDRs if flag=1 the processed data comesfrom IGDRs(3) Specific data processing was applied on long wave-length signal (sectIII23 of the user manual)
Table 4 Corrections and models applied in SSALTODUACS NRT products produced from OG-DRsFDGDRs
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III22 Acquisition
The acquisition process is twofold
bull straightforward retrieval and reformatting of altimeter data and dynamic auxiliary data (pressure andwet troposphere correction grids from ECMWF are provided by Meteo France TEC grids from JPLNRT MOG2D corrections) from external repositories
bull synchronisation process
To be homogenized properly altimeter data sets require various auxiliary data The acquisition softwaredetects downloads and processes incoming data as soon as they are available on remote sites (externaldatabase FTP site) Data are split into passes if necessary If data flows are missing or late the synchroni-sation engine put unusable data in waiting queues and automatically unfreezes them upon reception of themissing auxiliary data This processing step delivers raw data that is to say data that have been dividedinto cycles and passes and ordered chronologicallyFrom SSALTODUACS V80 the acquisition step uses two different data flows in near-real time the OGDRflow (within a few hours) and the IGDR flow (within a few days)For each OGDR input the system checks that no equivalent IGDR entry is available in the data base beforeacquisition for each IGDR input the system checks and delete the equivalent OGDR entry in the data baseThese operations aim to avoid duplicates in SSALTODUACS system
Figure 6 Overview of the near real time system data flow management
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III23 Homogenization
The Homogenization process consists in applying the most recent corrections models and references rec-ommended for altimeter products Each mission is processed separately as its needs depend on the baseinput data The list of corrections and models currently applied is provided in tables 3 and 4 for NRT dataThe system includes SLA filtering to process OGDR data DUACS extract from these data sets the shortscales (space and time) which are useful to better describe the ocean variability in real time and merge thisinformation with a fair description of large scale signals provided by the multi-satellite observation in nearreal time (read IGDR-based DUACS data) Finally an hybrid SLA is computed
Figure 7 Merging pertinent information from IGDR and OGDR processing
III24 Input data quality control
The Input Data Quality Control is a critical process applied to guarantee that DUACS uses only the mostaccurate altimeter data Thanks to the high quality of current missions this process rejects a small percent-age of altimeter measurements but these erroneous data could be the cause of a significant quality lossThe quality control relies on standard raw data editing with quality flags or parameter thresholds but alsoon complex data editing algorithms based on the detection of erroneous artefacts mono and multi-missioncrossover validation and macroscopic statistics to edit out large data flows that do not meet the systemrsquosrequirements
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III25 Multi-mission cross-calibration
The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistentand accurate information It removes any residual orbit error (OE Le Traon and Ogor 1998[32]) or longwavelength error (LWE Le Traon et al 1998[31]) as well as large scale biases and discrepancies betweenvarious data flows
This process is based on two very different algorithms a global multi-mission crossover minimization fororbit error reduction (OER) and Optimal Interpolation (OI) for LWE
Multi-satellite crossover determination is performed on a daily basis All altimeter fields (measurementcorrections and other fields such as bathymetry MSS) are interpolated at crossover locations and datesCrossovers are then appended to the existing crossover database as more altimeter data become availableThis crossover data set is the input of the Orbit Error Reduction (OER) method Using the precision of thereference mission orbit a very accurate orbit error can be estimated This processing step does not concernOGDR dataLWE is mostly due to residual tidal or inverse barometer errors and high frequency ocean signals The OIused for LWE reduction uses precise parameters derived from
bull accurate statistical description of sea level variability
bull localized correlation scales
bull mission-specific noise and precise assumptions on the long wavelength errors to be removed (from arecent analysis of one year of data from each mission)
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III26 Product generation
The product generation process is composed of four steps computation of raw SLA cross-validationfilteringampsub-sampling and generation of by-products
III261 Computation of raw SLA
Since the geoid is not well known yet the SSH cannot be used directly the SSH anomalies are used insteadThey are computed from the difference of the instantaneous SSH - a temporal reference This temporalreference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeattrack analysis cannot be used The errors affecting the SLAs MPs and MSS have different magnitudes andwavelengths The computation of the SLAs and their errors associated are detailed in Dibarboure et al 2010[9]
Use of a Mean ProfileIn the repeat track analysis (when the satellites flies over a repetitive orbit) measurements are re-sampledalong a theoretical ground track (or mean track) associated to each mission Then a Mean Profile (MP) issubtracted from the re-sampled data to obtain SLA The MP is a time average of similarly re-sampled dataover a long period
bull The Mean Profile used for Jason-2 is computed with 10 years of TP (cycles 11 to 353) and 6 years ofJason-1 (cycles 11 to 250)
bull The Mean Profile used from Jason-1 cycle 262 to 374 (where satellites are on interleaved ground-tracks) is computed with 3 years of TP (cycles 369 to 479)
bull No Mean Profile can be used for Envisat on its new orbit (enn) Jason-1 on its geodetic orbit (j1g) norfor Cryosat-2 mission (c2) because there is no repetitive track The MSS must be used instead (seebelow)
Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible
bull Indeed as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide precise cross-track projection andor interpolation schemes are required to avoid errors
bull The mesoscale variability error (which is lt35 cm for MP between 3 to 5 years and lt1cm for WLof 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a prioriknowledge from Sea Level maps derived from previous iterations or from other missions
bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for Envisat since november 2010 and for Cryosat-2 mission (c2)because the satellite is not in a repetitive orbit phase The alternative is to use the MSS instead The griddedMSS is derived from along track MPs and data from geodetic phases Thus any error on the MP is alsocontained in the MSS There are essentially 4 types of additional errors on gridded MSS which are hard toquantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
Note that for the Arctic regional products the DTU10 MSS [1] is taken into account instead of the CLS01MSS Indeed the accuracy of DTU10 compared to CLS01 is further demonstrated by the significant sealevel anomaly variance reduction found over the whole Arctic Ocean as shown in Prandi et al [42]
III262 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III263 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
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III27 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III271 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
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III272 Performance indicators
To appreciate the quality situation of the DUACS system new performance indicators are computed dailyThey aim at evaluate the status of the main processing steps of the system the input data availability theinput data coverage the input data quality and the output product quality These indicators are computed foreach and every currently working satellite and combined to obtain the overall status
Figure 8 Example with the key performance indicator on 20090627
See the description the latest and previous indicators on Aviso websitehttpwwwavisooceanobscomindexphpid=1516
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III3 Delayed Time processing steps
III31 Input data models and corrections applied
Delayed Time MyOcean products are generated
bull from Aviso GDR products for TP Jason-1 Jason-2 and Envisat (GDR-A cycles 1 to 22 GDR-Bcycles 23 to 85 GDR-C from cycle 86)
bull from NOAA GDR for GFO and from CERSAT (IFREMER) OPR for ERS-1 and ERS-2 (phases C(1st 35-day repeat orbit period) phase E and F (geodetic phases) phase G for ERS-1 (last 35-dayrepeat orbit period tandem phase with ERS-2 phase A for ERS-2 (1st 35-day repeat orbit periodtandem phase with ERS-1))
All GDR products are computed with a Precise Orbit Ephemeris (POE) and are delivered within 2 to 3months depending on the mission For several missions an updated orbit is used
bull For ERS-1amp-2 the orbit used is DGME-04 provided by Delft Institute (httpwwwdeostudelftnl)until June 2003
bull For TopexPoseidon the orbit used is GSFC (std0809) for the whole mission
bull For Envisat CNES POE of GDR-C standard is used for the whole mission
bull For the whole GFO mission the orbit used is GSFC (std0809) and when not available NASA POE isused
Altimetric product Source Availability Type of orbit
TopexPoseidon GDR NASACNES - GSFC POE
Jason-1 GDR (GDR-C) CNESNASA ~40 days CNES POE
Jason-2 GDR (GDR-C) CNESNASA ~60 days CNES POE
GFO GDR NOAA - GSFCNASA POE
ERS-1amp2 IFREMERESA - DGME-04
Envisat (GDR-A GDR-B andGDR-C from cycle 86)
ESA ~2 months CNES POE
Table 5 SSALTODUACS Delayed Time Input data overview
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
DU
AC
S20
11D
Tpr
oduc
t(gtV
30
0)j2
j1j1
ntp
tpn
e1e2
ene
nng2
Prod
uct
stan
dard
ref
GD
R-C
OPR
GD
R-A
(Cyc
les
1to
22)
GD
R-B
(cyc
les
23-8
5)
GD
R(N
OA
A)
Orb
itC
nes
POE
GSF
C(I
TR
F20
05G
RA
CE
last
stan
dard
s)
DG
ME
-04
(Sch
arro
oan
dV
isse
r19
98[4
8]C
NE
SPO
E(G
DR
-1st
anda
rds
forc
ycle
s9
to22
GD
R-C
stan
dard
sfr
omcy
cle
23)
GSF
C(I
TR
F20
05
GR
AC
Ela
stst
anda
rds
Iono
pher
icD
ual f
requ
ency
altim
eter
rang
em
easu
rem
ents
Dua
l fre
quen
cyal
timet
erra
nge
mea
sure
men
ts(T
opex
)D
OR
IS(P
OSE
IDO
N)
Ben
t mod
elB
ent m
odel
(cyc
les
1-36
)G
IMm
odem
from
cycl
e37
((Ii
jima
etal
19
98[2
4])
Dua
l-fr
eque
ncy
altim
eter
rang
em
easu
rem
ent(
cycl
e9-
64)a
ndG
IMm
odel
gtcyc
le65
(Iiji
ma
etal
19
99[2
4])c
orre
cted
from
8m
mbi
as
From
GIM
mod
el(I
ijim
aet
al1
998
[24]
)
Dry
trop
o-sp
here
Mod
elco
mpu
ted
from
EC
MW
FG
auss
ian
grid
s(n
ewS1
and
S2at
mos
pher
ictid
esar
eap
plie
d)
Mod
elco
mpu
ted
from
EC
MW
Fre
ctan
gula
rgri
ds(n
ewS1
and
S2at
mos
pher
ictid
esar
ein
clud
ed)
Wet
trop
o-sp
here
JMR
AM
Rra
diom
eter
furt
hert
han
50km
from
the
coas
tsF
rom
EC
MW
Fm
odel
ford
ista
nces
betw
een
10an
d50
km
TM
Rra
diom
eter
(Sch
aroo
etal
20
04[4
9])
MW
RC
orre
ctio
nof
the
drif
ton
the
236
GH
zbr
ight
ness
tem
pera
ture
(Sch
arro
oet
al
2004
[49]
)Neu
ral
Net
wor
kal
gori
thm
(Tra
nan
dO
blig
is
2003
[50]
MW
Rra
diom
eter
furt
hert
han
50km
from
the
coas
tsan
dco
rrec
ted
from
side
lobe
s(f
rom
cycl
e41
)E
CM
WF
mod
elfo
rdis
tanc
esbe
twee
n10
and
50km
GFO
radi
omet
er
DA
CM
OG
2DH
igh
Res
olut
ion
forc
edw
ithE
CM
WF
pres
sure
and
win
gfie
lds
(S1
and
S2w
ere
excl
uded
)+in
vers
eba
rom
eter
com
pute
dfr
omre
ctan
gula
rgri
ds
Tabl
e6
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(1
2)
Page 33
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
j2j1
j1n
tptp
ne1
e2en
enn
g2O
cean
tide
GO
T4v
7(S
1an
dS2
are
incl
uded
)Po
letid
e[W
ahr
1985
[53]
]So
lidea
rth
tide
Ela
stic
resp
onse
totid
alpo
tent
ial[
Car
twri
ghta
ndTa
yler
197
1[5]
][C
artw
righ
tand
Edd
en1
973[
6]]
Loa
ding
tide
GO
T4v
7(S
1pa
ram
eter
isin
clud
ed)
Sea
stat
ebi
asN
onpa
ram
etri
cSS
B[G
aspa
reta
l20
02[2
0]]
Non
para
met
ric
SSB
[NT
ran
and
al2
010[
51]]
BM
3[G
aspa
ran
dO
gor
1994
[17]
]
Non
para
met
ric
SSB
[Mer
tzet
al
2005
[38]
]
Non
para
met
ric
SSB
[Gas
pare
tal
2002
]w
ithG
DR
-Bst
anda
rds
forc
ycle
s9
to85
and
with
GD
R-C
stan
dard
sfr
omcy
cle
86
Non
para
met
ric
SSB
[NT
ran
etal
20
10[5
1]]
Orb
iter
ror
Glo
bal m
ulti-
mis
sion
cros
sove
rmin
imiz
atio
n(L
eTr
aon
and
Ogo
r19
98[3
2])
Lon
gw
ave-
leng
her
rors
Opt
imal
Inte
rpol
atio
n(L
eTr
aon
etal
19
98[3
1])
Inte
rcal
ibra
tion
Ref
eren
cefr
omcy
cle
11R
efer
ence
from
cycl
e1
to35
4C
orre
ctio
nof
regi
onal
bias
J2J
1de
duce
dfr
omin
terc
alib
ratio
nph
ase
(cyc
le11
J2)
Cor
rect
ion
ofgl
obal
biai
sJ1
TP
deacutedu
ced
from
inte
rcal
ibra
tion
phas
e(c
ycle
s11
J1)
Mea
npr
o-fil
e(s
eeII
I36
1)
Com
pute
dw
ithcy
cles
11-3
53T
Pda
taan
dw
ithcy
cles
11-2
50J1
data
ref
eren
ced
[199
319
99]
TP
J1 c
ompu
ted
with
cycl
es11
-353
TP
data
and
with
cycl
es11
-250
J1da
tar
efer
ence
d[1
993
1999
]T
PNJ
1Nc
ompu
ted
with
cycl
es36
9-47
9T
PNda
tar
efer
ence
d[1
993
1999
]
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
ref
eren
ced
[199
319
99]
EN
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
re
fere
nced
[199
319
99]
EN
Nu
seof
MSS
_CN
ES_
CL
S11
[39]
Com
pute
dw
ithcy
cles
37-1
87G
2da
ta
refe
renc
ed[1
993
1999
]
Peri
odof
use
from
cycl
e9
from
cycl
e9
cycl
es1
to48
1cy
cles
15to
43In
clud
ing
E-F
geod
etic
phas
es
cycl
es1
to83
from
cycl
e9
cycl
es37
to22
2
Tabl
e7
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(2
2)
Page 34
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III32 Acquisition
The acqusition process in Delayed time is much simpler than in Near Real time it consists in a synchronisa-tion process of all the auxiliary data required to homogenize propely the altimeter data sets The acquisitionstep uses the GDRs or the OPRs provided by the agencies
III33 Homogenization
The Homogenization process consists in applying the most recent corrections models and references rec-ommended for altimeter products Each mission is processed separately as its needs depend on the baseinput data The list of corrections and models currently applied is provided in tables 6 and 7 for DT data
III34 Input data quality control
The Input Data Quality Control is a critical process applied to guarantee that DUACS uses only the mostaccurate altimeter data Thanks to the high quality of current missions this process rejects a small percent-age of altimeter measurements but these erroneous data could be the cause of a significant quality lossThe quality control relies on standard raw data editing with quality flags or parameter thresholds but alsoon complex data editing algorithms based on the detection of erroneous artefacts mono and multi-missioncrossover validation and macroscopic statistics to edit out large data flows that do not meet the systemrsquosrequirements
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PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III35 Multi-mission cross-calibration
The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistentand accurate information It removes any residual orbit error (OE Le Traon and Ogor 1998[32]) or longwavelength error (LWE Le Traon et al 1998[31]) as well as large scale biases and discrepancies betweenvarious data flows
This process is based on two very different algorithms a global multi-mission crossover minimization fororbit error reduction (OER) and Optimal Interpolation (OI) for LWE
Multi-satellite crossover determination is performed on a daily basis All altimeter fields (measurementcorrections and other fields such as bathymetry MSS) are interpolated at crossover locations and datesCrossovers are then appended to the existing crossover database as more altimeter data become availableThis crossover data set is the input of the Orbit Error Reduction (OER) method Using the precision of thereference mission orbit a very accurate orbit error can be estimated LWE is mostly due to residual tidalor inverse barometer errors and high frequency ocean signals The OI used for LWE reduction uses preciseparameters derived from
bull accurate statistical description of sea level variability
bull localized correlation scales
bull mission-specific noise and precise assumptions on the long wavelength errors to be removed (from arecent analysis of one year of data from each mission)
Page 36
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III36 Product generation
The product generation process is composed of four steps computation of raw SLA cross-validationfilteringampsub-sampling and generation of by-products
III361 Computation of raw SLA
Since the geoid is not well known yet the SSH cannot be used directly the SSH anomalies are used insteadThey are computed from the difference of the instantaneous SSH - a temporal reference This temporalreference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeattrack analysis cannot be used The errors affecting the SLAs MPs and MSS have different magnitudes andwavelengths The computation of the SLAs and their errors associated are detailed in Dibarboure et al 2010[9]
Use of a Mean ProfileIn the repeat track analysis (when the satellites flies over a repetitive orbit) measurements are re-sampledalong a theoretical ground track (or mean track) associated to each mission Then a Mean Profile (MP) issubtracted from the re-sampled data to obtain SLA The MP is a time average of similarly re-sampled dataover a long period
bull The Mean Profile used for TP (cycles 1 to 364) Jason-1 (cycles 1 to 259) and Jason-2 is computedwith 10 years of TP (cycles 11 to 353) and 6 years of Jason-1 (cycles 11 to 250)
bull The Mean Profile used for TP (cycles 368 to 481) and from Jason-1 cycle 262 to 374 (where satellitesare on interleaved ground-tracks) is computed with 3 years of TP (cycles 369 to 479)
bull The Mean Profile used for ERS-1 in its 35 days repetitive orbit mission ERS-2 and Envisat (only forthe first orbit before November 2010) is computed with 8 years of ERS-2 (cycles 1 to 85) and 6 yearsof Envisat (cycles 10 to 72)
bull No Mean Profile can be used for Envisat on its new orbit (enn) Jason-1 on its geodetic orbit (j1g)because there is no repetitive track The MSS must be used instead (see below)
bull The Mean Profile used for GFO is computed with 7 years of GFO cycles 37 to 187
Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible
bull Indeed as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide precise cross-track projection andor interpolation schemes are required to avoid errors
bull The mesoscale variability error (which is lt35 cm for MP between 3 to 5 years and lt1cm for WLof 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a prioriknowledge from Sea Level maps derived from previous iterations or from other missions
Page 37
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for ERS-1 for its 168 days geodetic mission (phases E-F from April1994 to March 1995) or for Envisat since november 2010 because the satellite is not in a repetitive orbitphase The alternative is to use the MSS instead The gridded MSS is derived from along track MPs anddata from geodetic phases Thus any error on the MP is also contained in the MSS There are essentially 4types of additional errors on gridded MSS which are hard to quantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
III362 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III363 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
Page 38
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III37 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III371 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
Page 39
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
IV MYOCEAN PRODUCTS
IV1 Near Real Time Products
The purpose of the NRT DUACS component is the acquisition of altimeter data from various altimeter mis-sions in near-real time (ie within a few days at most) the validation and correction of these altimeter datasets (ie edition and selection update of corrections and homogenization orbit error reduction) in order toproduce each day along-track productsProducts are as follows
Along-track products global and regional (Mediterranean and Black Seas Arctic Ocean and Europeareas)
bull Sea Level Anomaly (NRT-SLA) for each mission with NRT-SLA ephemeris
IV11 Delay of the products
The availability of the products in near real time is three to twelve hours after the measurement for along-track products Those products are delivered every day
IV12 Temporal availibility
The following table presents the available products by mission and by data periodNear real time products
NRT Jason-2 Jason-1 and Jason-1geodetic
Envisat new Cryosat-2
Temporal Time availability ymlowast
ongoingymlowast-20120303 for
repeat track and20120507-ongoing for
geodetic track
ymlowast
2012040820120101
ongoing
NRT-SLA X X X X
lowastym the temporal coverage for NRT products is fluctuating and depends on updates of Delayed Time prod-ucts When DT products are updated (3 to 4 times per year) the oldest NRT products are replaced by thebetter quality DT products so that the 2 series are overlapping on few weeks or few months
IV2 Delayed Time Products
The Delayed Time component of SSALTODUACS system is responsible for the production of processedJason-1 Jason-2 TP Envisat GFO ERS12 and even Geosat data in order to provide a homogeneousinter-calibrated and highly accurate long time series of SLA DT products are more precise than NRT products Two reasons explain this quality difference The firstone is the better intrinsic quality of the POE orbit used in the GDR processing The second reason is that
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in the DT DUACS processing the products can be computed optimally with a centred computation timewindow for OER LWE On the contrary in NRT case future data are not available so the computationtime window is not centred and therefore not optimalAs for NRT products improved altimeter corrections and processing algorithms are used ocean tide modelto correct altimeter data improved methods for orbit error reduction and mapping
Along-Track products global and regional (Mediterranean and Black Seas)
bull Sea Level Anomaly (DT-SLA) for each mission
IV21 Delay of the products
Weekly products are delivered The availability of the products in delayed time is at the best two monthsafter the date of the measurement The product generation needs all the GDR data of all the missions to takeinto account the best corrections as possible The time delay can be longer in the case of a missing mission
IV22 Temporal availibility
The following table presents the available products by mission and by data periodDelayed time SSALTODUACS products
Upd Jason-2 Jason-1new6
Jason-1 GFO Envisatnew6
Envisat ERS-16
ERS-2Topexnew6
Topex
TemporalTimeavailabil-ity
200810ymlowast
200902ymlowast
200204200810
200001200809
201010ymlowast
200210201010
199210200304
200209200510
199209200204
DT-SLA X X X X X X X X X
lowast ym those dates are updated regularly (3 to 4 times per year) and are avalaible when you download thedata at httpwwwmyoceaneuweb24-cataloguephp6 Jason-1 new orbit starting 200809 Envisat new orbit starting 201010 TP new orbit starting 200209 ERS-1The geodetic phases (E-F) are included There are no ERS-1 data between December 23 1993 and April 10 1994(ERS-1 phase D - 2nd ice phase) Note that during that time products are based only on TopexPoseidon data
Page 41
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
V DESCRIPTION OF THE PRODUCT SPECIFICATION
V1 General information
Product Specification SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001
Geographical coverage global
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 20-50km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001 Product Specification
Page 42
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
Product Specification SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002
Geographical coverage 55˚W-35˚E 30˚N-46˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002 Product Specification
Page 43
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
Product Specification SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003
Geographical coverage 27˚E-42˚E 40˚N-47˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003 Product Specification
Page 44
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
Product Specification SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004
Geographical coverage 25˚W-42˚E 21˚N-66˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004 Product Specification
Page 45
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
Product Specification SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005
Geographical coverage 0˚W-360˚E 50˚N-82˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005 Product Specification
Page 46
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
VI NOMENCLATURE OF FILES
VI1 Nomenclature of files downloaded through the MyOcean Web PortalDirectgetfile Service
VI11 Nomenclature of the product line
The description of the syntax for the SL TAC SLA products line is given by
SEALEVEL_ltREGIONgt_SLA_L3_ltDELAYgt_OBSERVATIONS_008_ltZONEgt_ltLETTERgtwhere
REGION GLO global geographic coverage product
BS Black Sea products
MED Mediterranean products
ARC Arctic products (for NRT products)
EUROPE Europe products (for NRT products)
DELAY NRT near real time products
RAN delayed time or reanalysis products
ZONE 001 number on 3 digits
002
003
004
LETTER a letter on 1 digit
b
Page 47
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VI12 Nomenclature of the datasets
The nomenclature used is
dataset-duacs-ltdelaygt-ltzonegt-ltmissiongt-lttype of slagt-l3where the fileds in ltgt are described below
delay nrt near-real time productsran delayed time products
zone global global geographic coverage productmedsea Mediterranean productsblacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1 (only for ran)e2 ERS-2 (only for ran)tp TOPEXPoseidon (only for ran)tpn TOPEXPoseidon on its new orbit (only for
ran)g2 GFO (only for ran)j1 Jason-1 (only for ran)j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisat (only for ran)enn Envisat on its new orbitc2 Cryosat-2 (only for nrt)
type of sla sla filtered slasla_unfiltered non filtered sla (only for ran products)
Page 48
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
VI13 Nomenclature of the NetCdf files
The nomenclature used is
ltdelaygt_ltzonegt_ltmissiongt_sla_ltvariablegt_ltdatebegingt_ltdateendgt_ltdateprodgtnc where the fileds in ltgt are de-scribed below
delay nrt near-real time productsdt delayed time products
zone global global geographic coverage productmed Mediterranean products (for dt)mfstep Mediterranean products (for nrt)blacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1e2 ERS-2tp TOPEXPoseidontpn TOPEXPoseidon on its new orbitg2 GFOj1 Jason-1j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisatenn Envisat on its new orbitc2 Cryosat-2
variable vfec filtered and sub-sampled slavxxc non filtered and non sub-sampled sla (only
for dt)datebegin YYYYMMDD() beginning date of the datasetdateend YYYYMMDD() end date of the datasetdateprod YYYYMMDD production date of the dataset
() For dt data as the dates in the file names are rounded the user wanting data for date T has to read the filescontaining dates T+1 and T-1 in their name and check inside the files if there are some data for date T
Page 49
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
VII DATA FORMAT
This chapter presents the data storage format used for MyOcean products
VII1 NetCdf
The products are stored using the NetCDF format NetCDF (network Common Data Form) is an interface for array-oriented data access and a library that provides an implementation of the interface The netCDF library also definesa machine-independent format for representing scientific data Together the interface library and format support thecreation access and sharing of scientific data The netCDF software was developed at the Unidata Program Center inBoulder Colorado The netCDF libraries define a machine-independent format for representing scientific data Pleasesee Unidata NetCDF pages for more information and to retreive NetCDF software package onhttpwwwunidataucaredupackagesnetcdfindexhtml
NetCDF data is
bull Self-Describing A netCDF file includes information about the data it contains
bull Architecture-independent A netCDF file is represented in a form that can be accessed by computers with dif-ferent ways of storing integers characters and floating-point numbers
bull Direct-access A small subset of a large dataset may be accessed efficiently without first reading through allthe preceding data
bull Appendable Data can be appended to a netCDF dataset along one dimension without copying the dataset orredefining its structure The structure of a netCDF dataset can be changed though this sometimes causes thedataset to be copied
bull Sharable One writer and multiple readers may simultaneously access the same netCDF file
Page 50
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
VII2 Structure and semantic of NetCDF along-track files
The NetCDF Sea Level TAC files are based on the attribute data tags defined by the Cooperative OceanAtmosphereResearch Data Service (COARDS) and Climate and Forecast (CF) metadata conventions The CF convention gener-alises and extends the COARDS convention but relaxes the COARDS constraints on dimension and order and specifiesmethods for reducing the size of datasetsA wide range of software are available to write or read NetCDFCF files API are made available by UNIDATA(httpwwwunidataucaredusoftwarenetcdf)
bull CC++Fortran
bull Java
bull MATLAB Objective-C Perl Python R Ruby TclTk
In addition to these conventions the files are using a common structure and semantic
bull 1 dimension is defined
ndash time it is used to check NetCDF variables depending on time
bull 8 variables are defined
ndash short SLA contains the Sea Level Anomaly values for each time given
ndash int longitude contains the longitude for each measurement
ndash short track contains the track number for each measurement
ndash double time contains the time in days since 1950-01-01 000000 UTC for each measurement
ndash short mean_profile_point_index index of the corrsponding point in the track of the mean profile
ndash byte flag flag=0 the processed data comes from OGDR if flag=1 the processed data comes from theIGDR
ndash int latitude contains the latitude for each measurement
ndash short cycle contains the cycle number for each measurement
bull global attributes
ndash the global attributes gives information about the creation of the file
Example of a NetCDF sla file
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
netcdf nrt_global_j1_sla_vfec_20101230_20101230_20101230 dimensions
time = 10385 variables
short SLA(time) SLAcoordinates = longitude latitude SLAlong_name = Sea Level Anomaly SLA_FillValue = 32767s SLAadd_offset = 0 SLAscale_factor = 0001 SLAunits = m SLAstandard_name = sea_surface_height_above_sea_level
int longitude(time) longitudelong_name = Longitude of measurement longitude_FillValue = 2147483647 longitudeadd_offset = 0 longitudestandard_name = longitude longitudescale_factor = 1e-06 longitudeunits = degrees_east
short track(time) tracklong_name = Track in cycle the measurement belongs to track_FillValue = 32767s trackunits = 1 trackcoordinates = longitude latitude
double time(time) timelong_name = Time of measurement time_FillValue = 184467440737096e+19 timeaxis = T timestandard_name = time timeunits = days since 1950-01-01 000000 UTC
int latitude(time) latitudelong_name = Latitude of measurement latitude_FillValue = 2147483647 latitudeadd_offset = 0 latitudestandard_name = latitude latitudescale_factor = 1e-06 latitudeunits = degrees_north
short flag(time) flagcoordinates = longitude latitude flag_FillValue = 3267s flaglong_name = data origin flagflag_values = 1s 0s flagflag_meanings = igdr_like non_igdr_like flagcomment = The origin of the data is determined by the types of geophysical datarecords (GDR) used in computation of the SLA 1 for the Interim GDR (IGDR) and0 for Operational GDR (OGDR)
short cycle(time) cyclelong_name = Cycle the measurement belongs to cycle_FillValue = 32767s cycleunits = 1 cyclecoordinates = longitude latitude
global attributeshistory = 22-Feb-2011 155243 CET File created by the SSLATODUACS system version 1001 comment = Produce from ENVISAT Extension Phase satellite altimetry data institution = CLSCNES
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
references = httpwwwavisooceanobscomfileadmindocumentsdatatoolshdbk_duacspdf source = satellite altimetry title = along track Sea Level Anomaly Conventions = CF-14
dataSLA =
7 7 11 10 -2 -22 -39 -41 -30 -13 -3 -5 -16 -26 -32 -35-35 -35 -37 -35 -31 -29 -31 -35 -32 -21 -10 -10 -19 -20 -1-69 -57 -49 -45 -39 -30 -28 -31 -27 -13 -2 -5 -15 -3 1112 3 -7 -10 -14 -15 -22 -31 -37 -32 -17 -10
longitude =74743328 74868400 74993968 75120040 75246616 7537372875501368 75629568 75758320 75887656 76017568 76148080 7627920876388952 76477056 76565456 76654144 76743128 76832400 76921984329429568 329535424 329641792 329748672 329856096 329964032330072512 330181536 330291072 330401184
track =92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 9292 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92113 113 113 113 113 113 113 113 113 113 113 113 113 113113 113 113 113 113 113 113 113 113
time =222780000565705 222780001314719 222780002063733222780002812747 222780003561761 222780004310775 222780005059788222780005808802 222780006557816 22278000730683 222780008055844222780008804858 222780009553872 22278001017805 222780010677393222788257112198 222788257486705 222788257861212 222788258235719222788258610226 222788258984733 222788259359239 222788259733746222788260108253 22278826048276
mean_profile_point_index =1872 1878 1884 1890 1896 1902 1908 19141920 1926 1932 1938 1944 1949 1953 1957 1961 1965 1969 19732306 2309 2312 2315 2318 2321 2327 2330 2333 2336 2339 23422345 2348 2351 2354 2357 2360 2363 2366
flag =0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
latitude =-16225506 -16539731 -16853833 -17167810 -17481660 -17795380-18108966 -18422418 -18735729 -19048899 -19361924 -19674801-19987527 -20248015 -20456329 -20664569 -20872739 -2108083739481297 39628277 39775133 39921866 40068472 40214953 4036130840507533 40653629 40799592 40945423 41091120 41236684 41382111
cycle =331 331 331 331 331 331 331 331 331 331 331 331 331
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331 331 331 331 331 331 331 331 331 331 331 331 331 331331 331 331 331 331 331 331 331 331 331 331 331
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VIII HOW TO DOWNLOAD A PRODUCT
VIII1 Download a product through the MyOcean Web Portal DirectgetfileService
You first need to register Please find below the registration stepshttpwwwmyoceaneuweb34-products-and-services-faqphp1Once registered the MyOcean FAQ httpwwwmyoceaneuweb34-products-and-services-faqwill guide you on How to download a product through the MyOcean Web Portal Directgetfile Service
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IX NEWS AND UPDATES
IX1 [Duacs] Operational news
To be kept informed on events occurring on the satellites and on the eventual interruption of the services of the DUACSprocessing system see the [Duacs] operational news on the Aviso websitehttpwwwavisooceanobscomendataoperational-newsindexhtml
IX2 Updates
To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtmlSince 2010 a complete reprocessing of all altimetry data (cumulated total of about 55 years of data) is available Themain changes introduced in the Duacs DT v300 reprocessed data set in SSALTODUACS reprocessed DT data setare listed herehttpwwwavisooceanobscomfileadmindocumentsdataduacsduacs_DT_2010_reprocessing_impactpdf
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CHANGE RECORD
Issue Date sect Description of change Author Validated by
10 20110101 all First version of document FranccediloiseMertz VincaRosmorducAnne Dela-marche
Gilles Larnicol
11 20110223 all Correction of anomaliesin the format of the file
FranccediloiseMertz VincaRosmorducAnne Dela-marche
Gilles LarnicolGeacuterald Dibar-boure
20 20110901 all Version V2 of MyOceanproducts
FranccediloiseMertz VincaRosmorducAnne Dela-marche
Gilles LarnicolGeacuterald Dibar-boure
21 20111031 all New template FranccediloiseMertz VincaRosmorducAnne Dela-marche
Gilles LarnicolGeacuterald Dibar-boure
22 20120224 all Version V21 FranccediloiseMertz VincaRosmorducAnne Dela-marche
Gilles LarnicolGeacuterald Dibar-boure
30 20120525 all End of Envisat missionand addition of Jason-1 onits geodetic orbit (j1g)
FranccediloiseMertz VincaRosmorducAnne Dela-marche
Gilles LarnicolGeacuterald Dibar-boure
31 20120720 all New version D of Jason-2IGDR
FranccediloiseMertz VincaRosmorducAnne Dela-marche
Gilles LarnicolGeacuterald Dibar-boure
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CONTENTS
I Introduction 11
II Updates in 2011 and 2012 14II1 Version D of input IGDROGDR Jason-2 data for NRT processing (July 30 2012) 14II2 Integration of Jason-1 on its geodetic orbit (May 2012) 14II3 Envisat has stopped sending data (April 2012) 15II4 Integration of the Cryosat2 Mission (February 2012) 16
II41 Generalities about the mission 16II42 Integration in DUACS 17
II5 Addition of Europe and Arctic products (January 2012) 18
IIISSALTODUACS system 20III1 Introduction 20III2 Near Real Time processing steps 22
III21 Input data models and corrections applied 22III22 Acquisition 25III23 Homogenization 26III24 Input data quality control 26III25 Multi-mission cross-calibration 27III26 Product generation 28
III261 Computation of raw SLA 28III262 Cross validation 29III263 Filtering and sub-sampling 29
III27 Quality control 30III271 Final quality Control 30III272 Performance indicators 31
III3 Delayed Time processing steps 32III31 Input data models and corrections applied 32III32 Acquisition 35III33 Homogenization 35III34 Input data quality control 35III35 Multi-mission cross-calibration 36III36 Product generation 37
III361 Computation of raw SLA 37III362 Cross validation 38III363 Filtering and sub-sampling 38
III37 Quality control 39III371 Final quality Control 39
IV MyOcean Products 40IV1 Near Real Time Products 40
IV11 Delay of the products 40IV12 Temporal availibility 40
IV2 Delayed Time Products 40IV21 Delay of the products 41IV22 Temporal availibility 41
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V Description of the product specification 42V1 General information 42
VI Nomenclature of files 47VI1 Nomenclature of files downloaded through the MyOcean Web Portal DirectgetfileService 47
VI11 Nomenclature of the product line 47VI12 Nomenclature of the datasets 48VI13 Nomenclature of the NetCdf files 49
VIIData format 50VII1NetCdf 50VII2Structure and semantic of NetCDF along-track files 51
VIIIHow to download a product 55VIII1Download a product through the MyOcean Web Portal Directgetfile Service 55
IX News and Updates 56IX1 [Duacs] Operational news 56IX2 Updates 56
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LIST OF TABLES
1 Characteristics of the geodetic orbit for Jason-1 since May 7th 2012 142 SSALTODUACS Near-Real Time Input data overview 223 Corrections and models applied in SSALTODUACS NRT products produced from IGDRs 234 Corrections and models applied in SSALTODUACS NRT products produced from OG-
DRsFDGDRs 245 SSALTODUACS Delayed Time Input data overview 326 Corrections and models applied in SSALTODUACS DT products (gtv300) (12) 337 Corrections and models applied in SSALTODUACS DT products (gtv300) (22) 34
LIST OF FIGURES
1 DUACS and AVISO a user-driven altimetry service 112 SSH-MSS for Cryosat-2 with LRM mode only (left) or LRM+pseudo-LRM modes (right) 163 Coverage of the Europe product for Jason-1 Jason-2 and Envisat from August 18th to
September 9th 2011 184 Coverage of the Arctic region with Envisat from October 28th 2011 to January 3rd 2012 195 SSALTODUACS processing sequences 216 Overview of the near real time system data flow management 257 Merging pertinent information from IGDR and OGDR processing 268 Example with the key performance indicator on 20090627 31
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LIST OF ACRONYMS
ATP Along-Track ProductADT Absolute Dynamic TopographyAVISO Archiving Validation and Interpretation of Satellite Oceanographic dataBGLO Biais Grande Longueur drsquoOndeCalVal Calibration - ValidationCERSAT Centre ERS drsquoArchivage et de TraitementCMA Centre Multimission Altimetry centerCORSSH CORrected Sea Surface HeightC2 Cryosat-2DAC Dynamic Atmospheric CorrectionDT Delayed TimeDTU Mean Sea Surface computed by Technical University of DanemarkDUACS Data Unification and Altimeter Combination SystemE1 ERS-1E2 ERS-2EN EnvisatENN Envisat on its non repetitive orbit (since cycle 94)ECMWF European Centre for Medium-range Weather ForecastingENACT ENhanced ocean data Assimilation and Climate predictionG2 Geosat Follow OnGIM Global Ionospheric MapsGDR Geophysical Data Record(s)IERS International Earth Rotation ServiceIGDR Interim Geophysical Data Record(s)J1 Jason-1J1N Jason-1 on its new orbit (since cycle 262)J1G Jason-1 on its geodetic orbit (since May 2012)J2 Jason-2JPL Jet Propulsion LaboratoryLAS Live Access ServerLWE Long Wavelength ErrorsMADT Map of Absolute Dynamic TopgraphyMDT Mean Dynamic TopographyMOE Medium Orbit EphemerisMP Mean ProfileMSLA Map of Sea Level AnomalyMSS Mean Sea SurfaceNRT Near-Real TimeOE Orbit ErrorOER Orbit Error ReductionOpendap Open-source Project for a Network Data Access ProtocolPF Polynom FitPODAAC Physical Oceanography Distributed Active Archive CentrePOE Precise Orbit EphemerisRD Reference DocumentSAD Static Auxiliary Data
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SI Signed IntegerSLA Sea Level AnomalySL TAC Sea Level Thematic Assembly CentreSSALTO Ssalto multimission ground segmentSSH Sea Surface HeightTAC Thematic Assembly CentreTP TopexPoseidonTPN TopexPoseidon on its new orbit (since cycle 369)
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REFERENCES
[1] Andersen O B The DTU10 Gravity filed and Mean sea surface (2010) Second international sympo-sium of the gravity field of the Earth (IGFS2) Fairbanks Alaska
[2] Boy F et al (2011) Cryosat LRM TRK and SAR processing Presented at the 2011 Ocean Sur-face Topography Science Team meeting httpwwwavisooceanobscomfileadmindocumentsOSTST2011oral01_Wednesday
[3] Carrere L F Lyard 2003 Modeling the barotropic response of the global ocean to atmo-spheric wind and pressure forcing- comparisons with observations J Geophys Res 30(6) 1275doi1010292002GL016473
[4] Carrere L 2003 Etude et modeacutelisation de la reacuteponse HF de lrsquooceacutean global aux forccedilagesmeacuteteacuteorologiques PhD thesis Universiteacute Paul Sabatier (Toulouse III France) 318 pp
[5] Cartwright D E R J Tayler 1971 New computations of the tide-generating potential Geophys JR Astr Soc 23 45-74
[6] Cartwright D E A C Edden 1973 Corrected tables of tidal harmonics Geophys J R Astr Soc33 253-264
[7] Following the scientific recommendations from the OSTST meeting (San Diego October 2011) theESA Cryosat Project and the CNES SALP Project have been collaborating to generate these Cryosat-derived L3 and L4 products Level 1B and Level 2 products derived from CNES processors are notdistributed by AVISO as per the CNES ESA agreement
[8] Dibarboure G C Renaudie M-I Pujol S Labroue N Picot 2011 A demonstrationof the potential of Cryosat-2 to contribute to mesoscale observation J Adv Space Resdoi101016jasr201107002 httpdxdoiorg101016jasr201107002
[9] Dibarboure G P Schaeffer P Escudier M-IPujol JF Legeais Y Faugegravere R Morrow JK WillisJ Lambin JP Berthias N Picot 2010 Finding desirable orbit options for the Extension of Lifephase of Jason-1 Submitted to Marine Geodesy
[10] Dibarboure G M-IPujol FBriol PYLe Traon GLarnicol NPicot FMertz P Escudier MAblainCDufau 2010 Jason-2 in DUACS first tandem results and impact on processing and products Sub-mitted in Marine Geodesy
[11] Dibarboure G 2009 Using short scale content of OGDR data improve the Near Real Time productsof SsaltoDuacs oral presentation at Seattle OSTST meeting (pdf)
[12] Dorandeu J M Ablain Y Faugegravere F Mertz B Soussi and P Vincent 2004 Jason-1 global statisti-cal evaluation and performance assessment Calibration and cross-calibration results Marine Geodesy27(3-4) 345-372
[13] Dorandeu J M Ablain P-Y Le Traon 2003 Reducing Cross-Track Geoid Gradient Errors aroundTOPEXPoseidon and Jason-1 Nominal Tracks Application to Calculation of Sea Level AnomaliesJ of Atmosph and Ocean Techn20 1826-1838
[14] Dorandeu J and P-Y Le Traon 1999 Effects of global mean atmospheric pressure variations onmean sea level changes from TOPEXPoseidon J Atmos Oceanic Technol 16 1279-1283
[15] Ducet N P-Y Le Traon and G Reverdin 2000 Global high resolution mapping of ocean circulationfrom TOPEXPoseidon and ERS-1 and -2 J Geophys Res 105 19477-19498
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[16] Egbert Gary D Svetlana Y Erofeeva 2002 Efficient Inverse Modeling of Barotropic Ocean Tides JAtmos Oceanic Technol 19 183-204 doi 1011751520-0426(2002)019lt0183EIMOBOgt20CO2
[17] Gaspar P and F Ogor Estimation and analysis of the Sea State Bias of the ERS-1 altimeter Reportof task B1-B2 of IFREMER Contract n˚ 942426 016C 1994
[18] Gaspar P F Ogor and C Escoubes 1996 Nouvelles calibration et analyse du biais drsquoeacutetat de mer desaltimegravetres TOPEX et POSEIDON Technical note 96018 of CNES Contract 951523 1996
[19] Gaspar P and F Ogor Estimation and analysis of the Sea State Bias of the new ERS-1 and ERS-2altimetric data (OPR version 6) Report of task 2 of IFREMER Contract n˚ 962246 002C 1996
[20] Gaspar P S Labroue and F Ogor 2002 Improving nonparametric estimates of the sea state bias inradar altimeter measurements of seal level J Atmos Oceanic Technology 19 1690-1707
[21] Hernandez F P-Y Le Traon and R Morrow 1995 Mapping mesoscale variability of the AzoresCurrent using TOPEXPOSEIDON and ERS-1 altimetry together with hydrographic and Lagrangianmeasurements Journal of Geophysical Research 100 24995-25006
[22] Hernandez F and P Schaeffer 2000 Altimetric Mean Sea Surfaces and Gravity Anomaly maps inter-comparisons AVI-NT-011-5242-CLS 48 pp CLS Ramonville St Agne
[23] Hernandez F M-H Calvez J Dorandeu Y Faugegravere F Mertz and P Schaeffer 2000 Sur-face Moyenne Oceacuteanique Support scientifique agrave la mission altimeacutetrique Jason-1 et agrave une mis-sion micro-satellite altimeacutetrique Contrat SSALTO 2945 - Lot 2 - A1 Rapport drsquoavancementCLSDOSNT00313 40 pp CLS Ramonville St Agne
[24] Iijima BA IL Harris CM Ho UJ Lindqwiste AJ Mannucci X Pi MJ Reyes LC SparksBD Wilson 1999 Automated daily process for global ionospheric total electron content maps andsatellite ocean altimeter ionospheric calibration based on Global Positioning System data J AtmosSolar-Terrestrial Physics 61 16 1205-1218
[25] Labroue S F Boy N Picot M Urvoy M Ablain First quality assessment of the Cryosat-2 altimetricsystem over ocean J Adv Space Res 2011 doi101016jasr201111018 httpdxdoiorg101016jasr201111018
[26] Labroue S 2007 RA2 ocean and MWR measurement long term monitoring 2007 report for WP3Task 2 - SSB estimation for RA2 altimeter Contract 1729303I-OL CLS-DOS-NT-07-198 53ppCLS Ramonville St Agne
[27] Labroue S P Gaspar J Dorandeu OZ Zanifeacute F Mertz P Vincent and D Choquet 2004 Nonparametric estimates of the sea state bias for Jason-1 radar altimeter Marine Geodesy 27 453-481
[28] Lagerloef GSE GMitchum RLukas and PNiiler 1999 Tropical Pacific near-surface currentsestimated from altimeter wind and drifter data J Geophys Res 104 23313-23326
[29] Le Traon P-Y and F Hernandez 1992 Mapping the oceanic mesoscale circulation validation ofsatellite altimetry using surface drifters J Atmos Oceanic Technol 9 687-698
[30] Le Traon P-Y P Gaspar F Bouyssel and H Makhmara 1995 Using TopexPoseidon data to en-hance ERS-1 data J Atmos Oceanic Technol 12 161-170
[31] Le Traon P-Y F Nadal and N Ducet 1998 An improved mapping method of multisatellite altimeterdata J Atmos Oceanic Technol 15 522-534
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[32] Le Traon P-Y and F Ogor 1998 ERS-12 orbit improvement using TOPEXPOSEIDON the 2 cmchallenge J Geophys Res 103 8045-8057
[33] Le Traon P-Y and G Dibarboure 1999 Mesoscale mapping capabilities of multi-satellite altimetermissions J Atmos Oceanic Technol 16 1208-1223
[34] Le Traon P-Y G Dibarboure and N Ducet 2001 Use of a High-Resolution Model to Analyze theMapping Capabilities of Multiple-Altimeter Missions J Atmos Oceanic Technol 18 1277-1288
[35] Le Traon PY and G Dibarboure 2002 Velocity mapping capabilities of present and future altimetermissions the role of high frequency signals J Atmos Oceanic Technol 19 2077-2088
[36] Le Traon PY Faugegravere Y Hernandez F Dorandeu J Mertz F and M Ablain 2002 Can we mergeGEOSAT Follow-On with TOPEXPOSEIDON and ERS-2 for an improved description of the oceancirculation J Atmos Oceanic Technol 20 889-895
[37] Le Traon PY and G Dibarboure 2004 An Illustration of the Contribution of the TOPEXPoseidon-Jason-1 Tandem Mission to Mesoscale Variability Studies Marine Geodesy 27 (1-2)
[38] Mertz F F Mercier S Labroue N Tran J Dorandeu 2005 ERS-2 OPR data quality assessment Long-term monitoring - particular investigation CLSDOSNT-06001 (pdf)
[39] MSS_CNES_CLS11 was produced by CLS Space Oceanography Division and distributed by Avisowith support from Cnes (urlhttpwwwavisooceanobscom)
[40] Pascual A Y Faugegravere G Larnicol P-Y Le Traon 2006 Improved description of the oceanmesoscale variability by combining four satellite altimeters Geophys Res Lett 33
[41] Pascual A C Boone G Larnicol and P-Y Le Traon 2009 On the quality of Real-Time altimetergridded fields comparison with in-situ data Journ of Atm and Ocean Techn Vol 26(3) pp 556-569DOI 1011752008JTECHO5561
[42] Prandi P M Ablain A Cazenave N Picot 2011 A new estimation of mean sea level in the ArcticOcean from satellite altimetry Submitted to Marine Geodesy
[43] Pujol M-I et al 2009 Three-satellite quality level restored in NRT poster at OSTST meeting (pdf)
[44] Ray R 1999 A Global Ocean Tide model from TOPEXPoseidon Altimetry GOT992 NASA TechMemo NASATM-1999-209478 58 pp Goddard Space Flight Center NASA Greenbelt MD USA
[45] Rio M-H and F Hernandez 2003 A Mean Dynamic Topography computed over the worldocean from altimetry in-situ measurements and a geoid model J Geophys Res 109 C12032doi1010292003JC002226
[46] Rio M-H and F Hernandez 2003 High frequency response of wind-driven currents measured bydrifting buoys and altimetry over the world ocean J Geophys Res 108 39-1
[47] Rio M-H 2003 Combinaison de donneacutees in situ altimeacutetriques et gravimeacutetriques pour lrsquoestimationdrsquoune topographie dynamique moyenne globale Ed CLS PhD Thesis University Paul Sabatier(Toulouse III France) 260pp
[48] Scharroo R and P Visser 1998 Precise orbit determination and gravity field improvement for theERS satellites J Geophys Res 103 8113-8127
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[49] Scharroo R J Lillibridge and WHF Smith 2004 Cross-calibration and long-term monitoring ofthe Microwave Radiometers of ERS Topex GFO Jason-1 and Envisat Marine Geodesy 97
[50] Tran N and E Obligis December 2003 Validation of the use of ENVISAT neural algorithms onERS-2 CLSDOSNT03901
[51] Tran N S Labroue S Philipps E Bronner and N Picot 2010 Overview and Update of the SeaState Bias Corrections for the Jason-2 Jason-1 and TOPEX Missions Marine Geodesy accepted
[52] Vincent P Desai SDDorandeu J Ablain M Soussi B Callahan PS and BJ Haines 2003 Jason-1 Geophysical Performance Evaluation Marine Geodesy 26 167-186
[53] Wahr J W 1985 Deformation of the Earth induced by polar motionJ of Geophys Res (Solid Earth)90 9363-9368
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I INTRODUCTION
MyOcean is a European Network project aiming at monitoring analyzing and forecasting the Ocean Ituses satellite and in-situ data to describe the ocean in 3 dimensions and real time More information can befound on httpwwwmyoceaneuorgThe aim of this document is to describe the products delivered by the Sea Level TAC (Thematic AssemblyCentre) which is one of the five TAC of the MyOcean projectThe data produced in the frame of this TAC are generated by the processing system named DUACS (DataUnification and Altimeter Combination System)DUACS is part of the CNES multi-mission ground segment (SSALTO) It processes data from all altimetermissions Cryosat-2 OSTMJason-2 Jason-1 TopexPoseidon Envisat GFO ERS-1amp2 and even GeosatAt this time (May 25th 2012) DUACS is using three different altimeters in near real time Developed and operated by CLS it started as an European Commission Project (Developing Use Of Altime-try for Climate Studies) funded under the European Commission and the Midi-Pyreacuteneacutees regional councilIt has been integrated to the CNES multi-mission ground segment SSALTO in 2001 and it is maintainedupgraded and operated with funding from CNES with shared costs from EU projectsAt the beginning of 2004 DUACS was redefined as the Data Unification Altimeter Combination System
Figure 1 DUACS and AVISO a user-driven altimetry service
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The products lines described in this user manual are the followingSEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005
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The data provided to users have a global coverage (PL SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001)and regional products are also computed over specific areasMediterranean Sea (PL SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002)and Black Sea (PL SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003)Thanks to updates in 2011 and 2012 (see section II) new regional products are now availableEurope (PL SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004)and Arctic (PL SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005)
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II UPDATES IN 2011 AND 2012
This section describes the updates of the SSALTODUACS Near Real Time system that occurred during2011 and 2012 allowing to add new products (Europe and Arctic) the integration of the Cryosat-2 data inthe system the stopping delivery of Envisat data the addition of Jason-1 data on geodetic orbit (j1g)To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtml
II1 Version D of input IGDROGDR Jason-2 data for NRT processing(July 30 2012)
On July 30 2012 the version of Jason-2 IGDROGDR has changed and is now the D version Somecorrections have thus been updated as detailed in tables 3 and 4
II2 Integration of Jason-1 on its geodetic orbit (May 2012)
An anomaly occured on March 3rd 2012 on the Jason-2 mission (see httpwwwavisooceanobscomfractualitesactualitesindexhtmltx_ttnews[tt_news]=1162amptx_ttnews[backPid]=1399ampcHash=d5baeb645e) On April 23rd CNES began to command the satellite into a nadir ori-entation and after some propulsion anomalies CNES and NASA management through the Joint SteeringGroup have directed the Jason-1 Project to then begin a series of maneuvers to place Jason-1 into a neworbit as defined in table 1 After checking the current orbit carefully the operational team determined thata geodetic mission was still possible It was also decided to preserve all remaining fuel for future stationkeeping maneuvers which is mandatory in a geodetic orbit Core payloads were switched ON on May 4thand after some POSEIDON2 radar (PRF) adjustments the mission was resumed on May 7th at 151248UTCBelow are the characteristics of the new orbit which will be maintained as before within +- 1km controlbox at the Equator
Semi major axis 7702437 kmEccentricity 13 to 28 10-4Altitude equator 13240 kmOrbital period 6730s (1h52rsquo10rdquo)Inclination 66042˚Cycle 406 daysSub cycles 39 - 109 - 475 - 1795
days
Table 1 Characteristics of the geodetic orbit for Jason-1 since May 7th 2012
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For this new phase of the Jason-1 mission (called j1g) the cycle numbering will restart at 500 Off-lineproducts will be produced once a day for the IGDR and every 11 days for the GDRrsquos The integration ofJason-1 data in the DUACS system is available since May 25th 2012
II3 Envisat has stopped sending data (April 2012)
Since April 8th 2012 Envisat has stopped sending data to Earth Esarsquos mission control has worked tore-establish contact with the satellite but there has been no reaction from the satellite Thus Esa has de-clared officially the end of mission for Envisat (see httpwwwesaintesaCPSEM1SXSWT1H_index_0html) Therefore no SL TAC NRT data from Envisat can be released since this date
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II4 Integration of the Cryosat2 Mission (February 2012)
Since February 6th 2012 Cryosat-2 mission has been integrated in the DUACS sytem This mission isdedicated to the observation of the floating sea-ice as well as the continental ice sheets but all data acquiredover ocean are valuable for the observation of oceanic circulation and mesoscale variations This majorchange is the result of the long-standing and fruitful partnership between ESA and CNES and a responseto the request from scientific and operational oceanography users [7] The integration of Cryosat-2 impactsthe delivering of Near real time Sea Level Anomalies (SLA)
II41 Generalities about the mission
A Cryosat-2 Processing Prototype (C2P) (described in Boy et al 2011 [2]) has been developed on CNESside to lay the ground for various SAR processing studies The processing chains ingest Level-0 telemetryfiles distributed by ESA and perform the following steps to generate Sea Level Anomalies (SLA) values foreach altimeter measurements
bull Level-1 Decommutation time-tagging and localization of measurements
bull Level-1b Calculation of instrumental corrections and geophysicalmeteorological corrections
bull Level-2 MLE4 waveforms Retracking and calculation of SLA
The prototype processes data almost continuously over ocean either in Low Resolution Mode (LRM) or inthe DopplerSAR mode processed as pseudo-LRM mode allowing to increase the coverage (figure 2)
Figure 2 SSH-MSS for Cryosat-2 with LRM mode only (left) or LRM+pseudo-LRM modes (right)
Although Cryosat-2 raw SSH can be only corrected with GPS-derived ionospheric correction and ECMWFwet troposphere correction validation activities showed (Labroue et al 2011 [25]) that C2P outputs have anaccuracy roughly equivalent to Envisatrsquos Level 2 products if the latter are processed with the same standards
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II42 Integration in DUACS
The Cryosat-2 data are included in the Near Real time process The chain delivers now (for global coverageMediterranean and Black Seas) along track data from Cryosat-2 (SLAs) Note that the products distributedare of Level-3 and donrsquot replace Level-2 products distributed by agenciesThe details of the processing are given in Dibarboure et al 2011 [8]Here we just give an overview the data are computed with the corrections given in section III21 Thefiltering and sub-sampling of SLAs (section III263) are detailed in [8]
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II5 Addition of Europe and Arctic products (January 2012)
Since the MyOcean V2 two new along-track products are computed in Near Real Time intended foraddressing the needs of data assmilation and validation in regional models
bull Following the TAPAS (Tailored Altimeter Product for Assimilation Systems) initiative launched bySL TAC with all the Modeling and Forecasting Centers (MFCs) the Europe regional products (PLSEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004) have been proposed (figure 3) They areavailable in Near Real Time onlyThey are studied to partly fulfil the needs of the Centers with adapted filtering and resolution Thoseparameters have been tuned in order to provide boundary conditions for the Atlantic assimilationmodels They are different from the ones used for Mediterranean and Black Seas products If you needto study the Mediterranean Sea or the Black Sea yoursquod better use the dedicated products describedabove since the processing parameters have been fitted to be adapted to the dynamics of the ocean inthose regions
Figure 3 Coverage of the Europe product for Jason-1 Jason-2 and Envisat from August 18th to September9th 2011
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
bull The Arctic along-track products (PL SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005) coverlatitudes between 45 and 82 degrees (figure 4) They are available in Near Real Time only
Figure 4 Coverage of the Arctic region with Envisat from October 28th 2011 to January 3rd 2012
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III SSALTODUACS SYSTEM
III1 Introduction
This chapter presents the input data used by SSALTODUACS system and an overview of the different pro-cessing steps necessary to produce the output dataSSALTODUACS system is made of two components a Near Real Time one (NRT) and a Delayed Time(DT) oneIn NRT the systemrsquos primary objective is to provide operational applications with directly usable high qual-ity altimeter data from all missions availableIn DT it is to maintain a consistent and user-friendly altimeter database using the state-of-the-art recom-mendations from the altimetry communityFollowing figure gives an overview of DUACS system where processing sequences can be divided into 7main steps
bull acquisition
bull homogenization
bull input data quality control
bull multi-mission cross-calibration
bull product generation
bull merging
bull final quality control
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Figure 5 SSALTODUACS processing sequences
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III2 Near Real Time processing steps
III21 Input data models and corrections applied
To produce SLA in near-real time the DUACS system uses two flows based on the same instrumental mea-surements but with a different quality
bull The IGDR that are the latest high-quality altimeter data produced in near-real-time
bull The OGDR that includes real time data (OSTMJason-2 and Jason-1 OSDR) to complete IGDR Thesefast delivery products do not always benefit from precise orbit determination nor from some exter-nal model-based corrections (Dynamic Atmospheric Correction (DAC) Global Ionospheric Maps(GIM))
Integration of OGDR data and the introduction of Jason-2Jason-1 tandem increased the resilience and pre-cision of the system A better restitution of ocean variability is observed especially in high energetic areas
Altimetric product Source Availability Type of orbit
Jason-2 IGDR CNES ~24h CNES MOE GDR-Cuntil 20120730
CNES MOE GDR-Dsince 20120731
OGDR NOAAEUMETSAT ~3 to 5 h
Jason-1 IGDR CNESNASA ~48 h CNES MOE GDR-Dsince 20120507
OGDR CNESNASA ~3 to 12 h
Envisat IGDR ESACNES not deliveredsince 20120408
CNES MOE GDR-Dsince 20120121
FDGDR ESA not deliveredsince 20120408
Cryosat-2 IGDR-like ESACNES ~48 h CNES MOE GDR-D
not delivered
Table 2 SSALTODUACS Near-Real Time Input data overview
See Figure 6 Overview of the near real time system data flow management
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DUACS 2011 NRT product from IGDR1
j2 j1nj1g enn c2Productstandard ref
version C until20120730 and D after
version C version 21 CPP [2]
Orbit CNES MOE GDR-Cuntil 20120730
GDR-D after
CNES MOE GDR-C forj1n and CNES MOE
GDR-D for j1g
CNES MOE GDR-Dfrom 20120121 to
20120408
CNES MOE GDR-D
Ionopheric bi-frequency altimeter range measurements GIM model for cgt64 (Iijima et al1998[24])Dry tropo Model computed from ECMWF Gaussian grids (new S1 and S2 atm tides applied)Wet tropo-sphere
AMR radiometer(enhancement in coastal
regions since20120730)
JMR radiometer MWR radiometer andcorrected from side
lobes
Model computed fromECMWF Gaussian
grids
DAC MOG2D High Resolution forced with ECMWF pressure and wind fields (S1 and S2 wereexcluded) (Carrere and Lyard 2003[3])+ inverse barometer Filtering temporal window is
un-centered (no data in the future)Ocean tide GOT4v8 (S1 and S2 are included) and TPX 072 [16] for Arctic productsPole tide [Wahr 1985 [53]]Solid earthtide
Elastic response to tidal potential [Cartwright and Tayler 1971[5]] [Cartwright andEdden 1973[6]]
Loading tide GOT4v8 (S1 and S2 are included)Sea statebias
Non parametric SSB[Labroue 2004[27]](with cycles J1 1 to 11
using GDR-B standardsuntil 20120730 andderived from Jason-2
after)
Non parametric SSB[Labroue 2004[27]](with cycles 1 to 21
using GDR-Bstandards)
Non parametric SSB[Labroue 2004[27]](with cycles 41 to 60
using GDR-Bstandards)
Same as Jason-2 SSB
Orbit error Global multi-mission crossover minimization (Le Traon and Ogor1998[32])
Long wave-lengh errors
Optimal Interpolation [Le Traon et al 1998[31]]
Intercalibration Reference from cycle20
Mean pro-file (seeIII261)
Computed with cycles11-353 TP data andwith cycles 11-250J1 data referenced[19931999]
TPNJ1N computedwith cycles 369-479TPN data refer-enced [19931999]J1G No MP can beused instead theMSS_CNES_CLS11[39] is used
No Mean Profilecan be used forEnvisat on its neworbit Instead theMSS_CNES_CLS11[39] is used
No Mean Profilecan be used forCryosat-2 Instead theMSS_CNES_CLS11[39] is used
(1) A flag included in the along-track files indicates the source of the production (OGDRFDGDR orIGDR) If flag=0 the processed data comes from OGDRsFDGDRs if flag=1 the processed data comesfrom IGDRs
Table 3 Corrections and models applied in SSALTODUACS NRT products produced from IGDRs
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DUACS 2011 NRT product from OGDR or FDGDR2
j2 j1nj1g ennProduct stan-dard ref
version C until 20120730and D after
version C version 21
Orbit Navigator Extrapolated CNES MOEGDR-D since 20120121
Ionopheric From-dual frequency altimeter range measurements From GIM model fromcycle 65 (Iijima et al1998 [24])
Dry troposphere Model computed from ECMWF Gaussian grids (new S1 and S2 atmospherictides are applied)
Wet tropo-sphere
AMR radiometer(enhancement in coastal
regions since 20120730)
JMR radiometer MWR radiometer andcorrected from side lobes
DAC Inverse Barometer forecastedOcean tide GOT4v8 (S1 and S2 are included) and TPX 072 [16] for Arctic productsPole tide [Wahr 1985 [53]]Solid earth tide Elastic response to tidal potential [Cartwright and Tayler 1971[5]]
[Cartwright and Edden 1973[6]]Loading tide GOT4v8 (S1 and S2 are included)Sea state bias Non parametric SSB
[Labroue 2004[27]] (withcycles J1 1 to 11 usingGDR-B standards until20120730 and derivedfrom Jason-2 after)
Non parametric SSB[Labroue 2004[27]](with cycles 1 to 21 usingGDR-B standards)
Non parametric SSB[Labroue 2004[27]](with cycles 41 to 60using GDR-B standards)
Orbit error Specific filtering of long-wavelength signal3
Long wave-lengh errors
Optimal Interpolation [Le Traon et al 1998[31]]
Intercalibration Reference from cycle 20Mean profile(see III261)
Computed with cycles 11-353 TP data and with cy-cles 11-250 J1 data refer-enced [19931999]
TPNJ1N computedwith cycles 369-479TPN data referenced[19931999] J1G NoMP can be used insteadthe MSS_CNES_CLS11[39] is used
No Mean Profile can beused for Envisat on itsnew orbit Instead theMSS_CNES_CLS11 [39]is used
(2) A flag included in the along-track files indicates the source of the production (OGDRFDGDR orIGDR) If flag=0 the processed data comes from OGDRsFDGDRs if flag=1 the processed data comesfrom IGDRs(3) Specific data processing was applied on long wave-length signal (sectIII23 of the user manual)
Table 4 Corrections and models applied in SSALTODUACS NRT products produced from OG-DRsFDGDRs
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III22 Acquisition
The acquisition process is twofold
bull straightforward retrieval and reformatting of altimeter data and dynamic auxiliary data (pressure andwet troposphere correction grids from ECMWF are provided by Meteo France TEC grids from JPLNRT MOG2D corrections) from external repositories
bull synchronisation process
To be homogenized properly altimeter data sets require various auxiliary data The acquisition softwaredetects downloads and processes incoming data as soon as they are available on remote sites (externaldatabase FTP site) Data are split into passes if necessary If data flows are missing or late the synchroni-sation engine put unusable data in waiting queues and automatically unfreezes them upon reception of themissing auxiliary data This processing step delivers raw data that is to say data that have been dividedinto cycles and passes and ordered chronologicallyFrom SSALTODUACS V80 the acquisition step uses two different data flows in near-real time the OGDRflow (within a few hours) and the IGDR flow (within a few days)For each OGDR input the system checks that no equivalent IGDR entry is available in the data base beforeacquisition for each IGDR input the system checks and delete the equivalent OGDR entry in the data baseThese operations aim to avoid duplicates in SSALTODUACS system
Figure 6 Overview of the near real time system data flow management
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III23 Homogenization
The Homogenization process consists in applying the most recent corrections models and references rec-ommended for altimeter products Each mission is processed separately as its needs depend on the baseinput data The list of corrections and models currently applied is provided in tables 3 and 4 for NRT dataThe system includes SLA filtering to process OGDR data DUACS extract from these data sets the shortscales (space and time) which are useful to better describe the ocean variability in real time and merge thisinformation with a fair description of large scale signals provided by the multi-satellite observation in nearreal time (read IGDR-based DUACS data) Finally an hybrid SLA is computed
Figure 7 Merging pertinent information from IGDR and OGDR processing
III24 Input data quality control
The Input Data Quality Control is a critical process applied to guarantee that DUACS uses only the mostaccurate altimeter data Thanks to the high quality of current missions this process rejects a small percent-age of altimeter measurements but these erroneous data could be the cause of a significant quality lossThe quality control relies on standard raw data editing with quality flags or parameter thresholds but alsoon complex data editing algorithms based on the detection of erroneous artefacts mono and multi-missioncrossover validation and macroscopic statistics to edit out large data flows that do not meet the systemrsquosrequirements
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III25 Multi-mission cross-calibration
The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistentand accurate information It removes any residual orbit error (OE Le Traon and Ogor 1998[32]) or longwavelength error (LWE Le Traon et al 1998[31]) as well as large scale biases and discrepancies betweenvarious data flows
This process is based on two very different algorithms a global multi-mission crossover minimization fororbit error reduction (OER) and Optimal Interpolation (OI) for LWE
Multi-satellite crossover determination is performed on a daily basis All altimeter fields (measurementcorrections and other fields such as bathymetry MSS) are interpolated at crossover locations and datesCrossovers are then appended to the existing crossover database as more altimeter data become availableThis crossover data set is the input of the Orbit Error Reduction (OER) method Using the precision of thereference mission orbit a very accurate orbit error can be estimated This processing step does not concernOGDR dataLWE is mostly due to residual tidal or inverse barometer errors and high frequency ocean signals The OIused for LWE reduction uses precise parameters derived from
bull accurate statistical description of sea level variability
bull localized correlation scales
bull mission-specific noise and precise assumptions on the long wavelength errors to be removed (from arecent analysis of one year of data from each mission)
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III26 Product generation
The product generation process is composed of four steps computation of raw SLA cross-validationfilteringampsub-sampling and generation of by-products
III261 Computation of raw SLA
Since the geoid is not well known yet the SSH cannot be used directly the SSH anomalies are used insteadThey are computed from the difference of the instantaneous SSH - a temporal reference This temporalreference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeattrack analysis cannot be used The errors affecting the SLAs MPs and MSS have different magnitudes andwavelengths The computation of the SLAs and their errors associated are detailed in Dibarboure et al 2010[9]
Use of a Mean ProfileIn the repeat track analysis (when the satellites flies over a repetitive orbit) measurements are re-sampledalong a theoretical ground track (or mean track) associated to each mission Then a Mean Profile (MP) issubtracted from the re-sampled data to obtain SLA The MP is a time average of similarly re-sampled dataover a long period
bull The Mean Profile used for Jason-2 is computed with 10 years of TP (cycles 11 to 353) and 6 years ofJason-1 (cycles 11 to 250)
bull The Mean Profile used from Jason-1 cycle 262 to 374 (where satellites are on interleaved ground-tracks) is computed with 3 years of TP (cycles 369 to 479)
bull No Mean Profile can be used for Envisat on its new orbit (enn) Jason-1 on its geodetic orbit (j1g) norfor Cryosat-2 mission (c2) because there is no repetitive track The MSS must be used instead (seebelow)
Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible
bull Indeed as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide precise cross-track projection andor interpolation schemes are required to avoid errors
bull The mesoscale variability error (which is lt35 cm for MP between 3 to 5 years and lt1cm for WLof 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a prioriknowledge from Sea Level maps derived from previous iterations or from other missions
bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for Envisat since november 2010 and for Cryosat-2 mission (c2)because the satellite is not in a repetitive orbit phase The alternative is to use the MSS instead The griddedMSS is derived from along track MPs and data from geodetic phases Thus any error on the MP is alsocontained in the MSS There are essentially 4 types of additional errors on gridded MSS which are hard toquantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
Note that for the Arctic regional products the DTU10 MSS [1] is taken into account instead of the CLS01MSS Indeed the accuracy of DTU10 compared to CLS01 is further demonstrated by the significant sealevel anomaly variance reduction found over the whole Arctic Ocean as shown in Prandi et al [42]
III262 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III263 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
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III27 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III271 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
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III272 Performance indicators
To appreciate the quality situation of the DUACS system new performance indicators are computed dailyThey aim at evaluate the status of the main processing steps of the system the input data availability theinput data coverage the input data quality and the output product quality These indicators are computed foreach and every currently working satellite and combined to obtain the overall status
Figure 8 Example with the key performance indicator on 20090627
See the description the latest and previous indicators on Aviso websitehttpwwwavisooceanobscomindexphpid=1516
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III3 Delayed Time processing steps
III31 Input data models and corrections applied
Delayed Time MyOcean products are generated
bull from Aviso GDR products for TP Jason-1 Jason-2 and Envisat (GDR-A cycles 1 to 22 GDR-Bcycles 23 to 85 GDR-C from cycle 86)
bull from NOAA GDR for GFO and from CERSAT (IFREMER) OPR for ERS-1 and ERS-2 (phases C(1st 35-day repeat orbit period) phase E and F (geodetic phases) phase G for ERS-1 (last 35-dayrepeat orbit period tandem phase with ERS-2 phase A for ERS-2 (1st 35-day repeat orbit periodtandem phase with ERS-1))
All GDR products are computed with a Precise Orbit Ephemeris (POE) and are delivered within 2 to 3months depending on the mission For several missions an updated orbit is used
bull For ERS-1amp-2 the orbit used is DGME-04 provided by Delft Institute (httpwwwdeostudelftnl)until June 2003
bull For TopexPoseidon the orbit used is GSFC (std0809) for the whole mission
bull For Envisat CNES POE of GDR-C standard is used for the whole mission
bull For the whole GFO mission the orbit used is GSFC (std0809) and when not available NASA POE isused
Altimetric product Source Availability Type of orbit
TopexPoseidon GDR NASACNES - GSFC POE
Jason-1 GDR (GDR-C) CNESNASA ~40 days CNES POE
Jason-2 GDR (GDR-C) CNESNASA ~60 days CNES POE
GFO GDR NOAA - GSFCNASA POE
ERS-1amp2 IFREMERESA - DGME-04
Envisat (GDR-A GDR-B andGDR-C from cycle 86)
ESA ~2 months CNES POE
Table 5 SSALTODUACS Delayed Time Input data overview
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
DU
AC
S20
11D
Tpr
oduc
t(gtV
30
0)j2
j1j1
ntp
tpn
e1e2
ene
nng2
Prod
uct
stan
dard
ref
GD
R-C
OPR
GD
R-A
(Cyc
les
1to
22)
GD
R-B
(cyc
les
23-8
5)
GD
R(N
OA
A)
Orb
itC
nes
POE
GSF
C(I
TR
F20
05G
RA
CE
last
stan
dard
s)
DG
ME
-04
(Sch
arro
oan
dV
isse
r19
98[4
8]C
NE
SPO
E(G
DR
-1st
anda
rds
forc
ycle
s9
to22
GD
R-C
stan
dard
sfr
omcy
cle
23)
GSF
C(I
TR
F20
05
GR
AC
Ela
stst
anda
rds
Iono
pher
icD
ual f
requ
ency
altim
eter
rang
em
easu
rem
ents
Dua
l fre
quen
cyal
timet
erra
nge
mea
sure
men
ts(T
opex
)D
OR
IS(P
OSE
IDO
N)
Ben
t mod
elB
ent m
odel
(cyc
les
1-36
)G
IMm
odem
from
cycl
e37
((Ii
jima
etal
19
98[2
4])
Dua
l-fr
eque
ncy
altim
eter
rang
em
easu
rem
ent(
cycl
e9-
64)a
ndG
IMm
odel
gtcyc
le65
(Iiji
ma
etal
19
99[2
4])c
orre
cted
from
8m
mbi
as
From
GIM
mod
el(I
ijim
aet
al1
998
[24]
)
Dry
trop
o-sp
here
Mod
elco
mpu
ted
from
EC
MW
FG
auss
ian
grid
s(n
ewS1
and
S2at
mos
pher
ictid
esar
eap
plie
d)
Mod
elco
mpu
ted
from
EC
MW
Fre
ctan
gula
rgri
ds(n
ewS1
and
S2at
mos
pher
ictid
esar
ein
clud
ed)
Wet
trop
o-sp
here
JMR
AM
Rra
diom
eter
furt
hert
han
50km
from
the
coas
tsF
rom
EC
MW
Fm
odel
ford
ista
nces
betw
een
10an
d50
km
TM
Rra
diom
eter
(Sch
aroo
etal
20
04[4
9])
MW
RC
orre
ctio
nof
the
drif
ton
the
236
GH
zbr
ight
ness
tem
pera
ture
(Sch
arro
oet
al
2004
[49]
)Neu
ral
Net
wor
kal
gori
thm
(Tra
nan
dO
blig
is
2003
[50]
MW
Rra
diom
eter
furt
hert
han
50km
from
the
coas
tsan
dco
rrec
ted
from
side
lobe
s(f
rom
cycl
e41
)E
CM
WF
mod
elfo
rdis
tanc
esbe
twee
n10
and
50km
GFO
radi
omet
er
DA
CM
OG
2DH
igh
Res
olut
ion
forc
edw
ithE
CM
WF
pres
sure
and
win
gfie
lds
(S1
and
S2w
ere
excl
uded
)+in
vers
eba
rom
eter
com
pute
dfr
omre
ctan
gula
rgri
ds
Tabl
e6
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(1
2)
Page 33
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
j2j1
j1n
tptp
ne1
e2en
enn
g2O
cean
tide
GO
T4v
7(S
1an
dS2
are
incl
uded
)Po
letid
e[W
ahr
1985
[53]
]So
lidea
rth
tide
Ela
stic
resp
onse
totid
alpo
tent
ial[
Car
twri
ghta
ndTa
yler
197
1[5]
][C
artw
righ
tand
Edd
en1
973[
6]]
Loa
ding
tide
GO
T4v
7(S
1pa
ram
eter
isin
clud
ed)
Sea
stat
ebi
asN
onpa
ram
etri
cSS
B[G
aspa
reta
l20
02[2
0]]
Non
para
met
ric
SSB
[NT
ran
and
al2
010[
51]]
BM
3[G
aspa
ran
dO
gor
1994
[17]
]
Non
para
met
ric
SSB
[Mer
tzet
al
2005
[38]
]
Non
para
met
ric
SSB
[Gas
pare
tal
2002
]w
ithG
DR
-Bst
anda
rds
forc
ycle
s9
to85
and
with
GD
R-C
stan
dard
sfr
omcy
cle
86
Non
para
met
ric
SSB
[NT
ran
etal
20
10[5
1]]
Orb
iter
ror
Glo
bal m
ulti-
mis
sion
cros
sove
rmin
imiz
atio
n(L
eTr
aon
and
Ogo
r19
98[3
2])
Lon
gw
ave-
leng
her
rors
Opt
imal
Inte
rpol
atio
n(L
eTr
aon
etal
19
98[3
1])
Inte
rcal
ibra
tion
Ref
eren
cefr
omcy
cle
11R
efer
ence
from
cycl
e1
to35
4C
orre
ctio
nof
regi
onal
bias
J2J
1de
duce
dfr
omin
terc
alib
ratio
nph
ase
(cyc
le11
J2)
Cor
rect
ion
ofgl
obal
biai
sJ1
TP
deacutedu
ced
from
inte
rcal
ibra
tion
phas
e(c
ycle
s11
J1)
Mea
npr
o-fil
e(s
eeII
I36
1)
Com
pute
dw
ithcy
cles
11-3
53T
Pda
taan
dw
ithcy
cles
11-2
50J1
data
ref
eren
ced
[199
319
99]
TP
J1 c
ompu
ted
with
cycl
es11
-353
TP
data
and
with
cycl
es11
-250
J1da
tar
efer
ence
d[1
993
1999
]T
PNJ
1Nc
ompu
ted
with
cycl
es36
9-47
9T
PNda
tar
efer
ence
d[1
993
1999
]
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
ref
eren
ced
[199
319
99]
EN
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
re
fere
nced
[199
319
99]
EN
Nu
seof
MSS
_CN
ES_
CL
S11
[39]
Com
pute
dw
ithcy
cles
37-1
87G
2da
ta
refe
renc
ed[1
993
1999
]
Peri
odof
use
from
cycl
e9
from
cycl
e9
cycl
es1
to48
1cy
cles
15to
43In
clud
ing
E-F
geod
etic
phas
es
cycl
es1
to83
from
cycl
e9
cycl
es37
to22
2
Tabl
e7
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(2
2)
Page 34
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III32 Acquisition
The acqusition process in Delayed time is much simpler than in Near Real time it consists in a synchronisa-tion process of all the auxiliary data required to homogenize propely the altimeter data sets The acquisitionstep uses the GDRs or the OPRs provided by the agencies
III33 Homogenization
The Homogenization process consists in applying the most recent corrections models and references rec-ommended for altimeter products Each mission is processed separately as its needs depend on the baseinput data The list of corrections and models currently applied is provided in tables 6 and 7 for DT data
III34 Input data quality control
The Input Data Quality Control is a critical process applied to guarantee that DUACS uses only the mostaccurate altimeter data Thanks to the high quality of current missions this process rejects a small percent-age of altimeter measurements but these erroneous data could be the cause of a significant quality lossThe quality control relies on standard raw data editing with quality flags or parameter thresholds but alsoon complex data editing algorithms based on the detection of erroneous artefacts mono and multi-missioncrossover validation and macroscopic statistics to edit out large data flows that do not meet the systemrsquosrequirements
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III35 Multi-mission cross-calibration
The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistentand accurate information It removes any residual orbit error (OE Le Traon and Ogor 1998[32]) or longwavelength error (LWE Le Traon et al 1998[31]) as well as large scale biases and discrepancies betweenvarious data flows
This process is based on two very different algorithms a global multi-mission crossover minimization fororbit error reduction (OER) and Optimal Interpolation (OI) for LWE
Multi-satellite crossover determination is performed on a daily basis All altimeter fields (measurementcorrections and other fields such as bathymetry MSS) are interpolated at crossover locations and datesCrossovers are then appended to the existing crossover database as more altimeter data become availableThis crossover data set is the input of the Orbit Error Reduction (OER) method Using the precision of thereference mission orbit a very accurate orbit error can be estimated LWE is mostly due to residual tidalor inverse barometer errors and high frequency ocean signals The OI used for LWE reduction uses preciseparameters derived from
bull accurate statistical description of sea level variability
bull localized correlation scales
bull mission-specific noise and precise assumptions on the long wavelength errors to be removed (from arecent analysis of one year of data from each mission)
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III36 Product generation
The product generation process is composed of four steps computation of raw SLA cross-validationfilteringampsub-sampling and generation of by-products
III361 Computation of raw SLA
Since the geoid is not well known yet the SSH cannot be used directly the SSH anomalies are used insteadThey are computed from the difference of the instantaneous SSH - a temporal reference This temporalreference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeattrack analysis cannot be used The errors affecting the SLAs MPs and MSS have different magnitudes andwavelengths The computation of the SLAs and their errors associated are detailed in Dibarboure et al 2010[9]
Use of a Mean ProfileIn the repeat track analysis (when the satellites flies over a repetitive orbit) measurements are re-sampledalong a theoretical ground track (or mean track) associated to each mission Then a Mean Profile (MP) issubtracted from the re-sampled data to obtain SLA The MP is a time average of similarly re-sampled dataover a long period
bull The Mean Profile used for TP (cycles 1 to 364) Jason-1 (cycles 1 to 259) and Jason-2 is computedwith 10 years of TP (cycles 11 to 353) and 6 years of Jason-1 (cycles 11 to 250)
bull The Mean Profile used for TP (cycles 368 to 481) and from Jason-1 cycle 262 to 374 (where satellitesare on interleaved ground-tracks) is computed with 3 years of TP (cycles 369 to 479)
bull The Mean Profile used for ERS-1 in its 35 days repetitive orbit mission ERS-2 and Envisat (only forthe first orbit before November 2010) is computed with 8 years of ERS-2 (cycles 1 to 85) and 6 yearsof Envisat (cycles 10 to 72)
bull No Mean Profile can be used for Envisat on its new orbit (enn) Jason-1 on its geodetic orbit (j1g)because there is no repetitive track The MSS must be used instead (see below)
bull The Mean Profile used for GFO is computed with 7 years of GFO cycles 37 to 187
Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible
bull Indeed as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide precise cross-track projection andor interpolation schemes are required to avoid errors
bull The mesoscale variability error (which is lt35 cm for MP between 3 to 5 years and lt1cm for WLof 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a prioriknowledge from Sea Level maps derived from previous iterations or from other missions
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PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for ERS-1 for its 168 days geodetic mission (phases E-F from April1994 to March 1995) or for Envisat since november 2010 because the satellite is not in a repetitive orbitphase The alternative is to use the MSS instead The gridded MSS is derived from along track MPs anddata from geodetic phases Thus any error on the MP is also contained in the MSS There are essentially 4types of additional errors on gridded MSS which are hard to quantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
III362 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III363 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
Page 38
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III37 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III371 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
Page 39
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
IV MYOCEAN PRODUCTS
IV1 Near Real Time Products
The purpose of the NRT DUACS component is the acquisition of altimeter data from various altimeter mis-sions in near-real time (ie within a few days at most) the validation and correction of these altimeter datasets (ie edition and selection update of corrections and homogenization orbit error reduction) in order toproduce each day along-track productsProducts are as follows
Along-track products global and regional (Mediterranean and Black Seas Arctic Ocean and Europeareas)
bull Sea Level Anomaly (NRT-SLA) for each mission with NRT-SLA ephemeris
IV11 Delay of the products
The availability of the products in near real time is three to twelve hours after the measurement for along-track products Those products are delivered every day
IV12 Temporal availibility
The following table presents the available products by mission and by data periodNear real time products
NRT Jason-2 Jason-1 and Jason-1geodetic
Envisat new Cryosat-2
Temporal Time availability ymlowast
ongoingymlowast-20120303 for
repeat track and20120507-ongoing for
geodetic track
ymlowast
2012040820120101
ongoing
NRT-SLA X X X X
lowastym the temporal coverage for NRT products is fluctuating and depends on updates of Delayed Time prod-ucts When DT products are updated (3 to 4 times per year) the oldest NRT products are replaced by thebetter quality DT products so that the 2 series are overlapping on few weeks or few months
IV2 Delayed Time Products
The Delayed Time component of SSALTODUACS system is responsible for the production of processedJason-1 Jason-2 TP Envisat GFO ERS12 and even Geosat data in order to provide a homogeneousinter-calibrated and highly accurate long time series of SLA DT products are more precise than NRT products Two reasons explain this quality difference The firstone is the better intrinsic quality of the POE orbit used in the GDR processing The second reason is that
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in the DT DUACS processing the products can be computed optimally with a centred computation timewindow for OER LWE On the contrary in NRT case future data are not available so the computationtime window is not centred and therefore not optimalAs for NRT products improved altimeter corrections and processing algorithms are used ocean tide modelto correct altimeter data improved methods for orbit error reduction and mapping
Along-Track products global and regional (Mediterranean and Black Seas)
bull Sea Level Anomaly (DT-SLA) for each mission
IV21 Delay of the products
Weekly products are delivered The availability of the products in delayed time is at the best two monthsafter the date of the measurement The product generation needs all the GDR data of all the missions to takeinto account the best corrections as possible The time delay can be longer in the case of a missing mission
IV22 Temporal availibility
The following table presents the available products by mission and by data periodDelayed time SSALTODUACS products
Upd Jason-2 Jason-1new6
Jason-1 GFO Envisatnew6
Envisat ERS-16
ERS-2Topexnew6
Topex
TemporalTimeavailabil-ity
200810ymlowast
200902ymlowast
200204200810
200001200809
201010ymlowast
200210201010
199210200304
200209200510
199209200204
DT-SLA X X X X X X X X X
lowast ym those dates are updated regularly (3 to 4 times per year) and are avalaible when you download thedata at httpwwwmyoceaneuweb24-cataloguephp6 Jason-1 new orbit starting 200809 Envisat new orbit starting 201010 TP new orbit starting 200209 ERS-1The geodetic phases (E-F) are included There are no ERS-1 data between December 23 1993 and April 10 1994(ERS-1 phase D - 2nd ice phase) Note that during that time products are based only on TopexPoseidon data
Page 41
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V DESCRIPTION OF THE PRODUCT SPECIFICATION
V1 General information
Product Specification SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001
Geographical coverage global
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 20-50km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001 Product Specification
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
Product Specification SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002
Geographical coverage 55˚W-35˚E 30˚N-46˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002 Product Specification
Page 43
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Product Specification SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003
Geographical coverage 27˚E-42˚E 40˚N-47˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003 Product Specification
Page 44
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
Product Specification SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004
Geographical coverage 25˚W-42˚E 21˚N-66˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004 Product Specification
Page 45
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
Product Specification SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005
Geographical coverage 0˚W-360˚E 50˚N-82˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005 Product Specification
Page 46
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
VI NOMENCLATURE OF FILES
VI1 Nomenclature of files downloaded through the MyOcean Web PortalDirectgetfile Service
VI11 Nomenclature of the product line
The description of the syntax for the SL TAC SLA products line is given by
SEALEVEL_ltREGIONgt_SLA_L3_ltDELAYgt_OBSERVATIONS_008_ltZONEgt_ltLETTERgtwhere
REGION GLO global geographic coverage product
BS Black Sea products
MED Mediterranean products
ARC Arctic products (for NRT products)
EUROPE Europe products (for NRT products)
DELAY NRT near real time products
RAN delayed time or reanalysis products
ZONE 001 number on 3 digits
002
003
004
LETTER a letter on 1 digit
b
Page 47
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VI12 Nomenclature of the datasets
The nomenclature used is
dataset-duacs-ltdelaygt-ltzonegt-ltmissiongt-lttype of slagt-l3where the fileds in ltgt are described below
delay nrt near-real time productsran delayed time products
zone global global geographic coverage productmedsea Mediterranean productsblacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1 (only for ran)e2 ERS-2 (only for ran)tp TOPEXPoseidon (only for ran)tpn TOPEXPoseidon on its new orbit (only for
ran)g2 GFO (only for ran)j1 Jason-1 (only for ran)j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisat (only for ran)enn Envisat on its new orbitc2 Cryosat-2 (only for nrt)
type of sla sla filtered slasla_unfiltered non filtered sla (only for ran products)
Page 48
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
VI13 Nomenclature of the NetCdf files
The nomenclature used is
ltdelaygt_ltzonegt_ltmissiongt_sla_ltvariablegt_ltdatebegingt_ltdateendgt_ltdateprodgtnc where the fileds in ltgt are de-scribed below
delay nrt near-real time productsdt delayed time products
zone global global geographic coverage productmed Mediterranean products (for dt)mfstep Mediterranean products (for nrt)blacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1e2 ERS-2tp TOPEXPoseidontpn TOPEXPoseidon on its new orbitg2 GFOj1 Jason-1j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisatenn Envisat on its new orbitc2 Cryosat-2
variable vfec filtered and sub-sampled slavxxc non filtered and non sub-sampled sla (only
for dt)datebegin YYYYMMDD() beginning date of the datasetdateend YYYYMMDD() end date of the datasetdateprod YYYYMMDD production date of the dataset
() For dt data as the dates in the file names are rounded the user wanting data for date T has to read the filescontaining dates T+1 and T-1 in their name and check inside the files if there are some data for date T
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
VII DATA FORMAT
This chapter presents the data storage format used for MyOcean products
VII1 NetCdf
The products are stored using the NetCDF format NetCDF (network Common Data Form) is an interface for array-oriented data access and a library that provides an implementation of the interface The netCDF library also definesa machine-independent format for representing scientific data Together the interface library and format support thecreation access and sharing of scientific data The netCDF software was developed at the Unidata Program Center inBoulder Colorado The netCDF libraries define a machine-independent format for representing scientific data Pleasesee Unidata NetCDF pages for more information and to retreive NetCDF software package onhttpwwwunidataucaredupackagesnetcdfindexhtml
NetCDF data is
bull Self-Describing A netCDF file includes information about the data it contains
bull Architecture-independent A netCDF file is represented in a form that can be accessed by computers with dif-ferent ways of storing integers characters and floating-point numbers
bull Direct-access A small subset of a large dataset may be accessed efficiently without first reading through allthe preceding data
bull Appendable Data can be appended to a netCDF dataset along one dimension without copying the dataset orredefining its structure The structure of a netCDF dataset can be changed though this sometimes causes thedataset to be copied
bull Sharable One writer and multiple readers may simultaneously access the same netCDF file
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
VII2 Structure and semantic of NetCDF along-track files
The NetCDF Sea Level TAC files are based on the attribute data tags defined by the Cooperative OceanAtmosphereResearch Data Service (COARDS) and Climate and Forecast (CF) metadata conventions The CF convention gener-alises and extends the COARDS convention but relaxes the COARDS constraints on dimension and order and specifiesmethods for reducing the size of datasetsA wide range of software are available to write or read NetCDFCF files API are made available by UNIDATA(httpwwwunidataucaredusoftwarenetcdf)
bull CC++Fortran
bull Java
bull MATLAB Objective-C Perl Python R Ruby TclTk
In addition to these conventions the files are using a common structure and semantic
bull 1 dimension is defined
ndash time it is used to check NetCDF variables depending on time
bull 8 variables are defined
ndash short SLA contains the Sea Level Anomaly values for each time given
ndash int longitude contains the longitude for each measurement
ndash short track contains the track number for each measurement
ndash double time contains the time in days since 1950-01-01 000000 UTC for each measurement
ndash short mean_profile_point_index index of the corrsponding point in the track of the mean profile
ndash byte flag flag=0 the processed data comes from OGDR if flag=1 the processed data comes from theIGDR
ndash int latitude contains the latitude for each measurement
ndash short cycle contains the cycle number for each measurement
bull global attributes
ndash the global attributes gives information about the creation of the file
Example of a NetCDF sla file
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
netcdf nrt_global_j1_sla_vfec_20101230_20101230_20101230 dimensions
time = 10385 variables
short SLA(time) SLAcoordinates = longitude latitude SLAlong_name = Sea Level Anomaly SLA_FillValue = 32767s SLAadd_offset = 0 SLAscale_factor = 0001 SLAunits = m SLAstandard_name = sea_surface_height_above_sea_level
int longitude(time) longitudelong_name = Longitude of measurement longitude_FillValue = 2147483647 longitudeadd_offset = 0 longitudestandard_name = longitude longitudescale_factor = 1e-06 longitudeunits = degrees_east
short track(time) tracklong_name = Track in cycle the measurement belongs to track_FillValue = 32767s trackunits = 1 trackcoordinates = longitude latitude
double time(time) timelong_name = Time of measurement time_FillValue = 184467440737096e+19 timeaxis = T timestandard_name = time timeunits = days since 1950-01-01 000000 UTC
int latitude(time) latitudelong_name = Latitude of measurement latitude_FillValue = 2147483647 latitudeadd_offset = 0 latitudestandard_name = latitude latitudescale_factor = 1e-06 latitudeunits = degrees_north
short flag(time) flagcoordinates = longitude latitude flag_FillValue = 3267s flaglong_name = data origin flagflag_values = 1s 0s flagflag_meanings = igdr_like non_igdr_like flagcomment = The origin of the data is determined by the types of geophysical datarecords (GDR) used in computation of the SLA 1 for the Interim GDR (IGDR) and0 for Operational GDR (OGDR)
short cycle(time) cyclelong_name = Cycle the measurement belongs to cycle_FillValue = 32767s cycleunits = 1 cyclecoordinates = longitude latitude
global attributeshistory = 22-Feb-2011 155243 CET File created by the SSLATODUACS system version 1001 comment = Produce from ENVISAT Extension Phase satellite altimetry data institution = CLSCNES
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
references = httpwwwavisooceanobscomfileadmindocumentsdatatoolshdbk_duacspdf source = satellite altimetry title = along track Sea Level Anomaly Conventions = CF-14
dataSLA =
7 7 11 10 -2 -22 -39 -41 -30 -13 -3 -5 -16 -26 -32 -35-35 -35 -37 -35 -31 -29 -31 -35 -32 -21 -10 -10 -19 -20 -1-69 -57 -49 -45 -39 -30 -28 -31 -27 -13 -2 -5 -15 -3 1112 3 -7 -10 -14 -15 -22 -31 -37 -32 -17 -10
longitude =74743328 74868400 74993968 75120040 75246616 7537372875501368 75629568 75758320 75887656 76017568 76148080 7627920876388952 76477056 76565456 76654144 76743128 76832400 76921984329429568 329535424 329641792 329748672 329856096 329964032330072512 330181536 330291072 330401184
track =92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 9292 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92113 113 113 113 113 113 113 113 113 113 113 113 113 113113 113 113 113 113 113 113 113 113
time =222780000565705 222780001314719 222780002063733222780002812747 222780003561761 222780004310775 222780005059788222780005808802 222780006557816 22278000730683 222780008055844222780008804858 222780009553872 22278001017805 222780010677393222788257112198 222788257486705 222788257861212 222788258235719222788258610226 222788258984733 222788259359239 222788259733746222788260108253 22278826048276
mean_profile_point_index =1872 1878 1884 1890 1896 1902 1908 19141920 1926 1932 1938 1944 1949 1953 1957 1961 1965 1969 19732306 2309 2312 2315 2318 2321 2327 2330 2333 2336 2339 23422345 2348 2351 2354 2357 2360 2363 2366
flag =0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
latitude =-16225506 -16539731 -16853833 -17167810 -17481660 -17795380-18108966 -18422418 -18735729 -19048899 -19361924 -19674801-19987527 -20248015 -20456329 -20664569 -20872739 -2108083739481297 39628277 39775133 39921866 40068472 40214953 4036130840507533 40653629 40799592 40945423 41091120 41236684 41382111
cycle =331 331 331 331 331 331 331 331 331 331 331 331 331
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331 331 331 331 331 331 331 331 331 331 331 331 331 331331 331 331 331 331 331 331 331 331 331 331 331
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VIII HOW TO DOWNLOAD A PRODUCT
VIII1 Download a product through the MyOcean Web Portal DirectgetfileService
You first need to register Please find below the registration stepshttpwwwmyoceaneuweb34-products-and-services-faqphp1Once registered the MyOcean FAQ httpwwwmyoceaneuweb34-products-and-services-faqwill guide you on How to download a product through the MyOcean Web Portal Directgetfile Service
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IX NEWS AND UPDATES
IX1 [Duacs] Operational news
To be kept informed on events occurring on the satellites and on the eventual interruption of the services of the DUACSprocessing system see the [Duacs] operational news on the Aviso websitehttpwwwavisooceanobscomendataoperational-newsindexhtml
IX2 Updates
To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtmlSince 2010 a complete reprocessing of all altimetry data (cumulated total of about 55 years of data) is available Themain changes introduced in the Duacs DT v300 reprocessed data set in SSALTODUACS reprocessed DT data setare listed herehttpwwwavisooceanobscomfileadmindocumentsdataduacsduacs_DT_2010_reprocessing_impactpdf
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CONTENTS
I Introduction 11
II Updates in 2011 and 2012 14II1 Version D of input IGDROGDR Jason-2 data for NRT processing (July 30 2012) 14II2 Integration of Jason-1 on its geodetic orbit (May 2012) 14II3 Envisat has stopped sending data (April 2012) 15II4 Integration of the Cryosat2 Mission (February 2012) 16
II41 Generalities about the mission 16II42 Integration in DUACS 17
II5 Addition of Europe and Arctic products (January 2012) 18
IIISSALTODUACS system 20III1 Introduction 20III2 Near Real Time processing steps 22
III21 Input data models and corrections applied 22III22 Acquisition 25III23 Homogenization 26III24 Input data quality control 26III25 Multi-mission cross-calibration 27III26 Product generation 28
III261 Computation of raw SLA 28III262 Cross validation 29III263 Filtering and sub-sampling 29
III27 Quality control 30III271 Final quality Control 30III272 Performance indicators 31
III3 Delayed Time processing steps 32III31 Input data models and corrections applied 32III32 Acquisition 35III33 Homogenization 35III34 Input data quality control 35III35 Multi-mission cross-calibration 36III36 Product generation 37
III361 Computation of raw SLA 37III362 Cross validation 38III363 Filtering and sub-sampling 38
III37 Quality control 39III371 Final quality Control 39
IV MyOcean Products 40IV1 Near Real Time Products 40
IV11 Delay of the products 40IV12 Temporal availibility 40
IV2 Delayed Time Products 40IV21 Delay of the products 41IV22 Temporal availibility 41
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V Description of the product specification 42V1 General information 42
VI Nomenclature of files 47VI1 Nomenclature of files downloaded through the MyOcean Web Portal DirectgetfileService 47
VI11 Nomenclature of the product line 47VI12 Nomenclature of the datasets 48VI13 Nomenclature of the NetCdf files 49
VIIData format 50VII1NetCdf 50VII2Structure and semantic of NetCDF along-track files 51
VIIIHow to download a product 55VIII1Download a product through the MyOcean Web Portal Directgetfile Service 55
IX News and Updates 56IX1 [Duacs] Operational news 56IX2 Updates 56
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LIST OF TABLES
1 Characteristics of the geodetic orbit for Jason-1 since May 7th 2012 142 SSALTODUACS Near-Real Time Input data overview 223 Corrections and models applied in SSALTODUACS NRT products produced from IGDRs 234 Corrections and models applied in SSALTODUACS NRT products produced from OG-
DRsFDGDRs 245 SSALTODUACS Delayed Time Input data overview 326 Corrections and models applied in SSALTODUACS DT products (gtv300) (12) 337 Corrections and models applied in SSALTODUACS DT products (gtv300) (22) 34
LIST OF FIGURES
1 DUACS and AVISO a user-driven altimetry service 112 SSH-MSS for Cryosat-2 with LRM mode only (left) or LRM+pseudo-LRM modes (right) 163 Coverage of the Europe product for Jason-1 Jason-2 and Envisat from August 18th to
September 9th 2011 184 Coverage of the Arctic region with Envisat from October 28th 2011 to January 3rd 2012 195 SSALTODUACS processing sequences 216 Overview of the near real time system data flow management 257 Merging pertinent information from IGDR and OGDR processing 268 Example with the key performance indicator on 20090627 31
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LIST OF ACRONYMS
ATP Along-Track ProductADT Absolute Dynamic TopographyAVISO Archiving Validation and Interpretation of Satellite Oceanographic dataBGLO Biais Grande Longueur drsquoOndeCalVal Calibration - ValidationCERSAT Centre ERS drsquoArchivage et de TraitementCMA Centre Multimission Altimetry centerCORSSH CORrected Sea Surface HeightC2 Cryosat-2DAC Dynamic Atmospheric CorrectionDT Delayed TimeDTU Mean Sea Surface computed by Technical University of DanemarkDUACS Data Unification and Altimeter Combination SystemE1 ERS-1E2 ERS-2EN EnvisatENN Envisat on its non repetitive orbit (since cycle 94)ECMWF European Centre for Medium-range Weather ForecastingENACT ENhanced ocean data Assimilation and Climate predictionG2 Geosat Follow OnGIM Global Ionospheric MapsGDR Geophysical Data Record(s)IERS International Earth Rotation ServiceIGDR Interim Geophysical Data Record(s)J1 Jason-1J1N Jason-1 on its new orbit (since cycle 262)J1G Jason-1 on its geodetic orbit (since May 2012)J2 Jason-2JPL Jet Propulsion LaboratoryLAS Live Access ServerLWE Long Wavelength ErrorsMADT Map of Absolute Dynamic TopgraphyMDT Mean Dynamic TopographyMOE Medium Orbit EphemerisMP Mean ProfileMSLA Map of Sea Level AnomalyMSS Mean Sea SurfaceNRT Near-Real TimeOE Orbit ErrorOER Orbit Error ReductionOpendap Open-source Project for a Network Data Access ProtocolPF Polynom FitPODAAC Physical Oceanography Distributed Active Archive CentrePOE Precise Orbit EphemerisRD Reference DocumentSAD Static Auxiliary Data
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SI Signed IntegerSLA Sea Level AnomalySL TAC Sea Level Thematic Assembly CentreSSALTO Ssalto multimission ground segmentSSH Sea Surface HeightTAC Thematic Assembly CentreTP TopexPoseidonTPN TopexPoseidon on its new orbit (since cycle 369)
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REFERENCES
[1] Andersen O B The DTU10 Gravity filed and Mean sea surface (2010) Second international sympo-sium of the gravity field of the Earth (IGFS2) Fairbanks Alaska
[2] Boy F et al (2011) Cryosat LRM TRK and SAR processing Presented at the 2011 Ocean Sur-face Topography Science Team meeting httpwwwavisooceanobscomfileadmindocumentsOSTST2011oral01_Wednesday
[3] Carrere L F Lyard 2003 Modeling the barotropic response of the global ocean to atmo-spheric wind and pressure forcing- comparisons with observations J Geophys Res 30(6) 1275doi1010292002GL016473
[4] Carrere L 2003 Etude et modeacutelisation de la reacuteponse HF de lrsquooceacutean global aux forccedilagesmeacuteteacuteorologiques PhD thesis Universiteacute Paul Sabatier (Toulouse III France) 318 pp
[5] Cartwright D E R J Tayler 1971 New computations of the tide-generating potential Geophys JR Astr Soc 23 45-74
[6] Cartwright D E A C Edden 1973 Corrected tables of tidal harmonics Geophys J R Astr Soc33 253-264
[7] Following the scientific recommendations from the OSTST meeting (San Diego October 2011) theESA Cryosat Project and the CNES SALP Project have been collaborating to generate these Cryosat-derived L3 and L4 products Level 1B and Level 2 products derived from CNES processors are notdistributed by AVISO as per the CNES ESA agreement
[8] Dibarboure G C Renaudie M-I Pujol S Labroue N Picot 2011 A demonstrationof the potential of Cryosat-2 to contribute to mesoscale observation J Adv Space Resdoi101016jasr201107002 httpdxdoiorg101016jasr201107002
[9] Dibarboure G P Schaeffer P Escudier M-IPujol JF Legeais Y Faugegravere R Morrow JK WillisJ Lambin JP Berthias N Picot 2010 Finding desirable orbit options for the Extension of Lifephase of Jason-1 Submitted to Marine Geodesy
[10] Dibarboure G M-IPujol FBriol PYLe Traon GLarnicol NPicot FMertz P Escudier MAblainCDufau 2010 Jason-2 in DUACS first tandem results and impact on processing and products Sub-mitted in Marine Geodesy
[11] Dibarboure G 2009 Using short scale content of OGDR data improve the Near Real Time productsof SsaltoDuacs oral presentation at Seattle OSTST meeting (pdf)
[12] Dorandeu J M Ablain Y Faugegravere F Mertz B Soussi and P Vincent 2004 Jason-1 global statisti-cal evaluation and performance assessment Calibration and cross-calibration results Marine Geodesy27(3-4) 345-372
[13] Dorandeu J M Ablain P-Y Le Traon 2003 Reducing Cross-Track Geoid Gradient Errors aroundTOPEXPoseidon and Jason-1 Nominal Tracks Application to Calculation of Sea Level AnomaliesJ of Atmosph and Ocean Techn20 1826-1838
[14] Dorandeu J and P-Y Le Traon 1999 Effects of global mean atmospheric pressure variations onmean sea level changes from TOPEXPoseidon J Atmos Oceanic Technol 16 1279-1283
[15] Ducet N P-Y Le Traon and G Reverdin 2000 Global high resolution mapping of ocean circulationfrom TOPEXPoseidon and ERS-1 and -2 J Geophys Res 105 19477-19498
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[16] Egbert Gary D Svetlana Y Erofeeva 2002 Efficient Inverse Modeling of Barotropic Ocean Tides JAtmos Oceanic Technol 19 183-204 doi 1011751520-0426(2002)019lt0183EIMOBOgt20CO2
[17] Gaspar P and F Ogor Estimation and analysis of the Sea State Bias of the ERS-1 altimeter Reportof task B1-B2 of IFREMER Contract n˚ 942426 016C 1994
[18] Gaspar P F Ogor and C Escoubes 1996 Nouvelles calibration et analyse du biais drsquoeacutetat de mer desaltimegravetres TOPEX et POSEIDON Technical note 96018 of CNES Contract 951523 1996
[19] Gaspar P and F Ogor Estimation and analysis of the Sea State Bias of the new ERS-1 and ERS-2altimetric data (OPR version 6) Report of task 2 of IFREMER Contract n˚ 962246 002C 1996
[20] Gaspar P S Labroue and F Ogor 2002 Improving nonparametric estimates of the sea state bias inradar altimeter measurements of seal level J Atmos Oceanic Technology 19 1690-1707
[21] Hernandez F P-Y Le Traon and R Morrow 1995 Mapping mesoscale variability of the AzoresCurrent using TOPEXPOSEIDON and ERS-1 altimetry together with hydrographic and Lagrangianmeasurements Journal of Geophysical Research 100 24995-25006
[22] Hernandez F and P Schaeffer 2000 Altimetric Mean Sea Surfaces and Gravity Anomaly maps inter-comparisons AVI-NT-011-5242-CLS 48 pp CLS Ramonville St Agne
[23] Hernandez F M-H Calvez J Dorandeu Y Faugegravere F Mertz and P Schaeffer 2000 Sur-face Moyenne Oceacuteanique Support scientifique agrave la mission altimeacutetrique Jason-1 et agrave une mis-sion micro-satellite altimeacutetrique Contrat SSALTO 2945 - Lot 2 - A1 Rapport drsquoavancementCLSDOSNT00313 40 pp CLS Ramonville St Agne
[24] Iijima BA IL Harris CM Ho UJ Lindqwiste AJ Mannucci X Pi MJ Reyes LC SparksBD Wilson 1999 Automated daily process for global ionospheric total electron content maps andsatellite ocean altimeter ionospheric calibration based on Global Positioning System data J AtmosSolar-Terrestrial Physics 61 16 1205-1218
[25] Labroue S F Boy N Picot M Urvoy M Ablain First quality assessment of the Cryosat-2 altimetricsystem over ocean J Adv Space Res 2011 doi101016jasr201111018 httpdxdoiorg101016jasr201111018
[26] Labroue S 2007 RA2 ocean and MWR measurement long term monitoring 2007 report for WP3Task 2 - SSB estimation for RA2 altimeter Contract 1729303I-OL CLS-DOS-NT-07-198 53ppCLS Ramonville St Agne
[27] Labroue S P Gaspar J Dorandeu OZ Zanifeacute F Mertz P Vincent and D Choquet 2004 Nonparametric estimates of the sea state bias for Jason-1 radar altimeter Marine Geodesy 27 453-481
[28] Lagerloef GSE GMitchum RLukas and PNiiler 1999 Tropical Pacific near-surface currentsestimated from altimeter wind and drifter data J Geophys Res 104 23313-23326
[29] Le Traon P-Y and F Hernandez 1992 Mapping the oceanic mesoscale circulation validation ofsatellite altimetry using surface drifters J Atmos Oceanic Technol 9 687-698
[30] Le Traon P-Y P Gaspar F Bouyssel and H Makhmara 1995 Using TopexPoseidon data to en-hance ERS-1 data J Atmos Oceanic Technol 12 161-170
[31] Le Traon P-Y F Nadal and N Ducet 1998 An improved mapping method of multisatellite altimeterdata J Atmos Oceanic Technol 15 522-534
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[32] Le Traon P-Y and F Ogor 1998 ERS-12 orbit improvement using TOPEXPOSEIDON the 2 cmchallenge J Geophys Res 103 8045-8057
[33] Le Traon P-Y and G Dibarboure 1999 Mesoscale mapping capabilities of multi-satellite altimetermissions J Atmos Oceanic Technol 16 1208-1223
[34] Le Traon P-Y G Dibarboure and N Ducet 2001 Use of a High-Resolution Model to Analyze theMapping Capabilities of Multiple-Altimeter Missions J Atmos Oceanic Technol 18 1277-1288
[35] Le Traon PY and G Dibarboure 2002 Velocity mapping capabilities of present and future altimetermissions the role of high frequency signals J Atmos Oceanic Technol 19 2077-2088
[36] Le Traon PY Faugegravere Y Hernandez F Dorandeu J Mertz F and M Ablain 2002 Can we mergeGEOSAT Follow-On with TOPEXPOSEIDON and ERS-2 for an improved description of the oceancirculation J Atmos Oceanic Technol 20 889-895
[37] Le Traon PY and G Dibarboure 2004 An Illustration of the Contribution of the TOPEXPoseidon-Jason-1 Tandem Mission to Mesoscale Variability Studies Marine Geodesy 27 (1-2)
[38] Mertz F F Mercier S Labroue N Tran J Dorandeu 2005 ERS-2 OPR data quality assessment Long-term monitoring - particular investigation CLSDOSNT-06001 (pdf)
[39] MSS_CNES_CLS11 was produced by CLS Space Oceanography Division and distributed by Avisowith support from Cnes (urlhttpwwwavisooceanobscom)
[40] Pascual A Y Faugegravere G Larnicol P-Y Le Traon 2006 Improved description of the oceanmesoscale variability by combining four satellite altimeters Geophys Res Lett 33
[41] Pascual A C Boone G Larnicol and P-Y Le Traon 2009 On the quality of Real-Time altimetergridded fields comparison with in-situ data Journ of Atm and Ocean Techn Vol 26(3) pp 556-569DOI 1011752008JTECHO5561
[42] Prandi P M Ablain A Cazenave N Picot 2011 A new estimation of mean sea level in the ArcticOcean from satellite altimetry Submitted to Marine Geodesy
[43] Pujol M-I et al 2009 Three-satellite quality level restored in NRT poster at OSTST meeting (pdf)
[44] Ray R 1999 A Global Ocean Tide model from TOPEXPoseidon Altimetry GOT992 NASA TechMemo NASATM-1999-209478 58 pp Goddard Space Flight Center NASA Greenbelt MD USA
[45] Rio M-H and F Hernandez 2003 A Mean Dynamic Topography computed over the worldocean from altimetry in-situ measurements and a geoid model J Geophys Res 109 C12032doi1010292003JC002226
[46] Rio M-H and F Hernandez 2003 High frequency response of wind-driven currents measured bydrifting buoys and altimetry over the world ocean J Geophys Res 108 39-1
[47] Rio M-H 2003 Combinaison de donneacutees in situ altimeacutetriques et gravimeacutetriques pour lrsquoestimationdrsquoune topographie dynamique moyenne globale Ed CLS PhD Thesis University Paul Sabatier(Toulouse III France) 260pp
[48] Scharroo R and P Visser 1998 Precise orbit determination and gravity field improvement for theERS satellites J Geophys Res 103 8113-8127
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[49] Scharroo R J Lillibridge and WHF Smith 2004 Cross-calibration and long-term monitoring ofthe Microwave Radiometers of ERS Topex GFO Jason-1 and Envisat Marine Geodesy 97
[50] Tran N and E Obligis December 2003 Validation of the use of ENVISAT neural algorithms onERS-2 CLSDOSNT03901
[51] Tran N S Labroue S Philipps E Bronner and N Picot 2010 Overview and Update of the SeaState Bias Corrections for the Jason-2 Jason-1 and TOPEX Missions Marine Geodesy accepted
[52] Vincent P Desai SDDorandeu J Ablain M Soussi B Callahan PS and BJ Haines 2003 Jason-1 Geophysical Performance Evaluation Marine Geodesy 26 167-186
[53] Wahr J W 1985 Deformation of the Earth induced by polar motionJ of Geophys Res (Solid Earth)90 9363-9368
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I INTRODUCTION
MyOcean is a European Network project aiming at monitoring analyzing and forecasting the Ocean Ituses satellite and in-situ data to describe the ocean in 3 dimensions and real time More information can befound on httpwwwmyoceaneuorgThe aim of this document is to describe the products delivered by the Sea Level TAC (Thematic AssemblyCentre) which is one of the five TAC of the MyOcean projectThe data produced in the frame of this TAC are generated by the processing system named DUACS (DataUnification and Altimeter Combination System)DUACS is part of the CNES multi-mission ground segment (SSALTO) It processes data from all altimetermissions Cryosat-2 OSTMJason-2 Jason-1 TopexPoseidon Envisat GFO ERS-1amp2 and even GeosatAt this time (May 25th 2012) DUACS is using three different altimeters in near real time Developed and operated by CLS it started as an European Commission Project (Developing Use Of Altime-try for Climate Studies) funded under the European Commission and the Midi-Pyreacuteneacutees regional councilIt has been integrated to the CNES multi-mission ground segment SSALTO in 2001 and it is maintainedupgraded and operated with funding from CNES with shared costs from EU projectsAt the beginning of 2004 DUACS was redefined as the Data Unification Altimeter Combination System
Figure 1 DUACS and AVISO a user-driven altimetry service
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The products lines described in this user manual are the followingSEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005
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The data provided to users have a global coverage (PL SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001)and regional products are also computed over specific areasMediterranean Sea (PL SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002)and Black Sea (PL SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003)Thanks to updates in 2011 and 2012 (see section II) new regional products are now availableEurope (PL SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004)and Arctic (PL SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005)
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II UPDATES IN 2011 AND 2012
This section describes the updates of the SSALTODUACS Near Real Time system that occurred during2011 and 2012 allowing to add new products (Europe and Arctic) the integration of the Cryosat-2 data inthe system the stopping delivery of Envisat data the addition of Jason-1 data on geodetic orbit (j1g)To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtml
II1 Version D of input IGDROGDR Jason-2 data for NRT processing(July 30 2012)
On July 30 2012 the version of Jason-2 IGDROGDR has changed and is now the D version Somecorrections have thus been updated as detailed in tables 3 and 4
II2 Integration of Jason-1 on its geodetic orbit (May 2012)
An anomaly occured on March 3rd 2012 on the Jason-2 mission (see httpwwwavisooceanobscomfractualitesactualitesindexhtmltx_ttnews[tt_news]=1162amptx_ttnews[backPid]=1399ampcHash=d5baeb645e) On April 23rd CNES began to command the satellite into a nadir ori-entation and after some propulsion anomalies CNES and NASA management through the Joint SteeringGroup have directed the Jason-1 Project to then begin a series of maneuvers to place Jason-1 into a neworbit as defined in table 1 After checking the current orbit carefully the operational team determined thata geodetic mission was still possible It was also decided to preserve all remaining fuel for future stationkeeping maneuvers which is mandatory in a geodetic orbit Core payloads were switched ON on May 4thand after some POSEIDON2 radar (PRF) adjustments the mission was resumed on May 7th at 151248UTCBelow are the characteristics of the new orbit which will be maintained as before within +- 1km controlbox at the Equator
Semi major axis 7702437 kmEccentricity 13 to 28 10-4Altitude equator 13240 kmOrbital period 6730s (1h52rsquo10rdquo)Inclination 66042˚Cycle 406 daysSub cycles 39 - 109 - 475 - 1795
days
Table 1 Characteristics of the geodetic orbit for Jason-1 since May 7th 2012
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For this new phase of the Jason-1 mission (called j1g) the cycle numbering will restart at 500 Off-lineproducts will be produced once a day for the IGDR and every 11 days for the GDRrsquos The integration ofJason-1 data in the DUACS system is available since May 25th 2012
II3 Envisat has stopped sending data (April 2012)
Since April 8th 2012 Envisat has stopped sending data to Earth Esarsquos mission control has worked tore-establish contact with the satellite but there has been no reaction from the satellite Thus Esa has de-clared officially the end of mission for Envisat (see httpwwwesaintesaCPSEM1SXSWT1H_index_0html) Therefore no SL TAC NRT data from Envisat can be released since this date
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II4 Integration of the Cryosat2 Mission (February 2012)
Since February 6th 2012 Cryosat-2 mission has been integrated in the DUACS sytem This mission isdedicated to the observation of the floating sea-ice as well as the continental ice sheets but all data acquiredover ocean are valuable for the observation of oceanic circulation and mesoscale variations This majorchange is the result of the long-standing and fruitful partnership between ESA and CNES and a responseto the request from scientific and operational oceanography users [7] The integration of Cryosat-2 impactsthe delivering of Near real time Sea Level Anomalies (SLA)
II41 Generalities about the mission
A Cryosat-2 Processing Prototype (C2P) (described in Boy et al 2011 [2]) has been developed on CNESside to lay the ground for various SAR processing studies The processing chains ingest Level-0 telemetryfiles distributed by ESA and perform the following steps to generate Sea Level Anomalies (SLA) values foreach altimeter measurements
bull Level-1 Decommutation time-tagging and localization of measurements
bull Level-1b Calculation of instrumental corrections and geophysicalmeteorological corrections
bull Level-2 MLE4 waveforms Retracking and calculation of SLA
The prototype processes data almost continuously over ocean either in Low Resolution Mode (LRM) or inthe DopplerSAR mode processed as pseudo-LRM mode allowing to increase the coverage (figure 2)
Figure 2 SSH-MSS for Cryosat-2 with LRM mode only (left) or LRM+pseudo-LRM modes (right)
Although Cryosat-2 raw SSH can be only corrected with GPS-derived ionospheric correction and ECMWFwet troposphere correction validation activities showed (Labroue et al 2011 [25]) that C2P outputs have anaccuracy roughly equivalent to Envisatrsquos Level 2 products if the latter are processed with the same standards
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II42 Integration in DUACS
The Cryosat-2 data are included in the Near Real time process The chain delivers now (for global coverageMediterranean and Black Seas) along track data from Cryosat-2 (SLAs) Note that the products distributedare of Level-3 and donrsquot replace Level-2 products distributed by agenciesThe details of the processing are given in Dibarboure et al 2011 [8]Here we just give an overview the data are computed with the corrections given in section III21 Thefiltering and sub-sampling of SLAs (section III263) are detailed in [8]
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II5 Addition of Europe and Arctic products (January 2012)
Since the MyOcean V2 two new along-track products are computed in Near Real Time intended foraddressing the needs of data assmilation and validation in regional models
bull Following the TAPAS (Tailored Altimeter Product for Assimilation Systems) initiative launched bySL TAC with all the Modeling and Forecasting Centers (MFCs) the Europe regional products (PLSEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004) have been proposed (figure 3) They areavailable in Near Real Time onlyThey are studied to partly fulfil the needs of the Centers with adapted filtering and resolution Thoseparameters have been tuned in order to provide boundary conditions for the Atlantic assimilationmodels They are different from the ones used for Mediterranean and Black Seas products If you needto study the Mediterranean Sea or the Black Sea yoursquod better use the dedicated products describedabove since the processing parameters have been fitted to be adapted to the dynamics of the ocean inthose regions
Figure 3 Coverage of the Europe product for Jason-1 Jason-2 and Envisat from August 18th to September9th 2011
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bull The Arctic along-track products (PL SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005) coverlatitudes between 45 and 82 degrees (figure 4) They are available in Near Real Time only
Figure 4 Coverage of the Arctic region with Envisat from October 28th 2011 to January 3rd 2012
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III SSALTODUACS SYSTEM
III1 Introduction
This chapter presents the input data used by SSALTODUACS system and an overview of the different pro-cessing steps necessary to produce the output dataSSALTODUACS system is made of two components a Near Real Time one (NRT) and a Delayed Time(DT) oneIn NRT the systemrsquos primary objective is to provide operational applications with directly usable high qual-ity altimeter data from all missions availableIn DT it is to maintain a consistent and user-friendly altimeter database using the state-of-the-art recom-mendations from the altimetry communityFollowing figure gives an overview of DUACS system where processing sequences can be divided into 7main steps
bull acquisition
bull homogenization
bull input data quality control
bull multi-mission cross-calibration
bull product generation
bull merging
bull final quality control
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Figure 5 SSALTODUACS processing sequences
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III2 Near Real Time processing steps
III21 Input data models and corrections applied
To produce SLA in near-real time the DUACS system uses two flows based on the same instrumental mea-surements but with a different quality
bull The IGDR that are the latest high-quality altimeter data produced in near-real-time
bull The OGDR that includes real time data (OSTMJason-2 and Jason-1 OSDR) to complete IGDR Thesefast delivery products do not always benefit from precise orbit determination nor from some exter-nal model-based corrections (Dynamic Atmospheric Correction (DAC) Global Ionospheric Maps(GIM))
Integration of OGDR data and the introduction of Jason-2Jason-1 tandem increased the resilience and pre-cision of the system A better restitution of ocean variability is observed especially in high energetic areas
Altimetric product Source Availability Type of orbit
Jason-2 IGDR CNES ~24h CNES MOE GDR-Cuntil 20120730
CNES MOE GDR-Dsince 20120731
OGDR NOAAEUMETSAT ~3 to 5 h
Jason-1 IGDR CNESNASA ~48 h CNES MOE GDR-Dsince 20120507
OGDR CNESNASA ~3 to 12 h
Envisat IGDR ESACNES not deliveredsince 20120408
CNES MOE GDR-Dsince 20120121
FDGDR ESA not deliveredsince 20120408
Cryosat-2 IGDR-like ESACNES ~48 h CNES MOE GDR-D
not delivered
Table 2 SSALTODUACS Near-Real Time Input data overview
See Figure 6 Overview of the near real time system data flow management
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DUACS 2011 NRT product from IGDR1
j2 j1nj1g enn c2Productstandard ref
version C until20120730 and D after
version C version 21 CPP [2]
Orbit CNES MOE GDR-Cuntil 20120730
GDR-D after
CNES MOE GDR-C forj1n and CNES MOE
GDR-D for j1g
CNES MOE GDR-Dfrom 20120121 to
20120408
CNES MOE GDR-D
Ionopheric bi-frequency altimeter range measurements GIM model for cgt64 (Iijima et al1998[24])Dry tropo Model computed from ECMWF Gaussian grids (new S1 and S2 atm tides applied)Wet tropo-sphere
AMR radiometer(enhancement in coastal
regions since20120730)
JMR radiometer MWR radiometer andcorrected from side
lobes
Model computed fromECMWF Gaussian
grids
DAC MOG2D High Resolution forced with ECMWF pressure and wind fields (S1 and S2 wereexcluded) (Carrere and Lyard 2003[3])+ inverse barometer Filtering temporal window is
un-centered (no data in the future)Ocean tide GOT4v8 (S1 and S2 are included) and TPX 072 [16] for Arctic productsPole tide [Wahr 1985 [53]]Solid earthtide
Elastic response to tidal potential [Cartwright and Tayler 1971[5]] [Cartwright andEdden 1973[6]]
Loading tide GOT4v8 (S1 and S2 are included)Sea statebias
Non parametric SSB[Labroue 2004[27]](with cycles J1 1 to 11
using GDR-B standardsuntil 20120730 andderived from Jason-2
after)
Non parametric SSB[Labroue 2004[27]](with cycles 1 to 21
using GDR-Bstandards)
Non parametric SSB[Labroue 2004[27]](with cycles 41 to 60
using GDR-Bstandards)
Same as Jason-2 SSB
Orbit error Global multi-mission crossover minimization (Le Traon and Ogor1998[32])
Long wave-lengh errors
Optimal Interpolation [Le Traon et al 1998[31]]
Intercalibration Reference from cycle20
Mean pro-file (seeIII261)
Computed with cycles11-353 TP data andwith cycles 11-250J1 data referenced[19931999]
TPNJ1N computedwith cycles 369-479TPN data refer-enced [19931999]J1G No MP can beused instead theMSS_CNES_CLS11[39] is used
No Mean Profilecan be used forEnvisat on its neworbit Instead theMSS_CNES_CLS11[39] is used
No Mean Profilecan be used forCryosat-2 Instead theMSS_CNES_CLS11[39] is used
(1) A flag included in the along-track files indicates the source of the production (OGDRFDGDR orIGDR) If flag=0 the processed data comes from OGDRsFDGDRs if flag=1 the processed data comesfrom IGDRs
Table 3 Corrections and models applied in SSALTODUACS NRT products produced from IGDRs
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DUACS 2011 NRT product from OGDR or FDGDR2
j2 j1nj1g ennProduct stan-dard ref
version C until 20120730and D after
version C version 21
Orbit Navigator Extrapolated CNES MOEGDR-D since 20120121
Ionopheric From-dual frequency altimeter range measurements From GIM model fromcycle 65 (Iijima et al1998 [24])
Dry troposphere Model computed from ECMWF Gaussian grids (new S1 and S2 atmospherictides are applied)
Wet tropo-sphere
AMR radiometer(enhancement in coastal
regions since 20120730)
JMR radiometer MWR radiometer andcorrected from side lobes
DAC Inverse Barometer forecastedOcean tide GOT4v8 (S1 and S2 are included) and TPX 072 [16] for Arctic productsPole tide [Wahr 1985 [53]]Solid earth tide Elastic response to tidal potential [Cartwright and Tayler 1971[5]]
[Cartwright and Edden 1973[6]]Loading tide GOT4v8 (S1 and S2 are included)Sea state bias Non parametric SSB
[Labroue 2004[27]] (withcycles J1 1 to 11 usingGDR-B standards until20120730 and derivedfrom Jason-2 after)
Non parametric SSB[Labroue 2004[27]](with cycles 1 to 21 usingGDR-B standards)
Non parametric SSB[Labroue 2004[27]](with cycles 41 to 60using GDR-B standards)
Orbit error Specific filtering of long-wavelength signal3
Long wave-lengh errors
Optimal Interpolation [Le Traon et al 1998[31]]
Intercalibration Reference from cycle 20Mean profile(see III261)
Computed with cycles 11-353 TP data and with cy-cles 11-250 J1 data refer-enced [19931999]
TPNJ1N computedwith cycles 369-479TPN data referenced[19931999] J1G NoMP can be used insteadthe MSS_CNES_CLS11[39] is used
No Mean Profile can beused for Envisat on itsnew orbit Instead theMSS_CNES_CLS11 [39]is used
(2) A flag included in the along-track files indicates the source of the production (OGDRFDGDR orIGDR) If flag=0 the processed data comes from OGDRsFDGDRs if flag=1 the processed data comesfrom IGDRs(3) Specific data processing was applied on long wave-length signal (sectIII23 of the user manual)
Table 4 Corrections and models applied in SSALTODUACS NRT products produced from OG-DRsFDGDRs
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III22 Acquisition
The acquisition process is twofold
bull straightforward retrieval and reformatting of altimeter data and dynamic auxiliary data (pressure andwet troposphere correction grids from ECMWF are provided by Meteo France TEC grids from JPLNRT MOG2D corrections) from external repositories
bull synchronisation process
To be homogenized properly altimeter data sets require various auxiliary data The acquisition softwaredetects downloads and processes incoming data as soon as they are available on remote sites (externaldatabase FTP site) Data are split into passes if necessary If data flows are missing or late the synchroni-sation engine put unusable data in waiting queues and automatically unfreezes them upon reception of themissing auxiliary data This processing step delivers raw data that is to say data that have been dividedinto cycles and passes and ordered chronologicallyFrom SSALTODUACS V80 the acquisition step uses two different data flows in near-real time the OGDRflow (within a few hours) and the IGDR flow (within a few days)For each OGDR input the system checks that no equivalent IGDR entry is available in the data base beforeacquisition for each IGDR input the system checks and delete the equivalent OGDR entry in the data baseThese operations aim to avoid duplicates in SSALTODUACS system
Figure 6 Overview of the near real time system data flow management
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III23 Homogenization
The Homogenization process consists in applying the most recent corrections models and references rec-ommended for altimeter products Each mission is processed separately as its needs depend on the baseinput data The list of corrections and models currently applied is provided in tables 3 and 4 for NRT dataThe system includes SLA filtering to process OGDR data DUACS extract from these data sets the shortscales (space and time) which are useful to better describe the ocean variability in real time and merge thisinformation with a fair description of large scale signals provided by the multi-satellite observation in nearreal time (read IGDR-based DUACS data) Finally an hybrid SLA is computed
Figure 7 Merging pertinent information from IGDR and OGDR processing
III24 Input data quality control
The Input Data Quality Control is a critical process applied to guarantee that DUACS uses only the mostaccurate altimeter data Thanks to the high quality of current missions this process rejects a small percent-age of altimeter measurements but these erroneous data could be the cause of a significant quality lossThe quality control relies on standard raw data editing with quality flags or parameter thresholds but alsoon complex data editing algorithms based on the detection of erroneous artefacts mono and multi-missioncrossover validation and macroscopic statistics to edit out large data flows that do not meet the systemrsquosrequirements
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III25 Multi-mission cross-calibration
The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistentand accurate information It removes any residual orbit error (OE Le Traon and Ogor 1998[32]) or longwavelength error (LWE Le Traon et al 1998[31]) as well as large scale biases and discrepancies betweenvarious data flows
This process is based on two very different algorithms a global multi-mission crossover minimization fororbit error reduction (OER) and Optimal Interpolation (OI) for LWE
Multi-satellite crossover determination is performed on a daily basis All altimeter fields (measurementcorrections and other fields such as bathymetry MSS) are interpolated at crossover locations and datesCrossovers are then appended to the existing crossover database as more altimeter data become availableThis crossover data set is the input of the Orbit Error Reduction (OER) method Using the precision of thereference mission orbit a very accurate orbit error can be estimated This processing step does not concernOGDR dataLWE is mostly due to residual tidal or inverse barometer errors and high frequency ocean signals The OIused for LWE reduction uses precise parameters derived from
bull accurate statistical description of sea level variability
bull localized correlation scales
bull mission-specific noise and precise assumptions on the long wavelength errors to be removed (from arecent analysis of one year of data from each mission)
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III26 Product generation
The product generation process is composed of four steps computation of raw SLA cross-validationfilteringampsub-sampling and generation of by-products
III261 Computation of raw SLA
Since the geoid is not well known yet the SSH cannot be used directly the SSH anomalies are used insteadThey are computed from the difference of the instantaneous SSH - a temporal reference This temporalreference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeattrack analysis cannot be used The errors affecting the SLAs MPs and MSS have different magnitudes andwavelengths The computation of the SLAs and their errors associated are detailed in Dibarboure et al 2010[9]
Use of a Mean ProfileIn the repeat track analysis (when the satellites flies over a repetitive orbit) measurements are re-sampledalong a theoretical ground track (or mean track) associated to each mission Then a Mean Profile (MP) issubtracted from the re-sampled data to obtain SLA The MP is a time average of similarly re-sampled dataover a long period
bull The Mean Profile used for Jason-2 is computed with 10 years of TP (cycles 11 to 353) and 6 years ofJason-1 (cycles 11 to 250)
bull The Mean Profile used from Jason-1 cycle 262 to 374 (where satellites are on interleaved ground-tracks) is computed with 3 years of TP (cycles 369 to 479)
bull No Mean Profile can be used for Envisat on its new orbit (enn) Jason-1 on its geodetic orbit (j1g) norfor Cryosat-2 mission (c2) because there is no repetitive track The MSS must be used instead (seebelow)
Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible
bull Indeed as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide precise cross-track projection andor interpolation schemes are required to avoid errors
bull The mesoscale variability error (which is lt35 cm for MP between 3 to 5 years and lt1cm for WLof 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a prioriknowledge from Sea Level maps derived from previous iterations or from other missions
bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for Envisat since november 2010 and for Cryosat-2 mission (c2)because the satellite is not in a repetitive orbit phase The alternative is to use the MSS instead The griddedMSS is derived from along track MPs and data from geodetic phases Thus any error on the MP is alsocontained in the MSS There are essentially 4 types of additional errors on gridded MSS which are hard toquantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
Note that for the Arctic regional products the DTU10 MSS [1] is taken into account instead of the CLS01MSS Indeed the accuracy of DTU10 compared to CLS01 is further demonstrated by the significant sealevel anomaly variance reduction found over the whole Arctic Ocean as shown in Prandi et al [42]
III262 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III263 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
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III27 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III271 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
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III272 Performance indicators
To appreciate the quality situation of the DUACS system new performance indicators are computed dailyThey aim at evaluate the status of the main processing steps of the system the input data availability theinput data coverage the input data quality and the output product quality These indicators are computed foreach and every currently working satellite and combined to obtain the overall status
Figure 8 Example with the key performance indicator on 20090627
See the description the latest and previous indicators on Aviso websitehttpwwwavisooceanobscomindexphpid=1516
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III3 Delayed Time processing steps
III31 Input data models and corrections applied
Delayed Time MyOcean products are generated
bull from Aviso GDR products for TP Jason-1 Jason-2 and Envisat (GDR-A cycles 1 to 22 GDR-Bcycles 23 to 85 GDR-C from cycle 86)
bull from NOAA GDR for GFO and from CERSAT (IFREMER) OPR for ERS-1 and ERS-2 (phases C(1st 35-day repeat orbit period) phase E and F (geodetic phases) phase G for ERS-1 (last 35-dayrepeat orbit period tandem phase with ERS-2 phase A for ERS-2 (1st 35-day repeat orbit periodtandem phase with ERS-1))
All GDR products are computed with a Precise Orbit Ephemeris (POE) and are delivered within 2 to 3months depending on the mission For several missions an updated orbit is used
bull For ERS-1amp-2 the orbit used is DGME-04 provided by Delft Institute (httpwwwdeostudelftnl)until June 2003
bull For TopexPoseidon the orbit used is GSFC (std0809) for the whole mission
bull For Envisat CNES POE of GDR-C standard is used for the whole mission
bull For the whole GFO mission the orbit used is GSFC (std0809) and when not available NASA POE isused
Altimetric product Source Availability Type of orbit
TopexPoseidon GDR NASACNES - GSFC POE
Jason-1 GDR (GDR-C) CNESNASA ~40 days CNES POE
Jason-2 GDR (GDR-C) CNESNASA ~60 days CNES POE
GFO GDR NOAA - GSFCNASA POE
ERS-1amp2 IFREMERESA - DGME-04
Envisat (GDR-A GDR-B andGDR-C from cycle 86)
ESA ~2 months CNES POE
Table 5 SSALTODUACS Delayed Time Input data overview
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
DU
AC
S20
11D
Tpr
oduc
t(gtV
30
0)j2
j1j1
ntp
tpn
e1e2
ene
nng2
Prod
uct
stan
dard
ref
GD
R-C
OPR
GD
R-A
(Cyc
les
1to
22)
GD
R-B
(cyc
les
23-8
5)
GD
R(N
OA
A)
Orb
itC
nes
POE
GSF
C(I
TR
F20
05G
RA
CE
last
stan
dard
s)
DG
ME
-04
(Sch
arro
oan
dV
isse
r19
98[4
8]C
NE
SPO
E(G
DR
-1st
anda
rds
forc
ycle
s9
to22
GD
R-C
stan
dard
sfr
omcy
cle
23)
GSF
C(I
TR
F20
05
GR
AC
Ela
stst
anda
rds
Iono
pher
icD
ual f
requ
ency
altim
eter
rang
em
easu
rem
ents
Dua
l fre
quen
cyal
timet
erra
nge
mea
sure
men
ts(T
opex
)D
OR
IS(P
OSE
IDO
N)
Ben
t mod
elB
ent m
odel
(cyc
les
1-36
)G
IMm
odem
from
cycl
e37
((Ii
jima
etal
19
98[2
4])
Dua
l-fr
eque
ncy
altim
eter
rang
em
easu
rem
ent(
cycl
e9-
64)a
ndG
IMm
odel
gtcyc
le65
(Iiji
ma
etal
19
99[2
4])c
orre
cted
from
8m
mbi
as
From
GIM
mod
el(I
ijim
aet
al1
998
[24]
)
Dry
trop
o-sp
here
Mod
elco
mpu
ted
from
EC
MW
FG
auss
ian
grid
s(n
ewS1
and
S2at
mos
pher
ictid
esar
eap
plie
d)
Mod
elco
mpu
ted
from
EC
MW
Fre
ctan
gula
rgri
ds(n
ewS1
and
S2at
mos
pher
ictid
esar
ein
clud
ed)
Wet
trop
o-sp
here
JMR
AM
Rra
diom
eter
furt
hert
han
50km
from
the
coas
tsF
rom
EC
MW
Fm
odel
ford
ista
nces
betw
een
10an
d50
km
TM
Rra
diom
eter
(Sch
aroo
etal
20
04[4
9])
MW
RC
orre
ctio
nof
the
drif
ton
the
236
GH
zbr
ight
ness
tem
pera
ture
(Sch
arro
oet
al
2004
[49]
)Neu
ral
Net
wor
kal
gori
thm
(Tra
nan
dO
blig
is
2003
[50]
MW
Rra
diom
eter
furt
hert
han
50km
from
the
coas
tsan
dco
rrec
ted
from
side
lobe
s(f
rom
cycl
e41
)E
CM
WF
mod
elfo
rdis
tanc
esbe
twee
n10
and
50km
GFO
radi
omet
er
DA
CM
OG
2DH
igh
Res
olut
ion
forc
edw
ithE
CM
WF
pres
sure
and
win
gfie
lds
(S1
and
S2w
ere
excl
uded
)+in
vers
eba
rom
eter
com
pute
dfr
omre
ctan
gula
rgri
ds
Tabl
e6
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(1
2)
Page 33
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
j2j1
j1n
tptp
ne1
e2en
enn
g2O
cean
tide
GO
T4v
7(S
1an
dS2
are
incl
uded
)Po
letid
e[W
ahr
1985
[53]
]So
lidea
rth
tide
Ela
stic
resp
onse
totid
alpo
tent
ial[
Car
twri
ghta
ndTa
yler
197
1[5]
][C
artw
righ
tand
Edd
en1
973[
6]]
Loa
ding
tide
GO
T4v
7(S
1pa
ram
eter
isin
clud
ed)
Sea
stat
ebi
asN
onpa
ram
etri
cSS
B[G
aspa
reta
l20
02[2
0]]
Non
para
met
ric
SSB
[NT
ran
and
al2
010[
51]]
BM
3[G
aspa
ran
dO
gor
1994
[17]
]
Non
para
met
ric
SSB
[Mer
tzet
al
2005
[38]
]
Non
para
met
ric
SSB
[Gas
pare
tal
2002
]w
ithG
DR
-Bst
anda
rds
forc
ycle
s9
to85
and
with
GD
R-C
stan
dard
sfr
omcy
cle
86
Non
para
met
ric
SSB
[NT
ran
etal
20
10[5
1]]
Orb
iter
ror
Glo
bal m
ulti-
mis
sion
cros
sove
rmin
imiz
atio
n(L
eTr
aon
and
Ogo
r19
98[3
2])
Lon
gw
ave-
leng
her
rors
Opt
imal
Inte
rpol
atio
n(L
eTr
aon
etal
19
98[3
1])
Inte
rcal
ibra
tion
Ref
eren
cefr
omcy
cle
11R
efer
ence
from
cycl
e1
to35
4C
orre
ctio
nof
regi
onal
bias
J2J
1de
duce
dfr
omin
terc
alib
ratio
nph
ase
(cyc
le11
J2)
Cor
rect
ion
ofgl
obal
biai
sJ1
TP
deacutedu
ced
from
inte
rcal
ibra
tion
phas
e(c
ycle
s11
J1)
Mea
npr
o-fil
e(s
eeII
I36
1)
Com
pute
dw
ithcy
cles
11-3
53T
Pda
taan
dw
ithcy
cles
11-2
50J1
data
ref
eren
ced
[199
319
99]
TP
J1 c
ompu
ted
with
cycl
es11
-353
TP
data
and
with
cycl
es11
-250
J1da
tar
efer
ence
d[1
993
1999
]T
PNJ
1Nc
ompu
ted
with
cycl
es36
9-47
9T
PNda
tar
efer
ence
d[1
993
1999
]
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
ref
eren
ced
[199
319
99]
EN
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
re
fere
nced
[199
319
99]
EN
Nu
seof
MSS
_CN
ES_
CL
S11
[39]
Com
pute
dw
ithcy
cles
37-1
87G
2da
ta
refe
renc
ed[1
993
1999
]
Peri
odof
use
from
cycl
e9
from
cycl
e9
cycl
es1
to48
1cy
cles
15to
43In
clud
ing
E-F
geod
etic
phas
es
cycl
es1
to83
from
cycl
e9
cycl
es37
to22
2
Tabl
e7
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(2
2)
Page 34
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III32 Acquisition
The acqusition process in Delayed time is much simpler than in Near Real time it consists in a synchronisa-tion process of all the auxiliary data required to homogenize propely the altimeter data sets The acquisitionstep uses the GDRs or the OPRs provided by the agencies
III33 Homogenization
The Homogenization process consists in applying the most recent corrections models and references rec-ommended for altimeter products Each mission is processed separately as its needs depend on the baseinput data The list of corrections and models currently applied is provided in tables 6 and 7 for DT data
III34 Input data quality control
The Input Data Quality Control is a critical process applied to guarantee that DUACS uses only the mostaccurate altimeter data Thanks to the high quality of current missions this process rejects a small percent-age of altimeter measurements but these erroneous data could be the cause of a significant quality lossThe quality control relies on standard raw data editing with quality flags or parameter thresholds but alsoon complex data editing algorithms based on the detection of erroneous artefacts mono and multi-missioncrossover validation and macroscopic statistics to edit out large data flows that do not meet the systemrsquosrequirements
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PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III35 Multi-mission cross-calibration
The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistentand accurate information It removes any residual orbit error (OE Le Traon and Ogor 1998[32]) or longwavelength error (LWE Le Traon et al 1998[31]) as well as large scale biases and discrepancies betweenvarious data flows
This process is based on two very different algorithms a global multi-mission crossover minimization fororbit error reduction (OER) and Optimal Interpolation (OI) for LWE
Multi-satellite crossover determination is performed on a daily basis All altimeter fields (measurementcorrections and other fields such as bathymetry MSS) are interpolated at crossover locations and datesCrossovers are then appended to the existing crossover database as more altimeter data become availableThis crossover data set is the input of the Orbit Error Reduction (OER) method Using the precision of thereference mission orbit a very accurate orbit error can be estimated LWE is mostly due to residual tidalor inverse barometer errors and high frequency ocean signals The OI used for LWE reduction uses preciseparameters derived from
bull accurate statistical description of sea level variability
bull localized correlation scales
bull mission-specific noise and precise assumptions on the long wavelength errors to be removed (from arecent analysis of one year of data from each mission)
Page 36
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III36 Product generation
The product generation process is composed of four steps computation of raw SLA cross-validationfilteringampsub-sampling and generation of by-products
III361 Computation of raw SLA
Since the geoid is not well known yet the SSH cannot be used directly the SSH anomalies are used insteadThey are computed from the difference of the instantaneous SSH - a temporal reference This temporalreference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeattrack analysis cannot be used The errors affecting the SLAs MPs and MSS have different magnitudes andwavelengths The computation of the SLAs and their errors associated are detailed in Dibarboure et al 2010[9]
Use of a Mean ProfileIn the repeat track analysis (when the satellites flies over a repetitive orbit) measurements are re-sampledalong a theoretical ground track (or mean track) associated to each mission Then a Mean Profile (MP) issubtracted from the re-sampled data to obtain SLA The MP is a time average of similarly re-sampled dataover a long period
bull The Mean Profile used for TP (cycles 1 to 364) Jason-1 (cycles 1 to 259) and Jason-2 is computedwith 10 years of TP (cycles 11 to 353) and 6 years of Jason-1 (cycles 11 to 250)
bull The Mean Profile used for TP (cycles 368 to 481) and from Jason-1 cycle 262 to 374 (where satellitesare on interleaved ground-tracks) is computed with 3 years of TP (cycles 369 to 479)
bull The Mean Profile used for ERS-1 in its 35 days repetitive orbit mission ERS-2 and Envisat (only forthe first orbit before November 2010) is computed with 8 years of ERS-2 (cycles 1 to 85) and 6 yearsof Envisat (cycles 10 to 72)
bull No Mean Profile can be used for Envisat on its new orbit (enn) Jason-1 on its geodetic orbit (j1g)because there is no repetitive track The MSS must be used instead (see below)
bull The Mean Profile used for GFO is computed with 7 years of GFO cycles 37 to 187
Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible
bull Indeed as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide precise cross-track projection andor interpolation schemes are required to avoid errors
bull The mesoscale variability error (which is lt35 cm for MP between 3 to 5 years and lt1cm for WLof 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a prioriknowledge from Sea Level maps derived from previous iterations or from other missions
Page 37
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for ERS-1 for its 168 days geodetic mission (phases E-F from April1994 to March 1995) or for Envisat since november 2010 because the satellite is not in a repetitive orbitphase The alternative is to use the MSS instead The gridded MSS is derived from along track MPs anddata from geodetic phases Thus any error on the MP is also contained in the MSS There are essentially 4types of additional errors on gridded MSS which are hard to quantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
III362 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III363 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
Page 38
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III37 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III371 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
Page 39
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
IV MYOCEAN PRODUCTS
IV1 Near Real Time Products
The purpose of the NRT DUACS component is the acquisition of altimeter data from various altimeter mis-sions in near-real time (ie within a few days at most) the validation and correction of these altimeter datasets (ie edition and selection update of corrections and homogenization orbit error reduction) in order toproduce each day along-track productsProducts are as follows
Along-track products global and regional (Mediterranean and Black Seas Arctic Ocean and Europeareas)
bull Sea Level Anomaly (NRT-SLA) for each mission with NRT-SLA ephemeris
IV11 Delay of the products
The availability of the products in near real time is three to twelve hours after the measurement for along-track products Those products are delivered every day
IV12 Temporal availibility
The following table presents the available products by mission and by data periodNear real time products
NRT Jason-2 Jason-1 and Jason-1geodetic
Envisat new Cryosat-2
Temporal Time availability ymlowast
ongoingymlowast-20120303 for
repeat track and20120507-ongoing for
geodetic track
ymlowast
2012040820120101
ongoing
NRT-SLA X X X X
lowastym the temporal coverage for NRT products is fluctuating and depends on updates of Delayed Time prod-ucts When DT products are updated (3 to 4 times per year) the oldest NRT products are replaced by thebetter quality DT products so that the 2 series are overlapping on few weeks or few months
IV2 Delayed Time Products
The Delayed Time component of SSALTODUACS system is responsible for the production of processedJason-1 Jason-2 TP Envisat GFO ERS12 and even Geosat data in order to provide a homogeneousinter-calibrated and highly accurate long time series of SLA DT products are more precise than NRT products Two reasons explain this quality difference The firstone is the better intrinsic quality of the POE orbit used in the GDR processing The second reason is that
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in the DT DUACS processing the products can be computed optimally with a centred computation timewindow for OER LWE On the contrary in NRT case future data are not available so the computationtime window is not centred and therefore not optimalAs for NRT products improved altimeter corrections and processing algorithms are used ocean tide modelto correct altimeter data improved methods for orbit error reduction and mapping
Along-Track products global and regional (Mediterranean and Black Seas)
bull Sea Level Anomaly (DT-SLA) for each mission
IV21 Delay of the products
Weekly products are delivered The availability of the products in delayed time is at the best two monthsafter the date of the measurement The product generation needs all the GDR data of all the missions to takeinto account the best corrections as possible The time delay can be longer in the case of a missing mission
IV22 Temporal availibility
The following table presents the available products by mission and by data periodDelayed time SSALTODUACS products
Upd Jason-2 Jason-1new6
Jason-1 GFO Envisatnew6
Envisat ERS-16
ERS-2Topexnew6
Topex
TemporalTimeavailabil-ity
200810ymlowast
200902ymlowast
200204200810
200001200809
201010ymlowast
200210201010
199210200304
200209200510
199209200204
DT-SLA X X X X X X X X X
lowast ym those dates are updated regularly (3 to 4 times per year) and are avalaible when you download thedata at httpwwwmyoceaneuweb24-cataloguephp6 Jason-1 new orbit starting 200809 Envisat new orbit starting 201010 TP new orbit starting 200209 ERS-1The geodetic phases (E-F) are included There are no ERS-1 data between December 23 1993 and April 10 1994(ERS-1 phase D - 2nd ice phase) Note that during that time products are based only on TopexPoseidon data
Page 41
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
V DESCRIPTION OF THE PRODUCT SPECIFICATION
V1 General information
Product Specification SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001
Geographical coverage global
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 20-50km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001 Product Specification
Page 42
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
Product Specification SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002
Geographical coverage 55˚W-35˚E 30˚N-46˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002 Product Specification
Page 43
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
Product Specification SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003
Geographical coverage 27˚E-42˚E 40˚N-47˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003 Product Specification
Page 44
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
Product Specification SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004
Geographical coverage 25˚W-42˚E 21˚N-66˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004 Product Specification
Page 45
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
Product Specification SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005
Geographical coverage 0˚W-360˚E 50˚N-82˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005 Product Specification
Page 46
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
VI NOMENCLATURE OF FILES
VI1 Nomenclature of files downloaded through the MyOcean Web PortalDirectgetfile Service
VI11 Nomenclature of the product line
The description of the syntax for the SL TAC SLA products line is given by
SEALEVEL_ltREGIONgt_SLA_L3_ltDELAYgt_OBSERVATIONS_008_ltZONEgt_ltLETTERgtwhere
REGION GLO global geographic coverage product
BS Black Sea products
MED Mediterranean products
ARC Arctic products (for NRT products)
EUROPE Europe products (for NRT products)
DELAY NRT near real time products
RAN delayed time or reanalysis products
ZONE 001 number on 3 digits
002
003
004
LETTER a letter on 1 digit
b
Page 47
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VI12 Nomenclature of the datasets
The nomenclature used is
dataset-duacs-ltdelaygt-ltzonegt-ltmissiongt-lttype of slagt-l3where the fileds in ltgt are described below
delay nrt near-real time productsran delayed time products
zone global global geographic coverage productmedsea Mediterranean productsblacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1 (only for ran)e2 ERS-2 (only for ran)tp TOPEXPoseidon (only for ran)tpn TOPEXPoseidon on its new orbit (only for
ran)g2 GFO (only for ran)j1 Jason-1 (only for ran)j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisat (only for ran)enn Envisat on its new orbitc2 Cryosat-2 (only for nrt)
type of sla sla filtered slasla_unfiltered non filtered sla (only for ran products)
Page 48
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
VI13 Nomenclature of the NetCdf files
The nomenclature used is
ltdelaygt_ltzonegt_ltmissiongt_sla_ltvariablegt_ltdatebegingt_ltdateendgt_ltdateprodgtnc where the fileds in ltgt are de-scribed below
delay nrt near-real time productsdt delayed time products
zone global global geographic coverage productmed Mediterranean products (for dt)mfstep Mediterranean products (for nrt)blacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1e2 ERS-2tp TOPEXPoseidontpn TOPEXPoseidon on its new orbitg2 GFOj1 Jason-1j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisatenn Envisat on its new orbitc2 Cryosat-2
variable vfec filtered and sub-sampled slavxxc non filtered and non sub-sampled sla (only
for dt)datebegin YYYYMMDD() beginning date of the datasetdateend YYYYMMDD() end date of the datasetdateprod YYYYMMDD production date of the dataset
() For dt data as the dates in the file names are rounded the user wanting data for date T has to read the filescontaining dates T+1 and T-1 in their name and check inside the files if there are some data for date T
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
VII DATA FORMAT
This chapter presents the data storage format used for MyOcean products
VII1 NetCdf
The products are stored using the NetCDF format NetCDF (network Common Data Form) is an interface for array-oriented data access and a library that provides an implementation of the interface The netCDF library also definesa machine-independent format for representing scientific data Together the interface library and format support thecreation access and sharing of scientific data The netCDF software was developed at the Unidata Program Center inBoulder Colorado The netCDF libraries define a machine-independent format for representing scientific data Pleasesee Unidata NetCDF pages for more information and to retreive NetCDF software package onhttpwwwunidataucaredupackagesnetcdfindexhtml
NetCDF data is
bull Self-Describing A netCDF file includes information about the data it contains
bull Architecture-independent A netCDF file is represented in a form that can be accessed by computers with dif-ferent ways of storing integers characters and floating-point numbers
bull Direct-access A small subset of a large dataset may be accessed efficiently without first reading through allthe preceding data
bull Appendable Data can be appended to a netCDF dataset along one dimension without copying the dataset orredefining its structure The structure of a netCDF dataset can be changed though this sometimes causes thedataset to be copied
bull Sharable One writer and multiple readers may simultaneously access the same netCDF file
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
VII2 Structure and semantic of NetCDF along-track files
The NetCDF Sea Level TAC files are based on the attribute data tags defined by the Cooperative OceanAtmosphereResearch Data Service (COARDS) and Climate and Forecast (CF) metadata conventions The CF convention gener-alises and extends the COARDS convention but relaxes the COARDS constraints on dimension and order and specifiesmethods for reducing the size of datasetsA wide range of software are available to write or read NetCDFCF files API are made available by UNIDATA(httpwwwunidataucaredusoftwarenetcdf)
bull CC++Fortran
bull Java
bull MATLAB Objective-C Perl Python R Ruby TclTk
In addition to these conventions the files are using a common structure and semantic
bull 1 dimension is defined
ndash time it is used to check NetCDF variables depending on time
bull 8 variables are defined
ndash short SLA contains the Sea Level Anomaly values for each time given
ndash int longitude contains the longitude for each measurement
ndash short track contains the track number for each measurement
ndash double time contains the time in days since 1950-01-01 000000 UTC for each measurement
ndash short mean_profile_point_index index of the corrsponding point in the track of the mean profile
ndash byte flag flag=0 the processed data comes from OGDR if flag=1 the processed data comes from theIGDR
ndash int latitude contains the latitude for each measurement
ndash short cycle contains the cycle number for each measurement
bull global attributes
ndash the global attributes gives information about the creation of the file
Example of a NetCDF sla file
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
netcdf nrt_global_j1_sla_vfec_20101230_20101230_20101230 dimensions
time = 10385 variables
short SLA(time) SLAcoordinates = longitude latitude SLAlong_name = Sea Level Anomaly SLA_FillValue = 32767s SLAadd_offset = 0 SLAscale_factor = 0001 SLAunits = m SLAstandard_name = sea_surface_height_above_sea_level
int longitude(time) longitudelong_name = Longitude of measurement longitude_FillValue = 2147483647 longitudeadd_offset = 0 longitudestandard_name = longitude longitudescale_factor = 1e-06 longitudeunits = degrees_east
short track(time) tracklong_name = Track in cycle the measurement belongs to track_FillValue = 32767s trackunits = 1 trackcoordinates = longitude latitude
double time(time) timelong_name = Time of measurement time_FillValue = 184467440737096e+19 timeaxis = T timestandard_name = time timeunits = days since 1950-01-01 000000 UTC
int latitude(time) latitudelong_name = Latitude of measurement latitude_FillValue = 2147483647 latitudeadd_offset = 0 latitudestandard_name = latitude latitudescale_factor = 1e-06 latitudeunits = degrees_north
short flag(time) flagcoordinates = longitude latitude flag_FillValue = 3267s flaglong_name = data origin flagflag_values = 1s 0s flagflag_meanings = igdr_like non_igdr_like flagcomment = The origin of the data is determined by the types of geophysical datarecords (GDR) used in computation of the SLA 1 for the Interim GDR (IGDR) and0 for Operational GDR (OGDR)
short cycle(time) cyclelong_name = Cycle the measurement belongs to cycle_FillValue = 32767s cycleunits = 1 cyclecoordinates = longitude latitude
global attributeshistory = 22-Feb-2011 155243 CET File created by the SSLATODUACS system version 1001 comment = Produce from ENVISAT Extension Phase satellite altimetry data institution = CLSCNES
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
references = httpwwwavisooceanobscomfileadmindocumentsdatatoolshdbk_duacspdf source = satellite altimetry title = along track Sea Level Anomaly Conventions = CF-14
dataSLA =
7 7 11 10 -2 -22 -39 -41 -30 -13 -3 -5 -16 -26 -32 -35-35 -35 -37 -35 -31 -29 -31 -35 -32 -21 -10 -10 -19 -20 -1-69 -57 -49 -45 -39 -30 -28 -31 -27 -13 -2 -5 -15 -3 1112 3 -7 -10 -14 -15 -22 -31 -37 -32 -17 -10
longitude =74743328 74868400 74993968 75120040 75246616 7537372875501368 75629568 75758320 75887656 76017568 76148080 7627920876388952 76477056 76565456 76654144 76743128 76832400 76921984329429568 329535424 329641792 329748672 329856096 329964032330072512 330181536 330291072 330401184
track =92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 9292 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92113 113 113 113 113 113 113 113 113 113 113 113 113 113113 113 113 113 113 113 113 113 113
time =222780000565705 222780001314719 222780002063733222780002812747 222780003561761 222780004310775 222780005059788222780005808802 222780006557816 22278000730683 222780008055844222780008804858 222780009553872 22278001017805 222780010677393222788257112198 222788257486705 222788257861212 222788258235719222788258610226 222788258984733 222788259359239 222788259733746222788260108253 22278826048276
mean_profile_point_index =1872 1878 1884 1890 1896 1902 1908 19141920 1926 1932 1938 1944 1949 1953 1957 1961 1965 1969 19732306 2309 2312 2315 2318 2321 2327 2330 2333 2336 2339 23422345 2348 2351 2354 2357 2360 2363 2366
flag =0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
latitude =-16225506 -16539731 -16853833 -17167810 -17481660 -17795380-18108966 -18422418 -18735729 -19048899 -19361924 -19674801-19987527 -20248015 -20456329 -20664569 -20872739 -2108083739481297 39628277 39775133 39921866 40068472 40214953 4036130840507533 40653629 40799592 40945423 41091120 41236684 41382111
cycle =331 331 331 331 331 331 331 331 331 331 331 331 331
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331 331 331 331 331 331 331 331 331 331 331 331 331 331331 331 331 331 331 331 331 331 331 331 331 331
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VIII HOW TO DOWNLOAD A PRODUCT
VIII1 Download a product through the MyOcean Web Portal DirectgetfileService
You first need to register Please find below the registration stepshttpwwwmyoceaneuweb34-products-and-services-faqphp1Once registered the MyOcean FAQ httpwwwmyoceaneuweb34-products-and-services-faqwill guide you on How to download a product through the MyOcean Web Portal Directgetfile Service
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IX NEWS AND UPDATES
IX1 [Duacs] Operational news
To be kept informed on events occurring on the satellites and on the eventual interruption of the services of the DUACSprocessing system see the [Duacs] operational news on the Aviso websitehttpwwwavisooceanobscomendataoperational-newsindexhtml
IX2 Updates
To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtmlSince 2010 a complete reprocessing of all altimetry data (cumulated total of about 55 years of data) is available Themain changes introduced in the Duacs DT v300 reprocessed data set in SSALTODUACS reprocessed DT data setare listed herehttpwwwavisooceanobscomfileadmindocumentsdataduacsduacs_DT_2010_reprocessing_impactpdf
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V Description of the product specification 42V1 General information 42
VI Nomenclature of files 47VI1 Nomenclature of files downloaded through the MyOcean Web Portal DirectgetfileService 47
VI11 Nomenclature of the product line 47VI12 Nomenclature of the datasets 48VI13 Nomenclature of the NetCdf files 49
VIIData format 50VII1NetCdf 50VII2Structure and semantic of NetCDF along-track files 51
VIIIHow to download a product 55VIII1Download a product through the MyOcean Web Portal Directgetfile Service 55
IX News and Updates 56IX1 [Duacs] Operational news 56IX2 Updates 56
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LIST OF TABLES
1 Characteristics of the geodetic orbit for Jason-1 since May 7th 2012 142 SSALTODUACS Near-Real Time Input data overview 223 Corrections and models applied in SSALTODUACS NRT products produced from IGDRs 234 Corrections and models applied in SSALTODUACS NRT products produced from OG-
DRsFDGDRs 245 SSALTODUACS Delayed Time Input data overview 326 Corrections and models applied in SSALTODUACS DT products (gtv300) (12) 337 Corrections and models applied in SSALTODUACS DT products (gtv300) (22) 34
LIST OF FIGURES
1 DUACS and AVISO a user-driven altimetry service 112 SSH-MSS for Cryosat-2 with LRM mode only (left) or LRM+pseudo-LRM modes (right) 163 Coverage of the Europe product for Jason-1 Jason-2 and Envisat from August 18th to
September 9th 2011 184 Coverage of the Arctic region with Envisat from October 28th 2011 to January 3rd 2012 195 SSALTODUACS processing sequences 216 Overview of the near real time system data flow management 257 Merging pertinent information from IGDR and OGDR processing 268 Example with the key performance indicator on 20090627 31
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LIST OF ACRONYMS
ATP Along-Track ProductADT Absolute Dynamic TopographyAVISO Archiving Validation and Interpretation of Satellite Oceanographic dataBGLO Biais Grande Longueur drsquoOndeCalVal Calibration - ValidationCERSAT Centre ERS drsquoArchivage et de TraitementCMA Centre Multimission Altimetry centerCORSSH CORrected Sea Surface HeightC2 Cryosat-2DAC Dynamic Atmospheric CorrectionDT Delayed TimeDTU Mean Sea Surface computed by Technical University of DanemarkDUACS Data Unification and Altimeter Combination SystemE1 ERS-1E2 ERS-2EN EnvisatENN Envisat on its non repetitive orbit (since cycle 94)ECMWF European Centre for Medium-range Weather ForecastingENACT ENhanced ocean data Assimilation and Climate predictionG2 Geosat Follow OnGIM Global Ionospheric MapsGDR Geophysical Data Record(s)IERS International Earth Rotation ServiceIGDR Interim Geophysical Data Record(s)J1 Jason-1J1N Jason-1 on its new orbit (since cycle 262)J1G Jason-1 on its geodetic orbit (since May 2012)J2 Jason-2JPL Jet Propulsion LaboratoryLAS Live Access ServerLWE Long Wavelength ErrorsMADT Map of Absolute Dynamic TopgraphyMDT Mean Dynamic TopographyMOE Medium Orbit EphemerisMP Mean ProfileMSLA Map of Sea Level AnomalyMSS Mean Sea SurfaceNRT Near-Real TimeOE Orbit ErrorOER Orbit Error ReductionOpendap Open-source Project for a Network Data Access ProtocolPF Polynom FitPODAAC Physical Oceanography Distributed Active Archive CentrePOE Precise Orbit EphemerisRD Reference DocumentSAD Static Auxiliary Data
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SI Signed IntegerSLA Sea Level AnomalySL TAC Sea Level Thematic Assembly CentreSSALTO Ssalto multimission ground segmentSSH Sea Surface HeightTAC Thematic Assembly CentreTP TopexPoseidonTPN TopexPoseidon on its new orbit (since cycle 369)
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REFERENCES
[1] Andersen O B The DTU10 Gravity filed and Mean sea surface (2010) Second international sympo-sium of the gravity field of the Earth (IGFS2) Fairbanks Alaska
[2] Boy F et al (2011) Cryosat LRM TRK and SAR processing Presented at the 2011 Ocean Sur-face Topography Science Team meeting httpwwwavisooceanobscomfileadmindocumentsOSTST2011oral01_Wednesday
[3] Carrere L F Lyard 2003 Modeling the barotropic response of the global ocean to atmo-spheric wind and pressure forcing- comparisons with observations J Geophys Res 30(6) 1275doi1010292002GL016473
[4] Carrere L 2003 Etude et modeacutelisation de la reacuteponse HF de lrsquooceacutean global aux forccedilagesmeacuteteacuteorologiques PhD thesis Universiteacute Paul Sabatier (Toulouse III France) 318 pp
[5] Cartwright D E R J Tayler 1971 New computations of the tide-generating potential Geophys JR Astr Soc 23 45-74
[6] Cartwright D E A C Edden 1973 Corrected tables of tidal harmonics Geophys J R Astr Soc33 253-264
[7] Following the scientific recommendations from the OSTST meeting (San Diego October 2011) theESA Cryosat Project and the CNES SALP Project have been collaborating to generate these Cryosat-derived L3 and L4 products Level 1B and Level 2 products derived from CNES processors are notdistributed by AVISO as per the CNES ESA agreement
[8] Dibarboure G C Renaudie M-I Pujol S Labroue N Picot 2011 A demonstrationof the potential of Cryosat-2 to contribute to mesoscale observation J Adv Space Resdoi101016jasr201107002 httpdxdoiorg101016jasr201107002
[9] Dibarboure G P Schaeffer P Escudier M-IPujol JF Legeais Y Faugegravere R Morrow JK WillisJ Lambin JP Berthias N Picot 2010 Finding desirable orbit options for the Extension of Lifephase of Jason-1 Submitted to Marine Geodesy
[10] Dibarboure G M-IPujol FBriol PYLe Traon GLarnicol NPicot FMertz P Escudier MAblainCDufau 2010 Jason-2 in DUACS first tandem results and impact on processing and products Sub-mitted in Marine Geodesy
[11] Dibarboure G 2009 Using short scale content of OGDR data improve the Near Real Time productsof SsaltoDuacs oral presentation at Seattle OSTST meeting (pdf)
[12] Dorandeu J M Ablain Y Faugegravere F Mertz B Soussi and P Vincent 2004 Jason-1 global statisti-cal evaluation and performance assessment Calibration and cross-calibration results Marine Geodesy27(3-4) 345-372
[13] Dorandeu J M Ablain P-Y Le Traon 2003 Reducing Cross-Track Geoid Gradient Errors aroundTOPEXPoseidon and Jason-1 Nominal Tracks Application to Calculation of Sea Level AnomaliesJ of Atmosph and Ocean Techn20 1826-1838
[14] Dorandeu J and P-Y Le Traon 1999 Effects of global mean atmospheric pressure variations onmean sea level changes from TOPEXPoseidon J Atmos Oceanic Technol 16 1279-1283
[15] Ducet N P-Y Le Traon and G Reverdin 2000 Global high resolution mapping of ocean circulationfrom TOPEXPoseidon and ERS-1 and -2 J Geophys Res 105 19477-19498
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[16] Egbert Gary D Svetlana Y Erofeeva 2002 Efficient Inverse Modeling of Barotropic Ocean Tides JAtmos Oceanic Technol 19 183-204 doi 1011751520-0426(2002)019lt0183EIMOBOgt20CO2
[17] Gaspar P and F Ogor Estimation and analysis of the Sea State Bias of the ERS-1 altimeter Reportof task B1-B2 of IFREMER Contract n˚ 942426 016C 1994
[18] Gaspar P F Ogor and C Escoubes 1996 Nouvelles calibration et analyse du biais drsquoeacutetat de mer desaltimegravetres TOPEX et POSEIDON Technical note 96018 of CNES Contract 951523 1996
[19] Gaspar P and F Ogor Estimation and analysis of the Sea State Bias of the new ERS-1 and ERS-2altimetric data (OPR version 6) Report of task 2 of IFREMER Contract n˚ 962246 002C 1996
[20] Gaspar P S Labroue and F Ogor 2002 Improving nonparametric estimates of the sea state bias inradar altimeter measurements of seal level J Atmos Oceanic Technology 19 1690-1707
[21] Hernandez F P-Y Le Traon and R Morrow 1995 Mapping mesoscale variability of the AzoresCurrent using TOPEXPOSEIDON and ERS-1 altimetry together with hydrographic and Lagrangianmeasurements Journal of Geophysical Research 100 24995-25006
[22] Hernandez F and P Schaeffer 2000 Altimetric Mean Sea Surfaces and Gravity Anomaly maps inter-comparisons AVI-NT-011-5242-CLS 48 pp CLS Ramonville St Agne
[23] Hernandez F M-H Calvez J Dorandeu Y Faugegravere F Mertz and P Schaeffer 2000 Sur-face Moyenne Oceacuteanique Support scientifique agrave la mission altimeacutetrique Jason-1 et agrave une mis-sion micro-satellite altimeacutetrique Contrat SSALTO 2945 - Lot 2 - A1 Rapport drsquoavancementCLSDOSNT00313 40 pp CLS Ramonville St Agne
[24] Iijima BA IL Harris CM Ho UJ Lindqwiste AJ Mannucci X Pi MJ Reyes LC SparksBD Wilson 1999 Automated daily process for global ionospheric total electron content maps andsatellite ocean altimeter ionospheric calibration based on Global Positioning System data J AtmosSolar-Terrestrial Physics 61 16 1205-1218
[25] Labroue S F Boy N Picot M Urvoy M Ablain First quality assessment of the Cryosat-2 altimetricsystem over ocean J Adv Space Res 2011 doi101016jasr201111018 httpdxdoiorg101016jasr201111018
[26] Labroue S 2007 RA2 ocean and MWR measurement long term monitoring 2007 report for WP3Task 2 - SSB estimation for RA2 altimeter Contract 1729303I-OL CLS-DOS-NT-07-198 53ppCLS Ramonville St Agne
[27] Labroue S P Gaspar J Dorandeu OZ Zanifeacute F Mertz P Vincent and D Choquet 2004 Nonparametric estimates of the sea state bias for Jason-1 radar altimeter Marine Geodesy 27 453-481
[28] Lagerloef GSE GMitchum RLukas and PNiiler 1999 Tropical Pacific near-surface currentsestimated from altimeter wind and drifter data J Geophys Res 104 23313-23326
[29] Le Traon P-Y and F Hernandez 1992 Mapping the oceanic mesoscale circulation validation ofsatellite altimetry using surface drifters J Atmos Oceanic Technol 9 687-698
[30] Le Traon P-Y P Gaspar F Bouyssel and H Makhmara 1995 Using TopexPoseidon data to en-hance ERS-1 data J Atmos Oceanic Technol 12 161-170
[31] Le Traon P-Y F Nadal and N Ducet 1998 An improved mapping method of multisatellite altimeterdata J Atmos Oceanic Technol 15 522-534
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[32] Le Traon P-Y and F Ogor 1998 ERS-12 orbit improvement using TOPEXPOSEIDON the 2 cmchallenge J Geophys Res 103 8045-8057
[33] Le Traon P-Y and G Dibarboure 1999 Mesoscale mapping capabilities of multi-satellite altimetermissions J Atmos Oceanic Technol 16 1208-1223
[34] Le Traon P-Y G Dibarboure and N Ducet 2001 Use of a High-Resolution Model to Analyze theMapping Capabilities of Multiple-Altimeter Missions J Atmos Oceanic Technol 18 1277-1288
[35] Le Traon PY and G Dibarboure 2002 Velocity mapping capabilities of present and future altimetermissions the role of high frequency signals J Atmos Oceanic Technol 19 2077-2088
[36] Le Traon PY Faugegravere Y Hernandez F Dorandeu J Mertz F and M Ablain 2002 Can we mergeGEOSAT Follow-On with TOPEXPOSEIDON and ERS-2 for an improved description of the oceancirculation J Atmos Oceanic Technol 20 889-895
[37] Le Traon PY and G Dibarboure 2004 An Illustration of the Contribution of the TOPEXPoseidon-Jason-1 Tandem Mission to Mesoscale Variability Studies Marine Geodesy 27 (1-2)
[38] Mertz F F Mercier S Labroue N Tran J Dorandeu 2005 ERS-2 OPR data quality assessment Long-term monitoring - particular investigation CLSDOSNT-06001 (pdf)
[39] MSS_CNES_CLS11 was produced by CLS Space Oceanography Division and distributed by Avisowith support from Cnes (urlhttpwwwavisooceanobscom)
[40] Pascual A Y Faugegravere G Larnicol P-Y Le Traon 2006 Improved description of the oceanmesoscale variability by combining four satellite altimeters Geophys Res Lett 33
[41] Pascual A C Boone G Larnicol and P-Y Le Traon 2009 On the quality of Real-Time altimetergridded fields comparison with in-situ data Journ of Atm and Ocean Techn Vol 26(3) pp 556-569DOI 1011752008JTECHO5561
[42] Prandi P M Ablain A Cazenave N Picot 2011 A new estimation of mean sea level in the ArcticOcean from satellite altimetry Submitted to Marine Geodesy
[43] Pujol M-I et al 2009 Three-satellite quality level restored in NRT poster at OSTST meeting (pdf)
[44] Ray R 1999 A Global Ocean Tide model from TOPEXPoseidon Altimetry GOT992 NASA TechMemo NASATM-1999-209478 58 pp Goddard Space Flight Center NASA Greenbelt MD USA
[45] Rio M-H and F Hernandez 2003 A Mean Dynamic Topography computed over the worldocean from altimetry in-situ measurements and a geoid model J Geophys Res 109 C12032doi1010292003JC002226
[46] Rio M-H and F Hernandez 2003 High frequency response of wind-driven currents measured bydrifting buoys and altimetry over the world ocean J Geophys Res 108 39-1
[47] Rio M-H 2003 Combinaison de donneacutees in situ altimeacutetriques et gravimeacutetriques pour lrsquoestimationdrsquoune topographie dynamique moyenne globale Ed CLS PhD Thesis University Paul Sabatier(Toulouse III France) 260pp
[48] Scharroo R and P Visser 1998 Precise orbit determination and gravity field improvement for theERS satellites J Geophys Res 103 8113-8127
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[49] Scharroo R J Lillibridge and WHF Smith 2004 Cross-calibration and long-term monitoring ofthe Microwave Radiometers of ERS Topex GFO Jason-1 and Envisat Marine Geodesy 97
[50] Tran N and E Obligis December 2003 Validation of the use of ENVISAT neural algorithms onERS-2 CLSDOSNT03901
[51] Tran N S Labroue S Philipps E Bronner and N Picot 2010 Overview and Update of the SeaState Bias Corrections for the Jason-2 Jason-1 and TOPEX Missions Marine Geodesy accepted
[52] Vincent P Desai SDDorandeu J Ablain M Soussi B Callahan PS and BJ Haines 2003 Jason-1 Geophysical Performance Evaluation Marine Geodesy 26 167-186
[53] Wahr J W 1985 Deformation of the Earth induced by polar motionJ of Geophys Res (Solid Earth)90 9363-9368
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I INTRODUCTION
MyOcean is a European Network project aiming at monitoring analyzing and forecasting the Ocean Ituses satellite and in-situ data to describe the ocean in 3 dimensions and real time More information can befound on httpwwwmyoceaneuorgThe aim of this document is to describe the products delivered by the Sea Level TAC (Thematic AssemblyCentre) which is one of the five TAC of the MyOcean projectThe data produced in the frame of this TAC are generated by the processing system named DUACS (DataUnification and Altimeter Combination System)DUACS is part of the CNES multi-mission ground segment (SSALTO) It processes data from all altimetermissions Cryosat-2 OSTMJason-2 Jason-1 TopexPoseidon Envisat GFO ERS-1amp2 and even GeosatAt this time (May 25th 2012) DUACS is using three different altimeters in near real time Developed and operated by CLS it started as an European Commission Project (Developing Use Of Altime-try for Climate Studies) funded under the European Commission and the Midi-Pyreacuteneacutees regional councilIt has been integrated to the CNES multi-mission ground segment SSALTO in 2001 and it is maintainedupgraded and operated with funding from CNES with shared costs from EU projectsAt the beginning of 2004 DUACS was redefined as the Data Unification Altimeter Combination System
Figure 1 DUACS and AVISO a user-driven altimetry service
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The products lines described in this user manual are the followingSEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005
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The data provided to users have a global coverage (PL SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001)and regional products are also computed over specific areasMediterranean Sea (PL SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002)and Black Sea (PL SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003)Thanks to updates in 2011 and 2012 (see section II) new regional products are now availableEurope (PL SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004)and Arctic (PL SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005)
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II UPDATES IN 2011 AND 2012
This section describes the updates of the SSALTODUACS Near Real Time system that occurred during2011 and 2012 allowing to add new products (Europe and Arctic) the integration of the Cryosat-2 data inthe system the stopping delivery of Envisat data the addition of Jason-1 data on geodetic orbit (j1g)To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtml
II1 Version D of input IGDROGDR Jason-2 data for NRT processing(July 30 2012)
On July 30 2012 the version of Jason-2 IGDROGDR has changed and is now the D version Somecorrections have thus been updated as detailed in tables 3 and 4
II2 Integration of Jason-1 on its geodetic orbit (May 2012)
An anomaly occured on March 3rd 2012 on the Jason-2 mission (see httpwwwavisooceanobscomfractualitesactualitesindexhtmltx_ttnews[tt_news]=1162amptx_ttnews[backPid]=1399ampcHash=d5baeb645e) On April 23rd CNES began to command the satellite into a nadir ori-entation and after some propulsion anomalies CNES and NASA management through the Joint SteeringGroup have directed the Jason-1 Project to then begin a series of maneuvers to place Jason-1 into a neworbit as defined in table 1 After checking the current orbit carefully the operational team determined thata geodetic mission was still possible It was also decided to preserve all remaining fuel for future stationkeeping maneuvers which is mandatory in a geodetic orbit Core payloads were switched ON on May 4thand after some POSEIDON2 radar (PRF) adjustments the mission was resumed on May 7th at 151248UTCBelow are the characteristics of the new orbit which will be maintained as before within +- 1km controlbox at the Equator
Semi major axis 7702437 kmEccentricity 13 to 28 10-4Altitude equator 13240 kmOrbital period 6730s (1h52rsquo10rdquo)Inclination 66042˚Cycle 406 daysSub cycles 39 - 109 - 475 - 1795
days
Table 1 Characteristics of the geodetic orbit for Jason-1 since May 7th 2012
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For this new phase of the Jason-1 mission (called j1g) the cycle numbering will restart at 500 Off-lineproducts will be produced once a day for the IGDR and every 11 days for the GDRrsquos The integration ofJason-1 data in the DUACS system is available since May 25th 2012
II3 Envisat has stopped sending data (April 2012)
Since April 8th 2012 Envisat has stopped sending data to Earth Esarsquos mission control has worked tore-establish contact with the satellite but there has been no reaction from the satellite Thus Esa has de-clared officially the end of mission for Envisat (see httpwwwesaintesaCPSEM1SXSWT1H_index_0html) Therefore no SL TAC NRT data from Envisat can be released since this date
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II4 Integration of the Cryosat2 Mission (February 2012)
Since February 6th 2012 Cryosat-2 mission has been integrated in the DUACS sytem This mission isdedicated to the observation of the floating sea-ice as well as the continental ice sheets but all data acquiredover ocean are valuable for the observation of oceanic circulation and mesoscale variations This majorchange is the result of the long-standing and fruitful partnership between ESA and CNES and a responseto the request from scientific and operational oceanography users [7] The integration of Cryosat-2 impactsthe delivering of Near real time Sea Level Anomalies (SLA)
II41 Generalities about the mission
A Cryosat-2 Processing Prototype (C2P) (described in Boy et al 2011 [2]) has been developed on CNESside to lay the ground for various SAR processing studies The processing chains ingest Level-0 telemetryfiles distributed by ESA and perform the following steps to generate Sea Level Anomalies (SLA) values foreach altimeter measurements
bull Level-1 Decommutation time-tagging and localization of measurements
bull Level-1b Calculation of instrumental corrections and geophysicalmeteorological corrections
bull Level-2 MLE4 waveforms Retracking and calculation of SLA
The prototype processes data almost continuously over ocean either in Low Resolution Mode (LRM) or inthe DopplerSAR mode processed as pseudo-LRM mode allowing to increase the coverage (figure 2)
Figure 2 SSH-MSS for Cryosat-2 with LRM mode only (left) or LRM+pseudo-LRM modes (right)
Although Cryosat-2 raw SSH can be only corrected with GPS-derived ionospheric correction and ECMWFwet troposphere correction validation activities showed (Labroue et al 2011 [25]) that C2P outputs have anaccuracy roughly equivalent to Envisatrsquos Level 2 products if the latter are processed with the same standards
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II42 Integration in DUACS
The Cryosat-2 data are included in the Near Real time process The chain delivers now (for global coverageMediterranean and Black Seas) along track data from Cryosat-2 (SLAs) Note that the products distributedare of Level-3 and donrsquot replace Level-2 products distributed by agenciesThe details of the processing are given in Dibarboure et al 2011 [8]Here we just give an overview the data are computed with the corrections given in section III21 Thefiltering and sub-sampling of SLAs (section III263) are detailed in [8]
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II5 Addition of Europe and Arctic products (January 2012)
Since the MyOcean V2 two new along-track products are computed in Near Real Time intended foraddressing the needs of data assmilation and validation in regional models
bull Following the TAPAS (Tailored Altimeter Product for Assimilation Systems) initiative launched bySL TAC with all the Modeling and Forecasting Centers (MFCs) the Europe regional products (PLSEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004) have been proposed (figure 3) They areavailable in Near Real Time onlyThey are studied to partly fulfil the needs of the Centers with adapted filtering and resolution Thoseparameters have been tuned in order to provide boundary conditions for the Atlantic assimilationmodels They are different from the ones used for Mediterranean and Black Seas products If you needto study the Mediterranean Sea or the Black Sea yoursquod better use the dedicated products describedabove since the processing parameters have been fitted to be adapted to the dynamics of the ocean inthose regions
Figure 3 Coverage of the Europe product for Jason-1 Jason-2 and Envisat from August 18th to September9th 2011
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bull The Arctic along-track products (PL SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005) coverlatitudes between 45 and 82 degrees (figure 4) They are available in Near Real Time only
Figure 4 Coverage of the Arctic region with Envisat from October 28th 2011 to January 3rd 2012
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III SSALTODUACS SYSTEM
III1 Introduction
This chapter presents the input data used by SSALTODUACS system and an overview of the different pro-cessing steps necessary to produce the output dataSSALTODUACS system is made of two components a Near Real Time one (NRT) and a Delayed Time(DT) oneIn NRT the systemrsquos primary objective is to provide operational applications with directly usable high qual-ity altimeter data from all missions availableIn DT it is to maintain a consistent and user-friendly altimeter database using the state-of-the-art recom-mendations from the altimetry communityFollowing figure gives an overview of DUACS system where processing sequences can be divided into 7main steps
bull acquisition
bull homogenization
bull input data quality control
bull multi-mission cross-calibration
bull product generation
bull merging
bull final quality control
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Figure 5 SSALTODUACS processing sequences
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III2 Near Real Time processing steps
III21 Input data models and corrections applied
To produce SLA in near-real time the DUACS system uses two flows based on the same instrumental mea-surements but with a different quality
bull The IGDR that are the latest high-quality altimeter data produced in near-real-time
bull The OGDR that includes real time data (OSTMJason-2 and Jason-1 OSDR) to complete IGDR Thesefast delivery products do not always benefit from precise orbit determination nor from some exter-nal model-based corrections (Dynamic Atmospheric Correction (DAC) Global Ionospheric Maps(GIM))
Integration of OGDR data and the introduction of Jason-2Jason-1 tandem increased the resilience and pre-cision of the system A better restitution of ocean variability is observed especially in high energetic areas
Altimetric product Source Availability Type of orbit
Jason-2 IGDR CNES ~24h CNES MOE GDR-Cuntil 20120730
CNES MOE GDR-Dsince 20120731
OGDR NOAAEUMETSAT ~3 to 5 h
Jason-1 IGDR CNESNASA ~48 h CNES MOE GDR-Dsince 20120507
OGDR CNESNASA ~3 to 12 h
Envisat IGDR ESACNES not deliveredsince 20120408
CNES MOE GDR-Dsince 20120121
FDGDR ESA not deliveredsince 20120408
Cryosat-2 IGDR-like ESACNES ~48 h CNES MOE GDR-D
not delivered
Table 2 SSALTODUACS Near-Real Time Input data overview
See Figure 6 Overview of the near real time system data flow management
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DUACS 2011 NRT product from IGDR1
j2 j1nj1g enn c2Productstandard ref
version C until20120730 and D after
version C version 21 CPP [2]
Orbit CNES MOE GDR-Cuntil 20120730
GDR-D after
CNES MOE GDR-C forj1n and CNES MOE
GDR-D for j1g
CNES MOE GDR-Dfrom 20120121 to
20120408
CNES MOE GDR-D
Ionopheric bi-frequency altimeter range measurements GIM model for cgt64 (Iijima et al1998[24])Dry tropo Model computed from ECMWF Gaussian grids (new S1 and S2 atm tides applied)Wet tropo-sphere
AMR radiometer(enhancement in coastal
regions since20120730)
JMR radiometer MWR radiometer andcorrected from side
lobes
Model computed fromECMWF Gaussian
grids
DAC MOG2D High Resolution forced with ECMWF pressure and wind fields (S1 and S2 wereexcluded) (Carrere and Lyard 2003[3])+ inverse barometer Filtering temporal window is
un-centered (no data in the future)Ocean tide GOT4v8 (S1 and S2 are included) and TPX 072 [16] for Arctic productsPole tide [Wahr 1985 [53]]Solid earthtide
Elastic response to tidal potential [Cartwright and Tayler 1971[5]] [Cartwright andEdden 1973[6]]
Loading tide GOT4v8 (S1 and S2 are included)Sea statebias
Non parametric SSB[Labroue 2004[27]](with cycles J1 1 to 11
using GDR-B standardsuntil 20120730 andderived from Jason-2
after)
Non parametric SSB[Labroue 2004[27]](with cycles 1 to 21
using GDR-Bstandards)
Non parametric SSB[Labroue 2004[27]](with cycles 41 to 60
using GDR-Bstandards)
Same as Jason-2 SSB
Orbit error Global multi-mission crossover minimization (Le Traon and Ogor1998[32])
Long wave-lengh errors
Optimal Interpolation [Le Traon et al 1998[31]]
Intercalibration Reference from cycle20
Mean pro-file (seeIII261)
Computed with cycles11-353 TP data andwith cycles 11-250J1 data referenced[19931999]
TPNJ1N computedwith cycles 369-479TPN data refer-enced [19931999]J1G No MP can beused instead theMSS_CNES_CLS11[39] is used
No Mean Profilecan be used forEnvisat on its neworbit Instead theMSS_CNES_CLS11[39] is used
No Mean Profilecan be used forCryosat-2 Instead theMSS_CNES_CLS11[39] is used
(1) A flag included in the along-track files indicates the source of the production (OGDRFDGDR orIGDR) If flag=0 the processed data comes from OGDRsFDGDRs if flag=1 the processed data comesfrom IGDRs
Table 3 Corrections and models applied in SSALTODUACS NRT products produced from IGDRs
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DUACS 2011 NRT product from OGDR or FDGDR2
j2 j1nj1g ennProduct stan-dard ref
version C until 20120730and D after
version C version 21
Orbit Navigator Extrapolated CNES MOEGDR-D since 20120121
Ionopheric From-dual frequency altimeter range measurements From GIM model fromcycle 65 (Iijima et al1998 [24])
Dry troposphere Model computed from ECMWF Gaussian grids (new S1 and S2 atmospherictides are applied)
Wet tropo-sphere
AMR radiometer(enhancement in coastal
regions since 20120730)
JMR radiometer MWR radiometer andcorrected from side lobes
DAC Inverse Barometer forecastedOcean tide GOT4v8 (S1 and S2 are included) and TPX 072 [16] for Arctic productsPole tide [Wahr 1985 [53]]Solid earth tide Elastic response to tidal potential [Cartwright and Tayler 1971[5]]
[Cartwright and Edden 1973[6]]Loading tide GOT4v8 (S1 and S2 are included)Sea state bias Non parametric SSB
[Labroue 2004[27]] (withcycles J1 1 to 11 usingGDR-B standards until20120730 and derivedfrom Jason-2 after)
Non parametric SSB[Labroue 2004[27]](with cycles 1 to 21 usingGDR-B standards)
Non parametric SSB[Labroue 2004[27]](with cycles 41 to 60using GDR-B standards)
Orbit error Specific filtering of long-wavelength signal3
Long wave-lengh errors
Optimal Interpolation [Le Traon et al 1998[31]]
Intercalibration Reference from cycle 20Mean profile(see III261)
Computed with cycles 11-353 TP data and with cy-cles 11-250 J1 data refer-enced [19931999]
TPNJ1N computedwith cycles 369-479TPN data referenced[19931999] J1G NoMP can be used insteadthe MSS_CNES_CLS11[39] is used
No Mean Profile can beused for Envisat on itsnew orbit Instead theMSS_CNES_CLS11 [39]is used
(2) A flag included in the along-track files indicates the source of the production (OGDRFDGDR orIGDR) If flag=0 the processed data comes from OGDRsFDGDRs if flag=1 the processed data comesfrom IGDRs(3) Specific data processing was applied on long wave-length signal (sectIII23 of the user manual)
Table 4 Corrections and models applied in SSALTODUACS NRT products produced from OG-DRsFDGDRs
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III22 Acquisition
The acquisition process is twofold
bull straightforward retrieval and reformatting of altimeter data and dynamic auxiliary data (pressure andwet troposphere correction grids from ECMWF are provided by Meteo France TEC grids from JPLNRT MOG2D corrections) from external repositories
bull synchronisation process
To be homogenized properly altimeter data sets require various auxiliary data The acquisition softwaredetects downloads and processes incoming data as soon as they are available on remote sites (externaldatabase FTP site) Data are split into passes if necessary If data flows are missing or late the synchroni-sation engine put unusable data in waiting queues and automatically unfreezes them upon reception of themissing auxiliary data This processing step delivers raw data that is to say data that have been dividedinto cycles and passes and ordered chronologicallyFrom SSALTODUACS V80 the acquisition step uses two different data flows in near-real time the OGDRflow (within a few hours) and the IGDR flow (within a few days)For each OGDR input the system checks that no equivalent IGDR entry is available in the data base beforeacquisition for each IGDR input the system checks and delete the equivalent OGDR entry in the data baseThese operations aim to avoid duplicates in SSALTODUACS system
Figure 6 Overview of the near real time system data flow management
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III23 Homogenization
The Homogenization process consists in applying the most recent corrections models and references rec-ommended for altimeter products Each mission is processed separately as its needs depend on the baseinput data The list of corrections and models currently applied is provided in tables 3 and 4 for NRT dataThe system includes SLA filtering to process OGDR data DUACS extract from these data sets the shortscales (space and time) which are useful to better describe the ocean variability in real time and merge thisinformation with a fair description of large scale signals provided by the multi-satellite observation in nearreal time (read IGDR-based DUACS data) Finally an hybrid SLA is computed
Figure 7 Merging pertinent information from IGDR and OGDR processing
III24 Input data quality control
The Input Data Quality Control is a critical process applied to guarantee that DUACS uses only the mostaccurate altimeter data Thanks to the high quality of current missions this process rejects a small percent-age of altimeter measurements but these erroneous data could be the cause of a significant quality lossThe quality control relies on standard raw data editing with quality flags or parameter thresholds but alsoon complex data editing algorithms based on the detection of erroneous artefacts mono and multi-missioncrossover validation and macroscopic statistics to edit out large data flows that do not meet the systemrsquosrequirements
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III25 Multi-mission cross-calibration
The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistentand accurate information It removes any residual orbit error (OE Le Traon and Ogor 1998[32]) or longwavelength error (LWE Le Traon et al 1998[31]) as well as large scale biases and discrepancies betweenvarious data flows
This process is based on two very different algorithms a global multi-mission crossover minimization fororbit error reduction (OER) and Optimal Interpolation (OI) for LWE
Multi-satellite crossover determination is performed on a daily basis All altimeter fields (measurementcorrections and other fields such as bathymetry MSS) are interpolated at crossover locations and datesCrossovers are then appended to the existing crossover database as more altimeter data become availableThis crossover data set is the input of the Orbit Error Reduction (OER) method Using the precision of thereference mission orbit a very accurate orbit error can be estimated This processing step does not concernOGDR dataLWE is mostly due to residual tidal or inverse barometer errors and high frequency ocean signals The OIused for LWE reduction uses precise parameters derived from
bull accurate statistical description of sea level variability
bull localized correlation scales
bull mission-specific noise and precise assumptions on the long wavelength errors to be removed (from arecent analysis of one year of data from each mission)
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III26 Product generation
The product generation process is composed of four steps computation of raw SLA cross-validationfilteringampsub-sampling and generation of by-products
III261 Computation of raw SLA
Since the geoid is not well known yet the SSH cannot be used directly the SSH anomalies are used insteadThey are computed from the difference of the instantaneous SSH - a temporal reference This temporalreference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeattrack analysis cannot be used The errors affecting the SLAs MPs and MSS have different magnitudes andwavelengths The computation of the SLAs and their errors associated are detailed in Dibarboure et al 2010[9]
Use of a Mean ProfileIn the repeat track analysis (when the satellites flies over a repetitive orbit) measurements are re-sampledalong a theoretical ground track (or mean track) associated to each mission Then a Mean Profile (MP) issubtracted from the re-sampled data to obtain SLA The MP is a time average of similarly re-sampled dataover a long period
bull The Mean Profile used for Jason-2 is computed with 10 years of TP (cycles 11 to 353) and 6 years ofJason-1 (cycles 11 to 250)
bull The Mean Profile used from Jason-1 cycle 262 to 374 (where satellites are on interleaved ground-tracks) is computed with 3 years of TP (cycles 369 to 479)
bull No Mean Profile can be used for Envisat on its new orbit (enn) Jason-1 on its geodetic orbit (j1g) norfor Cryosat-2 mission (c2) because there is no repetitive track The MSS must be used instead (seebelow)
Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible
bull Indeed as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide precise cross-track projection andor interpolation schemes are required to avoid errors
bull The mesoscale variability error (which is lt35 cm for MP between 3 to 5 years and lt1cm for WLof 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a prioriknowledge from Sea Level maps derived from previous iterations or from other missions
bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for Envisat since november 2010 and for Cryosat-2 mission (c2)because the satellite is not in a repetitive orbit phase The alternative is to use the MSS instead The griddedMSS is derived from along track MPs and data from geodetic phases Thus any error on the MP is alsocontained in the MSS There are essentially 4 types of additional errors on gridded MSS which are hard toquantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
Note that for the Arctic regional products the DTU10 MSS [1] is taken into account instead of the CLS01MSS Indeed the accuracy of DTU10 compared to CLS01 is further demonstrated by the significant sealevel anomaly variance reduction found over the whole Arctic Ocean as shown in Prandi et al [42]
III262 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III263 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
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III27 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III271 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
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III272 Performance indicators
To appreciate the quality situation of the DUACS system new performance indicators are computed dailyThey aim at evaluate the status of the main processing steps of the system the input data availability theinput data coverage the input data quality and the output product quality These indicators are computed foreach and every currently working satellite and combined to obtain the overall status
Figure 8 Example with the key performance indicator on 20090627
See the description the latest and previous indicators on Aviso websitehttpwwwavisooceanobscomindexphpid=1516
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III3 Delayed Time processing steps
III31 Input data models and corrections applied
Delayed Time MyOcean products are generated
bull from Aviso GDR products for TP Jason-1 Jason-2 and Envisat (GDR-A cycles 1 to 22 GDR-Bcycles 23 to 85 GDR-C from cycle 86)
bull from NOAA GDR for GFO and from CERSAT (IFREMER) OPR for ERS-1 and ERS-2 (phases C(1st 35-day repeat orbit period) phase E and F (geodetic phases) phase G for ERS-1 (last 35-dayrepeat orbit period tandem phase with ERS-2 phase A for ERS-2 (1st 35-day repeat orbit periodtandem phase with ERS-1))
All GDR products are computed with a Precise Orbit Ephemeris (POE) and are delivered within 2 to 3months depending on the mission For several missions an updated orbit is used
bull For ERS-1amp-2 the orbit used is DGME-04 provided by Delft Institute (httpwwwdeostudelftnl)until June 2003
bull For TopexPoseidon the orbit used is GSFC (std0809) for the whole mission
bull For Envisat CNES POE of GDR-C standard is used for the whole mission
bull For the whole GFO mission the orbit used is GSFC (std0809) and when not available NASA POE isused
Altimetric product Source Availability Type of orbit
TopexPoseidon GDR NASACNES - GSFC POE
Jason-1 GDR (GDR-C) CNESNASA ~40 days CNES POE
Jason-2 GDR (GDR-C) CNESNASA ~60 days CNES POE
GFO GDR NOAA - GSFCNASA POE
ERS-1amp2 IFREMERESA - DGME-04
Envisat (GDR-A GDR-B andGDR-C from cycle 86)
ESA ~2 months CNES POE
Table 5 SSALTODUACS Delayed Time Input data overview
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
DU
AC
S20
11D
Tpr
oduc
t(gtV
30
0)j2
j1j1
ntp
tpn
e1e2
ene
nng2
Prod
uct
stan
dard
ref
GD
R-C
OPR
GD
R-A
(Cyc
les
1to
22)
GD
R-B
(cyc
les
23-8
5)
GD
R(N
OA
A)
Orb
itC
nes
POE
GSF
C(I
TR
F20
05G
RA
CE
last
stan
dard
s)
DG
ME
-04
(Sch
arro
oan
dV
isse
r19
98[4
8]C
NE
SPO
E(G
DR
-1st
anda
rds
forc
ycle
s9
to22
GD
R-C
stan
dard
sfr
omcy
cle
23)
GSF
C(I
TR
F20
05
GR
AC
Ela
stst
anda
rds
Iono
pher
icD
ual f
requ
ency
altim
eter
rang
em
easu
rem
ents
Dua
l fre
quen
cyal
timet
erra
nge
mea
sure
men
ts(T
opex
)D
OR
IS(P
OSE
IDO
N)
Ben
t mod
elB
ent m
odel
(cyc
les
1-36
)G
IMm
odem
from
cycl
e37
((Ii
jima
etal
19
98[2
4])
Dua
l-fr
eque
ncy
altim
eter
rang
em
easu
rem
ent(
cycl
e9-
64)a
ndG
IMm
odel
gtcyc
le65
(Iiji
ma
etal
19
99[2
4])c
orre
cted
from
8m
mbi
as
From
GIM
mod
el(I
ijim
aet
al1
998
[24]
)
Dry
trop
o-sp
here
Mod
elco
mpu
ted
from
EC
MW
FG
auss
ian
grid
s(n
ewS1
and
S2at
mos
pher
ictid
esar
eap
plie
d)
Mod
elco
mpu
ted
from
EC
MW
Fre
ctan
gula
rgri
ds(n
ewS1
and
S2at
mos
pher
ictid
esar
ein
clud
ed)
Wet
trop
o-sp
here
JMR
AM
Rra
diom
eter
furt
hert
han
50km
from
the
coas
tsF
rom
EC
MW
Fm
odel
ford
ista
nces
betw
een
10an
d50
km
TM
Rra
diom
eter
(Sch
aroo
etal
20
04[4
9])
MW
RC
orre
ctio
nof
the
drif
ton
the
236
GH
zbr
ight
ness
tem
pera
ture
(Sch
arro
oet
al
2004
[49]
)Neu
ral
Net
wor
kal
gori
thm
(Tra
nan
dO
blig
is
2003
[50]
MW
Rra
diom
eter
furt
hert
han
50km
from
the
coas
tsan
dco
rrec
ted
from
side
lobe
s(f
rom
cycl
e41
)E
CM
WF
mod
elfo
rdis
tanc
esbe
twee
n10
and
50km
GFO
radi
omet
er
DA
CM
OG
2DH
igh
Res
olut
ion
forc
edw
ithE
CM
WF
pres
sure
and
win
gfie
lds
(S1
and
S2w
ere
excl
uded
)+in
vers
eba
rom
eter
com
pute
dfr
omre
ctan
gula
rgri
ds
Tabl
e6
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(1
2)
Page 33
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
j2j1
j1n
tptp
ne1
e2en
enn
g2O
cean
tide
GO
T4v
7(S
1an
dS2
are
incl
uded
)Po
letid
e[W
ahr
1985
[53]
]So
lidea
rth
tide
Ela
stic
resp
onse
totid
alpo
tent
ial[
Car
twri
ghta
ndTa
yler
197
1[5]
][C
artw
righ
tand
Edd
en1
973[
6]]
Loa
ding
tide
GO
T4v
7(S
1pa
ram
eter
isin
clud
ed)
Sea
stat
ebi
asN
onpa
ram
etri
cSS
B[G
aspa
reta
l20
02[2
0]]
Non
para
met
ric
SSB
[NT
ran
and
al2
010[
51]]
BM
3[G
aspa
ran
dO
gor
1994
[17]
]
Non
para
met
ric
SSB
[Mer
tzet
al
2005
[38]
]
Non
para
met
ric
SSB
[Gas
pare
tal
2002
]w
ithG
DR
-Bst
anda
rds
forc
ycle
s9
to85
and
with
GD
R-C
stan
dard
sfr
omcy
cle
86
Non
para
met
ric
SSB
[NT
ran
etal
20
10[5
1]]
Orb
iter
ror
Glo
bal m
ulti-
mis
sion
cros
sove
rmin
imiz
atio
n(L
eTr
aon
and
Ogo
r19
98[3
2])
Lon
gw
ave-
leng
her
rors
Opt
imal
Inte
rpol
atio
n(L
eTr
aon
etal
19
98[3
1])
Inte
rcal
ibra
tion
Ref
eren
cefr
omcy
cle
11R
efer
ence
from
cycl
e1
to35
4C
orre
ctio
nof
regi
onal
bias
J2J
1de
duce
dfr
omin
terc
alib
ratio
nph
ase
(cyc
le11
J2)
Cor
rect
ion
ofgl
obal
biai
sJ1
TP
deacutedu
ced
from
inte
rcal
ibra
tion
phas
e(c
ycle
s11
J1)
Mea
npr
o-fil
e(s
eeII
I36
1)
Com
pute
dw
ithcy
cles
11-3
53T
Pda
taan
dw
ithcy
cles
11-2
50J1
data
ref
eren
ced
[199
319
99]
TP
J1 c
ompu
ted
with
cycl
es11
-353
TP
data
and
with
cycl
es11
-250
J1da
tar
efer
ence
d[1
993
1999
]T
PNJ
1Nc
ompu
ted
with
cycl
es36
9-47
9T
PNda
tar
efer
ence
d[1
993
1999
]
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
ref
eren
ced
[199
319
99]
EN
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
re
fere
nced
[199
319
99]
EN
Nu
seof
MSS
_CN
ES_
CL
S11
[39]
Com
pute
dw
ithcy
cles
37-1
87G
2da
ta
refe
renc
ed[1
993
1999
]
Peri
odof
use
from
cycl
e9
from
cycl
e9
cycl
es1
to48
1cy
cles
15to
43In
clud
ing
E-F
geod
etic
phas
es
cycl
es1
to83
from
cycl
e9
cycl
es37
to22
2
Tabl
e7
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(2
2)
Page 34
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III32 Acquisition
The acqusition process in Delayed time is much simpler than in Near Real time it consists in a synchronisa-tion process of all the auxiliary data required to homogenize propely the altimeter data sets The acquisitionstep uses the GDRs or the OPRs provided by the agencies
III33 Homogenization
The Homogenization process consists in applying the most recent corrections models and references rec-ommended for altimeter products Each mission is processed separately as its needs depend on the baseinput data The list of corrections and models currently applied is provided in tables 6 and 7 for DT data
III34 Input data quality control
The Input Data Quality Control is a critical process applied to guarantee that DUACS uses only the mostaccurate altimeter data Thanks to the high quality of current missions this process rejects a small percent-age of altimeter measurements but these erroneous data could be the cause of a significant quality lossThe quality control relies on standard raw data editing with quality flags or parameter thresholds but alsoon complex data editing algorithms based on the detection of erroneous artefacts mono and multi-missioncrossover validation and macroscopic statistics to edit out large data flows that do not meet the systemrsquosrequirements
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PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III35 Multi-mission cross-calibration
The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistentand accurate information It removes any residual orbit error (OE Le Traon and Ogor 1998[32]) or longwavelength error (LWE Le Traon et al 1998[31]) as well as large scale biases and discrepancies betweenvarious data flows
This process is based on two very different algorithms a global multi-mission crossover minimization fororbit error reduction (OER) and Optimal Interpolation (OI) for LWE
Multi-satellite crossover determination is performed on a daily basis All altimeter fields (measurementcorrections and other fields such as bathymetry MSS) are interpolated at crossover locations and datesCrossovers are then appended to the existing crossover database as more altimeter data become availableThis crossover data set is the input of the Orbit Error Reduction (OER) method Using the precision of thereference mission orbit a very accurate orbit error can be estimated LWE is mostly due to residual tidalor inverse barometer errors and high frequency ocean signals The OI used for LWE reduction uses preciseparameters derived from
bull accurate statistical description of sea level variability
bull localized correlation scales
bull mission-specific noise and precise assumptions on the long wavelength errors to be removed (from arecent analysis of one year of data from each mission)
Page 36
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III36 Product generation
The product generation process is composed of four steps computation of raw SLA cross-validationfilteringampsub-sampling and generation of by-products
III361 Computation of raw SLA
Since the geoid is not well known yet the SSH cannot be used directly the SSH anomalies are used insteadThey are computed from the difference of the instantaneous SSH - a temporal reference This temporalreference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeattrack analysis cannot be used The errors affecting the SLAs MPs and MSS have different magnitudes andwavelengths The computation of the SLAs and their errors associated are detailed in Dibarboure et al 2010[9]
Use of a Mean ProfileIn the repeat track analysis (when the satellites flies over a repetitive orbit) measurements are re-sampledalong a theoretical ground track (or mean track) associated to each mission Then a Mean Profile (MP) issubtracted from the re-sampled data to obtain SLA The MP is a time average of similarly re-sampled dataover a long period
bull The Mean Profile used for TP (cycles 1 to 364) Jason-1 (cycles 1 to 259) and Jason-2 is computedwith 10 years of TP (cycles 11 to 353) and 6 years of Jason-1 (cycles 11 to 250)
bull The Mean Profile used for TP (cycles 368 to 481) and from Jason-1 cycle 262 to 374 (where satellitesare on interleaved ground-tracks) is computed with 3 years of TP (cycles 369 to 479)
bull The Mean Profile used for ERS-1 in its 35 days repetitive orbit mission ERS-2 and Envisat (only forthe first orbit before November 2010) is computed with 8 years of ERS-2 (cycles 1 to 85) and 6 yearsof Envisat (cycles 10 to 72)
bull No Mean Profile can be used for Envisat on its new orbit (enn) Jason-1 on its geodetic orbit (j1g)because there is no repetitive track The MSS must be used instead (see below)
bull The Mean Profile used for GFO is computed with 7 years of GFO cycles 37 to 187
Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible
bull Indeed as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide precise cross-track projection andor interpolation schemes are required to avoid errors
bull The mesoscale variability error (which is lt35 cm for MP between 3 to 5 years and lt1cm for WLof 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a prioriknowledge from Sea Level maps derived from previous iterations or from other missions
Page 37
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for ERS-1 for its 168 days geodetic mission (phases E-F from April1994 to March 1995) or for Envisat since november 2010 because the satellite is not in a repetitive orbitphase The alternative is to use the MSS instead The gridded MSS is derived from along track MPs anddata from geodetic phases Thus any error on the MP is also contained in the MSS There are essentially 4types of additional errors on gridded MSS which are hard to quantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
III362 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III363 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
Page 38
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III37 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III371 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
Page 39
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
IV MYOCEAN PRODUCTS
IV1 Near Real Time Products
The purpose of the NRT DUACS component is the acquisition of altimeter data from various altimeter mis-sions in near-real time (ie within a few days at most) the validation and correction of these altimeter datasets (ie edition and selection update of corrections and homogenization orbit error reduction) in order toproduce each day along-track productsProducts are as follows
Along-track products global and regional (Mediterranean and Black Seas Arctic Ocean and Europeareas)
bull Sea Level Anomaly (NRT-SLA) for each mission with NRT-SLA ephemeris
IV11 Delay of the products
The availability of the products in near real time is three to twelve hours after the measurement for along-track products Those products are delivered every day
IV12 Temporal availibility
The following table presents the available products by mission and by data periodNear real time products
NRT Jason-2 Jason-1 and Jason-1geodetic
Envisat new Cryosat-2
Temporal Time availability ymlowast
ongoingymlowast-20120303 for
repeat track and20120507-ongoing for
geodetic track
ymlowast
2012040820120101
ongoing
NRT-SLA X X X X
lowastym the temporal coverage for NRT products is fluctuating and depends on updates of Delayed Time prod-ucts When DT products are updated (3 to 4 times per year) the oldest NRT products are replaced by thebetter quality DT products so that the 2 series are overlapping on few weeks or few months
IV2 Delayed Time Products
The Delayed Time component of SSALTODUACS system is responsible for the production of processedJason-1 Jason-2 TP Envisat GFO ERS12 and even Geosat data in order to provide a homogeneousinter-calibrated and highly accurate long time series of SLA DT products are more precise than NRT products Two reasons explain this quality difference The firstone is the better intrinsic quality of the POE orbit used in the GDR processing The second reason is that
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in the DT DUACS processing the products can be computed optimally with a centred computation timewindow for OER LWE On the contrary in NRT case future data are not available so the computationtime window is not centred and therefore not optimalAs for NRT products improved altimeter corrections and processing algorithms are used ocean tide modelto correct altimeter data improved methods for orbit error reduction and mapping
Along-Track products global and regional (Mediterranean and Black Seas)
bull Sea Level Anomaly (DT-SLA) for each mission
IV21 Delay of the products
Weekly products are delivered The availability of the products in delayed time is at the best two monthsafter the date of the measurement The product generation needs all the GDR data of all the missions to takeinto account the best corrections as possible The time delay can be longer in the case of a missing mission
IV22 Temporal availibility
The following table presents the available products by mission and by data periodDelayed time SSALTODUACS products
Upd Jason-2 Jason-1new6
Jason-1 GFO Envisatnew6
Envisat ERS-16
ERS-2Topexnew6
Topex
TemporalTimeavailabil-ity
200810ymlowast
200902ymlowast
200204200810
200001200809
201010ymlowast
200210201010
199210200304
200209200510
199209200204
DT-SLA X X X X X X X X X
lowast ym those dates are updated regularly (3 to 4 times per year) and are avalaible when you download thedata at httpwwwmyoceaneuweb24-cataloguephp6 Jason-1 new orbit starting 200809 Envisat new orbit starting 201010 TP new orbit starting 200209 ERS-1The geodetic phases (E-F) are included There are no ERS-1 data between December 23 1993 and April 10 1994(ERS-1 phase D - 2nd ice phase) Note that during that time products are based only on TopexPoseidon data
Page 41
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
V DESCRIPTION OF THE PRODUCT SPECIFICATION
V1 General information
Product Specification SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001
Geographical coverage global
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 20-50km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001 Product Specification
Page 42
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
Product Specification SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002
Geographical coverage 55˚W-35˚E 30˚N-46˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002 Product Specification
Page 43
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
Product Specification SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003
Geographical coverage 27˚E-42˚E 40˚N-47˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003 Product Specification
Page 44
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
Product Specification SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004
Geographical coverage 25˚W-42˚E 21˚N-66˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004 Product Specification
Page 45
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
Product Specification SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005
Geographical coverage 0˚W-360˚E 50˚N-82˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005 Product Specification
Page 46
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
VI NOMENCLATURE OF FILES
VI1 Nomenclature of files downloaded through the MyOcean Web PortalDirectgetfile Service
VI11 Nomenclature of the product line
The description of the syntax for the SL TAC SLA products line is given by
SEALEVEL_ltREGIONgt_SLA_L3_ltDELAYgt_OBSERVATIONS_008_ltZONEgt_ltLETTERgtwhere
REGION GLO global geographic coverage product
BS Black Sea products
MED Mediterranean products
ARC Arctic products (for NRT products)
EUROPE Europe products (for NRT products)
DELAY NRT near real time products
RAN delayed time or reanalysis products
ZONE 001 number on 3 digits
002
003
004
LETTER a letter on 1 digit
b
Page 47
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VI12 Nomenclature of the datasets
The nomenclature used is
dataset-duacs-ltdelaygt-ltzonegt-ltmissiongt-lttype of slagt-l3where the fileds in ltgt are described below
delay nrt near-real time productsran delayed time products
zone global global geographic coverage productmedsea Mediterranean productsblacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1 (only for ran)e2 ERS-2 (only for ran)tp TOPEXPoseidon (only for ran)tpn TOPEXPoseidon on its new orbit (only for
ran)g2 GFO (only for ran)j1 Jason-1 (only for ran)j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisat (only for ran)enn Envisat on its new orbitc2 Cryosat-2 (only for nrt)
type of sla sla filtered slasla_unfiltered non filtered sla (only for ran products)
Page 48
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
VI13 Nomenclature of the NetCdf files
The nomenclature used is
ltdelaygt_ltzonegt_ltmissiongt_sla_ltvariablegt_ltdatebegingt_ltdateendgt_ltdateprodgtnc where the fileds in ltgt are de-scribed below
delay nrt near-real time productsdt delayed time products
zone global global geographic coverage productmed Mediterranean products (for dt)mfstep Mediterranean products (for nrt)blacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1e2 ERS-2tp TOPEXPoseidontpn TOPEXPoseidon on its new orbitg2 GFOj1 Jason-1j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisatenn Envisat on its new orbitc2 Cryosat-2
variable vfec filtered and sub-sampled slavxxc non filtered and non sub-sampled sla (only
for dt)datebegin YYYYMMDD() beginning date of the datasetdateend YYYYMMDD() end date of the datasetdateprod YYYYMMDD production date of the dataset
() For dt data as the dates in the file names are rounded the user wanting data for date T has to read the filescontaining dates T+1 and T-1 in their name and check inside the files if there are some data for date T
Page 49
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
VII DATA FORMAT
This chapter presents the data storage format used for MyOcean products
VII1 NetCdf
The products are stored using the NetCDF format NetCDF (network Common Data Form) is an interface for array-oriented data access and a library that provides an implementation of the interface The netCDF library also definesa machine-independent format for representing scientific data Together the interface library and format support thecreation access and sharing of scientific data The netCDF software was developed at the Unidata Program Center inBoulder Colorado The netCDF libraries define a machine-independent format for representing scientific data Pleasesee Unidata NetCDF pages for more information and to retreive NetCDF software package onhttpwwwunidataucaredupackagesnetcdfindexhtml
NetCDF data is
bull Self-Describing A netCDF file includes information about the data it contains
bull Architecture-independent A netCDF file is represented in a form that can be accessed by computers with dif-ferent ways of storing integers characters and floating-point numbers
bull Direct-access A small subset of a large dataset may be accessed efficiently without first reading through allthe preceding data
bull Appendable Data can be appended to a netCDF dataset along one dimension without copying the dataset orredefining its structure The structure of a netCDF dataset can be changed though this sometimes causes thedataset to be copied
bull Sharable One writer and multiple readers may simultaneously access the same netCDF file
Page 50
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
VII2 Structure and semantic of NetCDF along-track files
The NetCDF Sea Level TAC files are based on the attribute data tags defined by the Cooperative OceanAtmosphereResearch Data Service (COARDS) and Climate and Forecast (CF) metadata conventions The CF convention gener-alises and extends the COARDS convention but relaxes the COARDS constraints on dimension and order and specifiesmethods for reducing the size of datasetsA wide range of software are available to write or read NetCDFCF files API are made available by UNIDATA(httpwwwunidataucaredusoftwarenetcdf)
bull CC++Fortran
bull Java
bull MATLAB Objective-C Perl Python R Ruby TclTk
In addition to these conventions the files are using a common structure and semantic
bull 1 dimension is defined
ndash time it is used to check NetCDF variables depending on time
bull 8 variables are defined
ndash short SLA contains the Sea Level Anomaly values for each time given
ndash int longitude contains the longitude for each measurement
ndash short track contains the track number for each measurement
ndash double time contains the time in days since 1950-01-01 000000 UTC for each measurement
ndash short mean_profile_point_index index of the corrsponding point in the track of the mean profile
ndash byte flag flag=0 the processed data comes from OGDR if flag=1 the processed data comes from theIGDR
ndash int latitude contains the latitude for each measurement
ndash short cycle contains the cycle number for each measurement
bull global attributes
ndash the global attributes gives information about the creation of the file
Example of a NetCDF sla file
Page 51
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
netcdf nrt_global_j1_sla_vfec_20101230_20101230_20101230 dimensions
time = 10385 variables
short SLA(time) SLAcoordinates = longitude latitude SLAlong_name = Sea Level Anomaly SLA_FillValue = 32767s SLAadd_offset = 0 SLAscale_factor = 0001 SLAunits = m SLAstandard_name = sea_surface_height_above_sea_level
int longitude(time) longitudelong_name = Longitude of measurement longitude_FillValue = 2147483647 longitudeadd_offset = 0 longitudestandard_name = longitude longitudescale_factor = 1e-06 longitudeunits = degrees_east
short track(time) tracklong_name = Track in cycle the measurement belongs to track_FillValue = 32767s trackunits = 1 trackcoordinates = longitude latitude
double time(time) timelong_name = Time of measurement time_FillValue = 184467440737096e+19 timeaxis = T timestandard_name = time timeunits = days since 1950-01-01 000000 UTC
int latitude(time) latitudelong_name = Latitude of measurement latitude_FillValue = 2147483647 latitudeadd_offset = 0 latitudestandard_name = latitude latitudescale_factor = 1e-06 latitudeunits = degrees_north
short flag(time) flagcoordinates = longitude latitude flag_FillValue = 3267s flaglong_name = data origin flagflag_values = 1s 0s flagflag_meanings = igdr_like non_igdr_like flagcomment = The origin of the data is determined by the types of geophysical datarecords (GDR) used in computation of the SLA 1 for the Interim GDR (IGDR) and0 for Operational GDR (OGDR)
short cycle(time) cyclelong_name = Cycle the measurement belongs to cycle_FillValue = 32767s cycleunits = 1 cyclecoordinates = longitude latitude
global attributeshistory = 22-Feb-2011 155243 CET File created by the SSLATODUACS system version 1001 comment = Produce from ENVISAT Extension Phase satellite altimetry data institution = CLSCNES
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
references = httpwwwavisooceanobscomfileadmindocumentsdatatoolshdbk_duacspdf source = satellite altimetry title = along track Sea Level Anomaly Conventions = CF-14
dataSLA =
7 7 11 10 -2 -22 -39 -41 -30 -13 -3 -5 -16 -26 -32 -35-35 -35 -37 -35 -31 -29 -31 -35 -32 -21 -10 -10 -19 -20 -1-69 -57 -49 -45 -39 -30 -28 -31 -27 -13 -2 -5 -15 -3 1112 3 -7 -10 -14 -15 -22 -31 -37 -32 -17 -10
longitude =74743328 74868400 74993968 75120040 75246616 7537372875501368 75629568 75758320 75887656 76017568 76148080 7627920876388952 76477056 76565456 76654144 76743128 76832400 76921984329429568 329535424 329641792 329748672 329856096 329964032330072512 330181536 330291072 330401184
track =92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 9292 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92113 113 113 113 113 113 113 113 113 113 113 113 113 113113 113 113 113 113 113 113 113 113
time =222780000565705 222780001314719 222780002063733222780002812747 222780003561761 222780004310775 222780005059788222780005808802 222780006557816 22278000730683 222780008055844222780008804858 222780009553872 22278001017805 222780010677393222788257112198 222788257486705 222788257861212 222788258235719222788258610226 222788258984733 222788259359239 222788259733746222788260108253 22278826048276
mean_profile_point_index =1872 1878 1884 1890 1896 1902 1908 19141920 1926 1932 1938 1944 1949 1953 1957 1961 1965 1969 19732306 2309 2312 2315 2318 2321 2327 2330 2333 2336 2339 23422345 2348 2351 2354 2357 2360 2363 2366
flag =0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
latitude =-16225506 -16539731 -16853833 -17167810 -17481660 -17795380-18108966 -18422418 -18735729 -19048899 -19361924 -19674801-19987527 -20248015 -20456329 -20664569 -20872739 -2108083739481297 39628277 39775133 39921866 40068472 40214953 4036130840507533 40653629 40799592 40945423 41091120 41236684 41382111
cycle =331 331 331 331 331 331 331 331 331 331 331 331 331
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331 331 331 331 331 331 331 331 331 331 331 331 331 331331 331 331 331 331 331 331 331 331 331 331 331
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VIII HOW TO DOWNLOAD A PRODUCT
VIII1 Download a product through the MyOcean Web Portal DirectgetfileService
You first need to register Please find below the registration stepshttpwwwmyoceaneuweb34-products-and-services-faqphp1Once registered the MyOcean FAQ httpwwwmyoceaneuweb34-products-and-services-faqwill guide you on How to download a product through the MyOcean Web Portal Directgetfile Service
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IX NEWS AND UPDATES
IX1 [Duacs] Operational news
To be kept informed on events occurring on the satellites and on the eventual interruption of the services of the DUACSprocessing system see the [Duacs] operational news on the Aviso websitehttpwwwavisooceanobscomendataoperational-newsindexhtml
IX2 Updates
To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtmlSince 2010 a complete reprocessing of all altimetry data (cumulated total of about 55 years of data) is available Themain changes introduced in the Duacs DT v300 reprocessed data set in SSALTODUACS reprocessed DT data setare listed herehttpwwwavisooceanobscomfileadmindocumentsdataduacsduacs_DT_2010_reprocessing_impactpdf
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LIST OF TABLES
1 Characteristics of the geodetic orbit for Jason-1 since May 7th 2012 142 SSALTODUACS Near-Real Time Input data overview 223 Corrections and models applied in SSALTODUACS NRT products produced from IGDRs 234 Corrections and models applied in SSALTODUACS NRT products produced from OG-
DRsFDGDRs 245 SSALTODUACS Delayed Time Input data overview 326 Corrections and models applied in SSALTODUACS DT products (gtv300) (12) 337 Corrections and models applied in SSALTODUACS DT products (gtv300) (22) 34
LIST OF FIGURES
1 DUACS and AVISO a user-driven altimetry service 112 SSH-MSS for Cryosat-2 with LRM mode only (left) or LRM+pseudo-LRM modes (right) 163 Coverage of the Europe product for Jason-1 Jason-2 and Envisat from August 18th to
September 9th 2011 184 Coverage of the Arctic region with Envisat from October 28th 2011 to January 3rd 2012 195 SSALTODUACS processing sequences 216 Overview of the near real time system data flow management 257 Merging pertinent information from IGDR and OGDR processing 268 Example with the key performance indicator on 20090627 31
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LIST OF ACRONYMS
ATP Along-Track ProductADT Absolute Dynamic TopographyAVISO Archiving Validation and Interpretation of Satellite Oceanographic dataBGLO Biais Grande Longueur drsquoOndeCalVal Calibration - ValidationCERSAT Centre ERS drsquoArchivage et de TraitementCMA Centre Multimission Altimetry centerCORSSH CORrected Sea Surface HeightC2 Cryosat-2DAC Dynamic Atmospheric CorrectionDT Delayed TimeDTU Mean Sea Surface computed by Technical University of DanemarkDUACS Data Unification and Altimeter Combination SystemE1 ERS-1E2 ERS-2EN EnvisatENN Envisat on its non repetitive orbit (since cycle 94)ECMWF European Centre for Medium-range Weather ForecastingENACT ENhanced ocean data Assimilation and Climate predictionG2 Geosat Follow OnGIM Global Ionospheric MapsGDR Geophysical Data Record(s)IERS International Earth Rotation ServiceIGDR Interim Geophysical Data Record(s)J1 Jason-1J1N Jason-1 on its new orbit (since cycle 262)J1G Jason-1 on its geodetic orbit (since May 2012)J2 Jason-2JPL Jet Propulsion LaboratoryLAS Live Access ServerLWE Long Wavelength ErrorsMADT Map of Absolute Dynamic TopgraphyMDT Mean Dynamic TopographyMOE Medium Orbit EphemerisMP Mean ProfileMSLA Map of Sea Level AnomalyMSS Mean Sea SurfaceNRT Near-Real TimeOE Orbit ErrorOER Orbit Error ReductionOpendap Open-source Project for a Network Data Access ProtocolPF Polynom FitPODAAC Physical Oceanography Distributed Active Archive CentrePOE Precise Orbit EphemerisRD Reference DocumentSAD Static Auxiliary Data
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SI Signed IntegerSLA Sea Level AnomalySL TAC Sea Level Thematic Assembly CentreSSALTO Ssalto multimission ground segmentSSH Sea Surface HeightTAC Thematic Assembly CentreTP TopexPoseidonTPN TopexPoseidon on its new orbit (since cycle 369)
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REFERENCES
[1] Andersen O B The DTU10 Gravity filed and Mean sea surface (2010) Second international sympo-sium of the gravity field of the Earth (IGFS2) Fairbanks Alaska
[2] Boy F et al (2011) Cryosat LRM TRK and SAR processing Presented at the 2011 Ocean Sur-face Topography Science Team meeting httpwwwavisooceanobscomfileadmindocumentsOSTST2011oral01_Wednesday
[3] Carrere L F Lyard 2003 Modeling the barotropic response of the global ocean to atmo-spheric wind and pressure forcing- comparisons with observations J Geophys Res 30(6) 1275doi1010292002GL016473
[4] Carrere L 2003 Etude et modeacutelisation de la reacuteponse HF de lrsquooceacutean global aux forccedilagesmeacuteteacuteorologiques PhD thesis Universiteacute Paul Sabatier (Toulouse III France) 318 pp
[5] Cartwright D E R J Tayler 1971 New computations of the tide-generating potential Geophys JR Astr Soc 23 45-74
[6] Cartwright D E A C Edden 1973 Corrected tables of tidal harmonics Geophys J R Astr Soc33 253-264
[7] Following the scientific recommendations from the OSTST meeting (San Diego October 2011) theESA Cryosat Project and the CNES SALP Project have been collaborating to generate these Cryosat-derived L3 and L4 products Level 1B and Level 2 products derived from CNES processors are notdistributed by AVISO as per the CNES ESA agreement
[8] Dibarboure G C Renaudie M-I Pujol S Labroue N Picot 2011 A demonstrationof the potential of Cryosat-2 to contribute to mesoscale observation J Adv Space Resdoi101016jasr201107002 httpdxdoiorg101016jasr201107002
[9] Dibarboure G P Schaeffer P Escudier M-IPujol JF Legeais Y Faugegravere R Morrow JK WillisJ Lambin JP Berthias N Picot 2010 Finding desirable orbit options for the Extension of Lifephase of Jason-1 Submitted to Marine Geodesy
[10] Dibarboure G M-IPujol FBriol PYLe Traon GLarnicol NPicot FMertz P Escudier MAblainCDufau 2010 Jason-2 in DUACS first tandem results and impact on processing and products Sub-mitted in Marine Geodesy
[11] Dibarboure G 2009 Using short scale content of OGDR data improve the Near Real Time productsof SsaltoDuacs oral presentation at Seattle OSTST meeting (pdf)
[12] Dorandeu J M Ablain Y Faugegravere F Mertz B Soussi and P Vincent 2004 Jason-1 global statisti-cal evaluation and performance assessment Calibration and cross-calibration results Marine Geodesy27(3-4) 345-372
[13] Dorandeu J M Ablain P-Y Le Traon 2003 Reducing Cross-Track Geoid Gradient Errors aroundTOPEXPoseidon and Jason-1 Nominal Tracks Application to Calculation of Sea Level AnomaliesJ of Atmosph and Ocean Techn20 1826-1838
[14] Dorandeu J and P-Y Le Traon 1999 Effects of global mean atmospheric pressure variations onmean sea level changes from TOPEXPoseidon J Atmos Oceanic Technol 16 1279-1283
[15] Ducet N P-Y Le Traon and G Reverdin 2000 Global high resolution mapping of ocean circulationfrom TOPEXPoseidon and ERS-1 and -2 J Geophys Res 105 19477-19498
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[16] Egbert Gary D Svetlana Y Erofeeva 2002 Efficient Inverse Modeling of Barotropic Ocean Tides JAtmos Oceanic Technol 19 183-204 doi 1011751520-0426(2002)019lt0183EIMOBOgt20CO2
[17] Gaspar P and F Ogor Estimation and analysis of the Sea State Bias of the ERS-1 altimeter Reportof task B1-B2 of IFREMER Contract n˚ 942426 016C 1994
[18] Gaspar P F Ogor and C Escoubes 1996 Nouvelles calibration et analyse du biais drsquoeacutetat de mer desaltimegravetres TOPEX et POSEIDON Technical note 96018 of CNES Contract 951523 1996
[19] Gaspar P and F Ogor Estimation and analysis of the Sea State Bias of the new ERS-1 and ERS-2altimetric data (OPR version 6) Report of task 2 of IFREMER Contract n˚ 962246 002C 1996
[20] Gaspar P S Labroue and F Ogor 2002 Improving nonparametric estimates of the sea state bias inradar altimeter measurements of seal level J Atmos Oceanic Technology 19 1690-1707
[21] Hernandez F P-Y Le Traon and R Morrow 1995 Mapping mesoscale variability of the AzoresCurrent using TOPEXPOSEIDON and ERS-1 altimetry together with hydrographic and Lagrangianmeasurements Journal of Geophysical Research 100 24995-25006
[22] Hernandez F and P Schaeffer 2000 Altimetric Mean Sea Surfaces and Gravity Anomaly maps inter-comparisons AVI-NT-011-5242-CLS 48 pp CLS Ramonville St Agne
[23] Hernandez F M-H Calvez J Dorandeu Y Faugegravere F Mertz and P Schaeffer 2000 Sur-face Moyenne Oceacuteanique Support scientifique agrave la mission altimeacutetrique Jason-1 et agrave une mis-sion micro-satellite altimeacutetrique Contrat SSALTO 2945 - Lot 2 - A1 Rapport drsquoavancementCLSDOSNT00313 40 pp CLS Ramonville St Agne
[24] Iijima BA IL Harris CM Ho UJ Lindqwiste AJ Mannucci X Pi MJ Reyes LC SparksBD Wilson 1999 Automated daily process for global ionospheric total electron content maps andsatellite ocean altimeter ionospheric calibration based on Global Positioning System data J AtmosSolar-Terrestrial Physics 61 16 1205-1218
[25] Labroue S F Boy N Picot M Urvoy M Ablain First quality assessment of the Cryosat-2 altimetricsystem over ocean J Adv Space Res 2011 doi101016jasr201111018 httpdxdoiorg101016jasr201111018
[26] Labroue S 2007 RA2 ocean and MWR measurement long term monitoring 2007 report for WP3Task 2 - SSB estimation for RA2 altimeter Contract 1729303I-OL CLS-DOS-NT-07-198 53ppCLS Ramonville St Agne
[27] Labroue S P Gaspar J Dorandeu OZ Zanifeacute F Mertz P Vincent and D Choquet 2004 Nonparametric estimates of the sea state bias for Jason-1 radar altimeter Marine Geodesy 27 453-481
[28] Lagerloef GSE GMitchum RLukas and PNiiler 1999 Tropical Pacific near-surface currentsestimated from altimeter wind and drifter data J Geophys Res 104 23313-23326
[29] Le Traon P-Y and F Hernandez 1992 Mapping the oceanic mesoscale circulation validation ofsatellite altimetry using surface drifters J Atmos Oceanic Technol 9 687-698
[30] Le Traon P-Y P Gaspar F Bouyssel and H Makhmara 1995 Using TopexPoseidon data to en-hance ERS-1 data J Atmos Oceanic Technol 12 161-170
[31] Le Traon P-Y F Nadal and N Ducet 1998 An improved mapping method of multisatellite altimeterdata J Atmos Oceanic Technol 15 522-534
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[32] Le Traon P-Y and F Ogor 1998 ERS-12 orbit improvement using TOPEXPOSEIDON the 2 cmchallenge J Geophys Res 103 8045-8057
[33] Le Traon P-Y and G Dibarboure 1999 Mesoscale mapping capabilities of multi-satellite altimetermissions J Atmos Oceanic Technol 16 1208-1223
[34] Le Traon P-Y G Dibarboure and N Ducet 2001 Use of a High-Resolution Model to Analyze theMapping Capabilities of Multiple-Altimeter Missions J Atmos Oceanic Technol 18 1277-1288
[35] Le Traon PY and G Dibarboure 2002 Velocity mapping capabilities of present and future altimetermissions the role of high frequency signals J Atmos Oceanic Technol 19 2077-2088
[36] Le Traon PY Faugegravere Y Hernandez F Dorandeu J Mertz F and M Ablain 2002 Can we mergeGEOSAT Follow-On with TOPEXPOSEIDON and ERS-2 for an improved description of the oceancirculation J Atmos Oceanic Technol 20 889-895
[37] Le Traon PY and G Dibarboure 2004 An Illustration of the Contribution of the TOPEXPoseidon-Jason-1 Tandem Mission to Mesoscale Variability Studies Marine Geodesy 27 (1-2)
[38] Mertz F F Mercier S Labroue N Tran J Dorandeu 2005 ERS-2 OPR data quality assessment Long-term monitoring - particular investigation CLSDOSNT-06001 (pdf)
[39] MSS_CNES_CLS11 was produced by CLS Space Oceanography Division and distributed by Avisowith support from Cnes (urlhttpwwwavisooceanobscom)
[40] Pascual A Y Faugegravere G Larnicol P-Y Le Traon 2006 Improved description of the oceanmesoscale variability by combining four satellite altimeters Geophys Res Lett 33
[41] Pascual A C Boone G Larnicol and P-Y Le Traon 2009 On the quality of Real-Time altimetergridded fields comparison with in-situ data Journ of Atm and Ocean Techn Vol 26(3) pp 556-569DOI 1011752008JTECHO5561
[42] Prandi P M Ablain A Cazenave N Picot 2011 A new estimation of mean sea level in the ArcticOcean from satellite altimetry Submitted to Marine Geodesy
[43] Pujol M-I et al 2009 Three-satellite quality level restored in NRT poster at OSTST meeting (pdf)
[44] Ray R 1999 A Global Ocean Tide model from TOPEXPoseidon Altimetry GOT992 NASA TechMemo NASATM-1999-209478 58 pp Goddard Space Flight Center NASA Greenbelt MD USA
[45] Rio M-H and F Hernandez 2003 A Mean Dynamic Topography computed over the worldocean from altimetry in-situ measurements and a geoid model J Geophys Res 109 C12032doi1010292003JC002226
[46] Rio M-H and F Hernandez 2003 High frequency response of wind-driven currents measured bydrifting buoys and altimetry over the world ocean J Geophys Res 108 39-1
[47] Rio M-H 2003 Combinaison de donneacutees in situ altimeacutetriques et gravimeacutetriques pour lrsquoestimationdrsquoune topographie dynamique moyenne globale Ed CLS PhD Thesis University Paul Sabatier(Toulouse III France) 260pp
[48] Scharroo R and P Visser 1998 Precise orbit determination and gravity field improvement for theERS satellites J Geophys Res 103 8113-8127
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[49] Scharroo R J Lillibridge and WHF Smith 2004 Cross-calibration and long-term monitoring ofthe Microwave Radiometers of ERS Topex GFO Jason-1 and Envisat Marine Geodesy 97
[50] Tran N and E Obligis December 2003 Validation of the use of ENVISAT neural algorithms onERS-2 CLSDOSNT03901
[51] Tran N S Labroue S Philipps E Bronner and N Picot 2010 Overview and Update of the SeaState Bias Corrections for the Jason-2 Jason-1 and TOPEX Missions Marine Geodesy accepted
[52] Vincent P Desai SDDorandeu J Ablain M Soussi B Callahan PS and BJ Haines 2003 Jason-1 Geophysical Performance Evaluation Marine Geodesy 26 167-186
[53] Wahr J W 1985 Deformation of the Earth induced by polar motionJ of Geophys Res (Solid Earth)90 9363-9368
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I INTRODUCTION
MyOcean is a European Network project aiming at monitoring analyzing and forecasting the Ocean Ituses satellite and in-situ data to describe the ocean in 3 dimensions and real time More information can befound on httpwwwmyoceaneuorgThe aim of this document is to describe the products delivered by the Sea Level TAC (Thematic AssemblyCentre) which is one of the five TAC of the MyOcean projectThe data produced in the frame of this TAC are generated by the processing system named DUACS (DataUnification and Altimeter Combination System)DUACS is part of the CNES multi-mission ground segment (SSALTO) It processes data from all altimetermissions Cryosat-2 OSTMJason-2 Jason-1 TopexPoseidon Envisat GFO ERS-1amp2 and even GeosatAt this time (May 25th 2012) DUACS is using three different altimeters in near real time Developed and operated by CLS it started as an European Commission Project (Developing Use Of Altime-try for Climate Studies) funded under the European Commission and the Midi-Pyreacuteneacutees regional councilIt has been integrated to the CNES multi-mission ground segment SSALTO in 2001 and it is maintainedupgraded and operated with funding from CNES with shared costs from EU projectsAt the beginning of 2004 DUACS was redefined as the Data Unification Altimeter Combination System
Figure 1 DUACS and AVISO a user-driven altimetry service
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The products lines described in this user manual are the followingSEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005
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The data provided to users have a global coverage (PL SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001)and regional products are also computed over specific areasMediterranean Sea (PL SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002)and Black Sea (PL SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003)Thanks to updates in 2011 and 2012 (see section II) new regional products are now availableEurope (PL SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004)and Arctic (PL SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005)
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II UPDATES IN 2011 AND 2012
This section describes the updates of the SSALTODUACS Near Real Time system that occurred during2011 and 2012 allowing to add new products (Europe and Arctic) the integration of the Cryosat-2 data inthe system the stopping delivery of Envisat data the addition of Jason-1 data on geodetic orbit (j1g)To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtml
II1 Version D of input IGDROGDR Jason-2 data for NRT processing(July 30 2012)
On July 30 2012 the version of Jason-2 IGDROGDR has changed and is now the D version Somecorrections have thus been updated as detailed in tables 3 and 4
II2 Integration of Jason-1 on its geodetic orbit (May 2012)
An anomaly occured on March 3rd 2012 on the Jason-2 mission (see httpwwwavisooceanobscomfractualitesactualitesindexhtmltx_ttnews[tt_news]=1162amptx_ttnews[backPid]=1399ampcHash=d5baeb645e) On April 23rd CNES began to command the satellite into a nadir ori-entation and after some propulsion anomalies CNES and NASA management through the Joint SteeringGroup have directed the Jason-1 Project to then begin a series of maneuvers to place Jason-1 into a neworbit as defined in table 1 After checking the current orbit carefully the operational team determined thata geodetic mission was still possible It was also decided to preserve all remaining fuel for future stationkeeping maneuvers which is mandatory in a geodetic orbit Core payloads were switched ON on May 4thand after some POSEIDON2 radar (PRF) adjustments the mission was resumed on May 7th at 151248UTCBelow are the characteristics of the new orbit which will be maintained as before within +- 1km controlbox at the Equator
Semi major axis 7702437 kmEccentricity 13 to 28 10-4Altitude equator 13240 kmOrbital period 6730s (1h52rsquo10rdquo)Inclination 66042˚Cycle 406 daysSub cycles 39 - 109 - 475 - 1795
days
Table 1 Characteristics of the geodetic orbit for Jason-1 since May 7th 2012
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For this new phase of the Jason-1 mission (called j1g) the cycle numbering will restart at 500 Off-lineproducts will be produced once a day for the IGDR and every 11 days for the GDRrsquos The integration ofJason-1 data in the DUACS system is available since May 25th 2012
II3 Envisat has stopped sending data (April 2012)
Since April 8th 2012 Envisat has stopped sending data to Earth Esarsquos mission control has worked tore-establish contact with the satellite but there has been no reaction from the satellite Thus Esa has de-clared officially the end of mission for Envisat (see httpwwwesaintesaCPSEM1SXSWT1H_index_0html) Therefore no SL TAC NRT data from Envisat can be released since this date
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II4 Integration of the Cryosat2 Mission (February 2012)
Since February 6th 2012 Cryosat-2 mission has been integrated in the DUACS sytem This mission isdedicated to the observation of the floating sea-ice as well as the continental ice sheets but all data acquiredover ocean are valuable for the observation of oceanic circulation and mesoscale variations This majorchange is the result of the long-standing and fruitful partnership between ESA and CNES and a responseto the request from scientific and operational oceanography users [7] The integration of Cryosat-2 impactsthe delivering of Near real time Sea Level Anomalies (SLA)
II41 Generalities about the mission
A Cryosat-2 Processing Prototype (C2P) (described in Boy et al 2011 [2]) has been developed on CNESside to lay the ground for various SAR processing studies The processing chains ingest Level-0 telemetryfiles distributed by ESA and perform the following steps to generate Sea Level Anomalies (SLA) values foreach altimeter measurements
bull Level-1 Decommutation time-tagging and localization of measurements
bull Level-1b Calculation of instrumental corrections and geophysicalmeteorological corrections
bull Level-2 MLE4 waveforms Retracking and calculation of SLA
The prototype processes data almost continuously over ocean either in Low Resolution Mode (LRM) or inthe DopplerSAR mode processed as pseudo-LRM mode allowing to increase the coverage (figure 2)
Figure 2 SSH-MSS for Cryosat-2 with LRM mode only (left) or LRM+pseudo-LRM modes (right)
Although Cryosat-2 raw SSH can be only corrected with GPS-derived ionospheric correction and ECMWFwet troposphere correction validation activities showed (Labroue et al 2011 [25]) that C2P outputs have anaccuracy roughly equivalent to Envisatrsquos Level 2 products if the latter are processed with the same standards
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II42 Integration in DUACS
The Cryosat-2 data are included in the Near Real time process The chain delivers now (for global coverageMediterranean and Black Seas) along track data from Cryosat-2 (SLAs) Note that the products distributedare of Level-3 and donrsquot replace Level-2 products distributed by agenciesThe details of the processing are given in Dibarboure et al 2011 [8]Here we just give an overview the data are computed with the corrections given in section III21 Thefiltering and sub-sampling of SLAs (section III263) are detailed in [8]
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II5 Addition of Europe and Arctic products (January 2012)
Since the MyOcean V2 two new along-track products are computed in Near Real Time intended foraddressing the needs of data assmilation and validation in regional models
bull Following the TAPAS (Tailored Altimeter Product for Assimilation Systems) initiative launched bySL TAC with all the Modeling and Forecasting Centers (MFCs) the Europe regional products (PLSEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004) have been proposed (figure 3) They areavailable in Near Real Time onlyThey are studied to partly fulfil the needs of the Centers with adapted filtering and resolution Thoseparameters have been tuned in order to provide boundary conditions for the Atlantic assimilationmodels They are different from the ones used for Mediterranean and Black Seas products If you needto study the Mediterranean Sea or the Black Sea yoursquod better use the dedicated products describedabove since the processing parameters have been fitted to be adapted to the dynamics of the ocean inthose regions
Figure 3 Coverage of the Europe product for Jason-1 Jason-2 and Envisat from August 18th to September9th 2011
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bull The Arctic along-track products (PL SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005) coverlatitudes between 45 and 82 degrees (figure 4) They are available in Near Real Time only
Figure 4 Coverage of the Arctic region with Envisat from October 28th 2011 to January 3rd 2012
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III SSALTODUACS SYSTEM
III1 Introduction
This chapter presents the input data used by SSALTODUACS system and an overview of the different pro-cessing steps necessary to produce the output dataSSALTODUACS system is made of two components a Near Real Time one (NRT) and a Delayed Time(DT) oneIn NRT the systemrsquos primary objective is to provide operational applications with directly usable high qual-ity altimeter data from all missions availableIn DT it is to maintain a consistent and user-friendly altimeter database using the state-of-the-art recom-mendations from the altimetry communityFollowing figure gives an overview of DUACS system where processing sequences can be divided into 7main steps
bull acquisition
bull homogenization
bull input data quality control
bull multi-mission cross-calibration
bull product generation
bull merging
bull final quality control
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Figure 5 SSALTODUACS processing sequences
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III2 Near Real Time processing steps
III21 Input data models and corrections applied
To produce SLA in near-real time the DUACS system uses two flows based on the same instrumental mea-surements but with a different quality
bull The IGDR that are the latest high-quality altimeter data produced in near-real-time
bull The OGDR that includes real time data (OSTMJason-2 and Jason-1 OSDR) to complete IGDR Thesefast delivery products do not always benefit from precise orbit determination nor from some exter-nal model-based corrections (Dynamic Atmospheric Correction (DAC) Global Ionospheric Maps(GIM))
Integration of OGDR data and the introduction of Jason-2Jason-1 tandem increased the resilience and pre-cision of the system A better restitution of ocean variability is observed especially in high energetic areas
Altimetric product Source Availability Type of orbit
Jason-2 IGDR CNES ~24h CNES MOE GDR-Cuntil 20120730
CNES MOE GDR-Dsince 20120731
OGDR NOAAEUMETSAT ~3 to 5 h
Jason-1 IGDR CNESNASA ~48 h CNES MOE GDR-Dsince 20120507
OGDR CNESNASA ~3 to 12 h
Envisat IGDR ESACNES not deliveredsince 20120408
CNES MOE GDR-Dsince 20120121
FDGDR ESA not deliveredsince 20120408
Cryosat-2 IGDR-like ESACNES ~48 h CNES MOE GDR-D
not delivered
Table 2 SSALTODUACS Near-Real Time Input data overview
See Figure 6 Overview of the near real time system data flow management
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DUACS 2011 NRT product from IGDR1
j2 j1nj1g enn c2Productstandard ref
version C until20120730 and D after
version C version 21 CPP [2]
Orbit CNES MOE GDR-Cuntil 20120730
GDR-D after
CNES MOE GDR-C forj1n and CNES MOE
GDR-D for j1g
CNES MOE GDR-Dfrom 20120121 to
20120408
CNES MOE GDR-D
Ionopheric bi-frequency altimeter range measurements GIM model for cgt64 (Iijima et al1998[24])Dry tropo Model computed from ECMWF Gaussian grids (new S1 and S2 atm tides applied)Wet tropo-sphere
AMR radiometer(enhancement in coastal
regions since20120730)
JMR radiometer MWR radiometer andcorrected from side
lobes
Model computed fromECMWF Gaussian
grids
DAC MOG2D High Resolution forced with ECMWF pressure and wind fields (S1 and S2 wereexcluded) (Carrere and Lyard 2003[3])+ inverse barometer Filtering temporal window is
un-centered (no data in the future)Ocean tide GOT4v8 (S1 and S2 are included) and TPX 072 [16] for Arctic productsPole tide [Wahr 1985 [53]]Solid earthtide
Elastic response to tidal potential [Cartwright and Tayler 1971[5]] [Cartwright andEdden 1973[6]]
Loading tide GOT4v8 (S1 and S2 are included)Sea statebias
Non parametric SSB[Labroue 2004[27]](with cycles J1 1 to 11
using GDR-B standardsuntil 20120730 andderived from Jason-2
after)
Non parametric SSB[Labroue 2004[27]](with cycles 1 to 21
using GDR-Bstandards)
Non parametric SSB[Labroue 2004[27]](with cycles 41 to 60
using GDR-Bstandards)
Same as Jason-2 SSB
Orbit error Global multi-mission crossover minimization (Le Traon and Ogor1998[32])
Long wave-lengh errors
Optimal Interpolation [Le Traon et al 1998[31]]
Intercalibration Reference from cycle20
Mean pro-file (seeIII261)
Computed with cycles11-353 TP data andwith cycles 11-250J1 data referenced[19931999]
TPNJ1N computedwith cycles 369-479TPN data refer-enced [19931999]J1G No MP can beused instead theMSS_CNES_CLS11[39] is used
No Mean Profilecan be used forEnvisat on its neworbit Instead theMSS_CNES_CLS11[39] is used
No Mean Profilecan be used forCryosat-2 Instead theMSS_CNES_CLS11[39] is used
(1) A flag included in the along-track files indicates the source of the production (OGDRFDGDR orIGDR) If flag=0 the processed data comes from OGDRsFDGDRs if flag=1 the processed data comesfrom IGDRs
Table 3 Corrections and models applied in SSALTODUACS NRT products produced from IGDRs
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DUACS 2011 NRT product from OGDR or FDGDR2
j2 j1nj1g ennProduct stan-dard ref
version C until 20120730and D after
version C version 21
Orbit Navigator Extrapolated CNES MOEGDR-D since 20120121
Ionopheric From-dual frequency altimeter range measurements From GIM model fromcycle 65 (Iijima et al1998 [24])
Dry troposphere Model computed from ECMWF Gaussian grids (new S1 and S2 atmospherictides are applied)
Wet tropo-sphere
AMR radiometer(enhancement in coastal
regions since 20120730)
JMR radiometer MWR radiometer andcorrected from side lobes
DAC Inverse Barometer forecastedOcean tide GOT4v8 (S1 and S2 are included) and TPX 072 [16] for Arctic productsPole tide [Wahr 1985 [53]]Solid earth tide Elastic response to tidal potential [Cartwright and Tayler 1971[5]]
[Cartwright and Edden 1973[6]]Loading tide GOT4v8 (S1 and S2 are included)Sea state bias Non parametric SSB
[Labroue 2004[27]] (withcycles J1 1 to 11 usingGDR-B standards until20120730 and derivedfrom Jason-2 after)
Non parametric SSB[Labroue 2004[27]](with cycles 1 to 21 usingGDR-B standards)
Non parametric SSB[Labroue 2004[27]](with cycles 41 to 60using GDR-B standards)
Orbit error Specific filtering of long-wavelength signal3
Long wave-lengh errors
Optimal Interpolation [Le Traon et al 1998[31]]
Intercalibration Reference from cycle 20Mean profile(see III261)
Computed with cycles 11-353 TP data and with cy-cles 11-250 J1 data refer-enced [19931999]
TPNJ1N computedwith cycles 369-479TPN data referenced[19931999] J1G NoMP can be used insteadthe MSS_CNES_CLS11[39] is used
No Mean Profile can beused for Envisat on itsnew orbit Instead theMSS_CNES_CLS11 [39]is used
(2) A flag included in the along-track files indicates the source of the production (OGDRFDGDR orIGDR) If flag=0 the processed data comes from OGDRsFDGDRs if flag=1 the processed data comesfrom IGDRs(3) Specific data processing was applied on long wave-length signal (sectIII23 of the user manual)
Table 4 Corrections and models applied in SSALTODUACS NRT products produced from OG-DRsFDGDRs
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III22 Acquisition
The acquisition process is twofold
bull straightforward retrieval and reformatting of altimeter data and dynamic auxiliary data (pressure andwet troposphere correction grids from ECMWF are provided by Meteo France TEC grids from JPLNRT MOG2D corrections) from external repositories
bull synchronisation process
To be homogenized properly altimeter data sets require various auxiliary data The acquisition softwaredetects downloads and processes incoming data as soon as they are available on remote sites (externaldatabase FTP site) Data are split into passes if necessary If data flows are missing or late the synchroni-sation engine put unusable data in waiting queues and automatically unfreezes them upon reception of themissing auxiliary data This processing step delivers raw data that is to say data that have been dividedinto cycles and passes and ordered chronologicallyFrom SSALTODUACS V80 the acquisition step uses two different data flows in near-real time the OGDRflow (within a few hours) and the IGDR flow (within a few days)For each OGDR input the system checks that no equivalent IGDR entry is available in the data base beforeacquisition for each IGDR input the system checks and delete the equivalent OGDR entry in the data baseThese operations aim to avoid duplicates in SSALTODUACS system
Figure 6 Overview of the near real time system data flow management
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III23 Homogenization
The Homogenization process consists in applying the most recent corrections models and references rec-ommended for altimeter products Each mission is processed separately as its needs depend on the baseinput data The list of corrections and models currently applied is provided in tables 3 and 4 for NRT dataThe system includes SLA filtering to process OGDR data DUACS extract from these data sets the shortscales (space and time) which are useful to better describe the ocean variability in real time and merge thisinformation with a fair description of large scale signals provided by the multi-satellite observation in nearreal time (read IGDR-based DUACS data) Finally an hybrid SLA is computed
Figure 7 Merging pertinent information from IGDR and OGDR processing
III24 Input data quality control
The Input Data Quality Control is a critical process applied to guarantee that DUACS uses only the mostaccurate altimeter data Thanks to the high quality of current missions this process rejects a small percent-age of altimeter measurements but these erroneous data could be the cause of a significant quality lossThe quality control relies on standard raw data editing with quality flags or parameter thresholds but alsoon complex data editing algorithms based on the detection of erroneous artefacts mono and multi-missioncrossover validation and macroscopic statistics to edit out large data flows that do not meet the systemrsquosrequirements
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III25 Multi-mission cross-calibration
The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistentand accurate information It removes any residual orbit error (OE Le Traon and Ogor 1998[32]) or longwavelength error (LWE Le Traon et al 1998[31]) as well as large scale biases and discrepancies betweenvarious data flows
This process is based on two very different algorithms a global multi-mission crossover minimization fororbit error reduction (OER) and Optimal Interpolation (OI) for LWE
Multi-satellite crossover determination is performed on a daily basis All altimeter fields (measurementcorrections and other fields such as bathymetry MSS) are interpolated at crossover locations and datesCrossovers are then appended to the existing crossover database as more altimeter data become availableThis crossover data set is the input of the Orbit Error Reduction (OER) method Using the precision of thereference mission orbit a very accurate orbit error can be estimated This processing step does not concernOGDR dataLWE is mostly due to residual tidal or inverse barometer errors and high frequency ocean signals The OIused for LWE reduction uses precise parameters derived from
bull accurate statistical description of sea level variability
bull localized correlation scales
bull mission-specific noise and precise assumptions on the long wavelength errors to be removed (from arecent analysis of one year of data from each mission)
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III26 Product generation
The product generation process is composed of four steps computation of raw SLA cross-validationfilteringampsub-sampling and generation of by-products
III261 Computation of raw SLA
Since the geoid is not well known yet the SSH cannot be used directly the SSH anomalies are used insteadThey are computed from the difference of the instantaneous SSH - a temporal reference This temporalreference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeattrack analysis cannot be used The errors affecting the SLAs MPs and MSS have different magnitudes andwavelengths The computation of the SLAs and their errors associated are detailed in Dibarboure et al 2010[9]
Use of a Mean ProfileIn the repeat track analysis (when the satellites flies over a repetitive orbit) measurements are re-sampledalong a theoretical ground track (or mean track) associated to each mission Then a Mean Profile (MP) issubtracted from the re-sampled data to obtain SLA The MP is a time average of similarly re-sampled dataover a long period
bull The Mean Profile used for Jason-2 is computed with 10 years of TP (cycles 11 to 353) and 6 years ofJason-1 (cycles 11 to 250)
bull The Mean Profile used from Jason-1 cycle 262 to 374 (where satellites are on interleaved ground-tracks) is computed with 3 years of TP (cycles 369 to 479)
bull No Mean Profile can be used for Envisat on its new orbit (enn) Jason-1 on its geodetic orbit (j1g) norfor Cryosat-2 mission (c2) because there is no repetitive track The MSS must be used instead (seebelow)
Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible
bull Indeed as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide precise cross-track projection andor interpolation schemes are required to avoid errors
bull The mesoscale variability error (which is lt35 cm for MP between 3 to 5 years and lt1cm for WLof 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a prioriknowledge from Sea Level maps derived from previous iterations or from other missions
bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for Envisat since november 2010 and for Cryosat-2 mission (c2)because the satellite is not in a repetitive orbit phase The alternative is to use the MSS instead The griddedMSS is derived from along track MPs and data from geodetic phases Thus any error on the MP is alsocontained in the MSS There are essentially 4 types of additional errors on gridded MSS which are hard toquantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
Note that for the Arctic regional products the DTU10 MSS [1] is taken into account instead of the CLS01MSS Indeed the accuracy of DTU10 compared to CLS01 is further demonstrated by the significant sealevel anomaly variance reduction found over the whole Arctic Ocean as shown in Prandi et al [42]
III262 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III263 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
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III27 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III271 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
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III272 Performance indicators
To appreciate the quality situation of the DUACS system new performance indicators are computed dailyThey aim at evaluate the status of the main processing steps of the system the input data availability theinput data coverage the input data quality and the output product quality These indicators are computed foreach and every currently working satellite and combined to obtain the overall status
Figure 8 Example with the key performance indicator on 20090627
See the description the latest and previous indicators on Aviso websitehttpwwwavisooceanobscomindexphpid=1516
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III3 Delayed Time processing steps
III31 Input data models and corrections applied
Delayed Time MyOcean products are generated
bull from Aviso GDR products for TP Jason-1 Jason-2 and Envisat (GDR-A cycles 1 to 22 GDR-Bcycles 23 to 85 GDR-C from cycle 86)
bull from NOAA GDR for GFO and from CERSAT (IFREMER) OPR for ERS-1 and ERS-2 (phases C(1st 35-day repeat orbit period) phase E and F (geodetic phases) phase G for ERS-1 (last 35-dayrepeat orbit period tandem phase with ERS-2 phase A for ERS-2 (1st 35-day repeat orbit periodtandem phase with ERS-1))
All GDR products are computed with a Precise Orbit Ephemeris (POE) and are delivered within 2 to 3months depending on the mission For several missions an updated orbit is used
bull For ERS-1amp-2 the orbit used is DGME-04 provided by Delft Institute (httpwwwdeostudelftnl)until June 2003
bull For TopexPoseidon the orbit used is GSFC (std0809) for the whole mission
bull For Envisat CNES POE of GDR-C standard is used for the whole mission
bull For the whole GFO mission the orbit used is GSFC (std0809) and when not available NASA POE isused
Altimetric product Source Availability Type of orbit
TopexPoseidon GDR NASACNES - GSFC POE
Jason-1 GDR (GDR-C) CNESNASA ~40 days CNES POE
Jason-2 GDR (GDR-C) CNESNASA ~60 days CNES POE
GFO GDR NOAA - GSFCNASA POE
ERS-1amp2 IFREMERESA - DGME-04
Envisat (GDR-A GDR-B andGDR-C from cycle 86)
ESA ~2 months CNES POE
Table 5 SSALTODUACS Delayed Time Input data overview
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
DU
AC
S20
11D
Tpr
oduc
t(gtV
30
0)j2
j1j1
ntp
tpn
e1e2
ene
nng2
Prod
uct
stan
dard
ref
GD
R-C
OPR
GD
R-A
(Cyc
les
1to
22)
GD
R-B
(cyc
les
23-8
5)
GD
R(N
OA
A)
Orb
itC
nes
POE
GSF
C(I
TR
F20
05G
RA
CE
last
stan
dard
s)
DG
ME
-04
(Sch
arro
oan
dV
isse
r19
98[4
8]C
NE
SPO
E(G
DR
-1st
anda
rds
forc
ycle
s9
to22
GD
R-C
stan
dard
sfr
omcy
cle
23)
GSF
C(I
TR
F20
05
GR
AC
Ela
stst
anda
rds
Iono
pher
icD
ual f
requ
ency
altim
eter
rang
em
easu
rem
ents
Dua
l fre
quen
cyal
timet
erra
nge
mea
sure
men
ts(T
opex
)D
OR
IS(P
OSE
IDO
N)
Ben
t mod
elB
ent m
odel
(cyc
les
1-36
)G
IMm
odem
from
cycl
e37
((Ii
jima
etal
19
98[2
4])
Dua
l-fr
eque
ncy
altim
eter
rang
em
easu
rem
ent(
cycl
e9-
64)a
ndG
IMm
odel
gtcyc
le65
(Iiji
ma
etal
19
99[2
4])c
orre
cted
from
8m
mbi
as
From
GIM
mod
el(I
ijim
aet
al1
998
[24]
)
Dry
trop
o-sp
here
Mod
elco
mpu
ted
from
EC
MW
FG
auss
ian
grid
s(n
ewS1
and
S2at
mos
pher
ictid
esar
eap
plie
d)
Mod
elco
mpu
ted
from
EC
MW
Fre
ctan
gula
rgri
ds(n
ewS1
and
S2at
mos
pher
ictid
esar
ein
clud
ed)
Wet
trop
o-sp
here
JMR
AM
Rra
diom
eter
furt
hert
han
50km
from
the
coas
tsF
rom
EC
MW
Fm
odel
ford
ista
nces
betw
een
10an
d50
km
TM
Rra
diom
eter
(Sch
aroo
etal
20
04[4
9])
MW
RC
orre
ctio
nof
the
drif
ton
the
236
GH
zbr
ight
ness
tem
pera
ture
(Sch
arro
oet
al
2004
[49]
)Neu
ral
Net
wor
kal
gori
thm
(Tra
nan
dO
blig
is
2003
[50]
MW
Rra
diom
eter
furt
hert
han
50km
from
the
coas
tsan
dco
rrec
ted
from
side
lobe
s(f
rom
cycl
e41
)E
CM
WF
mod
elfo
rdis
tanc
esbe
twee
n10
and
50km
GFO
radi
omet
er
DA
CM
OG
2DH
igh
Res
olut
ion
forc
edw
ithE
CM
WF
pres
sure
and
win
gfie
lds
(S1
and
S2w
ere
excl
uded
)+in
vers
eba
rom
eter
com
pute
dfr
omre
ctan
gula
rgri
ds
Tabl
e6
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(1
2)
Page 33
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
j2j1
j1n
tptp
ne1
e2en
enn
g2O
cean
tide
GO
T4v
7(S
1an
dS2
are
incl
uded
)Po
letid
e[W
ahr
1985
[53]
]So
lidea
rth
tide
Ela
stic
resp
onse
totid
alpo
tent
ial[
Car
twri
ghta
ndTa
yler
197
1[5]
][C
artw
righ
tand
Edd
en1
973[
6]]
Loa
ding
tide
GO
T4v
7(S
1pa
ram
eter
isin
clud
ed)
Sea
stat
ebi
asN
onpa
ram
etri
cSS
B[G
aspa
reta
l20
02[2
0]]
Non
para
met
ric
SSB
[NT
ran
and
al2
010[
51]]
BM
3[G
aspa
ran
dO
gor
1994
[17]
]
Non
para
met
ric
SSB
[Mer
tzet
al
2005
[38]
]
Non
para
met
ric
SSB
[Gas
pare
tal
2002
]w
ithG
DR
-Bst
anda
rds
forc
ycle
s9
to85
and
with
GD
R-C
stan
dard
sfr
omcy
cle
86
Non
para
met
ric
SSB
[NT
ran
etal
20
10[5
1]]
Orb
iter
ror
Glo
bal m
ulti-
mis
sion
cros
sove
rmin
imiz
atio
n(L
eTr
aon
and
Ogo
r19
98[3
2])
Lon
gw
ave-
leng
her
rors
Opt
imal
Inte
rpol
atio
n(L
eTr
aon
etal
19
98[3
1])
Inte
rcal
ibra
tion
Ref
eren
cefr
omcy
cle
11R
efer
ence
from
cycl
e1
to35
4C
orre
ctio
nof
regi
onal
bias
J2J
1de
duce
dfr
omin
terc
alib
ratio
nph
ase
(cyc
le11
J2)
Cor
rect
ion
ofgl
obal
biai
sJ1
TP
deacutedu
ced
from
inte
rcal
ibra
tion
phas
e(c
ycle
s11
J1)
Mea
npr
o-fil
e(s
eeII
I36
1)
Com
pute
dw
ithcy
cles
11-3
53T
Pda
taan
dw
ithcy
cles
11-2
50J1
data
ref
eren
ced
[199
319
99]
TP
J1 c
ompu
ted
with
cycl
es11
-353
TP
data
and
with
cycl
es11
-250
J1da
tar
efer
ence
d[1
993
1999
]T
PNJ
1Nc
ompu
ted
with
cycl
es36
9-47
9T
PNda
tar
efer
ence
d[1
993
1999
]
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
ref
eren
ced
[199
319
99]
EN
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
re
fere
nced
[199
319
99]
EN
Nu
seof
MSS
_CN
ES_
CL
S11
[39]
Com
pute
dw
ithcy
cles
37-1
87G
2da
ta
refe
renc
ed[1
993
1999
]
Peri
odof
use
from
cycl
e9
from
cycl
e9
cycl
es1
to48
1cy
cles
15to
43In
clud
ing
E-F
geod
etic
phas
es
cycl
es1
to83
from
cycl
e9
cycl
es37
to22
2
Tabl
e7
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(2
2)
Page 34
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III32 Acquisition
The acqusition process in Delayed time is much simpler than in Near Real time it consists in a synchronisa-tion process of all the auxiliary data required to homogenize propely the altimeter data sets The acquisitionstep uses the GDRs or the OPRs provided by the agencies
III33 Homogenization
The Homogenization process consists in applying the most recent corrections models and references rec-ommended for altimeter products Each mission is processed separately as its needs depend on the baseinput data The list of corrections and models currently applied is provided in tables 6 and 7 for DT data
III34 Input data quality control
The Input Data Quality Control is a critical process applied to guarantee that DUACS uses only the mostaccurate altimeter data Thanks to the high quality of current missions this process rejects a small percent-age of altimeter measurements but these erroneous data could be the cause of a significant quality lossThe quality control relies on standard raw data editing with quality flags or parameter thresholds but alsoon complex data editing algorithms based on the detection of erroneous artefacts mono and multi-missioncrossover validation and macroscopic statistics to edit out large data flows that do not meet the systemrsquosrequirements
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III35 Multi-mission cross-calibration
The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistentand accurate information It removes any residual orbit error (OE Le Traon and Ogor 1998[32]) or longwavelength error (LWE Le Traon et al 1998[31]) as well as large scale biases and discrepancies betweenvarious data flows
This process is based on two very different algorithms a global multi-mission crossover minimization fororbit error reduction (OER) and Optimal Interpolation (OI) for LWE
Multi-satellite crossover determination is performed on a daily basis All altimeter fields (measurementcorrections and other fields such as bathymetry MSS) are interpolated at crossover locations and datesCrossovers are then appended to the existing crossover database as more altimeter data become availableThis crossover data set is the input of the Orbit Error Reduction (OER) method Using the precision of thereference mission orbit a very accurate orbit error can be estimated LWE is mostly due to residual tidalor inverse barometer errors and high frequency ocean signals The OI used for LWE reduction uses preciseparameters derived from
bull accurate statistical description of sea level variability
bull localized correlation scales
bull mission-specific noise and precise assumptions on the long wavelength errors to be removed (from arecent analysis of one year of data from each mission)
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III36 Product generation
The product generation process is composed of four steps computation of raw SLA cross-validationfilteringampsub-sampling and generation of by-products
III361 Computation of raw SLA
Since the geoid is not well known yet the SSH cannot be used directly the SSH anomalies are used insteadThey are computed from the difference of the instantaneous SSH - a temporal reference This temporalreference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeattrack analysis cannot be used The errors affecting the SLAs MPs and MSS have different magnitudes andwavelengths The computation of the SLAs and their errors associated are detailed in Dibarboure et al 2010[9]
Use of a Mean ProfileIn the repeat track analysis (when the satellites flies over a repetitive orbit) measurements are re-sampledalong a theoretical ground track (or mean track) associated to each mission Then a Mean Profile (MP) issubtracted from the re-sampled data to obtain SLA The MP is a time average of similarly re-sampled dataover a long period
bull The Mean Profile used for TP (cycles 1 to 364) Jason-1 (cycles 1 to 259) and Jason-2 is computedwith 10 years of TP (cycles 11 to 353) and 6 years of Jason-1 (cycles 11 to 250)
bull The Mean Profile used for TP (cycles 368 to 481) and from Jason-1 cycle 262 to 374 (where satellitesare on interleaved ground-tracks) is computed with 3 years of TP (cycles 369 to 479)
bull The Mean Profile used for ERS-1 in its 35 days repetitive orbit mission ERS-2 and Envisat (only forthe first orbit before November 2010) is computed with 8 years of ERS-2 (cycles 1 to 85) and 6 yearsof Envisat (cycles 10 to 72)
bull No Mean Profile can be used for Envisat on its new orbit (enn) Jason-1 on its geodetic orbit (j1g)because there is no repetitive track The MSS must be used instead (see below)
bull The Mean Profile used for GFO is computed with 7 years of GFO cycles 37 to 187
Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible
bull Indeed as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide precise cross-track projection andor interpolation schemes are required to avoid errors
bull The mesoscale variability error (which is lt35 cm for MP between 3 to 5 years and lt1cm for WLof 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a prioriknowledge from Sea Level maps derived from previous iterations or from other missions
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PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for ERS-1 for its 168 days geodetic mission (phases E-F from April1994 to March 1995) or for Envisat since november 2010 because the satellite is not in a repetitive orbitphase The alternative is to use the MSS instead The gridded MSS is derived from along track MPs anddata from geodetic phases Thus any error on the MP is also contained in the MSS There are essentially 4types of additional errors on gridded MSS which are hard to quantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
III362 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III363 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
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III37 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III371 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
Page 39
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
IV MYOCEAN PRODUCTS
IV1 Near Real Time Products
The purpose of the NRT DUACS component is the acquisition of altimeter data from various altimeter mis-sions in near-real time (ie within a few days at most) the validation and correction of these altimeter datasets (ie edition and selection update of corrections and homogenization orbit error reduction) in order toproduce each day along-track productsProducts are as follows
Along-track products global and regional (Mediterranean and Black Seas Arctic Ocean and Europeareas)
bull Sea Level Anomaly (NRT-SLA) for each mission with NRT-SLA ephemeris
IV11 Delay of the products
The availability of the products in near real time is three to twelve hours after the measurement for along-track products Those products are delivered every day
IV12 Temporal availibility
The following table presents the available products by mission and by data periodNear real time products
NRT Jason-2 Jason-1 and Jason-1geodetic
Envisat new Cryosat-2
Temporal Time availability ymlowast
ongoingymlowast-20120303 for
repeat track and20120507-ongoing for
geodetic track
ymlowast
2012040820120101
ongoing
NRT-SLA X X X X
lowastym the temporal coverage for NRT products is fluctuating and depends on updates of Delayed Time prod-ucts When DT products are updated (3 to 4 times per year) the oldest NRT products are replaced by thebetter quality DT products so that the 2 series are overlapping on few weeks or few months
IV2 Delayed Time Products
The Delayed Time component of SSALTODUACS system is responsible for the production of processedJason-1 Jason-2 TP Envisat GFO ERS12 and even Geosat data in order to provide a homogeneousinter-calibrated and highly accurate long time series of SLA DT products are more precise than NRT products Two reasons explain this quality difference The firstone is the better intrinsic quality of the POE orbit used in the GDR processing The second reason is that
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in the DT DUACS processing the products can be computed optimally with a centred computation timewindow for OER LWE On the contrary in NRT case future data are not available so the computationtime window is not centred and therefore not optimalAs for NRT products improved altimeter corrections and processing algorithms are used ocean tide modelto correct altimeter data improved methods for orbit error reduction and mapping
Along-Track products global and regional (Mediterranean and Black Seas)
bull Sea Level Anomaly (DT-SLA) for each mission
IV21 Delay of the products
Weekly products are delivered The availability of the products in delayed time is at the best two monthsafter the date of the measurement The product generation needs all the GDR data of all the missions to takeinto account the best corrections as possible The time delay can be longer in the case of a missing mission
IV22 Temporal availibility
The following table presents the available products by mission and by data periodDelayed time SSALTODUACS products
Upd Jason-2 Jason-1new6
Jason-1 GFO Envisatnew6
Envisat ERS-16
ERS-2Topexnew6
Topex
TemporalTimeavailabil-ity
200810ymlowast
200902ymlowast
200204200810
200001200809
201010ymlowast
200210201010
199210200304
200209200510
199209200204
DT-SLA X X X X X X X X X
lowast ym those dates are updated regularly (3 to 4 times per year) and are avalaible when you download thedata at httpwwwmyoceaneuweb24-cataloguephp6 Jason-1 new orbit starting 200809 Envisat new orbit starting 201010 TP new orbit starting 200209 ERS-1The geodetic phases (E-F) are included There are no ERS-1 data between December 23 1993 and April 10 1994(ERS-1 phase D - 2nd ice phase) Note that during that time products are based only on TopexPoseidon data
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V DESCRIPTION OF THE PRODUCT SPECIFICATION
V1 General information
Product Specification SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001
Geographical coverage global
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 20-50km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001 Product Specification
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Product Specification SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002
Geographical coverage 55˚W-35˚E 30˚N-46˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002 Product Specification
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Product Specification SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003
Geographical coverage 27˚E-42˚E 40˚N-47˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003 Product Specification
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Product Specification SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004
Geographical coverage 25˚W-42˚E 21˚N-66˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004 Product Specification
Page 45
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Product Specification SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005
Geographical coverage 0˚W-360˚E 50˚N-82˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005 Product Specification
Page 46
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
VI NOMENCLATURE OF FILES
VI1 Nomenclature of files downloaded through the MyOcean Web PortalDirectgetfile Service
VI11 Nomenclature of the product line
The description of the syntax for the SL TAC SLA products line is given by
SEALEVEL_ltREGIONgt_SLA_L3_ltDELAYgt_OBSERVATIONS_008_ltZONEgt_ltLETTERgtwhere
REGION GLO global geographic coverage product
BS Black Sea products
MED Mediterranean products
ARC Arctic products (for NRT products)
EUROPE Europe products (for NRT products)
DELAY NRT near real time products
RAN delayed time or reanalysis products
ZONE 001 number on 3 digits
002
003
004
LETTER a letter on 1 digit
b
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VI12 Nomenclature of the datasets
The nomenclature used is
dataset-duacs-ltdelaygt-ltzonegt-ltmissiongt-lttype of slagt-l3where the fileds in ltgt are described below
delay nrt near-real time productsran delayed time products
zone global global geographic coverage productmedsea Mediterranean productsblacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1 (only for ran)e2 ERS-2 (only for ran)tp TOPEXPoseidon (only for ran)tpn TOPEXPoseidon on its new orbit (only for
ran)g2 GFO (only for ran)j1 Jason-1 (only for ran)j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisat (only for ran)enn Envisat on its new orbitc2 Cryosat-2 (only for nrt)
type of sla sla filtered slasla_unfiltered non filtered sla (only for ran products)
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VI13 Nomenclature of the NetCdf files
The nomenclature used is
ltdelaygt_ltzonegt_ltmissiongt_sla_ltvariablegt_ltdatebegingt_ltdateendgt_ltdateprodgtnc where the fileds in ltgt are de-scribed below
delay nrt near-real time productsdt delayed time products
zone global global geographic coverage productmed Mediterranean products (for dt)mfstep Mediterranean products (for nrt)blacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1e2 ERS-2tp TOPEXPoseidontpn TOPEXPoseidon on its new orbitg2 GFOj1 Jason-1j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisatenn Envisat on its new orbitc2 Cryosat-2
variable vfec filtered and sub-sampled slavxxc non filtered and non sub-sampled sla (only
for dt)datebegin YYYYMMDD() beginning date of the datasetdateend YYYYMMDD() end date of the datasetdateprod YYYYMMDD production date of the dataset
() For dt data as the dates in the file names are rounded the user wanting data for date T has to read the filescontaining dates T+1 and T-1 in their name and check inside the files if there are some data for date T
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
VII DATA FORMAT
This chapter presents the data storage format used for MyOcean products
VII1 NetCdf
The products are stored using the NetCDF format NetCDF (network Common Data Form) is an interface for array-oriented data access and a library that provides an implementation of the interface The netCDF library also definesa machine-independent format for representing scientific data Together the interface library and format support thecreation access and sharing of scientific data The netCDF software was developed at the Unidata Program Center inBoulder Colorado The netCDF libraries define a machine-independent format for representing scientific data Pleasesee Unidata NetCDF pages for more information and to retreive NetCDF software package onhttpwwwunidataucaredupackagesnetcdfindexhtml
NetCDF data is
bull Self-Describing A netCDF file includes information about the data it contains
bull Architecture-independent A netCDF file is represented in a form that can be accessed by computers with dif-ferent ways of storing integers characters and floating-point numbers
bull Direct-access A small subset of a large dataset may be accessed efficiently without first reading through allthe preceding data
bull Appendable Data can be appended to a netCDF dataset along one dimension without copying the dataset orredefining its structure The structure of a netCDF dataset can be changed though this sometimes causes thedataset to be copied
bull Sharable One writer and multiple readers may simultaneously access the same netCDF file
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VII2 Structure and semantic of NetCDF along-track files
The NetCDF Sea Level TAC files are based on the attribute data tags defined by the Cooperative OceanAtmosphereResearch Data Service (COARDS) and Climate and Forecast (CF) metadata conventions The CF convention gener-alises and extends the COARDS convention but relaxes the COARDS constraints on dimension and order and specifiesmethods for reducing the size of datasetsA wide range of software are available to write or read NetCDFCF files API are made available by UNIDATA(httpwwwunidataucaredusoftwarenetcdf)
bull CC++Fortran
bull Java
bull MATLAB Objective-C Perl Python R Ruby TclTk
In addition to these conventions the files are using a common structure and semantic
bull 1 dimension is defined
ndash time it is used to check NetCDF variables depending on time
bull 8 variables are defined
ndash short SLA contains the Sea Level Anomaly values for each time given
ndash int longitude contains the longitude for each measurement
ndash short track contains the track number for each measurement
ndash double time contains the time in days since 1950-01-01 000000 UTC for each measurement
ndash short mean_profile_point_index index of the corrsponding point in the track of the mean profile
ndash byte flag flag=0 the processed data comes from OGDR if flag=1 the processed data comes from theIGDR
ndash int latitude contains the latitude for each measurement
ndash short cycle contains the cycle number for each measurement
bull global attributes
ndash the global attributes gives information about the creation of the file
Example of a NetCDF sla file
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
netcdf nrt_global_j1_sla_vfec_20101230_20101230_20101230 dimensions
time = 10385 variables
short SLA(time) SLAcoordinates = longitude latitude SLAlong_name = Sea Level Anomaly SLA_FillValue = 32767s SLAadd_offset = 0 SLAscale_factor = 0001 SLAunits = m SLAstandard_name = sea_surface_height_above_sea_level
int longitude(time) longitudelong_name = Longitude of measurement longitude_FillValue = 2147483647 longitudeadd_offset = 0 longitudestandard_name = longitude longitudescale_factor = 1e-06 longitudeunits = degrees_east
short track(time) tracklong_name = Track in cycle the measurement belongs to track_FillValue = 32767s trackunits = 1 trackcoordinates = longitude latitude
double time(time) timelong_name = Time of measurement time_FillValue = 184467440737096e+19 timeaxis = T timestandard_name = time timeunits = days since 1950-01-01 000000 UTC
int latitude(time) latitudelong_name = Latitude of measurement latitude_FillValue = 2147483647 latitudeadd_offset = 0 latitudestandard_name = latitude latitudescale_factor = 1e-06 latitudeunits = degrees_north
short flag(time) flagcoordinates = longitude latitude flag_FillValue = 3267s flaglong_name = data origin flagflag_values = 1s 0s flagflag_meanings = igdr_like non_igdr_like flagcomment = The origin of the data is determined by the types of geophysical datarecords (GDR) used in computation of the SLA 1 for the Interim GDR (IGDR) and0 for Operational GDR (OGDR)
short cycle(time) cyclelong_name = Cycle the measurement belongs to cycle_FillValue = 32767s cycleunits = 1 cyclecoordinates = longitude latitude
global attributeshistory = 22-Feb-2011 155243 CET File created by the SSLATODUACS system version 1001 comment = Produce from ENVISAT Extension Phase satellite altimetry data institution = CLSCNES
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references = httpwwwavisooceanobscomfileadmindocumentsdatatoolshdbk_duacspdf source = satellite altimetry title = along track Sea Level Anomaly Conventions = CF-14
dataSLA =
7 7 11 10 -2 -22 -39 -41 -30 -13 -3 -5 -16 -26 -32 -35-35 -35 -37 -35 -31 -29 -31 -35 -32 -21 -10 -10 -19 -20 -1-69 -57 -49 -45 -39 -30 -28 -31 -27 -13 -2 -5 -15 -3 1112 3 -7 -10 -14 -15 -22 -31 -37 -32 -17 -10
longitude =74743328 74868400 74993968 75120040 75246616 7537372875501368 75629568 75758320 75887656 76017568 76148080 7627920876388952 76477056 76565456 76654144 76743128 76832400 76921984329429568 329535424 329641792 329748672 329856096 329964032330072512 330181536 330291072 330401184
track =92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 9292 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92113 113 113 113 113 113 113 113 113 113 113 113 113 113113 113 113 113 113 113 113 113 113
time =222780000565705 222780001314719 222780002063733222780002812747 222780003561761 222780004310775 222780005059788222780005808802 222780006557816 22278000730683 222780008055844222780008804858 222780009553872 22278001017805 222780010677393222788257112198 222788257486705 222788257861212 222788258235719222788258610226 222788258984733 222788259359239 222788259733746222788260108253 22278826048276
mean_profile_point_index =1872 1878 1884 1890 1896 1902 1908 19141920 1926 1932 1938 1944 1949 1953 1957 1961 1965 1969 19732306 2309 2312 2315 2318 2321 2327 2330 2333 2336 2339 23422345 2348 2351 2354 2357 2360 2363 2366
flag =0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
latitude =-16225506 -16539731 -16853833 -17167810 -17481660 -17795380-18108966 -18422418 -18735729 -19048899 -19361924 -19674801-19987527 -20248015 -20456329 -20664569 -20872739 -2108083739481297 39628277 39775133 39921866 40068472 40214953 4036130840507533 40653629 40799592 40945423 41091120 41236684 41382111
cycle =331 331 331 331 331 331 331 331 331 331 331 331 331
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331 331 331 331 331 331 331 331 331 331 331 331 331 331331 331 331 331 331 331 331 331 331 331 331 331
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VIII HOW TO DOWNLOAD A PRODUCT
VIII1 Download a product through the MyOcean Web Portal DirectgetfileService
You first need to register Please find below the registration stepshttpwwwmyoceaneuweb34-products-and-services-faqphp1Once registered the MyOcean FAQ httpwwwmyoceaneuweb34-products-and-services-faqwill guide you on How to download a product through the MyOcean Web Portal Directgetfile Service
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IX NEWS AND UPDATES
IX1 [Duacs] Operational news
To be kept informed on events occurring on the satellites and on the eventual interruption of the services of the DUACSprocessing system see the [Duacs] operational news on the Aviso websitehttpwwwavisooceanobscomendataoperational-newsindexhtml
IX2 Updates
To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtmlSince 2010 a complete reprocessing of all altimetry data (cumulated total of about 55 years of data) is available Themain changes introduced in the Duacs DT v300 reprocessed data set in SSALTODUACS reprocessed DT data setare listed herehttpwwwavisooceanobscomfileadmindocumentsdataduacsduacs_DT_2010_reprocessing_impactpdf
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LIST OF ACRONYMS
ATP Along-Track ProductADT Absolute Dynamic TopographyAVISO Archiving Validation and Interpretation of Satellite Oceanographic dataBGLO Biais Grande Longueur drsquoOndeCalVal Calibration - ValidationCERSAT Centre ERS drsquoArchivage et de TraitementCMA Centre Multimission Altimetry centerCORSSH CORrected Sea Surface HeightC2 Cryosat-2DAC Dynamic Atmospheric CorrectionDT Delayed TimeDTU Mean Sea Surface computed by Technical University of DanemarkDUACS Data Unification and Altimeter Combination SystemE1 ERS-1E2 ERS-2EN EnvisatENN Envisat on its non repetitive orbit (since cycle 94)ECMWF European Centre for Medium-range Weather ForecastingENACT ENhanced ocean data Assimilation and Climate predictionG2 Geosat Follow OnGIM Global Ionospheric MapsGDR Geophysical Data Record(s)IERS International Earth Rotation ServiceIGDR Interim Geophysical Data Record(s)J1 Jason-1J1N Jason-1 on its new orbit (since cycle 262)J1G Jason-1 on its geodetic orbit (since May 2012)J2 Jason-2JPL Jet Propulsion LaboratoryLAS Live Access ServerLWE Long Wavelength ErrorsMADT Map of Absolute Dynamic TopgraphyMDT Mean Dynamic TopographyMOE Medium Orbit EphemerisMP Mean ProfileMSLA Map of Sea Level AnomalyMSS Mean Sea SurfaceNRT Near-Real TimeOE Orbit ErrorOER Orbit Error ReductionOpendap Open-source Project for a Network Data Access ProtocolPF Polynom FitPODAAC Physical Oceanography Distributed Active Archive CentrePOE Precise Orbit EphemerisRD Reference DocumentSAD Static Auxiliary Data
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SI Signed IntegerSLA Sea Level AnomalySL TAC Sea Level Thematic Assembly CentreSSALTO Ssalto multimission ground segmentSSH Sea Surface HeightTAC Thematic Assembly CentreTP TopexPoseidonTPN TopexPoseidon on its new orbit (since cycle 369)
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REFERENCES
[1] Andersen O B The DTU10 Gravity filed and Mean sea surface (2010) Second international sympo-sium of the gravity field of the Earth (IGFS2) Fairbanks Alaska
[2] Boy F et al (2011) Cryosat LRM TRK and SAR processing Presented at the 2011 Ocean Sur-face Topography Science Team meeting httpwwwavisooceanobscomfileadmindocumentsOSTST2011oral01_Wednesday
[3] Carrere L F Lyard 2003 Modeling the barotropic response of the global ocean to atmo-spheric wind and pressure forcing- comparisons with observations J Geophys Res 30(6) 1275doi1010292002GL016473
[4] Carrere L 2003 Etude et modeacutelisation de la reacuteponse HF de lrsquooceacutean global aux forccedilagesmeacuteteacuteorologiques PhD thesis Universiteacute Paul Sabatier (Toulouse III France) 318 pp
[5] Cartwright D E R J Tayler 1971 New computations of the tide-generating potential Geophys JR Astr Soc 23 45-74
[6] Cartwright D E A C Edden 1973 Corrected tables of tidal harmonics Geophys J R Astr Soc33 253-264
[7] Following the scientific recommendations from the OSTST meeting (San Diego October 2011) theESA Cryosat Project and the CNES SALP Project have been collaborating to generate these Cryosat-derived L3 and L4 products Level 1B and Level 2 products derived from CNES processors are notdistributed by AVISO as per the CNES ESA agreement
[8] Dibarboure G C Renaudie M-I Pujol S Labroue N Picot 2011 A demonstrationof the potential of Cryosat-2 to contribute to mesoscale observation J Adv Space Resdoi101016jasr201107002 httpdxdoiorg101016jasr201107002
[9] Dibarboure G P Schaeffer P Escudier M-IPujol JF Legeais Y Faugegravere R Morrow JK WillisJ Lambin JP Berthias N Picot 2010 Finding desirable orbit options for the Extension of Lifephase of Jason-1 Submitted to Marine Geodesy
[10] Dibarboure G M-IPujol FBriol PYLe Traon GLarnicol NPicot FMertz P Escudier MAblainCDufau 2010 Jason-2 in DUACS first tandem results and impact on processing and products Sub-mitted in Marine Geodesy
[11] Dibarboure G 2009 Using short scale content of OGDR data improve the Near Real Time productsof SsaltoDuacs oral presentation at Seattle OSTST meeting (pdf)
[12] Dorandeu J M Ablain Y Faugegravere F Mertz B Soussi and P Vincent 2004 Jason-1 global statisti-cal evaluation and performance assessment Calibration and cross-calibration results Marine Geodesy27(3-4) 345-372
[13] Dorandeu J M Ablain P-Y Le Traon 2003 Reducing Cross-Track Geoid Gradient Errors aroundTOPEXPoseidon and Jason-1 Nominal Tracks Application to Calculation of Sea Level AnomaliesJ of Atmosph and Ocean Techn20 1826-1838
[14] Dorandeu J and P-Y Le Traon 1999 Effects of global mean atmospheric pressure variations onmean sea level changes from TOPEXPoseidon J Atmos Oceanic Technol 16 1279-1283
[15] Ducet N P-Y Le Traon and G Reverdin 2000 Global high resolution mapping of ocean circulationfrom TOPEXPoseidon and ERS-1 and -2 J Geophys Res 105 19477-19498
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[16] Egbert Gary D Svetlana Y Erofeeva 2002 Efficient Inverse Modeling of Barotropic Ocean Tides JAtmos Oceanic Technol 19 183-204 doi 1011751520-0426(2002)019lt0183EIMOBOgt20CO2
[17] Gaspar P and F Ogor Estimation and analysis of the Sea State Bias of the ERS-1 altimeter Reportof task B1-B2 of IFREMER Contract n˚ 942426 016C 1994
[18] Gaspar P F Ogor and C Escoubes 1996 Nouvelles calibration et analyse du biais drsquoeacutetat de mer desaltimegravetres TOPEX et POSEIDON Technical note 96018 of CNES Contract 951523 1996
[19] Gaspar P and F Ogor Estimation and analysis of the Sea State Bias of the new ERS-1 and ERS-2altimetric data (OPR version 6) Report of task 2 of IFREMER Contract n˚ 962246 002C 1996
[20] Gaspar P S Labroue and F Ogor 2002 Improving nonparametric estimates of the sea state bias inradar altimeter measurements of seal level J Atmos Oceanic Technology 19 1690-1707
[21] Hernandez F P-Y Le Traon and R Morrow 1995 Mapping mesoscale variability of the AzoresCurrent using TOPEXPOSEIDON and ERS-1 altimetry together with hydrographic and Lagrangianmeasurements Journal of Geophysical Research 100 24995-25006
[22] Hernandez F and P Schaeffer 2000 Altimetric Mean Sea Surfaces and Gravity Anomaly maps inter-comparisons AVI-NT-011-5242-CLS 48 pp CLS Ramonville St Agne
[23] Hernandez F M-H Calvez J Dorandeu Y Faugegravere F Mertz and P Schaeffer 2000 Sur-face Moyenne Oceacuteanique Support scientifique agrave la mission altimeacutetrique Jason-1 et agrave une mis-sion micro-satellite altimeacutetrique Contrat SSALTO 2945 - Lot 2 - A1 Rapport drsquoavancementCLSDOSNT00313 40 pp CLS Ramonville St Agne
[24] Iijima BA IL Harris CM Ho UJ Lindqwiste AJ Mannucci X Pi MJ Reyes LC SparksBD Wilson 1999 Automated daily process for global ionospheric total electron content maps andsatellite ocean altimeter ionospheric calibration based on Global Positioning System data J AtmosSolar-Terrestrial Physics 61 16 1205-1218
[25] Labroue S F Boy N Picot M Urvoy M Ablain First quality assessment of the Cryosat-2 altimetricsystem over ocean J Adv Space Res 2011 doi101016jasr201111018 httpdxdoiorg101016jasr201111018
[26] Labroue S 2007 RA2 ocean and MWR measurement long term monitoring 2007 report for WP3Task 2 - SSB estimation for RA2 altimeter Contract 1729303I-OL CLS-DOS-NT-07-198 53ppCLS Ramonville St Agne
[27] Labroue S P Gaspar J Dorandeu OZ Zanifeacute F Mertz P Vincent and D Choquet 2004 Nonparametric estimates of the sea state bias for Jason-1 radar altimeter Marine Geodesy 27 453-481
[28] Lagerloef GSE GMitchum RLukas and PNiiler 1999 Tropical Pacific near-surface currentsestimated from altimeter wind and drifter data J Geophys Res 104 23313-23326
[29] Le Traon P-Y and F Hernandez 1992 Mapping the oceanic mesoscale circulation validation ofsatellite altimetry using surface drifters J Atmos Oceanic Technol 9 687-698
[30] Le Traon P-Y P Gaspar F Bouyssel and H Makhmara 1995 Using TopexPoseidon data to en-hance ERS-1 data J Atmos Oceanic Technol 12 161-170
[31] Le Traon P-Y F Nadal and N Ducet 1998 An improved mapping method of multisatellite altimeterdata J Atmos Oceanic Technol 15 522-534
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[32] Le Traon P-Y and F Ogor 1998 ERS-12 orbit improvement using TOPEXPOSEIDON the 2 cmchallenge J Geophys Res 103 8045-8057
[33] Le Traon P-Y and G Dibarboure 1999 Mesoscale mapping capabilities of multi-satellite altimetermissions J Atmos Oceanic Technol 16 1208-1223
[34] Le Traon P-Y G Dibarboure and N Ducet 2001 Use of a High-Resolution Model to Analyze theMapping Capabilities of Multiple-Altimeter Missions J Atmos Oceanic Technol 18 1277-1288
[35] Le Traon PY and G Dibarboure 2002 Velocity mapping capabilities of present and future altimetermissions the role of high frequency signals J Atmos Oceanic Technol 19 2077-2088
[36] Le Traon PY Faugegravere Y Hernandez F Dorandeu J Mertz F and M Ablain 2002 Can we mergeGEOSAT Follow-On with TOPEXPOSEIDON and ERS-2 for an improved description of the oceancirculation J Atmos Oceanic Technol 20 889-895
[37] Le Traon PY and G Dibarboure 2004 An Illustration of the Contribution of the TOPEXPoseidon-Jason-1 Tandem Mission to Mesoscale Variability Studies Marine Geodesy 27 (1-2)
[38] Mertz F F Mercier S Labroue N Tran J Dorandeu 2005 ERS-2 OPR data quality assessment Long-term monitoring - particular investigation CLSDOSNT-06001 (pdf)
[39] MSS_CNES_CLS11 was produced by CLS Space Oceanography Division and distributed by Avisowith support from Cnes (urlhttpwwwavisooceanobscom)
[40] Pascual A Y Faugegravere G Larnicol P-Y Le Traon 2006 Improved description of the oceanmesoscale variability by combining four satellite altimeters Geophys Res Lett 33
[41] Pascual A C Boone G Larnicol and P-Y Le Traon 2009 On the quality of Real-Time altimetergridded fields comparison with in-situ data Journ of Atm and Ocean Techn Vol 26(3) pp 556-569DOI 1011752008JTECHO5561
[42] Prandi P M Ablain A Cazenave N Picot 2011 A new estimation of mean sea level in the ArcticOcean from satellite altimetry Submitted to Marine Geodesy
[43] Pujol M-I et al 2009 Three-satellite quality level restored in NRT poster at OSTST meeting (pdf)
[44] Ray R 1999 A Global Ocean Tide model from TOPEXPoseidon Altimetry GOT992 NASA TechMemo NASATM-1999-209478 58 pp Goddard Space Flight Center NASA Greenbelt MD USA
[45] Rio M-H and F Hernandez 2003 A Mean Dynamic Topography computed over the worldocean from altimetry in-situ measurements and a geoid model J Geophys Res 109 C12032doi1010292003JC002226
[46] Rio M-H and F Hernandez 2003 High frequency response of wind-driven currents measured bydrifting buoys and altimetry over the world ocean J Geophys Res 108 39-1
[47] Rio M-H 2003 Combinaison de donneacutees in situ altimeacutetriques et gravimeacutetriques pour lrsquoestimationdrsquoune topographie dynamique moyenne globale Ed CLS PhD Thesis University Paul Sabatier(Toulouse III France) 260pp
[48] Scharroo R and P Visser 1998 Precise orbit determination and gravity field improvement for theERS satellites J Geophys Res 103 8113-8127
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[49] Scharroo R J Lillibridge and WHF Smith 2004 Cross-calibration and long-term monitoring ofthe Microwave Radiometers of ERS Topex GFO Jason-1 and Envisat Marine Geodesy 97
[50] Tran N and E Obligis December 2003 Validation of the use of ENVISAT neural algorithms onERS-2 CLSDOSNT03901
[51] Tran N S Labroue S Philipps E Bronner and N Picot 2010 Overview and Update of the SeaState Bias Corrections for the Jason-2 Jason-1 and TOPEX Missions Marine Geodesy accepted
[52] Vincent P Desai SDDorandeu J Ablain M Soussi B Callahan PS and BJ Haines 2003 Jason-1 Geophysical Performance Evaluation Marine Geodesy 26 167-186
[53] Wahr J W 1985 Deformation of the Earth induced by polar motionJ of Geophys Res (Solid Earth)90 9363-9368
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I INTRODUCTION
MyOcean is a European Network project aiming at monitoring analyzing and forecasting the Ocean Ituses satellite and in-situ data to describe the ocean in 3 dimensions and real time More information can befound on httpwwwmyoceaneuorgThe aim of this document is to describe the products delivered by the Sea Level TAC (Thematic AssemblyCentre) which is one of the five TAC of the MyOcean projectThe data produced in the frame of this TAC are generated by the processing system named DUACS (DataUnification and Altimeter Combination System)DUACS is part of the CNES multi-mission ground segment (SSALTO) It processes data from all altimetermissions Cryosat-2 OSTMJason-2 Jason-1 TopexPoseidon Envisat GFO ERS-1amp2 and even GeosatAt this time (May 25th 2012) DUACS is using three different altimeters in near real time Developed and operated by CLS it started as an European Commission Project (Developing Use Of Altime-try for Climate Studies) funded under the European Commission and the Midi-Pyreacuteneacutees regional councilIt has been integrated to the CNES multi-mission ground segment SSALTO in 2001 and it is maintainedupgraded and operated with funding from CNES with shared costs from EU projectsAt the beginning of 2004 DUACS was redefined as the Data Unification Altimeter Combination System
Figure 1 DUACS and AVISO a user-driven altimetry service
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The products lines described in this user manual are the followingSEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005
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The data provided to users have a global coverage (PL SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001)and regional products are also computed over specific areasMediterranean Sea (PL SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002)and Black Sea (PL SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003)Thanks to updates in 2011 and 2012 (see section II) new regional products are now availableEurope (PL SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004)and Arctic (PL SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005)
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II UPDATES IN 2011 AND 2012
This section describes the updates of the SSALTODUACS Near Real Time system that occurred during2011 and 2012 allowing to add new products (Europe and Arctic) the integration of the Cryosat-2 data inthe system the stopping delivery of Envisat data the addition of Jason-1 data on geodetic orbit (j1g)To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtml
II1 Version D of input IGDROGDR Jason-2 data for NRT processing(July 30 2012)
On July 30 2012 the version of Jason-2 IGDROGDR has changed and is now the D version Somecorrections have thus been updated as detailed in tables 3 and 4
II2 Integration of Jason-1 on its geodetic orbit (May 2012)
An anomaly occured on March 3rd 2012 on the Jason-2 mission (see httpwwwavisooceanobscomfractualitesactualitesindexhtmltx_ttnews[tt_news]=1162amptx_ttnews[backPid]=1399ampcHash=d5baeb645e) On April 23rd CNES began to command the satellite into a nadir ori-entation and after some propulsion anomalies CNES and NASA management through the Joint SteeringGroup have directed the Jason-1 Project to then begin a series of maneuvers to place Jason-1 into a neworbit as defined in table 1 After checking the current orbit carefully the operational team determined thata geodetic mission was still possible It was also decided to preserve all remaining fuel for future stationkeeping maneuvers which is mandatory in a geodetic orbit Core payloads were switched ON on May 4thand after some POSEIDON2 radar (PRF) adjustments the mission was resumed on May 7th at 151248UTCBelow are the characteristics of the new orbit which will be maintained as before within +- 1km controlbox at the Equator
Semi major axis 7702437 kmEccentricity 13 to 28 10-4Altitude equator 13240 kmOrbital period 6730s (1h52rsquo10rdquo)Inclination 66042˚Cycle 406 daysSub cycles 39 - 109 - 475 - 1795
days
Table 1 Characteristics of the geodetic orbit for Jason-1 since May 7th 2012
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For this new phase of the Jason-1 mission (called j1g) the cycle numbering will restart at 500 Off-lineproducts will be produced once a day for the IGDR and every 11 days for the GDRrsquos The integration ofJason-1 data in the DUACS system is available since May 25th 2012
II3 Envisat has stopped sending data (April 2012)
Since April 8th 2012 Envisat has stopped sending data to Earth Esarsquos mission control has worked tore-establish contact with the satellite but there has been no reaction from the satellite Thus Esa has de-clared officially the end of mission for Envisat (see httpwwwesaintesaCPSEM1SXSWT1H_index_0html) Therefore no SL TAC NRT data from Envisat can be released since this date
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II4 Integration of the Cryosat2 Mission (February 2012)
Since February 6th 2012 Cryosat-2 mission has been integrated in the DUACS sytem This mission isdedicated to the observation of the floating sea-ice as well as the continental ice sheets but all data acquiredover ocean are valuable for the observation of oceanic circulation and mesoscale variations This majorchange is the result of the long-standing and fruitful partnership between ESA and CNES and a responseto the request from scientific and operational oceanography users [7] The integration of Cryosat-2 impactsthe delivering of Near real time Sea Level Anomalies (SLA)
II41 Generalities about the mission
A Cryosat-2 Processing Prototype (C2P) (described in Boy et al 2011 [2]) has been developed on CNESside to lay the ground for various SAR processing studies The processing chains ingest Level-0 telemetryfiles distributed by ESA and perform the following steps to generate Sea Level Anomalies (SLA) values foreach altimeter measurements
bull Level-1 Decommutation time-tagging and localization of measurements
bull Level-1b Calculation of instrumental corrections and geophysicalmeteorological corrections
bull Level-2 MLE4 waveforms Retracking and calculation of SLA
The prototype processes data almost continuously over ocean either in Low Resolution Mode (LRM) or inthe DopplerSAR mode processed as pseudo-LRM mode allowing to increase the coverage (figure 2)
Figure 2 SSH-MSS for Cryosat-2 with LRM mode only (left) or LRM+pseudo-LRM modes (right)
Although Cryosat-2 raw SSH can be only corrected with GPS-derived ionospheric correction and ECMWFwet troposphere correction validation activities showed (Labroue et al 2011 [25]) that C2P outputs have anaccuracy roughly equivalent to Envisatrsquos Level 2 products if the latter are processed with the same standards
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II42 Integration in DUACS
The Cryosat-2 data are included in the Near Real time process The chain delivers now (for global coverageMediterranean and Black Seas) along track data from Cryosat-2 (SLAs) Note that the products distributedare of Level-3 and donrsquot replace Level-2 products distributed by agenciesThe details of the processing are given in Dibarboure et al 2011 [8]Here we just give an overview the data are computed with the corrections given in section III21 Thefiltering and sub-sampling of SLAs (section III263) are detailed in [8]
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II5 Addition of Europe and Arctic products (January 2012)
Since the MyOcean V2 two new along-track products are computed in Near Real Time intended foraddressing the needs of data assmilation and validation in regional models
bull Following the TAPAS (Tailored Altimeter Product for Assimilation Systems) initiative launched bySL TAC with all the Modeling and Forecasting Centers (MFCs) the Europe regional products (PLSEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004) have been proposed (figure 3) They areavailable in Near Real Time onlyThey are studied to partly fulfil the needs of the Centers with adapted filtering and resolution Thoseparameters have been tuned in order to provide boundary conditions for the Atlantic assimilationmodels They are different from the ones used for Mediterranean and Black Seas products If you needto study the Mediterranean Sea or the Black Sea yoursquod better use the dedicated products describedabove since the processing parameters have been fitted to be adapted to the dynamics of the ocean inthose regions
Figure 3 Coverage of the Europe product for Jason-1 Jason-2 and Envisat from August 18th to September9th 2011
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bull The Arctic along-track products (PL SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005) coverlatitudes between 45 and 82 degrees (figure 4) They are available in Near Real Time only
Figure 4 Coverage of the Arctic region with Envisat from October 28th 2011 to January 3rd 2012
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III SSALTODUACS SYSTEM
III1 Introduction
This chapter presents the input data used by SSALTODUACS system and an overview of the different pro-cessing steps necessary to produce the output dataSSALTODUACS system is made of two components a Near Real Time one (NRT) and a Delayed Time(DT) oneIn NRT the systemrsquos primary objective is to provide operational applications with directly usable high qual-ity altimeter data from all missions availableIn DT it is to maintain a consistent and user-friendly altimeter database using the state-of-the-art recom-mendations from the altimetry communityFollowing figure gives an overview of DUACS system where processing sequences can be divided into 7main steps
bull acquisition
bull homogenization
bull input data quality control
bull multi-mission cross-calibration
bull product generation
bull merging
bull final quality control
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Figure 5 SSALTODUACS processing sequences
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III2 Near Real Time processing steps
III21 Input data models and corrections applied
To produce SLA in near-real time the DUACS system uses two flows based on the same instrumental mea-surements but with a different quality
bull The IGDR that are the latest high-quality altimeter data produced in near-real-time
bull The OGDR that includes real time data (OSTMJason-2 and Jason-1 OSDR) to complete IGDR Thesefast delivery products do not always benefit from precise orbit determination nor from some exter-nal model-based corrections (Dynamic Atmospheric Correction (DAC) Global Ionospheric Maps(GIM))
Integration of OGDR data and the introduction of Jason-2Jason-1 tandem increased the resilience and pre-cision of the system A better restitution of ocean variability is observed especially in high energetic areas
Altimetric product Source Availability Type of orbit
Jason-2 IGDR CNES ~24h CNES MOE GDR-Cuntil 20120730
CNES MOE GDR-Dsince 20120731
OGDR NOAAEUMETSAT ~3 to 5 h
Jason-1 IGDR CNESNASA ~48 h CNES MOE GDR-Dsince 20120507
OGDR CNESNASA ~3 to 12 h
Envisat IGDR ESACNES not deliveredsince 20120408
CNES MOE GDR-Dsince 20120121
FDGDR ESA not deliveredsince 20120408
Cryosat-2 IGDR-like ESACNES ~48 h CNES MOE GDR-D
not delivered
Table 2 SSALTODUACS Near-Real Time Input data overview
See Figure 6 Overview of the near real time system data flow management
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DUACS 2011 NRT product from IGDR1
j2 j1nj1g enn c2Productstandard ref
version C until20120730 and D after
version C version 21 CPP [2]
Orbit CNES MOE GDR-Cuntil 20120730
GDR-D after
CNES MOE GDR-C forj1n and CNES MOE
GDR-D for j1g
CNES MOE GDR-Dfrom 20120121 to
20120408
CNES MOE GDR-D
Ionopheric bi-frequency altimeter range measurements GIM model for cgt64 (Iijima et al1998[24])Dry tropo Model computed from ECMWF Gaussian grids (new S1 and S2 atm tides applied)Wet tropo-sphere
AMR radiometer(enhancement in coastal
regions since20120730)
JMR radiometer MWR radiometer andcorrected from side
lobes
Model computed fromECMWF Gaussian
grids
DAC MOG2D High Resolution forced with ECMWF pressure and wind fields (S1 and S2 wereexcluded) (Carrere and Lyard 2003[3])+ inverse barometer Filtering temporal window is
un-centered (no data in the future)Ocean tide GOT4v8 (S1 and S2 are included) and TPX 072 [16] for Arctic productsPole tide [Wahr 1985 [53]]Solid earthtide
Elastic response to tidal potential [Cartwright and Tayler 1971[5]] [Cartwright andEdden 1973[6]]
Loading tide GOT4v8 (S1 and S2 are included)Sea statebias
Non parametric SSB[Labroue 2004[27]](with cycles J1 1 to 11
using GDR-B standardsuntil 20120730 andderived from Jason-2
after)
Non parametric SSB[Labroue 2004[27]](with cycles 1 to 21
using GDR-Bstandards)
Non parametric SSB[Labroue 2004[27]](with cycles 41 to 60
using GDR-Bstandards)
Same as Jason-2 SSB
Orbit error Global multi-mission crossover minimization (Le Traon and Ogor1998[32])
Long wave-lengh errors
Optimal Interpolation [Le Traon et al 1998[31]]
Intercalibration Reference from cycle20
Mean pro-file (seeIII261)
Computed with cycles11-353 TP data andwith cycles 11-250J1 data referenced[19931999]
TPNJ1N computedwith cycles 369-479TPN data refer-enced [19931999]J1G No MP can beused instead theMSS_CNES_CLS11[39] is used
No Mean Profilecan be used forEnvisat on its neworbit Instead theMSS_CNES_CLS11[39] is used
No Mean Profilecan be used forCryosat-2 Instead theMSS_CNES_CLS11[39] is used
(1) A flag included in the along-track files indicates the source of the production (OGDRFDGDR orIGDR) If flag=0 the processed data comes from OGDRsFDGDRs if flag=1 the processed data comesfrom IGDRs
Table 3 Corrections and models applied in SSALTODUACS NRT products produced from IGDRs
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DUACS 2011 NRT product from OGDR or FDGDR2
j2 j1nj1g ennProduct stan-dard ref
version C until 20120730and D after
version C version 21
Orbit Navigator Extrapolated CNES MOEGDR-D since 20120121
Ionopheric From-dual frequency altimeter range measurements From GIM model fromcycle 65 (Iijima et al1998 [24])
Dry troposphere Model computed from ECMWF Gaussian grids (new S1 and S2 atmospherictides are applied)
Wet tropo-sphere
AMR radiometer(enhancement in coastal
regions since 20120730)
JMR radiometer MWR radiometer andcorrected from side lobes
DAC Inverse Barometer forecastedOcean tide GOT4v8 (S1 and S2 are included) and TPX 072 [16] for Arctic productsPole tide [Wahr 1985 [53]]Solid earth tide Elastic response to tidal potential [Cartwright and Tayler 1971[5]]
[Cartwright and Edden 1973[6]]Loading tide GOT4v8 (S1 and S2 are included)Sea state bias Non parametric SSB
[Labroue 2004[27]] (withcycles J1 1 to 11 usingGDR-B standards until20120730 and derivedfrom Jason-2 after)
Non parametric SSB[Labroue 2004[27]](with cycles 1 to 21 usingGDR-B standards)
Non parametric SSB[Labroue 2004[27]](with cycles 41 to 60using GDR-B standards)
Orbit error Specific filtering of long-wavelength signal3
Long wave-lengh errors
Optimal Interpolation [Le Traon et al 1998[31]]
Intercalibration Reference from cycle 20Mean profile(see III261)
Computed with cycles 11-353 TP data and with cy-cles 11-250 J1 data refer-enced [19931999]
TPNJ1N computedwith cycles 369-479TPN data referenced[19931999] J1G NoMP can be used insteadthe MSS_CNES_CLS11[39] is used
No Mean Profile can beused for Envisat on itsnew orbit Instead theMSS_CNES_CLS11 [39]is used
(2) A flag included in the along-track files indicates the source of the production (OGDRFDGDR orIGDR) If flag=0 the processed data comes from OGDRsFDGDRs if flag=1 the processed data comesfrom IGDRs(3) Specific data processing was applied on long wave-length signal (sectIII23 of the user manual)
Table 4 Corrections and models applied in SSALTODUACS NRT products produced from OG-DRsFDGDRs
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III22 Acquisition
The acquisition process is twofold
bull straightforward retrieval and reformatting of altimeter data and dynamic auxiliary data (pressure andwet troposphere correction grids from ECMWF are provided by Meteo France TEC grids from JPLNRT MOG2D corrections) from external repositories
bull synchronisation process
To be homogenized properly altimeter data sets require various auxiliary data The acquisition softwaredetects downloads and processes incoming data as soon as they are available on remote sites (externaldatabase FTP site) Data are split into passes if necessary If data flows are missing or late the synchroni-sation engine put unusable data in waiting queues and automatically unfreezes them upon reception of themissing auxiliary data This processing step delivers raw data that is to say data that have been dividedinto cycles and passes and ordered chronologicallyFrom SSALTODUACS V80 the acquisition step uses two different data flows in near-real time the OGDRflow (within a few hours) and the IGDR flow (within a few days)For each OGDR input the system checks that no equivalent IGDR entry is available in the data base beforeacquisition for each IGDR input the system checks and delete the equivalent OGDR entry in the data baseThese operations aim to avoid duplicates in SSALTODUACS system
Figure 6 Overview of the near real time system data flow management
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III23 Homogenization
The Homogenization process consists in applying the most recent corrections models and references rec-ommended for altimeter products Each mission is processed separately as its needs depend on the baseinput data The list of corrections and models currently applied is provided in tables 3 and 4 for NRT dataThe system includes SLA filtering to process OGDR data DUACS extract from these data sets the shortscales (space and time) which are useful to better describe the ocean variability in real time and merge thisinformation with a fair description of large scale signals provided by the multi-satellite observation in nearreal time (read IGDR-based DUACS data) Finally an hybrid SLA is computed
Figure 7 Merging pertinent information from IGDR and OGDR processing
III24 Input data quality control
The Input Data Quality Control is a critical process applied to guarantee that DUACS uses only the mostaccurate altimeter data Thanks to the high quality of current missions this process rejects a small percent-age of altimeter measurements but these erroneous data could be the cause of a significant quality lossThe quality control relies on standard raw data editing with quality flags or parameter thresholds but alsoon complex data editing algorithms based on the detection of erroneous artefacts mono and multi-missioncrossover validation and macroscopic statistics to edit out large data flows that do not meet the systemrsquosrequirements
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III25 Multi-mission cross-calibration
The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistentand accurate information It removes any residual orbit error (OE Le Traon and Ogor 1998[32]) or longwavelength error (LWE Le Traon et al 1998[31]) as well as large scale biases and discrepancies betweenvarious data flows
This process is based on two very different algorithms a global multi-mission crossover minimization fororbit error reduction (OER) and Optimal Interpolation (OI) for LWE
Multi-satellite crossover determination is performed on a daily basis All altimeter fields (measurementcorrections and other fields such as bathymetry MSS) are interpolated at crossover locations and datesCrossovers are then appended to the existing crossover database as more altimeter data become availableThis crossover data set is the input of the Orbit Error Reduction (OER) method Using the precision of thereference mission orbit a very accurate orbit error can be estimated This processing step does not concernOGDR dataLWE is mostly due to residual tidal or inverse barometer errors and high frequency ocean signals The OIused for LWE reduction uses precise parameters derived from
bull accurate statistical description of sea level variability
bull localized correlation scales
bull mission-specific noise and precise assumptions on the long wavelength errors to be removed (from arecent analysis of one year of data from each mission)
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III26 Product generation
The product generation process is composed of four steps computation of raw SLA cross-validationfilteringampsub-sampling and generation of by-products
III261 Computation of raw SLA
Since the geoid is not well known yet the SSH cannot be used directly the SSH anomalies are used insteadThey are computed from the difference of the instantaneous SSH - a temporal reference This temporalreference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeattrack analysis cannot be used The errors affecting the SLAs MPs and MSS have different magnitudes andwavelengths The computation of the SLAs and their errors associated are detailed in Dibarboure et al 2010[9]
Use of a Mean ProfileIn the repeat track analysis (when the satellites flies over a repetitive orbit) measurements are re-sampledalong a theoretical ground track (or mean track) associated to each mission Then a Mean Profile (MP) issubtracted from the re-sampled data to obtain SLA The MP is a time average of similarly re-sampled dataover a long period
bull The Mean Profile used for Jason-2 is computed with 10 years of TP (cycles 11 to 353) and 6 years ofJason-1 (cycles 11 to 250)
bull The Mean Profile used from Jason-1 cycle 262 to 374 (where satellites are on interleaved ground-tracks) is computed with 3 years of TP (cycles 369 to 479)
bull No Mean Profile can be used for Envisat on its new orbit (enn) Jason-1 on its geodetic orbit (j1g) norfor Cryosat-2 mission (c2) because there is no repetitive track The MSS must be used instead (seebelow)
Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible
bull Indeed as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide precise cross-track projection andor interpolation schemes are required to avoid errors
bull The mesoscale variability error (which is lt35 cm for MP between 3 to 5 years and lt1cm for WLof 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a prioriknowledge from Sea Level maps derived from previous iterations or from other missions
bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for Envisat since november 2010 and for Cryosat-2 mission (c2)because the satellite is not in a repetitive orbit phase The alternative is to use the MSS instead The griddedMSS is derived from along track MPs and data from geodetic phases Thus any error on the MP is alsocontained in the MSS There are essentially 4 types of additional errors on gridded MSS which are hard toquantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
Note that for the Arctic regional products the DTU10 MSS [1] is taken into account instead of the CLS01MSS Indeed the accuracy of DTU10 compared to CLS01 is further demonstrated by the significant sealevel anomaly variance reduction found over the whole Arctic Ocean as shown in Prandi et al [42]
III262 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III263 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
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III27 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III271 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
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III272 Performance indicators
To appreciate the quality situation of the DUACS system new performance indicators are computed dailyThey aim at evaluate the status of the main processing steps of the system the input data availability theinput data coverage the input data quality and the output product quality These indicators are computed foreach and every currently working satellite and combined to obtain the overall status
Figure 8 Example with the key performance indicator on 20090627
See the description the latest and previous indicators on Aviso websitehttpwwwavisooceanobscomindexphpid=1516
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PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III3 Delayed Time processing steps
III31 Input data models and corrections applied
Delayed Time MyOcean products are generated
bull from Aviso GDR products for TP Jason-1 Jason-2 and Envisat (GDR-A cycles 1 to 22 GDR-Bcycles 23 to 85 GDR-C from cycle 86)
bull from NOAA GDR for GFO and from CERSAT (IFREMER) OPR for ERS-1 and ERS-2 (phases C(1st 35-day repeat orbit period) phase E and F (geodetic phases) phase G for ERS-1 (last 35-dayrepeat orbit period tandem phase with ERS-2 phase A for ERS-2 (1st 35-day repeat orbit periodtandem phase with ERS-1))
All GDR products are computed with a Precise Orbit Ephemeris (POE) and are delivered within 2 to 3months depending on the mission For several missions an updated orbit is used
bull For ERS-1amp-2 the orbit used is DGME-04 provided by Delft Institute (httpwwwdeostudelftnl)until June 2003
bull For TopexPoseidon the orbit used is GSFC (std0809) for the whole mission
bull For Envisat CNES POE of GDR-C standard is used for the whole mission
bull For the whole GFO mission the orbit used is GSFC (std0809) and when not available NASA POE isused
Altimetric product Source Availability Type of orbit
TopexPoseidon GDR NASACNES - GSFC POE
Jason-1 GDR (GDR-C) CNESNASA ~40 days CNES POE
Jason-2 GDR (GDR-C) CNESNASA ~60 days CNES POE
GFO GDR NOAA - GSFCNASA POE
ERS-1amp2 IFREMERESA - DGME-04
Envisat (GDR-A GDR-B andGDR-C from cycle 86)
ESA ~2 months CNES POE
Table 5 SSALTODUACS Delayed Time Input data overview
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
DU
AC
S20
11D
Tpr
oduc
t(gtV
30
0)j2
j1j1
ntp
tpn
e1e2
ene
nng2
Prod
uct
stan
dard
ref
GD
R-C
OPR
GD
R-A
(Cyc
les
1to
22)
GD
R-B
(cyc
les
23-8
5)
GD
R(N
OA
A)
Orb
itC
nes
POE
GSF
C(I
TR
F20
05G
RA
CE
last
stan
dard
s)
DG
ME
-04
(Sch
arro
oan
dV
isse
r19
98[4
8]C
NE
SPO
E(G
DR
-1st
anda
rds
forc
ycle
s9
to22
GD
R-C
stan
dard
sfr
omcy
cle
23)
GSF
C(I
TR
F20
05
GR
AC
Ela
stst
anda
rds
Iono
pher
icD
ual f
requ
ency
altim
eter
rang
em
easu
rem
ents
Dua
l fre
quen
cyal
timet
erra
nge
mea
sure
men
ts(T
opex
)D
OR
IS(P
OSE
IDO
N)
Ben
t mod
elB
ent m
odel
(cyc
les
1-36
)G
IMm
odem
from
cycl
e37
((Ii
jima
etal
19
98[2
4])
Dua
l-fr
eque
ncy
altim
eter
rang
em
easu
rem
ent(
cycl
e9-
64)a
ndG
IMm
odel
gtcyc
le65
(Iiji
ma
etal
19
99[2
4])c
orre
cted
from
8m
mbi
as
From
GIM
mod
el(I
ijim
aet
al1
998
[24]
)
Dry
trop
o-sp
here
Mod
elco
mpu
ted
from
EC
MW
FG
auss
ian
grid
s(n
ewS1
and
S2at
mos
pher
ictid
esar
eap
plie
d)
Mod
elco
mpu
ted
from
EC
MW
Fre
ctan
gula
rgri
ds(n
ewS1
and
S2at
mos
pher
ictid
esar
ein
clud
ed)
Wet
trop
o-sp
here
JMR
AM
Rra
diom
eter
furt
hert
han
50km
from
the
coas
tsF
rom
EC
MW
Fm
odel
ford
ista
nces
betw
een
10an
d50
km
TM
Rra
diom
eter
(Sch
aroo
etal
20
04[4
9])
MW
RC
orre
ctio
nof
the
drif
ton
the
236
GH
zbr
ight
ness
tem
pera
ture
(Sch
arro
oet
al
2004
[49]
)Neu
ral
Net
wor
kal
gori
thm
(Tra
nan
dO
blig
is
2003
[50]
MW
Rra
diom
eter
furt
hert
han
50km
from
the
coas
tsan
dco
rrec
ted
from
side
lobe
s(f
rom
cycl
e41
)E
CM
WF
mod
elfo
rdis
tanc
esbe
twee
n10
and
50km
GFO
radi
omet
er
DA
CM
OG
2DH
igh
Res
olut
ion
forc
edw
ithE
CM
WF
pres
sure
and
win
gfie
lds
(S1
and
S2w
ere
excl
uded
)+in
vers
eba
rom
eter
com
pute
dfr
omre
ctan
gula
rgri
ds
Tabl
e6
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(1
2)
Page 33
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
j2j1
j1n
tptp
ne1
e2en
enn
g2O
cean
tide
GO
T4v
7(S
1an
dS2
are
incl
uded
)Po
letid
e[W
ahr
1985
[53]
]So
lidea
rth
tide
Ela
stic
resp
onse
totid
alpo
tent
ial[
Car
twri
ghta
ndTa
yler
197
1[5]
][C
artw
righ
tand
Edd
en1
973[
6]]
Loa
ding
tide
GO
T4v
7(S
1pa
ram
eter
isin
clud
ed)
Sea
stat
ebi
asN
onpa
ram
etri
cSS
B[G
aspa
reta
l20
02[2
0]]
Non
para
met
ric
SSB
[NT
ran
and
al2
010[
51]]
BM
3[G
aspa
ran
dO
gor
1994
[17]
]
Non
para
met
ric
SSB
[Mer
tzet
al
2005
[38]
]
Non
para
met
ric
SSB
[Gas
pare
tal
2002
]w
ithG
DR
-Bst
anda
rds
forc
ycle
s9
to85
and
with
GD
R-C
stan
dard
sfr
omcy
cle
86
Non
para
met
ric
SSB
[NT
ran
etal
20
10[5
1]]
Orb
iter
ror
Glo
bal m
ulti-
mis
sion
cros
sove
rmin
imiz
atio
n(L
eTr
aon
and
Ogo
r19
98[3
2])
Lon
gw
ave-
leng
her
rors
Opt
imal
Inte
rpol
atio
n(L
eTr
aon
etal
19
98[3
1])
Inte
rcal
ibra
tion
Ref
eren
cefr
omcy
cle
11R
efer
ence
from
cycl
e1
to35
4C
orre
ctio
nof
regi
onal
bias
J2J
1de
duce
dfr
omin
terc
alib
ratio
nph
ase
(cyc
le11
J2)
Cor
rect
ion
ofgl
obal
biai
sJ1
TP
deacutedu
ced
from
inte
rcal
ibra
tion
phas
e(c
ycle
s11
J1)
Mea
npr
o-fil
e(s
eeII
I36
1)
Com
pute
dw
ithcy
cles
11-3
53T
Pda
taan
dw
ithcy
cles
11-2
50J1
data
ref
eren
ced
[199
319
99]
TP
J1 c
ompu
ted
with
cycl
es11
-353
TP
data
and
with
cycl
es11
-250
J1da
tar
efer
ence
d[1
993
1999
]T
PNJ
1Nc
ompu
ted
with
cycl
es36
9-47
9T
PNda
tar
efer
ence
d[1
993
1999
]
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
ref
eren
ced
[199
319
99]
EN
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
re
fere
nced
[199
319
99]
EN
Nu
seof
MSS
_CN
ES_
CL
S11
[39]
Com
pute
dw
ithcy
cles
37-1
87G
2da
ta
refe
renc
ed[1
993
1999
]
Peri
odof
use
from
cycl
e9
from
cycl
e9
cycl
es1
to48
1cy
cles
15to
43In
clud
ing
E-F
geod
etic
phas
es
cycl
es1
to83
from
cycl
e9
cycl
es37
to22
2
Tabl
e7
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(2
2)
Page 34
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III32 Acquisition
The acqusition process in Delayed time is much simpler than in Near Real time it consists in a synchronisa-tion process of all the auxiliary data required to homogenize propely the altimeter data sets The acquisitionstep uses the GDRs or the OPRs provided by the agencies
III33 Homogenization
The Homogenization process consists in applying the most recent corrections models and references rec-ommended for altimeter products Each mission is processed separately as its needs depend on the baseinput data The list of corrections and models currently applied is provided in tables 6 and 7 for DT data
III34 Input data quality control
The Input Data Quality Control is a critical process applied to guarantee that DUACS uses only the mostaccurate altimeter data Thanks to the high quality of current missions this process rejects a small percent-age of altimeter measurements but these erroneous data could be the cause of a significant quality lossThe quality control relies on standard raw data editing with quality flags or parameter thresholds but alsoon complex data editing algorithms based on the detection of erroneous artefacts mono and multi-missioncrossover validation and macroscopic statistics to edit out large data flows that do not meet the systemrsquosrequirements
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III35 Multi-mission cross-calibration
The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistentand accurate information It removes any residual orbit error (OE Le Traon and Ogor 1998[32]) or longwavelength error (LWE Le Traon et al 1998[31]) as well as large scale biases and discrepancies betweenvarious data flows
This process is based on two very different algorithms a global multi-mission crossover minimization fororbit error reduction (OER) and Optimal Interpolation (OI) for LWE
Multi-satellite crossover determination is performed on a daily basis All altimeter fields (measurementcorrections and other fields such as bathymetry MSS) are interpolated at crossover locations and datesCrossovers are then appended to the existing crossover database as more altimeter data become availableThis crossover data set is the input of the Orbit Error Reduction (OER) method Using the precision of thereference mission orbit a very accurate orbit error can be estimated LWE is mostly due to residual tidalor inverse barometer errors and high frequency ocean signals The OI used for LWE reduction uses preciseparameters derived from
bull accurate statistical description of sea level variability
bull localized correlation scales
bull mission-specific noise and precise assumptions on the long wavelength errors to be removed (from arecent analysis of one year of data from each mission)
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III36 Product generation
The product generation process is composed of four steps computation of raw SLA cross-validationfilteringampsub-sampling and generation of by-products
III361 Computation of raw SLA
Since the geoid is not well known yet the SSH cannot be used directly the SSH anomalies are used insteadThey are computed from the difference of the instantaneous SSH - a temporal reference This temporalreference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeattrack analysis cannot be used The errors affecting the SLAs MPs and MSS have different magnitudes andwavelengths The computation of the SLAs and their errors associated are detailed in Dibarboure et al 2010[9]
Use of a Mean ProfileIn the repeat track analysis (when the satellites flies over a repetitive orbit) measurements are re-sampledalong a theoretical ground track (or mean track) associated to each mission Then a Mean Profile (MP) issubtracted from the re-sampled data to obtain SLA The MP is a time average of similarly re-sampled dataover a long period
bull The Mean Profile used for TP (cycles 1 to 364) Jason-1 (cycles 1 to 259) and Jason-2 is computedwith 10 years of TP (cycles 11 to 353) and 6 years of Jason-1 (cycles 11 to 250)
bull The Mean Profile used for TP (cycles 368 to 481) and from Jason-1 cycle 262 to 374 (where satellitesare on interleaved ground-tracks) is computed with 3 years of TP (cycles 369 to 479)
bull The Mean Profile used for ERS-1 in its 35 days repetitive orbit mission ERS-2 and Envisat (only forthe first orbit before November 2010) is computed with 8 years of ERS-2 (cycles 1 to 85) and 6 yearsof Envisat (cycles 10 to 72)
bull No Mean Profile can be used for Envisat on its new orbit (enn) Jason-1 on its geodetic orbit (j1g)because there is no repetitive track The MSS must be used instead (see below)
bull The Mean Profile used for GFO is computed with 7 years of GFO cycles 37 to 187
Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible
bull Indeed as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide precise cross-track projection andor interpolation schemes are required to avoid errors
bull The mesoscale variability error (which is lt35 cm for MP between 3 to 5 years and lt1cm for WLof 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a prioriknowledge from Sea Level maps derived from previous iterations or from other missions
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bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for ERS-1 for its 168 days geodetic mission (phases E-F from April1994 to March 1995) or for Envisat since november 2010 because the satellite is not in a repetitive orbitphase The alternative is to use the MSS instead The gridded MSS is derived from along track MPs anddata from geodetic phases Thus any error on the MP is also contained in the MSS There are essentially 4types of additional errors on gridded MSS which are hard to quantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
III362 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III363 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
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III37 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III371 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
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IV MYOCEAN PRODUCTS
IV1 Near Real Time Products
The purpose of the NRT DUACS component is the acquisition of altimeter data from various altimeter mis-sions in near-real time (ie within a few days at most) the validation and correction of these altimeter datasets (ie edition and selection update of corrections and homogenization orbit error reduction) in order toproduce each day along-track productsProducts are as follows
Along-track products global and regional (Mediterranean and Black Seas Arctic Ocean and Europeareas)
bull Sea Level Anomaly (NRT-SLA) for each mission with NRT-SLA ephemeris
IV11 Delay of the products
The availability of the products in near real time is three to twelve hours after the measurement for along-track products Those products are delivered every day
IV12 Temporal availibility
The following table presents the available products by mission and by data periodNear real time products
NRT Jason-2 Jason-1 and Jason-1geodetic
Envisat new Cryosat-2
Temporal Time availability ymlowast
ongoingymlowast-20120303 for
repeat track and20120507-ongoing for
geodetic track
ymlowast
2012040820120101
ongoing
NRT-SLA X X X X
lowastym the temporal coverage for NRT products is fluctuating and depends on updates of Delayed Time prod-ucts When DT products are updated (3 to 4 times per year) the oldest NRT products are replaced by thebetter quality DT products so that the 2 series are overlapping on few weeks or few months
IV2 Delayed Time Products
The Delayed Time component of SSALTODUACS system is responsible for the production of processedJason-1 Jason-2 TP Envisat GFO ERS12 and even Geosat data in order to provide a homogeneousinter-calibrated and highly accurate long time series of SLA DT products are more precise than NRT products Two reasons explain this quality difference The firstone is the better intrinsic quality of the POE orbit used in the GDR processing The second reason is that
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in the DT DUACS processing the products can be computed optimally with a centred computation timewindow for OER LWE On the contrary in NRT case future data are not available so the computationtime window is not centred and therefore not optimalAs for NRT products improved altimeter corrections and processing algorithms are used ocean tide modelto correct altimeter data improved methods for orbit error reduction and mapping
Along-Track products global and regional (Mediterranean and Black Seas)
bull Sea Level Anomaly (DT-SLA) for each mission
IV21 Delay of the products
Weekly products are delivered The availability of the products in delayed time is at the best two monthsafter the date of the measurement The product generation needs all the GDR data of all the missions to takeinto account the best corrections as possible The time delay can be longer in the case of a missing mission
IV22 Temporal availibility
The following table presents the available products by mission and by data periodDelayed time SSALTODUACS products
Upd Jason-2 Jason-1new6
Jason-1 GFO Envisatnew6
Envisat ERS-16
ERS-2Topexnew6
Topex
TemporalTimeavailabil-ity
200810ymlowast
200902ymlowast
200204200810
200001200809
201010ymlowast
200210201010
199210200304
200209200510
199209200204
DT-SLA X X X X X X X X X
lowast ym those dates are updated regularly (3 to 4 times per year) and are avalaible when you download thedata at httpwwwmyoceaneuweb24-cataloguephp6 Jason-1 new orbit starting 200809 Envisat new orbit starting 201010 TP new orbit starting 200209 ERS-1The geodetic phases (E-F) are included There are no ERS-1 data between December 23 1993 and April 10 1994(ERS-1 phase D - 2nd ice phase) Note that during that time products are based only on TopexPoseidon data
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V DESCRIPTION OF THE PRODUCT SPECIFICATION
V1 General information
Product Specification SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001
Geographical coverage global
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 20-50km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001 Product Specification
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Product Specification SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002
Geographical coverage 55˚W-35˚E 30˚N-46˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002 Product Specification
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Product Specification SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003
Geographical coverage 27˚E-42˚E 40˚N-47˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003 Product Specification
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Product Specification SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004
Geographical coverage 25˚W-42˚E 21˚N-66˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004 Product Specification
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Product Specification SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005
Geographical coverage 0˚W-360˚E 50˚N-82˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005 Product Specification
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VI NOMENCLATURE OF FILES
VI1 Nomenclature of files downloaded through the MyOcean Web PortalDirectgetfile Service
VI11 Nomenclature of the product line
The description of the syntax for the SL TAC SLA products line is given by
SEALEVEL_ltREGIONgt_SLA_L3_ltDELAYgt_OBSERVATIONS_008_ltZONEgt_ltLETTERgtwhere
REGION GLO global geographic coverage product
BS Black Sea products
MED Mediterranean products
ARC Arctic products (for NRT products)
EUROPE Europe products (for NRT products)
DELAY NRT near real time products
RAN delayed time or reanalysis products
ZONE 001 number on 3 digits
002
003
004
LETTER a letter on 1 digit
b
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VI12 Nomenclature of the datasets
The nomenclature used is
dataset-duacs-ltdelaygt-ltzonegt-ltmissiongt-lttype of slagt-l3where the fileds in ltgt are described below
delay nrt near-real time productsran delayed time products
zone global global geographic coverage productmedsea Mediterranean productsblacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1 (only for ran)e2 ERS-2 (only for ran)tp TOPEXPoseidon (only for ran)tpn TOPEXPoseidon on its new orbit (only for
ran)g2 GFO (only for ran)j1 Jason-1 (only for ran)j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisat (only for ran)enn Envisat on its new orbitc2 Cryosat-2 (only for nrt)
type of sla sla filtered slasla_unfiltered non filtered sla (only for ran products)
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VI13 Nomenclature of the NetCdf files
The nomenclature used is
ltdelaygt_ltzonegt_ltmissiongt_sla_ltvariablegt_ltdatebegingt_ltdateendgt_ltdateprodgtnc where the fileds in ltgt are de-scribed below
delay nrt near-real time productsdt delayed time products
zone global global geographic coverage productmed Mediterranean products (for dt)mfstep Mediterranean products (for nrt)blacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1e2 ERS-2tp TOPEXPoseidontpn TOPEXPoseidon on its new orbitg2 GFOj1 Jason-1j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisatenn Envisat on its new orbitc2 Cryosat-2
variable vfec filtered and sub-sampled slavxxc non filtered and non sub-sampled sla (only
for dt)datebegin YYYYMMDD() beginning date of the datasetdateend YYYYMMDD() end date of the datasetdateprod YYYYMMDD production date of the dataset
() For dt data as the dates in the file names are rounded the user wanting data for date T has to read the filescontaining dates T+1 and T-1 in their name and check inside the files if there are some data for date T
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VII DATA FORMAT
This chapter presents the data storage format used for MyOcean products
VII1 NetCdf
The products are stored using the NetCDF format NetCDF (network Common Data Form) is an interface for array-oriented data access and a library that provides an implementation of the interface The netCDF library also definesa machine-independent format for representing scientific data Together the interface library and format support thecreation access and sharing of scientific data The netCDF software was developed at the Unidata Program Center inBoulder Colorado The netCDF libraries define a machine-independent format for representing scientific data Pleasesee Unidata NetCDF pages for more information and to retreive NetCDF software package onhttpwwwunidataucaredupackagesnetcdfindexhtml
NetCDF data is
bull Self-Describing A netCDF file includes information about the data it contains
bull Architecture-independent A netCDF file is represented in a form that can be accessed by computers with dif-ferent ways of storing integers characters and floating-point numbers
bull Direct-access A small subset of a large dataset may be accessed efficiently without first reading through allthe preceding data
bull Appendable Data can be appended to a netCDF dataset along one dimension without copying the dataset orredefining its structure The structure of a netCDF dataset can be changed though this sometimes causes thedataset to be copied
bull Sharable One writer and multiple readers may simultaneously access the same netCDF file
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VII2 Structure and semantic of NetCDF along-track files
The NetCDF Sea Level TAC files are based on the attribute data tags defined by the Cooperative OceanAtmosphereResearch Data Service (COARDS) and Climate and Forecast (CF) metadata conventions The CF convention gener-alises and extends the COARDS convention but relaxes the COARDS constraints on dimension and order and specifiesmethods for reducing the size of datasetsA wide range of software are available to write or read NetCDFCF files API are made available by UNIDATA(httpwwwunidataucaredusoftwarenetcdf)
bull CC++Fortran
bull Java
bull MATLAB Objective-C Perl Python R Ruby TclTk
In addition to these conventions the files are using a common structure and semantic
bull 1 dimension is defined
ndash time it is used to check NetCDF variables depending on time
bull 8 variables are defined
ndash short SLA contains the Sea Level Anomaly values for each time given
ndash int longitude contains the longitude for each measurement
ndash short track contains the track number for each measurement
ndash double time contains the time in days since 1950-01-01 000000 UTC for each measurement
ndash short mean_profile_point_index index of the corrsponding point in the track of the mean profile
ndash byte flag flag=0 the processed data comes from OGDR if flag=1 the processed data comes from theIGDR
ndash int latitude contains the latitude for each measurement
ndash short cycle contains the cycle number for each measurement
bull global attributes
ndash the global attributes gives information about the creation of the file
Example of a NetCDF sla file
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netcdf nrt_global_j1_sla_vfec_20101230_20101230_20101230 dimensions
time = 10385 variables
short SLA(time) SLAcoordinates = longitude latitude SLAlong_name = Sea Level Anomaly SLA_FillValue = 32767s SLAadd_offset = 0 SLAscale_factor = 0001 SLAunits = m SLAstandard_name = sea_surface_height_above_sea_level
int longitude(time) longitudelong_name = Longitude of measurement longitude_FillValue = 2147483647 longitudeadd_offset = 0 longitudestandard_name = longitude longitudescale_factor = 1e-06 longitudeunits = degrees_east
short track(time) tracklong_name = Track in cycle the measurement belongs to track_FillValue = 32767s trackunits = 1 trackcoordinates = longitude latitude
double time(time) timelong_name = Time of measurement time_FillValue = 184467440737096e+19 timeaxis = T timestandard_name = time timeunits = days since 1950-01-01 000000 UTC
int latitude(time) latitudelong_name = Latitude of measurement latitude_FillValue = 2147483647 latitudeadd_offset = 0 latitudestandard_name = latitude latitudescale_factor = 1e-06 latitudeunits = degrees_north
short flag(time) flagcoordinates = longitude latitude flag_FillValue = 3267s flaglong_name = data origin flagflag_values = 1s 0s flagflag_meanings = igdr_like non_igdr_like flagcomment = The origin of the data is determined by the types of geophysical datarecords (GDR) used in computation of the SLA 1 for the Interim GDR (IGDR) and0 for Operational GDR (OGDR)
short cycle(time) cyclelong_name = Cycle the measurement belongs to cycle_FillValue = 32767s cycleunits = 1 cyclecoordinates = longitude latitude
global attributeshistory = 22-Feb-2011 155243 CET File created by the SSLATODUACS system version 1001 comment = Produce from ENVISAT Extension Phase satellite altimetry data institution = CLSCNES
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references = httpwwwavisooceanobscomfileadmindocumentsdatatoolshdbk_duacspdf source = satellite altimetry title = along track Sea Level Anomaly Conventions = CF-14
dataSLA =
7 7 11 10 -2 -22 -39 -41 -30 -13 -3 -5 -16 -26 -32 -35-35 -35 -37 -35 -31 -29 -31 -35 -32 -21 -10 -10 -19 -20 -1-69 -57 -49 -45 -39 -30 -28 -31 -27 -13 -2 -5 -15 -3 1112 3 -7 -10 -14 -15 -22 -31 -37 -32 -17 -10
longitude =74743328 74868400 74993968 75120040 75246616 7537372875501368 75629568 75758320 75887656 76017568 76148080 7627920876388952 76477056 76565456 76654144 76743128 76832400 76921984329429568 329535424 329641792 329748672 329856096 329964032330072512 330181536 330291072 330401184
track =92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 9292 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92113 113 113 113 113 113 113 113 113 113 113 113 113 113113 113 113 113 113 113 113 113 113
time =222780000565705 222780001314719 222780002063733222780002812747 222780003561761 222780004310775 222780005059788222780005808802 222780006557816 22278000730683 222780008055844222780008804858 222780009553872 22278001017805 222780010677393222788257112198 222788257486705 222788257861212 222788258235719222788258610226 222788258984733 222788259359239 222788259733746222788260108253 22278826048276
mean_profile_point_index =1872 1878 1884 1890 1896 1902 1908 19141920 1926 1932 1938 1944 1949 1953 1957 1961 1965 1969 19732306 2309 2312 2315 2318 2321 2327 2330 2333 2336 2339 23422345 2348 2351 2354 2357 2360 2363 2366
flag =0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
latitude =-16225506 -16539731 -16853833 -17167810 -17481660 -17795380-18108966 -18422418 -18735729 -19048899 -19361924 -19674801-19987527 -20248015 -20456329 -20664569 -20872739 -2108083739481297 39628277 39775133 39921866 40068472 40214953 4036130840507533 40653629 40799592 40945423 41091120 41236684 41382111
cycle =331 331 331 331 331 331 331 331 331 331 331 331 331
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331 331 331 331 331 331 331 331 331 331 331 331 331 331331 331 331 331 331 331 331 331 331 331 331 331
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VIII HOW TO DOWNLOAD A PRODUCT
VIII1 Download a product through the MyOcean Web Portal DirectgetfileService
You first need to register Please find below the registration stepshttpwwwmyoceaneuweb34-products-and-services-faqphp1Once registered the MyOcean FAQ httpwwwmyoceaneuweb34-products-and-services-faqwill guide you on How to download a product through the MyOcean Web Portal Directgetfile Service
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IX NEWS AND UPDATES
IX1 [Duacs] Operational news
To be kept informed on events occurring on the satellites and on the eventual interruption of the services of the DUACSprocessing system see the [Duacs] operational news on the Aviso websitehttpwwwavisooceanobscomendataoperational-newsindexhtml
IX2 Updates
To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtmlSince 2010 a complete reprocessing of all altimetry data (cumulated total of about 55 years of data) is available Themain changes introduced in the Duacs DT v300 reprocessed data set in SSALTODUACS reprocessed DT data setare listed herehttpwwwavisooceanobscomfileadmindocumentsdataduacsduacs_DT_2010_reprocessing_impactpdf
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SI Signed IntegerSLA Sea Level AnomalySL TAC Sea Level Thematic Assembly CentreSSALTO Ssalto multimission ground segmentSSH Sea Surface HeightTAC Thematic Assembly CentreTP TopexPoseidonTPN TopexPoseidon on its new orbit (since cycle 369)
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REFERENCES
[1] Andersen O B The DTU10 Gravity filed and Mean sea surface (2010) Second international sympo-sium of the gravity field of the Earth (IGFS2) Fairbanks Alaska
[2] Boy F et al (2011) Cryosat LRM TRK and SAR processing Presented at the 2011 Ocean Sur-face Topography Science Team meeting httpwwwavisooceanobscomfileadmindocumentsOSTST2011oral01_Wednesday
[3] Carrere L F Lyard 2003 Modeling the barotropic response of the global ocean to atmo-spheric wind and pressure forcing- comparisons with observations J Geophys Res 30(6) 1275doi1010292002GL016473
[4] Carrere L 2003 Etude et modeacutelisation de la reacuteponse HF de lrsquooceacutean global aux forccedilagesmeacuteteacuteorologiques PhD thesis Universiteacute Paul Sabatier (Toulouse III France) 318 pp
[5] Cartwright D E R J Tayler 1971 New computations of the tide-generating potential Geophys JR Astr Soc 23 45-74
[6] Cartwright D E A C Edden 1973 Corrected tables of tidal harmonics Geophys J R Astr Soc33 253-264
[7] Following the scientific recommendations from the OSTST meeting (San Diego October 2011) theESA Cryosat Project and the CNES SALP Project have been collaborating to generate these Cryosat-derived L3 and L4 products Level 1B and Level 2 products derived from CNES processors are notdistributed by AVISO as per the CNES ESA agreement
[8] Dibarboure G C Renaudie M-I Pujol S Labroue N Picot 2011 A demonstrationof the potential of Cryosat-2 to contribute to mesoscale observation J Adv Space Resdoi101016jasr201107002 httpdxdoiorg101016jasr201107002
[9] Dibarboure G P Schaeffer P Escudier M-IPujol JF Legeais Y Faugegravere R Morrow JK WillisJ Lambin JP Berthias N Picot 2010 Finding desirable orbit options for the Extension of Lifephase of Jason-1 Submitted to Marine Geodesy
[10] Dibarboure G M-IPujol FBriol PYLe Traon GLarnicol NPicot FMertz P Escudier MAblainCDufau 2010 Jason-2 in DUACS first tandem results and impact on processing and products Sub-mitted in Marine Geodesy
[11] Dibarboure G 2009 Using short scale content of OGDR data improve the Near Real Time productsof SsaltoDuacs oral presentation at Seattle OSTST meeting (pdf)
[12] Dorandeu J M Ablain Y Faugegravere F Mertz B Soussi and P Vincent 2004 Jason-1 global statisti-cal evaluation and performance assessment Calibration and cross-calibration results Marine Geodesy27(3-4) 345-372
[13] Dorandeu J M Ablain P-Y Le Traon 2003 Reducing Cross-Track Geoid Gradient Errors aroundTOPEXPoseidon and Jason-1 Nominal Tracks Application to Calculation of Sea Level AnomaliesJ of Atmosph and Ocean Techn20 1826-1838
[14] Dorandeu J and P-Y Le Traon 1999 Effects of global mean atmospheric pressure variations onmean sea level changes from TOPEXPoseidon J Atmos Oceanic Technol 16 1279-1283
[15] Ducet N P-Y Le Traon and G Reverdin 2000 Global high resolution mapping of ocean circulationfrom TOPEXPoseidon and ERS-1 and -2 J Geophys Res 105 19477-19498
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[16] Egbert Gary D Svetlana Y Erofeeva 2002 Efficient Inverse Modeling of Barotropic Ocean Tides JAtmos Oceanic Technol 19 183-204 doi 1011751520-0426(2002)019lt0183EIMOBOgt20CO2
[17] Gaspar P and F Ogor Estimation and analysis of the Sea State Bias of the ERS-1 altimeter Reportof task B1-B2 of IFREMER Contract n˚ 942426 016C 1994
[18] Gaspar P F Ogor and C Escoubes 1996 Nouvelles calibration et analyse du biais drsquoeacutetat de mer desaltimegravetres TOPEX et POSEIDON Technical note 96018 of CNES Contract 951523 1996
[19] Gaspar P and F Ogor Estimation and analysis of the Sea State Bias of the new ERS-1 and ERS-2altimetric data (OPR version 6) Report of task 2 of IFREMER Contract n˚ 962246 002C 1996
[20] Gaspar P S Labroue and F Ogor 2002 Improving nonparametric estimates of the sea state bias inradar altimeter measurements of seal level J Atmos Oceanic Technology 19 1690-1707
[21] Hernandez F P-Y Le Traon and R Morrow 1995 Mapping mesoscale variability of the AzoresCurrent using TOPEXPOSEIDON and ERS-1 altimetry together with hydrographic and Lagrangianmeasurements Journal of Geophysical Research 100 24995-25006
[22] Hernandez F and P Schaeffer 2000 Altimetric Mean Sea Surfaces and Gravity Anomaly maps inter-comparisons AVI-NT-011-5242-CLS 48 pp CLS Ramonville St Agne
[23] Hernandez F M-H Calvez J Dorandeu Y Faugegravere F Mertz and P Schaeffer 2000 Sur-face Moyenne Oceacuteanique Support scientifique agrave la mission altimeacutetrique Jason-1 et agrave une mis-sion micro-satellite altimeacutetrique Contrat SSALTO 2945 - Lot 2 - A1 Rapport drsquoavancementCLSDOSNT00313 40 pp CLS Ramonville St Agne
[24] Iijima BA IL Harris CM Ho UJ Lindqwiste AJ Mannucci X Pi MJ Reyes LC SparksBD Wilson 1999 Automated daily process for global ionospheric total electron content maps andsatellite ocean altimeter ionospheric calibration based on Global Positioning System data J AtmosSolar-Terrestrial Physics 61 16 1205-1218
[25] Labroue S F Boy N Picot M Urvoy M Ablain First quality assessment of the Cryosat-2 altimetricsystem over ocean J Adv Space Res 2011 doi101016jasr201111018 httpdxdoiorg101016jasr201111018
[26] Labroue S 2007 RA2 ocean and MWR measurement long term monitoring 2007 report for WP3Task 2 - SSB estimation for RA2 altimeter Contract 1729303I-OL CLS-DOS-NT-07-198 53ppCLS Ramonville St Agne
[27] Labroue S P Gaspar J Dorandeu OZ Zanifeacute F Mertz P Vincent and D Choquet 2004 Nonparametric estimates of the sea state bias for Jason-1 radar altimeter Marine Geodesy 27 453-481
[28] Lagerloef GSE GMitchum RLukas and PNiiler 1999 Tropical Pacific near-surface currentsestimated from altimeter wind and drifter data J Geophys Res 104 23313-23326
[29] Le Traon P-Y and F Hernandez 1992 Mapping the oceanic mesoscale circulation validation ofsatellite altimetry using surface drifters J Atmos Oceanic Technol 9 687-698
[30] Le Traon P-Y P Gaspar F Bouyssel and H Makhmara 1995 Using TopexPoseidon data to en-hance ERS-1 data J Atmos Oceanic Technol 12 161-170
[31] Le Traon P-Y F Nadal and N Ducet 1998 An improved mapping method of multisatellite altimeterdata J Atmos Oceanic Technol 15 522-534
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[32] Le Traon P-Y and F Ogor 1998 ERS-12 orbit improvement using TOPEXPOSEIDON the 2 cmchallenge J Geophys Res 103 8045-8057
[33] Le Traon P-Y and G Dibarboure 1999 Mesoscale mapping capabilities of multi-satellite altimetermissions J Atmos Oceanic Technol 16 1208-1223
[34] Le Traon P-Y G Dibarboure and N Ducet 2001 Use of a High-Resolution Model to Analyze theMapping Capabilities of Multiple-Altimeter Missions J Atmos Oceanic Technol 18 1277-1288
[35] Le Traon PY and G Dibarboure 2002 Velocity mapping capabilities of present and future altimetermissions the role of high frequency signals J Atmos Oceanic Technol 19 2077-2088
[36] Le Traon PY Faugegravere Y Hernandez F Dorandeu J Mertz F and M Ablain 2002 Can we mergeGEOSAT Follow-On with TOPEXPOSEIDON and ERS-2 for an improved description of the oceancirculation J Atmos Oceanic Technol 20 889-895
[37] Le Traon PY and G Dibarboure 2004 An Illustration of the Contribution of the TOPEXPoseidon-Jason-1 Tandem Mission to Mesoscale Variability Studies Marine Geodesy 27 (1-2)
[38] Mertz F F Mercier S Labroue N Tran J Dorandeu 2005 ERS-2 OPR data quality assessment Long-term monitoring - particular investigation CLSDOSNT-06001 (pdf)
[39] MSS_CNES_CLS11 was produced by CLS Space Oceanography Division and distributed by Avisowith support from Cnes (urlhttpwwwavisooceanobscom)
[40] Pascual A Y Faugegravere G Larnicol P-Y Le Traon 2006 Improved description of the oceanmesoscale variability by combining four satellite altimeters Geophys Res Lett 33
[41] Pascual A C Boone G Larnicol and P-Y Le Traon 2009 On the quality of Real-Time altimetergridded fields comparison with in-situ data Journ of Atm and Ocean Techn Vol 26(3) pp 556-569DOI 1011752008JTECHO5561
[42] Prandi P M Ablain A Cazenave N Picot 2011 A new estimation of mean sea level in the ArcticOcean from satellite altimetry Submitted to Marine Geodesy
[43] Pujol M-I et al 2009 Three-satellite quality level restored in NRT poster at OSTST meeting (pdf)
[44] Ray R 1999 A Global Ocean Tide model from TOPEXPoseidon Altimetry GOT992 NASA TechMemo NASATM-1999-209478 58 pp Goddard Space Flight Center NASA Greenbelt MD USA
[45] Rio M-H and F Hernandez 2003 A Mean Dynamic Topography computed over the worldocean from altimetry in-situ measurements and a geoid model J Geophys Res 109 C12032doi1010292003JC002226
[46] Rio M-H and F Hernandez 2003 High frequency response of wind-driven currents measured bydrifting buoys and altimetry over the world ocean J Geophys Res 108 39-1
[47] Rio M-H 2003 Combinaison de donneacutees in situ altimeacutetriques et gravimeacutetriques pour lrsquoestimationdrsquoune topographie dynamique moyenne globale Ed CLS PhD Thesis University Paul Sabatier(Toulouse III France) 260pp
[48] Scharroo R and P Visser 1998 Precise orbit determination and gravity field improvement for theERS satellites J Geophys Res 103 8113-8127
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[49] Scharroo R J Lillibridge and WHF Smith 2004 Cross-calibration and long-term monitoring ofthe Microwave Radiometers of ERS Topex GFO Jason-1 and Envisat Marine Geodesy 97
[50] Tran N and E Obligis December 2003 Validation of the use of ENVISAT neural algorithms onERS-2 CLSDOSNT03901
[51] Tran N S Labroue S Philipps E Bronner and N Picot 2010 Overview and Update of the SeaState Bias Corrections for the Jason-2 Jason-1 and TOPEX Missions Marine Geodesy accepted
[52] Vincent P Desai SDDorandeu J Ablain M Soussi B Callahan PS and BJ Haines 2003 Jason-1 Geophysical Performance Evaluation Marine Geodesy 26 167-186
[53] Wahr J W 1985 Deformation of the Earth induced by polar motionJ of Geophys Res (Solid Earth)90 9363-9368
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I INTRODUCTION
MyOcean is a European Network project aiming at monitoring analyzing and forecasting the Ocean Ituses satellite and in-situ data to describe the ocean in 3 dimensions and real time More information can befound on httpwwwmyoceaneuorgThe aim of this document is to describe the products delivered by the Sea Level TAC (Thematic AssemblyCentre) which is one of the five TAC of the MyOcean projectThe data produced in the frame of this TAC are generated by the processing system named DUACS (DataUnification and Altimeter Combination System)DUACS is part of the CNES multi-mission ground segment (SSALTO) It processes data from all altimetermissions Cryosat-2 OSTMJason-2 Jason-1 TopexPoseidon Envisat GFO ERS-1amp2 and even GeosatAt this time (May 25th 2012) DUACS is using three different altimeters in near real time Developed and operated by CLS it started as an European Commission Project (Developing Use Of Altime-try for Climate Studies) funded under the European Commission and the Midi-Pyreacuteneacutees regional councilIt has been integrated to the CNES multi-mission ground segment SSALTO in 2001 and it is maintainedupgraded and operated with funding from CNES with shared costs from EU projectsAt the beginning of 2004 DUACS was redefined as the Data Unification Altimeter Combination System
Figure 1 DUACS and AVISO a user-driven altimetry service
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The products lines described in this user manual are the followingSEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005
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The data provided to users have a global coverage (PL SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001)and regional products are also computed over specific areasMediterranean Sea (PL SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002)and Black Sea (PL SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003)Thanks to updates in 2011 and 2012 (see section II) new regional products are now availableEurope (PL SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004)and Arctic (PL SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005)
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II UPDATES IN 2011 AND 2012
This section describes the updates of the SSALTODUACS Near Real Time system that occurred during2011 and 2012 allowing to add new products (Europe and Arctic) the integration of the Cryosat-2 data inthe system the stopping delivery of Envisat data the addition of Jason-1 data on geodetic orbit (j1g)To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtml
II1 Version D of input IGDROGDR Jason-2 data for NRT processing(July 30 2012)
On July 30 2012 the version of Jason-2 IGDROGDR has changed and is now the D version Somecorrections have thus been updated as detailed in tables 3 and 4
II2 Integration of Jason-1 on its geodetic orbit (May 2012)
An anomaly occured on March 3rd 2012 on the Jason-2 mission (see httpwwwavisooceanobscomfractualitesactualitesindexhtmltx_ttnews[tt_news]=1162amptx_ttnews[backPid]=1399ampcHash=d5baeb645e) On April 23rd CNES began to command the satellite into a nadir ori-entation and after some propulsion anomalies CNES and NASA management through the Joint SteeringGroup have directed the Jason-1 Project to then begin a series of maneuvers to place Jason-1 into a neworbit as defined in table 1 After checking the current orbit carefully the operational team determined thata geodetic mission was still possible It was also decided to preserve all remaining fuel for future stationkeeping maneuvers which is mandatory in a geodetic orbit Core payloads were switched ON on May 4thand after some POSEIDON2 radar (PRF) adjustments the mission was resumed on May 7th at 151248UTCBelow are the characteristics of the new orbit which will be maintained as before within +- 1km controlbox at the Equator
Semi major axis 7702437 kmEccentricity 13 to 28 10-4Altitude equator 13240 kmOrbital period 6730s (1h52rsquo10rdquo)Inclination 66042˚Cycle 406 daysSub cycles 39 - 109 - 475 - 1795
days
Table 1 Characteristics of the geodetic orbit for Jason-1 since May 7th 2012
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For this new phase of the Jason-1 mission (called j1g) the cycle numbering will restart at 500 Off-lineproducts will be produced once a day for the IGDR and every 11 days for the GDRrsquos The integration ofJason-1 data in the DUACS system is available since May 25th 2012
II3 Envisat has stopped sending data (April 2012)
Since April 8th 2012 Envisat has stopped sending data to Earth Esarsquos mission control has worked tore-establish contact with the satellite but there has been no reaction from the satellite Thus Esa has de-clared officially the end of mission for Envisat (see httpwwwesaintesaCPSEM1SXSWT1H_index_0html) Therefore no SL TAC NRT data from Envisat can be released since this date
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II4 Integration of the Cryosat2 Mission (February 2012)
Since February 6th 2012 Cryosat-2 mission has been integrated in the DUACS sytem This mission isdedicated to the observation of the floating sea-ice as well as the continental ice sheets but all data acquiredover ocean are valuable for the observation of oceanic circulation and mesoscale variations This majorchange is the result of the long-standing and fruitful partnership between ESA and CNES and a responseto the request from scientific and operational oceanography users [7] The integration of Cryosat-2 impactsthe delivering of Near real time Sea Level Anomalies (SLA)
II41 Generalities about the mission
A Cryosat-2 Processing Prototype (C2P) (described in Boy et al 2011 [2]) has been developed on CNESside to lay the ground for various SAR processing studies The processing chains ingest Level-0 telemetryfiles distributed by ESA and perform the following steps to generate Sea Level Anomalies (SLA) values foreach altimeter measurements
bull Level-1 Decommutation time-tagging and localization of measurements
bull Level-1b Calculation of instrumental corrections and geophysicalmeteorological corrections
bull Level-2 MLE4 waveforms Retracking and calculation of SLA
The prototype processes data almost continuously over ocean either in Low Resolution Mode (LRM) or inthe DopplerSAR mode processed as pseudo-LRM mode allowing to increase the coverage (figure 2)
Figure 2 SSH-MSS for Cryosat-2 with LRM mode only (left) or LRM+pseudo-LRM modes (right)
Although Cryosat-2 raw SSH can be only corrected with GPS-derived ionospheric correction and ECMWFwet troposphere correction validation activities showed (Labroue et al 2011 [25]) that C2P outputs have anaccuracy roughly equivalent to Envisatrsquos Level 2 products if the latter are processed with the same standards
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II42 Integration in DUACS
The Cryosat-2 data are included in the Near Real time process The chain delivers now (for global coverageMediterranean and Black Seas) along track data from Cryosat-2 (SLAs) Note that the products distributedare of Level-3 and donrsquot replace Level-2 products distributed by agenciesThe details of the processing are given in Dibarboure et al 2011 [8]Here we just give an overview the data are computed with the corrections given in section III21 Thefiltering and sub-sampling of SLAs (section III263) are detailed in [8]
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II5 Addition of Europe and Arctic products (January 2012)
Since the MyOcean V2 two new along-track products are computed in Near Real Time intended foraddressing the needs of data assmilation and validation in regional models
bull Following the TAPAS (Tailored Altimeter Product for Assimilation Systems) initiative launched bySL TAC with all the Modeling and Forecasting Centers (MFCs) the Europe regional products (PLSEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004) have been proposed (figure 3) They areavailable in Near Real Time onlyThey are studied to partly fulfil the needs of the Centers with adapted filtering and resolution Thoseparameters have been tuned in order to provide boundary conditions for the Atlantic assimilationmodels They are different from the ones used for Mediterranean and Black Seas products If you needto study the Mediterranean Sea or the Black Sea yoursquod better use the dedicated products describedabove since the processing parameters have been fitted to be adapted to the dynamics of the ocean inthose regions
Figure 3 Coverage of the Europe product for Jason-1 Jason-2 and Envisat from August 18th to September9th 2011
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bull The Arctic along-track products (PL SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005) coverlatitudes between 45 and 82 degrees (figure 4) They are available in Near Real Time only
Figure 4 Coverage of the Arctic region with Envisat from October 28th 2011 to January 3rd 2012
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III SSALTODUACS SYSTEM
III1 Introduction
This chapter presents the input data used by SSALTODUACS system and an overview of the different pro-cessing steps necessary to produce the output dataSSALTODUACS system is made of two components a Near Real Time one (NRT) and a Delayed Time(DT) oneIn NRT the systemrsquos primary objective is to provide operational applications with directly usable high qual-ity altimeter data from all missions availableIn DT it is to maintain a consistent and user-friendly altimeter database using the state-of-the-art recom-mendations from the altimetry communityFollowing figure gives an overview of DUACS system where processing sequences can be divided into 7main steps
bull acquisition
bull homogenization
bull input data quality control
bull multi-mission cross-calibration
bull product generation
bull merging
bull final quality control
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Figure 5 SSALTODUACS processing sequences
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III2 Near Real Time processing steps
III21 Input data models and corrections applied
To produce SLA in near-real time the DUACS system uses two flows based on the same instrumental mea-surements but with a different quality
bull The IGDR that are the latest high-quality altimeter data produced in near-real-time
bull The OGDR that includes real time data (OSTMJason-2 and Jason-1 OSDR) to complete IGDR Thesefast delivery products do not always benefit from precise orbit determination nor from some exter-nal model-based corrections (Dynamic Atmospheric Correction (DAC) Global Ionospheric Maps(GIM))
Integration of OGDR data and the introduction of Jason-2Jason-1 tandem increased the resilience and pre-cision of the system A better restitution of ocean variability is observed especially in high energetic areas
Altimetric product Source Availability Type of orbit
Jason-2 IGDR CNES ~24h CNES MOE GDR-Cuntil 20120730
CNES MOE GDR-Dsince 20120731
OGDR NOAAEUMETSAT ~3 to 5 h
Jason-1 IGDR CNESNASA ~48 h CNES MOE GDR-Dsince 20120507
OGDR CNESNASA ~3 to 12 h
Envisat IGDR ESACNES not deliveredsince 20120408
CNES MOE GDR-Dsince 20120121
FDGDR ESA not deliveredsince 20120408
Cryosat-2 IGDR-like ESACNES ~48 h CNES MOE GDR-D
not delivered
Table 2 SSALTODUACS Near-Real Time Input data overview
See Figure 6 Overview of the near real time system data flow management
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DUACS 2011 NRT product from IGDR1
j2 j1nj1g enn c2Productstandard ref
version C until20120730 and D after
version C version 21 CPP [2]
Orbit CNES MOE GDR-Cuntil 20120730
GDR-D after
CNES MOE GDR-C forj1n and CNES MOE
GDR-D for j1g
CNES MOE GDR-Dfrom 20120121 to
20120408
CNES MOE GDR-D
Ionopheric bi-frequency altimeter range measurements GIM model for cgt64 (Iijima et al1998[24])Dry tropo Model computed from ECMWF Gaussian grids (new S1 and S2 atm tides applied)Wet tropo-sphere
AMR radiometer(enhancement in coastal
regions since20120730)
JMR radiometer MWR radiometer andcorrected from side
lobes
Model computed fromECMWF Gaussian
grids
DAC MOG2D High Resolution forced with ECMWF pressure and wind fields (S1 and S2 wereexcluded) (Carrere and Lyard 2003[3])+ inverse barometer Filtering temporal window is
un-centered (no data in the future)Ocean tide GOT4v8 (S1 and S2 are included) and TPX 072 [16] for Arctic productsPole tide [Wahr 1985 [53]]Solid earthtide
Elastic response to tidal potential [Cartwright and Tayler 1971[5]] [Cartwright andEdden 1973[6]]
Loading tide GOT4v8 (S1 and S2 are included)Sea statebias
Non parametric SSB[Labroue 2004[27]](with cycles J1 1 to 11
using GDR-B standardsuntil 20120730 andderived from Jason-2
after)
Non parametric SSB[Labroue 2004[27]](with cycles 1 to 21
using GDR-Bstandards)
Non parametric SSB[Labroue 2004[27]](with cycles 41 to 60
using GDR-Bstandards)
Same as Jason-2 SSB
Orbit error Global multi-mission crossover minimization (Le Traon and Ogor1998[32])
Long wave-lengh errors
Optimal Interpolation [Le Traon et al 1998[31]]
Intercalibration Reference from cycle20
Mean pro-file (seeIII261)
Computed with cycles11-353 TP data andwith cycles 11-250J1 data referenced[19931999]
TPNJ1N computedwith cycles 369-479TPN data refer-enced [19931999]J1G No MP can beused instead theMSS_CNES_CLS11[39] is used
No Mean Profilecan be used forEnvisat on its neworbit Instead theMSS_CNES_CLS11[39] is used
No Mean Profilecan be used forCryosat-2 Instead theMSS_CNES_CLS11[39] is used
(1) A flag included in the along-track files indicates the source of the production (OGDRFDGDR orIGDR) If flag=0 the processed data comes from OGDRsFDGDRs if flag=1 the processed data comesfrom IGDRs
Table 3 Corrections and models applied in SSALTODUACS NRT products produced from IGDRs
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DUACS 2011 NRT product from OGDR or FDGDR2
j2 j1nj1g ennProduct stan-dard ref
version C until 20120730and D after
version C version 21
Orbit Navigator Extrapolated CNES MOEGDR-D since 20120121
Ionopheric From-dual frequency altimeter range measurements From GIM model fromcycle 65 (Iijima et al1998 [24])
Dry troposphere Model computed from ECMWF Gaussian grids (new S1 and S2 atmospherictides are applied)
Wet tropo-sphere
AMR radiometer(enhancement in coastal
regions since 20120730)
JMR radiometer MWR radiometer andcorrected from side lobes
DAC Inverse Barometer forecastedOcean tide GOT4v8 (S1 and S2 are included) and TPX 072 [16] for Arctic productsPole tide [Wahr 1985 [53]]Solid earth tide Elastic response to tidal potential [Cartwright and Tayler 1971[5]]
[Cartwright and Edden 1973[6]]Loading tide GOT4v8 (S1 and S2 are included)Sea state bias Non parametric SSB
[Labroue 2004[27]] (withcycles J1 1 to 11 usingGDR-B standards until20120730 and derivedfrom Jason-2 after)
Non parametric SSB[Labroue 2004[27]](with cycles 1 to 21 usingGDR-B standards)
Non parametric SSB[Labroue 2004[27]](with cycles 41 to 60using GDR-B standards)
Orbit error Specific filtering of long-wavelength signal3
Long wave-lengh errors
Optimal Interpolation [Le Traon et al 1998[31]]
Intercalibration Reference from cycle 20Mean profile(see III261)
Computed with cycles 11-353 TP data and with cy-cles 11-250 J1 data refer-enced [19931999]
TPNJ1N computedwith cycles 369-479TPN data referenced[19931999] J1G NoMP can be used insteadthe MSS_CNES_CLS11[39] is used
No Mean Profile can beused for Envisat on itsnew orbit Instead theMSS_CNES_CLS11 [39]is used
(2) A flag included in the along-track files indicates the source of the production (OGDRFDGDR orIGDR) If flag=0 the processed data comes from OGDRsFDGDRs if flag=1 the processed data comesfrom IGDRs(3) Specific data processing was applied on long wave-length signal (sectIII23 of the user manual)
Table 4 Corrections and models applied in SSALTODUACS NRT products produced from OG-DRsFDGDRs
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III22 Acquisition
The acquisition process is twofold
bull straightforward retrieval and reformatting of altimeter data and dynamic auxiliary data (pressure andwet troposphere correction grids from ECMWF are provided by Meteo France TEC grids from JPLNRT MOG2D corrections) from external repositories
bull synchronisation process
To be homogenized properly altimeter data sets require various auxiliary data The acquisition softwaredetects downloads and processes incoming data as soon as they are available on remote sites (externaldatabase FTP site) Data are split into passes if necessary If data flows are missing or late the synchroni-sation engine put unusable data in waiting queues and automatically unfreezes them upon reception of themissing auxiliary data This processing step delivers raw data that is to say data that have been dividedinto cycles and passes and ordered chronologicallyFrom SSALTODUACS V80 the acquisition step uses two different data flows in near-real time the OGDRflow (within a few hours) and the IGDR flow (within a few days)For each OGDR input the system checks that no equivalent IGDR entry is available in the data base beforeacquisition for each IGDR input the system checks and delete the equivalent OGDR entry in the data baseThese operations aim to avoid duplicates in SSALTODUACS system
Figure 6 Overview of the near real time system data flow management
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III23 Homogenization
The Homogenization process consists in applying the most recent corrections models and references rec-ommended for altimeter products Each mission is processed separately as its needs depend on the baseinput data The list of corrections and models currently applied is provided in tables 3 and 4 for NRT dataThe system includes SLA filtering to process OGDR data DUACS extract from these data sets the shortscales (space and time) which are useful to better describe the ocean variability in real time and merge thisinformation with a fair description of large scale signals provided by the multi-satellite observation in nearreal time (read IGDR-based DUACS data) Finally an hybrid SLA is computed
Figure 7 Merging pertinent information from IGDR and OGDR processing
III24 Input data quality control
The Input Data Quality Control is a critical process applied to guarantee that DUACS uses only the mostaccurate altimeter data Thanks to the high quality of current missions this process rejects a small percent-age of altimeter measurements but these erroneous data could be the cause of a significant quality lossThe quality control relies on standard raw data editing with quality flags or parameter thresholds but alsoon complex data editing algorithms based on the detection of erroneous artefacts mono and multi-missioncrossover validation and macroscopic statistics to edit out large data flows that do not meet the systemrsquosrequirements
Page 26
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III25 Multi-mission cross-calibration
The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistentand accurate information It removes any residual orbit error (OE Le Traon and Ogor 1998[32]) or longwavelength error (LWE Le Traon et al 1998[31]) as well as large scale biases and discrepancies betweenvarious data flows
This process is based on two very different algorithms a global multi-mission crossover minimization fororbit error reduction (OER) and Optimal Interpolation (OI) for LWE
Multi-satellite crossover determination is performed on a daily basis All altimeter fields (measurementcorrections and other fields such as bathymetry MSS) are interpolated at crossover locations and datesCrossovers are then appended to the existing crossover database as more altimeter data become availableThis crossover data set is the input of the Orbit Error Reduction (OER) method Using the precision of thereference mission orbit a very accurate orbit error can be estimated This processing step does not concernOGDR dataLWE is mostly due to residual tidal or inverse barometer errors and high frequency ocean signals The OIused for LWE reduction uses precise parameters derived from
bull accurate statistical description of sea level variability
bull localized correlation scales
bull mission-specific noise and precise assumptions on the long wavelength errors to be removed (from arecent analysis of one year of data from each mission)
Page 27
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III26 Product generation
The product generation process is composed of four steps computation of raw SLA cross-validationfilteringampsub-sampling and generation of by-products
III261 Computation of raw SLA
Since the geoid is not well known yet the SSH cannot be used directly the SSH anomalies are used insteadThey are computed from the difference of the instantaneous SSH - a temporal reference This temporalreference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeattrack analysis cannot be used The errors affecting the SLAs MPs and MSS have different magnitudes andwavelengths The computation of the SLAs and their errors associated are detailed in Dibarboure et al 2010[9]
Use of a Mean ProfileIn the repeat track analysis (when the satellites flies over a repetitive orbit) measurements are re-sampledalong a theoretical ground track (or mean track) associated to each mission Then a Mean Profile (MP) issubtracted from the re-sampled data to obtain SLA The MP is a time average of similarly re-sampled dataover a long period
bull The Mean Profile used for Jason-2 is computed with 10 years of TP (cycles 11 to 353) and 6 years ofJason-1 (cycles 11 to 250)
bull The Mean Profile used from Jason-1 cycle 262 to 374 (where satellites are on interleaved ground-tracks) is computed with 3 years of TP (cycles 369 to 479)
bull No Mean Profile can be used for Envisat on its new orbit (enn) Jason-1 on its geodetic orbit (j1g) norfor Cryosat-2 mission (c2) because there is no repetitive track The MSS must be used instead (seebelow)
Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible
bull Indeed as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide precise cross-track projection andor interpolation schemes are required to avoid errors
bull The mesoscale variability error (which is lt35 cm for MP between 3 to 5 years and lt1cm for WLof 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a prioriknowledge from Sea Level maps derived from previous iterations or from other missions
bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
Page 28
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for Envisat since november 2010 and for Cryosat-2 mission (c2)because the satellite is not in a repetitive orbit phase The alternative is to use the MSS instead The griddedMSS is derived from along track MPs and data from geodetic phases Thus any error on the MP is alsocontained in the MSS There are essentially 4 types of additional errors on gridded MSS which are hard toquantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
Note that for the Arctic regional products the DTU10 MSS [1] is taken into account instead of the CLS01MSS Indeed the accuracy of DTU10 compared to CLS01 is further demonstrated by the significant sealevel anomaly variance reduction found over the whole Arctic Ocean as shown in Prandi et al [42]
III262 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III263 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
Page 29
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III27 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III271 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
Page 30
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III272 Performance indicators
To appreciate the quality situation of the DUACS system new performance indicators are computed dailyThey aim at evaluate the status of the main processing steps of the system the input data availability theinput data coverage the input data quality and the output product quality These indicators are computed foreach and every currently working satellite and combined to obtain the overall status
Figure 8 Example with the key performance indicator on 20090627
See the description the latest and previous indicators on Aviso websitehttpwwwavisooceanobscomindexphpid=1516
Page 31
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III3 Delayed Time processing steps
III31 Input data models and corrections applied
Delayed Time MyOcean products are generated
bull from Aviso GDR products for TP Jason-1 Jason-2 and Envisat (GDR-A cycles 1 to 22 GDR-Bcycles 23 to 85 GDR-C from cycle 86)
bull from NOAA GDR for GFO and from CERSAT (IFREMER) OPR for ERS-1 and ERS-2 (phases C(1st 35-day repeat orbit period) phase E and F (geodetic phases) phase G for ERS-1 (last 35-dayrepeat orbit period tandem phase with ERS-2 phase A for ERS-2 (1st 35-day repeat orbit periodtandem phase with ERS-1))
All GDR products are computed with a Precise Orbit Ephemeris (POE) and are delivered within 2 to 3months depending on the mission For several missions an updated orbit is used
bull For ERS-1amp-2 the orbit used is DGME-04 provided by Delft Institute (httpwwwdeostudelftnl)until June 2003
bull For TopexPoseidon the orbit used is GSFC (std0809) for the whole mission
bull For Envisat CNES POE of GDR-C standard is used for the whole mission
bull For the whole GFO mission the orbit used is GSFC (std0809) and when not available NASA POE isused
Altimetric product Source Availability Type of orbit
TopexPoseidon GDR NASACNES - GSFC POE
Jason-1 GDR (GDR-C) CNESNASA ~40 days CNES POE
Jason-2 GDR (GDR-C) CNESNASA ~60 days CNES POE
GFO GDR NOAA - GSFCNASA POE
ERS-1amp2 IFREMERESA - DGME-04
Envisat (GDR-A GDR-B andGDR-C from cycle 86)
ESA ~2 months CNES POE
Table 5 SSALTODUACS Delayed Time Input data overview
Page 32
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
DU
AC
S20
11D
Tpr
oduc
t(gtV
30
0)j2
j1j1
ntp
tpn
e1e2
ene
nng2
Prod
uct
stan
dard
ref
GD
R-C
OPR
GD
R-A
(Cyc
les
1to
22)
GD
R-B
(cyc
les
23-8
5)
GD
R(N
OA
A)
Orb
itC
nes
POE
GSF
C(I
TR
F20
05G
RA
CE
last
stan
dard
s)
DG
ME
-04
(Sch
arro
oan
dV
isse
r19
98[4
8]C
NE
SPO
E(G
DR
-1st
anda
rds
forc
ycle
s9
to22
GD
R-C
stan
dard
sfr
omcy
cle
23)
GSF
C(I
TR
F20
05
GR
AC
Ela
stst
anda
rds
Iono
pher
icD
ual f
requ
ency
altim
eter
rang
em
easu
rem
ents
Dua
l fre
quen
cyal
timet
erra
nge
mea
sure
men
ts(T
opex
)D
OR
IS(P
OSE
IDO
N)
Ben
t mod
elB
ent m
odel
(cyc
les
1-36
)G
IMm
odem
from
cycl
e37
((Ii
jima
etal
19
98[2
4])
Dua
l-fr
eque
ncy
altim
eter
rang
em
easu
rem
ent(
cycl
e9-
64)a
ndG
IMm
odel
gtcyc
le65
(Iiji
ma
etal
19
99[2
4])c
orre
cted
from
8m
mbi
as
From
GIM
mod
el(I
ijim
aet
al1
998
[24]
)
Dry
trop
o-sp
here
Mod
elco
mpu
ted
from
EC
MW
FG
auss
ian
grid
s(n
ewS1
and
S2at
mos
pher
ictid
esar
eap
plie
d)
Mod
elco
mpu
ted
from
EC
MW
Fre
ctan
gula
rgri
ds(n
ewS1
and
S2at
mos
pher
ictid
esar
ein
clud
ed)
Wet
trop
o-sp
here
JMR
AM
Rra
diom
eter
furt
hert
han
50km
from
the
coas
tsF
rom
EC
MW
Fm
odel
ford
ista
nces
betw
een
10an
d50
km
TM
Rra
diom
eter
(Sch
aroo
etal
20
04[4
9])
MW
RC
orre
ctio
nof
the
drif
ton
the
236
GH
zbr
ight
ness
tem
pera
ture
(Sch
arro
oet
al
2004
[49]
)Neu
ral
Net
wor
kal
gori
thm
(Tra
nan
dO
blig
is
2003
[50]
MW
Rra
diom
eter
furt
hert
han
50km
from
the
coas
tsan
dco
rrec
ted
from
side
lobe
s(f
rom
cycl
e41
)E
CM
WF
mod
elfo
rdis
tanc
esbe
twee
n10
and
50km
GFO
radi
omet
er
DA
CM
OG
2DH
igh
Res
olut
ion
forc
edw
ithE
CM
WF
pres
sure
and
win
gfie
lds
(S1
and
S2w
ere
excl
uded
)+in
vers
eba
rom
eter
com
pute
dfr
omre
ctan
gula
rgri
ds
Tabl
e6
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(1
2)
Page 33
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
j2j1
j1n
tptp
ne1
e2en
enn
g2O
cean
tide
GO
T4v
7(S
1an
dS2
are
incl
uded
)Po
letid
e[W
ahr
1985
[53]
]So
lidea
rth
tide
Ela
stic
resp
onse
totid
alpo
tent
ial[
Car
twri
ghta
ndTa
yler
197
1[5]
][C
artw
righ
tand
Edd
en1
973[
6]]
Loa
ding
tide
GO
T4v
7(S
1pa
ram
eter
isin
clud
ed)
Sea
stat
ebi
asN
onpa
ram
etri
cSS
B[G
aspa
reta
l20
02[2
0]]
Non
para
met
ric
SSB
[NT
ran
and
al2
010[
51]]
BM
3[G
aspa
ran
dO
gor
1994
[17]
]
Non
para
met
ric
SSB
[Mer
tzet
al
2005
[38]
]
Non
para
met
ric
SSB
[Gas
pare
tal
2002
]w
ithG
DR
-Bst
anda
rds
forc
ycle
s9
to85
and
with
GD
R-C
stan
dard
sfr
omcy
cle
86
Non
para
met
ric
SSB
[NT
ran
etal
20
10[5
1]]
Orb
iter
ror
Glo
bal m
ulti-
mis
sion
cros
sove
rmin
imiz
atio
n(L
eTr
aon
and
Ogo
r19
98[3
2])
Lon
gw
ave-
leng
her
rors
Opt
imal
Inte
rpol
atio
n(L
eTr
aon
etal
19
98[3
1])
Inte
rcal
ibra
tion
Ref
eren
cefr
omcy
cle
11R
efer
ence
from
cycl
e1
to35
4C
orre
ctio
nof
regi
onal
bias
J2J
1de
duce
dfr
omin
terc
alib
ratio
nph
ase
(cyc
le11
J2)
Cor
rect
ion
ofgl
obal
biai
sJ1
TP
deacutedu
ced
from
inte
rcal
ibra
tion
phas
e(c
ycle
s11
J1)
Mea
npr
o-fil
e(s
eeII
I36
1)
Com
pute
dw
ithcy
cles
11-3
53T
Pda
taan
dw
ithcy
cles
11-2
50J1
data
ref
eren
ced
[199
319
99]
TP
J1 c
ompu
ted
with
cycl
es11
-353
TP
data
and
with
cycl
es11
-250
J1da
tar
efer
ence
d[1
993
1999
]T
PNJ
1Nc
ompu
ted
with
cycl
es36
9-47
9T
PNda
tar
efer
ence
d[1
993
1999
]
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
ref
eren
ced
[199
319
99]
EN
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
re
fere
nced
[199
319
99]
EN
Nu
seof
MSS
_CN
ES_
CL
S11
[39]
Com
pute
dw
ithcy
cles
37-1
87G
2da
ta
refe
renc
ed[1
993
1999
]
Peri
odof
use
from
cycl
e9
from
cycl
e9
cycl
es1
to48
1cy
cles
15to
43In
clud
ing
E-F
geod
etic
phas
es
cycl
es1
to83
from
cycl
e9
cycl
es37
to22
2
Tabl
e7
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(2
2)
Page 34
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III32 Acquisition
The acqusition process in Delayed time is much simpler than in Near Real time it consists in a synchronisa-tion process of all the auxiliary data required to homogenize propely the altimeter data sets The acquisitionstep uses the GDRs or the OPRs provided by the agencies
III33 Homogenization
The Homogenization process consists in applying the most recent corrections models and references rec-ommended for altimeter products Each mission is processed separately as its needs depend on the baseinput data The list of corrections and models currently applied is provided in tables 6 and 7 for DT data
III34 Input data quality control
The Input Data Quality Control is a critical process applied to guarantee that DUACS uses only the mostaccurate altimeter data Thanks to the high quality of current missions this process rejects a small percent-age of altimeter measurements but these erroneous data could be the cause of a significant quality lossThe quality control relies on standard raw data editing with quality flags or parameter thresholds but alsoon complex data editing algorithms based on the detection of erroneous artefacts mono and multi-missioncrossover validation and macroscopic statistics to edit out large data flows that do not meet the systemrsquosrequirements
Page 35
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III35 Multi-mission cross-calibration
The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistentand accurate information It removes any residual orbit error (OE Le Traon and Ogor 1998[32]) or longwavelength error (LWE Le Traon et al 1998[31]) as well as large scale biases and discrepancies betweenvarious data flows
This process is based on two very different algorithms a global multi-mission crossover minimization fororbit error reduction (OER) and Optimal Interpolation (OI) for LWE
Multi-satellite crossover determination is performed on a daily basis All altimeter fields (measurementcorrections and other fields such as bathymetry MSS) are interpolated at crossover locations and datesCrossovers are then appended to the existing crossover database as more altimeter data become availableThis crossover data set is the input of the Orbit Error Reduction (OER) method Using the precision of thereference mission orbit a very accurate orbit error can be estimated LWE is mostly due to residual tidalor inverse barometer errors and high frequency ocean signals The OI used for LWE reduction uses preciseparameters derived from
bull accurate statistical description of sea level variability
bull localized correlation scales
bull mission-specific noise and precise assumptions on the long wavelength errors to be removed (from arecent analysis of one year of data from each mission)
Page 36
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III36 Product generation
The product generation process is composed of four steps computation of raw SLA cross-validationfilteringampsub-sampling and generation of by-products
III361 Computation of raw SLA
Since the geoid is not well known yet the SSH cannot be used directly the SSH anomalies are used insteadThey are computed from the difference of the instantaneous SSH - a temporal reference This temporalreference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeattrack analysis cannot be used The errors affecting the SLAs MPs and MSS have different magnitudes andwavelengths The computation of the SLAs and their errors associated are detailed in Dibarboure et al 2010[9]
Use of a Mean ProfileIn the repeat track analysis (when the satellites flies over a repetitive orbit) measurements are re-sampledalong a theoretical ground track (or mean track) associated to each mission Then a Mean Profile (MP) issubtracted from the re-sampled data to obtain SLA The MP is a time average of similarly re-sampled dataover a long period
bull The Mean Profile used for TP (cycles 1 to 364) Jason-1 (cycles 1 to 259) and Jason-2 is computedwith 10 years of TP (cycles 11 to 353) and 6 years of Jason-1 (cycles 11 to 250)
bull The Mean Profile used for TP (cycles 368 to 481) and from Jason-1 cycle 262 to 374 (where satellitesare on interleaved ground-tracks) is computed with 3 years of TP (cycles 369 to 479)
bull The Mean Profile used for ERS-1 in its 35 days repetitive orbit mission ERS-2 and Envisat (only forthe first orbit before November 2010) is computed with 8 years of ERS-2 (cycles 1 to 85) and 6 yearsof Envisat (cycles 10 to 72)
bull No Mean Profile can be used for Envisat on its new orbit (enn) Jason-1 on its geodetic orbit (j1g)because there is no repetitive track The MSS must be used instead (see below)
bull The Mean Profile used for GFO is computed with 7 years of GFO cycles 37 to 187
Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible
bull Indeed as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide precise cross-track projection andor interpolation schemes are required to avoid errors
bull The mesoscale variability error (which is lt35 cm for MP between 3 to 5 years and lt1cm for WLof 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a prioriknowledge from Sea Level maps derived from previous iterations or from other missions
Page 37
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for ERS-1 for its 168 days geodetic mission (phases E-F from April1994 to March 1995) or for Envisat since november 2010 because the satellite is not in a repetitive orbitphase The alternative is to use the MSS instead The gridded MSS is derived from along track MPs anddata from geodetic phases Thus any error on the MP is also contained in the MSS There are essentially 4types of additional errors on gridded MSS which are hard to quantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
III362 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III363 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
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III37 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III371 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
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IV MYOCEAN PRODUCTS
IV1 Near Real Time Products
The purpose of the NRT DUACS component is the acquisition of altimeter data from various altimeter mis-sions in near-real time (ie within a few days at most) the validation and correction of these altimeter datasets (ie edition and selection update of corrections and homogenization orbit error reduction) in order toproduce each day along-track productsProducts are as follows
Along-track products global and regional (Mediterranean and Black Seas Arctic Ocean and Europeareas)
bull Sea Level Anomaly (NRT-SLA) for each mission with NRT-SLA ephemeris
IV11 Delay of the products
The availability of the products in near real time is three to twelve hours after the measurement for along-track products Those products are delivered every day
IV12 Temporal availibility
The following table presents the available products by mission and by data periodNear real time products
NRT Jason-2 Jason-1 and Jason-1geodetic
Envisat new Cryosat-2
Temporal Time availability ymlowast
ongoingymlowast-20120303 for
repeat track and20120507-ongoing for
geodetic track
ymlowast
2012040820120101
ongoing
NRT-SLA X X X X
lowastym the temporal coverage for NRT products is fluctuating and depends on updates of Delayed Time prod-ucts When DT products are updated (3 to 4 times per year) the oldest NRT products are replaced by thebetter quality DT products so that the 2 series are overlapping on few weeks or few months
IV2 Delayed Time Products
The Delayed Time component of SSALTODUACS system is responsible for the production of processedJason-1 Jason-2 TP Envisat GFO ERS12 and even Geosat data in order to provide a homogeneousinter-calibrated and highly accurate long time series of SLA DT products are more precise than NRT products Two reasons explain this quality difference The firstone is the better intrinsic quality of the POE orbit used in the GDR processing The second reason is that
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in the DT DUACS processing the products can be computed optimally with a centred computation timewindow for OER LWE On the contrary in NRT case future data are not available so the computationtime window is not centred and therefore not optimalAs for NRT products improved altimeter corrections and processing algorithms are used ocean tide modelto correct altimeter data improved methods for orbit error reduction and mapping
Along-Track products global and regional (Mediterranean and Black Seas)
bull Sea Level Anomaly (DT-SLA) for each mission
IV21 Delay of the products
Weekly products are delivered The availability of the products in delayed time is at the best two monthsafter the date of the measurement The product generation needs all the GDR data of all the missions to takeinto account the best corrections as possible The time delay can be longer in the case of a missing mission
IV22 Temporal availibility
The following table presents the available products by mission and by data periodDelayed time SSALTODUACS products
Upd Jason-2 Jason-1new6
Jason-1 GFO Envisatnew6
Envisat ERS-16
ERS-2Topexnew6
Topex
TemporalTimeavailabil-ity
200810ymlowast
200902ymlowast
200204200810
200001200809
201010ymlowast
200210201010
199210200304
200209200510
199209200204
DT-SLA X X X X X X X X X
lowast ym those dates are updated regularly (3 to 4 times per year) and are avalaible when you download thedata at httpwwwmyoceaneuweb24-cataloguephp6 Jason-1 new orbit starting 200809 Envisat new orbit starting 201010 TP new orbit starting 200209 ERS-1The geodetic phases (E-F) are included There are no ERS-1 data between December 23 1993 and April 10 1994(ERS-1 phase D - 2nd ice phase) Note that during that time products are based only on TopexPoseidon data
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V DESCRIPTION OF THE PRODUCT SPECIFICATION
V1 General information
Product Specification SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001
Geographical coverage global
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 20-50km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001 Product Specification
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Product Specification SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002
Geographical coverage 55˚W-35˚E 30˚N-46˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002 Product Specification
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Product Specification SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003
Geographical coverage 27˚E-42˚E 40˚N-47˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003 Product Specification
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Product Specification SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004
Geographical coverage 25˚W-42˚E 21˚N-66˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004 Product Specification
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Product Specification SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005
Geographical coverage 0˚W-360˚E 50˚N-82˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005 Product Specification
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VI NOMENCLATURE OF FILES
VI1 Nomenclature of files downloaded through the MyOcean Web PortalDirectgetfile Service
VI11 Nomenclature of the product line
The description of the syntax for the SL TAC SLA products line is given by
SEALEVEL_ltREGIONgt_SLA_L3_ltDELAYgt_OBSERVATIONS_008_ltZONEgt_ltLETTERgtwhere
REGION GLO global geographic coverage product
BS Black Sea products
MED Mediterranean products
ARC Arctic products (for NRT products)
EUROPE Europe products (for NRT products)
DELAY NRT near real time products
RAN delayed time or reanalysis products
ZONE 001 number on 3 digits
002
003
004
LETTER a letter on 1 digit
b
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VI12 Nomenclature of the datasets
The nomenclature used is
dataset-duacs-ltdelaygt-ltzonegt-ltmissiongt-lttype of slagt-l3where the fileds in ltgt are described below
delay nrt near-real time productsran delayed time products
zone global global geographic coverage productmedsea Mediterranean productsblacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1 (only for ran)e2 ERS-2 (only for ran)tp TOPEXPoseidon (only for ran)tpn TOPEXPoseidon on its new orbit (only for
ran)g2 GFO (only for ran)j1 Jason-1 (only for ran)j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisat (only for ran)enn Envisat on its new orbitc2 Cryosat-2 (only for nrt)
type of sla sla filtered slasla_unfiltered non filtered sla (only for ran products)
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VI13 Nomenclature of the NetCdf files
The nomenclature used is
ltdelaygt_ltzonegt_ltmissiongt_sla_ltvariablegt_ltdatebegingt_ltdateendgt_ltdateprodgtnc where the fileds in ltgt are de-scribed below
delay nrt near-real time productsdt delayed time products
zone global global geographic coverage productmed Mediterranean products (for dt)mfstep Mediterranean products (for nrt)blacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1e2 ERS-2tp TOPEXPoseidontpn TOPEXPoseidon on its new orbitg2 GFOj1 Jason-1j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisatenn Envisat on its new orbitc2 Cryosat-2
variable vfec filtered and sub-sampled slavxxc non filtered and non sub-sampled sla (only
for dt)datebegin YYYYMMDD() beginning date of the datasetdateend YYYYMMDD() end date of the datasetdateprod YYYYMMDD production date of the dataset
() For dt data as the dates in the file names are rounded the user wanting data for date T has to read the filescontaining dates T+1 and T-1 in their name and check inside the files if there are some data for date T
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VII DATA FORMAT
This chapter presents the data storage format used for MyOcean products
VII1 NetCdf
The products are stored using the NetCDF format NetCDF (network Common Data Form) is an interface for array-oriented data access and a library that provides an implementation of the interface The netCDF library also definesa machine-independent format for representing scientific data Together the interface library and format support thecreation access and sharing of scientific data The netCDF software was developed at the Unidata Program Center inBoulder Colorado The netCDF libraries define a machine-independent format for representing scientific data Pleasesee Unidata NetCDF pages for more information and to retreive NetCDF software package onhttpwwwunidataucaredupackagesnetcdfindexhtml
NetCDF data is
bull Self-Describing A netCDF file includes information about the data it contains
bull Architecture-independent A netCDF file is represented in a form that can be accessed by computers with dif-ferent ways of storing integers characters and floating-point numbers
bull Direct-access A small subset of a large dataset may be accessed efficiently without first reading through allthe preceding data
bull Appendable Data can be appended to a netCDF dataset along one dimension without copying the dataset orredefining its structure The structure of a netCDF dataset can be changed though this sometimes causes thedataset to be copied
bull Sharable One writer and multiple readers may simultaneously access the same netCDF file
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VII2 Structure and semantic of NetCDF along-track files
The NetCDF Sea Level TAC files are based on the attribute data tags defined by the Cooperative OceanAtmosphereResearch Data Service (COARDS) and Climate and Forecast (CF) metadata conventions The CF convention gener-alises and extends the COARDS convention but relaxes the COARDS constraints on dimension and order and specifiesmethods for reducing the size of datasetsA wide range of software are available to write or read NetCDFCF files API are made available by UNIDATA(httpwwwunidataucaredusoftwarenetcdf)
bull CC++Fortran
bull Java
bull MATLAB Objective-C Perl Python R Ruby TclTk
In addition to these conventions the files are using a common structure and semantic
bull 1 dimension is defined
ndash time it is used to check NetCDF variables depending on time
bull 8 variables are defined
ndash short SLA contains the Sea Level Anomaly values for each time given
ndash int longitude contains the longitude for each measurement
ndash short track contains the track number for each measurement
ndash double time contains the time in days since 1950-01-01 000000 UTC for each measurement
ndash short mean_profile_point_index index of the corrsponding point in the track of the mean profile
ndash byte flag flag=0 the processed data comes from OGDR if flag=1 the processed data comes from theIGDR
ndash int latitude contains the latitude for each measurement
ndash short cycle contains the cycle number for each measurement
bull global attributes
ndash the global attributes gives information about the creation of the file
Example of a NetCDF sla file
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netcdf nrt_global_j1_sla_vfec_20101230_20101230_20101230 dimensions
time = 10385 variables
short SLA(time) SLAcoordinates = longitude latitude SLAlong_name = Sea Level Anomaly SLA_FillValue = 32767s SLAadd_offset = 0 SLAscale_factor = 0001 SLAunits = m SLAstandard_name = sea_surface_height_above_sea_level
int longitude(time) longitudelong_name = Longitude of measurement longitude_FillValue = 2147483647 longitudeadd_offset = 0 longitudestandard_name = longitude longitudescale_factor = 1e-06 longitudeunits = degrees_east
short track(time) tracklong_name = Track in cycle the measurement belongs to track_FillValue = 32767s trackunits = 1 trackcoordinates = longitude latitude
double time(time) timelong_name = Time of measurement time_FillValue = 184467440737096e+19 timeaxis = T timestandard_name = time timeunits = days since 1950-01-01 000000 UTC
int latitude(time) latitudelong_name = Latitude of measurement latitude_FillValue = 2147483647 latitudeadd_offset = 0 latitudestandard_name = latitude latitudescale_factor = 1e-06 latitudeunits = degrees_north
short flag(time) flagcoordinates = longitude latitude flag_FillValue = 3267s flaglong_name = data origin flagflag_values = 1s 0s flagflag_meanings = igdr_like non_igdr_like flagcomment = The origin of the data is determined by the types of geophysical datarecords (GDR) used in computation of the SLA 1 for the Interim GDR (IGDR) and0 for Operational GDR (OGDR)
short cycle(time) cyclelong_name = Cycle the measurement belongs to cycle_FillValue = 32767s cycleunits = 1 cyclecoordinates = longitude latitude
global attributeshistory = 22-Feb-2011 155243 CET File created by the SSLATODUACS system version 1001 comment = Produce from ENVISAT Extension Phase satellite altimetry data institution = CLSCNES
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references = httpwwwavisooceanobscomfileadmindocumentsdatatoolshdbk_duacspdf source = satellite altimetry title = along track Sea Level Anomaly Conventions = CF-14
dataSLA =
7 7 11 10 -2 -22 -39 -41 -30 -13 -3 -5 -16 -26 -32 -35-35 -35 -37 -35 -31 -29 -31 -35 -32 -21 -10 -10 -19 -20 -1-69 -57 -49 -45 -39 -30 -28 -31 -27 -13 -2 -5 -15 -3 1112 3 -7 -10 -14 -15 -22 -31 -37 -32 -17 -10
longitude =74743328 74868400 74993968 75120040 75246616 7537372875501368 75629568 75758320 75887656 76017568 76148080 7627920876388952 76477056 76565456 76654144 76743128 76832400 76921984329429568 329535424 329641792 329748672 329856096 329964032330072512 330181536 330291072 330401184
track =92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 9292 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92113 113 113 113 113 113 113 113 113 113 113 113 113 113113 113 113 113 113 113 113 113 113
time =222780000565705 222780001314719 222780002063733222780002812747 222780003561761 222780004310775 222780005059788222780005808802 222780006557816 22278000730683 222780008055844222780008804858 222780009553872 22278001017805 222780010677393222788257112198 222788257486705 222788257861212 222788258235719222788258610226 222788258984733 222788259359239 222788259733746222788260108253 22278826048276
mean_profile_point_index =1872 1878 1884 1890 1896 1902 1908 19141920 1926 1932 1938 1944 1949 1953 1957 1961 1965 1969 19732306 2309 2312 2315 2318 2321 2327 2330 2333 2336 2339 23422345 2348 2351 2354 2357 2360 2363 2366
flag =0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
latitude =-16225506 -16539731 -16853833 -17167810 -17481660 -17795380-18108966 -18422418 -18735729 -19048899 -19361924 -19674801-19987527 -20248015 -20456329 -20664569 -20872739 -2108083739481297 39628277 39775133 39921866 40068472 40214953 4036130840507533 40653629 40799592 40945423 41091120 41236684 41382111
cycle =331 331 331 331 331 331 331 331 331 331 331 331 331
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331 331 331 331 331 331 331 331 331 331 331 331 331 331331 331 331 331 331 331 331 331 331 331 331 331
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VIII HOW TO DOWNLOAD A PRODUCT
VIII1 Download a product through the MyOcean Web Portal DirectgetfileService
You first need to register Please find below the registration stepshttpwwwmyoceaneuweb34-products-and-services-faqphp1Once registered the MyOcean FAQ httpwwwmyoceaneuweb34-products-and-services-faqwill guide you on How to download a product through the MyOcean Web Portal Directgetfile Service
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IX NEWS AND UPDATES
IX1 [Duacs] Operational news
To be kept informed on events occurring on the satellites and on the eventual interruption of the services of the DUACSprocessing system see the [Duacs] operational news on the Aviso websitehttpwwwavisooceanobscomendataoperational-newsindexhtml
IX2 Updates
To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtmlSince 2010 a complete reprocessing of all altimetry data (cumulated total of about 55 years of data) is available Themain changes introduced in the Duacs DT v300 reprocessed data set in SSALTODUACS reprocessed DT data setare listed herehttpwwwavisooceanobscomfileadmindocumentsdataduacsduacs_DT_2010_reprocessing_impactpdf
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REFERENCES
[1] Andersen O B The DTU10 Gravity filed and Mean sea surface (2010) Second international sympo-sium of the gravity field of the Earth (IGFS2) Fairbanks Alaska
[2] Boy F et al (2011) Cryosat LRM TRK and SAR processing Presented at the 2011 Ocean Sur-face Topography Science Team meeting httpwwwavisooceanobscomfileadmindocumentsOSTST2011oral01_Wednesday
[3] Carrere L F Lyard 2003 Modeling the barotropic response of the global ocean to atmo-spheric wind and pressure forcing- comparisons with observations J Geophys Res 30(6) 1275doi1010292002GL016473
[4] Carrere L 2003 Etude et modeacutelisation de la reacuteponse HF de lrsquooceacutean global aux forccedilagesmeacuteteacuteorologiques PhD thesis Universiteacute Paul Sabatier (Toulouse III France) 318 pp
[5] Cartwright D E R J Tayler 1971 New computations of the tide-generating potential Geophys JR Astr Soc 23 45-74
[6] Cartwright D E A C Edden 1973 Corrected tables of tidal harmonics Geophys J R Astr Soc33 253-264
[7] Following the scientific recommendations from the OSTST meeting (San Diego October 2011) theESA Cryosat Project and the CNES SALP Project have been collaborating to generate these Cryosat-derived L3 and L4 products Level 1B and Level 2 products derived from CNES processors are notdistributed by AVISO as per the CNES ESA agreement
[8] Dibarboure G C Renaudie M-I Pujol S Labroue N Picot 2011 A demonstrationof the potential of Cryosat-2 to contribute to mesoscale observation J Adv Space Resdoi101016jasr201107002 httpdxdoiorg101016jasr201107002
[9] Dibarboure G P Schaeffer P Escudier M-IPujol JF Legeais Y Faugegravere R Morrow JK WillisJ Lambin JP Berthias N Picot 2010 Finding desirable orbit options for the Extension of Lifephase of Jason-1 Submitted to Marine Geodesy
[10] Dibarboure G M-IPujol FBriol PYLe Traon GLarnicol NPicot FMertz P Escudier MAblainCDufau 2010 Jason-2 in DUACS first tandem results and impact on processing and products Sub-mitted in Marine Geodesy
[11] Dibarboure G 2009 Using short scale content of OGDR data improve the Near Real Time productsof SsaltoDuacs oral presentation at Seattle OSTST meeting (pdf)
[12] Dorandeu J M Ablain Y Faugegravere F Mertz B Soussi and P Vincent 2004 Jason-1 global statisti-cal evaluation and performance assessment Calibration and cross-calibration results Marine Geodesy27(3-4) 345-372
[13] Dorandeu J M Ablain P-Y Le Traon 2003 Reducing Cross-Track Geoid Gradient Errors aroundTOPEXPoseidon and Jason-1 Nominal Tracks Application to Calculation of Sea Level AnomaliesJ of Atmosph and Ocean Techn20 1826-1838
[14] Dorandeu J and P-Y Le Traon 1999 Effects of global mean atmospheric pressure variations onmean sea level changes from TOPEXPoseidon J Atmos Oceanic Technol 16 1279-1283
[15] Ducet N P-Y Le Traon and G Reverdin 2000 Global high resolution mapping of ocean circulationfrom TOPEXPoseidon and ERS-1 and -2 J Geophys Res 105 19477-19498
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[16] Egbert Gary D Svetlana Y Erofeeva 2002 Efficient Inverse Modeling of Barotropic Ocean Tides JAtmos Oceanic Technol 19 183-204 doi 1011751520-0426(2002)019lt0183EIMOBOgt20CO2
[17] Gaspar P and F Ogor Estimation and analysis of the Sea State Bias of the ERS-1 altimeter Reportof task B1-B2 of IFREMER Contract n˚ 942426 016C 1994
[18] Gaspar P F Ogor and C Escoubes 1996 Nouvelles calibration et analyse du biais drsquoeacutetat de mer desaltimegravetres TOPEX et POSEIDON Technical note 96018 of CNES Contract 951523 1996
[19] Gaspar P and F Ogor Estimation and analysis of the Sea State Bias of the new ERS-1 and ERS-2altimetric data (OPR version 6) Report of task 2 of IFREMER Contract n˚ 962246 002C 1996
[20] Gaspar P S Labroue and F Ogor 2002 Improving nonparametric estimates of the sea state bias inradar altimeter measurements of seal level J Atmos Oceanic Technology 19 1690-1707
[21] Hernandez F P-Y Le Traon and R Morrow 1995 Mapping mesoscale variability of the AzoresCurrent using TOPEXPOSEIDON and ERS-1 altimetry together with hydrographic and Lagrangianmeasurements Journal of Geophysical Research 100 24995-25006
[22] Hernandez F and P Schaeffer 2000 Altimetric Mean Sea Surfaces and Gravity Anomaly maps inter-comparisons AVI-NT-011-5242-CLS 48 pp CLS Ramonville St Agne
[23] Hernandez F M-H Calvez J Dorandeu Y Faugegravere F Mertz and P Schaeffer 2000 Sur-face Moyenne Oceacuteanique Support scientifique agrave la mission altimeacutetrique Jason-1 et agrave une mis-sion micro-satellite altimeacutetrique Contrat SSALTO 2945 - Lot 2 - A1 Rapport drsquoavancementCLSDOSNT00313 40 pp CLS Ramonville St Agne
[24] Iijima BA IL Harris CM Ho UJ Lindqwiste AJ Mannucci X Pi MJ Reyes LC SparksBD Wilson 1999 Automated daily process for global ionospheric total electron content maps andsatellite ocean altimeter ionospheric calibration based on Global Positioning System data J AtmosSolar-Terrestrial Physics 61 16 1205-1218
[25] Labroue S F Boy N Picot M Urvoy M Ablain First quality assessment of the Cryosat-2 altimetricsystem over ocean J Adv Space Res 2011 doi101016jasr201111018 httpdxdoiorg101016jasr201111018
[26] Labroue S 2007 RA2 ocean and MWR measurement long term monitoring 2007 report for WP3Task 2 - SSB estimation for RA2 altimeter Contract 1729303I-OL CLS-DOS-NT-07-198 53ppCLS Ramonville St Agne
[27] Labroue S P Gaspar J Dorandeu OZ Zanifeacute F Mertz P Vincent and D Choquet 2004 Nonparametric estimates of the sea state bias for Jason-1 radar altimeter Marine Geodesy 27 453-481
[28] Lagerloef GSE GMitchum RLukas and PNiiler 1999 Tropical Pacific near-surface currentsestimated from altimeter wind and drifter data J Geophys Res 104 23313-23326
[29] Le Traon P-Y and F Hernandez 1992 Mapping the oceanic mesoscale circulation validation ofsatellite altimetry using surface drifters J Atmos Oceanic Technol 9 687-698
[30] Le Traon P-Y P Gaspar F Bouyssel and H Makhmara 1995 Using TopexPoseidon data to en-hance ERS-1 data J Atmos Oceanic Technol 12 161-170
[31] Le Traon P-Y F Nadal and N Ducet 1998 An improved mapping method of multisatellite altimeterdata J Atmos Oceanic Technol 15 522-534
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[32] Le Traon P-Y and F Ogor 1998 ERS-12 orbit improvement using TOPEXPOSEIDON the 2 cmchallenge J Geophys Res 103 8045-8057
[33] Le Traon P-Y and G Dibarboure 1999 Mesoscale mapping capabilities of multi-satellite altimetermissions J Atmos Oceanic Technol 16 1208-1223
[34] Le Traon P-Y G Dibarboure and N Ducet 2001 Use of a High-Resolution Model to Analyze theMapping Capabilities of Multiple-Altimeter Missions J Atmos Oceanic Technol 18 1277-1288
[35] Le Traon PY and G Dibarboure 2002 Velocity mapping capabilities of present and future altimetermissions the role of high frequency signals J Atmos Oceanic Technol 19 2077-2088
[36] Le Traon PY Faugegravere Y Hernandez F Dorandeu J Mertz F and M Ablain 2002 Can we mergeGEOSAT Follow-On with TOPEXPOSEIDON and ERS-2 for an improved description of the oceancirculation J Atmos Oceanic Technol 20 889-895
[37] Le Traon PY and G Dibarboure 2004 An Illustration of the Contribution of the TOPEXPoseidon-Jason-1 Tandem Mission to Mesoscale Variability Studies Marine Geodesy 27 (1-2)
[38] Mertz F F Mercier S Labroue N Tran J Dorandeu 2005 ERS-2 OPR data quality assessment Long-term monitoring - particular investigation CLSDOSNT-06001 (pdf)
[39] MSS_CNES_CLS11 was produced by CLS Space Oceanography Division and distributed by Avisowith support from Cnes (urlhttpwwwavisooceanobscom)
[40] Pascual A Y Faugegravere G Larnicol P-Y Le Traon 2006 Improved description of the oceanmesoscale variability by combining four satellite altimeters Geophys Res Lett 33
[41] Pascual A C Boone G Larnicol and P-Y Le Traon 2009 On the quality of Real-Time altimetergridded fields comparison with in-situ data Journ of Atm and Ocean Techn Vol 26(3) pp 556-569DOI 1011752008JTECHO5561
[42] Prandi P M Ablain A Cazenave N Picot 2011 A new estimation of mean sea level in the ArcticOcean from satellite altimetry Submitted to Marine Geodesy
[43] Pujol M-I et al 2009 Three-satellite quality level restored in NRT poster at OSTST meeting (pdf)
[44] Ray R 1999 A Global Ocean Tide model from TOPEXPoseidon Altimetry GOT992 NASA TechMemo NASATM-1999-209478 58 pp Goddard Space Flight Center NASA Greenbelt MD USA
[45] Rio M-H and F Hernandez 2003 A Mean Dynamic Topography computed over the worldocean from altimetry in-situ measurements and a geoid model J Geophys Res 109 C12032doi1010292003JC002226
[46] Rio M-H and F Hernandez 2003 High frequency response of wind-driven currents measured bydrifting buoys and altimetry over the world ocean J Geophys Res 108 39-1
[47] Rio M-H 2003 Combinaison de donneacutees in situ altimeacutetriques et gravimeacutetriques pour lrsquoestimationdrsquoune topographie dynamique moyenne globale Ed CLS PhD Thesis University Paul Sabatier(Toulouse III France) 260pp
[48] Scharroo R and P Visser 1998 Precise orbit determination and gravity field improvement for theERS satellites J Geophys Res 103 8113-8127
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[49] Scharroo R J Lillibridge and WHF Smith 2004 Cross-calibration and long-term monitoring ofthe Microwave Radiometers of ERS Topex GFO Jason-1 and Envisat Marine Geodesy 97
[50] Tran N and E Obligis December 2003 Validation of the use of ENVISAT neural algorithms onERS-2 CLSDOSNT03901
[51] Tran N S Labroue S Philipps E Bronner and N Picot 2010 Overview and Update of the SeaState Bias Corrections for the Jason-2 Jason-1 and TOPEX Missions Marine Geodesy accepted
[52] Vincent P Desai SDDorandeu J Ablain M Soussi B Callahan PS and BJ Haines 2003 Jason-1 Geophysical Performance Evaluation Marine Geodesy 26 167-186
[53] Wahr J W 1985 Deformation of the Earth induced by polar motionJ of Geophys Res (Solid Earth)90 9363-9368
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I INTRODUCTION
MyOcean is a European Network project aiming at monitoring analyzing and forecasting the Ocean Ituses satellite and in-situ data to describe the ocean in 3 dimensions and real time More information can befound on httpwwwmyoceaneuorgThe aim of this document is to describe the products delivered by the Sea Level TAC (Thematic AssemblyCentre) which is one of the five TAC of the MyOcean projectThe data produced in the frame of this TAC are generated by the processing system named DUACS (DataUnification and Altimeter Combination System)DUACS is part of the CNES multi-mission ground segment (SSALTO) It processes data from all altimetermissions Cryosat-2 OSTMJason-2 Jason-1 TopexPoseidon Envisat GFO ERS-1amp2 and even GeosatAt this time (May 25th 2012) DUACS is using three different altimeters in near real time Developed and operated by CLS it started as an European Commission Project (Developing Use Of Altime-try for Climate Studies) funded under the European Commission and the Midi-Pyreacuteneacutees regional councilIt has been integrated to the CNES multi-mission ground segment SSALTO in 2001 and it is maintainedupgraded and operated with funding from CNES with shared costs from EU projectsAt the beginning of 2004 DUACS was redefined as the Data Unification Altimeter Combination System
Figure 1 DUACS and AVISO a user-driven altimetry service
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The products lines described in this user manual are the followingSEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005
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The data provided to users have a global coverage (PL SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001)and regional products are also computed over specific areasMediterranean Sea (PL SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002)and Black Sea (PL SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003)Thanks to updates in 2011 and 2012 (see section II) new regional products are now availableEurope (PL SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004)and Arctic (PL SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005)
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II UPDATES IN 2011 AND 2012
This section describes the updates of the SSALTODUACS Near Real Time system that occurred during2011 and 2012 allowing to add new products (Europe and Arctic) the integration of the Cryosat-2 data inthe system the stopping delivery of Envisat data the addition of Jason-1 data on geodetic orbit (j1g)To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtml
II1 Version D of input IGDROGDR Jason-2 data for NRT processing(July 30 2012)
On July 30 2012 the version of Jason-2 IGDROGDR has changed and is now the D version Somecorrections have thus been updated as detailed in tables 3 and 4
II2 Integration of Jason-1 on its geodetic orbit (May 2012)
An anomaly occured on March 3rd 2012 on the Jason-2 mission (see httpwwwavisooceanobscomfractualitesactualitesindexhtmltx_ttnews[tt_news]=1162amptx_ttnews[backPid]=1399ampcHash=d5baeb645e) On April 23rd CNES began to command the satellite into a nadir ori-entation and after some propulsion anomalies CNES and NASA management through the Joint SteeringGroup have directed the Jason-1 Project to then begin a series of maneuvers to place Jason-1 into a neworbit as defined in table 1 After checking the current orbit carefully the operational team determined thata geodetic mission was still possible It was also decided to preserve all remaining fuel for future stationkeeping maneuvers which is mandatory in a geodetic orbit Core payloads were switched ON on May 4thand after some POSEIDON2 radar (PRF) adjustments the mission was resumed on May 7th at 151248UTCBelow are the characteristics of the new orbit which will be maintained as before within +- 1km controlbox at the Equator
Semi major axis 7702437 kmEccentricity 13 to 28 10-4Altitude equator 13240 kmOrbital period 6730s (1h52rsquo10rdquo)Inclination 66042˚Cycle 406 daysSub cycles 39 - 109 - 475 - 1795
days
Table 1 Characteristics of the geodetic orbit for Jason-1 since May 7th 2012
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For this new phase of the Jason-1 mission (called j1g) the cycle numbering will restart at 500 Off-lineproducts will be produced once a day for the IGDR and every 11 days for the GDRrsquos The integration ofJason-1 data in the DUACS system is available since May 25th 2012
II3 Envisat has stopped sending data (April 2012)
Since April 8th 2012 Envisat has stopped sending data to Earth Esarsquos mission control has worked tore-establish contact with the satellite but there has been no reaction from the satellite Thus Esa has de-clared officially the end of mission for Envisat (see httpwwwesaintesaCPSEM1SXSWT1H_index_0html) Therefore no SL TAC NRT data from Envisat can be released since this date
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II4 Integration of the Cryosat2 Mission (February 2012)
Since February 6th 2012 Cryosat-2 mission has been integrated in the DUACS sytem This mission isdedicated to the observation of the floating sea-ice as well as the continental ice sheets but all data acquiredover ocean are valuable for the observation of oceanic circulation and mesoscale variations This majorchange is the result of the long-standing and fruitful partnership between ESA and CNES and a responseto the request from scientific and operational oceanography users [7] The integration of Cryosat-2 impactsthe delivering of Near real time Sea Level Anomalies (SLA)
II41 Generalities about the mission
A Cryosat-2 Processing Prototype (C2P) (described in Boy et al 2011 [2]) has been developed on CNESside to lay the ground for various SAR processing studies The processing chains ingest Level-0 telemetryfiles distributed by ESA and perform the following steps to generate Sea Level Anomalies (SLA) values foreach altimeter measurements
bull Level-1 Decommutation time-tagging and localization of measurements
bull Level-1b Calculation of instrumental corrections and geophysicalmeteorological corrections
bull Level-2 MLE4 waveforms Retracking and calculation of SLA
The prototype processes data almost continuously over ocean either in Low Resolution Mode (LRM) or inthe DopplerSAR mode processed as pseudo-LRM mode allowing to increase the coverage (figure 2)
Figure 2 SSH-MSS for Cryosat-2 with LRM mode only (left) or LRM+pseudo-LRM modes (right)
Although Cryosat-2 raw SSH can be only corrected with GPS-derived ionospheric correction and ECMWFwet troposphere correction validation activities showed (Labroue et al 2011 [25]) that C2P outputs have anaccuracy roughly equivalent to Envisatrsquos Level 2 products if the latter are processed with the same standards
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II42 Integration in DUACS
The Cryosat-2 data are included in the Near Real time process The chain delivers now (for global coverageMediterranean and Black Seas) along track data from Cryosat-2 (SLAs) Note that the products distributedare of Level-3 and donrsquot replace Level-2 products distributed by agenciesThe details of the processing are given in Dibarboure et al 2011 [8]Here we just give an overview the data are computed with the corrections given in section III21 Thefiltering and sub-sampling of SLAs (section III263) are detailed in [8]
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II5 Addition of Europe and Arctic products (January 2012)
Since the MyOcean V2 two new along-track products are computed in Near Real Time intended foraddressing the needs of data assmilation and validation in regional models
bull Following the TAPAS (Tailored Altimeter Product for Assimilation Systems) initiative launched bySL TAC with all the Modeling and Forecasting Centers (MFCs) the Europe regional products (PLSEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004) have been proposed (figure 3) They areavailable in Near Real Time onlyThey are studied to partly fulfil the needs of the Centers with adapted filtering and resolution Thoseparameters have been tuned in order to provide boundary conditions for the Atlantic assimilationmodels They are different from the ones used for Mediterranean and Black Seas products If you needto study the Mediterranean Sea or the Black Sea yoursquod better use the dedicated products describedabove since the processing parameters have been fitted to be adapted to the dynamics of the ocean inthose regions
Figure 3 Coverage of the Europe product for Jason-1 Jason-2 and Envisat from August 18th to September9th 2011
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bull The Arctic along-track products (PL SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005) coverlatitudes between 45 and 82 degrees (figure 4) They are available in Near Real Time only
Figure 4 Coverage of the Arctic region with Envisat from October 28th 2011 to January 3rd 2012
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III SSALTODUACS SYSTEM
III1 Introduction
This chapter presents the input data used by SSALTODUACS system and an overview of the different pro-cessing steps necessary to produce the output dataSSALTODUACS system is made of two components a Near Real Time one (NRT) and a Delayed Time(DT) oneIn NRT the systemrsquos primary objective is to provide operational applications with directly usable high qual-ity altimeter data from all missions availableIn DT it is to maintain a consistent and user-friendly altimeter database using the state-of-the-art recom-mendations from the altimetry communityFollowing figure gives an overview of DUACS system where processing sequences can be divided into 7main steps
bull acquisition
bull homogenization
bull input data quality control
bull multi-mission cross-calibration
bull product generation
bull merging
bull final quality control
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Figure 5 SSALTODUACS processing sequences
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III2 Near Real Time processing steps
III21 Input data models and corrections applied
To produce SLA in near-real time the DUACS system uses two flows based on the same instrumental mea-surements but with a different quality
bull The IGDR that are the latest high-quality altimeter data produced in near-real-time
bull The OGDR that includes real time data (OSTMJason-2 and Jason-1 OSDR) to complete IGDR Thesefast delivery products do not always benefit from precise orbit determination nor from some exter-nal model-based corrections (Dynamic Atmospheric Correction (DAC) Global Ionospheric Maps(GIM))
Integration of OGDR data and the introduction of Jason-2Jason-1 tandem increased the resilience and pre-cision of the system A better restitution of ocean variability is observed especially in high energetic areas
Altimetric product Source Availability Type of orbit
Jason-2 IGDR CNES ~24h CNES MOE GDR-Cuntil 20120730
CNES MOE GDR-Dsince 20120731
OGDR NOAAEUMETSAT ~3 to 5 h
Jason-1 IGDR CNESNASA ~48 h CNES MOE GDR-Dsince 20120507
OGDR CNESNASA ~3 to 12 h
Envisat IGDR ESACNES not deliveredsince 20120408
CNES MOE GDR-Dsince 20120121
FDGDR ESA not deliveredsince 20120408
Cryosat-2 IGDR-like ESACNES ~48 h CNES MOE GDR-D
not delivered
Table 2 SSALTODUACS Near-Real Time Input data overview
See Figure 6 Overview of the near real time system data flow management
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DUACS 2011 NRT product from IGDR1
j2 j1nj1g enn c2Productstandard ref
version C until20120730 and D after
version C version 21 CPP [2]
Orbit CNES MOE GDR-Cuntil 20120730
GDR-D after
CNES MOE GDR-C forj1n and CNES MOE
GDR-D for j1g
CNES MOE GDR-Dfrom 20120121 to
20120408
CNES MOE GDR-D
Ionopheric bi-frequency altimeter range measurements GIM model for cgt64 (Iijima et al1998[24])Dry tropo Model computed from ECMWF Gaussian grids (new S1 and S2 atm tides applied)Wet tropo-sphere
AMR radiometer(enhancement in coastal
regions since20120730)
JMR radiometer MWR radiometer andcorrected from side
lobes
Model computed fromECMWF Gaussian
grids
DAC MOG2D High Resolution forced with ECMWF pressure and wind fields (S1 and S2 wereexcluded) (Carrere and Lyard 2003[3])+ inverse barometer Filtering temporal window is
un-centered (no data in the future)Ocean tide GOT4v8 (S1 and S2 are included) and TPX 072 [16] for Arctic productsPole tide [Wahr 1985 [53]]Solid earthtide
Elastic response to tidal potential [Cartwright and Tayler 1971[5]] [Cartwright andEdden 1973[6]]
Loading tide GOT4v8 (S1 and S2 are included)Sea statebias
Non parametric SSB[Labroue 2004[27]](with cycles J1 1 to 11
using GDR-B standardsuntil 20120730 andderived from Jason-2
after)
Non parametric SSB[Labroue 2004[27]](with cycles 1 to 21
using GDR-Bstandards)
Non parametric SSB[Labroue 2004[27]](with cycles 41 to 60
using GDR-Bstandards)
Same as Jason-2 SSB
Orbit error Global multi-mission crossover minimization (Le Traon and Ogor1998[32])
Long wave-lengh errors
Optimal Interpolation [Le Traon et al 1998[31]]
Intercalibration Reference from cycle20
Mean pro-file (seeIII261)
Computed with cycles11-353 TP data andwith cycles 11-250J1 data referenced[19931999]
TPNJ1N computedwith cycles 369-479TPN data refer-enced [19931999]J1G No MP can beused instead theMSS_CNES_CLS11[39] is used
No Mean Profilecan be used forEnvisat on its neworbit Instead theMSS_CNES_CLS11[39] is used
No Mean Profilecan be used forCryosat-2 Instead theMSS_CNES_CLS11[39] is used
(1) A flag included in the along-track files indicates the source of the production (OGDRFDGDR orIGDR) If flag=0 the processed data comes from OGDRsFDGDRs if flag=1 the processed data comesfrom IGDRs
Table 3 Corrections and models applied in SSALTODUACS NRT products produced from IGDRs
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DUACS 2011 NRT product from OGDR or FDGDR2
j2 j1nj1g ennProduct stan-dard ref
version C until 20120730and D after
version C version 21
Orbit Navigator Extrapolated CNES MOEGDR-D since 20120121
Ionopheric From-dual frequency altimeter range measurements From GIM model fromcycle 65 (Iijima et al1998 [24])
Dry troposphere Model computed from ECMWF Gaussian grids (new S1 and S2 atmospherictides are applied)
Wet tropo-sphere
AMR radiometer(enhancement in coastal
regions since 20120730)
JMR radiometer MWR radiometer andcorrected from side lobes
DAC Inverse Barometer forecastedOcean tide GOT4v8 (S1 and S2 are included) and TPX 072 [16] for Arctic productsPole tide [Wahr 1985 [53]]Solid earth tide Elastic response to tidal potential [Cartwright and Tayler 1971[5]]
[Cartwright and Edden 1973[6]]Loading tide GOT4v8 (S1 and S2 are included)Sea state bias Non parametric SSB
[Labroue 2004[27]] (withcycles J1 1 to 11 usingGDR-B standards until20120730 and derivedfrom Jason-2 after)
Non parametric SSB[Labroue 2004[27]](with cycles 1 to 21 usingGDR-B standards)
Non parametric SSB[Labroue 2004[27]](with cycles 41 to 60using GDR-B standards)
Orbit error Specific filtering of long-wavelength signal3
Long wave-lengh errors
Optimal Interpolation [Le Traon et al 1998[31]]
Intercalibration Reference from cycle 20Mean profile(see III261)
Computed with cycles 11-353 TP data and with cy-cles 11-250 J1 data refer-enced [19931999]
TPNJ1N computedwith cycles 369-479TPN data referenced[19931999] J1G NoMP can be used insteadthe MSS_CNES_CLS11[39] is used
No Mean Profile can beused for Envisat on itsnew orbit Instead theMSS_CNES_CLS11 [39]is used
(2) A flag included in the along-track files indicates the source of the production (OGDRFDGDR orIGDR) If flag=0 the processed data comes from OGDRsFDGDRs if flag=1 the processed data comesfrom IGDRs(3) Specific data processing was applied on long wave-length signal (sectIII23 of the user manual)
Table 4 Corrections and models applied in SSALTODUACS NRT products produced from OG-DRsFDGDRs
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III22 Acquisition
The acquisition process is twofold
bull straightforward retrieval and reformatting of altimeter data and dynamic auxiliary data (pressure andwet troposphere correction grids from ECMWF are provided by Meteo France TEC grids from JPLNRT MOG2D corrections) from external repositories
bull synchronisation process
To be homogenized properly altimeter data sets require various auxiliary data The acquisition softwaredetects downloads and processes incoming data as soon as they are available on remote sites (externaldatabase FTP site) Data are split into passes if necessary If data flows are missing or late the synchroni-sation engine put unusable data in waiting queues and automatically unfreezes them upon reception of themissing auxiliary data This processing step delivers raw data that is to say data that have been dividedinto cycles and passes and ordered chronologicallyFrom SSALTODUACS V80 the acquisition step uses two different data flows in near-real time the OGDRflow (within a few hours) and the IGDR flow (within a few days)For each OGDR input the system checks that no equivalent IGDR entry is available in the data base beforeacquisition for each IGDR input the system checks and delete the equivalent OGDR entry in the data baseThese operations aim to avoid duplicates in SSALTODUACS system
Figure 6 Overview of the near real time system data flow management
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III23 Homogenization
The Homogenization process consists in applying the most recent corrections models and references rec-ommended for altimeter products Each mission is processed separately as its needs depend on the baseinput data The list of corrections and models currently applied is provided in tables 3 and 4 for NRT dataThe system includes SLA filtering to process OGDR data DUACS extract from these data sets the shortscales (space and time) which are useful to better describe the ocean variability in real time and merge thisinformation with a fair description of large scale signals provided by the multi-satellite observation in nearreal time (read IGDR-based DUACS data) Finally an hybrid SLA is computed
Figure 7 Merging pertinent information from IGDR and OGDR processing
III24 Input data quality control
The Input Data Quality Control is a critical process applied to guarantee that DUACS uses only the mostaccurate altimeter data Thanks to the high quality of current missions this process rejects a small percent-age of altimeter measurements but these erroneous data could be the cause of a significant quality lossThe quality control relies on standard raw data editing with quality flags or parameter thresholds but alsoon complex data editing algorithms based on the detection of erroneous artefacts mono and multi-missioncrossover validation and macroscopic statistics to edit out large data flows that do not meet the systemrsquosrequirements
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III25 Multi-mission cross-calibration
The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistentand accurate information It removes any residual orbit error (OE Le Traon and Ogor 1998[32]) or longwavelength error (LWE Le Traon et al 1998[31]) as well as large scale biases and discrepancies betweenvarious data flows
This process is based on two very different algorithms a global multi-mission crossover minimization fororbit error reduction (OER) and Optimal Interpolation (OI) for LWE
Multi-satellite crossover determination is performed on a daily basis All altimeter fields (measurementcorrections and other fields such as bathymetry MSS) are interpolated at crossover locations and datesCrossovers are then appended to the existing crossover database as more altimeter data become availableThis crossover data set is the input of the Orbit Error Reduction (OER) method Using the precision of thereference mission orbit a very accurate orbit error can be estimated This processing step does not concernOGDR dataLWE is mostly due to residual tidal or inverse barometer errors and high frequency ocean signals The OIused for LWE reduction uses precise parameters derived from
bull accurate statistical description of sea level variability
bull localized correlation scales
bull mission-specific noise and precise assumptions on the long wavelength errors to be removed (from arecent analysis of one year of data from each mission)
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III26 Product generation
The product generation process is composed of four steps computation of raw SLA cross-validationfilteringampsub-sampling and generation of by-products
III261 Computation of raw SLA
Since the geoid is not well known yet the SSH cannot be used directly the SSH anomalies are used insteadThey are computed from the difference of the instantaneous SSH - a temporal reference This temporalreference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeattrack analysis cannot be used The errors affecting the SLAs MPs and MSS have different magnitudes andwavelengths The computation of the SLAs and their errors associated are detailed in Dibarboure et al 2010[9]
Use of a Mean ProfileIn the repeat track analysis (when the satellites flies over a repetitive orbit) measurements are re-sampledalong a theoretical ground track (or mean track) associated to each mission Then a Mean Profile (MP) issubtracted from the re-sampled data to obtain SLA The MP is a time average of similarly re-sampled dataover a long period
bull The Mean Profile used for Jason-2 is computed with 10 years of TP (cycles 11 to 353) and 6 years ofJason-1 (cycles 11 to 250)
bull The Mean Profile used from Jason-1 cycle 262 to 374 (where satellites are on interleaved ground-tracks) is computed with 3 years of TP (cycles 369 to 479)
bull No Mean Profile can be used for Envisat on its new orbit (enn) Jason-1 on its geodetic orbit (j1g) norfor Cryosat-2 mission (c2) because there is no repetitive track The MSS must be used instead (seebelow)
Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible
bull Indeed as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide precise cross-track projection andor interpolation schemes are required to avoid errors
bull The mesoscale variability error (which is lt35 cm for MP between 3 to 5 years and lt1cm for WLof 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a prioriknowledge from Sea Level maps derived from previous iterations or from other missions
bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
Page 28
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for Envisat since november 2010 and for Cryosat-2 mission (c2)because the satellite is not in a repetitive orbit phase The alternative is to use the MSS instead The griddedMSS is derived from along track MPs and data from geodetic phases Thus any error on the MP is alsocontained in the MSS There are essentially 4 types of additional errors on gridded MSS which are hard toquantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
Note that for the Arctic regional products the DTU10 MSS [1] is taken into account instead of the CLS01MSS Indeed the accuracy of DTU10 compared to CLS01 is further demonstrated by the significant sealevel anomaly variance reduction found over the whole Arctic Ocean as shown in Prandi et al [42]
III262 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III263 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
Page 29
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III27 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III271 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
Page 30
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III272 Performance indicators
To appreciate the quality situation of the DUACS system new performance indicators are computed dailyThey aim at evaluate the status of the main processing steps of the system the input data availability theinput data coverage the input data quality and the output product quality These indicators are computed foreach and every currently working satellite and combined to obtain the overall status
Figure 8 Example with the key performance indicator on 20090627
See the description the latest and previous indicators on Aviso websitehttpwwwavisooceanobscomindexphpid=1516
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III3 Delayed Time processing steps
III31 Input data models and corrections applied
Delayed Time MyOcean products are generated
bull from Aviso GDR products for TP Jason-1 Jason-2 and Envisat (GDR-A cycles 1 to 22 GDR-Bcycles 23 to 85 GDR-C from cycle 86)
bull from NOAA GDR for GFO and from CERSAT (IFREMER) OPR for ERS-1 and ERS-2 (phases C(1st 35-day repeat orbit period) phase E and F (geodetic phases) phase G for ERS-1 (last 35-dayrepeat orbit period tandem phase with ERS-2 phase A for ERS-2 (1st 35-day repeat orbit periodtandem phase with ERS-1))
All GDR products are computed with a Precise Orbit Ephemeris (POE) and are delivered within 2 to 3months depending on the mission For several missions an updated orbit is used
bull For ERS-1amp-2 the orbit used is DGME-04 provided by Delft Institute (httpwwwdeostudelftnl)until June 2003
bull For TopexPoseidon the orbit used is GSFC (std0809) for the whole mission
bull For Envisat CNES POE of GDR-C standard is used for the whole mission
bull For the whole GFO mission the orbit used is GSFC (std0809) and when not available NASA POE isused
Altimetric product Source Availability Type of orbit
TopexPoseidon GDR NASACNES - GSFC POE
Jason-1 GDR (GDR-C) CNESNASA ~40 days CNES POE
Jason-2 GDR (GDR-C) CNESNASA ~60 days CNES POE
GFO GDR NOAA - GSFCNASA POE
ERS-1amp2 IFREMERESA - DGME-04
Envisat (GDR-A GDR-B andGDR-C from cycle 86)
ESA ~2 months CNES POE
Table 5 SSALTODUACS Delayed Time Input data overview
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
DU
AC
S20
11D
Tpr
oduc
t(gtV
30
0)j2
j1j1
ntp
tpn
e1e2
ene
nng2
Prod
uct
stan
dard
ref
GD
R-C
OPR
GD
R-A
(Cyc
les
1to
22)
GD
R-B
(cyc
les
23-8
5)
GD
R(N
OA
A)
Orb
itC
nes
POE
GSF
C(I
TR
F20
05G
RA
CE
last
stan
dard
s)
DG
ME
-04
(Sch
arro
oan
dV
isse
r19
98[4
8]C
NE
SPO
E(G
DR
-1st
anda
rds
forc
ycle
s9
to22
GD
R-C
stan
dard
sfr
omcy
cle
23)
GSF
C(I
TR
F20
05
GR
AC
Ela
stst
anda
rds
Iono
pher
icD
ual f
requ
ency
altim
eter
rang
em
easu
rem
ents
Dua
l fre
quen
cyal
timet
erra
nge
mea
sure
men
ts(T
opex
)D
OR
IS(P
OSE
IDO
N)
Ben
t mod
elB
ent m
odel
(cyc
les
1-36
)G
IMm
odem
from
cycl
e37
((Ii
jima
etal
19
98[2
4])
Dua
l-fr
eque
ncy
altim
eter
rang
em
easu
rem
ent(
cycl
e9-
64)a
ndG
IMm
odel
gtcyc
le65
(Iiji
ma
etal
19
99[2
4])c
orre
cted
from
8m
mbi
as
From
GIM
mod
el(I
ijim
aet
al1
998
[24]
)
Dry
trop
o-sp
here
Mod
elco
mpu
ted
from
EC
MW
FG
auss
ian
grid
s(n
ewS1
and
S2at
mos
pher
ictid
esar
eap
plie
d)
Mod
elco
mpu
ted
from
EC
MW
Fre
ctan
gula
rgri
ds(n
ewS1
and
S2at
mos
pher
ictid
esar
ein
clud
ed)
Wet
trop
o-sp
here
JMR
AM
Rra
diom
eter
furt
hert
han
50km
from
the
coas
tsF
rom
EC
MW
Fm
odel
ford
ista
nces
betw
een
10an
d50
km
TM
Rra
diom
eter
(Sch
aroo
etal
20
04[4
9])
MW
RC
orre
ctio
nof
the
drif
ton
the
236
GH
zbr
ight
ness
tem
pera
ture
(Sch
arro
oet
al
2004
[49]
)Neu
ral
Net
wor
kal
gori
thm
(Tra
nan
dO
blig
is
2003
[50]
MW
Rra
diom
eter
furt
hert
han
50km
from
the
coas
tsan
dco
rrec
ted
from
side
lobe
s(f
rom
cycl
e41
)E
CM
WF
mod
elfo
rdis
tanc
esbe
twee
n10
and
50km
GFO
radi
omet
er
DA
CM
OG
2DH
igh
Res
olut
ion
forc
edw
ithE
CM
WF
pres
sure
and
win
gfie
lds
(S1
and
S2w
ere
excl
uded
)+in
vers
eba
rom
eter
com
pute
dfr
omre
ctan
gula
rgri
ds
Tabl
e6
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(1
2)
Page 33
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
j2j1
j1n
tptp
ne1
e2en
enn
g2O
cean
tide
GO
T4v
7(S
1an
dS2
are
incl
uded
)Po
letid
e[W
ahr
1985
[53]
]So
lidea
rth
tide
Ela
stic
resp
onse
totid
alpo
tent
ial[
Car
twri
ghta
ndTa
yler
197
1[5]
][C
artw
righ
tand
Edd
en1
973[
6]]
Loa
ding
tide
GO
T4v
7(S
1pa
ram
eter
isin
clud
ed)
Sea
stat
ebi
asN
onpa
ram
etri
cSS
B[G
aspa
reta
l20
02[2
0]]
Non
para
met
ric
SSB
[NT
ran
and
al2
010[
51]]
BM
3[G
aspa
ran
dO
gor
1994
[17]
]
Non
para
met
ric
SSB
[Mer
tzet
al
2005
[38]
]
Non
para
met
ric
SSB
[Gas
pare
tal
2002
]w
ithG
DR
-Bst
anda
rds
forc
ycle
s9
to85
and
with
GD
R-C
stan
dard
sfr
omcy
cle
86
Non
para
met
ric
SSB
[NT
ran
etal
20
10[5
1]]
Orb
iter
ror
Glo
bal m
ulti-
mis
sion
cros
sove
rmin
imiz
atio
n(L
eTr
aon
and
Ogo
r19
98[3
2])
Lon
gw
ave-
leng
her
rors
Opt
imal
Inte
rpol
atio
n(L
eTr
aon
etal
19
98[3
1])
Inte
rcal
ibra
tion
Ref
eren
cefr
omcy
cle
11R
efer
ence
from
cycl
e1
to35
4C
orre
ctio
nof
regi
onal
bias
J2J
1de
duce
dfr
omin
terc
alib
ratio
nph
ase
(cyc
le11
J2)
Cor
rect
ion
ofgl
obal
biai
sJ1
TP
deacutedu
ced
from
inte
rcal
ibra
tion
phas
e(c
ycle
s11
J1)
Mea
npr
o-fil
e(s
eeII
I36
1)
Com
pute
dw
ithcy
cles
11-3
53T
Pda
taan
dw
ithcy
cles
11-2
50J1
data
ref
eren
ced
[199
319
99]
TP
J1 c
ompu
ted
with
cycl
es11
-353
TP
data
and
with
cycl
es11
-250
J1da
tar
efer
ence
d[1
993
1999
]T
PNJ
1Nc
ompu
ted
with
cycl
es36
9-47
9T
PNda
tar
efer
ence
d[1
993
1999
]
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
ref
eren
ced
[199
319
99]
EN
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
re
fere
nced
[199
319
99]
EN
Nu
seof
MSS
_CN
ES_
CL
S11
[39]
Com
pute
dw
ithcy
cles
37-1
87G
2da
ta
refe
renc
ed[1
993
1999
]
Peri
odof
use
from
cycl
e9
from
cycl
e9
cycl
es1
to48
1cy
cles
15to
43In
clud
ing
E-F
geod
etic
phas
es
cycl
es1
to83
from
cycl
e9
cycl
es37
to22
2
Tabl
e7
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(2
2)
Page 34
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III32 Acquisition
The acqusition process in Delayed time is much simpler than in Near Real time it consists in a synchronisa-tion process of all the auxiliary data required to homogenize propely the altimeter data sets The acquisitionstep uses the GDRs or the OPRs provided by the agencies
III33 Homogenization
The Homogenization process consists in applying the most recent corrections models and references rec-ommended for altimeter products Each mission is processed separately as its needs depend on the baseinput data The list of corrections and models currently applied is provided in tables 6 and 7 for DT data
III34 Input data quality control
The Input Data Quality Control is a critical process applied to guarantee that DUACS uses only the mostaccurate altimeter data Thanks to the high quality of current missions this process rejects a small percent-age of altimeter measurements but these erroneous data could be the cause of a significant quality lossThe quality control relies on standard raw data editing with quality flags or parameter thresholds but alsoon complex data editing algorithms based on the detection of erroneous artefacts mono and multi-missioncrossover validation and macroscopic statistics to edit out large data flows that do not meet the systemrsquosrequirements
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III35 Multi-mission cross-calibration
The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistentand accurate information It removes any residual orbit error (OE Le Traon and Ogor 1998[32]) or longwavelength error (LWE Le Traon et al 1998[31]) as well as large scale biases and discrepancies betweenvarious data flows
This process is based on two very different algorithms a global multi-mission crossover minimization fororbit error reduction (OER) and Optimal Interpolation (OI) for LWE
Multi-satellite crossover determination is performed on a daily basis All altimeter fields (measurementcorrections and other fields such as bathymetry MSS) are interpolated at crossover locations and datesCrossovers are then appended to the existing crossover database as more altimeter data become availableThis crossover data set is the input of the Orbit Error Reduction (OER) method Using the precision of thereference mission orbit a very accurate orbit error can be estimated LWE is mostly due to residual tidalor inverse barometer errors and high frequency ocean signals The OI used for LWE reduction uses preciseparameters derived from
bull accurate statistical description of sea level variability
bull localized correlation scales
bull mission-specific noise and precise assumptions on the long wavelength errors to be removed (from arecent analysis of one year of data from each mission)
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III36 Product generation
The product generation process is composed of four steps computation of raw SLA cross-validationfilteringampsub-sampling and generation of by-products
III361 Computation of raw SLA
Since the geoid is not well known yet the SSH cannot be used directly the SSH anomalies are used insteadThey are computed from the difference of the instantaneous SSH - a temporal reference This temporalreference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeattrack analysis cannot be used The errors affecting the SLAs MPs and MSS have different magnitudes andwavelengths The computation of the SLAs and their errors associated are detailed in Dibarboure et al 2010[9]
Use of a Mean ProfileIn the repeat track analysis (when the satellites flies over a repetitive orbit) measurements are re-sampledalong a theoretical ground track (or mean track) associated to each mission Then a Mean Profile (MP) issubtracted from the re-sampled data to obtain SLA The MP is a time average of similarly re-sampled dataover a long period
bull The Mean Profile used for TP (cycles 1 to 364) Jason-1 (cycles 1 to 259) and Jason-2 is computedwith 10 years of TP (cycles 11 to 353) and 6 years of Jason-1 (cycles 11 to 250)
bull The Mean Profile used for TP (cycles 368 to 481) and from Jason-1 cycle 262 to 374 (where satellitesare on interleaved ground-tracks) is computed with 3 years of TP (cycles 369 to 479)
bull The Mean Profile used for ERS-1 in its 35 days repetitive orbit mission ERS-2 and Envisat (only forthe first orbit before November 2010) is computed with 8 years of ERS-2 (cycles 1 to 85) and 6 yearsof Envisat (cycles 10 to 72)
bull No Mean Profile can be used for Envisat on its new orbit (enn) Jason-1 on its geodetic orbit (j1g)because there is no repetitive track The MSS must be used instead (see below)
bull The Mean Profile used for GFO is computed with 7 years of GFO cycles 37 to 187
Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible
bull Indeed as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide precise cross-track projection andor interpolation schemes are required to avoid errors
bull The mesoscale variability error (which is lt35 cm for MP between 3 to 5 years and lt1cm for WLof 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a prioriknowledge from Sea Level maps derived from previous iterations or from other missions
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bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for ERS-1 for its 168 days geodetic mission (phases E-F from April1994 to March 1995) or for Envisat since november 2010 because the satellite is not in a repetitive orbitphase The alternative is to use the MSS instead The gridded MSS is derived from along track MPs anddata from geodetic phases Thus any error on the MP is also contained in the MSS There are essentially 4types of additional errors on gridded MSS which are hard to quantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
III362 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III363 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
Page 38
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III37 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III371 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
Page 39
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
IV MYOCEAN PRODUCTS
IV1 Near Real Time Products
The purpose of the NRT DUACS component is the acquisition of altimeter data from various altimeter mis-sions in near-real time (ie within a few days at most) the validation and correction of these altimeter datasets (ie edition and selection update of corrections and homogenization orbit error reduction) in order toproduce each day along-track productsProducts are as follows
Along-track products global and regional (Mediterranean and Black Seas Arctic Ocean and Europeareas)
bull Sea Level Anomaly (NRT-SLA) for each mission with NRT-SLA ephemeris
IV11 Delay of the products
The availability of the products in near real time is three to twelve hours after the measurement for along-track products Those products are delivered every day
IV12 Temporal availibility
The following table presents the available products by mission and by data periodNear real time products
NRT Jason-2 Jason-1 and Jason-1geodetic
Envisat new Cryosat-2
Temporal Time availability ymlowast
ongoingymlowast-20120303 for
repeat track and20120507-ongoing for
geodetic track
ymlowast
2012040820120101
ongoing
NRT-SLA X X X X
lowastym the temporal coverage for NRT products is fluctuating and depends on updates of Delayed Time prod-ucts When DT products are updated (3 to 4 times per year) the oldest NRT products are replaced by thebetter quality DT products so that the 2 series are overlapping on few weeks or few months
IV2 Delayed Time Products
The Delayed Time component of SSALTODUACS system is responsible for the production of processedJason-1 Jason-2 TP Envisat GFO ERS12 and even Geosat data in order to provide a homogeneousinter-calibrated and highly accurate long time series of SLA DT products are more precise than NRT products Two reasons explain this quality difference The firstone is the better intrinsic quality of the POE orbit used in the GDR processing The second reason is that
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in the DT DUACS processing the products can be computed optimally with a centred computation timewindow for OER LWE On the contrary in NRT case future data are not available so the computationtime window is not centred and therefore not optimalAs for NRT products improved altimeter corrections and processing algorithms are used ocean tide modelto correct altimeter data improved methods for orbit error reduction and mapping
Along-Track products global and regional (Mediterranean and Black Seas)
bull Sea Level Anomaly (DT-SLA) for each mission
IV21 Delay of the products
Weekly products are delivered The availability of the products in delayed time is at the best two monthsafter the date of the measurement The product generation needs all the GDR data of all the missions to takeinto account the best corrections as possible The time delay can be longer in the case of a missing mission
IV22 Temporal availibility
The following table presents the available products by mission and by data periodDelayed time SSALTODUACS products
Upd Jason-2 Jason-1new6
Jason-1 GFO Envisatnew6
Envisat ERS-16
ERS-2Topexnew6
Topex
TemporalTimeavailabil-ity
200810ymlowast
200902ymlowast
200204200810
200001200809
201010ymlowast
200210201010
199210200304
200209200510
199209200204
DT-SLA X X X X X X X X X
lowast ym those dates are updated regularly (3 to 4 times per year) and are avalaible when you download thedata at httpwwwmyoceaneuweb24-cataloguephp6 Jason-1 new orbit starting 200809 Envisat new orbit starting 201010 TP new orbit starting 200209 ERS-1The geodetic phases (E-F) are included There are no ERS-1 data between December 23 1993 and April 10 1994(ERS-1 phase D - 2nd ice phase) Note that during that time products are based only on TopexPoseidon data
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V DESCRIPTION OF THE PRODUCT SPECIFICATION
V1 General information
Product Specification SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001
Geographical coverage global
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 20-50km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001 Product Specification
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Product Specification SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002
Geographical coverage 55˚W-35˚E 30˚N-46˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002 Product Specification
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Product Specification SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003
Geographical coverage 27˚E-42˚E 40˚N-47˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003 Product Specification
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Product Specification SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004
Geographical coverage 25˚W-42˚E 21˚N-66˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004 Product Specification
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Product Specification SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005
Geographical coverage 0˚W-360˚E 50˚N-82˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005 Product Specification
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VI NOMENCLATURE OF FILES
VI1 Nomenclature of files downloaded through the MyOcean Web PortalDirectgetfile Service
VI11 Nomenclature of the product line
The description of the syntax for the SL TAC SLA products line is given by
SEALEVEL_ltREGIONgt_SLA_L3_ltDELAYgt_OBSERVATIONS_008_ltZONEgt_ltLETTERgtwhere
REGION GLO global geographic coverage product
BS Black Sea products
MED Mediterranean products
ARC Arctic products (for NRT products)
EUROPE Europe products (for NRT products)
DELAY NRT near real time products
RAN delayed time or reanalysis products
ZONE 001 number on 3 digits
002
003
004
LETTER a letter on 1 digit
b
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VI12 Nomenclature of the datasets
The nomenclature used is
dataset-duacs-ltdelaygt-ltzonegt-ltmissiongt-lttype of slagt-l3where the fileds in ltgt are described below
delay nrt near-real time productsran delayed time products
zone global global geographic coverage productmedsea Mediterranean productsblacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1 (only for ran)e2 ERS-2 (only for ran)tp TOPEXPoseidon (only for ran)tpn TOPEXPoseidon on its new orbit (only for
ran)g2 GFO (only for ran)j1 Jason-1 (only for ran)j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisat (only for ran)enn Envisat on its new orbitc2 Cryosat-2 (only for nrt)
type of sla sla filtered slasla_unfiltered non filtered sla (only for ran products)
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VI13 Nomenclature of the NetCdf files
The nomenclature used is
ltdelaygt_ltzonegt_ltmissiongt_sla_ltvariablegt_ltdatebegingt_ltdateendgt_ltdateprodgtnc where the fileds in ltgt are de-scribed below
delay nrt near-real time productsdt delayed time products
zone global global geographic coverage productmed Mediterranean products (for dt)mfstep Mediterranean products (for nrt)blacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1e2 ERS-2tp TOPEXPoseidontpn TOPEXPoseidon on its new orbitg2 GFOj1 Jason-1j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisatenn Envisat on its new orbitc2 Cryosat-2
variable vfec filtered and sub-sampled slavxxc non filtered and non sub-sampled sla (only
for dt)datebegin YYYYMMDD() beginning date of the datasetdateend YYYYMMDD() end date of the datasetdateprod YYYYMMDD production date of the dataset
() For dt data as the dates in the file names are rounded the user wanting data for date T has to read the filescontaining dates T+1 and T-1 in their name and check inside the files if there are some data for date T
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VII DATA FORMAT
This chapter presents the data storage format used for MyOcean products
VII1 NetCdf
The products are stored using the NetCDF format NetCDF (network Common Data Form) is an interface for array-oriented data access and a library that provides an implementation of the interface The netCDF library also definesa machine-independent format for representing scientific data Together the interface library and format support thecreation access and sharing of scientific data The netCDF software was developed at the Unidata Program Center inBoulder Colorado The netCDF libraries define a machine-independent format for representing scientific data Pleasesee Unidata NetCDF pages for more information and to retreive NetCDF software package onhttpwwwunidataucaredupackagesnetcdfindexhtml
NetCDF data is
bull Self-Describing A netCDF file includes information about the data it contains
bull Architecture-independent A netCDF file is represented in a form that can be accessed by computers with dif-ferent ways of storing integers characters and floating-point numbers
bull Direct-access A small subset of a large dataset may be accessed efficiently without first reading through allthe preceding data
bull Appendable Data can be appended to a netCDF dataset along one dimension without copying the dataset orredefining its structure The structure of a netCDF dataset can be changed though this sometimes causes thedataset to be copied
bull Sharable One writer and multiple readers may simultaneously access the same netCDF file
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VII2 Structure and semantic of NetCDF along-track files
The NetCDF Sea Level TAC files are based on the attribute data tags defined by the Cooperative OceanAtmosphereResearch Data Service (COARDS) and Climate and Forecast (CF) metadata conventions The CF convention gener-alises and extends the COARDS convention but relaxes the COARDS constraints on dimension and order and specifiesmethods for reducing the size of datasetsA wide range of software are available to write or read NetCDFCF files API are made available by UNIDATA(httpwwwunidataucaredusoftwarenetcdf)
bull CC++Fortran
bull Java
bull MATLAB Objective-C Perl Python R Ruby TclTk
In addition to these conventions the files are using a common structure and semantic
bull 1 dimension is defined
ndash time it is used to check NetCDF variables depending on time
bull 8 variables are defined
ndash short SLA contains the Sea Level Anomaly values for each time given
ndash int longitude contains the longitude for each measurement
ndash short track contains the track number for each measurement
ndash double time contains the time in days since 1950-01-01 000000 UTC for each measurement
ndash short mean_profile_point_index index of the corrsponding point in the track of the mean profile
ndash byte flag flag=0 the processed data comes from OGDR if flag=1 the processed data comes from theIGDR
ndash int latitude contains the latitude for each measurement
ndash short cycle contains the cycle number for each measurement
bull global attributes
ndash the global attributes gives information about the creation of the file
Example of a NetCDF sla file
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netcdf nrt_global_j1_sla_vfec_20101230_20101230_20101230 dimensions
time = 10385 variables
short SLA(time) SLAcoordinates = longitude latitude SLAlong_name = Sea Level Anomaly SLA_FillValue = 32767s SLAadd_offset = 0 SLAscale_factor = 0001 SLAunits = m SLAstandard_name = sea_surface_height_above_sea_level
int longitude(time) longitudelong_name = Longitude of measurement longitude_FillValue = 2147483647 longitudeadd_offset = 0 longitudestandard_name = longitude longitudescale_factor = 1e-06 longitudeunits = degrees_east
short track(time) tracklong_name = Track in cycle the measurement belongs to track_FillValue = 32767s trackunits = 1 trackcoordinates = longitude latitude
double time(time) timelong_name = Time of measurement time_FillValue = 184467440737096e+19 timeaxis = T timestandard_name = time timeunits = days since 1950-01-01 000000 UTC
int latitude(time) latitudelong_name = Latitude of measurement latitude_FillValue = 2147483647 latitudeadd_offset = 0 latitudestandard_name = latitude latitudescale_factor = 1e-06 latitudeunits = degrees_north
short flag(time) flagcoordinates = longitude latitude flag_FillValue = 3267s flaglong_name = data origin flagflag_values = 1s 0s flagflag_meanings = igdr_like non_igdr_like flagcomment = The origin of the data is determined by the types of geophysical datarecords (GDR) used in computation of the SLA 1 for the Interim GDR (IGDR) and0 for Operational GDR (OGDR)
short cycle(time) cyclelong_name = Cycle the measurement belongs to cycle_FillValue = 32767s cycleunits = 1 cyclecoordinates = longitude latitude
global attributeshistory = 22-Feb-2011 155243 CET File created by the SSLATODUACS system version 1001 comment = Produce from ENVISAT Extension Phase satellite altimetry data institution = CLSCNES
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references = httpwwwavisooceanobscomfileadmindocumentsdatatoolshdbk_duacspdf source = satellite altimetry title = along track Sea Level Anomaly Conventions = CF-14
dataSLA =
7 7 11 10 -2 -22 -39 -41 -30 -13 -3 -5 -16 -26 -32 -35-35 -35 -37 -35 -31 -29 -31 -35 -32 -21 -10 -10 -19 -20 -1-69 -57 -49 -45 -39 -30 -28 -31 -27 -13 -2 -5 -15 -3 1112 3 -7 -10 -14 -15 -22 -31 -37 -32 -17 -10
longitude =74743328 74868400 74993968 75120040 75246616 7537372875501368 75629568 75758320 75887656 76017568 76148080 7627920876388952 76477056 76565456 76654144 76743128 76832400 76921984329429568 329535424 329641792 329748672 329856096 329964032330072512 330181536 330291072 330401184
track =92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 9292 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92113 113 113 113 113 113 113 113 113 113 113 113 113 113113 113 113 113 113 113 113 113 113
time =222780000565705 222780001314719 222780002063733222780002812747 222780003561761 222780004310775 222780005059788222780005808802 222780006557816 22278000730683 222780008055844222780008804858 222780009553872 22278001017805 222780010677393222788257112198 222788257486705 222788257861212 222788258235719222788258610226 222788258984733 222788259359239 222788259733746222788260108253 22278826048276
mean_profile_point_index =1872 1878 1884 1890 1896 1902 1908 19141920 1926 1932 1938 1944 1949 1953 1957 1961 1965 1969 19732306 2309 2312 2315 2318 2321 2327 2330 2333 2336 2339 23422345 2348 2351 2354 2357 2360 2363 2366
flag =0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
latitude =-16225506 -16539731 -16853833 -17167810 -17481660 -17795380-18108966 -18422418 -18735729 -19048899 -19361924 -19674801-19987527 -20248015 -20456329 -20664569 -20872739 -2108083739481297 39628277 39775133 39921866 40068472 40214953 4036130840507533 40653629 40799592 40945423 41091120 41236684 41382111
cycle =331 331 331 331 331 331 331 331 331 331 331 331 331
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331 331 331 331 331 331 331 331 331 331 331 331 331 331331 331 331 331 331 331 331 331 331 331 331 331
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VIII HOW TO DOWNLOAD A PRODUCT
VIII1 Download a product through the MyOcean Web Portal DirectgetfileService
You first need to register Please find below the registration stepshttpwwwmyoceaneuweb34-products-and-services-faqphp1Once registered the MyOcean FAQ httpwwwmyoceaneuweb34-products-and-services-faqwill guide you on How to download a product through the MyOcean Web Portal Directgetfile Service
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IX NEWS AND UPDATES
IX1 [Duacs] Operational news
To be kept informed on events occurring on the satellites and on the eventual interruption of the services of the DUACSprocessing system see the [Duacs] operational news on the Aviso websitehttpwwwavisooceanobscomendataoperational-newsindexhtml
IX2 Updates
To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtmlSince 2010 a complete reprocessing of all altimetry data (cumulated total of about 55 years of data) is available Themain changes introduced in the Duacs DT v300 reprocessed data set in SSALTODUACS reprocessed DT data setare listed herehttpwwwavisooceanobscomfileadmindocumentsdataduacsduacs_DT_2010_reprocessing_impactpdf
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[16] Egbert Gary D Svetlana Y Erofeeva 2002 Efficient Inverse Modeling of Barotropic Ocean Tides JAtmos Oceanic Technol 19 183-204 doi 1011751520-0426(2002)019lt0183EIMOBOgt20CO2
[17] Gaspar P and F Ogor Estimation and analysis of the Sea State Bias of the ERS-1 altimeter Reportof task B1-B2 of IFREMER Contract n˚ 942426 016C 1994
[18] Gaspar P F Ogor and C Escoubes 1996 Nouvelles calibration et analyse du biais drsquoeacutetat de mer desaltimegravetres TOPEX et POSEIDON Technical note 96018 of CNES Contract 951523 1996
[19] Gaspar P and F Ogor Estimation and analysis of the Sea State Bias of the new ERS-1 and ERS-2altimetric data (OPR version 6) Report of task 2 of IFREMER Contract n˚ 962246 002C 1996
[20] Gaspar P S Labroue and F Ogor 2002 Improving nonparametric estimates of the sea state bias inradar altimeter measurements of seal level J Atmos Oceanic Technology 19 1690-1707
[21] Hernandez F P-Y Le Traon and R Morrow 1995 Mapping mesoscale variability of the AzoresCurrent using TOPEXPOSEIDON and ERS-1 altimetry together with hydrographic and Lagrangianmeasurements Journal of Geophysical Research 100 24995-25006
[22] Hernandez F and P Schaeffer 2000 Altimetric Mean Sea Surfaces and Gravity Anomaly maps inter-comparisons AVI-NT-011-5242-CLS 48 pp CLS Ramonville St Agne
[23] Hernandez F M-H Calvez J Dorandeu Y Faugegravere F Mertz and P Schaeffer 2000 Sur-face Moyenne Oceacuteanique Support scientifique agrave la mission altimeacutetrique Jason-1 et agrave une mis-sion micro-satellite altimeacutetrique Contrat SSALTO 2945 - Lot 2 - A1 Rapport drsquoavancementCLSDOSNT00313 40 pp CLS Ramonville St Agne
[24] Iijima BA IL Harris CM Ho UJ Lindqwiste AJ Mannucci X Pi MJ Reyes LC SparksBD Wilson 1999 Automated daily process for global ionospheric total electron content maps andsatellite ocean altimeter ionospheric calibration based on Global Positioning System data J AtmosSolar-Terrestrial Physics 61 16 1205-1218
[25] Labroue S F Boy N Picot M Urvoy M Ablain First quality assessment of the Cryosat-2 altimetricsystem over ocean J Adv Space Res 2011 doi101016jasr201111018 httpdxdoiorg101016jasr201111018
[26] Labroue S 2007 RA2 ocean and MWR measurement long term monitoring 2007 report for WP3Task 2 - SSB estimation for RA2 altimeter Contract 1729303I-OL CLS-DOS-NT-07-198 53ppCLS Ramonville St Agne
[27] Labroue S P Gaspar J Dorandeu OZ Zanifeacute F Mertz P Vincent and D Choquet 2004 Nonparametric estimates of the sea state bias for Jason-1 radar altimeter Marine Geodesy 27 453-481
[28] Lagerloef GSE GMitchum RLukas and PNiiler 1999 Tropical Pacific near-surface currentsestimated from altimeter wind and drifter data J Geophys Res 104 23313-23326
[29] Le Traon P-Y and F Hernandez 1992 Mapping the oceanic mesoscale circulation validation ofsatellite altimetry using surface drifters J Atmos Oceanic Technol 9 687-698
[30] Le Traon P-Y P Gaspar F Bouyssel and H Makhmara 1995 Using TopexPoseidon data to en-hance ERS-1 data J Atmos Oceanic Technol 12 161-170
[31] Le Traon P-Y F Nadal and N Ducet 1998 An improved mapping method of multisatellite altimeterdata J Atmos Oceanic Technol 15 522-534
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[32] Le Traon P-Y and F Ogor 1998 ERS-12 orbit improvement using TOPEXPOSEIDON the 2 cmchallenge J Geophys Res 103 8045-8057
[33] Le Traon P-Y and G Dibarboure 1999 Mesoscale mapping capabilities of multi-satellite altimetermissions J Atmos Oceanic Technol 16 1208-1223
[34] Le Traon P-Y G Dibarboure and N Ducet 2001 Use of a High-Resolution Model to Analyze theMapping Capabilities of Multiple-Altimeter Missions J Atmos Oceanic Technol 18 1277-1288
[35] Le Traon PY and G Dibarboure 2002 Velocity mapping capabilities of present and future altimetermissions the role of high frequency signals J Atmos Oceanic Technol 19 2077-2088
[36] Le Traon PY Faugegravere Y Hernandez F Dorandeu J Mertz F and M Ablain 2002 Can we mergeGEOSAT Follow-On with TOPEXPOSEIDON and ERS-2 for an improved description of the oceancirculation J Atmos Oceanic Technol 20 889-895
[37] Le Traon PY and G Dibarboure 2004 An Illustration of the Contribution of the TOPEXPoseidon-Jason-1 Tandem Mission to Mesoscale Variability Studies Marine Geodesy 27 (1-2)
[38] Mertz F F Mercier S Labroue N Tran J Dorandeu 2005 ERS-2 OPR data quality assessment Long-term monitoring - particular investigation CLSDOSNT-06001 (pdf)
[39] MSS_CNES_CLS11 was produced by CLS Space Oceanography Division and distributed by Avisowith support from Cnes (urlhttpwwwavisooceanobscom)
[40] Pascual A Y Faugegravere G Larnicol P-Y Le Traon 2006 Improved description of the oceanmesoscale variability by combining four satellite altimeters Geophys Res Lett 33
[41] Pascual A C Boone G Larnicol and P-Y Le Traon 2009 On the quality of Real-Time altimetergridded fields comparison with in-situ data Journ of Atm and Ocean Techn Vol 26(3) pp 556-569DOI 1011752008JTECHO5561
[42] Prandi P M Ablain A Cazenave N Picot 2011 A new estimation of mean sea level in the ArcticOcean from satellite altimetry Submitted to Marine Geodesy
[43] Pujol M-I et al 2009 Three-satellite quality level restored in NRT poster at OSTST meeting (pdf)
[44] Ray R 1999 A Global Ocean Tide model from TOPEXPoseidon Altimetry GOT992 NASA TechMemo NASATM-1999-209478 58 pp Goddard Space Flight Center NASA Greenbelt MD USA
[45] Rio M-H and F Hernandez 2003 A Mean Dynamic Topography computed over the worldocean from altimetry in-situ measurements and a geoid model J Geophys Res 109 C12032doi1010292003JC002226
[46] Rio M-H and F Hernandez 2003 High frequency response of wind-driven currents measured bydrifting buoys and altimetry over the world ocean J Geophys Res 108 39-1
[47] Rio M-H 2003 Combinaison de donneacutees in situ altimeacutetriques et gravimeacutetriques pour lrsquoestimationdrsquoune topographie dynamique moyenne globale Ed CLS PhD Thesis University Paul Sabatier(Toulouse III France) 260pp
[48] Scharroo R and P Visser 1998 Precise orbit determination and gravity field improvement for theERS satellites J Geophys Res 103 8113-8127
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[49] Scharroo R J Lillibridge and WHF Smith 2004 Cross-calibration and long-term monitoring ofthe Microwave Radiometers of ERS Topex GFO Jason-1 and Envisat Marine Geodesy 97
[50] Tran N and E Obligis December 2003 Validation of the use of ENVISAT neural algorithms onERS-2 CLSDOSNT03901
[51] Tran N S Labroue S Philipps E Bronner and N Picot 2010 Overview and Update of the SeaState Bias Corrections for the Jason-2 Jason-1 and TOPEX Missions Marine Geodesy accepted
[52] Vincent P Desai SDDorandeu J Ablain M Soussi B Callahan PS and BJ Haines 2003 Jason-1 Geophysical Performance Evaluation Marine Geodesy 26 167-186
[53] Wahr J W 1985 Deformation of the Earth induced by polar motionJ of Geophys Res (Solid Earth)90 9363-9368
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I INTRODUCTION
MyOcean is a European Network project aiming at monitoring analyzing and forecasting the Ocean Ituses satellite and in-situ data to describe the ocean in 3 dimensions and real time More information can befound on httpwwwmyoceaneuorgThe aim of this document is to describe the products delivered by the Sea Level TAC (Thematic AssemblyCentre) which is one of the five TAC of the MyOcean projectThe data produced in the frame of this TAC are generated by the processing system named DUACS (DataUnification and Altimeter Combination System)DUACS is part of the CNES multi-mission ground segment (SSALTO) It processes data from all altimetermissions Cryosat-2 OSTMJason-2 Jason-1 TopexPoseidon Envisat GFO ERS-1amp2 and even GeosatAt this time (May 25th 2012) DUACS is using three different altimeters in near real time Developed and operated by CLS it started as an European Commission Project (Developing Use Of Altime-try for Climate Studies) funded under the European Commission and the Midi-Pyreacuteneacutees regional councilIt has been integrated to the CNES multi-mission ground segment SSALTO in 2001 and it is maintainedupgraded and operated with funding from CNES with shared costs from EU projectsAt the beginning of 2004 DUACS was redefined as the Data Unification Altimeter Combination System
Figure 1 DUACS and AVISO a user-driven altimetry service
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The products lines described in this user manual are the followingSEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005
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The data provided to users have a global coverage (PL SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001)and regional products are also computed over specific areasMediterranean Sea (PL SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002)and Black Sea (PL SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003)Thanks to updates in 2011 and 2012 (see section II) new regional products are now availableEurope (PL SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004)and Arctic (PL SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005)
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II UPDATES IN 2011 AND 2012
This section describes the updates of the SSALTODUACS Near Real Time system that occurred during2011 and 2012 allowing to add new products (Europe and Arctic) the integration of the Cryosat-2 data inthe system the stopping delivery of Envisat data the addition of Jason-1 data on geodetic orbit (j1g)To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtml
II1 Version D of input IGDROGDR Jason-2 data for NRT processing(July 30 2012)
On July 30 2012 the version of Jason-2 IGDROGDR has changed and is now the D version Somecorrections have thus been updated as detailed in tables 3 and 4
II2 Integration of Jason-1 on its geodetic orbit (May 2012)
An anomaly occured on March 3rd 2012 on the Jason-2 mission (see httpwwwavisooceanobscomfractualitesactualitesindexhtmltx_ttnews[tt_news]=1162amptx_ttnews[backPid]=1399ampcHash=d5baeb645e) On April 23rd CNES began to command the satellite into a nadir ori-entation and after some propulsion anomalies CNES and NASA management through the Joint SteeringGroup have directed the Jason-1 Project to then begin a series of maneuvers to place Jason-1 into a neworbit as defined in table 1 After checking the current orbit carefully the operational team determined thata geodetic mission was still possible It was also decided to preserve all remaining fuel for future stationkeeping maneuvers which is mandatory in a geodetic orbit Core payloads were switched ON on May 4thand after some POSEIDON2 radar (PRF) adjustments the mission was resumed on May 7th at 151248UTCBelow are the characteristics of the new orbit which will be maintained as before within +- 1km controlbox at the Equator
Semi major axis 7702437 kmEccentricity 13 to 28 10-4Altitude equator 13240 kmOrbital period 6730s (1h52rsquo10rdquo)Inclination 66042˚Cycle 406 daysSub cycles 39 - 109 - 475 - 1795
days
Table 1 Characteristics of the geodetic orbit for Jason-1 since May 7th 2012
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For this new phase of the Jason-1 mission (called j1g) the cycle numbering will restart at 500 Off-lineproducts will be produced once a day for the IGDR and every 11 days for the GDRrsquos The integration ofJason-1 data in the DUACS system is available since May 25th 2012
II3 Envisat has stopped sending data (April 2012)
Since April 8th 2012 Envisat has stopped sending data to Earth Esarsquos mission control has worked tore-establish contact with the satellite but there has been no reaction from the satellite Thus Esa has de-clared officially the end of mission for Envisat (see httpwwwesaintesaCPSEM1SXSWT1H_index_0html) Therefore no SL TAC NRT data from Envisat can be released since this date
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II4 Integration of the Cryosat2 Mission (February 2012)
Since February 6th 2012 Cryosat-2 mission has been integrated in the DUACS sytem This mission isdedicated to the observation of the floating sea-ice as well as the continental ice sheets but all data acquiredover ocean are valuable for the observation of oceanic circulation and mesoscale variations This majorchange is the result of the long-standing and fruitful partnership between ESA and CNES and a responseto the request from scientific and operational oceanography users [7] The integration of Cryosat-2 impactsthe delivering of Near real time Sea Level Anomalies (SLA)
II41 Generalities about the mission
A Cryosat-2 Processing Prototype (C2P) (described in Boy et al 2011 [2]) has been developed on CNESside to lay the ground for various SAR processing studies The processing chains ingest Level-0 telemetryfiles distributed by ESA and perform the following steps to generate Sea Level Anomalies (SLA) values foreach altimeter measurements
bull Level-1 Decommutation time-tagging and localization of measurements
bull Level-1b Calculation of instrumental corrections and geophysicalmeteorological corrections
bull Level-2 MLE4 waveforms Retracking and calculation of SLA
The prototype processes data almost continuously over ocean either in Low Resolution Mode (LRM) or inthe DopplerSAR mode processed as pseudo-LRM mode allowing to increase the coverage (figure 2)
Figure 2 SSH-MSS for Cryosat-2 with LRM mode only (left) or LRM+pseudo-LRM modes (right)
Although Cryosat-2 raw SSH can be only corrected with GPS-derived ionospheric correction and ECMWFwet troposphere correction validation activities showed (Labroue et al 2011 [25]) that C2P outputs have anaccuracy roughly equivalent to Envisatrsquos Level 2 products if the latter are processed with the same standards
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II42 Integration in DUACS
The Cryosat-2 data are included in the Near Real time process The chain delivers now (for global coverageMediterranean and Black Seas) along track data from Cryosat-2 (SLAs) Note that the products distributedare of Level-3 and donrsquot replace Level-2 products distributed by agenciesThe details of the processing are given in Dibarboure et al 2011 [8]Here we just give an overview the data are computed with the corrections given in section III21 Thefiltering and sub-sampling of SLAs (section III263) are detailed in [8]
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II5 Addition of Europe and Arctic products (January 2012)
Since the MyOcean V2 two new along-track products are computed in Near Real Time intended foraddressing the needs of data assmilation and validation in regional models
bull Following the TAPAS (Tailored Altimeter Product for Assimilation Systems) initiative launched bySL TAC with all the Modeling and Forecasting Centers (MFCs) the Europe regional products (PLSEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004) have been proposed (figure 3) They areavailable in Near Real Time onlyThey are studied to partly fulfil the needs of the Centers with adapted filtering and resolution Thoseparameters have been tuned in order to provide boundary conditions for the Atlantic assimilationmodels They are different from the ones used for Mediterranean and Black Seas products If you needto study the Mediterranean Sea or the Black Sea yoursquod better use the dedicated products describedabove since the processing parameters have been fitted to be adapted to the dynamics of the ocean inthose regions
Figure 3 Coverage of the Europe product for Jason-1 Jason-2 and Envisat from August 18th to September9th 2011
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bull The Arctic along-track products (PL SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005) coverlatitudes between 45 and 82 degrees (figure 4) They are available in Near Real Time only
Figure 4 Coverage of the Arctic region with Envisat from October 28th 2011 to January 3rd 2012
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III SSALTODUACS SYSTEM
III1 Introduction
This chapter presents the input data used by SSALTODUACS system and an overview of the different pro-cessing steps necessary to produce the output dataSSALTODUACS system is made of two components a Near Real Time one (NRT) and a Delayed Time(DT) oneIn NRT the systemrsquos primary objective is to provide operational applications with directly usable high qual-ity altimeter data from all missions availableIn DT it is to maintain a consistent and user-friendly altimeter database using the state-of-the-art recom-mendations from the altimetry communityFollowing figure gives an overview of DUACS system where processing sequences can be divided into 7main steps
bull acquisition
bull homogenization
bull input data quality control
bull multi-mission cross-calibration
bull product generation
bull merging
bull final quality control
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Figure 5 SSALTODUACS processing sequences
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III2 Near Real Time processing steps
III21 Input data models and corrections applied
To produce SLA in near-real time the DUACS system uses two flows based on the same instrumental mea-surements but with a different quality
bull The IGDR that are the latest high-quality altimeter data produced in near-real-time
bull The OGDR that includes real time data (OSTMJason-2 and Jason-1 OSDR) to complete IGDR Thesefast delivery products do not always benefit from precise orbit determination nor from some exter-nal model-based corrections (Dynamic Atmospheric Correction (DAC) Global Ionospheric Maps(GIM))
Integration of OGDR data and the introduction of Jason-2Jason-1 tandem increased the resilience and pre-cision of the system A better restitution of ocean variability is observed especially in high energetic areas
Altimetric product Source Availability Type of orbit
Jason-2 IGDR CNES ~24h CNES MOE GDR-Cuntil 20120730
CNES MOE GDR-Dsince 20120731
OGDR NOAAEUMETSAT ~3 to 5 h
Jason-1 IGDR CNESNASA ~48 h CNES MOE GDR-Dsince 20120507
OGDR CNESNASA ~3 to 12 h
Envisat IGDR ESACNES not deliveredsince 20120408
CNES MOE GDR-Dsince 20120121
FDGDR ESA not deliveredsince 20120408
Cryosat-2 IGDR-like ESACNES ~48 h CNES MOE GDR-D
not delivered
Table 2 SSALTODUACS Near-Real Time Input data overview
See Figure 6 Overview of the near real time system data flow management
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DUACS 2011 NRT product from IGDR1
j2 j1nj1g enn c2Productstandard ref
version C until20120730 and D after
version C version 21 CPP [2]
Orbit CNES MOE GDR-Cuntil 20120730
GDR-D after
CNES MOE GDR-C forj1n and CNES MOE
GDR-D for j1g
CNES MOE GDR-Dfrom 20120121 to
20120408
CNES MOE GDR-D
Ionopheric bi-frequency altimeter range measurements GIM model for cgt64 (Iijima et al1998[24])Dry tropo Model computed from ECMWF Gaussian grids (new S1 and S2 atm tides applied)Wet tropo-sphere
AMR radiometer(enhancement in coastal
regions since20120730)
JMR radiometer MWR radiometer andcorrected from side
lobes
Model computed fromECMWF Gaussian
grids
DAC MOG2D High Resolution forced with ECMWF pressure and wind fields (S1 and S2 wereexcluded) (Carrere and Lyard 2003[3])+ inverse barometer Filtering temporal window is
un-centered (no data in the future)Ocean tide GOT4v8 (S1 and S2 are included) and TPX 072 [16] for Arctic productsPole tide [Wahr 1985 [53]]Solid earthtide
Elastic response to tidal potential [Cartwright and Tayler 1971[5]] [Cartwright andEdden 1973[6]]
Loading tide GOT4v8 (S1 and S2 are included)Sea statebias
Non parametric SSB[Labroue 2004[27]](with cycles J1 1 to 11
using GDR-B standardsuntil 20120730 andderived from Jason-2
after)
Non parametric SSB[Labroue 2004[27]](with cycles 1 to 21
using GDR-Bstandards)
Non parametric SSB[Labroue 2004[27]](with cycles 41 to 60
using GDR-Bstandards)
Same as Jason-2 SSB
Orbit error Global multi-mission crossover minimization (Le Traon and Ogor1998[32])
Long wave-lengh errors
Optimal Interpolation [Le Traon et al 1998[31]]
Intercalibration Reference from cycle20
Mean pro-file (seeIII261)
Computed with cycles11-353 TP data andwith cycles 11-250J1 data referenced[19931999]
TPNJ1N computedwith cycles 369-479TPN data refer-enced [19931999]J1G No MP can beused instead theMSS_CNES_CLS11[39] is used
No Mean Profilecan be used forEnvisat on its neworbit Instead theMSS_CNES_CLS11[39] is used
No Mean Profilecan be used forCryosat-2 Instead theMSS_CNES_CLS11[39] is used
(1) A flag included in the along-track files indicates the source of the production (OGDRFDGDR orIGDR) If flag=0 the processed data comes from OGDRsFDGDRs if flag=1 the processed data comesfrom IGDRs
Table 3 Corrections and models applied in SSALTODUACS NRT products produced from IGDRs
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DUACS 2011 NRT product from OGDR or FDGDR2
j2 j1nj1g ennProduct stan-dard ref
version C until 20120730and D after
version C version 21
Orbit Navigator Extrapolated CNES MOEGDR-D since 20120121
Ionopheric From-dual frequency altimeter range measurements From GIM model fromcycle 65 (Iijima et al1998 [24])
Dry troposphere Model computed from ECMWF Gaussian grids (new S1 and S2 atmospherictides are applied)
Wet tropo-sphere
AMR radiometer(enhancement in coastal
regions since 20120730)
JMR radiometer MWR radiometer andcorrected from side lobes
DAC Inverse Barometer forecastedOcean tide GOT4v8 (S1 and S2 are included) and TPX 072 [16] for Arctic productsPole tide [Wahr 1985 [53]]Solid earth tide Elastic response to tidal potential [Cartwright and Tayler 1971[5]]
[Cartwright and Edden 1973[6]]Loading tide GOT4v8 (S1 and S2 are included)Sea state bias Non parametric SSB
[Labroue 2004[27]] (withcycles J1 1 to 11 usingGDR-B standards until20120730 and derivedfrom Jason-2 after)
Non parametric SSB[Labroue 2004[27]](with cycles 1 to 21 usingGDR-B standards)
Non parametric SSB[Labroue 2004[27]](with cycles 41 to 60using GDR-B standards)
Orbit error Specific filtering of long-wavelength signal3
Long wave-lengh errors
Optimal Interpolation [Le Traon et al 1998[31]]
Intercalibration Reference from cycle 20Mean profile(see III261)
Computed with cycles 11-353 TP data and with cy-cles 11-250 J1 data refer-enced [19931999]
TPNJ1N computedwith cycles 369-479TPN data referenced[19931999] J1G NoMP can be used insteadthe MSS_CNES_CLS11[39] is used
No Mean Profile can beused for Envisat on itsnew orbit Instead theMSS_CNES_CLS11 [39]is used
(2) A flag included in the along-track files indicates the source of the production (OGDRFDGDR orIGDR) If flag=0 the processed data comes from OGDRsFDGDRs if flag=1 the processed data comesfrom IGDRs(3) Specific data processing was applied on long wave-length signal (sectIII23 of the user manual)
Table 4 Corrections and models applied in SSALTODUACS NRT products produced from OG-DRsFDGDRs
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III22 Acquisition
The acquisition process is twofold
bull straightforward retrieval and reformatting of altimeter data and dynamic auxiliary data (pressure andwet troposphere correction grids from ECMWF are provided by Meteo France TEC grids from JPLNRT MOG2D corrections) from external repositories
bull synchronisation process
To be homogenized properly altimeter data sets require various auxiliary data The acquisition softwaredetects downloads and processes incoming data as soon as they are available on remote sites (externaldatabase FTP site) Data are split into passes if necessary If data flows are missing or late the synchroni-sation engine put unusable data in waiting queues and automatically unfreezes them upon reception of themissing auxiliary data This processing step delivers raw data that is to say data that have been dividedinto cycles and passes and ordered chronologicallyFrom SSALTODUACS V80 the acquisition step uses two different data flows in near-real time the OGDRflow (within a few hours) and the IGDR flow (within a few days)For each OGDR input the system checks that no equivalent IGDR entry is available in the data base beforeacquisition for each IGDR input the system checks and delete the equivalent OGDR entry in the data baseThese operations aim to avoid duplicates in SSALTODUACS system
Figure 6 Overview of the near real time system data flow management
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III23 Homogenization
The Homogenization process consists in applying the most recent corrections models and references rec-ommended for altimeter products Each mission is processed separately as its needs depend on the baseinput data The list of corrections and models currently applied is provided in tables 3 and 4 for NRT dataThe system includes SLA filtering to process OGDR data DUACS extract from these data sets the shortscales (space and time) which are useful to better describe the ocean variability in real time and merge thisinformation with a fair description of large scale signals provided by the multi-satellite observation in nearreal time (read IGDR-based DUACS data) Finally an hybrid SLA is computed
Figure 7 Merging pertinent information from IGDR and OGDR processing
III24 Input data quality control
The Input Data Quality Control is a critical process applied to guarantee that DUACS uses only the mostaccurate altimeter data Thanks to the high quality of current missions this process rejects a small percent-age of altimeter measurements but these erroneous data could be the cause of a significant quality lossThe quality control relies on standard raw data editing with quality flags or parameter thresholds but alsoon complex data editing algorithms based on the detection of erroneous artefacts mono and multi-missioncrossover validation and macroscopic statistics to edit out large data flows that do not meet the systemrsquosrequirements
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III25 Multi-mission cross-calibration
The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistentand accurate information It removes any residual orbit error (OE Le Traon and Ogor 1998[32]) or longwavelength error (LWE Le Traon et al 1998[31]) as well as large scale biases and discrepancies betweenvarious data flows
This process is based on two very different algorithms a global multi-mission crossover minimization fororbit error reduction (OER) and Optimal Interpolation (OI) for LWE
Multi-satellite crossover determination is performed on a daily basis All altimeter fields (measurementcorrections and other fields such as bathymetry MSS) are interpolated at crossover locations and datesCrossovers are then appended to the existing crossover database as more altimeter data become availableThis crossover data set is the input of the Orbit Error Reduction (OER) method Using the precision of thereference mission orbit a very accurate orbit error can be estimated This processing step does not concernOGDR dataLWE is mostly due to residual tidal or inverse barometer errors and high frequency ocean signals The OIused for LWE reduction uses precise parameters derived from
bull accurate statistical description of sea level variability
bull localized correlation scales
bull mission-specific noise and precise assumptions on the long wavelength errors to be removed (from arecent analysis of one year of data from each mission)
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III26 Product generation
The product generation process is composed of four steps computation of raw SLA cross-validationfilteringampsub-sampling and generation of by-products
III261 Computation of raw SLA
Since the geoid is not well known yet the SSH cannot be used directly the SSH anomalies are used insteadThey are computed from the difference of the instantaneous SSH - a temporal reference This temporalreference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeattrack analysis cannot be used The errors affecting the SLAs MPs and MSS have different magnitudes andwavelengths The computation of the SLAs and their errors associated are detailed in Dibarboure et al 2010[9]
Use of a Mean ProfileIn the repeat track analysis (when the satellites flies over a repetitive orbit) measurements are re-sampledalong a theoretical ground track (or mean track) associated to each mission Then a Mean Profile (MP) issubtracted from the re-sampled data to obtain SLA The MP is a time average of similarly re-sampled dataover a long period
bull The Mean Profile used for Jason-2 is computed with 10 years of TP (cycles 11 to 353) and 6 years ofJason-1 (cycles 11 to 250)
bull The Mean Profile used from Jason-1 cycle 262 to 374 (where satellites are on interleaved ground-tracks) is computed with 3 years of TP (cycles 369 to 479)
bull No Mean Profile can be used for Envisat on its new orbit (enn) Jason-1 on its geodetic orbit (j1g) norfor Cryosat-2 mission (c2) because there is no repetitive track The MSS must be used instead (seebelow)
Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible
bull Indeed as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide precise cross-track projection andor interpolation schemes are required to avoid errors
bull The mesoscale variability error (which is lt35 cm for MP between 3 to 5 years and lt1cm for WLof 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a prioriknowledge from Sea Level maps derived from previous iterations or from other missions
bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
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bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for Envisat since november 2010 and for Cryosat-2 mission (c2)because the satellite is not in a repetitive orbit phase The alternative is to use the MSS instead The griddedMSS is derived from along track MPs and data from geodetic phases Thus any error on the MP is alsocontained in the MSS There are essentially 4 types of additional errors on gridded MSS which are hard toquantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
Note that for the Arctic regional products the DTU10 MSS [1] is taken into account instead of the CLS01MSS Indeed the accuracy of DTU10 compared to CLS01 is further demonstrated by the significant sealevel anomaly variance reduction found over the whole Arctic Ocean as shown in Prandi et al [42]
III262 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III263 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
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III27 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III271 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
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III272 Performance indicators
To appreciate the quality situation of the DUACS system new performance indicators are computed dailyThey aim at evaluate the status of the main processing steps of the system the input data availability theinput data coverage the input data quality and the output product quality These indicators are computed foreach and every currently working satellite and combined to obtain the overall status
Figure 8 Example with the key performance indicator on 20090627
See the description the latest and previous indicators on Aviso websitehttpwwwavisooceanobscomindexphpid=1516
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III3 Delayed Time processing steps
III31 Input data models and corrections applied
Delayed Time MyOcean products are generated
bull from Aviso GDR products for TP Jason-1 Jason-2 and Envisat (GDR-A cycles 1 to 22 GDR-Bcycles 23 to 85 GDR-C from cycle 86)
bull from NOAA GDR for GFO and from CERSAT (IFREMER) OPR for ERS-1 and ERS-2 (phases C(1st 35-day repeat orbit period) phase E and F (geodetic phases) phase G for ERS-1 (last 35-dayrepeat orbit period tandem phase with ERS-2 phase A for ERS-2 (1st 35-day repeat orbit periodtandem phase with ERS-1))
All GDR products are computed with a Precise Orbit Ephemeris (POE) and are delivered within 2 to 3months depending on the mission For several missions an updated orbit is used
bull For ERS-1amp-2 the orbit used is DGME-04 provided by Delft Institute (httpwwwdeostudelftnl)until June 2003
bull For TopexPoseidon the orbit used is GSFC (std0809) for the whole mission
bull For Envisat CNES POE of GDR-C standard is used for the whole mission
bull For the whole GFO mission the orbit used is GSFC (std0809) and when not available NASA POE isused
Altimetric product Source Availability Type of orbit
TopexPoseidon GDR NASACNES - GSFC POE
Jason-1 GDR (GDR-C) CNESNASA ~40 days CNES POE
Jason-2 GDR (GDR-C) CNESNASA ~60 days CNES POE
GFO GDR NOAA - GSFCNASA POE
ERS-1amp2 IFREMERESA - DGME-04
Envisat (GDR-A GDR-B andGDR-C from cycle 86)
ESA ~2 months CNES POE
Table 5 SSALTODUACS Delayed Time Input data overview
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DU
AC
S20
11D
Tpr
oduc
t(gtV
30
0)j2
j1j1
ntp
tpn
e1e2
ene
nng2
Prod
uct
stan
dard
ref
GD
R-C
OPR
GD
R-A
(Cyc
les
1to
22)
GD
R-B
(cyc
les
23-8
5)
GD
R(N
OA
A)
Orb
itC
nes
POE
GSF
C(I
TR
F20
05G
RA
CE
last
stan
dard
s)
DG
ME
-04
(Sch
arro
oan
dV
isse
r19
98[4
8]C
NE
SPO
E(G
DR
-1st
anda
rds
forc
ycle
s9
to22
GD
R-C
stan
dard
sfr
omcy
cle
23)
GSF
C(I
TR
F20
05
GR
AC
Ela
stst
anda
rds
Iono
pher
icD
ual f
requ
ency
altim
eter
rang
em
easu
rem
ents
Dua
l fre
quen
cyal
timet
erra
nge
mea
sure
men
ts(T
opex
)D
OR
IS(P
OSE
IDO
N)
Ben
t mod
elB
ent m
odel
(cyc
les
1-36
)G
IMm
odem
from
cycl
e37
((Ii
jima
etal
19
98[2
4])
Dua
l-fr
eque
ncy
altim
eter
rang
em
easu
rem
ent(
cycl
e9-
64)a
ndG
IMm
odel
gtcyc
le65
(Iiji
ma
etal
19
99[2
4])c
orre
cted
from
8m
mbi
as
From
GIM
mod
el(I
ijim
aet
al1
998
[24]
)
Dry
trop
o-sp
here
Mod
elco
mpu
ted
from
EC
MW
FG
auss
ian
grid
s(n
ewS1
and
S2at
mos
pher
ictid
esar
eap
plie
d)
Mod
elco
mpu
ted
from
EC
MW
Fre
ctan
gula
rgri
ds(n
ewS1
and
S2at
mos
pher
ictid
esar
ein
clud
ed)
Wet
trop
o-sp
here
JMR
AM
Rra
diom
eter
furt
hert
han
50km
from
the
coas
tsF
rom
EC
MW
Fm
odel
ford
ista
nces
betw
een
10an
d50
km
TM
Rra
diom
eter
(Sch
aroo
etal
20
04[4
9])
MW
RC
orre
ctio
nof
the
drif
ton
the
236
GH
zbr
ight
ness
tem
pera
ture
(Sch
arro
oet
al
2004
[49]
)Neu
ral
Net
wor
kal
gori
thm
(Tra
nan
dO
blig
is
2003
[50]
MW
Rra
diom
eter
furt
hert
han
50km
from
the
coas
tsan
dco
rrec
ted
from
side
lobe
s(f
rom
cycl
e41
)E
CM
WF
mod
elfo
rdis
tanc
esbe
twee
n10
and
50km
GFO
radi
omet
er
DA
CM
OG
2DH
igh
Res
olut
ion
forc
edw
ithE
CM
WF
pres
sure
and
win
gfie
lds
(S1
and
S2w
ere
excl
uded
)+in
vers
eba
rom
eter
com
pute
dfr
omre
ctan
gula
rgri
ds
Tabl
e6
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(1
2)
Page 33
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
j2j1
j1n
tptp
ne1
e2en
enn
g2O
cean
tide
GO
T4v
7(S
1an
dS2
are
incl
uded
)Po
letid
e[W
ahr
1985
[53]
]So
lidea
rth
tide
Ela
stic
resp
onse
totid
alpo
tent
ial[
Car
twri
ghta
ndTa
yler
197
1[5]
][C
artw
righ
tand
Edd
en1
973[
6]]
Loa
ding
tide
GO
T4v
7(S
1pa
ram
eter
isin
clud
ed)
Sea
stat
ebi
asN
onpa
ram
etri
cSS
B[G
aspa
reta
l20
02[2
0]]
Non
para
met
ric
SSB
[NT
ran
and
al2
010[
51]]
BM
3[G
aspa
ran
dO
gor
1994
[17]
]
Non
para
met
ric
SSB
[Mer
tzet
al
2005
[38]
]
Non
para
met
ric
SSB
[Gas
pare
tal
2002
]w
ithG
DR
-Bst
anda
rds
forc
ycle
s9
to85
and
with
GD
R-C
stan
dard
sfr
omcy
cle
86
Non
para
met
ric
SSB
[NT
ran
etal
20
10[5
1]]
Orb
iter
ror
Glo
bal m
ulti-
mis
sion
cros
sove
rmin
imiz
atio
n(L
eTr
aon
and
Ogo
r19
98[3
2])
Lon
gw
ave-
leng
her
rors
Opt
imal
Inte
rpol
atio
n(L
eTr
aon
etal
19
98[3
1])
Inte
rcal
ibra
tion
Ref
eren
cefr
omcy
cle
11R
efer
ence
from
cycl
e1
to35
4C
orre
ctio
nof
regi
onal
bias
J2J
1de
duce
dfr
omin
terc
alib
ratio
nph
ase
(cyc
le11
J2)
Cor
rect
ion
ofgl
obal
biai
sJ1
TP
deacutedu
ced
from
inte
rcal
ibra
tion
phas
e(c
ycle
s11
J1)
Mea
npr
o-fil
e(s
eeII
I36
1)
Com
pute
dw
ithcy
cles
11-3
53T
Pda
taan
dw
ithcy
cles
11-2
50J1
data
ref
eren
ced
[199
319
99]
TP
J1 c
ompu
ted
with
cycl
es11
-353
TP
data
and
with
cycl
es11
-250
J1da
tar
efer
ence
d[1
993
1999
]T
PNJ
1Nc
ompu
ted
with
cycl
es36
9-47
9T
PNda
tar
efer
ence
d[1
993
1999
]
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
ref
eren
ced
[199
319
99]
EN
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
re
fere
nced
[199
319
99]
EN
Nu
seof
MSS
_CN
ES_
CL
S11
[39]
Com
pute
dw
ithcy
cles
37-1
87G
2da
ta
refe
renc
ed[1
993
1999
]
Peri
odof
use
from
cycl
e9
from
cycl
e9
cycl
es1
to48
1cy
cles
15to
43In
clud
ing
E-F
geod
etic
phas
es
cycl
es1
to83
from
cycl
e9
cycl
es37
to22
2
Tabl
e7
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(2
2)
Page 34
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III32 Acquisition
The acqusition process in Delayed time is much simpler than in Near Real time it consists in a synchronisa-tion process of all the auxiliary data required to homogenize propely the altimeter data sets The acquisitionstep uses the GDRs or the OPRs provided by the agencies
III33 Homogenization
The Homogenization process consists in applying the most recent corrections models and references rec-ommended for altimeter products Each mission is processed separately as its needs depend on the baseinput data The list of corrections and models currently applied is provided in tables 6 and 7 for DT data
III34 Input data quality control
The Input Data Quality Control is a critical process applied to guarantee that DUACS uses only the mostaccurate altimeter data Thanks to the high quality of current missions this process rejects a small percent-age of altimeter measurements but these erroneous data could be the cause of a significant quality lossThe quality control relies on standard raw data editing with quality flags or parameter thresholds but alsoon complex data editing algorithms based on the detection of erroneous artefacts mono and multi-missioncrossover validation and macroscopic statistics to edit out large data flows that do not meet the systemrsquosrequirements
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PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III35 Multi-mission cross-calibration
The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistentand accurate information It removes any residual orbit error (OE Le Traon and Ogor 1998[32]) or longwavelength error (LWE Le Traon et al 1998[31]) as well as large scale biases and discrepancies betweenvarious data flows
This process is based on two very different algorithms a global multi-mission crossover minimization fororbit error reduction (OER) and Optimal Interpolation (OI) for LWE
Multi-satellite crossover determination is performed on a daily basis All altimeter fields (measurementcorrections and other fields such as bathymetry MSS) are interpolated at crossover locations and datesCrossovers are then appended to the existing crossover database as more altimeter data become availableThis crossover data set is the input of the Orbit Error Reduction (OER) method Using the precision of thereference mission orbit a very accurate orbit error can be estimated LWE is mostly due to residual tidalor inverse barometer errors and high frequency ocean signals The OI used for LWE reduction uses preciseparameters derived from
bull accurate statistical description of sea level variability
bull localized correlation scales
bull mission-specific noise and precise assumptions on the long wavelength errors to be removed (from arecent analysis of one year of data from each mission)
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PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III36 Product generation
The product generation process is composed of four steps computation of raw SLA cross-validationfilteringampsub-sampling and generation of by-products
III361 Computation of raw SLA
Since the geoid is not well known yet the SSH cannot be used directly the SSH anomalies are used insteadThey are computed from the difference of the instantaneous SSH - a temporal reference This temporalreference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeattrack analysis cannot be used The errors affecting the SLAs MPs and MSS have different magnitudes andwavelengths The computation of the SLAs and their errors associated are detailed in Dibarboure et al 2010[9]
Use of a Mean ProfileIn the repeat track analysis (when the satellites flies over a repetitive orbit) measurements are re-sampledalong a theoretical ground track (or mean track) associated to each mission Then a Mean Profile (MP) issubtracted from the re-sampled data to obtain SLA The MP is a time average of similarly re-sampled dataover a long period
bull The Mean Profile used for TP (cycles 1 to 364) Jason-1 (cycles 1 to 259) and Jason-2 is computedwith 10 years of TP (cycles 11 to 353) and 6 years of Jason-1 (cycles 11 to 250)
bull The Mean Profile used for TP (cycles 368 to 481) and from Jason-1 cycle 262 to 374 (where satellitesare on interleaved ground-tracks) is computed with 3 years of TP (cycles 369 to 479)
bull The Mean Profile used for ERS-1 in its 35 days repetitive orbit mission ERS-2 and Envisat (only forthe first orbit before November 2010) is computed with 8 years of ERS-2 (cycles 1 to 85) and 6 yearsof Envisat (cycles 10 to 72)
bull No Mean Profile can be used for Envisat on its new orbit (enn) Jason-1 on its geodetic orbit (j1g)because there is no repetitive track The MSS must be used instead (see below)
bull The Mean Profile used for GFO is computed with 7 years of GFO cycles 37 to 187
Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible
bull Indeed as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide precise cross-track projection andor interpolation schemes are required to avoid errors
bull The mesoscale variability error (which is lt35 cm for MP between 3 to 5 years and lt1cm for WLof 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a prioriknowledge from Sea Level maps derived from previous iterations or from other missions
Page 37
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for ERS-1 for its 168 days geodetic mission (phases E-F from April1994 to March 1995) or for Envisat since november 2010 because the satellite is not in a repetitive orbitphase The alternative is to use the MSS instead The gridded MSS is derived from along track MPs anddata from geodetic phases Thus any error on the MP is also contained in the MSS There are essentially 4types of additional errors on gridded MSS which are hard to quantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
III362 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III363 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
Page 38
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III37 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III371 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
Page 39
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
IV MYOCEAN PRODUCTS
IV1 Near Real Time Products
The purpose of the NRT DUACS component is the acquisition of altimeter data from various altimeter mis-sions in near-real time (ie within a few days at most) the validation and correction of these altimeter datasets (ie edition and selection update of corrections and homogenization orbit error reduction) in order toproduce each day along-track productsProducts are as follows
Along-track products global and regional (Mediterranean and Black Seas Arctic Ocean and Europeareas)
bull Sea Level Anomaly (NRT-SLA) for each mission with NRT-SLA ephemeris
IV11 Delay of the products
The availability of the products in near real time is three to twelve hours after the measurement for along-track products Those products are delivered every day
IV12 Temporal availibility
The following table presents the available products by mission and by data periodNear real time products
NRT Jason-2 Jason-1 and Jason-1geodetic
Envisat new Cryosat-2
Temporal Time availability ymlowast
ongoingymlowast-20120303 for
repeat track and20120507-ongoing for
geodetic track
ymlowast
2012040820120101
ongoing
NRT-SLA X X X X
lowastym the temporal coverage for NRT products is fluctuating and depends on updates of Delayed Time prod-ucts When DT products are updated (3 to 4 times per year) the oldest NRT products are replaced by thebetter quality DT products so that the 2 series are overlapping on few weeks or few months
IV2 Delayed Time Products
The Delayed Time component of SSALTODUACS system is responsible for the production of processedJason-1 Jason-2 TP Envisat GFO ERS12 and even Geosat data in order to provide a homogeneousinter-calibrated and highly accurate long time series of SLA DT products are more precise than NRT products Two reasons explain this quality difference The firstone is the better intrinsic quality of the POE orbit used in the GDR processing The second reason is that
Page 40
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
in the DT DUACS processing the products can be computed optimally with a centred computation timewindow for OER LWE On the contrary in NRT case future data are not available so the computationtime window is not centred and therefore not optimalAs for NRT products improved altimeter corrections and processing algorithms are used ocean tide modelto correct altimeter data improved methods for orbit error reduction and mapping
Along-Track products global and regional (Mediterranean and Black Seas)
bull Sea Level Anomaly (DT-SLA) for each mission
IV21 Delay of the products
Weekly products are delivered The availability of the products in delayed time is at the best two monthsafter the date of the measurement The product generation needs all the GDR data of all the missions to takeinto account the best corrections as possible The time delay can be longer in the case of a missing mission
IV22 Temporal availibility
The following table presents the available products by mission and by data periodDelayed time SSALTODUACS products
Upd Jason-2 Jason-1new6
Jason-1 GFO Envisatnew6
Envisat ERS-16
ERS-2Topexnew6
Topex
TemporalTimeavailabil-ity
200810ymlowast
200902ymlowast
200204200810
200001200809
201010ymlowast
200210201010
199210200304
200209200510
199209200204
DT-SLA X X X X X X X X X
lowast ym those dates are updated regularly (3 to 4 times per year) and are avalaible when you download thedata at httpwwwmyoceaneuweb24-cataloguephp6 Jason-1 new orbit starting 200809 Envisat new orbit starting 201010 TP new orbit starting 200209 ERS-1The geodetic phases (E-F) are included There are no ERS-1 data between December 23 1993 and April 10 1994(ERS-1 phase D - 2nd ice phase) Note that during that time products are based only on TopexPoseidon data
Page 41
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
V DESCRIPTION OF THE PRODUCT SPECIFICATION
V1 General information
Product Specification SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001
Geographical coverage global
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 20-50km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001 Product Specification
Page 42
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
Product Specification SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002
Geographical coverage 55˚W-35˚E 30˚N-46˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002 Product Specification
Page 43
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
Product Specification SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003
Geographical coverage 27˚E-42˚E 40˚N-47˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003 Product Specification
Page 44
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
Product Specification SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004
Geographical coverage 25˚W-42˚E 21˚N-66˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004 Product Specification
Page 45
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
Product Specification SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005
Geographical coverage 0˚W-360˚E 50˚N-82˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005 Product Specification
Page 46
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
VI NOMENCLATURE OF FILES
VI1 Nomenclature of files downloaded through the MyOcean Web PortalDirectgetfile Service
VI11 Nomenclature of the product line
The description of the syntax for the SL TAC SLA products line is given by
SEALEVEL_ltREGIONgt_SLA_L3_ltDELAYgt_OBSERVATIONS_008_ltZONEgt_ltLETTERgtwhere
REGION GLO global geographic coverage product
BS Black Sea products
MED Mediterranean products
ARC Arctic products (for NRT products)
EUROPE Europe products (for NRT products)
DELAY NRT near real time products
RAN delayed time or reanalysis products
ZONE 001 number on 3 digits
002
003
004
LETTER a letter on 1 digit
b
Page 47
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
VI12 Nomenclature of the datasets
The nomenclature used is
dataset-duacs-ltdelaygt-ltzonegt-ltmissiongt-lttype of slagt-l3where the fileds in ltgt are described below
delay nrt near-real time productsran delayed time products
zone global global geographic coverage productmedsea Mediterranean productsblacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1 (only for ran)e2 ERS-2 (only for ran)tp TOPEXPoseidon (only for ran)tpn TOPEXPoseidon on its new orbit (only for
ran)g2 GFO (only for ran)j1 Jason-1 (only for ran)j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisat (only for ran)enn Envisat on its new orbitc2 Cryosat-2 (only for nrt)
type of sla sla filtered slasla_unfiltered non filtered sla (only for ran products)
Page 48
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
VI13 Nomenclature of the NetCdf files
The nomenclature used is
ltdelaygt_ltzonegt_ltmissiongt_sla_ltvariablegt_ltdatebegingt_ltdateendgt_ltdateprodgtnc where the fileds in ltgt are de-scribed below
delay nrt near-real time productsdt delayed time products
zone global global geographic coverage productmed Mediterranean products (for dt)mfstep Mediterranean products (for nrt)blacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1e2 ERS-2tp TOPEXPoseidontpn TOPEXPoseidon on its new orbitg2 GFOj1 Jason-1j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisatenn Envisat on its new orbitc2 Cryosat-2
variable vfec filtered and sub-sampled slavxxc non filtered and non sub-sampled sla (only
for dt)datebegin YYYYMMDD() beginning date of the datasetdateend YYYYMMDD() end date of the datasetdateprod YYYYMMDD production date of the dataset
() For dt data as the dates in the file names are rounded the user wanting data for date T has to read the filescontaining dates T+1 and T-1 in their name and check inside the files if there are some data for date T
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VII DATA FORMAT
This chapter presents the data storage format used for MyOcean products
VII1 NetCdf
The products are stored using the NetCDF format NetCDF (network Common Data Form) is an interface for array-oriented data access and a library that provides an implementation of the interface The netCDF library also definesa machine-independent format for representing scientific data Together the interface library and format support thecreation access and sharing of scientific data The netCDF software was developed at the Unidata Program Center inBoulder Colorado The netCDF libraries define a machine-independent format for representing scientific data Pleasesee Unidata NetCDF pages for more information and to retreive NetCDF software package onhttpwwwunidataucaredupackagesnetcdfindexhtml
NetCDF data is
bull Self-Describing A netCDF file includes information about the data it contains
bull Architecture-independent A netCDF file is represented in a form that can be accessed by computers with dif-ferent ways of storing integers characters and floating-point numbers
bull Direct-access A small subset of a large dataset may be accessed efficiently without first reading through allthe preceding data
bull Appendable Data can be appended to a netCDF dataset along one dimension without copying the dataset orredefining its structure The structure of a netCDF dataset can be changed though this sometimes causes thedataset to be copied
bull Sharable One writer and multiple readers may simultaneously access the same netCDF file
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VII2 Structure and semantic of NetCDF along-track files
The NetCDF Sea Level TAC files are based on the attribute data tags defined by the Cooperative OceanAtmosphereResearch Data Service (COARDS) and Climate and Forecast (CF) metadata conventions The CF convention gener-alises and extends the COARDS convention but relaxes the COARDS constraints on dimension and order and specifiesmethods for reducing the size of datasetsA wide range of software are available to write or read NetCDFCF files API are made available by UNIDATA(httpwwwunidataucaredusoftwarenetcdf)
bull CC++Fortran
bull Java
bull MATLAB Objective-C Perl Python R Ruby TclTk
In addition to these conventions the files are using a common structure and semantic
bull 1 dimension is defined
ndash time it is used to check NetCDF variables depending on time
bull 8 variables are defined
ndash short SLA contains the Sea Level Anomaly values for each time given
ndash int longitude contains the longitude for each measurement
ndash short track contains the track number for each measurement
ndash double time contains the time in days since 1950-01-01 000000 UTC for each measurement
ndash short mean_profile_point_index index of the corrsponding point in the track of the mean profile
ndash byte flag flag=0 the processed data comes from OGDR if flag=1 the processed data comes from theIGDR
ndash int latitude contains the latitude for each measurement
ndash short cycle contains the cycle number for each measurement
bull global attributes
ndash the global attributes gives information about the creation of the file
Example of a NetCDF sla file
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netcdf nrt_global_j1_sla_vfec_20101230_20101230_20101230 dimensions
time = 10385 variables
short SLA(time) SLAcoordinates = longitude latitude SLAlong_name = Sea Level Anomaly SLA_FillValue = 32767s SLAadd_offset = 0 SLAscale_factor = 0001 SLAunits = m SLAstandard_name = sea_surface_height_above_sea_level
int longitude(time) longitudelong_name = Longitude of measurement longitude_FillValue = 2147483647 longitudeadd_offset = 0 longitudestandard_name = longitude longitudescale_factor = 1e-06 longitudeunits = degrees_east
short track(time) tracklong_name = Track in cycle the measurement belongs to track_FillValue = 32767s trackunits = 1 trackcoordinates = longitude latitude
double time(time) timelong_name = Time of measurement time_FillValue = 184467440737096e+19 timeaxis = T timestandard_name = time timeunits = days since 1950-01-01 000000 UTC
int latitude(time) latitudelong_name = Latitude of measurement latitude_FillValue = 2147483647 latitudeadd_offset = 0 latitudestandard_name = latitude latitudescale_factor = 1e-06 latitudeunits = degrees_north
short flag(time) flagcoordinates = longitude latitude flag_FillValue = 3267s flaglong_name = data origin flagflag_values = 1s 0s flagflag_meanings = igdr_like non_igdr_like flagcomment = The origin of the data is determined by the types of geophysical datarecords (GDR) used in computation of the SLA 1 for the Interim GDR (IGDR) and0 for Operational GDR (OGDR)
short cycle(time) cyclelong_name = Cycle the measurement belongs to cycle_FillValue = 32767s cycleunits = 1 cyclecoordinates = longitude latitude
global attributeshistory = 22-Feb-2011 155243 CET File created by the SSLATODUACS system version 1001 comment = Produce from ENVISAT Extension Phase satellite altimetry data institution = CLSCNES
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references = httpwwwavisooceanobscomfileadmindocumentsdatatoolshdbk_duacspdf source = satellite altimetry title = along track Sea Level Anomaly Conventions = CF-14
dataSLA =
7 7 11 10 -2 -22 -39 -41 -30 -13 -3 -5 -16 -26 -32 -35-35 -35 -37 -35 -31 -29 -31 -35 -32 -21 -10 -10 -19 -20 -1-69 -57 -49 -45 -39 -30 -28 -31 -27 -13 -2 -5 -15 -3 1112 3 -7 -10 -14 -15 -22 -31 -37 -32 -17 -10
longitude =74743328 74868400 74993968 75120040 75246616 7537372875501368 75629568 75758320 75887656 76017568 76148080 7627920876388952 76477056 76565456 76654144 76743128 76832400 76921984329429568 329535424 329641792 329748672 329856096 329964032330072512 330181536 330291072 330401184
track =92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 9292 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92113 113 113 113 113 113 113 113 113 113 113 113 113 113113 113 113 113 113 113 113 113 113
time =222780000565705 222780001314719 222780002063733222780002812747 222780003561761 222780004310775 222780005059788222780005808802 222780006557816 22278000730683 222780008055844222780008804858 222780009553872 22278001017805 222780010677393222788257112198 222788257486705 222788257861212 222788258235719222788258610226 222788258984733 222788259359239 222788259733746222788260108253 22278826048276
mean_profile_point_index =1872 1878 1884 1890 1896 1902 1908 19141920 1926 1932 1938 1944 1949 1953 1957 1961 1965 1969 19732306 2309 2312 2315 2318 2321 2327 2330 2333 2336 2339 23422345 2348 2351 2354 2357 2360 2363 2366
flag =0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
latitude =-16225506 -16539731 -16853833 -17167810 -17481660 -17795380-18108966 -18422418 -18735729 -19048899 -19361924 -19674801-19987527 -20248015 -20456329 -20664569 -20872739 -2108083739481297 39628277 39775133 39921866 40068472 40214953 4036130840507533 40653629 40799592 40945423 41091120 41236684 41382111
cycle =331 331 331 331 331 331 331 331 331 331 331 331 331
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331 331 331 331 331 331 331 331 331 331 331 331 331 331331 331 331 331 331 331 331 331 331 331 331 331
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VIII HOW TO DOWNLOAD A PRODUCT
VIII1 Download a product through the MyOcean Web Portal DirectgetfileService
You first need to register Please find below the registration stepshttpwwwmyoceaneuweb34-products-and-services-faqphp1Once registered the MyOcean FAQ httpwwwmyoceaneuweb34-products-and-services-faqwill guide you on How to download a product through the MyOcean Web Portal Directgetfile Service
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IX NEWS AND UPDATES
IX1 [Duacs] Operational news
To be kept informed on events occurring on the satellites and on the eventual interruption of the services of the DUACSprocessing system see the [Duacs] operational news on the Aviso websitehttpwwwavisooceanobscomendataoperational-newsindexhtml
IX2 Updates
To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtmlSince 2010 a complete reprocessing of all altimetry data (cumulated total of about 55 years of data) is available Themain changes introduced in the Duacs DT v300 reprocessed data set in SSALTODUACS reprocessed DT data setare listed herehttpwwwavisooceanobscomfileadmindocumentsdataduacsduacs_DT_2010_reprocessing_impactpdf
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[32] Le Traon P-Y and F Ogor 1998 ERS-12 orbit improvement using TOPEXPOSEIDON the 2 cmchallenge J Geophys Res 103 8045-8057
[33] Le Traon P-Y and G Dibarboure 1999 Mesoscale mapping capabilities of multi-satellite altimetermissions J Atmos Oceanic Technol 16 1208-1223
[34] Le Traon P-Y G Dibarboure and N Ducet 2001 Use of a High-Resolution Model to Analyze theMapping Capabilities of Multiple-Altimeter Missions J Atmos Oceanic Technol 18 1277-1288
[35] Le Traon PY and G Dibarboure 2002 Velocity mapping capabilities of present and future altimetermissions the role of high frequency signals J Atmos Oceanic Technol 19 2077-2088
[36] Le Traon PY Faugegravere Y Hernandez F Dorandeu J Mertz F and M Ablain 2002 Can we mergeGEOSAT Follow-On with TOPEXPOSEIDON and ERS-2 for an improved description of the oceancirculation J Atmos Oceanic Technol 20 889-895
[37] Le Traon PY and G Dibarboure 2004 An Illustration of the Contribution of the TOPEXPoseidon-Jason-1 Tandem Mission to Mesoscale Variability Studies Marine Geodesy 27 (1-2)
[38] Mertz F F Mercier S Labroue N Tran J Dorandeu 2005 ERS-2 OPR data quality assessment Long-term monitoring - particular investigation CLSDOSNT-06001 (pdf)
[39] MSS_CNES_CLS11 was produced by CLS Space Oceanography Division and distributed by Avisowith support from Cnes (urlhttpwwwavisooceanobscom)
[40] Pascual A Y Faugegravere G Larnicol P-Y Le Traon 2006 Improved description of the oceanmesoscale variability by combining four satellite altimeters Geophys Res Lett 33
[41] Pascual A C Boone G Larnicol and P-Y Le Traon 2009 On the quality of Real-Time altimetergridded fields comparison with in-situ data Journ of Atm and Ocean Techn Vol 26(3) pp 556-569DOI 1011752008JTECHO5561
[42] Prandi P M Ablain A Cazenave N Picot 2011 A new estimation of mean sea level in the ArcticOcean from satellite altimetry Submitted to Marine Geodesy
[43] Pujol M-I et al 2009 Three-satellite quality level restored in NRT poster at OSTST meeting (pdf)
[44] Ray R 1999 A Global Ocean Tide model from TOPEXPoseidon Altimetry GOT992 NASA TechMemo NASATM-1999-209478 58 pp Goddard Space Flight Center NASA Greenbelt MD USA
[45] Rio M-H and F Hernandez 2003 A Mean Dynamic Topography computed over the worldocean from altimetry in-situ measurements and a geoid model J Geophys Res 109 C12032doi1010292003JC002226
[46] Rio M-H and F Hernandez 2003 High frequency response of wind-driven currents measured bydrifting buoys and altimetry over the world ocean J Geophys Res 108 39-1
[47] Rio M-H 2003 Combinaison de donneacutees in situ altimeacutetriques et gravimeacutetriques pour lrsquoestimationdrsquoune topographie dynamique moyenne globale Ed CLS PhD Thesis University Paul Sabatier(Toulouse III France) 260pp
[48] Scharroo R and P Visser 1998 Precise orbit determination and gravity field improvement for theERS satellites J Geophys Res 103 8113-8127
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[49] Scharroo R J Lillibridge and WHF Smith 2004 Cross-calibration and long-term monitoring ofthe Microwave Radiometers of ERS Topex GFO Jason-1 and Envisat Marine Geodesy 97
[50] Tran N and E Obligis December 2003 Validation of the use of ENVISAT neural algorithms onERS-2 CLSDOSNT03901
[51] Tran N S Labroue S Philipps E Bronner and N Picot 2010 Overview and Update of the SeaState Bias Corrections for the Jason-2 Jason-1 and TOPEX Missions Marine Geodesy accepted
[52] Vincent P Desai SDDorandeu J Ablain M Soussi B Callahan PS and BJ Haines 2003 Jason-1 Geophysical Performance Evaluation Marine Geodesy 26 167-186
[53] Wahr J W 1985 Deformation of the Earth induced by polar motionJ of Geophys Res (Solid Earth)90 9363-9368
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I INTRODUCTION
MyOcean is a European Network project aiming at monitoring analyzing and forecasting the Ocean Ituses satellite and in-situ data to describe the ocean in 3 dimensions and real time More information can befound on httpwwwmyoceaneuorgThe aim of this document is to describe the products delivered by the Sea Level TAC (Thematic AssemblyCentre) which is one of the five TAC of the MyOcean projectThe data produced in the frame of this TAC are generated by the processing system named DUACS (DataUnification and Altimeter Combination System)DUACS is part of the CNES multi-mission ground segment (SSALTO) It processes data from all altimetermissions Cryosat-2 OSTMJason-2 Jason-1 TopexPoseidon Envisat GFO ERS-1amp2 and even GeosatAt this time (May 25th 2012) DUACS is using three different altimeters in near real time Developed and operated by CLS it started as an European Commission Project (Developing Use Of Altime-try for Climate Studies) funded under the European Commission and the Midi-Pyreacuteneacutees regional councilIt has been integrated to the CNES multi-mission ground segment SSALTO in 2001 and it is maintainedupgraded and operated with funding from CNES with shared costs from EU projectsAt the beginning of 2004 DUACS was redefined as the Data Unification Altimeter Combination System
Figure 1 DUACS and AVISO a user-driven altimetry service
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The products lines described in this user manual are the followingSEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005
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The data provided to users have a global coverage (PL SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001)and regional products are also computed over specific areasMediterranean Sea (PL SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002)and Black Sea (PL SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003)Thanks to updates in 2011 and 2012 (see section II) new regional products are now availableEurope (PL SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004)and Arctic (PL SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005)
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II UPDATES IN 2011 AND 2012
This section describes the updates of the SSALTODUACS Near Real Time system that occurred during2011 and 2012 allowing to add new products (Europe and Arctic) the integration of the Cryosat-2 data inthe system the stopping delivery of Envisat data the addition of Jason-1 data on geodetic orbit (j1g)To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtml
II1 Version D of input IGDROGDR Jason-2 data for NRT processing(July 30 2012)
On July 30 2012 the version of Jason-2 IGDROGDR has changed and is now the D version Somecorrections have thus been updated as detailed in tables 3 and 4
II2 Integration of Jason-1 on its geodetic orbit (May 2012)
An anomaly occured on March 3rd 2012 on the Jason-2 mission (see httpwwwavisooceanobscomfractualitesactualitesindexhtmltx_ttnews[tt_news]=1162amptx_ttnews[backPid]=1399ampcHash=d5baeb645e) On April 23rd CNES began to command the satellite into a nadir ori-entation and after some propulsion anomalies CNES and NASA management through the Joint SteeringGroup have directed the Jason-1 Project to then begin a series of maneuvers to place Jason-1 into a neworbit as defined in table 1 After checking the current orbit carefully the operational team determined thata geodetic mission was still possible It was also decided to preserve all remaining fuel for future stationkeeping maneuvers which is mandatory in a geodetic orbit Core payloads were switched ON on May 4thand after some POSEIDON2 radar (PRF) adjustments the mission was resumed on May 7th at 151248UTCBelow are the characteristics of the new orbit which will be maintained as before within +- 1km controlbox at the Equator
Semi major axis 7702437 kmEccentricity 13 to 28 10-4Altitude equator 13240 kmOrbital period 6730s (1h52rsquo10rdquo)Inclination 66042˚Cycle 406 daysSub cycles 39 - 109 - 475 - 1795
days
Table 1 Characteristics of the geodetic orbit for Jason-1 since May 7th 2012
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For this new phase of the Jason-1 mission (called j1g) the cycle numbering will restart at 500 Off-lineproducts will be produced once a day for the IGDR and every 11 days for the GDRrsquos The integration ofJason-1 data in the DUACS system is available since May 25th 2012
II3 Envisat has stopped sending data (April 2012)
Since April 8th 2012 Envisat has stopped sending data to Earth Esarsquos mission control has worked tore-establish contact with the satellite but there has been no reaction from the satellite Thus Esa has de-clared officially the end of mission for Envisat (see httpwwwesaintesaCPSEM1SXSWT1H_index_0html) Therefore no SL TAC NRT data from Envisat can be released since this date
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II4 Integration of the Cryosat2 Mission (February 2012)
Since February 6th 2012 Cryosat-2 mission has been integrated in the DUACS sytem This mission isdedicated to the observation of the floating sea-ice as well as the continental ice sheets but all data acquiredover ocean are valuable for the observation of oceanic circulation and mesoscale variations This majorchange is the result of the long-standing and fruitful partnership between ESA and CNES and a responseto the request from scientific and operational oceanography users [7] The integration of Cryosat-2 impactsthe delivering of Near real time Sea Level Anomalies (SLA)
II41 Generalities about the mission
A Cryosat-2 Processing Prototype (C2P) (described in Boy et al 2011 [2]) has been developed on CNESside to lay the ground for various SAR processing studies The processing chains ingest Level-0 telemetryfiles distributed by ESA and perform the following steps to generate Sea Level Anomalies (SLA) values foreach altimeter measurements
bull Level-1 Decommutation time-tagging and localization of measurements
bull Level-1b Calculation of instrumental corrections and geophysicalmeteorological corrections
bull Level-2 MLE4 waveforms Retracking and calculation of SLA
The prototype processes data almost continuously over ocean either in Low Resolution Mode (LRM) or inthe DopplerSAR mode processed as pseudo-LRM mode allowing to increase the coverage (figure 2)
Figure 2 SSH-MSS for Cryosat-2 with LRM mode only (left) or LRM+pseudo-LRM modes (right)
Although Cryosat-2 raw SSH can be only corrected with GPS-derived ionospheric correction and ECMWFwet troposphere correction validation activities showed (Labroue et al 2011 [25]) that C2P outputs have anaccuracy roughly equivalent to Envisatrsquos Level 2 products if the latter are processed with the same standards
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II42 Integration in DUACS
The Cryosat-2 data are included in the Near Real time process The chain delivers now (for global coverageMediterranean and Black Seas) along track data from Cryosat-2 (SLAs) Note that the products distributedare of Level-3 and donrsquot replace Level-2 products distributed by agenciesThe details of the processing are given in Dibarboure et al 2011 [8]Here we just give an overview the data are computed with the corrections given in section III21 Thefiltering and sub-sampling of SLAs (section III263) are detailed in [8]
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II5 Addition of Europe and Arctic products (January 2012)
Since the MyOcean V2 two new along-track products are computed in Near Real Time intended foraddressing the needs of data assmilation and validation in regional models
bull Following the TAPAS (Tailored Altimeter Product for Assimilation Systems) initiative launched bySL TAC with all the Modeling and Forecasting Centers (MFCs) the Europe regional products (PLSEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004) have been proposed (figure 3) They areavailable in Near Real Time onlyThey are studied to partly fulfil the needs of the Centers with adapted filtering and resolution Thoseparameters have been tuned in order to provide boundary conditions for the Atlantic assimilationmodels They are different from the ones used for Mediterranean and Black Seas products If you needto study the Mediterranean Sea or the Black Sea yoursquod better use the dedicated products describedabove since the processing parameters have been fitted to be adapted to the dynamics of the ocean inthose regions
Figure 3 Coverage of the Europe product for Jason-1 Jason-2 and Envisat from August 18th to September9th 2011
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bull The Arctic along-track products (PL SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005) coverlatitudes between 45 and 82 degrees (figure 4) They are available in Near Real Time only
Figure 4 Coverage of the Arctic region with Envisat from October 28th 2011 to January 3rd 2012
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III SSALTODUACS SYSTEM
III1 Introduction
This chapter presents the input data used by SSALTODUACS system and an overview of the different pro-cessing steps necessary to produce the output dataSSALTODUACS system is made of two components a Near Real Time one (NRT) and a Delayed Time(DT) oneIn NRT the systemrsquos primary objective is to provide operational applications with directly usable high qual-ity altimeter data from all missions availableIn DT it is to maintain a consistent and user-friendly altimeter database using the state-of-the-art recom-mendations from the altimetry communityFollowing figure gives an overview of DUACS system where processing sequences can be divided into 7main steps
bull acquisition
bull homogenization
bull input data quality control
bull multi-mission cross-calibration
bull product generation
bull merging
bull final quality control
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Figure 5 SSALTODUACS processing sequences
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III2 Near Real Time processing steps
III21 Input data models and corrections applied
To produce SLA in near-real time the DUACS system uses two flows based on the same instrumental mea-surements but with a different quality
bull The IGDR that are the latest high-quality altimeter data produced in near-real-time
bull The OGDR that includes real time data (OSTMJason-2 and Jason-1 OSDR) to complete IGDR Thesefast delivery products do not always benefit from precise orbit determination nor from some exter-nal model-based corrections (Dynamic Atmospheric Correction (DAC) Global Ionospheric Maps(GIM))
Integration of OGDR data and the introduction of Jason-2Jason-1 tandem increased the resilience and pre-cision of the system A better restitution of ocean variability is observed especially in high energetic areas
Altimetric product Source Availability Type of orbit
Jason-2 IGDR CNES ~24h CNES MOE GDR-Cuntil 20120730
CNES MOE GDR-Dsince 20120731
OGDR NOAAEUMETSAT ~3 to 5 h
Jason-1 IGDR CNESNASA ~48 h CNES MOE GDR-Dsince 20120507
OGDR CNESNASA ~3 to 12 h
Envisat IGDR ESACNES not deliveredsince 20120408
CNES MOE GDR-Dsince 20120121
FDGDR ESA not deliveredsince 20120408
Cryosat-2 IGDR-like ESACNES ~48 h CNES MOE GDR-D
not delivered
Table 2 SSALTODUACS Near-Real Time Input data overview
See Figure 6 Overview of the near real time system data flow management
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DUACS 2011 NRT product from IGDR1
j2 j1nj1g enn c2Productstandard ref
version C until20120730 and D after
version C version 21 CPP [2]
Orbit CNES MOE GDR-Cuntil 20120730
GDR-D after
CNES MOE GDR-C forj1n and CNES MOE
GDR-D for j1g
CNES MOE GDR-Dfrom 20120121 to
20120408
CNES MOE GDR-D
Ionopheric bi-frequency altimeter range measurements GIM model for cgt64 (Iijima et al1998[24])Dry tropo Model computed from ECMWF Gaussian grids (new S1 and S2 atm tides applied)Wet tropo-sphere
AMR radiometer(enhancement in coastal
regions since20120730)
JMR radiometer MWR radiometer andcorrected from side
lobes
Model computed fromECMWF Gaussian
grids
DAC MOG2D High Resolution forced with ECMWF pressure and wind fields (S1 and S2 wereexcluded) (Carrere and Lyard 2003[3])+ inverse barometer Filtering temporal window is
un-centered (no data in the future)Ocean tide GOT4v8 (S1 and S2 are included) and TPX 072 [16] for Arctic productsPole tide [Wahr 1985 [53]]Solid earthtide
Elastic response to tidal potential [Cartwright and Tayler 1971[5]] [Cartwright andEdden 1973[6]]
Loading tide GOT4v8 (S1 and S2 are included)Sea statebias
Non parametric SSB[Labroue 2004[27]](with cycles J1 1 to 11
using GDR-B standardsuntil 20120730 andderived from Jason-2
after)
Non parametric SSB[Labroue 2004[27]](with cycles 1 to 21
using GDR-Bstandards)
Non parametric SSB[Labroue 2004[27]](with cycles 41 to 60
using GDR-Bstandards)
Same as Jason-2 SSB
Orbit error Global multi-mission crossover minimization (Le Traon and Ogor1998[32])
Long wave-lengh errors
Optimal Interpolation [Le Traon et al 1998[31]]
Intercalibration Reference from cycle20
Mean pro-file (seeIII261)
Computed with cycles11-353 TP data andwith cycles 11-250J1 data referenced[19931999]
TPNJ1N computedwith cycles 369-479TPN data refer-enced [19931999]J1G No MP can beused instead theMSS_CNES_CLS11[39] is used
No Mean Profilecan be used forEnvisat on its neworbit Instead theMSS_CNES_CLS11[39] is used
No Mean Profilecan be used forCryosat-2 Instead theMSS_CNES_CLS11[39] is used
(1) A flag included in the along-track files indicates the source of the production (OGDRFDGDR orIGDR) If flag=0 the processed data comes from OGDRsFDGDRs if flag=1 the processed data comesfrom IGDRs
Table 3 Corrections and models applied in SSALTODUACS NRT products produced from IGDRs
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
DUACS 2011 NRT product from OGDR or FDGDR2
j2 j1nj1g ennProduct stan-dard ref
version C until 20120730and D after
version C version 21
Orbit Navigator Extrapolated CNES MOEGDR-D since 20120121
Ionopheric From-dual frequency altimeter range measurements From GIM model fromcycle 65 (Iijima et al1998 [24])
Dry troposphere Model computed from ECMWF Gaussian grids (new S1 and S2 atmospherictides are applied)
Wet tropo-sphere
AMR radiometer(enhancement in coastal
regions since 20120730)
JMR radiometer MWR radiometer andcorrected from side lobes
DAC Inverse Barometer forecastedOcean tide GOT4v8 (S1 and S2 are included) and TPX 072 [16] for Arctic productsPole tide [Wahr 1985 [53]]Solid earth tide Elastic response to tidal potential [Cartwright and Tayler 1971[5]]
[Cartwright and Edden 1973[6]]Loading tide GOT4v8 (S1 and S2 are included)Sea state bias Non parametric SSB
[Labroue 2004[27]] (withcycles J1 1 to 11 usingGDR-B standards until20120730 and derivedfrom Jason-2 after)
Non parametric SSB[Labroue 2004[27]](with cycles 1 to 21 usingGDR-B standards)
Non parametric SSB[Labroue 2004[27]](with cycles 41 to 60using GDR-B standards)
Orbit error Specific filtering of long-wavelength signal3
Long wave-lengh errors
Optimal Interpolation [Le Traon et al 1998[31]]
Intercalibration Reference from cycle 20Mean profile(see III261)
Computed with cycles 11-353 TP data and with cy-cles 11-250 J1 data refer-enced [19931999]
TPNJ1N computedwith cycles 369-479TPN data referenced[19931999] J1G NoMP can be used insteadthe MSS_CNES_CLS11[39] is used
No Mean Profile can beused for Envisat on itsnew orbit Instead theMSS_CNES_CLS11 [39]is used
(2) A flag included in the along-track files indicates the source of the production (OGDRFDGDR orIGDR) If flag=0 the processed data comes from OGDRsFDGDRs if flag=1 the processed data comesfrom IGDRs(3) Specific data processing was applied on long wave-length signal (sectIII23 of the user manual)
Table 4 Corrections and models applied in SSALTODUACS NRT products produced from OG-DRsFDGDRs
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III22 Acquisition
The acquisition process is twofold
bull straightforward retrieval and reformatting of altimeter data and dynamic auxiliary data (pressure andwet troposphere correction grids from ECMWF are provided by Meteo France TEC grids from JPLNRT MOG2D corrections) from external repositories
bull synchronisation process
To be homogenized properly altimeter data sets require various auxiliary data The acquisition softwaredetects downloads and processes incoming data as soon as they are available on remote sites (externaldatabase FTP site) Data are split into passes if necessary If data flows are missing or late the synchroni-sation engine put unusable data in waiting queues and automatically unfreezes them upon reception of themissing auxiliary data This processing step delivers raw data that is to say data that have been dividedinto cycles and passes and ordered chronologicallyFrom SSALTODUACS V80 the acquisition step uses two different data flows in near-real time the OGDRflow (within a few hours) and the IGDR flow (within a few days)For each OGDR input the system checks that no equivalent IGDR entry is available in the data base beforeacquisition for each IGDR input the system checks and delete the equivalent OGDR entry in the data baseThese operations aim to avoid duplicates in SSALTODUACS system
Figure 6 Overview of the near real time system data flow management
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III23 Homogenization
The Homogenization process consists in applying the most recent corrections models and references rec-ommended for altimeter products Each mission is processed separately as its needs depend on the baseinput data The list of corrections and models currently applied is provided in tables 3 and 4 for NRT dataThe system includes SLA filtering to process OGDR data DUACS extract from these data sets the shortscales (space and time) which are useful to better describe the ocean variability in real time and merge thisinformation with a fair description of large scale signals provided by the multi-satellite observation in nearreal time (read IGDR-based DUACS data) Finally an hybrid SLA is computed
Figure 7 Merging pertinent information from IGDR and OGDR processing
III24 Input data quality control
The Input Data Quality Control is a critical process applied to guarantee that DUACS uses only the mostaccurate altimeter data Thanks to the high quality of current missions this process rejects a small percent-age of altimeter measurements but these erroneous data could be the cause of a significant quality lossThe quality control relies on standard raw data editing with quality flags or parameter thresholds but alsoon complex data editing algorithms based on the detection of erroneous artefacts mono and multi-missioncrossover validation and macroscopic statistics to edit out large data flows that do not meet the systemrsquosrequirements
Page 26
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III25 Multi-mission cross-calibration
The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistentand accurate information It removes any residual orbit error (OE Le Traon and Ogor 1998[32]) or longwavelength error (LWE Le Traon et al 1998[31]) as well as large scale biases and discrepancies betweenvarious data flows
This process is based on two very different algorithms a global multi-mission crossover minimization fororbit error reduction (OER) and Optimal Interpolation (OI) for LWE
Multi-satellite crossover determination is performed on a daily basis All altimeter fields (measurementcorrections and other fields such as bathymetry MSS) are interpolated at crossover locations and datesCrossovers are then appended to the existing crossover database as more altimeter data become availableThis crossover data set is the input of the Orbit Error Reduction (OER) method Using the precision of thereference mission orbit a very accurate orbit error can be estimated This processing step does not concernOGDR dataLWE is mostly due to residual tidal or inverse barometer errors and high frequency ocean signals The OIused for LWE reduction uses precise parameters derived from
bull accurate statistical description of sea level variability
bull localized correlation scales
bull mission-specific noise and precise assumptions on the long wavelength errors to be removed (from arecent analysis of one year of data from each mission)
Page 27
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III26 Product generation
The product generation process is composed of four steps computation of raw SLA cross-validationfilteringampsub-sampling and generation of by-products
III261 Computation of raw SLA
Since the geoid is not well known yet the SSH cannot be used directly the SSH anomalies are used insteadThey are computed from the difference of the instantaneous SSH - a temporal reference This temporalreference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeattrack analysis cannot be used The errors affecting the SLAs MPs and MSS have different magnitudes andwavelengths The computation of the SLAs and their errors associated are detailed in Dibarboure et al 2010[9]
Use of a Mean ProfileIn the repeat track analysis (when the satellites flies over a repetitive orbit) measurements are re-sampledalong a theoretical ground track (or mean track) associated to each mission Then a Mean Profile (MP) issubtracted from the re-sampled data to obtain SLA The MP is a time average of similarly re-sampled dataover a long period
bull The Mean Profile used for Jason-2 is computed with 10 years of TP (cycles 11 to 353) and 6 years ofJason-1 (cycles 11 to 250)
bull The Mean Profile used from Jason-1 cycle 262 to 374 (where satellites are on interleaved ground-tracks) is computed with 3 years of TP (cycles 369 to 479)
bull No Mean Profile can be used for Envisat on its new orbit (enn) Jason-1 on its geodetic orbit (j1g) norfor Cryosat-2 mission (c2) because there is no repetitive track The MSS must be used instead (seebelow)
Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible
bull Indeed as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide precise cross-track projection andor interpolation schemes are required to avoid errors
bull The mesoscale variability error (which is lt35 cm for MP between 3 to 5 years and lt1cm for WLof 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a prioriknowledge from Sea Level maps derived from previous iterations or from other missions
bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
Page 28
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for Envisat since november 2010 and for Cryosat-2 mission (c2)because the satellite is not in a repetitive orbit phase The alternative is to use the MSS instead The griddedMSS is derived from along track MPs and data from geodetic phases Thus any error on the MP is alsocontained in the MSS There are essentially 4 types of additional errors on gridded MSS which are hard toquantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
Note that for the Arctic regional products the DTU10 MSS [1] is taken into account instead of the CLS01MSS Indeed the accuracy of DTU10 compared to CLS01 is further demonstrated by the significant sealevel anomaly variance reduction found over the whole Arctic Ocean as shown in Prandi et al [42]
III262 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III263 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
Page 29
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III27 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III271 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
Page 30
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III272 Performance indicators
To appreciate the quality situation of the DUACS system new performance indicators are computed dailyThey aim at evaluate the status of the main processing steps of the system the input data availability theinput data coverage the input data quality and the output product quality These indicators are computed foreach and every currently working satellite and combined to obtain the overall status
Figure 8 Example with the key performance indicator on 20090627
See the description the latest and previous indicators on Aviso websitehttpwwwavisooceanobscomindexphpid=1516
Page 31
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III3 Delayed Time processing steps
III31 Input data models and corrections applied
Delayed Time MyOcean products are generated
bull from Aviso GDR products for TP Jason-1 Jason-2 and Envisat (GDR-A cycles 1 to 22 GDR-Bcycles 23 to 85 GDR-C from cycle 86)
bull from NOAA GDR for GFO and from CERSAT (IFREMER) OPR for ERS-1 and ERS-2 (phases C(1st 35-day repeat orbit period) phase E and F (geodetic phases) phase G for ERS-1 (last 35-dayrepeat orbit period tandem phase with ERS-2 phase A for ERS-2 (1st 35-day repeat orbit periodtandem phase with ERS-1))
All GDR products are computed with a Precise Orbit Ephemeris (POE) and are delivered within 2 to 3months depending on the mission For several missions an updated orbit is used
bull For ERS-1amp-2 the orbit used is DGME-04 provided by Delft Institute (httpwwwdeostudelftnl)until June 2003
bull For TopexPoseidon the orbit used is GSFC (std0809) for the whole mission
bull For Envisat CNES POE of GDR-C standard is used for the whole mission
bull For the whole GFO mission the orbit used is GSFC (std0809) and when not available NASA POE isused
Altimetric product Source Availability Type of orbit
TopexPoseidon GDR NASACNES - GSFC POE
Jason-1 GDR (GDR-C) CNESNASA ~40 days CNES POE
Jason-2 GDR (GDR-C) CNESNASA ~60 days CNES POE
GFO GDR NOAA - GSFCNASA POE
ERS-1amp2 IFREMERESA - DGME-04
Envisat (GDR-A GDR-B andGDR-C from cycle 86)
ESA ~2 months CNES POE
Table 5 SSALTODUACS Delayed Time Input data overview
Page 32
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
DU
AC
S20
11D
Tpr
oduc
t(gtV
30
0)j2
j1j1
ntp
tpn
e1e2
ene
nng2
Prod
uct
stan
dard
ref
GD
R-C
OPR
GD
R-A
(Cyc
les
1to
22)
GD
R-B
(cyc
les
23-8
5)
GD
R(N
OA
A)
Orb
itC
nes
POE
GSF
C(I
TR
F20
05G
RA
CE
last
stan
dard
s)
DG
ME
-04
(Sch
arro
oan
dV
isse
r19
98[4
8]C
NE
SPO
E(G
DR
-1st
anda
rds
forc
ycle
s9
to22
GD
R-C
stan
dard
sfr
omcy
cle
23)
GSF
C(I
TR
F20
05
GR
AC
Ela
stst
anda
rds
Iono
pher
icD
ual f
requ
ency
altim
eter
rang
em
easu
rem
ents
Dua
l fre
quen
cyal
timet
erra
nge
mea
sure
men
ts(T
opex
)D
OR
IS(P
OSE
IDO
N)
Ben
t mod
elB
ent m
odel
(cyc
les
1-36
)G
IMm
odem
from
cycl
e37
((Ii
jima
etal
19
98[2
4])
Dua
l-fr
eque
ncy
altim
eter
rang
em
easu
rem
ent(
cycl
e9-
64)a
ndG
IMm
odel
gtcyc
le65
(Iiji
ma
etal
19
99[2
4])c
orre
cted
from
8m
mbi
as
From
GIM
mod
el(I
ijim
aet
al1
998
[24]
)
Dry
trop
o-sp
here
Mod
elco
mpu
ted
from
EC
MW
FG
auss
ian
grid
s(n
ewS1
and
S2at
mos
pher
ictid
esar
eap
plie
d)
Mod
elco
mpu
ted
from
EC
MW
Fre
ctan
gula
rgri
ds(n
ewS1
and
S2at
mos
pher
ictid
esar
ein
clud
ed)
Wet
trop
o-sp
here
JMR
AM
Rra
diom
eter
furt
hert
han
50km
from
the
coas
tsF
rom
EC
MW
Fm
odel
ford
ista
nces
betw
een
10an
d50
km
TM
Rra
diom
eter
(Sch
aroo
etal
20
04[4
9])
MW
RC
orre
ctio
nof
the
drif
ton
the
236
GH
zbr
ight
ness
tem
pera
ture
(Sch
arro
oet
al
2004
[49]
)Neu
ral
Net
wor
kal
gori
thm
(Tra
nan
dO
blig
is
2003
[50]
MW
Rra
diom
eter
furt
hert
han
50km
from
the
coas
tsan
dco
rrec
ted
from
side
lobe
s(f
rom
cycl
e41
)E
CM
WF
mod
elfo
rdis
tanc
esbe
twee
n10
and
50km
GFO
radi
omet
er
DA
CM
OG
2DH
igh
Res
olut
ion
forc
edw
ithE
CM
WF
pres
sure
and
win
gfie
lds
(S1
and
S2w
ere
excl
uded
)+in
vers
eba
rom
eter
com
pute
dfr
omre
ctan
gula
rgri
ds
Tabl
e6
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(1
2)
Page 33
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
j2j1
j1n
tptp
ne1
e2en
enn
g2O
cean
tide
GO
T4v
7(S
1an
dS2
are
incl
uded
)Po
letid
e[W
ahr
1985
[53]
]So
lidea
rth
tide
Ela
stic
resp
onse
totid
alpo
tent
ial[
Car
twri
ghta
ndTa
yler
197
1[5]
][C
artw
righ
tand
Edd
en1
973[
6]]
Loa
ding
tide
GO
T4v
7(S
1pa
ram
eter
isin
clud
ed)
Sea
stat
ebi
asN
onpa
ram
etri
cSS
B[G
aspa
reta
l20
02[2
0]]
Non
para
met
ric
SSB
[NT
ran
and
al2
010[
51]]
BM
3[G
aspa
ran
dO
gor
1994
[17]
]
Non
para
met
ric
SSB
[Mer
tzet
al
2005
[38]
]
Non
para
met
ric
SSB
[Gas
pare
tal
2002
]w
ithG
DR
-Bst
anda
rds
forc
ycle
s9
to85
and
with
GD
R-C
stan
dard
sfr
omcy
cle
86
Non
para
met
ric
SSB
[NT
ran
etal
20
10[5
1]]
Orb
iter
ror
Glo
bal m
ulti-
mis
sion
cros
sove
rmin
imiz
atio
n(L
eTr
aon
and
Ogo
r19
98[3
2])
Lon
gw
ave-
leng
her
rors
Opt
imal
Inte
rpol
atio
n(L
eTr
aon
etal
19
98[3
1])
Inte
rcal
ibra
tion
Ref
eren
cefr
omcy
cle
11R
efer
ence
from
cycl
e1
to35
4C
orre
ctio
nof
regi
onal
bias
J2J
1de
duce
dfr
omin
terc
alib
ratio
nph
ase
(cyc
le11
J2)
Cor
rect
ion
ofgl
obal
biai
sJ1
TP
deacutedu
ced
from
inte
rcal
ibra
tion
phas
e(c
ycle
s11
J1)
Mea
npr
o-fil
e(s
eeII
I36
1)
Com
pute
dw
ithcy
cles
11-3
53T
Pda
taan
dw
ithcy
cles
11-2
50J1
data
ref
eren
ced
[199
319
99]
TP
J1 c
ompu
ted
with
cycl
es11
-353
TP
data
and
with
cycl
es11
-250
J1da
tar
efer
ence
d[1
993
1999
]T
PNJ
1Nc
ompu
ted
with
cycl
es36
9-47
9T
PNda
tar
efer
ence
d[1
993
1999
]
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
ref
eren
ced
[199
319
99]
EN
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
re
fere
nced
[199
319
99]
EN
Nu
seof
MSS
_CN
ES_
CL
S11
[39]
Com
pute
dw
ithcy
cles
37-1
87G
2da
ta
refe
renc
ed[1
993
1999
]
Peri
odof
use
from
cycl
e9
from
cycl
e9
cycl
es1
to48
1cy
cles
15to
43In
clud
ing
E-F
geod
etic
phas
es
cycl
es1
to83
from
cycl
e9
cycl
es37
to22
2
Tabl
e7
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(2
2)
Page 34
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III32 Acquisition
The acqusition process in Delayed time is much simpler than in Near Real time it consists in a synchronisa-tion process of all the auxiliary data required to homogenize propely the altimeter data sets The acquisitionstep uses the GDRs or the OPRs provided by the agencies
III33 Homogenization
The Homogenization process consists in applying the most recent corrections models and references rec-ommended for altimeter products Each mission is processed separately as its needs depend on the baseinput data The list of corrections and models currently applied is provided in tables 6 and 7 for DT data
III34 Input data quality control
The Input Data Quality Control is a critical process applied to guarantee that DUACS uses only the mostaccurate altimeter data Thanks to the high quality of current missions this process rejects a small percent-age of altimeter measurements but these erroneous data could be the cause of a significant quality lossThe quality control relies on standard raw data editing with quality flags or parameter thresholds but alsoon complex data editing algorithms based on the detection of erroneous artefacts mono and multi-missioncrossover validation and macroscopic statistics to edit out large data flows that do not meet the systemrsquosrequirements
Page 35
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III35 Multi-mission cross-calibration
The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistentand accurate information It removes any residual orbit error (OE Le Traon and Ogor 1998[32]) or longwavelength error (LWE Le Traon et al 1998[31]) as well as large scale biases and discrepancies betweenvarious data flows
This process is based on two very different algorithms a global multi-mission crossover minimization fororbit error reduction (OER) and Optimal Interpolation (OI) for LWE
Multi-satellite crossover determination is performed on a daily basis All altimeter fields (measurementcorrections and other fields such as bathymetry MSS) are interpolated at crossover locations and datesCrossovers are then appended to the existing crossover database as more altimeter data become availableThis crossover data set is the input of the Orbit Error Reduction (OER) method Using the precision of thereference mission orbit a very accurate orbit error can be estimated LWE is mostly due to residual tidalor inverse barometer errors and high frequency ocean signals The OI used for LWE reduction uses preciseparameters derived from
bull accurate statistical description of sea level variability
bull localized correlation scales
bull mission-specific noise and precise assumptions on the long wavelength errors to be removed (from arecent analysis of one year of data from each mission)
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III36 Product generation
The product generation process is composed of four steps computation of raw SLA cross-validationfilteringampsub-sampling and generation of by-products
III361 Computation of raw SLA
Since the geoid is not well known yet the SSH cannot be used directly the SSH anomalies are used insteadThey are computed from the difference of the instantaneous SSH - a temporal reference This temporalreference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeattrack analysis cannot be used The errors affecting the SLAs MPs and MSS have different magnitudes andwavelengths The computation of the SLAs and their errors associated are detailed in Dibarboure et al 2010[9]
Use of a Mean ProfileIn the repeat track analysis (when the satellites flies over a repetitive orbit) measurements are re-sampledalong a theoretical ground track (or mean track) associated to each mission Then a Mean Profile (MP) issubtracted from the re-sampled data to obtain SLA The MP is a time average of similarly re-sampled dataover a long period
bull The Mean Profile used for TP (cycles 1 to 364) Jason-1 (cycles 1 to 259) and Jason-2 is computedwith 10 years of TP (cycles 11 to 353) and 6 years of Jason-1 (cycles 11 to 250)
bull The Mean Profile used for TP (cycles 368 to 481) and from Jason-1 cycle 262 to 374 (where satellitesare on interleaved ground-tracks) is computed with 3 years of TP (cycles 369 to 479)
bull The Mean Profile used for ERS-1 in its 35 days repetitive orbit mission ERS-2 and Envisat (only forthe first orbit before November 2010) is computed with 8 years of ERS-2 (cycles 1 to 85) and 6 yearsof Envisat (cycles 10 to 72)
bull No Mean Profile can be used for Envisat on its new orbit (enn) Jason-1 on its geodetic orbit (j1g)because there is no repetitive track The MSS must be used instead (see below)
bull The Mean Profile used for GFO is computed with 7 years of GFO cycles 37 to 187
Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible
bull Indeed as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide precise cross-track projection andor interpolation schemes are required to avoid errors
bull The mesoscale variability error (which is lt35 cm for MP between 3 to 5 years and lt1cm for WLof 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a prioriknowledge from Sea Level maps derived from previous iterations or from other missions
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bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for ERS-1 for its 168 days geodetic mission (phases E-F from April1994 to March 1995) or for Envisat since november 2010 because the satellite is not in a repetitive orbitphase The alternative is to use the MSS instead The gridded MSS is derived from along track MPs anddata from geodetic phases Thus any error on the MP is also contained in the MSS There are essentially 4types of additional errors on gridded MSS which are hard to quantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
III362 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III363 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
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III37 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III371 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
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IV MYOCEAN PRODUCTS
IV1 Near Real Time Products
The purpose of the NRT DUACS component is the acquisition of altimeter data from various altimeter mis-sions in near-real time (ie within a few days at most) the validation and correction of these altimeter datasets (ie edition and selection update of corrections and homogenization orbit error reduction) in order toproduce each day along-track productsProducts are as follows
Along-track products global and regional (Mediterranean and Black Seas Arctic Ocean and Europeareas)
bull Sea Level Anomaly (NRT-SLA) for each mission with NRT-SLA ephemeris
IV11 Delay of the products
The availability of the products in near real time is three to twelve hours after the measurement for along-track products Those products are delivered every day
IV12 Temporal availibility
The following table presents the available products by mission and by data periodNear real time products
NRT Jason-2 Jason-1 and Jason-1geodetic
Envisat new Cryosat-2
Temporal Time availability ymlowast
ongoingymlowast-20120303 for
repeat track and20120507-ongoing for
geodetic track
ymlowast
2012040820120101
ongoing
NRT-SLA X X X X
lowastym the temporal coverage for NRT products is fluctuating and depends on updates of Delayed Time prod-ucts When DT products are updated (3 to 4 times per year) the oldest NRT products are replaced by thebetter quality DT products so that the 2 series are overlapping on few weeks or few months
IV2 Delayed Time Products
The Delayed Time component of SSALTODUACS system is responsible for the production of processedJason-1 Jason-2 TP Envisat GFO ERS12 and even Geosat data in order to provide a homogeneousinter-calibrated and highly accurate long time series of SLA DT products are more precise than NRT products Two reasons explain this quality difference The firstone is the better intrinsic quality of the POE orbit used in the GDR processing The second reason is that
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in the DT DUACS processing the products can be computed optimally with a centred computation timewindow for OER LWE On the contrary in NRT case future data are not available so the computationtime window is not centred and therefore not optimalAs for NRT products improved altimeter corrections and processing algorithms are used ocean tide modelto correct altimeter data improved methods for orbit error reduction and mapping
Along-Track products global and regional (Mediterranean and Black Seas)
bull Sea Level Anomaly (DT-SLA) for each mission
IV21 Delay of the products
Weekly products are delivered The availability of the products in delayed time is at the best two monthsafter the date of the measurement The product generation needs all the GDR data of all the missions to takeinto account the best corrections as possible The time delay can be longer in the case of a missing mission
IV22 Temporal availibility
The following table presents the available products by mission and by data periodDelayed time SSALTODUACS products
Upd Jason-2 Jason-1new6
Jason-1 GFO Envisatnew6
Envisat ERS-16
ERS-2Topexnew6
Topex
TemporalTimeavailabil-ity
200810ymlowast
200902ymlowast
200204200810
200001200809
201010ymlowast
200210201010
199210200304
200209200510
199209200204
DT-SLA X X X X X X X X X
lowast ym those dates are updated regularly (3 to 4 times per year) and are avalaible when you download thedata at httpwwwmyoceaneuweb24-cataloguephp6 Jason-1 new orbit starting 200809 Envisat new orbit starting 201010 TP new orbit starting 200209 ERS-1The geodetic phases (E-F) are included There are no ERS-1 data between December 23 1993 and April 10 1994(ERS-1 phase D - 2nd ice phase) Note that during that time products are based only on TopexPoseidon data
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V DESCRIPTION OF THE PRODUCT SPECIFICATION
V1 General information
Product Specification SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001
Geographical coverage global
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 20-50km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001 Product Specification
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Product Specification SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002
Geographical coverage 55˚W-35˚E 30˚N-46˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002 Product Specification
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Product Specification SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003
Geographical coverage 27˚E-42˚E 40˚N-47˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003 Product Specification
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Product Specification SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004
Geographical coverage 25˚W-42˚E 21˚N-66˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004 Product Specification
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Product Specification SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005
Geographical coverage 0˚W-360˚E 50˚N-82˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005 Product Specification
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VI NOMENCLATURE OF FILES
VI1 Nomenclature of files downloaded through the MyOcean Web PortalDirectgetfile Service
VI11 Nomenclature of the product line
The description of the syntax for the SL TAC SLA products line is given by
SEALEVEL_ltREGIONgt_SLA_L3_ltDELAYgt_OBSERVATIONS_008_ltZONEgt_ltLETTERgtwhere
REGION GLO global geographic coverage product
BS Black Sea products
MED Mediterranean products
ARC Arctic products (for NRT products)
EUROPE Europe products (for NRT products)
DELAY NRT near real time products
RAN delayed time or reanalysis products
ZONE 001 number on 3 digits
002
003
004
LETTER a letter on 1 digit
b
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VI12 Nomenclature of the datasets
The nomenclature used is
dataset-duacs-ltdelaygt-ltzonegt-ltmissiongt-lttype of slagt-l3where the fileds in ltgt are described below
delay nrt near-real time productsran delayed time products
zone global global geographic coverage productmedsea Mediterranean productsblacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1 (only for ran)e2 ERS-2 (only for ran)tp TOPEXPoseidon (only for ran)tpn TOPEXPoseidon on its new orbit (only for
ran)g2 GFO (only for ran)j1 Jason-1 (only for ran)j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisat (only for ran)enn Envisat on its new orbitc2 Cryosat-2 (only for nrt)
type of sla sla filtered slasla_unfiltered non filtered sla (only for ran products)
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VI13 Nomenclature of the NetCdf files
The nomenclature used is
ltdelaygt_ltzonegt_ltmissiongt_sla_ltvariablegt_ltdatebegingt_ltdateendgt_ltdateprodgtnc where the fileds in ltgt are de-scribed below
delay nrt near-real time productsdt delayed time products
zone global global geographic coverage productmed Mediterranean products (for dt)mfstep Mediterranean products (for nrt)blacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1e2 ERS-2tp TOPEXPoseidontpn TOPEXPoseidon on its new orbitg2 GFOj1 Jason-1j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisatenn Envisat on its new orbitc2 Cryosat-2
variable vfec filtered and sub-sampled slavxxc non filtered and non sub-sampled sla (only
for dt)datebegin YYYYMMDD() beginning date of the datasetdateend YYYYMMDD() end date of the datasetdateprod YYYYMMDD production date of the dataset
() For dt data as the dates in the file names are rounded the user wanting data for date T has to read the filescontaining dates T+1 and T-1 in their name and check inside the files if there are some data for date T
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VII DATA FORMAT
This chapter presents the data storage format used for MyOcean products
VII1 NetCdf
The products are stored using the NetCDF format NetCDF (network Common Data Form) is an interface for array-oriented data access and a library that provides an implementation of the interface The netCDF library also definesa machine-independent format for representing scientific data Together the interface library and format support thecreation access and sharing of scientific data The netCDF software was developed at the Unidata Program Center inBoulder Colorado The netCDF libraries define a machine-independent format for representing scientific data Pleasesee Unidata NetCDF pages for more information and to retreive NetCDF software package onhttpwwwunidataucaredupackagesnetcdfindexhtml
NetCDF data is
bull Self-Describing A netCDF file includes information about the data it contains
bull Architecture-independent A netCDF file is represented in a form that can be accessed by computers with dif-ferent ways of storing integers characters and floating-point numbers
bull Direct-access A small subset of a large dataset may be accessed efficiently without first reading through allthe preceding data
bull Appendable Data can be appended to a netCDF dataset along one dimension without copying the dataset orredefining its structure The structure of a netCDF dataset can be changed though this sometimes causes thedataset to be copied
bull Sharable One writer and multiple readers may simultaneously access the same netCDF file
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VII2 Structure and semantic of NetCDF along-track files
The NetCDF Sea Level TAC files are based on the attribute data tags defined by the Cooperative OceanAtmosphereResearch Data Service (COARDS) and Climate and Forecast (CF) metadata conventions The CF convention gener-alises and extends the COARDS convention but relaxes the COARDS constraints on dimension and order and specifiesmethods for reducing the size of datasetsA wide range of software are available to write or read NetCDFCF files API are made available by UNIDATA(httpwwwunidataucaredusoftwarenetcdf)
bull CC++Fortran
bull Java
bull MATLAB Objective-C Perl Python R Ruby TclTk
In addition to these conventions the files are using a common structure and semantic
bull 1 dimension is defined
ndash time it is used to check NetCDF variables depending on time
bull 8 variables are defined
ndash short SLA contains the Sea Level Anomaly values for each time given
ndash int longitude contains the longitude for each measurement
ndash short track contains the track number for each measurement
ndash double time contains the time in days since 1950-01-01 000000 UTC for each measurement
ndash short mean_profile_point_index index of the corrsponding point in the track of the mean profile
ndash byte flag flag=0 the processed data comes from OGDR if flag=1 the processed data comes from theIGDR
ndash int latitude contains the latitude for each measurement
ndash short cycle contains the cycle number for each measurement
bull global attributes
ndash the global attributes gives information about the creation of the file
Example of a NetCDF sla file
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netcdf nrt_global_j1_sla_vfec_20101230_20101230_20101230 dimensions
time = 10385 variables
short SLA(time) SLAcoordinates = longitude latitude SLAlong_name = Sea Level Anomaly SLA_FillValue = 32767s SLAadd_offset = 0 SLAscale_factor = 0001 SLAunits = m SLAstandard_name = sea_surface_height_above_sea_level
int longitude(time) longitudelong_name = Longitude of measurement longitude_FillValue = 2147483647 longitudeadd_offset = 0 longitudestandard_name = longitude longitudescale_factor = 1e-06 longitudeunits = degrees_east
short track(time) tracklong_name = Track in cycle the measurement belongs to track_FillValue = 32767s trackunits = 1 trackcoordinates = longitude latitude
double time(time) timelong_name = Time of measurement time_FillValue = 184467440737096e+19 timeaxis = T timestandard_name = time timeunits = days since 1950-01-01 000000 UTC
int latitude(time) latitudelong_name = Latitude of measurement latitude_FillValue = 2147483647 latitudeadd_offset = 0 latitudestandard_name = latitude latitudescale_factor = 1e-06 latitudeunits = degrees_north
short flag(time) flagcoordinates = longitude latitude flag_FillValue = 3267s flaglong_name = data origin flagflag_values = 1s 0s flagflag_meanings = igdr_like non_igdr_like flagcomment = The origin of the data is determined by the types of geophysical datarecords (GDR) used in computation of the SLA 1 for the Interim GDR (IGDR) and0 for Operational GDR (OGDR)
short cycle(time) cyclelong_name = Cycle the measurement belongs to cycle_FillValue = 32767s cycleunits = 1 cyclecoordinates = longitude latitude
global attributeshistory = 22-Feb-2011 155243 CET File created by the SSLATODUACS system version 1001 comment = Produce from ENVISAT Extension Phase satellite altimetry data institution = CLSCNES
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references = httpwwwavisooceanobscomfileadmindocumentsdatatoolshdbk_duacspdf source = satellite altimetry title = along track Sea Level Anomaly Conventions = CF-14
dataSLA =
7 7 11 10 -2 -22 -39 -41 -30 -13 -3 -5 -16 -26 -32 -35-35 -35 -37 -35 -31 -29 -31 -35 -32 -21 -10 -10 -19 -20 -1-69 -57 -49 -45 -39 -30 -28 -31 -27 -13 -2 -5 -15 -3 1112 3 -7 -10 -14 -15 -22 -31 -37 -32 -17 -10
longitude =74743328 74868400 74993968 75120040 75246616 7537372875501368 75629568 75758320 75887656 76017568 76148080 7627920876388952 76477056 76565456 76654144 76743128 76832400 76921984329429568 329535424 329641792 329748672 329856096 329964032330072512 330181536 330291072 330401184
track =92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 9292 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92113 113 113 113 113 113 113 113 113 113 113 113 113 113113 113 113 113 113 113 113 113 113
time =222780000565705 222780001314719 222780002063733222780002812747 222780003561761 222780004310775 222780005059788222780005808802 222780006557816 22278000730683 222780008055844222780008804858 222780009553872 22278001017805 222780010677393222788257112198 222788257486705 222788257861212 222788258235719222788258610226 222788258984733 222788259359239 222788259733746222788260108253 22278826048276
mean_profile_point_index =1872 1878 1884 1890 1896 1902 1908 19141920 1926 1932 1938 1944 1949 1953 1957 1961 1965 1969 19732306 2309 2312 2315 2318 2321 2327 2330 2333 2336 2339 23422345 2348 2351 2354 2357 2360 2363 2366
flag =0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
latitude =-16225506 -16539731 -16853833 -17167810 -17481660 -17795380-18108966 -18422418 -18735729 -19048899 -19361924 -19674801-19987527 -20248015 -20456329 -20664569 -20872739 -2108083739481297 39628277 39775133 39921866 40068472 40214953 4036130840507533 40653629 40799592 40945423 41091120 41236684 41382111
cycle =331 331 331 331 331 331 331 331 331 331 331 331 331
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331 331 331 331 331 331 331 331 331 331 331 331 331 331331 331 331 331 331 331 331 331 331 331 331 331
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VIII HOW TO DOWNLOAD A PRODUCT
VIII1 Download a product through the MyOcean Web Portal DirectgetfileService
You first need to register Please find below the registration stepshttpwwwmyoceaneuweb34-products-and-services-faqphp1Once registered the MyOcean FAQ httpwwwmyoceaneuweb34-products-and-services-faqwill guide you on How to download a product through the MyOcean Web Portal Directgetfile Service
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IX NEWS AND UPDATES
IX1 [Duacs] Operational news
To be kept informed on events occurring on the satellites and on the eventual interruption of the services of the DUACSprocessing system see the [Duacs] operational news on the Aviso websitehttpwwwavisooceanobscomendataoperational-newsindexhtml
IX2 Updates
To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtmlSince 2010 a complete reprocessing of all altimetry data (cumulated total of about 55 years of data) is available Themain changes introduced in the Duacs DT v300 reprocessed data set in SSALTODUACS reprocessed DT data setare listed herehttpwwwavisooceanobscomfileadmindocumentsdataduacsduacs_DT_2010_reprocessing_impactpdf
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[49] Scharroo R J Lillibridge and WHF Smith 2004 Cross-calibration and long-term monitoring ofthe Microwave Radiometers of ERS Topex GFO Jason-1 and Envisat Marine Geodesy 97
[50] Tran N and E Obligis December 2003 Validation of the use of ENVISAT neural algorithms onERS-2 CLSDOSNT03901
[51] Tran N S Labroue S Philipps E Bronner and N Picot 2010 Overview and Update of the SeaState Bias Corrections for the Jason-2 Jason-1 and TOPEX Missions Marine Geodesy accepted
[52] Vincent P Desai SDDorandeu J Ablain M Soussi B Callahan PS and BJ Haines 2003 Jason-1 Geophysical Performance Evaluation Marine Geodesy 26 167-186
[53] Wahr J W 1985 Deformation of the Earth induced by polar motionJ of Geophys Res (Solid Earth)90 9363-9368
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I INTRODUCTION
MyOcean is a European Network project aiming at monitoring analyzing and forecasting the Ocean Ituses satellite and in-situ data to describe the ocean in 3 dimensions and real time More information can befound on httpwwwmyoceaneuorgThe aim of this document is to describe the products delivered by the Sea Level TAC (Thematic AssemblyCentre) which is one of the five TAC of the MyOcean projectThe data produced in the frame of this TAC are generated by the processing system named DUACS (DataUnification and Altimeter Combination System)DUACS is part of the CNES multi-mission ground segment (SSALTO) It processes data from all altimetermissions Cryosat-2 OSTMJason-2 Jason-1 TopexPoseidon Envisat GFO ERS-1amp2 and even GeosatAt this time (May 25th 2012) DUACS is using three different altimeters in near real time Developed and operated by CLS it started as an European Commission Project (Developing Use Of Altime-try for Climate Studies) funded under the European Commission and the Midi-Pyreacuteneacutees regional councilIt has been integrated to the CNES multi-mission ground segment SSALTO in 2001 and it is maintainedupgraded and operated with funding from CNES with shared costs from EU projectsAt the beginning of 2004 DUACS was redefined as the Data Unification Altimeter Combination System
Figure 1 DUACS and AVISO a user-driven altimetry service
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The products lines described in this user manual are the followingSEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005
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The data provided to users have a global coverage (PL SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001)and regional products are also computed over specific areasMediterranean Sea (PL SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002)and Black Sea (PL SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003)Thanks to updates in 2011 and 2012 (see section II) new regional products are now availableEurope (PL SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004)and Arctic (PL SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005)
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II UPDATES IN 2011 AND 2012
This section describes the updates of the SSALTODUACS Near Real Time system that occurred during2011 and 2012 allowing to add new products (Europe and Arctic) the integration of the Cryosat-2 data inthe system the stopping delivery of Envisat data the addition of Jason-1 data on geodetic orbit (j1g)To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtml
II1 Version D of input IGDROGDR Jason-2 data for NRT processing(July 30 2012)
On July 30 2012 the version of Jason-2 IGDROGDR has changed and is now the D version Somecorrections have thus been updated as detailed in tables 3 and 4
II2 Integration of Jason-1 on its geodetic orbit (May 2012)
An anomaly occured on March 3rd 2012 on the Jason-2 mission (see httpwwwavisooceanobscomfractualitesactualitesindexhtmltx_ttnews[tt_news]=1162amptx_ttnews[backPid]=1399ampcHash=d5baeb645e) On April 23rd CNES began to command the satellite into a nadir ori-entation and after some propulsion anomalies CNES and NASA management through the Joint SteeringGroup have directed the Jason-1 Project to then begin a series of maneuvers to place Jason-1 into a neworbit as defined in table 1 After checking the current orbit carefully the operational team determined thata geodetic mission was still possible It was also decided to preserve all remaining fuel for future stationkeeping maneuvers which is mandatory in a geodetic orbit Core payloads were switched ON on May 4thand after some POSEIDON2 radar (PRF) adjustments the mission was resumed on May 7th at 151248UTCBelow are the characteristics of the new orbit which will be maintained as before within +- 1km controlbox at the Equator
Semi major axis 7702437 kmEccentricity 13 to 28 10-4Altitude equator 13240 kmOrbital period 6730s (1h52rsquo10rdquo)Inclination 66042˚Cycle 406 daysSub cycles 39 - 109 - 475 - 1795
days
Table 1 Characteristics of the geodetic orbit for Jason-1 since May 7th 2012
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For this new phase of the Jason-1 mission (called j1g) the cycle numbering will restart at 500 Off-lineproducts will be produced once a day for the IGDR and every 11 days for the GDRrsquos The integration ofJason-1 data in the DUACS system is available since May 25th 2012
II3 Envisat has stopped sending data (April 2012)
Since April 8th 2012 Envisat has stopped sending data to Earth Esarsquos mission control has worked tore-establish contact with the satellite but there has been no reaction from the satellite Thus Esa has de-clared officially the end of mission for Envisat (see httpwwwesaintesaCPSEM1SXSWT1H_index_0html) Therefore no SL TAC NRT data from Envisat can be released since this date
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II4 Integration of the Cryosat2 Mission (February 2012)
Since February 6th 2012 Cryosat-2 mission has been integrated in the DUACS sytem This mission isdedicated to the observation of the floating sea-ice as well as the continental ice sheets but all data acquiredover ocean are valuable for the observation of oceanic circulation and mesoscale variations This majorchange is the result of the long-standing and fruitful partnership between ESA and CNES and a responseto the request from scientific and operational oceanography users [7] The integration of Cryosat-2 impactsthe delivering of Near real time Sea Level Anomalies (SLA)
II41 Generalities about the mission
A Cryosat-2 Processing Prototype (C2P) (described in Boy et al 2011 [2]) has been developed on CNESside to lay the ground for various SAR processing studies The processing chains ingest Level-0 telemetryfiles distributed by ESA and perform the following steps to generate Sea Level Anomalies (SLA) values foreach altimeter measurements
bull Level-1 Decommutation time-tagging and localization of measurements
bull Level-1b Calculation of instrumental corrections and geophysicalmeteorological corrections
bull Level-2 MLE4 waveforms Retracking and calculation of SLA
The prototype processes data almost continuously over ocean either in Low Resolution Mode (LRM) or inthe DopplerSAR mode processed as pseudo-LRM mode allowing to increase the coverage (figure 2)
Figure 2 SSH-MSS for Cryosat-2 with LRM mode only (left) or LRM+pseudo-LRM modes (right)
Although Cryosat-2 raw SSH can be only corrected with GPS-derived ionospheric correction and ECMWFwet troposphere correction validation activities showed (Labroue et al 2011 [25]) that C2P outputs have anaccuracy roughly equivalent to Envisatrsquos Level 2 products if the latter are processed with the same standards
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II42 Integration in DUACS
The Cryosat-2 data are included in the Near Real time process The chain delivers now (for global coverageMediterranean and Black Seas) along track data from Cryosat-2 (SLAs) Note that the products distributedare of Level-3 and donrsquot replace Level-2 products distributed by agenciesThe details of the processing are given in Dibarboure et al 2011 [8]Here we just give an overview the data are computed with the corrections given in section III21 Thefiltering and sub-sampling of SLAs (section III263) are detailed in [8]
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II5 Addition of Europe and Arctic products (January 2012)
Since the MyOcean V2 two new along-track products are computed in Near Real Time intended foraddressing the needs of data assmilation and validation in regional models
bull Following the TAPAS (Tailored Altimeter Product for Assimilation Systems) initiative launched bySL TAC with all the Modeling and Forecasting Centers (MFCs) the Europe regional products (PLSEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004) have been proposed (figure 3) They areavailable in Near Real Time onlyThey are studied to partly fulfil the needs of the Centers with adapted filtering and resolution Thoseparameters have been tuned in order to provide boundary conditions for the Atlantic assimilationmodels They are different from the ones used for Mediterranean and Black Seas products If you needto study the Mediterranean Sea or the Black Sea yoursquod better use the dedicated products describedabove since the processing parameters have been fitted to be adapted to the dynamics of the ocean inthose regions
Figure 3 Coverage of the Europe product for Jason-1 Jason-2 and Envisat from August 18th to September9th 2011
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bull The Arctic along-track products (PL SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005) coverlatitudes between 45 and 82 degrees (figure 4) They are available in Near Real Time only
Figure 4 Coverage of the Arctic region with Envisat from October 28th 2011 to January 3rd 2012
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III SSALTODUACS SYSTEM
III1 Introduction
This chapter presents the input data used by SSALTODUACS system and an overview of the different pro-cessing steps necessary to produce the output dataSSALTODUACS system is made of two components a Near Real Time one (NRT) and a Delayed Time(DT) oneIn NRT the systemrsquos primary objective is to provide operational applications with directly usable high qual-ity altimeter data from all missions availableIn DT it is to maintain a consistent and user-friendly altimeter database using the state-of-the-art recom-mendations from the altimetry communityFollowing figure gives an overview of DUACS system where processing sequences can be divided into 7main steps
bull acquisition
bull homogenization
bull input data quality control
bull multi-mission cross-calibration
bull product generation
bull merging
bull final quality control
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Figure 5 SSALTODUACS processing sequences
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III2 Near Real Time processing steps
III21 Input data models and corrections applied
To produce SLA in near-real time the DUACS system uses two flows based on the same instrumental mea-surements but with a different quality
bull The IGDR that are the latest high-quality altimeter data produced in near-real-time
bull The OGDR that includes real time data (OSTMJason-2 and Jason-1 OSDR) to complete IGDR Thesefast delivery products do not always benefit from precise orbit determination nor from some exter-nal model-based corrections (Dynamic Atmospheric Correction (DAC) Global Ionospheric Maps(GIM))
Integration of OGDR data and the introduction of Jason-2Jason-1 tandem increased the resilience and pre-cision of the system A better restitution of ocean variability is observed especially in high energetic areas
Altimetric product Source Availability Type of orbit
Jason-2 IGDR CNES ~24h CNES MOE GDR-Cuntil 20120730
CNES MOE GDR-Dsince 20120731
OGDR NOAAEUMETSAT ~3 to 5 h
Jason-1 IGDR CNESNASA ~48 h CNES MOE GDR-Dsince 20120507
OGDR CNESNASA ~3 to 12 h
Envisat IGDR ESACNES not deliveredsince 20120408
CNES MOE GDR-Dsince 20120121
FDGDR ESA not deliveredsince 20120408
Cryosat-2 IGDR-like ESACNES ~48 h CNES MOE GDR-D
not delivered
Table 2 SSALTODUACS Near-Real Time Input data overview
See Figure 6 Overview of the near real time system data flow management
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DUACS 2011 NRT product from IGDR1
j2 j1nj1g enn c2Productstandard ref
version C until20120730 and D after
version C version 21 CPP [2]
Orbit CNES MOE GDR-Cuntil 20120730
GDR-D after
CNES MOE GDR-C forj1n and CNES MOE
GDR-D for j1g
CNES MOE GDR-Dfrom 20120121 to
20120408
CNES MOE GDR-D
Ionopheric bi-frequency altimeter range measurements GIM model for cgt64 (Iijima et al1998[24])Dry tropo Model computed from ECMWF Gaussian grids (new S1 and S2 atm tides applied)Wet tropo-sphere
AMR radiometer(enhancement in coastal
regions since20120730)
JMR radiometer MWR radiometer andcorrected from side
lobes
Model computed fromECMWF Gaussian
grids
DAC MOG2D High Resolution forced with ECMWF pressure and wind fields (S1 and S2 wereexcluded) (Carrere and Lyard 2003[3])+ inverse barometer Filtering temporal window is
un-centered (no data in the future)Ocean tide GOT4v8 (S1 and S2 are included) and TPX 072 [16] for Arctic productsPole tide [Wahr 1985 [53]]Solid earthtide
Elastic response to tidal potential [Cartwright and Tayler 1971[5]] [Cartwright andEdden 1973[6]]
Loading tide GOT4v8 (S1 and S2 are included)Sea statebias
Non parametric SSB[Labroue 2004[27]](with cycles J1 1 to 11
using GDR-B standardsuntil 20120730 andderived from Jason-2
after)
Non parametric SSB[Labroue 2004[27]](with cycles 1 to 21
using GDR-Bstandards)
Non parametric SSB[Labroue 2004[27]](with cycles 41 to 60
using GDR-Bstandards)
Same as Jason-2 SSB
Orbit error Global multi-mission crossover minimization (Le Traon and Ogor1998[32])
Long wave-lengh errors
Optimal Interpolation [Le Traon et al 1998[31]]
Intercalibration Reference from cycle20
Mean pro-file (seeIII261)
Computed with cycles11-353 TP data andwith cycles 11-250J1 data referenced[19931999]
TPNJ1N computedwith cycles 369-479TPN data refer-enced [19931999]J1G No MP can beused instead theMSS_CNES_CLS11[39] is used
No Mean Profilecan be used forEnvisat on its neworbit Instead theMSS_CNES_CLS11[39] is used
No Mean Profilecan be used forCryosat-2 Instead theMSS_CNES_CLS11[39] is used
(1) A flag included in the along-track files indicates the source of the production (OGDRFDGDR orIGDR) If flag=0 the processed data comes from OGDRsFDGDRs if flag=1 the processed data comesfrom IGDRs
Table 3 Corrections and models applied in SSALTODUACS NRT products produced from IGDRs
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DUACS 2011 NRT product from OGDR or FDGDR2
j2 j1nj1g ennProduct stan-dard ref
version C until 20120730and D after
version C version 21
Orbit Navigator Extrapolated CNES MOEGDR-D since 20120121
Ionopheric From-dual frequency altimeter range measurements From GIM model fromcycle 65 (Iijima et al1998 [24])
Dry troposphere Model computed from ECMWF Gaussian grids (new S1 and S2 atmospherictides are applied)
Wet tropo-sphere
AMR radiometer(enhancement in coastal
regions since 20120730)
JMR radiometer MWR radiometer andcorrected from side lobes
DAC Inverse Barometer forecastedOcean tide GOT4v8 (S1 and S2 are included) and TPX 072 [16] for Arctic productsPole tide [Wahr 1985 [53]]Solid earth tide Elastic response to tidal potential [Cartwright and Tayler 1971[5]]
[Cartwright and Edden 1973[6]]Loading tide GOT4v8 (S1 and S2 are included)Sea state bias Non parametric SSB
[Labroue 2004[27]] (withcycles J1 1 to 11 usingGDR-B standards until20120730 and derivedfrom Jason-2 after)
Non parametric SSB[Labroue 2004[27]](with cycles 1 to 21 usingGDR-B standards)
Non parametric SSB[Labroue 2004[27]](with cycles 41 to 60using GDR-B standards)
Orbit error Specific filtering of long-wavelength signal3
Long wave-lengh errors
Optimal Interpolation [Le Traon et al 1998[31]]
Intercalibration Reference from cycle 20Mean profile(see III261)
Computed with cycles 11-353 TP data and with cy-cles 11-250 J1 data refer-enced [19931999]
TPNJ1N computedwith cycles 369-479TPN data referenced[19931999] J1G NoMP can be used insteadthe MSS_CNES_CLS11[39] is used
No Mean Profile can beused for Envisat on itsnew orbit Instead theMSS_CNES_CLS11 [39]is used
(2) A flag included in the along-track files indicates the source of the production (OGDRFDGDR orIGDR) If flag=0 the processed data comes from OGDRsFDGDRs if flag=1 the processed data comesfrom IGDRs(3) Specific data processing was applied on long wave-length signal (sectIII23 of the user manual)
Table 4 Corrections and models applied in SSALTODUACS NRT products produced from OG-DRsFDGDRs
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III22 Acquisition
The acquisition process is twofold
bull straightforward retrieval and reformatting of altimeter data and dynamic auxiliary data (pressure andwet troposphere correction grids from ECMWF are provided by Meteo France TEC grids from JPLNRT MOG2D corrections) from external repositories
bull synchronisation process
To be homogenized properly altimeter data sets require various auxiliary data The acquisition softwaredetects downloads and processes incoming data as soon as they are available on remote sites (externaldatabase FTP site) Data are split into passes if necessary If data flows are missing or late the synchroni-sation engine put unusable data in waiting queues and automatically unfreezes them upon reception of themissing auxiliary data This processing step delivers raw data that is to say data that have been dividedinto cycles and passes and ordered chronologicallyFrom SSALTODUACS V80 the acquisition step uses two different data flows in near-real time the OGDRflow (within a few hours) and the IGDR flow (within a few days)For each OGDR input the system checks that no equivalent IGDR entry is available in the data base beforeacquisition for each IGDR input the system checks and delete the equivalent OGDR entry in the data baseThese operations aim to avoid duplicates in SSALTODUACS system
Figure 6 Overview of the near real time system data flow management
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III23 Homogenization
The Homogenization process consists in applying the most recent corrections models and references rec-ommended for altimeter products Each mission is processed separately as its needs depend on the baseinput data The list of corrections and models currently applied is provided in tables 3 and 4 for NRT dataThe system includes SLA filtering to process OGDR data DUACS extract from these data sets the shortscales (space and time) which are useful to better describe the ocean variability in real time and merge thisinformation with a fair description of large scale signals provided by the multi-satellite observation in nearreal time (read IGDR-based DUACS data) Finally an hybrid SLA is computed
Figure 7 Merging pertinent information from IGDR and OGDR processing
III24 Input data quality control
The Input Data Quality Control is a critical process applied to guarantee that DUACS uses only the mostaccurate altimeter data Thanks to the high quality of current missions this process rejects a small percent-age of altimeter measurements but these erroneous data could be the cause of a significant quality lossThe quality control relies on standard raw data editing with quality flags or parameter thresholds but alsoon complex data editing algorithms based on the detection of erroneous artefacts mono and multi-missioncrossover validation and macroscopic statistics to edit out large data flows that do not meet the systemrsquosrequirements
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III25 Multi-mission cross-calibration
The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistentand accurate information It removes any residual orbit error (OE Le Traon and Ogor 1998[32]) or longwavelength error (LWE Le Traon et al 1998[31]) as well as large scale biases and discrepancies betweenvarious data flows
This process is based on two very different algorithms a global multi-mission crossover minimization fororbit error reduction (OER) and Optimal Interpolation (OI) for LWE
Multi-satellite crossover determination is performed on a daily basis All altimeter fields (measurementcorrections and other fields such as bathymetry MSS) are interpolated at crossover locations and datesCrossovers are then appended to the existing crossover database as more altimeter data become availableThis crossover data set is the input of the Orbit Error Reduction (OER) method Using the precision of thereference mission orbit a very accurate orbit error can be estimated This processing step does not concernOGDR dataLWE is mostly due to residual tidal or inverse barometer errors and high frequency ocean signals The OIused for LWE reduction uses precise parameters derived from
bull accurate statistical description of sea level variability
bull localized correlation scales
bull mission-specific noise and precise assumptions on the long wavelength errors to be removed (from arecent analysis of one year of data from each mission)
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III26 Product generation
The product generation process is composed of four steps computation of raw SLA cross-validationfilteringampsub-sampling and generation of by-products
III261 Computation of raw SLA
Since the geoid is not well known yet the SSH cannot be used directly the SSH anomalies are used insteadThey are computed from the difference of the instantaneous SSH - a temporal reference This temporalreference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeattrack analysis cannot be used The errors affecting the SLAs MPs and MSS have different magnitudes andwavelengths The computation of the SLAs and their errors associated are detailed in Dibarboure et al 2010[9]
Use of a Mean ProfileIn the repeat track analysis (when the satellites flies over a repetitive orbit) measurements are re-sampledalong a theoretical ground track (or mean track) associated to each mission Then a Mean Profile (MP) issubtracted from the re-sampled data to obtain SLA The MP is a time average of similarly re-sampled dataover a long period
bull The Mean Profile used for Jason-2 is computed with 10 years of TP (cycles 11 to 353) and 6 years ofJason-1 (cycles 11 to 250)
bull The Mean Profile used from Jason-1 cycle 262 to 374 (where satellites are on interleaved ground-tracks) is computed with 3 years of TP (cycles 369 to 479)
bull No Mean Profile can be used for Envisat on its new orbit (enn) Jason-1 on its geodetic orbit (j1g) norfor Cryosat-2 mission (c2) because there is no repetitive track The MSS must be used instead (seebelow)
Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible
bull Indeed as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide precise cross-track projection andor interpolation schemes are required to avoid errors
bull The mesoscale variability error (which is lt35 cm for MP between 3 to 5 years and lt1cm for WLof 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a prioriknowledge from Sea Level maps derived from previous iterations or from other missions
bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
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bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for Envisat since november 2010 and for Cryosat-2 mission (c2)because the satellite is not in a repetitive orbit phase The alternative is to use the MSS instead The griddedMSS is derived from along track MPs and data from geodetic phases Thus any error on the MP is alsocontained in the MSS There are essentially 4 types of additional errors on gridded MSS which are hard toquantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
Note that for the Arctic regional products the DTU10 MSS [1] is taken into account instead of the CLS01MSS Indeed the accuracy of DTU10 compared to CLS01 is further demonstrated by the significant sealevel anomaly variance reduction found over the whole Arctic Ocean as shown in Prandi et al [42]
III262 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III263 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
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III27 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III271 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
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III272 Performance indicators
To appreciate the quality situation of the DUACS system new performance indicators are computed dailyThey aim at evaluate the status of the main processing steps of the system the input data availability theinput data coverage the input data quality and the output product quality These indicators are computed foreach and every currently working satellite and combined to obtain the overall status
Figure 8 Example with the key performance indicator on 20090627
See the description the latest and previous indicators on Aviso websitehttpwwwavisooceanobscomindexphpid=1516
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III3 Delayed Time processing steps
III31 Input data models and corrections applied
Delayed Time MyOcean products are generated
bull from Aviso GDR products for TP Jason-1 Jason-2 and Envisat (GDR-A cycles 1 to 22 GDR-Bcycles 23 to 85 GDR-C from cycle 86)
bull from NOAA GDR for GFO and from CERSAT (IFREMER) OPR for ERS-1 and ERS-2 (phases C(1st 35-day repeat orbit period) phase E and F (geodetic phases) phase G for ERS-1 (last 35-dayrepeat orbit period tandem phase with ERS-2 phase A for ERS-2 (1st 35-day repeat orbit periodtandem phase with ERS-1))
All GDR products are computed with a Precise Orbit Ephemeris (POE) and are delivered within 2 to 3months depending on the mission For several missions an updated orbit is used
bull For ERS-1amp-2 the orbit used is DGME-04 provided by Delft Institute (httpwwwdeostudelftnl)until June 2003
bull For TopexPoseidon the orbit used is GSFC (std0809) for the whole mission
bull For Envisat CNES POE of GDR-C standard is used for the whole mission
bull For the whole GFO mission the orbit used is GSFC (std0809) and when not available NASA POE isused
Altimetric product Source Availability Type of orbit
TopexPoseidon GDR NASACNES - GSFC POE
Jason-1 GDR (GDR-C) CNESNASA ~40 days CNES POE
Jason-2 GDR (GDR-C) CNESNASA ~60 days CNES POE
GFO GDR NOAA - GSFCNASA POE
ERS-1amp2 IFREMERESA - DGME-04
Envisat (GDR-A GDR-B andGDR-C from cycle 86)
ESA ~2 months CNES POE
Table 5 SSALTODUACS Delayed Time Input data overview
Page 32
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
DU
AC
S20
11D
Tpr
oduc
t(gtV
30
0)j2
j1j1
ntp
tpn
e1e2
ene
nng2
Prod
uct
stan
dard
ref
GD
R-C
OPR
GD
R-A
(Cyc
les
1to
22)
GD
R-B
(cyc
les
23-8
5)
GD
R(N
OA
A)
Orb
itC
nes
POE
GSF
C(I
TR
F20
05G
RA
CE
last
stan
dard
s)
DG
ME
-04
(Sch
arro
oan
dV
isse
r19
98[4
8]C
NE
SPO
E(G
DR
-1st
anda
rds
forc
ycle
s9
to22
GD
R-C
stan
dard
sfr
omcy
cle
23)
GSF
C(I
TR
F20
05
GR
AC
Ela
stst
anda
rds
Iono
pher
icD
ual f
requ
ency
altim
eter
rang
em
easu
rem
ents
Dua
l fre
quen
cyal
timet
erra
nge
mea
sure
men
ts(T
opex
)D
OR
IS(P
OSE
IDO
N)
Ben
t mod
elB
ent m
odel
(cyc
les
1-36
)G
IMm
odem
from
cycl
e37
((Ii
jima
etal
19
98[2
4])
Dua
l-fr
eque
ncy
altim
eter
rang
em
easu
rem
ent(
cycl
e9-
64)a
ndG
IMm
odel
gtcyc
le65
(Iiji
ma
etal
19
99[2
4])c
orre
cted
from
8m
mbi
as
From
GIM
mod
el(I
ijim
aet
al1
998
[24]
)
Dry
trop
o-sp
here
Mod
elco
mpu
ted
from
EC
MW
FG
auss
ian
grid
s(n
ewS1
and
S2at
mos
pher
ictid
esar
eap
plie
d)
Mod
elco
mpu
ted
from
EC
MW
Fre
ctan
gula
rgri
ds(n
ewS1
and
S2at
mos
pher
ictid
esar
ein
clud
ed)
Wet
trop
o-sp
here
JMR
AM
Rra
diom
eter
furt
hert
han
50km
from
the
coas
tsF
rom
EC
MW
Fm
odel
ford
ista
nces
betw
een
10an
d50
km
TM
Rra
diom
eter
(Sch
aroo
etal
20
04[4
9])
MW
RC
orre
ctio
nof
the
drif
ton
the
236
GH
zbr
ight
ness
tem
pera
ture
(Sch
arro
oet
al
2004
[49]
)Neu
ral
Net
wor
kal
gori
thm
(Tra
nan
dO
blig
is
2003
[50]
MW
Rra
diom
eter
furt
hert
han
50km
from
the
coas
tsan
dco
rrec
ted
from
side
lobe
s(f
rom
cycl
e41
)E
CM
WF
mod
elfo
rdis
tanc
esbe
twee
n10
and
50km
GFO
radi
omet
er
DA
CM
OG
2DH
igh
Res
olut
ion
forc
edw
ithE
CM
WF
pres
sure
and
win
gfie
lds
(S1
and
S2w
ere
excl
uded
)+in
vers
eba
rom
eter
com
pute
dfr
omre
ctan
gula
rgri
ds
Tabl
e6
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(1
2)
Page 33
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
j2j1
j1n
tptp
ne1
e2en
enn
g2O
cean
tide
GO
T4v
7(S
1an
dS2
are
incl
uded
)Po
letid
e[W
ahr
1985
[53]
]So
lidea
rth
tide
Ela
stic
resp
onse
totid
alpo
tent
ial[
Car
twri
ghta
ndTa
yler
197
1[5]
][C
artw
righ
tand
Edd
en1
973[
6]]
Loa
ding
tide
GO
T4v
7(S
1pa
ram
eter
isin
clud
ed)
Sea
stat
ebi
asN
onpa
ram
etri
cSS
B[G
aspa
reta
l20
02[2
0]]
Non
para
met
ric
SSB
[NT
ran
and
al2
010[
51]]
BM
3[G
aspa
ran
dO
gor
1994
[17]
]
Non
para
met
ric
SSB
[Mer
tzet
al
2005
[38]
]
Non
para
met
ric
SSB
[Gas
pare
tal
2002
]w
ithG
DR
-Bst
anda
rds
forc
ycle
s9
to85
and
with
GD
R-C
stan
dard
sfr
omcy
cle
86
Non
para
met
ric
SSB
[NT
ran
etal
20
10[5
1]]
Orb
iter
ror
Glo
bal m
ulti-
mis
sion
cros
sove
rmin
imiz
atio
n(L
eTr
aon
and
Ogo
r19
98[3
2])
Lon
gw
ave-
leng
her
rors
Opt
imal
Inte
rpol
atio
n(L
eTr
aon
etal
19
98[3
1])
Inte
rcal
ibra
tion
Ref
eren
cefr
omcy
cle
11R
efer
ence
from
cycl
e1
to35
4C
orre
ctio
nof
regi
onal
bias
J2J
1de
duce
dfr
omin
terc
alib
ratio
nph
ase
(cyc
le11
J2)
Cor
rect
ion
ofgl
obal
biai
sJ1
TP
deacutedu
ced
from
inte
rcal
ibra
tion
phas
e(c
ycle
s11
J1)
Mea
npr
o-fil
e(s
eeII
I36
1)
Com
pute
dw
ithcy
cles
11-3
53T
Pda
taan
dw
ithcy
cles
11-2
50J1
data
ref
eren
ced
[199
319
99]
TP
J1 c
ompu
ted
with
cycl
es11
-353
TP
data
and
with
cycl
es11
-250
J1da
tar
efer
ence
d[1
993
1999
]T
PNJ
1Nc
ompu
ted
with
cycl
es36
9-47
9T
PNda
tar
efer
ence
d[1
993
1999
]
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
ref
eren
ced
[199
319
99]
EN
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
re
fere
nced
[199
319
99]
EN
Nu
seof
MSS
_CN
ES_
CL
S11
[39]
Com
pute
dw
ithcy
cles
37-1
87G
2da
ta
refe
renc
ed[1
993
1999
]
Peri
odof
use
from
cycl
e9
from
cycl
e9
cycl
es1
to48
1cy
cles
15to
43In
clud
ing
E-F
geod
etic
phas
es
cycl
es1
to83
from
cycl
e9
cycl
es37
to22
2
Tabl
e7
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(2
2)
Page 34
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III32 Acquisition
The acqusition process in Delayed time is much simpler than in Near Real time it consists in a synchronisa-tion process of all the auxiliary data required to homogenize propely the altimeter data sets The acquisitionstep uses the GDRs or the OPRs provided by the agencies
III33 Homogenization
The Homogenization process consists in applying the most recent corrections models and references rec-ommended for altimeter products Each mission is processed separately as its needs depend on the baseinput data The list of corrections and models currently applied is provided in tables 6 and 7 for DT data
III34 Input data quality control
The Input Data Quality Control is a critical process applied to guarantee that DUACS uses only the mostaccurate altimeter data Thanks to the high quality of current missions this process rejects a small percent-age of altimeter measurements but these erroneous data could be the cause of a significant quality lossThe quality control relies on standard raw data editing with quality flags or parameter thresholds but alsoon complex data editing algorithms based on the detection of erroneous artefacts mono and multi-missioncrossover validation and macroscopic statistics to edit out large data flows that do not meet the systemrsquosrequirements
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PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III35 Multi-mission cross-calibration
The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistentand accurate information It removes any residual orbit error (OE Le Traon and Ogor 1998[32]) or longwavelength error (LWE Le Traon et al 1998[31]) as well as large scale biases and discrepancies betweenvarious data flows
This process is based on two very different algorithms a global multi-mission crossover minimization fororbit error reduction (OER) and Optimal Interpolation (OI) for LWE
Multi-satellite crossover determination is performed on a daily basis All altimeter fields (measurementcorrections and other fields such as bathymetry MSS) are interpolated at crossover locations and datesCrossovers are then appended to the existing crossover database as more altimeter data become availableThis crossover data set is the input of the Orbit Error Reduction (OER) method Using the precision of thereference mission orbit a very accurate orbit error can be estimated LWE is mostly due to residual tidalor inverse barometer errors and high frequency ocean signals The OI used for LWE reduction uses preciseparameters derived from
bull accurate statistical description of sea level variability
bull localized correlation scales
bull mission-specific noise and precise assumptions on the long wavelength errors to be removed (from arecent analysis of one year of data from each mission)
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III36 Product generation
The product generation process is composed of four steps computation of raw SLA cross-validationfilteringampsub-sampling and generation of by-products
III361 Computation of raw SLA
Since the geoid is not well known yet the SSH cannot be used directly the SSH anomalies are used insteadThey are computed from the difference of the instantaneous SSH - a temporal reference This temporalreference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeattrack analysis cannot be used The errors affecting the SLAs MPs and MSS have different magnitudes andwavelengths The computation of the SLAs and their errors associated are detailed in Dibarboure et al 2010[9]
Use of a Mean ProfileIn the repeat track analysis (when the satellites flies over a repetitive orbit) measurements are re-sampledalong a theoretical ground track (or mean track) associated to each mission Then a Mean Profile (MP) issubtracted from the re-sampled data to obtain SLA The MP is a time average of similarly re-sampled dataover a long period
bull The Mean Profile used for TP (cycles 1 to 364) Jason-1 (cycles 1 to 259) and Jason-2 is computedwith 10 years of TP (cycles 11 to 353) and 6 years of Jason-1 (cycles 11 to 250)
bull The Mean Profile used for TP (cycles 368 to 481) and from Jason-1 cycle 262 to 374 (where satellitesare on interleaved ground-tracks) is computed with 3 years of TP (cycles 369 to 479)
bull The Mean Profile used for ERS-1 in its 35 days repetitive orbit mission ERS-2 and Envisat (only forthe first orbit before November 2010) is computed with 8 years of ERS-2 (cycles 1 to 85) and 6 yearsof Envisat (cycles 10 to 72)
bull No Mean Profile can be used for Envisat on its new orbit (enn) Jason-1 on its geodetic orbit (j1g)because there is no repetitive track The MSS must be used instead (see below)
bull The Mean Profile used for GFO is computed with 7 years of GFO cycles 37 to 187
Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible
bull Indeed as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide precise cross-track projection andor interpolation schemes are required to avoid errors
bull The mesoscale variability error (which is lt35 cm for MP between 3 to 5 years and lt1cm for WLof 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a prioriknowledge from Sea Level maps derived from previous iterations or from other missions
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PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for ERS-1 for its 168 days geodetic mission (phases E-F from April1994 to March 1995) or for Envisat since november 2010 because the satellite is not in a repetitive orbitphase The alternative is to use the MSS instead The gridded MSS is derived from along track MPs anddata from geodetic phases Thus any error on the MP is also contained in the MSS There are essentially 4types of additional errors on gridded MSS which are hard to quantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
III362 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III363 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
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PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
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III37 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III371 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
Page 39
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
IV MYOCEAN PRODUCTS
IV1 Near Real Time Products
The purpose of the NRT DUACS component is the acquisition of altimeter data from various altimeter mis-sions in near-real time (ie within a few days at most) the validation and correction of these altimeter datasets (ie edition and selection update of corrections and homogenization orbit error reduction) in order toproduce each day along-track productsProducts are as follows
Along-track products global and regional (Mediterranean and Black Seas Arctic Ocean and Europeareas)
bull Sea Level Anomaly (NRT-SLA) for each mission with NRT-SLA ephemeris
IV11 Delay of the products
The availability of the products in near real time is three to twelve hours after the measurement for along-track products Those products are delivered every day
IV12 Temporal availibility
The following table presents the available products by mission and by data periodNear real time products
NRT Jason-2 Jason-1 and Jason-1geodetic
Envisat new Cryosat-2
Temporal Time availability ymlowast
ongoingymlowast-20120303 for
repeat track and20120507-ongoing for
geodetic track
ymlowast
2012040820120101
ongoing
NRT-SLA X X X X
lowastym the temporal coverage for NRT products is fluctuating and depends on updates of Delayed Time prod-ucts When DT products are updated (3 to 4 times per year) the oldest NRT products are replaced by thebetter quality DT products so that the 2 series are overlapping on few weeks or few months
IV2 Delayed Time Products
The Delayed Time component of SSALTODUACS system is responsible for the production of processedJason-1 Jason-2 TP Envisat GFO ERS12 and even Geosat data in order to provide a homogeneousinter-calibrated and highly accurate long time series of SLA DT products are more precise than NRT products Two reasons explain this quality difference The firstone is the better intrinsic quality of the POE orbit used in the GDR processing The second reason is that
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PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
in the DT DUACS processing the products can be computed optimally with a centred computation timewindow for OER LWE On the contrary in NRT case future data are not available so the computationtime window is not centred and therefore not optimalAs for NRT products improved altimeter corrections and processing algorithms are used ocean tide modelto correct altimeter data improved methods for orbit error reduction and mapping
Along-Track products global and regional (Mediterranean and Black Seas)
bull Sea Level Anomaly (DT-SLA) for each mission
IV21 Delay of the products
Weekly products are delivered The availability of the products in delayed time is at the best two monthsafter the date of the measurement The product generation needs all the GDR data of all the missions to takeinto account the best corrections as possible The time delay can be longer in the case of a missing mission
IV22 Temporal availibility
The following table presents the available products by mission and by data periodDelayed time SSALTODUACS products
Upd Jason-2 Jason-1new6
Jason-1 GFO Envisatnew6
Envisat ERS-16
ERS-2Topexnew6
Topex
TemporalTimeavailabil-ity
200810ymlowast
200902ymlowast
200204200810
200001200809
201010ymlowast
200210201010
199210200304
200209200510
199209200204
DT-SLA X X X X X X X X X
lowast ym those dates are updated regularly (3 to 4 times per year) and are avalaible when you download thedata at httpwwwmyoceaneuweb24-cataloguephp6 Jason-1 new orbit starting 200809 Envisat new orbit starting 201010 TP new orbit starting 200209 ERS-1The geodetic phases (E-F) are included There are no ERS-1 data between December 23 1993 and April 10 1994(ERS-1 phase D - 2nd ice phase) Note that during that time products are based only on TopexPoseidon data
Page 41
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
V DESCRIPTION OF THE PRODUCT SPECIFICATION
V1 General information
Product Specification SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001
Geographical coverage global
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 20-50km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001 Product Specification
Page 42
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
Product Specification SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002
Geographical coverage 55˚W-35˚E 30˚N-46˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002 Product Specification
Page 43
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
Product Specification SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003
Geographical coverage 27˚E-42˚E 40˚N-47˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003 Product Specification
Page 44
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
Product Specification SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004
Geographical coverage 25˚W-42˚E 21˚N-66˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004 Product Specification
Page 45
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
Product Specification SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005
Geographical coverage 0˚W-360˚E 50˚N-82˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005 Product Specification
Page 46
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
VI NOMENCLATURE OF FILES
VI1 Nomenclature of files downloaded through the MyOcean Web PortalDirectgetfile Service
VI11 Nomenclature of the product line
The description of the syntax for the SL TAC SLA products line is given by
SEALEVEL_ltREGIONgt_SLA_L3_ltDELAYgt_OBSERVATIONS_008_ltZONEgt_ltLETTERgtwhere
REGION GLO global geographic coverage product
BS Black Sea products
MED Mediterranean products
ARC Arctic products (for NRT products)
EUROPE Europe products (for NRT products)
DELAY NRT near real time products
RAN delayed time or reanalysis products
ZONE 001 number on 3 digits
002
003
004
LETTER a letter on 1 digit
b
Page 47
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
VI12 Nomenclature of the datasets
The nomenclature used is
dataset-duacs-ltdelaygt-ltzonegt-ltmissiongt-lttype of slagt-l3where the fileds in ltgt are described below
delay nrt near-real time productsran delayed time products
zone global global geographic coverage productmedsea Mediterranean productsblacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1 (only for ran)e2 ERS-2 (only for ran)tp TOPEXPoseidon (only for ran)tpn TOPEXPoseidon on its new orbit (only for
ran)g2 GFO (only for ran)j1 Jason-1 (only for ran)j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisat (only for ran)enn Envisat on its new orbitc2 Cryosat-2 (only for nrt)
type of sla sla filtered slasla_unfiltered non filtered sla (only for ran products)
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VI13 Nomenclature of the NetCdf files
The nomenclature used is
ltdelaygt_ltzonegt_ltmissiongt_sla_ltvariablegt_ltdatebegingt_ltdateendgt_ltdateprodgtnc where the fileds in ltgt are de-scribed below
delay nrt near-real time productsdt delayed time products
zone global global geographic coverage productmed Mediterranean products (for dt)mfstep Mediterranean products (for nrt)blacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1e2 ERS-2tp TOPEXPoseidontpn TOPEXPoseidon on its new orbitg2 GFOj1 Jason-1j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisatenn Envisat on its new orbitc2 Cryosat-2
variable vfec filtered and sub-sampled slavxxc non filtered and non sub-sampled sla (only
for dt)datebegin YYYYMMDD() beginning date of the datasetdateend YYYYMMDD() end date of the datasetdateprod YYYYMMDD production date of the dataset
() For dt data as the dates in the file names are rounded the user wanting data for date T has to read the filescontaining dates T+1 and T-1 in their name and check inside the files if there are some data for date T
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VII DATA FORMAT
This chapter presents the data storage format used for MyOcean products
VII1 NetCdf
The products are stored using the NetCDF format NetCDF (network Common Data Form) is an interface for array-oriented data access and a library that provides an implementation of the interface The netCDF library also definesa machine-independent format for representing scientific data Together the interface library and format support thecreation access and sharing of scientific data The netCDF software was developed at the Unidata Program Center inBoulder Colorado The netCDF libraries define a machine-independent format for representing scientific data Pleasesee Unidata NetCDF pages for more information and to retreive NetCDF software package onhttpwwwunidataucaredupackagesnetcdfindexhtml
NetCDF data is
bull Self-Describing A netCDF file includes information about the data it contains
bull Architecture-independent A netCDF file is represented in a form that can be accessed by computers with dif-ferent ways of storing integers characters and floating-point numbers
bull Direct-access A small subset of a large dataset may be accessed efficiently without first reading through allthe preceding data
bull Appendable Data can be appended to a netCDF dataset along one dimension without copying the dataset orredefining its structure The structure of a netCDF dataset can be changed though this sometimes causes thedataset to be copied
bull Sharable One writer and multiple readers may simultaneously access the same netCDF file
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VII2 Structure and semantic of NetCDF along-track files
The NetCDF Sea Level TAC files are based on the attribute data tags defined by the Cooperative OceanAtmosphereResearch Data Service (COARDS) and Climate and Forecast (CF) metadata conventions The CF convention gener-alises and extends the COARDS convention but relaxes the COARDS constraints on dimension and order and specifiesmethods for reducing the size of datasetsA wide range of software are available to write or read NetCDFCF files API are made available by UNIDATA(httpwwwunidataucaredusoftwarenetcdf)
bull CC++Fortran
bull Java
bull MATLAB Objective-C Perl Python R Ruby TclTk
In addition to these conventions the files are using a common structure and semantic
bull 1 dimension is defined
ndash time it is used to check NetCDF variables depending on time
bull 8 variables are defined
ndash short SLA contains the Sea Level Anomaly values for each time given
ndash int longitude contains the longitude for each measurement
ndash short track contains the track number for each measurement
ndash double time contains the time in days since 1950-01-01 000000 UTC for each measurement
ndash short mean_profile_point_index index of the corrsponding point in the track of the mean profile
ndash byte flag flag=0 the processed data comes from OGDR if flag=1 the processed data comes from theIGDR
ndash int latitude contains the latitude for each measurement
ndash short cycle contains the cycle number for each measurement
bull global attributes
ndash the global attributes gives information about the creation of the file
Example of a NetCDF sla file
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netcdf nrt_global_j1_sla_vfec_20101230_20101230_20101230 dimensions
time = 10385 variables
short SLA(time) SLAcoordinates = longitude latitude SLAlong_name = Sea Level Anomaly SLA_FillValue = 32767s SLAadd_offset = 0 SLAscale_factor = 0001 SLAunits = m SLAstandard_name = sea_surface_height_above_sea_level
int longitude(time) longitudelong_name = Longitude of measurement longitude_FillValue = 2147483647 longitudeadd_offset = 0 longitudestandard_name = longitude longitudescale_factor = 1e-06 longitudeunits = degrees_east
short track(time) tracklong_name = Track in cycle the measurement belongs to track_FillValue = 32767s trackunits = 1 trackcoordinates = longitude latitude
double time(time) timelong_name = Time of measurement time_FillValue = 184467440737096e+19 timeaxis = T timestandard_name = time timeunits = days since 1950-01-01 000000 UTC
int latitude(time) latitudelong_name = Latitude of measurement latitude_FillValue = 2147483647 latitudeadd_offset = 0 latitudestandard_name = latitude latitudescale_factor = 1e-06 latitudeunits = degrees_north
short flag(time) flagcoordinates = longitude latitude flag_FillValue = 3267s flaglong_name = data origin flagflag_values = 1s 0s flagflag_meanings = igdr_like non_igdr_like flagcomment = The origin of the data is determined by the types of geophysical datarecords (GDR) used in computation of the SLA 1 for the Interim GDR (IGDR) and0 for Operational GDR (OGDR)
short cycle(time) cyclelong_name = Cycle the measurement belongs to cycle_FillValue = 32767s cycleunits = 1 cyclecoordinates = longitude latitude
global attributeshistory = 22-Feb-2011 155243 CET File created by the SSLATODUACS system version 1001 comment = Produce from ENVISAT Extension Phase satellite altimetry data institution = CLSCNES
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references = httpwwwavisooceanobscomfileadmindocumentsdatatoolshdbk_duacspdf source = satellite altimetry title = along track Sea Level Anomaly Conventions = CF-14
dataSLA =
7 7 11 10 -2 -22 -39 -41 -30 -13 -3 -5 -16 -26 -32 -35-35 -35 -37 -35 -31 -29 -31 -35 -32 -21 -10 -10 -19 -20 -1-69 -57 -49 -45 -39 -30 -28 -31 -27 -13 -2 -5 -15 -3 1112 3 -7 -10 -14 -15 -22 -31 -37 -32 -17 -10
longitude =74743328 74868400 74993968 75120040 75246616 7537372875501368 75629568 75758320 75887656 76017568 76148080 7627920876388952 76477056 76565456 76654144 76743128 76832400 76921984329429568 329535424 329641792 329748672 329856096 329964032330072512 330181536 330291072 330401184
track =92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 9292 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92113 113 113 113 113 113 113 113 113 113 113 113 113 113113 113 113 113 113 113 113 113 113
time =222780000565705 222780001314719 222780002063733222780002812747 222780003561761 222780004310775 222780005059788222780005808802 222780006557816 22278000730683 222780008055844222780008804858 222780009553872 22278001017805 222780010677393222788257112198 222788257486705 222788257861212 222788258235719222788258610226 222788258984733 222788259359239 222788259733746222788260108253 22278826048276
mean_profile_point_index =1872 1878 1884 1890 1896 1902 1908 19141920 1926 1932 1938 1944 1949 1953 1957 1961 1965 1969 19732306 2309 2312 2315 2318 2321 2327 2330 2333 2336 2339 23422345 2348 2351 2354 2357 2360 2363 2366
flag =0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
latitude =-16225506 -16539731 -16853833 -17167810 -17481660 -17795380-18108966 -18422418 -18735729 -19048899 -19361924 -19674801-19987527 -20248015 -20456329 -20664569 -20872739 -2108083739481297 39628277 39775133 39921866 40068472 40214953 4036130840507533 40653629 40799592 40945423 41091120 41236684 41382111
cycle =331 331 331 331 331 331 331 331 331 331 331 331 331
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331 331 331 331 331 331 331 331 331 331 331 331 331 331331 331 331 331 331 331 331 331 331 331 331 331
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VIII HOW TO DOWNLOAD A PRODUCT
VIII1 Download a product through the MyOcean Web Portal DirectgetfileService
You first need to register Please find below the registration stepshttpwwwmyoceaneuweb34-products-and-services-faqphp1Once registered the MyOcean FAQ httpwwwmyoceaneuweb34-products-and-services-faqwill guide you on How to download a product through the MyOcean Web Portal Directgetfile Service
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IX NEWS AND UPDATES
IX1 [Duacs] Operational news
To be kept informed on events occurring on the satellites and on the eventual interruption of the services of the DUACSprocessing system see the [Duacs] operational news on the Aviso websitehttpwwwavisooceanobscomendataoperational-newsindexhtml
IX2 Updates
To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtmlSince 2010 a complete reprocessing of all altimetry data (cumulated total of about 55 years of data) is available Themain changes introduced in the Duacs DT v300 reprocessed data set in SSALTODUACS reprocessed DT data setare listed herehttpwwwavisooceanobscomfileadmindocumentsdataduacsduacs_DT_2010_reprocessing_impactpdf
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I INTRODUCTION
MyOcean is a European Network project aiming at monitoring analyzing and forecasting the Ocean Ituses satellite and in-situ data to describe the ocean in 3 dimensions and real time More information can befound on httpwwwmyoceaneuorgThe aim of this document is to describe the products delivered by the Sea Level TAC (Thematic AssemblyCentre) which is one of the five TAC of the MyOcean projectThe data produced in the frame of this TAC are generated by the processing system named DUACS (DataUnification and Altimeter Combination System)DUACS is part of the CNES multi-mission ground segment (SSALTO) It processes data from all altimetermissions Cryosat-2 OSTMJason-2 Jason-1 TopexPoseidon Envisat GFO ERS-1amp2 and even GeosatAt this time (May 25th 2012) DUACS is using three different altimeters in near real time Developed and operated by CLS it started as an European Commission Project (Developing Use Of Altime-try for Climate Studies) funded under the European Commission and the Midi-Pyreacuteneacutees regional councilIt has been integrated to the CNES multi-mission ground segment SSALTO in 2001 and it is maintainedupgraded and operated with funding from CNES with shared costs from EU projectsAt the beginning of 2004 DUACS was redefined as the Data Unification Altimeter Combination System
Figure 1 DUACS and AVISO a user-driven altimetry service
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The products lines described in this user manual are the followingSEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005
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The data provided to users have a global coverage (PL SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001)and regional products are also computed over specific areasMediterranean Sea (PL SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002)and Black Sea (PL SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003)Thanks to updates in 2011 and 2012 (see section II) new regional products are now availableEurope (PL SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004)and Arctic (PL SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005)
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II UPDATES IN 2011 AND 2012
This section describes the updates of the SSALTODUACS Near Real Time system that occurred during2011 and 2012 allowing to add new products (Europe and Arctic) the integration of the Cryosat-2 data inthe system the stopping delivery of Envisat data the addition of Jason-1 data on geodetic orbit (j1g)To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtml
II1 Version D of input IGDROGDR Jason-2 data for NRT processing(July 30 2012)
On July 30 2012 the version of Jason-2 IGDROGDR has changed and is now the D version Somecorrections have thus been updated as detailed in tables 3 and 4
II2 Integration of Jason-1 on its geodetic orbit (May 2012)
An anomaly occured on March 3rd 2012 on the Jason-2 mission (see httpwwwavisooceanobscomfractualitesactualitesindexhtmltx_ttnews[tt_news]=1162amptx_ttnews[backPid]=1399ampcHash=d5baeb645e) On April 23rd CNES began to command the satellite into a nadir ori-entation and after some propulsion anomalies CNES and NASA management through the Joint SteeringGroup have directed the Jason-1 Project to then begin a series of maneuvers to place Jason-1 into a neworbit as defined in table 1 After checking the current orbit carefully the operational team determined thata geodetic mission was still possible It was also decided to preserve all remaining fuel for future stationkeeping maneuvers which is mandatory in a geodetic orbit Core payloads were switched ON on May 4thand after some POSEIDON2 radar (PRF) adjustments the mission was resumed on May 7th at 151248UTCBelow are the characteristics of the new orbit which will be maintained as before within +- 1km controlbox at the Equator
Semi major axis 7702437 kmEccentricity 13 to 28 10-4Altitude equator 13240 kmOrbital period 6730s (1h52rsquo10rdquo)Inclination 66042˚Cycle 406 daysSub cycles 39 - 109 - 475 - 1795
days
Table 1 Characteristics of the geodetic orbit for Jason-1 since May 7th 2012
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For this new phase of the Jason-1 mission (called j1g) the cycle numbering will restart at 500 Off-lineproducts will be produced once a day for the IGDR and every 11 days for the GDRrsquos The integration ofJason-1 data in the DUACS system is available since May 25th 2012
II3 Envisat has stopped sending data (April 2012)
Since April 8th 2012 Envisat has stopped sending data to Earth Esarsquos mission control has worked tore-establish contact with the satellite but there has been no reaction from the satellite Thus Esa has de-clared officially the end of mission for Envisat (see httpwwwesaintesaCPSEM1SXSWT1H_index_0html) Therefore no SL TAC NRT data from Envisat can be released since this date
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II4 Integration of the Cryosat2 Mission (February 2012)
Since February 6th 2012 Cryosat-2 mission has been integrated in the DUACS sytem This mission isdedicated to the observation of the floating sea-ice as well as the continental ice sheets but all data acquiredover ocean are valuable for the observation of oceanic circulation and mesoscale variations This majorchange is the result of the long-standing and fruitful partnership between ESA and CNES and a responseto the request from scientific and operational oceanography users [7] The integration of Cryosat-2 impactsthe delivering of Near real time Sea Level Anomalies (SLA)
II41 Generalities about the mission
A Cryosat-2 Processing Prototype (C2P) (described in Boy et al 2011 [2]) has been developed on CNESside to lay the ground for various SAR processing studies The processing chains ingest Level-0 telemetryfiles distributed by ESA and perform the following steps to generate Sea Level Anomalies (SLA) values foreach altimeter measurements
bull Level-1 Decommutation time-tagging and localization of measurements
bull Level-1b Calculation of instrumental corrections and geophysicalmeteorological corrections
bull Level-2 MLE4 waveforms Retracking and calculation of SLA
The prototype processes data almost continuously over ocean either in Low Resolution Mode (LRM) or inthe DopplerSAR mode processed as pseudo-LRM mode allowing to increase the coverage (figure 2)
Figure 2 SSH-MSS for Cryosat-2 with LRM mode only (left) or LRM+pseudo-LRM modes (right)
Although Cryosat-2 raw SSH can be only corrected with GPS-derived ionospheric correction and ECMWFwet troposphere correction validation activities showed (Labroue et al 2011 [25]) that C2P outputs have anaccuracy roughly equivalent to Envisatrsquos Level 2 products if the latter are processed with the same standards
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II42 Integration in DUACS
The Cryosat-2 data are included in the Near Real time process The chain delivers now (for global coverageMediterranean and Black Seas) along track data from Cryosat-2 (SLAs) Note that the products distributedare of Level-3 and donrsquot replace Level-2 products distributed by agenciesThe details of the processing are given in Dibarboure et al 2011 [8]Here we just give an overview the data are computed with the corrections given in section III21 Thefiltering and sub-sampling of SLAs (section III263) are detailed in [8]
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II5 Addition of Europe and Arctic products (January 2012)
Since the MyOcean V2 two new along-track products are computed in Near Real Time intended foraddressing the needs of data assmilation and validation in regional models
bull Following the TAPAS (Tailored Altimeter Product for Assimilation Systems) initiative launched bySL TAC with all the Modeling and Forecasting Centers (MFCs) the Europe regional products (PLSEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004) have been proposed (figure 3) They areavailable in Near Real Time onlyThey are studied to partly fulfil the needs of the Centers with adapted filtering and resolution Thoseparameters have been tuned in order to provide boundary conditions for the Atlantic assimilationmodels They are different from the ones used for Mediterranean and Black Seas products If you needto study the Mediterranean Sea or the Black Sea yoursquod better use the dedicated products describedabove since the processing parameters have been fitted to be adapted to the dynamics of the ocean inthose regions
Figure 3 Coverage of the Europe product for Jason-1 Jason-2 and Envisat from August 18th to September9th 2011
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bull The Arctic along-track products (PL SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005) coverlatitudes between 45 and 82 degrees (figure 4) They are available in Near Real Time only
Figure 4 Coverage of the Arctic region with Envisat from October 28th 2011 to January 3rd 2012
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III SSALTODUACS SYSTEM
III1 Introduction
This chapter presents the input data used by SSALTODUACS system and an overview of the different pro-cessing steps necessary to produce the output dataSSALTODUACS system is made of two components a Near Real Time one (NRT) and a Delayed Time(DT) oneIn NRT the systemrsquos primary objective is to provide operational applications with directly usable high qual-ity altimeter data from all missions availableIn DT it is to maintain a consistent and user-friendly altimeter database using the state-of-the-art recom-mendations from the altimetry communityFollowing figure gives an overview of DUACS system where processing sequences can be divided into 7main steps
bull acquisition
bull homogenization
bull input data quality control
bull multi-mission cross-calibration
bull product generation
bull merging
bull final quality control
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Figure 5 SSALTODUACS processing sequences
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III2 Near Real Time processing steps
III21 Input data models and corrections applied
To produce SLA in near-real time the DUACS system uses two flows based on the same instrumental mea-surements but with a different quality
bull The IGDR that are the latest high-quality altimeter data produced in near-real-time
bull The OGDR that includes real time data (OSTMJason-2 and Jason-1 OSDR) to complete IGDR Thesefast delivery products do not always benefit from precise orbit determination nor from some exter-nal model-based corrections (Dynamic Atmospheric Correction (DAC) Global Ionospheric Maps(GIM))
Integration of OGDR data and the introduction of Jason-2Jason-1 tandem increased the resilience and pre-cision of the system A better restitution of ocean variability is observed especially in high energetic areas
Altimetric product Source Availability Type of orbit
Jason-2 IGDR CNES ~24h CNES MOE GDR-Cuntil 20120730
CNES MOE GDR-Dsince 20120731
OGDR NOAAEUMETSAT ~3 to 5 h
Jason-1 IGDR CNESNASA ~48 h CNES MOE GDR-Dsince 20120507
OGDR CNESNASA ~3 to 12 h
Envisat IGDR ESACNES not deliveredsince 20120408
CNES MOE GDR-Dsince 20120121
FDGDR ESA not deliveredsince 20120408
Cryosat-2 IGDR-like ESACNES ~48 h CNES MOE GDR-D
not delivered
Table 2 SSALTODUACS Near-Real Time Input data overview
See Figure 6 Overview of the near real time system data flow management
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DUACS 2011 NRT product from IGDR1
j2 j1nj1g enn c2Productstandard ref
version C until20120730 and D after
version C version 21 CPP [2]
Orbit CNES MOE GDR-Cuntil 20120730
GDR-D after
CNES MOE GDR-C forj1n and CNES MOE
GDR-D for j1g
CNES MOE GDR-Dfrom 20120121 to
20120408
CNES MOE GDR-D
Ionopheric bi-frequency altimeter range measurements GIM model for cgt64 (Iijima et al1998[24])Dry tropo Model computed from ECMWF Gaussian grids (new S1 and S2 atm tides applied)Wet tropo-sphere
AMR radiometer(enhancement in coastal
regions since20120730)
JMR radiometer MWR radiometer andcorrected from side
lobes
Model computed fromECMWF Gaussian
grids
DAC MOG2D High Resolution forced with ECMWF pressure and wind fields (S1 and S2 wereexcluded) (Carrere and Lyard 2003[3])+ inverse barometer Filtering temporal window is
un-centered (no data in the future)Ocean tide GOT4v8 (S1 and S2 are included) and TPX 072 [16] for Arctic productsPole tide [Wahr 1985 [53]]Solid earthtide
Elastic response to tidal potential [Cartwright and Tayler 1971[5]] [Cartwright andEdden 1973[6]]
Loading tide GOT4v8 (S1 and S2 are included)Sea statebias
Non parametric SSB[Labroue 2004[27]](with cycles J1 1 to 11
using GDR-B standardsuntil 20120730 andderived from Jason-2
after)
Non parametric SSB[Labroue 2004[27]](with cycles 1 to 21
using GDR-Bstandards)
Non parametric SSB[Labroue 2004[27]](with cycles 41 to 60
using GDR-Bstandards)
Same as Jason-2 SSB
Orbit error Global multi-mission crossover minimization (Le Traon and Ogor1998[32])
Long wave-lengh errors
Optimal Interpolation [Le Traon et al 1998[31]]
Intercalibration Reference from cycle20
Mean pro-file (seeIII261)
Computed with cycles11-353 TP data andwith cycles 11-250J1 data referenced[19931999]
TPNJ1N computedwith cycles 369-479TPN data refer-enced [19931999]J1G No MP can beused instead theMSS_CNES_CLS11[39] is used
No Mean Profilecan be used forEnvisat on its neworbit Instead theMSS_CNES_CLS11[39] is used
No Mean Profilecan be used forCryosat-2 Instead theMSS_CNES_CLS11[39] is used
(1) A flag included in the along-track files indicates the source of the production (OGDRFDGDR orIGDR) If flag=0 the processed data comes from OGDRsFDGDRs if flag=1 the processed data comesfrom IGDRs
Table 3 Corrections and models applied in SSALTODUACS NRT products produced from IGDRs
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DUACS 2011 NRT product from OGDR or FDGDR2
j2 j1nj1g ennProduct stan-dard ref
version C until 20120730and D after
version C version 21
Orbit Navigator Extrapolated CNES MOEGDR-D since 20120121
Ionopheric From-dual frequency altimeter range measurements From GIM model fromcycle 65 (Iijima et al1998 [24])
Dry troposphere Model computed from ECMWF Gaussian grids (new S1 and S2 atmospherictides are applied)
Wet tropo-sphere
AMR radiometer(enhancement in coastal
regions since 20120730)
JMR radiometer MWR radiometer andcorrected from side lobes
DAC Inverse Barometer forecastedOcean tide GOT4v8 (S1 and S2 are included) and TPX 072 [16] for Arctic productsPole tide [Wahr 1985 [53]]Solid earth tide Elastic response to tidal potential [Cartwright and Tayler 1971[5]]
[Cartwright and Edden 1973[6]]Loading tide GOT4v8 (S1 and S2 are included)Sea state bias Non parametric SSB
[Labroue 2004[27]] (withcycles J1 1 to 11 usingGDR-B standards until20120730 and derivedfrom Jason-2 after)
Non parametric SSB[Labroue 2004[27]](with cycles 1 to 21 usingGDR-B standards)
Non parametric SSB[Labroue 2004[27]](with cycles 41 to 60using GDR-B standards)
Orbit error Specific filtering of long-wavelength signal3
Long wave-lengh errors
Optimal Interpolation [Le Traon et al 1998[31]]
Intercalibration Reference from cycle 20Mean profile(see III261)
Computed with cycles 11-353 TP data and with cy-cles 11-250 J1 data refer-enced [19931999]
TPNJ1N computedwith cycles 369-479TPN data referenced[19931999] J1G NoMP can be used insteadthe MSS_CNES_CLS11[39] is used
No Mean Profile can beused for Envisat on itsnew orbit Instead theMSS_CNES_CLS11 [39]is used
(2) A flag included in the along-track files indicates the source of the production (OGDRFDGDR orIGDR) If flag=0 the processed data comes from OGDRsFDGDRs if flag=1 the processed data comesfrom IGDRs(3) Specific data processing was applied on long wave-length signal (sectIII23 of the user manual)
Table 4 Corrections and models applied in SSALTODUACS NRT products produced from OG-DRsFDGDRs
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III22 Acquisition
The acquisition process is twofold
bull straightforward retrieval and reformatting of altimeter data and dynamic auxiliary data (pressure andwet troposphere correction grids from ECMWF are provided by Meteo France TEC grids from JPLNRT MOG2D corrections) from external repositories
bull synchronisation process
To be homogenized properly altimeter data sets require various auxiliary data The acquisition softwaredetects downloads and processes incoming data as soon as they are available on remote sites (externaldatabase FTP site) Data are split into passes if necessary If data flows are missing or late the synchroni-sation engine put unusable data in waiting queues and automatically unfreezes them upon reception of themissing auxiliary data This processing step delivers raw data that is to say data that have been dividedinto cycles and passes and ordered chronologicallyFrom SSALTODUACS V80 the acquisition step uses two different data flows in near-real time the OGDRflow (within a few hours) and the IGDR flow (within a few days)For each OGDR input the system checks that no equivalent IGDR entry is available in the data base beforeacquisition for each IGDR input the system checks and delete the equivalent OGDR entry in the data baseThese operations aim to avoid duplicates in SSALTODUACS system
Figure 6 Overview of the near real time system data flow management
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III23 Homogenization
The Homogenization process consists in applying the most recent corrections models and references rec-ommended for altimeter products Each mission is processed separately as its needs depend on the baseinput data The list of corrections and models currently applied is provided in tables 3 and 4 for NRT dataThe system includes SLA filtering to process OGDR data DUACS extract from these data sets the shortscales (space and time) which are useful to better describe the ocean variability in real time and merge thisinformation with a fair description of large scale signals provided by the multi-satellite observation in nearreal time (read IGDR-based DUACS data) Finally an hybrid SLA is computed
Figure 7 Merging pertinent information from IGDR and OGDR processing
III24 Input data quality control
The Input Data Quality Control is a critical process applied to guarantee that DUACS uses only the mostaccurate altimeter data Thanks to the high quality of current missions this process rejects a small percent-age of altimeter measurements but these erroneous data could be the cause of a significant quality lossThe quality control relies on standard raw data editing with quality flags or parameter thresholds but alsoon complex data editing algorithms based on the detection of erroneous artefacts mono and multi-missioncrossover validation and macroscopic statistics to edit out large data flows that do not meet the systemrsquosrequirements
Page 26
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III25 Multi-mission cross-calibration
The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistentand accurate information It removes any residual orbit error (OE Le Traon and Ogor 1998[32]) or longwavelength error (LWE Le Traon et al 1998[31]) as well as large scale biases and discrepancies betweenvarious data flows
This process is based on two very different algorithms a global multi-mission crossover minimization fororbit error reduction (OER) and Optimal Interpolation (OI) for LWE
Multi-satellite crossover determination is performed on a daily basis All altimeter fields (measurementcorrections and other fields such as bathymetry MSS) are interpolated at crossover locations and datesCrossovers are then appended to the existing crossover database as more altimeter data become availableThis crossover data set is the input of the Orbit Error Reduction (OER) method Using the precision of thereference mission orbit a very accurate orbit error can be estimated This processing step does not concernOGDR dataLWE is mostly due to residual tidal or inverse barometer errors and high frequency ocean signals The OIused for LWE reduction uses precise parameters derived from
bull accurate statistical description of sea level variability
bull localized correlation scales
bull mission-specific noise and precise assumptions on the long wavelength errors to be removed (from arecent analysis of one year of data from each mission)
Page 27
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III26 Product generation
The product generation process is composed of four steps computation of raw SLA cross-validationfilteringampsub-sampling and generation of by-products
III261 Computation of raw SLA
Since the geoid is not well known yet the SSH cannot be used directly the SSH anomalies are used insteadThey are computed from the difference of the instantaneous SSH - a temporal reference This temporalreference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeattrack analysis cannot be used The errors affecting the SLAs MPs and MSS have different magnitudes andwavelengths The computation of the SLAs and their errors associated are detailed in Dibarboure et al 2010[9]
Use of a Mean ProfileIn the repeat track analysis (when the satellites flies over a repetitive orbit) measurements are re-sampledalong a theoretical ground track (or mean track) associated to each mission Then a Mean Profile (MP) issubtracted from the re-sampled data to obtain SLA The MP is a time average of similarly re-sampled dataover a long period
bull The Mean Profile used for Jason-2 is computed with 10 years of TP (cycles 11 to 353) and 6 years ofJason-1 (cycles 11 to 250)
bull The Mean Profile used from Jason-1 cycle 262 to 374 (where satellites are on interleaved ground-tracks) is computed with 3 years of TP (cycles 369 to 479)
bull No Mean Profile can be used for Envisat on its new orbit (enn) Jason-1 on its geodetic orbit (j1g) norfor Cryosat-2 mission (c2) because there is no repetitive track The MSS must be used instead (seebelow)
Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible
bull Indeed as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide precise cross-track projection andor interpolation schemes are required to avoid errors
bull The mesoscale variability error (which is lt35 cm for MP between 3 to 5 years and lt1cm for WLof 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a prioriknowledge from Sea Level maps derived from previous iterations or from other missions
bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
Page 28
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for Envisat since november 2010 and for Cryosat-2 mission (c2)because the satellite is not in a repetitive orbit phase The alternative is to use the MSS instead The griddedMSS is derived from along track MPs and data from geodetic phases Thus any error on the MP is alsocontained in the MSS There are essentially 4 types of additional errors on gridded MSS which are hard toquantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
Note that for the Arctic regional products the DTU10 MSS [1] is taken into account instead of the CLS01MSS Indeed the accuracy of DTU10 compared to CLS01 is further demonstrated by the significant sealevel anomaly variance reduction found over the whole Arctic Ocean as shown in Prandi et al [42]
III262 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III263 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
Page 29
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III27 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III271 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
Page 30
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III272 Performance indicators
To appreciate the quality situation of the DUACS system new performance indicators are computed dailyThey aim at evaluate the status of the main processing steps of the system the input data availability theinput data coverage the input data quality and the output product quality These indicators are computed foreach and every currently working satellite and combined to obtain the overall status
Figure 8 Example with the key performance indicator on 20090627
See the description the latest and previous indicators on Aviso websitehttpwwwavisooceanobscomindexphpid=1516
Page 31
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III3 Delayed Time processing steps
III31 Input data models and corrections applied
Delayed Time MyOcean products are generated
bull from Aviso GDR products for TP Jason-1 Jason-2 and Envisat (GDR-A cycles 1 to 22 GDR-Bcycles 23 to 85 GDR-C from cycle 86)
bull from NOAA GDR for GFO and from CERSAT (IFREMER) OPR for ERS-1 and ERS-2 (phases C(1st 35-day repeat orbit period) phase E and F (geodetic phases) phase G for ERS-1 (last 35-dayrepeat orbit period tandem phase with ERS-2 phase A for ERS-2 (1st 35-day repeat orbit periodtandem phase with ERS-1))
All GDR products are computed with a Precise Orbit Ephemeris (POE) and are delivered within 2 to 3months depending on the mission For several missions an updated orbit is used
bull For ERS-1amp-2 the orbit used is DGME-04 provided by Delft Institute (httpwwwdeostudelftnl)until June 2003
bull For TopexPoseidon the orbit used is GSFC (std0809) for the whole mission
bull For Envisat CNES POE of GDR-C standard is used for the whole mission
bull For the whole GFO mission the orbit used is GSFC (std0809) and when not available NASA POE isused
Altimetric product Source Availability Type of orbit
TopexPoseidon GDR NASACNES - GSFC POE
Jason-1 GDR (GDR-C) CNESNASA ~40 days CNES POE
Jason-2 GDR (GDR-C) CNESNASA ~60 days CNES POE
GFO GDR NOAA - GSFCNASA POE
ERS-1amp2 IFREMERESA - DGME-04
Envisat (GDR-A GDR-B andGDR-C from cycle 86)
ESA ~2 months CNES POE
Table 5 SSALTODUACS Delayed Time Input data overview
Page 32
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
DU
AC
S20
11D
Tpr
oduc
t(gtV
30
0)j2
j1j1
ntp
tpn
e1e2
ene
nng2
Prod
uct
stan
dard
ref
GD
R-C
OPR
GD
R-A
(Cyc
les
1to
22)
GD
R-B
(cyc
les
23-8
5)
GD
R(N
OA
A)
Orb
itC
nes
POE
GSF
C(I
TR
F20
05G
RA
CE
last
stan
dard
s)
DG
ME
-04
(Sch
arro
oan
dV
isse
r19
98[4
8]C
NE
SPO
E(G
DR
-1st
anda
rds
forc
ycle
s9
to22
GD
R-C
stan
dard
sfr
omcy
cle
23)
GSF
C(I
TR
F20
05
GR
AC
Ela
stst
anda
rds
Iono
pher
icD
ual f
requ
ency
altim
eter
rang
em
easu
rem
ents
Dua
l fre
quen
cyal
timet
erra
nge
mea
sure
men
ts(T
opex
)D
OR
IS(P
OSE
IDO
N)
Ben
t mod
elB
ent m
odel
(cyc
les
1-36
)G
IMm
odem
from
cycl
e37
((Ii
jima
etal
19
98[2
4])
Dua
l-fr
eque
ncy
altim
eter
rang
em
easu
rem
ent(
cycl
e9-
64)a
ndG
IMm
odel
gtcyc
le65
(Iiji
ma
etal
19
99[2
4])c
orre
cted
from
8m
mbi
as
From
GIM
mod
el(I
ijim
aet
al1
998
[24]
)
Dry
trop
o-sp
here
Mod
elco
mpu
ted
from
EC
MW
FG
auss
ian
grid
s(n
ewS1
and
S2at
mos
pher
ictid
esar
eap
plie
d)
Mod
elco
mpu
ted
from
EC
MW
Fre
ctan
gula
rgri
ds(n
ewS1
and
S2at
mos
pher
ictid
esar
ein
clud
ed)
Wet
trop
o-sp
here
JMR
AM
Rra
diom
eter
furt
hert
han
50km
from
the
coas
tsF
rom
EC
MW
Fm
odel
ford
ista
nces
betw
een
10an
d50
km
TM
Rra
diom
eter
(Sch
aroo
etal
20
04[4
9])
MW
RC
orre
ctio
nof
the
drif
ton
the
236
GH
zbr
ight
ness
tem
pera
ture
(Sch
arro
oet
al
2004
[49]
)Neu
ral
Net
wor
kal
gori
thm
(Tra
nan
dO
blig
is
2003
[50]
MW
Rra
diom
eter
furt
hert
han
50km
from
the
coas
tsan
dco
rrec
ted
from
side
lobe
s(f
rom
cycl
e41
)E
CM
WF
mod
elfo
rdis
tanc
esbe
twee
n10
and
50km
GFO
radi
omet
er
DA
CM
OG
2DH
igh
Res
olut
ion
forc
edw
ithE
CM
WF
pres
sure
and
win
gfie
lds
(S1
and
S2w
ere
excl
uded
)+in
vers
eba
rom
eter
com
pute
dfr
omre
ctan
gula
rgri
ds
Tabl
e6
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(1
2)
Page 33
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
j2j1
j1n
tptp
ne1
e2en
enn
g2O
cean
tide
GO
T4v
7(S
1an
dS2
are
incl
uded
)Po
letid
e[W
ahr
1985
[53]
]So
lidea
rth
tide
Ela
stic
resp
onse
totid
alpo
tent
ial[
Car
twri
ghta
ndTa
yler
197
1[5]
][C
artw
righ
tand
Edd
en1
973[
6]]
Loa
ding
tide
GO
T4v
7(S
1pa
ram
eter
isin
clud
ed)
Sea
stat
ebi
asN
onpa
ram
etri
cSS
B[G
aspa
reta
l20
02[2
0]]
Non
para
met
ric
SSB
[NT
ran
and
al2
010[
51]]
BM
3[G
aspa
ran
dO
gor
1994
[17]
]
Non
para
met
ric
SSB
[Mer
tzet
al
2005
[38]
]
Non
para
met
ric
SSB
[Gas
pare
tal
2002
]w
ithG
DR
-Bst
anda
rds
forc
ycle
s9
to85
and
with
GD
R-C
stan
dard
sfr
omcy
cle
86
Non
para
met
ric
SSB
[NT
ran
etal
20
10[5
1]]
Orb
iter
ror
Glo
bal m
ulti-
mis
sion
cros
sove
rmin
imiz
atio
n(L
eTr
aon
and
Ogo
r19
98[3
2])
Lon
gw
ave-
leng
her
rors
Opt
imal
Inte
rpol
atio
n(L
eTr
aon
etal
19
98[3
1])
Inte
rcal
ibra
tion
Ref
eren
cefr
omcy
cle
11R
efer
ence
from
cycl
e1
to35
4C
orre
ctio
nof
regi
onal
bias
J2J
1de
duce
dfr
omin
terc
alib
ratio
nph
ase
(cyc
le11
J2)
Cor
rect
ion
ofgl
obal
biai
sJ1
TP
deacutedu
ced
from
inte
rcal
ibra
tion
phas
e(c
ycle
s11
J1)
Mea
npr
o-fil
e(s
eeII
I36
1)
Com
pute
dw
ithcy
cles
11-3
53T
Pda
taan
dw
ithcy
cles
11-2
50J1
data
ref
eren
ced
[199
319
99]
TP
J1 c
ompu
ted
with
cycl
es11
-353
TP
data
and
with
cycl
es11
-250
J1da
tar
efer
ence
d[1
993
1999
]T
PNJ
1Nc
ompu
ted
with
cycl
es36
9-47
9T
PNda
tar
efer
ence
d[1
993
1999
]
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
ref
eren
ced
[199
319
99]
EN
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
re
fere
nced
[199
319
99]
EN
Nu
seof
MSS
_CN
ES_
CL
S11
[39]
Com
pute
dw
ithcy
cles
37-1
87G
2da
ta
refe
renc
ed[1
993
1999
]
Peri
odof
use
from
cycl
e9
from
cycl
e9
cycl
es1
to48
1cy
cles
15to
43In
clud
ing
E-F
geod
etic
phas
es
cycl
es1
to83
from
cycl
e9
cycl
es37
to22
2
Tabl
e7
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(2
2)
Page 34
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III32 Acquisition
The acqusition process in Delayed time is much simpler than in Near Real time it consists in a synchronisa-tion process of all the auxiliary data required to homogenize propely the altimeter data sets The acquisitionstep uses the GDRs or the OPRs provided by the agencies
III33 Homogenization
The Homogenization process consists in applying the most recent corrections models and references rec-ommended for altimeter products Each mission is processed separately as its needs depend on the baseinput data The list of corrections and models currently applied is provided in tables 6 and 7 for DT data
III34 Input data quality control
The Input Data Quality Control is a critical process applied to guarantee that DUACS uses only the mostaccurate altimeter data Thanks to the high quality of current missions this process rejects a small percent-age of altimeter measurements but these erroneous data could be the cause of a significant quality lossThe quality control relies on standard raw data editing with quality flags or parameter thresholds but alsoon complex data editing algorithms based on the detection of erroneous artefacts mono and multi-missioncrossover validation and macroscopic statistics to edit out large data flows that do not meet the systemrsquosrequirements
Page 35
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III35 Multi-mission cross-calibration
The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistentand accurate information It removes any residual orbit error (OE Le Traon and Ogor 1998[32]) or longwavelength error (LWE Le Traon et al 1998[31]) as well as large scale biases and discrepancies betweenvarious data flows
This process is based on two very different algorithms a global multi-mission crossover minimization fororbit error reduction (OER) and Optimal Interpolation (OI) for LWE
Multi-satellite crossover determination is performed on a daily basis All altimeter fields (measurementcorrections and other fields such as bathymetry MSS) are interpolated at crossover locations and datesCrossovers are then appended to the existing crossover database as more altimeter data become availableThis crossover data set is the input of the Orbit Error Reduction (OER) method Using the precision of thereference mission orbit a very accurate orbit error can be estimated LWE is mostly due to residual tidalor inverse barometer errors and high frequency ocean signals The OI used for LWE reduction uses preciseparameters derived from
bull accurate statistical description of sea level variability
bull localized correlation scales
bull mission-specific noise and precise assumptions on the long wavelength errors to be removed (from arecent analysis of one year of data from each mission)
Page 36
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III36 Product generation
The product generation process is composed of four steps computation of raw SLA cross-validationfilteringampsub-sampling and generation of by-products
III361 Computation of raw SLA
Since the geoid is not well known yet the SSH cannot be used directly the SSH anomalies are used insteadThey are computed from the difference of the instantaneous SSH - a temporal reference This temporalreference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeattrack analysis cannot be used The errors affecting the SLAs MPs and MSS have different magnitudes andwavelengths The computation of the SLAs and their errors associated are detailed in Dibarboure et al 2010[9]
Use of a Mean ProfileIn the repeat track analysis (when the satellites flies over a repetitive orbit) measurements are re-sampledalong a theoretical ground track (or mean track) associated to each mission Then a Mean Profile (MP) issubtracted from the re-sampled data to obtain SLA The MP is a time average of similarly re-sampled dataover a long period
bull The Mean Profile used for TP (cycles 1 to 364) Jason-1 (cycles 1 to 259) and Jason-2 is computedwith 10 years of TP (cycles 11 to 353) and 6 years of Jason-1 (cycles 11 to 250)
bull The Mean Profile used for TP (cycles 368 to 481) and from Jason-1 cycle 262 to 374 (where satellitesare on interleaved ground-tracks) is computed with 3 years of TP (cycles 369 to 479)
bull The Mean Profile used for ERS-1 in its 35 days repetitive orbit mission ERS-2 and Envisat (only forthe first orbit before November 2010) is computed with 8 years of ERS-2 (cycles 1 to 85) and 6 yearsof Envisat (cycles 10 to 72)
bull No Mean Profile can be used for Envisat on its new orbit (enn) Jason-1 on its geodetic orbit (j1g)because there is no repetitive track The MSS must be used instead (see below)
bull The Mean Profile used for GFO is computed with 7 years of GFO cycles 37 to 187
Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible
bull Indeed as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide precise cross-track projection andor interpolation schemes are required to avoid errors
bull The mesoscale variability error (which is lt35 cm for MP between 3 to 5 years and lt1cm for WLof 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a prioriknowledge from Sea Level maps derived from previous iterations or from other missions
Page 37
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bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for ERS-1 for its 168 days geodetic mission (phases E-F from April1994 to March 1995) or for Envisat since november 2010 because the satellite is not in a repetitive orbitphase The alternative is to use the MSS instead The gridded MSS is derived from along track MPs anddata from geodetic phases Thus any error on the MP is also contained in the MSS There are essentially 4types of additional errors on gridded MSS which are hard to quantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
III362 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III363 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
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III37 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III371 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
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IV MYOCEAN PRODUCTS
IV1 Near Real Time Products
The purpose of the NRT DUACS component is the acquisition of altimeter data from various altimeter mis-sions in near-real time (ie within a few days at most) the validation and correction of these altimeter datasets (ie edition and selection update of corrections and homogenization orbit error reduction) in order toproduce each day along-track productsProducts are as follows
Along-track products global and regional (Mediterranean and Black Seas Arctic Ocean and Europeareas)
bull Sea Level Anomaly (NRT-SLA) for each mission with NRT-SLA ephemeris
IV11 Delay of the products
The availability of the products in near real time is three to twelve hours after the measurement for along-track products Those products are delivered every day
IV12 Temporal availibility
The following table presents the available products by mission and by data periodNear real time products
NRT Jason-2 Jason-1 and Jason-1geodetic
Envisat new Cryosat-2
Temporal Time availability ymlowast
ongoingymlowast-20120303 for
repeat track and20120507-ongoing for
geodetic track
ymlowast
2012040820120101
ongoing
NRT-SLA X X X X
lowastym the temporal coverage for NRT products is fluctuating and depends on updates of Delayed Time prod-ucts When DT products are updated (3 to 4 times per year) the oldest NRT products are replaced by thebetter quality DT products so that the 2 series are overlapping on few weeks or few months
IV2 Delayed Time Products
The Delayed Time component of SSALTODUACS system is responsible for the production of processedJason-1 Jason-2 TP Envisat GFO ERS12 and even Geosat data in order to provide a homogeneousinter-calibrated and highly accurate long time series of SLA DT products are more precise than NRT products Two reasons explain this quality difference The firstone is the better intrinsic quality of the POE orbit used in the GDR processing The second reason is that
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in the DT DUACS processing the products can be computed optimally with a centred computation timewindow for OER LWE On the contrary in NRT case future data are not available so the computationtime window is not centred and therefore not optimalAs for NRT products improved altimeter corrections and processing algorithms are used ocean tide modelto correct altimeter data improved methods for orbit error reduction and mapping
Along-Track products global and regional (Mediterranean and Black Seas)
bull Sea Level Anomaly (DT-SLA) for each mission
IV21 Delay of the products
Weekly products are delivered The availability of the products in delayed time is at the best two monthsafter the date of the measurement The product generation needs all the GDR data of all the missions to takeinto account the best corrections as possible The time delay can be longer in the case of a missing mission
IV22 Temporal availibility
The following table presents the available products by mission and by data periodDelayed time SSALTODUACS products
Upd Jason-2 Jason-1new6
Jason-1 GFO Envisatnew6
Envisat ERS-16
ERS-2Topexnew6
Topex
TemporalTimeavailabil-ity
200810ymlowast
200902ymlowast
200204200810
200001200809
201010ymlowast
200210201010
199210200304
200209200510
199209200204
DT-SLA X X X X X X X X X
lowast ym those dates are updated regularly (3 to 4 times per year) and are avalaible when you download thedata at httpwwwmyoceaneuweb24-cataloguephp6 Jason-1 new orbit starting 200809 Envisat new orbit starting 201010 TP new orbit starting 200209 ERS-1The geodetic phases (E-F) are included There are no ERS-1 data between December 23 1993 and April 10 1994(ERS-1 phase D - 2nd ice phase) Note that during that time products are based only on TopexPoseidon data
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V DESCRIPTION OF THE PRODUCT SPECIFICATION
V1 General information
Product Specification SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001
Geographical coverage global
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 20-50km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001 Product Specification
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Product Specification SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002
Geographical coverage 55˚W-35˚E 30˚N-46˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002 Product Specification
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Product Specification SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003
Geographical coverage 27˚E-42˚E 40˚N-47˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003 Product Specification
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Product Specification SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004
Geographical coverage 25˚W-42˚E 21˚N-66˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004 Product Specification
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Product Specification SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005
Geographical coverage 0˚W-360˚E 50˚N-82˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005 Product Specification
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VI NOMENCLATURE OF FILES
VI1 Nomenclature of files downloaded through the MyOcean Web PortalDirectgetfile Service
VI11 Nomenclature of the product line
The description of the syntax for the SL TAC SLA products line is given by
SEALEVEL_ltREGIONgt_SLA_L3_ltDELAYgt_OBSERVATIONS_008_ltZONEgt_ltLETTERgtwhere
REGION GLO global geographic coverage product
BS Black Sea products
MED Mediterranean products
ARC Arctic products (for NRT products)
EUROPE Europe products (for NRT products)
DELAY NRT near real time products
RAN delayed time or reanalysis products
ZONE 001 number on 3 digits
002
003
004
LETTER a letter on 1 digit
b
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VI12 Nomenclature of the datasets
The nomenclature used is
dataset-duacs-ltdelaygt-ltzonegt-ltmissiongt-lttype of slagt-l3where the fileds in ltgt are described below
delay nrt near-real time productsran delayed time products
zone global global geographic coverage productmedsea Mediterranean productsblacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1 (only for ran)e2 ERS-2 (only for ran)tp TOPEXPoseidon (only for ran)tpn TOPEXPoseidon on its new orbit (only for
ran)g2 GFO (only for ran)j1 Jason-1 (only for ran)j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisat (only for ran)enn Envisat on its new orbitc2 Cryosat-2 (only for nrt)
type of sla sla filtered slasla_unfiltered non filtered sla (only for ran products)
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VI13 Nomenclature of the NetCdf files
The nomenclature used is
ltdelaygt_ltzonegt_ltmissiongt_sla_ltvariablegt_ltdatebegingt_ltdateendgt_ltdateprodgtnc where the fileds in ltgt are de-scribed below
delay nrt near-real time productsdt delayed time products
zone global global geographic coverage productmed Mediterranean products (for dt)mfstep Mediterranean products (for nrt)blacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1e2 ERS-2tp TOPEXPoseidontpn TOPEXPoseidon on its new orbitg2 GFOj1 Jason-1j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisatenn Envisat on its new orbitc2 Cryosat-2
variable vfec filtered and sub-sampled slavxxc non filtered and non sub-sampled sla (only
for dt)datebegin YYYYMMDD() beginning date of the datasetdateend YYYYMMDD() end date of the datasetdateprod YYYYMMDD production date of the dataset
() For dt data as the dates in the file names are rounded the user wanting data for date T has to read the filescontaining dates T+1 and T-1 in their name and check inside the files if there are some data for date T
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VII DATA FORMAT
This chapter presents the data storage format used for MyOcean products
VII1 NetCdf
The products are stored using the NetCDF format NetCDF (network Common Data Form) is an interface for array-oriented data access and a library that provides an implementation of the interface The netCDF library also definesa machine-independent format for representing scientific data Together the interface library and format support thecreation access and sharing of scientific data The netCDF software was developed at the Unidata Program Center inBoulder Colorado The netCDF libraries define a machine-independent format for representing scientific data Pleasesee Unidata NetCDF pages for more information and to retreive NetCDF software package onhttpwwwunidataucaredupackagesnetcdfindexhtml
NetCDF data is
bull Self-Describing A netCDF file includes information about the data it contains
bull Architecture-independent A netCDF file is represented in a form that can be accessed by computers with dif-ferent ways of storing integers characters and floating-point numbers
bull Direct-access A small subset of a large dataset may be accessed efficiently without first reading through allthe preceding data
bull Appendable Data can be appended to a netCDF dataset along one dimension without copying the dataset orredefining its structure The structure of a netCDF dataset can be changed though this sometimes causes thedataset to be copied
bull Sharable One writer and multiple readers may simultaneously access the same netCDF file
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VII2 Structure and semantic of NetCDF along-track files
The NetCDF Sea Level TAC files are based on the attribute data tags defined by the Cooperative OceanAtmosphereResearch Data Service (COARDS) and Climate and Forecast (CF) metadata conventions The CF convention gener-alises and extends the COARDS convention but relaxes the COARDS constraints on dimension and order and specifiesmethods for reducing the size of datasetsA wide range of software are available to write or read NetCDFCF files API are made available by UNIDATA(httpwwwunidataucaredusoftwarenetcdf)
bull CC++Fortran
bull Java
bull MATLAB Objective-C Perl Python R Ruby TclTk
In addition to these conventions the files are using a common structure and semantic
bull 1 dimension is defined
ndash time it is used to check NetCDF variables depending on time
bull 8 variables are defined
ndash short SLA contains the Sea Level Anomaly values for each time given
ndash int longitude contains the longitude for each measurement
ndash short track contains the track number for each measurement
ndash double time contains the time in days since 1950-01-01 000000 UTC for each measurement
ndash short mean_profile_point_index index of the corrsponding point in the track of the mean profile
ndash byte flag flag=0 the processed data comes from OGDR if flag=1 the processed data comes from theIGDR
ndash int latitude contains the latitude for each measurement
ndash short cycle contains the cycle number for each measurement
bull global attributes
ndash the global attributes gives information about the creation of the file
Example of a NetCDF sla file
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netcdf nrt_global_j1_sla_vfec_20101230_20101230_20101230 dimensions
time = 10385 variables
short SLA(time) SLAcoordinates = longitude latitude SLAlong_name = Sea Level Anomaly SLA_FillValue = 32767s SLAadd_offset = 0 SLAscale_factor = 0001 SLAunits = m SLAstandard_name = sea_surface_height_above_sea_level
int longitude(time) longitudelong_name = Longitude of measurement longitude_FillValue = 2147483647 longitudeadd_offset = 0 longitudestandard_name = longitude longitudescale_factor = 1e-06 longitudeunits = degrees_east
short track(time) tracklong_name = Track in cycle the measurement belongs to track_FillValue = 32767s trackunits = 1 trackcoordinates = longitude latitude
double time(time) timelong_name = Time of measurement time_FillValue = 184467440737096e+19 timeaxis = T timestandard_name = time timeunits = days since 1950-01-01 000000 UTC
int latitude(time) latitudelong_name = Latitude of measurement latitude_FillValue = 2147483647 latitudeadd_offset = 0 latitudestandard_name = latitude latitudescale_factor = 1e-06 latitudeunits = degrees_north
short flag(time) flagcoordinates = longitude latitude flag_FillValue = 3267s flaglong_name = data origin flagflag_values = 1s 0s flagflag_meanings = igdr_like non_igdr_like flagcomment = The origin of the data is determined by the types of geophysical datarecords (GDR) used in computation of the SLA 1 for the Interim GDR (IGDR) and0 for Operational GDR (OGDR)
short cycle(time) cyclelong_name = Cycle the measurement belongs to cycle_FillValue = 32767s cycleunits = 1 cyclecoordinates = longitude latitude
global attributeshistory = 22-Feb-2011 155243 CET File created by the SSLATODUACS system version 1001 comment = Produce from ENVISAT Extension Phase satellite altimetry data institution = CLSCNES
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references = httpwwwavisooceanobscomfileadmindocumentsdatatoolshdbk_duacspdf source = satellite altimetry title = along track Sea Level Anomaly Conventions = CF-14
dataSLA =
7 7 11 10 -2 -22 -39 -41 -30 -13 -3 -5 -16 -26 -32 -35-35 -35 -37 -35 -31 -29 -31 -35 -32 -21 -10 -10 -19 -20 -1-69 -57 -49 -45 -39 -30 -28 -31 -27 -13 -2 -5 -15 -3 1112 3 -7 -10 -14 -15 -22 -31 -37 -32 -17 -10
longitude =74743328 74868400 74993968 75120040 75246616 7537372875501368 75629568 75758320 75887656 76017568 76148080 7627920876388952 76477056 76565456 76654144 76743128 76832400 76921984329429568 329535424 329641792 329748672 329856096 329964032330072512 330181536 330291072 330401184
track =92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 9292 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92113 113 113 113 113 113 113 113 113 113 113 113 113 113113 113 113 113 113 113 113 113 113
time =222780000565705 222780001314719 222780002063733222780002812747 222780003561761 222780004310775 222780005059788222780005808802 222780006557816 22278000730683 222780008055844222780008804858 222780009553872 22278001017805 222780010677393222788257112198 222788257486705 222788257861212 222788258235719222788258610226 222788258984733 222788259359239 222788259733746222788260108253 22278826048276
mean_profile_point_index =1872 1878 1884 1890 1896 1902 1908 19141920 1926 1932 1938 1944 1949 1953 1957 1961 1965 1969 19732306 2309 2312 2315 2318 2321 2327 2330 2333 2336 2339 23422345 2348 2351 2354 2357 2360 2363 2366
flag =0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
latitude =-16225506 -16539731 -16853833 -17167810 -17481660 -17795380-18108966 -18422418 -18735729 -19048899 -19361924 -19674801-19987527 -20248015 -20456329 -20664569 -20872739 -2108083739481297 39628277 39775133 39921866 40068472 40214953 4036130840507533 40653629 40799592 40945423 41091120 41236684 41382111
cycle =331 331 331 331 331 331 331 331 331 331 331 331 331
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331 331 331 331 331 331 331 331 331 331 331 331 331 331331 331 331 331 331 331 331 331 331 331 331 331
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VIII HOW TO DOWNLOAD A PRODUCT
VIII1 Download a product through the MyOcean Web Portal DirectgetfileService
You first need to register Please find below the registration stepshttpwwwmyoceaneuweb34-products-and-services-faqphp1Once registered the MyOcean FAQ httpwwwmyoceaneuweb34-products-and-services-faqwill guide you on How to download a product through the MyOcean Web Portal Directgetfile Service
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IX NEWS AND UPDATES
IX1 [Duacs] Operational news
To be kept informed on events occurring on the satellites and on the eventual interruption of the services of the DUACSprocessing system see the [Duacs] operational news on the Aviso websitehttpwwwavisooceanobscomendataoperational-newsindexhtml
IX2 Updates
To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtmlSince 2010 a complete reprocessing of all altimetry data (cumulated total of about 55 years of data) is available Themain changes introduced in the Duacs DT v300 reprocessed data set in SSALTODUACS reprocessed DT data setare listed herehttpwwwavisooceanobscomfileadmindocumentsdataduacsduacs_DT_2010_reprocessing_impactpdf
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The products lines described in this user manual are the followingSEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005
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The data provided to users have a global coverage (PL SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001)and regional products are also computed over specific areasMediterranean Sea (PL SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002)and Black Sea (PL SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003)Thanks to updates in 2011 and 2012 (see section II) new regional products are now availableEurope (PL SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004)and Arctic (PL SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005)
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II UPDATES IN 2011 AND 2012
This section describes the updates of the SSALTODUACS Near Real Time system that occurred during2011 and 2012 allowing to add new products (Europe and Arctic) the integration of the Cryosat-2 data inthe system the stopping delivery of Envisat data the addition of Jason-1 data on geodetic orbit (j1g)To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtml
II1 Version D of input IGDROGDR Jason-2 data for NRT processing(July 30 2012)
On July 30 2012 the version of Jason-2 IGDROGDR has changed and is now the D version Somecorrections have thus been updated as detailed in tables 3 and 4
II2 Integration of Jason-1 on its geodetic orbit (May 2012)
An anomaly occured on March 3rd 2012 on the Jason-2 mission (see httpwwwavisooceanobscomfractualitesactualitesindexhtmltx_ttnews[tt_news]=1162amptx_ttnews[backPid]=1399ampcHash=d5baeb645e) On April 23rd CNES began to command the satellite into a nadir ori-entation and after some propulsion anomalies CNES and NASA management through the Joint SteeringGroup have directed the Jason-1 Project to then begin a series of maneuvers to place Jason-1 into a neworbit as defined in table 1 After checking the current orbit carefully the operational team determined thata geodetic mission was still possible It was also decided to preserve all remaining fuel for future stationkeeping maneuvers which is mandatory in a geodetic orbit Core payloads were switched ON on May 4thand after some POSEIDON2 radar (PRF) adjustments the mission was resumed on May 7th at 151248UTCBelow are the characteristics of the new orbit which will be maintained as before within +- 1km controlbox at the Equator
Semi major axis 7702437 kmEccentricity 13 to 28 10-4Altitude equator 13240 kmOrbital period 6730s (1h52rsquo10rdquo)Inclination 66042˚Cycle 406 daysSub cycles 39 - 109 - 475 - 1795
days
Table 1 Characteristics of the geodetic orbit for Jason-1 since May 7th 2012
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For this new phase of the Jason-1 mission (called j1g) the cycle numbering will restart at 500 Off-lineproducts will be produced once a day for the IGDR and every 11 days for the GDRrsquos The integration ofJason-1 data in the DUACS system is available since May 25th 2012
II3 Envisat has stopped sending data (April 2012)
Since April 8th 2012 Envisat has stopped sending data to Earth Esarsquos mission control has worked tore-establish contact with the satellite but there has been no reaction from the satellite Thus Esa has de-clared officially the end of mission for Envisat (see httpwwwesaintesaCPSEM1SXSWT1H_index_0html) Therefore no SL TAC NRT data from Envisat can be released since this date
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II4 Integration of the Cryosat2 Mission (February 2012)
Since February 6th 2012 Cryosat-2 mission has been integrated in the DUACS sytem This mission isdedicated to the observation of the floating sea-ice as well as the continental ice sheets but all data acquiredover ocean are valuable for the observation of oceanic circulation and mesoscale variations This majorchange is the result of the long-standing and fruitful partnership between ESA and CNES and a responseto the request from scientific and operational oceanography users [7] The integration of Cryosat-2 impactsthe delivering of Near real time Sea Level Anomalies (SLA)
II41 Generalities about the mission
A Cryosat-2 Processing Prototype (C2P) (described in Boy et al 2011 [2]) has been developed on CNESside to lay the ground for various SAR processing studies The processing chains ingest Level-0 telemetryfiles distributed by ESA and perform the following steps to generate Sea Level Anomalies (SLA) values foreach altimeter measurements
bull Level-1 Decommutation time-tagging and localization of measurements
bull Level-1b Calculation of instrumental corrections and geophysicalmeteorological corrections
bull Level-2 MLE4 waveforms Retracking and calculation of SLA
The prototype processes data almost continuously over ocean either in Low Resolution Mode (LRM) or inthe DopplerSAR mode processed as pseudo-LRM mode allowing to increase the coverage (figure 2)
Figure 2 SSH-MSS for Cryosat-2 with LRM mode only (left) or LRM+pseudo-LRM modes (right)
Although Cryosat-2 raw SSH can be only corrected with GPS-derived ionospheric correction and ECMWFwet troposphere correction validation activities showed (Labroue et al 2011 [25]) that C2P outputs have anaccuracy roughly equivalent to Envisatrsquos Level 2 products if the latter are processed with the same standards
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II42 Integration in DUACS
The Cryosat-2 data are included in the Near Real time process The chain delivers now (for global coverageMediterranean and Black Seas) along track data from Cryosat-2 (SLAs) Note that the products distributedare of Level-3 and donrsquot replace Level-2 products distributed by agenciesThe details of the processing are given in Dibarboure et al 2011 [8]Here we just give an overview the data are computed with the corrections given in section III21 Thefiltering and sub-sampling of SLAs (section III263) are detailed in [8]
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II5 Addition of Europe and Arctic products (January 2012)
Since the MyOcean V2 two new along-track products are computed in Near Real Time intended foraddressing the needs of data assmilation and validation in regional models
bull Following the TAPAS (Tailored Altimeter Product for Assimilation Systems) initiative launched bySL TAC with all the Modeling and Forecasting Centers (MFCs) the Europe regional products (PLSEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004) have been proposed (figure 3) They areavailable in Near Real Time onlyThey are studied to partly fulfil the needs of the Centers with adapted filtering and resolution Thoseparameters have been tuned in order to provide boundary conditions for the Atlantic assimilationmodels They are different from the ones used for Mediterranean and Black Seas products If you needto study the Mediterranean Sea or the Black Sea yoursquod better use the dedicated products describedabove since the processing parameters have been fitted to be adapted to the dynamics of the ocean inthose regions
Figure 3 Coverage of the Europe product for Jason-1 Jason-2 and Envisat from August 18th to September9th 2011
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bull The Arctic along-track products (PL SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005) coverlatitudes between 45 and 82 degrees (figure 4) They are available in Near Real Time only
Figure 4 Coverage of the Arctic region with Envisat from October 28th 2011 to January 3rd 2012
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III SSALTODUACS SYSTEM
III1 Introduction
This chapter presents the input data used by SSALTODUACS system and an overview of the different pro-cessing steps necessary to produce the output dataSSALTODUACS system is made of two components a Near Real Time one (NRT) and a Delayed Time(DT) oneIn NRT the systemrsquos primary objective is to provide operational applications with directly usable high qual-ity altimeter data from all missions availableIn DT it is to maintain a consistent and user-friendly altimeter database using the state-of-the-art recom-mendations from the altimetry communityFollowing figure gives an overview of DUACS system where processing sequences can be divided into 7main steps
bull acquisition
bull homogenization
bull input data quality control
bull multi-mission cross-calibration
bull product generation
bull merging
bull final quality control
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Figure 5 SSALTODUACS processing sequences
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III2 Near Real Time processing steps
III21 Input data models and corrections applied
To produce SLA in near-real time the DUACS system uses two flows based on the same instrumental mea-surements but with a different quality
bull The IGDR that are the latest high-quality altimeter data produced in near-real-time
bull The OGDR that includes real time data (OSTMJason-2 and Jason-1 OSDR) to complete IGDR Thesefast delivery products do not always benefit from precise orbit determination nor from some exter-nal model-based corrections (Dynamic Atmospheric Correction (DAC) Global Ionospheric Maps(GIM))
Integration of OGDR data and the introduction of Jason-2Jason-1 tandem increased the resilience and pre-cision of the system A better restitution of ocean variability is observed especially in high energetic areas
Altimetric product Source Availability Type of orbit
Jason-2 IGDR CNES ~24h CNES MOE GDR-Cuntil 20120730
CNES MOE GDR-Dsince 20120731
OGDR NOAAEUMETSAT ~3 to 5 h
Jason-1 IGDR CNESNASA ~48 h CNES MOE GDR-Dsince 20120507
OGDR CNESNASA ~3 to 12 h
Envisat IGDR ESACNES not deliveredsince 20120408
CNES MOE GDR-Dsince 20120121
FDGDR ESA not deliveredsince 20120408
Cryosat-2 IGDR-like ESACNES ~48 h CNES MOE GDR-D
not delivered
Table 2 SSALTODUACS Near-Real Time Input data overview
See Figure 6 Overview of the near real time system data flow management
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DUACS 2011 NRT product from IGDR1
j2 j1nj1g enn c2Productstandard ref
version C until20120730 and D after
version C version 21 CPP [2]
Orbit CNES MOE GDR-Cuntil 20120730
GDR-D after
CNES MOE GDR-C forj1n and CNES MOE
GDR-D for j1g
CNES MOE GDR-Dfrom 20120121 to
20120408
CNES MOE GDR-D
Ionopheric bi-frequency altimeter range measurements GIM model for cgt64 (Iijima et al1998[24])Dry tropo Model computed from ECMWF Gaussian grids (new S1 and S2 atm tides applied)Wet tropo-sphere
AMR radiometer(enhancement in coastal
regions since20120730)
JMR radiometer MWR radiometer andcorrected from side
lobes
Model computed fromECMWF Gaussian
grids
DAC MOG2D High Resolution forced with ECMWF pressure and wind fields (S1 and S2 wereexcluded) (Carrere and Lyard 2003[3])+ inverse barometer Filtering temporal window is
un-centered (no data in the future)Ocean tide GOT4v8 (S1 and S2 are included) and TPX 072 [16] for Arctic productsPole tide [Wahr 1985 [53]]Solid earthtide
Elastic response to tidal potential [Cartwright and Tayler 1971[5]] [Cartwright andEdden 1973[6]]
Loading tide GOT4v8 (S1 and S2 are included)Sea statebias
Non parametric SSB[Labroue 2004[27]](with cycles J1 1 to 11
using GDR-B standardsuntil 20120730 andderived from Jason-2
after)
Non parametric SSB[Labroue 2004[27]](with cycles 1 to 21
using GDR-Bstandards)
Non parametric SSB[Labroue 2004[27]](with cycles 41 to 60
using GDR-Bstandards)
Same as Jason-2 SSB
Orbit error Global multi-mission crossover minimization (Le Traon and Ogor1998[32])
Long wave-lengh errors
Optimal Interpolation [Le Traon et al 1998[31]]
Intercalibration Reference from cycle20
Mean pro-file (seeIII261)
Computed with cycles11-353 TP data andwith cycles 11-250J1 data referenced[19931999]
TPNJ1N computedwith cycles 369-479TPN data refer-enced [19931999]J1G No MP can beused instead theMSS_CNES_CLS11[39] is used
No Mean Profilecan be used forEnvisat on its neworbit Instead theMSS_CNES_CLS11[39] is used
No Mean Profilecan be used forCryosat-2 Instead theMSS_CNES_CLS11[39] is used
(1) A flag included in the along-track files indicates the source of the production (OGDRFDGDR orIGDR) If flag=0 the processed data comes from OGDRsFDGDRs if flag=1 the processed data comesfrom IGDRs
Table 3 Corrections and models applied in SSALTODUACS NRT products produced from IGDRs
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DUACS 2011 NRT product from OGDR or FDGDR2
j2 j1nj1g ennProduct stan-dard ref
version C until 20120730and D after
version C version 21
Orbit Navigator Extrapolated CNES MOEGDR-D since 20120121
Ionopheric From-dual frequency altimeter range measurements From GIM model fromcycle 65 (Iijima et al1998 [24])
Dry troposphere Model computed from ECMWF Gaussian grids (new S1 and S2 atmospherictides are applied)
Wet tropo-sphere
AMR radiometer(enhancement in coastal
regions since 20120730)
JMR radiometer MWR radiometer andcorrected from side lobes
DAC Inverse Barometer forecastedOcean tide GOT4v8 (S1 and S2 are included) and TPX 072 [16] for Arctic productsPole tide [Wahr 1985 [53]]Solid earth tide Elastic response to tidal potential [Cartwright and Tayler 1971[5]]
[Cartwright and Edden 1973[6]]Loading tide GOT4v8 (S1 and S2 are included)Sea state bias Non parametric SSB
[Labroue 2004[27]] (withcycles J1 1 to 11 usingGDR-B standards until20120730 and derivedfrom Jason-2 after)
Non parametric SSB[Labroue 2004[27]](with cycles 1 to 21 usingGDR-B standards)
Non parametric SSB[Labroue 2004[27]](with cycles 41 to 60using GDR-B standards)
Orbit error Specific filtering of long-wavelength signal3
Long wave-lengh errors
Optimal Interpolation [Le Traon et al 1998[31]]
Intercalibration Reference from cycle 20Mean profile(see III261)
Computed with cycles 11-353 TP data and with cy-cles 11-250 J1 data refer-enced [19931999]
TPNJ1N computedwith cycles 369-479TPN data referenced[19931999] J1G NoMP can be used insteadthe MSS_CNES_CLS11[39] is used
No Mean Profile can beused for Envisat on itsnew orbit Instead theMSS_CNES_CLS11 [39]is used
(2) A flag included in the along-track files indicates the source of the production (OGDRFDGDR orIGDR) If flag=0 the processed data comes from OGDRsFDGDRs if flag=1 the processed data comesfrom IGDRs(3) Specific data processing was applied on long wave-length signal (sectIII23 of the user manual)
Table 4 Corrections and models applied in SSALTODUACS NRT products produced from OG-DRsFDGDRs
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III22 Acquisition
The acquisition process is twofold
bull straightforward retrieval and reformatting of altimeter data and dynamic auxiliary data (pressure andwet troposphere correction grids from ECMWF are provided by Meteo France TEC grids from JPLNRT MOG2D corrections) from external repositories
bull synchronisation process
To be homogenized properly altimeter data sets require various auxiliary data The acquisition softwaredetects downloads and processes incoming data as soon as they are available on remote sites (externaldatabase FTP site) Data are split into passes if necessary If data flows are missing or late the synchroni-sation engine put unusable data in waiting queues and automatically unfreezes them upon reception of themissing auxiliary data This processing step delivers raw data that is to say data that have been dividedinto cycles and passes and ordered chronologicallyFrom SSALTODUACS V80 the acquisition step uses two different data flows in near-real time the OGDRflow (within a few hours) and the IGDR flow (within a few days)For each OGDR input the system checks that no equivalent IGDR entry is available in the data base beforeacquisition for each IGDR input the system checks and delete the equivalent OGDR entry in the data baseThese operations aim to avoid duplicates in SSALTODUACS system
Figure 6 Overview of the near real time system data flow management
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III23 Homogenization
The Homogenization process consists in applying the most recent corrections models and references rec-ommended for altimeter products Each mission is processed separately as its needs depend on the baseinput data The list of corrections and models currently applied is provided in tables 3 and 4 for NRT dataThe system includes SLA filtering to process OGDR data DUACS extract from these data sets the shortscales (space and time) which are useful to better describe the ocean variability in real time and merge thisinformation with a fair description of large scale signals provided by the multi-satellite observation in nearreal time (read IGDR-based DUACS data) Finally an hybrid SLA is computed
Figure 7 Merging pertinent information from IGDR and OGDR processing
III24 Input data quality control
The Input Data Quality Control is a critical process applied to guarantee that DUACS uses only the mostaccurate altimeter data Thanks to the high quality of current missions this process rejects a small percent-age of altimeter measurements but these erroneous data could be the cause of a significant quality lossThe quality control relies on standard raw data editing with quality flags or parameter thresholds but alsoon complex data editing algorithms based on the detection of erroneous artefacts mono and multi-missioncrossover validation and macroscopic statistics to edit out large data flows that do not meet the systemrsquosrequirements
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III25 Multi-mission cross-calibration
The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistentand accurate information It removes any residual orbit error (OE Le Traon and Ogor 1998[32]) or longwavelength error (LWE Le Traon et al 1998[31]) as well as large scale biases and discrepancies betweenvarious data flows
This process is based on two very different algorithms a global multi-mission crossover minimization fororbit error reduction (OER) and Optimal Interpolation (OI) for LWE
Multi-satellite crossover determination is performed on a daily basis All altimeter fields (measurementcorrections and other fields such as bathymetry MSS) are interpolated at crossover locations and datesCrossovers are then appended to the existing crossover database as more altimeter data become availableThis crossover data set is the input of the Orbit Error Reduction (OER) method Using the precision of thereference mission orbit a very accurate orbit error can be estimated This processing step does not concernOGDR dataLWE is mostly due to residual tidal or inverse barometer errors and high frequency ocean signals The OIused for LWE reduction uses precise parameters derived from
bull accurate statistical description of sea level variability
bull localized correlation scales
bull mission-specific noise and precise assumptions on the long wavelength errors to be removed (from arecent analysis of one year of data from each mission)
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III26 Product generation
The product generation process is composed of four steps computation of raw SLA cross-validationfilteringampsub-sampling and generation of by-products
III261 Computation of raw SLA
Since the geoid is not well known yet the SSH cannot be used directly the SSH anomalies are used insteadThey are computed from the difference of the instantaneous SSH - a temporal reference This temporalreference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeattrack analysis cannot be used The errors affecting the SLAs MPs and MSS have different magnitudes andwavelengths The computation of the SLAs and their errors associated are detailed in Dibarboure et al 2010[9]
Use of a Mean ProfileIn the repeat track analysis (when the satellites flies over a repetitive orbit) measurements are re-sampledalong a theoretical ground track (or mean track) associated to each mission Then a Mean Profile (MP) issubtracted from the re-sampled data to obtain SLA The MP is a time average of similarly re-sampled dataover a long period
bull The Mean Profile used for Jason-2 is computed with 10 years of TP (cycles 11 to 353) and 6 years ofJason-1 (cycles 11 to 250)
bull The Mean Profile used from Jason-1 cycle 262 to 374 (where satellites are on interleaved ground-tracks) is computed with 3 years of TP (cycles 369 to 479)
bull No Mean Profile can be used for Envisat on its new orbit (enn) Jason-1 on its geodetic orbit (j1g) norfor Cryosat-2 mission (c2) because there is no repetitive track The MSS must be used instead (seebelow)
Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible
bull Indeed as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide precise cross-track projection andor interpolation schemes are required to avoid errors
bull The mesoscale variability error (which is lt35 cm for MP between 3 to 5 years and lt1cm for WLof 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a prioriknowledge from Sea Level maps derived from previous iterations or from other missions
bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
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bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for Envisat since november 2010 and for Cryosat-2 mission (c2)because the satellite is not in a repetitive orbit phase The alternative is to use the MSS instead The griddedMSS is derived from along track MPs and data from geodetic phases Thus any error on the MP is alsocontained in the MSS There are essentially 4 types of additional errors on gridded MSS which are hard toquantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
Note that for the Arctic regional products the DTU10 MSS [1] is taken into account instead of the CLS01MSS Indeed the accuracy of DTU10 compared to CLS01 is further demonstrated by the significant sealevel anomaly variance reduction found over the whole Arctic Ocean as shown in Prandi et al [42]
III262 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III263 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
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III27 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III271 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
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III272 Performance indicators
To appreciate the quality situation of the DUACS system new performance indicators are computed dailyThey aim at evaluate the status of the main processing steps of the system the input data availability theinput data coverage the input data quality and the output product quality These indicators are computed foreach and every currently working satellite and combined to obtain the overall status
Figure 8 Example with the key performance indicator on 20090627
See the description the latest and previous indicators on Aviso websitehttpwwwavisooceanobscomindexphpid=1516
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III3 Delayed Time processing steps
III31 Input data models and corrections applied
Delayed Time MyOcean products are generated
bull from Aviso GDR products for TP Jason-1 Jason-2 and Envisat (GDR-A cycles 1 to 22 GDR-Bcycles 23 to 85 GDR-C from cycle 86)
bull from NOAA GDR for GFO and from CERSAT (IFREMER) OPR for ERS-1 and ERS-2 (phases C(1st 35-day repeat orbit period) phase E and F (geodetic phases) phase G for ERS-1 (last 35-dayrepeat orbit period tandem phase with ERS-2 phase A for ERS-2 (1st 35-day repeat orbit periodtandem phase with ERS-1))
All GDR products are computed with a Precise Orbit Ephemeris (POE) and are delivered within 2 to 3months depending on the mission For several missions an updated orbit is used
bull For ERS-1amp-2 the orbit used is DGME-04 provided by Delft Institute (httpwwwdeostudelftnl)until June 2003
bull For TopexPoseidon the orbit used is GSFC (std0809) for the whole mission
bull For Envisat CNES POE of GDR-C standard is used for the whole mission
bull For the whole GFO mission the orbit used is GSFC (std0809) and when not available NASA POE isused
Altimetric product Source Availability Type of orbit
TopexPoseidon GDR NASACNES - GSFC POE
Jason-1 GDR (GDR-C) CNESNASA ~40 days CNES POE
Jason-2 GDR (GDR-C) CNESNASA ~60 days CNES POE
GFO GDR NOAA - GSFCNASA POE
ERS-1amp2 IFREMERESA - DGME-04
Envisat (GDR-A GDR-B andGDR-C from cycle 86)
ESA ~2 months CNES POE
Table 5 SSALTODUACS Delayed Time Input data overview
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DU
AC
S20
11D
Tpr
oduc
t(gtV
30
0)j2
j1j1
ntp
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e1e2
ene
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Prod
uct
stan
dard
ref
GD
R-C
OPR
GD
R-A
(Cyc
les
1to
22)
GD
R-B
(cyc
les
23-8
5)
GD
R(N
OA
A)
Orb
itC
nes
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C(I
TR
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last
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ts(T
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Ben
t mod
elB
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odel
(cyc
les
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)G
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cycl
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((Ii
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Dua
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cted
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8m
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From
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ijim
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)
Dry
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here
Mod
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ed)
Wet
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JMR
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Rra
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50km
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the
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rom
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the
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(Sch
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2004
[49]
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thm
(Tra
nan
dO
blig
is
2003
[50]
MW
Rra
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eter
furt
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50km
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ted
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side
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rom
cycl
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and
50km
GFO
radi
omet
er
DA
CM
OG
2DH
igh
Res
olut
ion
forc
edw
ithE
CM
WF
pres
sure
and
win
gfie
lds
(S1
and
S2w
ere
excl
uded
)+in
vers
eba
rom
eter
com
pute
dfr
omre
ctan
gula
rgri
ds
Tabl
e6
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(1
2)
Page 33
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
j2j1
j1n
tptp
ne1
e2en
enn
g2O
cean
tide
GO
T4v
7(S
1an
dS2
are
incl
uded
)Po
letid
e[W
ahr
1985
[53]
]So
lidea
rth
tide
Ela
stic
resp
onse
totid
alpo
tent
ial[
Car
twri
ghta
ndTa
yler
197
1[5]
][C
artw
righ
tand
Edd
en1
973[
6]]
Loa
ding
tide
GO
T4v
7(S
1pa
ram
eter
isin
clud
ed)
Sea
stat
ebi
asN
onpa
ram
etri
cSS
B[G
aspa
reta
l20
02[2
0]]
Non
para
met
ric
SSB
[NT
ran
and
al2
010[
51]]
BM
3[G
aspa
ran
dO
gor
1994
[17]
]
Non
para
met
ric
SSB
[Mer
tzet
al
2005
[38]
]
Non
para
met
ric
SSB
[Gas
pare
tal
2002
]w
ithG
DR
-Bst
anda
rds
forc
ycle
s9
to85
and
with
GD
R-C
stan
dard
sfr
omcy
cle
86
Non
para
met
ric
SSB
[NT
ran
etal
20
10[5
1]]
Orb
iter
ror
Glo
bal m
ulti-
mis
sion
cros
sove
rmin
imiz
atio
n(L
eTr
aon
and
Ogo
r19
98[3
2])
Lon
gw
ave-
leng
her
rors
Opt
imal
Inte
rpol
atio
n(L
eTr
aon
etal
19
98[3
1])
Inte
rcal
ibra
tion
Ref
eren
cefr
omcy
cle
11R
efer
ence
from
cycl
e1
to35
4C
orre
ctio
nof
regi
onal
bias
J2J
1de
duce
dfr
omin
terc
alib
ratio
nph
ase
(cyc
le11
J2)
Cor
rect
ion
ofgl
obal
biai
sJ1
TP
deacutedu
ced
from
inte
rcal
ibra
tion
phas
e(c
ycle
s11
J1)
Mea
npr
o-fil
e(s
eeII
I36
1)
Com
pute
dw
ithcy
cles
11-3
53T
Pda
taan
dw
ithcy
cles
11-2
50J1
data
ref
eren
ced
[199
319
99]
TP
J1 c
ompu
ted
with
cycl
es11
-353
TP
data
and
with
cycl
es11
-250
J1da
tar
efer
ence
d[1
993
1999
]T
PNJ
1Nc
ompu
ted
with
cycl
es36
9-47
9T
PNda
tar
efer
ence
d[1
993
1999
]
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
ref
eren
ced
[199
319
99]
EN
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
re
fere
nced
[199
319
99]
EN
Nu
seof
MSS
_CN
ES_
CL
S11
[39]
Com
pute
dw
ithcy
cles
37-1
87G
2da
ta
refe
renc
ed[1
993
1999
]
Peri
odof
use
from
cycl
e9
from
cycl
e9
cycl
es1
to48
1cy
cles
15to
43In
clud
ing
E-F
geod
etic
phas
es
cycl
es1
to83
from
cycl
e9
cycl
es37
to22
2
Tabl
e7
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(2
2)
Page 34
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III32 Acquisition
The acqusition process in Delayed time is much simpler than in Near Real time it consists in a synchronisa-tion process of all the auxiliary data required to homogenize propely the altimeter data sets The acquisitionstep uses the GDRs or the OPRs provided by the agencies
III33 Homogenization
The Homogenization process consists in applying the most recent corrections models and references rec-ommended for altimeter products Each mission is processed separately as its needs depend on the baseinput data The list of corrections and models currently applied is provided in tables 6 and 7 for DT data
III34 Input data quality control
The Input Data Quality Control is a critical process applied to guarantee that DUACS uses only the mostaccurate altimeter data Thanks to the high quality of current missions this process rejects a small percent-age of altimeter measurements but these erroneous data could be the cause of a significant quality lossThe quality control relies on standard raw data editing with quality flags or parameter thresholds but alsoon complex data editing algorithms based on the detection of erroneous artefacts mono and multi-missioncrossover validation and macroscopic statistics to edit out large data flows that do not meet the systemrsquosrequirements
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III35 Multi-mission cross-calibration
The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistentand accurate information It removes any residual orbit error (OE Le Traon and Ogor 1998[32]) or longwavelength error (LWE Le Traon et al 1998[31]) as well as large scale biases and discrepancies betweenvarious data flows
This process is based on two very different algorithms a global multi-mission crossover minimization fororbit error reduction (OER) and Optimal Interpolation (OI) for LWE
Multi-satellite crossover determination is performed on a daily basis All altimeter fields (measurementcorrections and other fields such as bathymetry MSS) are interpolated at crossover locations and datesCrossovers are then appended to the existing crossover database as more altimeter data become availableThis crossover data set is the input of the Orbit Error Reduction (OER) method Using the precision of thereference mission orbit a very accurate orbit error can be estimated LWE is mostly due to residual tidalor inverse barometer errors and high frequency ocean signals The OI used for LWE reduction uses preciseparameters derived from
bull accurate statistical description of sea level variability
bull localized correlation scales
bull mission-specific noise and precise assumptions on the long wavelength errors to be removed (from arecent analysis of one year of data from each mission)
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III36 Product generation
The product generation process is composed of four steps computation of raw SLA cross-validationfilteringampsub-sampling and generation of by-products
III361 Computation of raw SLA
Since the geoid is not well known yet the SSH cannot be used directly the SSH anomalies are used insteadThey are computed from the difference of the instantaneous SSH - a temporal reference This temporalreference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeattrack analysis cannot be used The errors affecting the SLAs MPs and MSS have different magnitudes andwavelengths The computation of the SLAs and their errors associated are detailed in Dibarboure et al 2010[9]
Use of a Mean ProfileIn the repeat track analysis (when the satellites flies over a repetitive orbit) measurements are re-sampledalong a theoretical ground track (or mean track) associated to each mission Then a Mean Profile (MP) issubtracted from the re-sampled data to obtain SLA The MP is a time average of similarly re-sampled dataover a long period
bull The Mean Profile used for TP (cycles 1 to 364) Jason-1 (cycles 1 to 259) and Jason-2 is computedwith 10 years of TP (cycles 11 to 353) and 6 years of Jason-1 (cycles 11 to 250)
bull The Mean Profile used for TP (cycles 368 to 481) and from Jason-1 cycle 262 to 374 (where satellitesare on interleaved ground-tracks) is computed with 3 years of TP (cycles 369 to 479)
bull The Mean Profile used for ERS-1 in its 35 days repetitive orbit mission ERS-2 and Envisat (only forthe first orbit before November 2010) is computed with 8 years of ERS-2 (cycles 1 to 85) and 6 yearsof Envisat (cycles 10 to 72)
bull No Mean Profile can be used for Envisat on its new orbit (enn) Jason-1 on its geodetic orbit (j1g)because there is no repetitive track The MSS must be used instead (see below)
bull The Mean Profile used for GFO is computed with 7 years of GFO cycles 37 to 187
Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible
bull Indeed as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide precise cross-track projection andor interpolation schemes are required to avoid errors
bull The mesoscale variability error (which is lt35 cm for MP between 3 to 5 years and lt1cm for WLof 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a prioriknowledge from Sea Level maps derived from previous iterations or from other missions
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PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for ERS-1 for its 168 days geodetic mission (phases E-F from April1994 to March 1995) or for Envisat since november 2010 because the satellite is not in a repetitive orbitphase The alternative is to use the MSS instead The gridded MSS is derived from along track MPs anddata from geodetic phases Thus any error on the MP is also contained in the MSS There are essentially 4types of additional errors on gridded MSS which are hard to quantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
III362 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III363 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
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PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III37 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III371 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
Page 39
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
IV MYOCEAN PRODUCTS
IV1 Near Real Time Products
The purpose of the NRT DUACS component is the acquisition of altimeter data from various altimeter mis-sions in near-real time (ie within a few days at most) the validation and correction of these altimeter datasets (ie edition and selection update of corrections and homogenization orbit error reduction) in order toproduce each day along-track productsProducts are as follows
Along-track products global and regional (Mediterranean and Black Seas Arctic Ocean and Europeareas)
bull Sea Level Anomaly (NRT-SLA) for each mission with NRT-SLA ephemeris
IV11 Delay of the products
The availability of the products in near real time is three to twelve hours after the measurement for along-track products Those products are delivered every day
IV12 Temporal availibility
The following table presents the available products by mission and by data periodNear real time products
NRT Jason-2 Jason-1 and Jason-1geodetic
Envisat new Cryosat-2
Temporal Time availability ymlowast
ongoingymlowast-20120303 for
repeat track and20120507-ongoing for
geodetic track
ymlowast
2012040820120101
ongoing
NRT-SLA X X X X
lowastym the temporal coverage for NRT products is fluctuating and depends on updates of Delayed Time prod-ucts When DT products are updated (3 to 4 times per year) the oldest NRT products are replaced by thebetter quality DT products so that the 2 series are overlapping on few weeks or few months
IV2 Delayed Time Products
The Delayed Time component of SSALTODUACS system is responsible for the production of processedJason-1 Jason-2 TP Envisat GFO ERS12 and even Geosat data in order to provide a homogeneousinter-calibrated and highly accurate long time series of SLA DT products are more precise than NRT products Two reasons explain this quality difference The firstone is the better intrinsic quality of the POE orbit used in the GDR processing The second reason is that
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in the DT DUACS processing the products can be computed optimally with a centred computation timewindow for OER LWE On the contrary in NRT case future data are not available so the computationtime window is not centred and therefore not optimalAs for NRT products improved altimeter corrections and processing algorithms are used ocean tide modelto correct altimeter data improved methods for orbit error reduction and mapping
Along-Track products global and regional (Mediterranean and Black Seas)
bull Sea Level Anomaly (DT-SLA) for each mission
IV21 Delay of the products
Weekly products are delivered The availability of the products in delayed time is at the best two monthsafter the date of the measurement The product generation needs all the GDR data of all the missions to takeinto account the best corrections as possible The time delay can be longer in the case of a missing mission
IV22 Temporal availibility
The following table presents the available products by mission and by data periodDelayed time SSALTODUACS products
Upd Jason-2 Jason-1new6
Jason-1 GFO Envisatnew6
Envisat ERS-16
ERS-2Topexnew6
Topex
TemporalTimeavailabil-ity
200810ymlowast
200902ymlowast
200204200810
200001200809
201010ymlowast
200210201010
199210200304
200209200510
199209200204
DT-SLA X X X X X X X X X
lowast ym those dates are updated regularly (3 to 4 times per year) and are avalaible when you download thedata at httpwwwmyoceaneuweb24-cataloguephp6 Jason-1 new orbit starting 200809 Envisat new orbit starting 201010 TP new orbit starting 200209 ERS-1The geodetic phases (E-F) are included There are no ERS-1 data between December 23 1993 and April 10 1994(ERS-1 phase D - 2nd ice phase) Note that during that time products are based only on TopexPoseidon data
Page 41
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V DESCRIPTION OF THE PRODUCT SPECIFICATION
V1 General information
Product Specification SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001
Geographical coverage global
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 20-50km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001 Product Specification
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
Product Specification SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002
Geographical coverage 55˚W-35˚E 30˚N-46˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002 Product Specification
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
Product Specification SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003
Geographical coverage 27˚E-42˚E 40˚N-47˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003 Product Specification
Page 44
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
Product Specification SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004
Geographical coverage 25˚W-42˚E 21˚N-66˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004 Product Specification
Page 45
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
Product Specification SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005
Geographical coverage 0˚W-360˚E 50˚N-82˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005 Product Specification
Page 46
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
VI NOMENCLATURE OF FILES
VI1 Nomenclature of files downloaded through the MyOcean Web PortalDirectgetfile Service
VI11 Nomenclature of the product line
The description of the syntax for the SL TAC SLA products line is given by
SEALEVEL_ltREGIONgt_SLA_L3_ltDELAYgt_OBSERVATIONS_008_ltZONEgt_ltLETTERgtwhere
REGION GLO global geographic coverage product
BS Black Sea products
MED Mediterranean products
ARC Arctic products (for NRT products)
EUROPE Europe products (for NRT products)
DELAY NRT near real time products
RAN delayed time or reanalysis products
ZONE 001 number on 3 digits
002
003
004
LETTER a letter on 1 digit
b
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VI12 Nomenclature of the datasets
The nomenclature used is
dataset-duacs-ltdelaygt-ltzonegt-ltmissiongt-lttype of slagt-l3where the fileds in ltgt are described below
delay nrt near-real time productsran delayed time products
zone global global geographic coverage productmedsea Mediterranean productsblacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1 (only for ran)e2 ERS-2 (only for ran)tp TOPEXPoseidon (only for ran)tpn TOPEXPoseidon on its new orbit (only for
ran)g2 GFO (only for ran)j1 Jason-1 (only for ran)j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisat (only for ran)enn Envisat on its new orbitc2 Cryosat-2 (only for nrt)
type of sla sla filtered slasla_unfiltered non filtered sla (only for ran products)
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
VI13 Nomenclature of the NetCdf files
The nomenclature used is
ltdelaygt_ltzonegt_ltmissiongt_sla_ltvariablegt_ltdatebegingt_ltdateendgt_ltdateprodgtnc where the fileds in ltgt are de-scribed below
delay nrt near-real time productsdt delayed time products
zone global global geographic coverage productmed Mediterranean products (for dt)mfstep Mediterranean products (for nrt)blacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1e2 ERS-2tp TOPEXPoseidontpn TOPEXPoseidon on its new orbitg2 GFOj1 Jason-1j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisatenn Envisat on its new orbitc2 Cryosat-2
variable vfec filtered and sub-sampled slavxxc non filtered and non sub-sampled sla (only
for dt)datebegin YYYYMMDD() beginning date of the datasetdateend YYYYMMDD() end date of the datasetdateprod YYYYMMDD production date of the dataset
() For dt data as the dates in the file names are rounded the user wanting data for date T has to read the filescontaining dates T+1 and T-1 in their name and check inside the files if there are some data for date T
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
VII DATA FORMAT
This chapter presents the data storage format used for MyOcean products
VII1 NetCdf
The products are stored using the NetCDF format NetCDF (network Common Data Form) is an interface for array-oriented data access and a library that provides an implementation of the interface The netCDF library also definesa machine-independent format for representing scientific data Together the interface library and format support thecreation access and sharing of scientific data The netCDF software was developed at the Unidata Program Center inBoulder Colorado The netCDF libraries define a machine-independent format for representing scientific data Pleasesee Unidata NetCDF pages for more information and to retreive NetCDF software package onhttpwwwunidataucaredupackagesnetcdfindexhtml
NetCDF data is
bull Self-Describing A netCDF file includes information about the data it contains
bull Architecture-independent A netCDF file is represented in a form that can be accessed by computers with dif-ferent ways of storing integers characters and floating-point numbers
bull Direct-access A small subset of a large dataset may be accessed efficiently without first reading through allthe preceding data
bull Appendable Data can be appended to a netCDF dataset along one dimension without copying the dataset orredefining its structure The structure of a netCDF dataset can be changed though this sometimes causes thedataset to be copied
bull Sharable One writer and multiple readers may simultaneously access the same netCDF file
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
VII2 Structure and semantic of NetCDF along-track files
The NetCDF Sea Level TAC files are based on the attribute data tags defined by the Cooperative OceanAtmosphereResearch Data Service (COARDS) and Climate and Forecast (CF) metadata conventions The CF convention gener-alises and extends the COARDS convention but relaxes the COARDS constraints on dimension and order and specifiesmethods for reducing the size of datasetsA wide range of software are available to write or read NetCDFCF files API are made available by UNIDATA(httpwwwunidataucaredusoftwarenetcdf)
bull CC++Fortran
bull Java
bull MATLAB Objective-C Perl Python R Ruby TclTk
In addition to these conventions the files are using a common structure and semantic
bull 1 dimension is defined
ndash time it is used to check NetCDF variables depending on time
bull 8 variables are defined
ndash short SLA contains the Sea Level Anomaly values for each time given
ndash int longitude contains the longitude for each measurement
ndash short track contains the track number for each measurement
ndash double time contains the time in days since 1950-01-01 000000 UTC for each measurement
ndash short mean_profile_point_index index of the corrsponding point in the track of the mean profile
ndash byte flag flag=0 the processed data comes from OGDR if flag=1 the processed data comes from theIGDR
ndash int latitude contains the latitude for each measurement
ndash short cycle contains the cycle number for each measurement
bull global attributes
ndash the global attributes gives information about the creation of the file
Example of a NetCDF sla file
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netcdf nrt_global_j1_sla_vfec_20101230_20101230_20101230 dimensions
time = 10385 variables
short SLA(time) SLAcoordinates = longitude latitude SLAlong_name = Sea Level Anomaly SLA_FillValue = 32767s SLAadd_offset = 0 SLAscale_factor = 0001 SLAunits = m SLAstandard_name = sea_surface_height_above_sea_level
int longitude(time) longitudelong_name = Longitude of measurement longitude_FillValue = 2147483647 longitudeadd_offset = 0 longitudestandard_name = longitude longitudescale_factor = 1e-06 longitudeunits = degrees_east
short track(time) tracklong_name = Track in cycle the measurement belongs to track_FillValue = 32767s trackunits = 1 trackcoordinates = longitude latitude
double time(time) timelong_name = Time of measurement time_FillValue = 184467440737096e+19 timeaxis = T timestandard_name = time timeunits = days since 1950-01-01 000000 UTC
int latitude(time) latitudelong_name = Latitude of measurement latitude_FillValue = 2147483647 latitudeadd_offset = 0 latitudestandard_name = latitude latitudescale_factor = 1e-06 latitudeunits = degrees_north
short flag(time) flagcoordinates = longitude latitude flag_FillValue = 3267s flaglong_name = data origin flagflag_values = 1s 0s flagflag_meanings = igdr_like non_igdr_like flagcomment = The origin of the data is determined by the types of geophysical datarecords (GDR) used in computation of the SLA 1 for the Interim GDR (IGDR) and0 for Operational GDR (OGDR)
short cycle(time) cyclelong_name = Cycle the measurement belongs to cycle_FillValue = 32767s cycleunits = 1 cyclecoordinates = longitude latitude
global attributeshistory = 22-Feb-2011 155243 CET File created by the SSLATODUACS system version 1001 comment = Produce from ENVISAT Extension Phase satellite altimetry data institution = CLSCNES
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references = httpwwwavisooceanobscomfileadmindocumentsdatatoolshdbk_duacspdf source = satellite altimetry title = along track Sea Level Anomaly Conventions = CF-14
dataSLA =
7 7 11 10 -2 -22 -39 -41 -30 -13 -3 -5 -16 -26 -32 -35-35 -35 -37 -35 -31 -29 -31 -35 -32 -21 -10 -10 -19 -20 -1-69 -57 -49 -45 -39 -30 -28 -31 -27 -13 -2 -5 -15 -3 1112 3 -7 -10 -14 -15 -22 -31 -37 -32 -17 -10
longitude =74743328 74868400 74993968 75120040 75246616 7537372875501368 75629568 75758320 75887656 76017568 76148080 7627920876388952 76477056 76565456 76654144 76743128 76832400 76921984329429568 329535424 329641792 329748672 329856096 329964032330072512 330181536 330291072 330401184
track =92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 9292 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92113 113 113 113 113 113 113 113 113 113 113 113 113 113113 113 113 113 113 113 113 113 113
time =222780000565705 222780001314719 222780002063733222780002812747 222780003561761 222780004310775 222780005059788222780005808802 222780006557816 22278000730683 222780008055844222780008804858 222780009553872 22278001017805 222780010677393222788257112198 222788257486705 222788257861212 222788258235719222788258610226 222788258984733 222788259359239 222788259733746222788260108253 22278826048276
mean_profile_point_index =1872 1878 1884 1890 1896 1902 1908 19141920 1926 1932 1938 1944 1949 1953 1957 1961 1965 1969 19732306 2309 2312 2315 2318 2321 2327 2330 2333 2336 2339 23422345 2348 2351 2354 2357 2360 2363 2366
flag =0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
latitude =-16225506 -16539731 -16853833 -17167810 -17481660 -17795380-18108966 -18422418 -18735729 -19048899 -19361924 -19674801-19987527 -20248015 -20456329 -20664569 -20872739 -2108083739481297 39628277 39775133 39921866 40068472 40214953 4036130840507533 40653629 40799592 40945423 41091120 41236684 41382111
cycle =331 331 331 331 331 331 331 331 331 331 331 331 331
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331 331 331 331 331 331 331 331 331 331 331 331 331 331331 331 331 331 331 331 331 331 331 331 331 331
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VIII HOW TO DOWNLOAD A PRODUCT
VIII1 Download a product through the MyOcean Web Portal DirectgetfileService
You first need to register Please find below the registration stepshttpwwwmyoceaneuweb34-products-and-services-faqphp1Once registered the MyOcean FAQ httpwwwmyoceaneuweb34-products-and-services-faqwill guide you on How to download a product through the MyOcean Web Portal Directgetfile Service
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IX NEWS AND UPDATES
IX1 [Duacs] Operational news
To be kept informed on events occurring on the satellites and on the eventual interruption of the services of the DUACSprocessing system see the [Duacs] operational news on the Aviso websitehttpwwwavisooceanobscomendataoperational-newsindexhtml
IX2 Updates
To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtmlSince 2010 a complete reprocessing of all altimetry data (cumulated total of about 55 years of data) is available Themain changes introduced in the Duacs DT v300 reprocessed data set in SSALTODUACS reprocessed DT data setare listed herehttpwwwavisooceanobscomfileadmindocumentsdataduacsduacs_DT_2010_reprocessing_impactpdf
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The data provided to users have a global coverage (PL SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001)and regional products are also computed over specific areasMediterranean Sea (PL SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002)and Black Sea (PL SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003)Thanks to updates in 2011 and 2012 (see section II) new regional products are now availableEurope (PL SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004)and Arctic (PL SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005)
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II UPDATES IN 2011 AND 2012
This section describes the updates of the SSALTODUACS Near Real Time system that occurred during2011 and 2012 allowing to add new products (Europe and Arctic) the integration of the Cryosat-2 data inthe system the stopping delivery of Envisat data the addition of Jason-1 data on geodetic orbit (j1g)To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtml
II1 Version D of input IGDROGDR Jason-2 data for NRT processing(July 30 2012)
On July 30 2012 the version of Jason-2 IGDROGDR has changed and is now the D version Somecorrections have thus been updated as detailed in tables 3 and 4
II2 Integration of Jason-1 on its geodetic orbit (May 2012)
An anomaly occured on March 3rd 2012 on the Jason-2 mission (see httpwwwavisooceanobscomfractualitesactualitesindexhtmltx_ttnews[tt_news]=1162amptx_ttnews[backPid]=1399ampcHash=d5baeb645e) On April 23rd CNES began to command the satellite into a nadir ori-entation and after some propulsion anomalies CNES and NASA management through the Joint SteeringGroup have directed the Jason-1 Project to then begin a series of maneuvers to place Jason-1 into a neworbit as defined in table 1 After checking the current orbit carefully the operational team determined thata geodetic mission was still possible It was also decided to preserve all remaining fuel for future stationkeeping maneuvers which is mandatory in a geodetic orbit Core payloads were switched ON on May 4thand after some POSEIDON2 radar (PRF) adjustments the mission was resumed on May 7th at 151248UTCBelow are the characteristics of the new orbit which will be maintained as before within +- 1km controlbox at the Equator
Semi major axis 7702437 kmEccentricity 13 to 28 10-4Altitude equator 13240 kmOrbital period 6730s (1h52rsquo10rdquo)Inclination 66042˚Cycle 406 daysSub cycles 39 - 109 - 475 - 1795
days
Table 1 Characteristics of the geodetic orbit for Jason-1 since May 7th 2012
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For this new phase of the Jason-1 mission (called j1g) the cycle numbering will restart at 500 Off-lineproducts will be produced once a day for the IGDR and every 11 days for the GDRrsquos The integration ofJason-1 data in the DUACS system is available since May 25th 2012
II3 Envisat has stopped sending data (April 2012)
Since April 8th 2012 Envisat has stopped sending data to Earth Esarsquos mission control has worked tore-establish contact with the satellite but there has been no reaction from the satellite Thus Esa has de-clared officially the end of mission for Envisat (see httpwwwesaintesaCPSEM1SXSWT1H_index_0html) Therefore no SL TAC NRT data from Envisat can be released since this date
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II4 Integration of the Cryosat2 Mission (February 2012)
Since February 6th 2012 Cryosat-2 mission has been integrated in the DUACS sytem This mission isdedicated to the observation of the floating sea-ice as well as the continental ice sheets but all data acquiredover ocean are valuable for the observation of oceanic circulation and mesoscale variations This majorchange is the result of the long-standing and fruitful partnership between ESA and CNES and a responseto the request from scientific and operational oceanography users [7] The integration of Cryosat-2 impactsthe delivering of Near real time Sea Level Anomalies (SLA)
II41 Generalities about the mission
A Cryosat-2 Processing Prototype (C2P) (described in Boy et al 2011 [2]) has been developed on CNESside to lay the ground for various SAR processing studies The processing chains ingest Level-0 telemetryfiles distributed by ESA and perform the following steps to generate Sea Level Anomalies (SLA) values foreach altimeter measurements
bull Level-1 Decommutation time-tagging and localization of measurements
bull Level-1b Calculation of instrumental corrections and geophysicalmeteorological corrections
bull Level-2 MLE4 waveforms Retracking and calculation of SLA
The prototype processes data almost continuously over ocean either in Low Resolution Mode (LRM) or inthe DopplerSAR mode processed as pseudo-LRM mode allowing to increase the coverage (figure 2)
Figure 2 SSH-MSS for Cryosat-2 with LRM mode only (left) or LRM+pseudo-LRM modes (right)
Although Cryosat-2 raw SSH can be only corrected with GPS-derived ionospheric correction and ECMWFwet troposphere correction validation activities showed (Labroue et al 2011 [25]) that C2P outputs have anaccuracy roughly equivalent to Envisatrsquos Level 2 products if the latter are processed with the same standards
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II42 Integration in DUACS
The Cryosat-2 data are included in the Near Real time process The chain delivers now (for global coverageMediterranean and Black Seas) along track data from Cryosat-2 (SLAs) Note that the products distributedare of Level-3 and donrsquot replace Level-2 products distributed by agenciesThe details of the processing are given in Dibarboure et al 2011 [8]Here we just give an overview the data are computed with the corrections given in section III21 Thefiltering and sub-sampling of SLAs (section III263) are detailed in [8]
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II5 Addition of Europe and Arctic products (January 2012)
Since the MyOcean V2 two new along-track products are computed in Near Real Time intended foraddressing the needs of data assmilation and validation in regional models
bull Following the TAPAS (Tailored Altimeter Product for Assimilation Systems) initiative launched bySL TAC with all the Modeling and Forecasting Centers (MFCs) the Europe regional products (PLSEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004) have been proposed (figure 3) They areavailable in Near Real Time onlyThey are studied to partly fulfil the needs of the Centers with adapted filtering and resolution Thoseparameters have been tuned in order to provide boundary conditions for the Atlantic assimilationmodels They are different from the ones used for Mediterranean and Black Seas products If you needto study the Mediterranean Sea or the Black Sea yoursquod better use the dedicated products describedabove since the processing parameters have been fitted to be adapted to the dynamics of the ocean inthose regions
Figure 3 Coverage of the Europe product for Jason-1 Jason-2 and Envisat from August 18th to September9th 2011
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bull The Arctic along-track products (PL SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005) coverlatitudes between 45 and 82 degrees (figure 4) They are available in Near Real Time only
Figure 4 Coverage of the Arctic region with Envisat from October 28th 2011 to January 3rd 2012
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III SSALTODUACS SYSTEM
III1 Introduction
This chapter presents the input data used by SSALTODUACS system and an overview of the different pro-cessing steps necessary to produce the output dataSSALTODUACS system is made of two components a Near Real Time one (NRT) and a Delayed Time(DT) oneIn NRT the systemrsquos primary objective is to provide operational applications with directly usable high qual-ity altimeter data from all missions availableIn DT it is to maintain a consistent and user-friendly altimeter database using the state-of-the-art recom-mendations from the altimetry communityFollowing figure gives an overview of DUACS system where processing sequences can be divided into 7main steps
bull acquisition
bull homogenization
bull input data quality control
bull multi-mission cross-calibration
bull product generation
bull merging
bull final quality control
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Figure 5 SSALTODUACS processing sequences
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III2 Near Real Time processing steps
III21 Input data models and corrections applied
To produce SLA in near-real time the DUACS system uses two flows based on the same instrumental mea-surements but with a different quality
bull The IGDR that are the latest high-quality altimeter data produced in near-real-time
bull The OGDR that includes real time data (OSTMJason-2 and Jason-1 OSDR) to complete IGDR Thesefast delivery products do not always benefit from precise orbit determination nor from some exter-nal model-based corrections (Dynamic Atmospheric Correction (DAC) Global Ionospheric Maps(GIM))
Integration of OGDR data and the introduction of Jason-2Jason-1 tandem increased the resilience and pre-cision of the system A better restitution of ocean variability is observed especially in high energetic areas
Altimetric product Source Availability Type of orbit
Jason-2 IGDR CNES ~24h CNES MOE GDR-Cuntil 20120730
CNES MOE GDR-Dsince 20120731
OGDR NOAAEUMETSAT ~3 to 5 h
Jason-1 IGDR CNESNASA ~48 h CNES MOE GDR-Dsince 20120507
OGDR CNESNASA ~3 to 12 h
Envisat IGDR ESACNES not deliveredsince 20120408
CNES MOE GDR-Dsince 20120121
FDGDR ESA not deliveredsince 20120408
Cryosat-2 IGDR-like ESACNES ~48 h CNES MOE GDR-D
not delivered
Table 2 SSALTODUACS Near-Real Time Input data overview
See Figure 6 Overview of the near real time system data flow management
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DUACS 2011 NRT product from IGDR1
j2 j1nj1g enn c2Productstandard ref
version C until20120730 and D after
version C version 21 CPP [2]
Orbit CNES MOE GDR-Cuntil 20120730
GDR-D after
CNES MOE GDR-C forj1n and CNES MOE
GDR-D for j1g
CNES MOE GDR-Dfrom 20120121 to
20120408
CNES MOE GDR-D
Ionopheric bi-frequency altimeter range measurements GIM model for cgt64 (Iijima et al1998[24])Dry tropo Model computed from ECMWF Gaussian grids (new S1 and S2 atm tides applied)Wet tropo-sphere
AMR radiometer(enhancement in coastal
regions since20120730)
JMR radiometer MWR radiometer andcorrected from side
lobes
Model computed fromECMWF Gaussian
grids
DAC MOG2D High Resolution forced with ECMWF pressure and wind fields (S1 and S2 wereexcluded) (Carrere and Lyard 2003[3])+ inverse barometer Filtering temporal window is
un-centered (no data in the future)Ocean tide GOT4v8 (S1 and S2 are included) and TPX 072 [16] for Arctic productsPole tide [Wahr 1985 [53]]Solid earthtide
Elastic response to tidal potential [Cartwright and Tayler 1971[5]] [Cartwright andEdden 1973[6]]
Loading tide GOT4v8 (S1 and S2 are included)Sea statebias
Non parametric SSB[Labroue 2004[27]](with cycles J1 1 to 11
using GDR-B standardsuntil 20120730 andderived from Jason-2
after)
Non parametric SSB[Labroue 2004[27]](with cycles 1 to 21
using GDR-Bstandards)
Non parametric SSB[Labroue 2004[27]](with cycles 41 to 60
using GDR-Bstandards)
Same as Jason-2 SSB
Orbit error Global multi-mission crossover minimization (Le Traon and Ogor1998[32])
Long wave-lengh errors
Optimal Interpolation [Le Traon et al 1998[31]]
Intercalibration Reference from cycle20
Mean pro-file (seeIII261)
Computed with cycles11-353 TP data andwith cycles 11-250J1 data referenced[19931999]
TPNJ1N computedwith cycles 369-479TPN data refer-enced [19931999]J1G No MP can beused instead theMSS_CNES_CLS11[39] is used
No Mean Profilecan be used forEnvisat on its neworbit Instead theMSS_CNES_CLS11[39] is used
No Mean Profilecan be used forCryosat-2 Instead theMSS_CNES_CLS11[39] is used
(1) A flag included in the along-track files indicates the source of the production (OGDRFDGDR orIGDR) If flag=0 the processed data comes from OGDRsFDGDRs if flag=1 the processed data comesfrom IGDRs
Table 3 Corrections and models applied in SSALTODUACS NRT products produced from IGDRs
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DUACS 2011 NRT product from OGDR or FDGDR2
j2 j1nj1g ennProduct stan-dard ref
version C until 20120730and D after
version C version 21
Orbit Navigator Extrapolated CNES MOEGDR-D since 20120121
Ionopheric From-dual frequency altimeter range measurements From GIM model fromcycle 65 (Iijima et al1998 [24])
Dry troposphere Model computed from ECMWF Gaussian grids (new S1 and S2 atmospherictides are applied)
Wet tropo-sphere
AMR radiometer(enhancement in coastal
regions since 20120730)
JMR radiometer MWR radiometer andcorrected from side lobes
DAC Inverse Barometer forecastedOcean tide GOT4v8 (S1 and S2 are included) and TPX 072 [16] for Arctic productsPole tide [Wahr 1985 [53]]Solid earth tide Elastic response to tidal potential [Cartwright and Tayler 1971[5]]
[Cartwright and Edden 1973[6]]Loading tide GOT4v8 (S1 and S2 are included)Sea state bias Non parametric SSB
[Labroue 2004[27]] (withcycles J1 1 to 11 usingGDR-B standards until20120730 and derivedfrom Jason-2 after)
Non parametric SSB[Labroue 2004[27]](with cycles 1 to 21 usingGDR-B standards)
Non parametric SSB[Labroue 2004[27]](with cycles 41 to 60using GDR-B standards)
Orbit error Specific filtering of long-wavelength signal3
Long wave-lengh errors
Optimal Interpolation [Le Traon et al 1998[31]]
Intercalibration Reference from cycle 20Mean profile(see III261)
Computed with cycles 11-353 TP data and with cy-cles 11-250 J1 data refer-enced [19931999]
TPNJ1N computedwith cycles 369-479TPN data referenced[19931999] J1G NoMP can be used insteadthe MSS_CNES_CLS11[39] is used
No Mean Profile can beused for Envisat on itsnew orbit Instead theMSS_CNES_CLS11 [39]is used
(2) A flag included in the along-track files indicates the source of the production (OGDRFDGDR orIGDR) If flag=0 the processed data comes from OGDRsFDGDRs if flag=1 the processed data comesfrom IGDRs(3) Specific data processing was applied on long wave-length signal (sectIII23 of the user manual)
Table 4 Corrections and models applied in SSALTODUACS NRT products produced from OG-DRsFDGDRs
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III22 Acquisition
The acquisition process is twofold
bull straightforward retrieval and reformatting of altimeter data and dynamic auxiliary data (pressure andwet troposphere correction grids from ECMWF are provided by Meteo France TEC grids from JPLNRT MOG2D corrections) from external repositories
bull synchronisation process
To be homogenized properly altimeter data sets require various auxiliary data The acquisition softwaredetects downloads and processes incoming data as soon as they are available on remote sites (externaldatabase FTP site) Data are split into passes if necessary If data flows are missing or late the synchroni-sation engine put unusable data in waiting queues and automatically unfreezes them upon reception of themissing auxiliary data This processing step delivers raw data that is to say data that have been dividedinto cycles and passes and ordered chronologicallyFrom SSALTODUACS V80 the acquisition step uses two different data flows in near-real time the OGDRflow (within a few hours) and the IGDR flow (within a few days)For each OGDR input the system checks that no equivalent IGDR entry is available in the data base beforeacquisition for each IGDR input the system checks and delete the equivalent OGDR entry in the data baseThese operations aim to avoid duplicates in SSALTODUACS system
Figure 6 Overview of the near real time system data flow management
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III23 Homogenization
The Homogenization process consists in applying the most recent corrections models and references rec-ommended for altimeter products Each mission is processed separately as its needs depend on the baseinput data The list of corrections and models currently applied is provided in tables 3 and 4 for NRT dataThe system includes SLA filtering to process OGDR data DUACS extract from these data sets the shortscales (space and time) which are useful to better describe the ocean variability in real time and merge thisinformation with a fair description of large scale signals provided by the multi-satellite observation in nearreal time (read IGDR-based DUACS data) Finally an hybrid SLA is computed
Figure 7 Merging pertinent information from IGDR and OGDR processing
III24 Input data quality control
The Input Data Quality Control is a critical process applied to guarantee that DUACS uses only the mostaccurate altimeter data Thanks to the high quality of current missions this process rejects a small percent-age of altimeter measurements but these erroneous data could be the cause of a significant quality lossThe quality control relies on standard raw data editing with quality flags or parameter thresholds but alsoon complex data editing algorithms based on the detection of erroneous artefacts mono and multi-missioncrossover validation and macroscopic statistics to edit out large data flows that do not meet the systemrsquosrequirements
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III25 Multi-mission cross-calibration
The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistentand accurate information It removes any residual orbit error (OE Le Traon and Ogor 1998[32]) or longwavelength error (LWE Le Traon et al 1998[31]) as well as large scale biases and discrepancies betweenvarious data flows
This process is based on two very different algorithms a global multi-mission crossover minimization fororbit error reduction (OER) and Optimal Interpolation (OI) for LWE
Multi-satellite crossover determination is performed on a daily basis All altimeter fields (measurementcorrections and other fields such as bathymetry MSS) are interpolated at crossover locations and datesCrossovers are then appended to the existing crossover database as more altimeter data become availableThis crossover data set is the input of the Orbit Error Reduction (OER) method Using the precision of thereference mission orbit a very accurate orbit error can be estimated This processing step does not concernOGDR dataLWE is mostly due to residual tidal or inverse barometer errors and high frequency ocean signals The OIused for LWE reduction uses precise parameters derived from
bull accurate statistical description of sea level variability
bull localized correlation scales
bull mission-specific noise and precise assumptions on the long wavelength errors to be removed (from arecent analysis of one year of data from each mission)
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III26 Product generation
The product generation process is composed of four steps computation of raw SLA cross-validationfilteringampsub-sampling and generation of by-products
III261 Computation of raw SLA
Since the geoid is not well known yet the SSH cannot be used directly the SSH anomalies are used insteadThey are computed from the difference of the instantaneous SSH - a temporal reference This temporalreference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeattrack analysis cannot be used The errors affecting the SLAs MPs and MSS have different magnitudes andwavelengths The computation of the SLAs and their errors associated are detailed in Dibarboure et al 2010[9]
Use of a Mean ProfileIn the repeat track analysis (when the satellites flies over a repetitive orbit) measurements are re-sampledalong a theoretical ground track (or mean track) associated to each mission Then a Mean Profile (MP) issubtracted from the re-sampled data to obtain SLA The MP is a time average of similarly re-sampled dataover a long period
bull The Mean Profile used for Jason-2 is computed with 10 years of TP (cycles 11 to 353) and 6 years ofJason-1 (cycles 11 to 250)
bull The Mean Profile used from Jason-1 cycle 262 to 374 (where satellites are on interleaved ground-tracks) is computed with 3 years of TP (cycles 369 to 479)
bull No Mean Profile can be used for Envisat on its new orbit (enn) Jason-1 on its geodetic orbit (j1g) norfor Cryosat-2 mission (c2) because there is no repetitive track The MSS must be used instead (seebelow)
Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible
bull Indeed as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide precise cross-track projection andor interpolation schemes are required to avoid errors
bull The mesoscale variability error (which is lt35 cm for MP between 3 to 5 years and lt1cm for WLof 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a prioriknowledge from Sea Level maps derived from previous iterations or from other missions
bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
Page 28
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for Envisat since november 2010 and for Cryosat-2 mission (c2)because the satellite is not in a repetitive orbit phase The alternative is to use the MSS instead The griddedMSS is derived from along track MPs and data from geodetic phases Thus any error on the MP is alsocontained in the MSS There are essentially 4 types of additional errors on gridded MSS which are hard toquantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
Note that for the Arctic regional products the DTU10 MSS [1] is taken into account instead of the CLS01MSS Indeed the accuracy of DTU10 compared to CLS01 is further demonstrated by the significant sealevel anomaly variance reduction found over the whole Arctic Ocean as shown in Prandi et al [42]
III262 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III263 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
Page 29
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III27 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III271 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
Page 30
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III272 Performance indicators
To appreciate the quality situation of the DUACS system new performance indicators are computed dailyThey aim at evaluate the status of the main processing steps of the system the input data availability theinput data coverage the input data quality and the output product quality These indicators are computed foreach and every currently working satellite and combined to obtain the overall status
Figure 8 Example with the key performance indicator on 20090627
See the description the latest and previous indicators on Aviso websitehttpwwwavisooceanobscomindexphpid=1516
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III3 Delayed Time processing steps
III31 Input data models and corrections applied
Delayed Time MyOcean products are generated
bull from Aviso GDR products for TP Jason-1 Jason-2 and Envisat (GDR-A cycles 1 to 22 GDR-Bcycles 23 to 85 GDR-C from cycle 86)
bull from NOAA GDR for GFO and from CERSAT (IFREMER) OPR for ERS-1 and ERS-2 (phases C(1st 35-day repeat orbit period) phase E and F (geodetic phases) phase G for ERS-1 (last 35-dayrepeat orbit period tandem phase with ERS-2 phase A for ERS-2 (1st 35-day repeat orbit periodtandem phase with ERS-1))
All GDR products are computed with a Precise Orbit Ephemeris (POE) and are delivered within 2 to 3months depending on the mission For several missions an updated orbit is used
bull For ERS-1amp-2 the orbit used is DGME-04 provided by Delft Institute (httpwwwdeostudelftnl)until June 2003
bull For TopexPoseidon the orbit used is GSFC (std0809) for the whole mission
bull For Envisat CNES POE of GDR-C standard is used for the whole mission
bull For the whole GFO mission the orbit used is GSFC (std0809) and when not available NASA POE isused
Altimetric product Source Availability Type of orbit
TopexPoseidon GDR NASACNES - GSFC POE
Jason-1 GDR (GDR-C) CNESNASA ~40 days CNES POE
Jason-2 GDR (GDR-C) CNESNASA ~60 days CNES POE
GFO GDR NOAA - GSFCNASA POE
ERS-1amp2 IFREMERESA - DGME-04
Envisat (GDR-A GDR-B andGDR-C from cycle 86)
ESA ~2 months CNES POE
Table 5 SSALTODUACS Delayed Time Input data overview
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
DU
AC
S20
11D
Tpr
oduc
t(gtV
30
0)j2
j1j1
ntp
tpn
e1e2
ene
nng2
Prod
uct
stan
dard
ref
GD
R-C
OPR
GD
R-A
(Cyc
les
1to
22)
GD
R-B
(cyc
les
23-8
5)
GD
R(N
OA
A)
Orb
itC
nes
POE
GSF
C(I
TR
F20
05G
RA
CE
last
stan
dard
s)
DG
ME
-04
(Sch
arro
oan
dV
isse
r19
98[4
8]C
NE
SPO
E(G
DR
-1st
anda
rds
forc
ycle
s9
to22
GD
R-C
stan
dard
sfr
omcy
cle
23)
GSF
C(I
TR
F20
05
GR
AC
Ela
stst
anda
rds
Iono
pher
icD
ual f
requ
ency
altim
eter
rang
em
easu
rem
ents
Dua
l fre
quen
cyal
timet
erra
nge
mea
sure
men
ts(T
opex
)D
OR
IS(P
OSE
IDO
N)
Ben
t mod
elB
ent m
odel
(cyc
les
1-36
)G
IMm
odem
from
cycl
e37
((Ii
jima
etal
19
98[2
4])
Dua
l-fr
eque
ncy
altim
eter
rang
em
easu
rem
ent(
cycl
e9-
64)a
ndG
IMm
odel
gtcyc
le65
(Iiji
ma
etal
19
99[2
4])c
orre
cted
from
8m
mbi
as
From
GIM
mod
el(I
ijim
aet
al1
998
[24]
)
Dry
trop
o-sp
here
Mod
elco
mpu
ted
from
EC
MW
FG
auss
ian
grid
s(n
ewS1
and
S2at
mos
pher
ictid
esar
eap
plie
d)
Mod
elco
mpu
ted
from
EC
MW
Fre
ctan
gula
rgri
ds(n
ewS1
and
S2at
mos
pher
ictid
esar
ein
clud
ed)
Wet
trop
o-sp
here
JMR
AM
Rra
diom
eter
furt
hert
han
50km
from
the
coas
tsF
rom
EC
MW
Fm
odel
ford
ista
nces
betw
een
10an
d50
km
TM
Rra
diom
eter
(Sch
aroo
etal
20
04[4
9])
MW
RC
orre
ctio
nof
the
drif
ton
the
236
GH
zbr
ight
ness
tem
pera
ture
(Sch
arro
oet
al
2004
[49]
)Neu
ral
Net
wor
kal
gori
thm
(Tra
nan
dO
blig
is
2003
[50]
MW
Rra
diom
eter
furt
hert
han
50km
from
the
coas
tsan
dco
rrec
ted
from
side
lobe
s(f
rom
cycl
e41
)E
CM
WF
mod
elfo
rdis
tanc
esbe
twee
n10
and
50km
GFO
radi
omet
er
DA
CM
OG
2DH
igh
Res
olut
ion
forc
edw
ithE
CM
WF
pres
sure
and
win
gfie
lds
(S1
and
S2w
ere
excl
uded
)+in
vers
eba
rom
eter
com
pute
dfr
omre
ctan
gula
rgri
ds
Tabl
e6
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(1
2)
Page 33
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
j2j1
j1n
tptp
ne1
e2en
enn
g2O
cean
tide
GO
T4v
7(S
1an
dS2
are
incl
uded
)Po
letid
e[W
ahr
1985
[53]
]So
lidea
rth
tide
Ela
stic
resp
onse
totid
alpo
tent
ial[
Car
twri
ghta
ndTa
yler
197
1[5]
][C
artw
righ
tand
Edd
en1
973[
6]]
Loa
ding
tide
GO
T4v
7(S
1pa
ram
eter
isin
clud
ed)
Sea
stat
ebi
asN
onpa
ram
etri
cSS
B[G
aspa
reta
l20
02[2
0]]
Non
para
met
ric
SSB
[NT
ran
and
al2
010[
51]]
BM
3[G
aspa
ran
dO
gor
1994
[17]
]
Non
para
met
ric
SSB
[Mer
tzet
al
2005
[38]
]
Non
para
met
ric
SSB
[Gas
pare
tal
2002
]w
ithG
DR
-Bst
anda
rds
forc
ycle
s9
to85
and
with
GD
R-C
stan
dard
sfr
omcy
cle
86
Non
para
met
ric
SSB
[NT
ran
etal
20
10[5
1]]
Orb
iter
ror
Glo
bal m
ulti-
mis
sion
cros
sove
rmin
imiz
atio
n(L
eTr
aon
and
Ogo
r19
98[3
2])
Lon
gw
ave-
leng
her
rors
Opt
imal
Inte
rpol
atio
n(L
eTr
aon
etal
19
98[3
1])
Inte
rcal
ibra
tion
Ref
eren
cefr
omcy
cle
11R
efer
ence
from
cycl
e1
to35
4C
orre
ctio
nof
regi
onal
bias
J2J
1de
duce
dfr
omin
terc
alib
ratio
nph
ase
(cyc
le11
J2)
Cor
rect
ion
ofgl
obal
biai
sJ1
TP
deacutedu
ced
from
inte
rcal
ibra
tion
phas
e(c
ycle
s11
J1)
Mea
npr
o-fil
e(s
eeII
I36
1)
Com
pute
dw
ithcy
cles
11-3
53T
Pda
taan
dw
ithcy
cles
11-2
50J1
data
ref
eren
ced
[199
319
99]
TP
J1 c
ompu
ted
with
cycl
es11
-353
TP
data
and
with
cycl
es11
-250
J1da
tar
efer
ence
d[1
993
1999
]T
PNJ
1Nc
ompu
ted
with
cycl
es36
9-47
9T
PNda
tar
efer
ence
d[1
993
1999
]
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
ref
eren
ced
[199
319
99]
EN
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
re
fere
nced
[199
319
99]
EN
Nu
seof
MSS
_CN
ES_
CL
S11
[39]
Com
pute
dw
ithcy
cles
37-1
87G
2da
ta
refe
renc
ed[1
993
1999
]
Peri
odof
use
from
cycl
e9
from
cycl
e9
cycl
es1
to48
1cy
cles
15to
43In
clud
ing
E-F
geod
etic
phas
es
cycl
es1
to83
from
cycl
e9
cycl
es37
to22
2
Tabl
e7
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(2
2)
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III32 Acquisition
The acqusition process in Delayed time is much simpler than in Near Real time it consists in a synchronisa-tion process of all the auxiliary data required to homogenize propely the altimeter data sets The acquisitionstep uses the GDRs or the OPRs provided by the agencies
III33 Homogenization
The Homogenization process consists in applying the most recent corrections models and references rec-ommended for altimeter products Each mission is processed separately as its needs depend on the baseinput data The list of corrections and models currently applied is provided in tables 6 and 7 for DT data
III34 Input data quality control
The Input Data Quality Control is a critical process applied to guarantee that DUACS uses only the mostaccurate altimeter data Thanks to the high quality of current missions this process rejects a small percent-age of altimeter measurements but these erroneous data could be the cause of a significant quality lossThe quality control relies on standard raw data editing with quality flags or parameter thresholds but alsoon complex data editing algorithms based on the detection of erroneous artefacts mono and multi-missioncrossover validation and macroscopic statistics to edit out large data flows that do not meet the systemrsquosrequirements
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III35 Multi-mission cross-calibration
The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistentand accurate information It removes any residual orbit error (OE Le Traon and Ogor 1998[32]) or longwavelength error (LWE Le Traon et al 1998[31]) as well as large scale biases and discrepancies betweenvarious data flows
This process is based on two very different algorithms a global multi-mission crossover minimization fororbit error reduction (OER) and Optimal Interpolation (OI) for LWE
Multi-satellite crossover determination is performed on a daily basis All altimeter fields (measurementcorrections and other fields such as bathymetry MSS) are interpolated at crossover locations and datesCrossovers are then appended to the existing crossover database as more altimeter data become availableThis crossover data set is the input of the Orbit Error Reduction (OER) method Using the precision of thereference mission orbit a very accurate orbit error can be estimated LWE is mostly due to residual tidalor inverse barometer errors and high frequency ocean signals The OI used for LWE reduction uses preciseparameters derived from
bull accurate statistical description of sea level variability
bull localized correlation scales
bull mission-specific noise and precise assumptions on the long wavelength errors to be removed (from arecent analysis of one year of data from each mission)
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III36 Product generation
The product generation process is composed of four steps computation of raw SLA cross-validationfilteringampsub-sampling and generation of by-products
III361 Computation of raw SLA
Since the geoid is not well known yet the SSH cannot be used directly the SSH anomalies are used insteadThey are computed from the difference of the instantaneous SSH - a temporal reference This temporalreference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeattrack analysis cannot be used The errors affecting the SLAs MPs and MSS have different magnitudes andwavelengths The computation of the SLAs and their errors associated are detailed in Dibarboure et al 2010[9]
Use of a Mean ProfileIn the repeat track analysis (when the satellites flies over a repetitive orbit) measurements are re-sampledalong a theoretical ground track (or mean track) associated to each mission Then a Mean Profile (MP) issubtracted from the re-sampled data to obtain SLA The MP is a time average of similarly re-sampled dataover a long period
bull The Mean Profile used for TP (cycles 1 to 364) Jason-1 (cycles 1 to 259) and Jason-2 is computedwith 10 years of TP (cycles 11 to 353) and 6 years of Jason-1 (cycles 11 to 250)
bull The Mean Profile used for TP (cycles 368 to 481) and from Jason-1 cycle 262 to 374 (where satellitesare on interleaved ground-tracks) is computed with 3 years of TP (cycles 369 to 479)
bull The Mean Profile used for ERS-1 in its 35 days repetitive orbit mission ERS-2 and Envisat (only forthe first orbit before November 2010) is computed with 8 years of ERS-2 (cycles 1 to 85) and 6 yearsof Envisat (cycles 10 to 72)
bull No Mean Profile can be used for Envisat on its new orbit (enn) Jason-1 on its geodetic orbit (j1g)because there is no repetitive track The MSS must be used instead (see below)
bull The Mean Profile used for GFO is computed with 7 years of GFO cycles 37 to 187
Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible
bull Indeed as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide precise cross-track projection andor interpolation schemes are required to avoid errors
bull The mesoscale variability error (which is lt35 cm for MP between 3 to 5 years and lt1cm for WLof 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a prioriknowledge from Sea Level maps derived from previous iterations or from other missions
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bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for ERS-1 for its 168 days geodetic mission (phases E-F from April1994 to March 1995) or for Envisat since november 2010 because the satellite is not in a repetitive orbitphase The alternative is to use the MSS instead The gridded MSS is derived from along track MPs anddata from geodetic phases Thus any error on the MP is also contained in the MSS There are essentially 4types of additional errors on gridded MSS which are hard to quantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
III362 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III363 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
Page 38
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III37 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III371 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
Page 39
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
IV MYOCEAN PRODUCTS
IV1 Near Real Time Products
The purpose of the NRT DUACS component is the acquisition of altimeter data from various altimeter mis-sions in near-real time (ie within a few days at most) the validation and correction of these altimeter datasets (ie edition and selection update of corrections and homogenization orbit error reduction) in order toproduce each day along-track productsProducts are as follows
Along-track products global and regional (Mediterranean and Black Seas Arctic Ocean and Europeareas)
bull Sea Level Anomaly (NRT-SLA) for each mission with NRT-SLA ephemeris
IV11 Delay of the products
The availability of the products in near real time is three to twelve hours after the measurement for along-track products Those products are delivered every day
IV12 Temporal availibility
The following table presents the available products by mission and by data periodNear real time products
NRT Jason-2 Jason-1 and Jason-1geodetic
Envisat new Cryosat-2
Temporal Time availability ymlowast
ongoingymlowast-20120303 for
repeat track and20120507-ongoing for
geodetic track
ymlowast
2012040820120101
ongoing
NRT-SLA X X X X
lowastym the temporal coverage for NRT products is fluctuating and depends on updates of Delayed Time prod-ucts When DT products are updated (3 to 4 times per year) the oldest NRT products are replaced by thebetter quality DT products so that the 2 series are overlapping on few weeks or few months
IV2 Delayed Time Products
The Delayed Time component of SSALTODUACS system is responsible for the production of processedJason-1 Jason-2 TP Envisat GFO ERS12 and even Geosat data in order to provide a homogeneousinter-calibrated and highly accurate long time series of SLA DT products are more precise than NRT products Two reasons explain this quality difference The firstone is the better intrinsic quality of the POE orbit used in the GDR processing The second reason is that
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in the DT DUACS processing the products can be computed optimally with a centred computation timewindow for OER LWE On the contrary in NRT case future data are not available so the computationtime window is not centred and therefore not optimalAs for NRT products improved altimeter corrections and processing algorithms are used ocean tide modelto correct altimeter data improved methods for orbit error reduction and mapping
Along-Track products global and regional (Mediterranean and Black Seas)
bull Sea Level Anomaly (DT-SLA) for each mission
IV21 Delay of the products
Weekly products are delivered The availability of the products in delayed time is at the best two monthsafter the date of the measurement The product generation needs all the GDR data of all the missions to takeinto account the best corrections as possible The time delay can be longer in the case of a missing mission
IV22 Temporal availibility
The following table presents the available products by mission and by data periodDelayed time SSALTODUACS products
Upd Jason-2 Jason-1new6
Jason-1 GFO Envisatnew6
Envisat ERS-16
ERS-2Topexnew6
Topex
TemporalTimeavailabil-ity
200810ymlowast
200902ymlowast
200204200810
200001200809
201010ymlowast
200210201010
199210200304
200209200510
199209200204
DT-SLA X X X X X X X X X
lowast ym those dates are updated regularly (3 to 4 times per year) and are avalaible when you download thedata at httpwwwmyoceaneuweb24-cataloguephp6 Jason-1 new orbit starting 200809 Envisat new orbit starting 201010 TP new orbit starting 200209 ERS-1The geodetic phases (E-F) are included There are no ERS-1 data between December 23 1993 and April 10 1994(ERS-1 phase D - 2nd ice phase) Note that during that time products are based only on TopexPoseidon data
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V DESCRIPTION OF THE PRODUCT SPECIFICATION
V1 General information
Product Specification SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001
Geographical coverage global
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 20-50km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001 Product Specification
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Product Specification SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002
Geographical coverage 55˚W-35˚E 30˚N-46˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002 Product Specification
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Product Specification SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003
Geographical coverage 27˚E-42˚E 40˚N-47˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003 Product Specification
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Product Specification SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004
Geographical coverage 25˚W-42˚E 21˚N-66˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004 Product Specification
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Product Specification SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005
Geographical coverage 0˚W-360˚E 50˚N-82˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005 Product Specification
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VI NOMENCLATURE OF FILES
VI1 Nomenclature of files downloaded through the MyOcean Web PortalDirectgetfile Service
VI11 Nomenclature of the product line
The description of the syntax for the SL TAC SLA products line is given by
SEALEVEL_ltREGIONgt_SLA_L3_ltDELAYgt_OBSERVATIONS_008_ltZONEgt_ltLETTERgtwhere
REGION GLO global geographic coverage product
BS Black Sea products
MED Mediterranean products
ARC Arctic products (for NRT products)
EUROPE Europe products (for NRT products)
DELAY NRT near real time products
RAN delayed time or reanalysis products
ZONE 001 number on 3 digits
002
003
004
LETTER a letter on 1 digit
b
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VI12 Nomenclature of the datasets
The nomenclature used is
dataset-duacs-ltdelaygt-ltzonegt-ltmissiongt-lttype of slagt-l3where the fileds in ltgt are described below
delay nrt near-real time productsran delayed time products
zone global global geographic coverage productmedsea Mediterranean productsblacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1 (only for ran)e2 ERS-2 (only for ran)tp TOPEXPoseidon (only for ran)tpn TOPEXPoseidon on its new orbit (only for
ran)g2 GFO (only for ran)j1 Jason-1 (only for ran)j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisat (only for ran)enn Envisat on its new orbitc2 Cryosat-2 (only for nrt)
type of sla sla filtered slasla_unfiltered non filtered sla (only for ran products)
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VI13 Nomenclature of the NetCdf files
The nomenclature used is
ltdelaygt_ltzonegt_ltmissiongt_sla_ltvariablegt_ltdatebegingt_ltdateendgt_ltdateprodgtnc where the fileds in ltgt are de-scribed below
delay nrt near-real time productsdt delayed time products
zone global global geographic coverage productmed Mediterranean products (for dt)mfstep Mediterranean products (for nrt)blacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1e2 ERS-2tp TOPEXPoseidontpn TOPEXPoseidon on its new orbitg2 GFOj1 Jason-1j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisatenn Envisat on its new orbitc2 Cryosat-2
variable vfec filtered and sub-sampled slavxxc non filtered and non sub-sampled sla (only
for dt)datebegin YYYYMMDD() beginning date of the datasetdateend YYYYMMDD() end date of the datasetdateprod YYYYMMDD production date of the dataset
() For dt data as the dates in the file names are rounded the user wanting data for date T has to read the filescontaining dates T+1 and T-1 in their name and check inside the files if there are some data for date T
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VII DATA FORMAT
This chapter presents the data storage format used for MyOcean products
VII1 NetCdf
The products are stored using the NetCDF format NetCDF (network Common Data Form) is an interface for array-oriented data access and a library that provides an implementation of the interface The netCDF library also definesa machine-independent format for representing scientific data Together the interface library and format support thecreation access and sharing of scientific data The netCDF software was developed at the Unidata Program Center inBoulder Colorado The netCDF libraries define a machine-independent format for representing scientific data Pleasesee Unidata NetCDF pages for more information and to retreive NetCDF software package onhttpwwwunidataucaredupackagesnetcdfindexhtml
NetCDF data is
bull Self-Describing A netCDF file includes information about the data it contains
bull Architecture-independent A netCDF file is represented in a form that can be accessed by computers with dif-ferent ways of storing integers characters and floating-point numbers
bull Direct-access A small subset of a large dataset may be accessed efficiently without first reading through allthe preceding data
bull Appendable Data can be appended to a netCDF dataset along one dimension without copying the dataset orredefining its structure The structure of a netCDF dataset can be changed though this sometimes causes thedataset to be copied
bull Sharable One writer and multiple readers may simultaneously access the same netCDF file
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VII2 Structure and semantic of NetCDF along-track files
The NetCDF Sea Level TAC files are based on the attribute data tags defined by the Cooperative OceanAtmosphereResearch Data Service (COARDS) and Climate and Forecast (CF) metadata conventions The CF convention gener-alises and extends the COARDS convention but relaxes the COARDS constraints on dimension and order and specifiesmethods for reducing the size of datasetsA wide range of software are available to write or read NetCDFCF files API are made available by UNIDATA(httpwwwunidataucaredusoftwarenetcdf)
bull CC++Fortran
bull Java
bull MATLAB Objective-C Perl Python R Ruby TclTk
In addition to these conventions the files are using a common structure and semantic
bull 1 dimension is defined
ndash time it is used to check NetCDF variables depending on time
bull 8 variables are defined
ndash short SLA contains the Sea Level Anomaly values for each time given
ndash int longitude contains the longitude for each measurement
ndash short track contains the track number for each measurement
ndash double time contains the time in days since 1950-01-01 000000 UTC for each measurement
ndash short mean_profile_point_index index of the corrsponding point in the track of the mean profile
ndash byte flag flag=0 the processed data comes from OGDR if flag=1 the processed data comes from theIGDR
ndash int latitude contains the latitude for each measurement
ndash short cycle contains the cycle number for each measurement
bull global attributes
ndash the global attributes gives information about the creation of the file
Example of a NetCDF sla file
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netcdf nrt_global_j1_sla_vfec_20101230_20101230_20101230 dimensions
time = 10385 variables
short SLA(time) SLAcoordinates = longitude latitude SLAlong_name = Sea Level Anomaly SLA_FillValue = 32767s SLAadd_offset = 0 SLAscale_factor = 0001 SLAunits = m SLAstandard_name = sea_surface_height_above_sea_level
int longitude(time) longitudelong_name = Longitude of measurement longitude_FillValue = 2147483647 longitudeadd_offset = 0 longitudestandard_name = longitude longitudescale_factor = 1e-06 longitudeunits = degrees_east
short track(time) tracklong_name = Track in cycle the measurement belongs to track_FillValue = 32767s trackunits = 1 trackcoordinates = longitude latitude
double time(time) timelong_name = Time of measurement time_FillValue = 184467440737096e+19 timeaxis = T timestandard_name = time timeunits = days since 1950-01-01 000000 UTC
int latitude(time) latitudelong_name = Latitude of measurement latitude_FillValue = 2147483647 latitudeadd_offset = 0 latitudestandard_name = latitude latitudescale_factor = 1e-06 latitudeunits = degrees_north
short flag(time) flagcoordinates = longitude latitude flag_FillValue = 3267s flaglong_name = data origin flagflag_values = 1s 0s flagflag_meanings = igdr_like non_igdr_like flagcomment = The origin of the data is determined by the types of geophysical datarecords (GDR) used in computation of the SLA 1 for the Interim GDR (IGDR) and0 for Operational GDR (OGDR)
short cycle(time) cyclelong_name = Cycle the measurement belongs to cycle_FillValue = 32767s cycleunits = 1 cyclecoordinates = longitude latitude
global attributeshistory = 22-Feb-2011 155243 CET File created by the SSLATODUACS system version 1001 comment = Produce from ENVISAT Extension Phase satellite altimetry data institution = CLSCNES
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references = httpwwwavisooceanobscomfileadmindocumentsdatatoolshdbk_duacspdf source = satellite altimetry title = along track Sea Level Anomaly Conventions = CF-14
dataSLA =
7 7 11 10 -2 -22 -39 -41 -30 -13 -3 -5 -16 -26 -32 -35-35 -35 -37 -35 -31 -29 -31 -35 -32 -21 -10 -10 -19 -20 -1-69 -57 -49 -45 -39 -30 -28 -31 -27 -13 -2 -5 -15 -3 1112 3 -7 -10 -14 -15 -22 -31 -37 -32 -17 -10
longitude =74743328 74868400 74993968 75120040 75246616 7537372875501368 75629568 75758320 75887656 76017568 76148080 7627920876388952 76477056 76565456 76654144 76743128 76832400 76921984329429568 329535424 329641792 329748672 329856096 329964032330072512 330181536 330291072 330401184
track =92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 9292 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92113 113 113 113 113 113 113 113 113 113 113 113 113 113113 113 113 113 113 113 113 113 113
time =222780000565705 222780001314719 222780002063733222780002812747 222780003561761 222780004310775 222780005059788222780005808802 222780006557816 22278000730683 222780008055844222780008804858 222780009553872 22278001017805 222780010677393222788257112198 222788257486705 222788257861212 222788258235719222788258610226 222788258984733 222788259359239 222788259733746222788260108253 22278826048276
mean_profile_point_index =1872 1878 1884 1890 1896 1902 1908 19141920 1926 1932 1938 1944 1949 1953 1957 1961 1965 1969 19732306 2309 2312 2315 2318 2321 2327 2330 2333 2336 2339 23422345 2348 2351 2354 2357 2360 2363 2366
flag =0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
latitude =-16225506 -16539731 -16853833 -17167810 -17481660 -17795380-18108966 -18422418 -18735729 -19048899 -19361924 -19674801-19987527 -20248015 -20456329 -20664569 -20872739 -2108083739481297 39628277 39775133 39921866 40068472 40214953 4036130840507533 40653629 40799592 40945423 41091120 41236684 41382111
cycle =331 331 331 331 331 331 331 331 331 331 331 331 331
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331 331 331 331 331 331 331 331 331 331 331 331 331 331331 331 331 331 331 331 331 331 331 331 331 331
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VIII HOW TO DOWNLOAD A PRODUCT
VIII1 Download a product through the MyOcean Web Portal DirectgetfileService
You first need to register Please find below the registration stepshttpwwwmyoceaneuweb34-products-and-services-faqphp1Once registered the MyOcean FAQ httpwwwmyoceaneuweb34-products-and-services-faqwill guide you on How to download a product through the MyOcean Web Portal Directgetfile Service
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IX NEWS AND UPDATES
IX1 [Duacs] Operational news
To be kept informed on events occurring on the satellites and on the eventual interruption of the services of the DUACSprocessing system see the [Duacs] operational news on the Aviso websitehttpwwwavisooceanobscomendataoperational-newsindexhtml
IX2 Updates
To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtmlSince 2010 a complete reprocessing of all altimetry data (cumulated total of about 55 years of data) is available Themain changes introduced in the Duacs DT v300 reprocessed data set in SSALTODUACS reprocessed DT data setare listed herehttpwwwavisooceanobscomfileadmindocumentsdataduacsduacs_DT_2010_reprocessing_impactpdf
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II UPDATES IN 2011 AND 2012
This section describes the updates of the SSALTODUACS Near Real Time system that occurred during2011 and 2012 allowing to add new products (Europe and Arctic) the integration of the Cryosat-2 data inthe system the stopping delivery of Envisat data the addition of Jason-1 data on geodetic orbit (j1g)To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtml
II1 Version D of input IGDROGDR Jason-2 data for NRT processing(July 30 2012)
On July 30 2012 the version of Jason-2 IGDROGDR has changed and is now the D version Somecorrections have thus been updated as detailed in tables 3 and 4
II2 Integration of Jason-1 on its geodetic orbit (May 2012)
An anomaly occured on March 3rd 2012 on the Jason-2 mission (see httpwwwavisooceanobscomfractualitesactualitesindexhtmltx_ttnews[tt_news]=1162amptx_ttnews[backPid]=1399ampcHash=d5baeb645e) On April 23rd CNES began to command the satellite into a nadir ori-entation and after some propulsion anomalies CNES and NASA management through the Joint SteeringGroup have directed the Jason-1 Project to then begin a series of maneuvers to place Jason-1 into a neworbit as defined in table 1 After checking the current orbit carefully the operational team determined thata geodetic mission was still possible It was also decided to preserve all remaining fuel for future stationkeeping maneuvers which is mandatory in a geodetic orbit Core payloads were switched ON on May 4thand after some POSEIDON2 radar (PRF) adjustments the mission was resumed on May 7th at 151248UTCBelow are the characteristics of the new orbit which will be maintained as before within +- 1km controlbox at the Equator
Semi major axis 7702437 kmEccentricity 13 to 28 10-4Altitude equator 13240 kmOrbital period 6730s (1h52rsquo10rdquo)Inclination 66042˚Cycle 406 daysSub cycles 39 - 109 - 475 - 1795
days
Table 1 Characteristics of the geodetic orbit for Jason-1 since May 7th 2012
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For this new phase of the Jason-1 mission (called j1g) the cycle numbering will restart at 500 Off-lineproducts will be produced once a day for the IGDR and every 11 days for the GDRrsquos The integration ofJason-1 data in the DUACS system is available since May 25th 2012
II3 Envisat has stopped sending data (April 2012)
Since April 8th 2012 Envisat has stopped sending data to Earth Esarsquos mission control has worked tore-establish contact with the satellite but there has been no reaction from the satellite Thus Esa has de-clared officially the end of mission for Envisat (see httpwwwesaintesaCPSEM1SXSWT1H_index_0html) Therefore no SL TAC NRT data from Envisat can be released since this date
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II4 Integration of the Cryosat2 Mission (February 2012)
Since February 6th 2012 Cryosat-2 mission has been integrated in the DUACS sytem This mission isdedicated to the observation of the floating sea-ice as well as the continental ice sheets but all data acquiredover ocean are valuable for the observation of oceanic circulation and mesoscale variations This majorchange is the result of the long-standing and fruitful partnership between ESA and CNES and a responseto the request from scientific and operational oceanography users [7] The integration of Cryosat-2 impactsthe delivering of Near real time Sea Level Anomalies (SLA)
II41 Generalities about the mission
A Cryosat-2 Processing Prototype (C2P) (described in Boy et al 2011 [2]) has been developed on CNESside to lay the ground for various SAR processing studies The processing chains ingest Level-0 telemetryfiles distributed by ESA and perform the following steps to generate Sea Level Anomalies (SLA) values foreach altimeter measurements
bull Level-1 Decommutation time-tagging and localization of measurements
bull Level-1b Calculation of instrumental corrections and geophysicalmeteorological corrections
bull Level-2 MLE4 waveforms Retracking and calculation of SLA
The prototype processes data almost continuously over ocean either in Low Resolution Mode (LRM) or inthe DopplerSAR mode processed as pseudo-LRM mode allowing to increase the coverage (figure 2)
Figure 2 SSH-MSS for Cryosat-2 with LRM mode only (left) or LRM+pseudo-LRM modes (right)
Although Cryosat-2 raw SSH can be only corrected with GPS-derived ionospheric correction and ECMWFwet troposphere correction validation activities showed (Labroue et al 2011 [25]) that C2P outputs have anaccuracy roughly equivalent to Envisatrsquos Level 2 products if the latter are processed with the same standards
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II42 Integration in DUACS
The Cryosat-2 data are included in the Near Real time process The chain delivers now (for global coverageMediterranean and Black Seas) along track data from Cryosat-2 (SLAs) Note that the products distributedare of Level-3 and donrsquot replace Level-2 products distributed by agenciesThe details of the processing are given in Dibarboure et al 2011 [8]Here we just give an overview the data are computed with the corrections given in section III21 Thefiltering and sub-sampling of SLAs (section III263) are detailed in [8]
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II5 Addition of Europe and Arctic products (January 2012)
Since the MyOcean V2 two new along-track products are computed in Near Real Time intended foraddressing the needs of data assmilation and validation in regional models
bull Following the TAPAS (Tailored Altimeter Product for Assimilation Systems) initiative launched bySL TAC with all the Modeling and Forecasting Centers (MFCs) the Europe regional products (PLSEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004) have been proposed (figure 3) They areavailable in Near Real Time onlyThey are studied to partly fulfil the needs of the Centers with adapted filtering and resolution Thoseparameters have been tuned in order to provide boundary conditions for the Atlantic assimilationmodels They are different from the ones used for Mediterranean and Black Seas products If you needto study the Mediterranean Sea or the Black Sea yoursquod better use the dedicated products describedabove since the processing parameters have been fitted to be adapted to the dynamics of the ocean inthose regions
Figure 3 Coverage of the Europe product for Jason-1 Jason-2 and Envisat from August 18th to September9th 2011
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bull The Arctic along-track products (PL SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005) coverlatitudes between 45 and 82 degrees (figure 4) They are available in Near Real Time only
Figure 4 Coverage of the Arctic region with Envisat from October 28th 2011 to January 3rd 2012
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III SSALTODUACS SYSTEM
III1 Introduction
This chapter presents the input data used by SSALTODUACS system and an overview of the different pro-cessing steps necessary to produce the output dataSSALTODUACS system is made of two components a Near Real Time one (NRT) and a Delayed Time(DT) oneIn NRT the systemrsquos primary objective is to provide operational applications with directly usable high qual-ity altimeter data from all missions availableIn DT it is to maintain a consistent and user-friendly altimeter database using the state-of-the-art recom-mendations from the altimetry communityFollowing figure gives an overview of DUACS system where processing sequences can be divided into 7main steps
bull acquisition
bull homogenization
bull input data quality control
bull multi-mission cross-calibration
bull product generation
bull merging
bull final quality control
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Figure 5 SSALTODUACS processing sequences
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III2 Near Real Time processing steps
III21 Input data models and corrections applied
To produce SLA in near-real time the DUACS system uses two flows based on the same instrumental mea-surements but with a different quality
bull The IGDR that are the latest high-quality altimeter data produced in near-real-time
bull The OGDR that includes real time data (OSTMJason-2 and Jason-1 OSDR) to complete IGDR Thesefast delivery products do not always benefit from precise orbit determination nor from some exter-nal model-based corrections (Dynamic Atmospheric Correction (DAC) Global Ionospheric Maps(GIM))
Integration of OGDR data and the introduction of Jason-2Jason-1 tandem increased the resilience and pre-cision of the system A better restitution of ocean variability is observed especially in high energetic areas
Altimetric product Source Availability Type of orbit
Jason-2 IGDR CNES ~24h CNES MOE GDR-Cuntil 20120730
CNES MOE GDR-Dsince 20120731
OGDR NOAAEUMETSAT ~3 to 5 h
Jason-1 IGDR CNESNASA ~48 h CNES MOE GDR-Dsince 20120507
OGDR CNESNASA ~3 to 12 h
Envisat IGDR ESACNES not deliveredsince 20120408
CNES MOE GDR-Dsince 20120121
FDGDR ESA not deliveredsince 20120408
Cryosat-2 IGDR-like ESACNES ~48 h CNES MOE GDR-D
not delivered
Table 2 SSALTODUACS Near-Real Time Input data overview
See Figure 6 Overview of the near real time system data flow management
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DUACS 2011 NRT product from IGDR1
j2 j1nj1g enn c2Productstandard ref
version C until20120730 and D after
version C version 21 CPP [2]
Orbit CNES MOE GDR-Cuntil 20120730
GDR-D after
CNES MOE GDR-C forj1n and CNES MOE
GDR-D for j1g
CNES MOE GDR-Dfrom 20120121 to
20120408
CNES MOE GDR-D
Ionopheric bi-frequency altimeter range measurements GIM model for cgt64 (Iijima et al1998[24])Dry tropo Model computed from ECMWF Gaussian grids (new S1 and S2 atm tides applied)Wet tropo-sphere
AMR radiometer(enhancement in coastal
regions since20120730)
JMR radiometer MWR radiometer andcorrected from side
lobes
Model computed fromECMWF Gaussian
grids
DAC MOG2D High Resolution forced with ECMWF pressure and wind fields (S1 and S2 wereexcluded) (Carrere and Lyard 2003[3])+ inverse barometer Filtering temporal window is
un-centered (no data in the future)Ocean tide GOT4v8 (S1 and S2 are included) and TPX 072 [16] for Arctic productsPole tide [Wahr 1985 [53]]Solid earthtide
Elastic response to tidal potential [Cartwright and Tayler 1971[5]] [Cartwright andEdden 1973[6]]
Loading tide GOT4v8 (S1 and S2 are included)Sea statebias
Non parametric SSB[Labroue 2004[27]](with cycles J1 1 to 11
using GDR-B standardsuntil 20120730 andderived from Jason-2
after)
Non parametric SSB[Labroue 2004[27]](with cycles 1 to 21
using GDR-Bstandards)
Non parametric SSB[Labroue 2004[27]](with cycles 41 to 60
using GDR-Bstandards)
Same as Jason-2 SSB
Orbit error Global multi-mission crossover minimization (Le Traon and Ogor1998[32])
Long wave-lengh errors
Optimal Interpolation [Le Traon et al 1998[31]]
Intercalibration Reference from cycle20
Mean pro-file (seeIII261)
Computed with cycles11-353 TP data andwith cycles 11-250J1 data referenced[19931999]
TPNJ1N computedwith cycles 369-479TPN data refer-enced [19931999]J1G No MP can beused instead theMSS_CNES_CLS11[39] is used
No Mean Profilecan be used forEnvisat on its neworbit Instead theMSS_CNES_CLS11[39] is used
No Mean Profilecan be used forCryosat-2 Instead theMSS_CNES_CLS11[39] is used
(1) A flag included in the along-track files indicates the source of the production (OGDRFDGDR orIGDR) If flag=0 the processed data comes from OGDRsFDGDRs if flag=1 the processed data comesfrom IGDRs
Table 3 Corrections and models applied in SSALTODUACS NRT products produced from IGDRs
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
DUACS 2011 NRT product from OGDR or FDGDR2
j2 j1nj1g ennProduct stan-dard ref
version C until 20120730and D after
version C version 21
Orbit Navigator Extrapolated CNES MOEGDR-D since 20120121
Ionopheric From-dual frequency altimeter range measurements From GIM model fromcycle 65 (Iijima et al1998 [24])
Dry troposphere Model computed from ECMWF Gaussian grids (new S1 and S2 atmospherictides are applied)
Wet tropo-sphere
AMR radiometer(enhancement in coastal
regions since 20120730)
JMR radiometer MWR radiometer andcorrected from side lobes
DAC Inverse Barometer forecastedOcean tide GOT4v8 (S1 and S2 are included) and TPX 072 [16] for Arctic productsPole tide [Wahr 1985 [53]]Solid earth tide Elastic response to tidal potential [Cartwright and Tayler 1971[5]]
[Cartwright and Edden 1973[6]]Loading tide GOT4v8 (S1 and S2 are included)Sea state bias Non parametric SSB
[Labroue 2004[27]] (withcycles J1 1 to 11 usingGDR-B standards until20120730 and derivedfrom Jason-2 after)
Non parametric SSB[Labroue 2004[27]](with cycles 1 to 21 usingGDR-B standards)
Non parametric SSB[Labroue 2004[27]](with cycles 41 to 60using GDR-B standards)
Orbit error Specific filtering of long-wavelength signal3
Long wave-lengh errors
Optimal Interpolation [Le Traon et al 1998[31]]
Intercalibration Reference from cycle 20Mean profile(see III261)
Computed with cycles 11-353 TP data and with cy-cles 11-250 J1 data refer-enced [19931999]
TPNJ1N computedwith cycles 369-479TPN data referenced[19931999] J1G NoMP can be used insteadthe MSS_CNES_CLS11[39] is used
No Mean Profile can beused for Envisat on itsnew orbit Instead theMSS_CNES_CLS11 [39]is used
(2) A flag included in the along-track files indicates the source of the production (OGDRFDGDR orIGDR) If flag=0 the processed data comes from OGDRsFDGDRs if flag=1 the processed data comesfrom IGDRs(3) Specific data processing was applied on long wave-length signal (sectIII23 of the user manual)
Table 4 Corrections and models applied in SSALTODUACS NRT products produced from OG-DRsFDGDRs
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III22 Acquisition
The acquisition process is twofold
bull straightforward retrieval and reformatting of altimeter data and dynamic auxiliary data (pressure andwet troposphere correction grids from ECMWF are provided by Meteo France TEC grids from JPLNRT MOG2D corrections) from external repositories
bull synchronisation process
To be homogenized properly altimeter data sets require various auxiliary data The acquisition softwaredetects downloads and processes incoming data as soon as they are available on remote sites (externaldatabase FTP site) Data are split into passes if necessary If data flows are missing or late the synchroni-sation engine put unusable data in waiting queues and automatically unfreezes them upon reception of themissing auxiliary data This processing step delivers raw data that is to say data that have been dividedinto cycles and passes and ordered chronologicallyFrom SSALTODUACS V80 the acquisition step uses two different data flows in near-real time the OGDRflow (within a few hours) and the IGDR flow (within a few days)For each OGDR input the system checks that no equivalent IGDR entry is available in the data base beforeacquisition for each IGDR input the system checks and delete the equivalent OGDR entry in the data baseThese operations aim to avoid duplicates in SSALTODUACS system
Figure 6 Overview of the near real time system data flow management
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III23 Homogenization
The Homogenization process consists in applying the most recent corrections models and references rec-ommended for altimeter products Each mission is processed separately as its needs depend on the baseinput data The list of corrections and models currently applied is provided in tables 3 and 4 for NRT dataThe system includes SLA filtering to process OGDR data DUACS extract from these data sets the shortscales (space and time) which are useful to better describe the ocean variability in real time and merge thisinformation with a fair description of large scale signals provided by the multi-satellite observation in nearreal time (read IGDR-based DUACS data) Finally an hybrid SLA is computed
Figure 7 Merging pertinent information from IGDR and OGDR processing
III24 Input data quality control
The Input Data Quality Control is a critical process applied to guarantee that DUACS uses only the mostaccurate altimeter data Thanks to the high quality of current missions this process rejects a small percent-age of altimeter measurements but these erroneous data could be the cause of a significant quality lossThe quality control relies on standard raw data editing with quality flags or parameter thresholds but alsoon complex data editing algorithms based on the detection of erroneous artefacts mono and multi-missioncrossover validation and macroscopic statistics to edit out large data flows that do not meet the systemrsquosrequirements
Page 26
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III25 Multi-mission cross-calibration
The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistentand accurate information It removes any residual orbit error (OE Le Traon and Ogor 1998[32]) or longwavelength error (LWE Le Traon et al 1998[31]) as well as large scale biases and discrepancies betweenvarious data flows
This process is based on two very different algorithms a global multi-mission crossover minimization fororbit error reduction (OER) and Optimal Interpolation (OI) for LWE
Multi-satellite crossover determination is performed on a daily basis All altimeter fields (measurementcorrections and other fields such as bathymetry MSS) are interpolated at crossover locations and datesCrossovers are then appended to the existing crossover database as more altimeter data become availableThis crossover data set is the input of the Orbit Error Reduction (OER) method Using the precision of thereference mission orbit a very accurate orbit error can be estimated This processing step does not concernOGDR dataLWE is mostly due to residual tidal or inverse barometer errors and high frequency ocean signals The OIused for LWE reduction uses precise parameters derived from
bull accurate statistical description of sea level variability
bull localized correlation scales
bull mission-specific noise and precise assumptions on the long wavelength errors to be removed (from arecent analysis of one year of data from each mission)
Page 27
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III26 Product generation
The product generation process is composed of four steps computation of raw SLA cross-validationfilteringampsub-sampling and generation of by-products
III261 Computation of raw SLA
Since the geoid is not well known yet the SSH cannot be used directly the SSH anomalies are used insteadThey are computed from the difference of the instantaneous SSH - a temporal reference This temporalreference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeattrack analysis cannot be used The errors affecting the SLAs MPs and MSS have different magnitudes andwavelengths The computation of the SLAs and their errors associated are detailed in Dibarboure et al 2010[9]
Use of a Mean ProfileIn the repeat track analysis (when the satellites flies over a repetitive orbit) measurements are re-sampledalong a theoretical ground track (or mean track) associated to each mission Then a Mean Profile (MP) issubtracted from the re-sampled data to obtain SLA The MP is a time average of similarly re-sampled dataover a long period
bull The Mean Profile used for Jason-2 is computed with 10 years of TP (cycles 11 to 353) and 6 years ofJason-1 (cycles 11 to 250)
bull The Mean Profile used from Jason-1 cycle 262 to 374 (where satellites are on interleaved ground-tracks) is computed with 3 years of TP (cycles 369 to 479)
bull No Mean Profile can be used for Envisat on its new orbit (enn) Jason-1 on its geodetic orbit (j1g) norfor Cryosat-2 mission (c2) because there is no repetitive track The MSS must be used instead (seebelow)
Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible
bull Indeed as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide precise cross-track projection andor interpolation schemes are required to avoid errors
bull The mesoscale variability error (which is lt35 cm for MP between 3 to 5 years and lt1cm for WLof 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a prioriknowledge from Sea Level maps derived from previous iterations or from other missions
bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
Page 28
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for Envisat since november 2010 and for Cryosat-2 mission (c2)because the satellite is not in a repetitive orbit phase The alternative is to use the MSS instead The griddedMSS is derived from along track MPs and data from geodetic phases Thus any error on the MP is alsocontained in the MSS There are essentially 4 types of additional errors on gridded MSS which are hard toquantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
Note that for the Arctic regional products the DTU10 MSS [1] is taken into account instead of the CLS01MSS Indeed the accuracy of DTU10 compared to CLS01 is further demonstrated by the significant sealevel anomaly variance reduction found over the whole Arctic Ocean as shown in Prandi et al [42]
III262 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III263 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
Page 29
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III27 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III271 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
Page 30
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III272 Performance indicators
To appreciate the quality situation of the DUACS system new performance indicators are computed dailyThey aim at evaluate the status of the main processing steps of the system the input data availability theinput data coverage the input data quality and the output product quality These indicators are computed foreach and every currently working satellite and combined to obtain the overall status
Figure 8 Example with the key performance indicator on 20090627
See the description the latest and previous indicators on Aviso websitehttpwwwavisooceanobscomindexphpid=1516
Page 31
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III3 Delayed Time processing steps
III31 Input data models and corrections applied
Delayed Time MyOcean products are generated
bull from Aviso GDR products for TP Jason-1 Jason-2 and Envisat (GDR-A cycles 1 to 22 GDR-Bcycles 23 to 85 GDR-C from cycle 86)
bull from NOAA GDR for GFO and from CERSAT (IFREMER) OPR for ERS-1 and ERS-2 (phases C(1st 35-day repeat orbit period) phase E and F (geodetic phases) phase G for ERS-1 (last 35-dayrepeat orbit period tandem phase with ERS-2 phase A for ERS-2 (1st 35-day repeat orbit periodtandem phase with ERS-1))
All GDR products are computed with a Precise Orbit Ephemeris (POE) and are delivered within 2 to 3months depending on the mission For several missions an updated orbit is used
bull For ERS-1amp-2 the orbit used is DGME-04 provided by Delft Institute (httpwwwdeostudelftnl)until June 2003
bull For TopexPoseidon the orbit used is GSFC (std0809) for the whole mission
bull For Envisat CNES POE of GDR-C standard is used for the whole mission
bull For the whole GFO mission the orbit used is GSFC (std0809) and when not available NASA POE isused
Altimetric product Source Availability Type of orbit
TopexPoseidon GDR NASACNES - GSFC POE
Jason-1 GDR (GDR-C) CNESNASA ~40 days CNES POE
Jason-2 GDR (GDR-C) CNESNASA ~60 days CNES POE
GFO GDR NOAA - GSFCNASA POE
ERS-1amp2 IFREMERESA - DGME-04
Envisat (GDR-A GDR-B andGDR-C from cycle 86)
ESA ~2 months CNES POE
Table 5 SSALTODUACS Delayed Time Input data overview
Page 32
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
DU
AC
S20
11D
Tpr
oduc
t(gtV
30
0)j2
j1j1
ntp
tpn
e1e2
ene
nng2
Prod
uct
stan
dard
ref
GD
R-C
OPR
GD
R-A
(Cyc
les
1to
22)
GD
R-B
(cyc
les
23-8
5)
GD
R(N
OA
A)
Orb
itC
nes
POE
GSF
C(I
TR
F20
05G
RA
CE
last
stan
dard
s)
DG
ME
-04
(Sch
arro
oan
dV
isse
r19
98[4
8]C
NE
SPO
E(G
DR
-1st
anda
rds
forc
ycle
s9
to22
GD
R-C
stan
dard
sfr
omcy
cle
23)
GSF
C(I
TR
F20
05
GR
AC
Ela
stst
anda
rds
Iono
pher
icD
ual f
requ
ency
altim
eter
rang
em
easu
rem
ents
Dua
l fre
quen
cyal
timet
erra
nge
mea
sure
men
ts(T
opex
)D
OR
IS(P
OSE
IDO
N)
Ben
t mod
elB
ent m
odel
(cyc
les
1-36
)G
IMm
odem
from
cycl
e37
((Ii
jima
etal
19
98[2
4])
Dua
l-fr
eque
ncy
altim
eter
rang
em
easu
rem
ent(
cycl
e9-
64)a
ndG
IMm
odel
gtcyc
le65
(Iiji
ma
etal
19
99[2
4])c
orre
cted
from
8m
mbi
as
From
GIM
mod
el(I
ijim
aet
al1
998
[24]
)
Dry
trop
o-sp
here
Mod
elco
mpu
ted
from
EC
MW
FG
auss
ian
grid
s(n
ewS1
and
S2at
mos
pher
ictid
esar
eap
plie
d)
Mod
elco
mpu
ted
from
EC
MW
Fre
ctan
gula
rgri
ds(n
ewS1
and
S2at
mos
pher
ictid
esar
ein
clud
ed)
Wet
trop
o-sp
here
JMR
AM
Rra
diom
eter
furt
hert
han
50km
from
the
coas
tsF
rom
EC
MW
Fm
odel
ford
ista
nces
betw
een
10an
d50
km
TM
Rra
diom
eter
(Sch
aroo
etal
20
04[4
9])
MW
RC
orre
ctio
nof
the
drif
ton
the
236
GH
zbr
ight
ness
tem
pera
ture
(Sch
arro
oet
al
2004
[49]
)Neu
ral
Net
wor
kal
gori
thm
(Tra
nan
dO
blig
is
2003
[50]
MW
Rra
diom
eter
furt
hert
han
50km
from
the
coas
tsan
dco
rrec
ted
from
side
lobe
s(f
rom
cycl
e41
)E
CM
WF
mod
elfo
rdis
tanc
esbe
twee
n10
and
50km
GFO
radi
omet
er
DA
CM
OG
2DH
igh
Res
olut
ion
forc
edw
ithE
CM
WF
pres
sure
and
win
gfie
lds
(S1
and
S2w
ere
excl
uded
)+in
vers
eba
rom
eter
com
pute
dfr
omre
ctan
gula
rgri
ds
Tabl
e6
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(1
2)
Page 33
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
j2j1
j1n
tptp
ne1
e2en
enn
g2O
cean
tide
GO
T4v
7(S
1an
dS2
are
incl
uded
)Po
letid
e[W
ahr
1985
[53]
]So
lidea
rth
tide
Ela
stic
resp
onse
totid
alpo
tent
ial[
Car
twri
ghta
ndTa
yler
197
1[5]
][C
artw
righ
tand
Edd
en1
973[
6]]
Loa
ding
tide
GO
T4v
7(S
1pa
ram
eter
isin
clud
ed)
Sea
stat
ebi
asN
onpa
ram
etri
cSS
B[G
aspa
reta
l20
02[2
0]]
Non
para
met
ric
SSB
[NT
ran
and
al2
010[
51]]
BM
3[G
aspa
ran
dO
gor
1994
[17]
]
Non
para
met
ric
SSB
[Mer
tzet
al
2005
[38]
]
Non
para
met
ric
SSB
[Gas
pare
tal
2002
]w
ithG
DR
-Bst
anda
rds
forc
ycle
s9
to85
and
with
GD
R-C
stan
dard
sfr
omcy
cle
86
Non
para
met
ric
SSB
[NT
ran
etal
20
10[5
1]]
Orb
iter
ror
Glo
bal m
ulti-
mis
sion
cros
sove
rmin
imiz
atio
n(L
eTr
aon
and
Ogo
r19
98[3
2])
Lon
gw
ave-
leng
her
rors
Opt
imal
Inte
rpol
atio
n(L
eTr
aon
etal
19
98[3
1])
Inte
rcal
ibra
tion
Ref
eren
cefr
omcy
cle
11R
efer
ence
from
cycl
e1
to35
4C
orre
ctio
nof
regi
onal
bias
J2J
1de
duce
dfr
omin
terc
alib
ratio
nph
ase
(cyc
le11
J2)
Cor
rect
ion
ofgl
obal
biai
sJ1
TP
deacutedu
ced
from
inte
rcal
ibra
tion
phas
e(c
ycle
s11
J1)
Mea
npr
o-fil
e(s
eeII
I36
1)
Com
pute
dw
ithcy
cles
11-3
53T
Pda
taan
dw
ithcy
cles
11-2
50J1
data
ref
eren
ced
[199
319
99]
TP
J1 c
ompu
ted
with
cycl
es11
-353
TP
data
and
with
cycl
es11
-250
J1da
tar
efer
ence
d[1
993
1999
]T
PNJ
1Nc
ompu
ted
with
cycl
es36
9-47
9T
PNda
tar
efer
ence
d[1
993
1999
]
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
ref
eren
ced
[199
319
99]
EN
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
re
fere
nced
[199
319
99]
EN
Nu
seof
MSS
_CN
ES_
CL
S11
[39]
Com
pute
dw
ithcy
cles
37-1
87G
2da
ta
refe
renc
ed[1
993
1999
]
Peri
odof
use
from
cycl
e9
from
cycl
e9
cycl
es1
to48
1cy
cles
15to
43In
clud
ing
E-F
geod
etic
phas
es
cycl
es1
to83
from
cycl
e9
cycl
es37
to22
2
Tabl
e7
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(2
2)
Page 34
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III32 Acquisition
The acqusition process in Delayed time is much simpler than in Near Real time it consists in a synchronisa-tion process of all the auxiliary data required to homogenize propely the altimeter data sets The acquisitionstep uses the GDRs or the OPRs provided by the agencies
III33 Homogenization
The Homogenization process consists in applying the most recent corrections models and references rec-ommended for altimeter products Each mission is processed separately as its needs depend on the baseinput data The list of corrections and models currently applied is provided in tables 6 and 7 for DT data
III34 Input data quality control
The Input Data Quality Control is a critical process applied to guarantee that DUACS uses only the mostaccurate altimeter data Thanks to the high quality of current missions this process rejects a small percent-age of altimeter measurements but these erroneous data could be the cause of a significant quality lossThe quality control relies on standard raw data editing with quality flags or parameter thresholds but alsoon complex data editing algorithms based on the detection of erroneous artefacts mono and multi-missioncrossover validation and macroscopic statistics to edit out large data flows that do not meet the systemrsquosrequirements
Page 35
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III35 Multi-mission cross-calibration
The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistentand accurate information It removes any residual orbit error (OE Le Traon and Ogor 1998[32]) or longwavelength error (LWE Le Traon et al 1998[31]) as well as large scale biases and discrepancies betweenvarious data flows
This process is based on two very different algorithms a global multi-mission crossover minimization fororbit error reduction (OER) and Optimal Interpolation (OI) for LWE
Multi-satellite crossover determination is performed on a daily basis All altimeter fields (measurementcorrections and other fields such as bathymetry MSS) are interpolated at crossover locations and datesCrossovers are then appended to the existing crossover database as more altimeter data become availableThis crossover data set is the input of the Orbit Error Reduction (OER) method Using the precision of thereference mission orbit a very accurate orbit error can be estimated LWE is mostly due to residual tidalor inverse barometer errors and high frequency ocean signals The OI used for LWE reduction uses preciseparameters derived from
bull accurate statistical description of sea level variability
bull localized correlation scales
bull mission-specific noise and precise assumptions on the long wavelength errors to be removed (from arecent analysis of one year of data from each mission)
Page 36
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III36 Product generation
The product generation process is composed of four steps computation of raw SLA cross-validationfilteringampsub-sampling and generation of by-products
III361 Computation of raw SLA
Since the geoid is not well known yet the SSH cannot be used directly the SSH anomalies are used insteadThey are computed from the difference of the instantaneous SSH - a temporal reference This temporalreference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeattrack analysis cannot be used The errors affecting the SLAs MPs and MSS have different magnitudes andwavelengths The computation of the SLAs and their errors associated are detailed in Dibarboure et al 2010[9]
Use of a Mean ProfileIn the repeat track analysis (when the satellites flies over a repetitive orbit) measurements are re-sampledalong a theoretical ground track (or mean track) associated to each mission Then a Mean Profile (MP) issubtracted from the re-sampled data to obtain SLA The MP is a time average of similarly re-sampled dataover a long period
bull The Mean Profile used for TP (cycles 1 to 364) Jason-1 (cycles 1 to 259) and Jason-2 is computedwith 10 years of TP (cycles 11 to 353) and 6 years of Jason-1 (cycles 11 to 250)
bull The Mean Profile used for TP (cycles 368 to 481) and from Jason-1 cycle 262 to 374 (where satellitesare on interleaved ground-tracks) is computed with 3 years of TP (cycles 369 to 479)
bull The Mean Profile used for ERS-1 in its 35 days repetitive orbit mission ERS-2 and Envisat (only forthe first orbit before November 2010) is computed with 8 years of ERS-2 (cycles 1 to 85) and 6 yearsof Envisat (cycles 10 to 72)
bull No Mean Profile can be used for Envisat on its new orbit (enn) Jason-1 on its geodetic orbit (j1g)because there is no repetitive track The MSS must be used instead (see below)
bull The Mean Profile used for GFO is computed with 7 years of GFO cycles 37 to 187
Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible
bull Indeed as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide precise cross-track projection andor interpolation schemes are required to avoid errors
bull The mesoscale variability error (which is lt35 cm for MP between 3 to 5 years and lt1cm for WLof 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a prioriknowledge from Sea Level maps derived from previous iterations or from other missions
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bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for ERS-1 for its 168 days geodetic mission (phases E-F from April1994 to March 1995) or for Envisat since november 2010 because the satellite is not in a repetitive orbitphase The alternative is to use the MSS instead The gridded MSS is derived from along track MPs anddata from geodetic phases Thus any error on the MP is also contained in the MSS There are essentially 4types of additional errors on gridded MSS which are hard to quantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
III362 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III363 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
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III37 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III371 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
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IV MYOCEAN PRODUCTS
IV1 Near Real Time Products
The purpose of the NRT DUACS component is the acquisition of altimeter data from various altimeter mis-sions in near-real time (ie within a few days at most) the validation and correction of these altimeter datasets (ie edition and selection update of corrections and homogenization orbit error reduction) in order toproduce each day along-track productsProducts are as follows
Along-track products global and regional (Mediterranean and Black Seas Arctic Ocean and Europeareas)
bull Sea Level Anomaly (NRT-SLA) for each mission with NRT-SLA ephemeris
IV11 Delay of the products
The availability of the products in near real time is three to twelve hours after the measurement for along-track products Those products are delivered every day
IV12 Temporal availibility
The following table presents the available products by mission and by data periodNear real time products
NRT Jason-2 Jason-1 and Jason-1geodetic
Envisat new Cryosat-2
Temporal Time availability ymlowast
ongoingymlowast-20120303 for
repeat track and20120507-ongoing for
geodetic track
ymlowast
2012040820120101
ongoing
NRT-SLA X X X X
lowastym the temporal coverage for NRT products is fluctuating and depends on updates of Delayed Time prod-ucts When DT products are updated (3 to 4 times per year) the oldest NRT products are replaced by thebetter quality DT products so that the 2 series are overlapping on few weeks or few months
IV2 Delayed Time Products
The Delayed Time component of SSALTODUACS system is responsible for the production of processedJason-1 Jason-2 TP Envisat GFO ERS12 and even Geosat data in order to provide a homogeneousinter-calibrated and highly accurate long time series of SLA DT products are more precise than NRT products Two reasons explain this quality difference The firstone is the better intrinsic quality of the POE orbit used in the GDR processing The second reason is that
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in the DT DUACS processing the products can be computed optimally with a centred computation timewindow for OER LWE On the contrary in NRT case future data are not available so the computationtime window is not centred and therefore not optimalAs for NRT products improved altimeter corrections and processing algorithms are used ocean tide modelto correct altimeter data improved methods for orbit error reduction and mapping
Along-Track products global and regional (Mediterranean and Black Seas)
bull Sea Level Anomaly (DT-SLA) for each mission
IV21 Delay of the products
Weekly products are delivered The availability of the products in delayed time is at the best two monthsafter the date of the measurement The product generation needs all the GDR data of all the missions to takeinto account the best corrections as possible The time delay can be longer in the case of a missing mission
IV22 Temporal availibility
The following table presents the available products by mission and by data periodDelayed time SSALTODUACS products
Upd Jason-2 Jason-1new6
Jason-1 GFO Envisatnew6
Envisat ERS-16
ERS-2Topexnew6
Topex
TemporalTimeavailabil-ity
200810ymlowast
200902ymlowast
200204200810
200001200809
201010ymlowast
200210201010
199210200304
200209200510
199209200204
DT-SLA X X X X X X X X X
lowast ym those dates are updated regularly (3 to 4 times per year) and are avalaible when you download thedata at httpwwwmyoceaneuweb24-cataloguephp6 Jason-1 new orbit starting 200809 Envisat new orbit starting 201010 TP new orbit starting 200209 ERS-1The geodetic phases (E-F) are included There are no ERS-1 data between December 23 1993 and April 10 1994(ERS-1 phase D - 2nd ice phase) Note that during that time products are based only on TopexPoseidon data
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V DESCRIPTION OF THE PRODUCT SPECIFICATION
V1 General information
Product Specification SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001
Geographical coverage global
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 20-50km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001 Product Specification
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Product Specification SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002
Geographical coverage 55˚W-35˚E 30˚N-46˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002 Product Specification
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Product Specification SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003
Geographical coverage 27˚E-42˚E 40˚N-47˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003 Product Specification
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Product Specification SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004
Geographical coverage 25˚W-42˚E 21˚N-66˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004 Product Specification
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Product Specification SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005
Geographical coverage 0˚W-360˚E 50˚N-82˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005 Product Specification
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VI NOMENCLATURE OF FILES
VI1 Nomenclature of files downloaded through the MyOcean Web PortalDirectgetfile Service
VI11 Nomenclature of the product line
The description of the syntax for the SL TAC SLA products line is given by
SEALEVEL_ltREGIONgt_SLA_L3_ltDELAYgt_OBSERVATIONS_008_ltZONEgt_ltLETTERgtwhere
REGION GLO global geographic coverage product
BS Black Sea products
MED Mediterranean products
ARC Arctic products (for NRT products)
EUROPE Europe products (for NRT products)
DELAY NRT near real time products
RAN delayed time or reanalysis products
ZONE 001 number on 3 digits
002
003
004
LETTER a letter on 1 digit
b
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VI12 Nomenclature of the datasets
The nomenclature used is
dataset-duacs-ltdelaygt-ltzonegt-ltmissiongt-lttype of slagt-l3where the fileds in ltgt are described below
delay nrt near-real time productsran delayed time products
zone global global geographic coverage productmedsea Mediterranean productsblacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1 (only for ran)e2 ERS-2 (only for ran)tp TOPEXPoseidon (only for ran)tpn TOPEXPoseidon on its new orbit (only for
ran)g2 GFO (only for ran)j1 Jason-1 (only for ran)j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisat (only for ran)enn Envisat on its new orbitc2 Cryosat-2 (only for nrt)
type of sla sla filtered slasla_unfiltered non filtered sla (only for ran products)
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VI13 Nomenclature of the NetCdf files
The nomenclature used is
ltdelaygt_ltzonegt_ltmissiongt_sla_ltvariablegt_ltdatebegingt_ltdateendgt_ltdateprodgtnc where the fileds in ltgt are de-scribed below
delay nrt near-real time productsdt delayed time products
zone global global geographic coverage productmed Mediterranean products (for dt)mfstep Mediterranean products (for nrt)blacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1e2 ERS-2tp TOPEXPoseidontpn TOPEXPoseidon on its new orbitg2 GFOj1 Jason-1j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisatenn Envisat on its new orbitc2 Cryosat-2
variable vfec filtered and sub-sampled slavxxc non filtered and non sub-sampled sla (only
for dt)datebegin YYYYMMDD() beginning date of the datasetdateend YYYYMMDD() end date of the datasetdateprod YYYYMMDD production date of the dataset
() For dt data as the dates in the file names are rounded the user wanting data for date T has to read the filescontaining dates T+1 and T-1 in their name and check inside the files if there are some data for date T
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VII DATA FORMAT
This chapter presents the data storage format used for MyOcean products
VII1 NetCdf
The products are stored using the NetCDF format NetCDF (network Common Data Form) is an interface for array-oriented data access and a library that provides an implementation of the interface The netCDF library also definesa machine-independent format for representing scientific data Together the interface library and format support thecreation access and sharing of scientific data The netCDF software was developed at the Unidata Program Center inBoulder Colorado The netCDF libraries define a machine-independent format for representing scientific data Pleasesee Unidata NetCDF pages for more information and to retreive NetCDF software package onhttpwwwunidataucaredupackagesnetcdfindexhtml
NetCDF data is
bull Self-Describing A netCDF file includes information about the data it contains
bull Architecture-independent A netCDF file is represented in a form that can be accessed by computers with dif-ferent ways of storing integers characters and floating-point numbers
bull Direct-access A small subset of a large dataset may be accessed efficiently without first reading through allthe preceding data
bull Appendable Data can be appended to a netCDF dataset along one dimension without copying the dataset orredefining its structure The structure of a netCDF dataset can be changed though this sometimes causes thedataset to be copied
bull Sharable One writer and multiple readers may simultaneously access the same netCDF file
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VII2 Structure and semantic of NetCDF along-track files
The NetCDF Sea Level TAC files are based on the attribute data tags defined by the Cooperative OceanAtmosphereResearch Data Service (COARDS) and Climate and Forecast (CF) metadata conventions The CF convention gener-alises and extends the COARDS convention but relaxes the COARDS constraints on dimension and order and specifiesmethods for reducing the size of datasetsA wide range of software are available to write or read NetCDFCF files API are made available by UNIDATA(httpwwwunidataucaredusoftwarenetcdf)
bull CC++Fortran
bull Java
bull MATLAB Objective-C Perl Python R Ruby TclTk
In addition to these conventions the files are using a common structure and semantic
bull 1 dimension is defined
ndash time it is used to check NetCDF variables depending on time
bull 8 variables are defined
ndash short SLA contains the Sea Level Anomaly values for each time given
ndash int longitude contains the longitude for each measurement
ndash short track contains the track number for each measurement
ndash double time contains the time in days since 1950-01-01 000000 UTC for each measurement
ndash short mean_profile_point_index index of the corrsponding point in the track of the mean profile
ndash byte flag flag=0 the processed data comes from OGDR if flag=1 the processed data comes from theIGDR
ndash int latitude contains the latitude for each measurement
ndash short cycle contains the cycle number for each measurement
bull global attributes
ndash the global attributes gives information about the creation of the file
Example of a NetCDF sla file
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netcdf nrt_global_j1_sla_vfec_20101230_20101230_20101230 dimensions
time = 10385 variables
short SLA(time) SLAcoordinates = longitude latitude SLAlong_name = Sea Level Anomaly SLA_FillValue = 32767s SLAadd_offset = 0 SLAscale_factor = 0001 SLAunits = m SLAstandard_name = sea_surface_height_above_sea_level
int longitude(time) longitudelong_name = Longitude of measurement longitude_FillValue = 2147483647 longitudeadd_offset = 0 longitudestandard_name = longitude longitudescale_factor = 1e-06 longitudeunits = degrees_east
short track(time) tracklong_name = Track in cycle the measurement belongs to track_FillValue = 32767s trackunits = 1 trackcoordinates = longitude latitude
double time(time) timelong_name = Time of measurement time_FillValue = 184467440737096e+19 timeaxis = T timestandard_name = time timeunits = days since 1950-01-01 000000 UTC
int latitude(time) latitudelong_name = Latitude of measurement latitude_FillValue = 2147483647 latitudeadd_offset = 0 latitudestandard_name = latitude latitudescale_factor = 1e-06 latitudeunits = degrees_north
short flag(time) flagcoordinates = longitude latitude flag_FillValue = 3267s flaglong_name = data origin flagflag_values = 1s 0s flagflag_meanings = igdr_like non_igdr_like flagcomment = The origin of the data is determined by the types of geophysical datarecords (GDR) used in computation of the SLA 1 for the Interim GDR (IGDR) and0 for Operational GDR (OGDR)
short cycle(time) cyclelong_name = Cycle the measurement belongs to cycle_FillValue = 32767s cycleunits = 1 cyclecoordinates = longitude latitude
global attributeshistory = 22-Feb-2011 155243 CET File created by the SSLATODUACS system version 1001 comment = Produce from ENVISAT Extension Phase satellite altimetry data institution = CLSCNES
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references = httpwwwavisooceanobscomfileadmindocumentsdatatoolshdbk_duacspdf source = satellite altimetry title = along track Sea Level Anomaly Conventions = CF-14
dataSLA =
7 7 11 10 -2 -22 -39 -41 -30 -13 -3 -5 -16 -26 -32 -35-35 -35 -37 -35 -31 -29 -31 -35 -32 -21 -10 -10 -19 -20 -1-69 -57 -49 -45 -39 -30 -28 -31 -27 -13 -2 -5 -15 -3 1112 3 -7 -10 -14 -15 -22 -31 -37 -32 -17 -10
longitude =74743328 74868400 74993968 75120040 75246616 7537372875501368 75629568 75758320 75887656 76017568 76148080 7627920876388952 76477056 76565456 76654144 76743128 76832400 76921984329429568 329535424 329641792 329748672 329856096 329964032330072512 330181536 330291072 330401184
track =92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 9292 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92113 113 113 113 113 113 113 113 113 113 113 113 113 113113 113 113 113 113 113 113 113 113
time =222780000565705 222780001314719 222780002063733222780002812747 222780003561761 222780004310775 222780005059788222780005808802 222780006557816 22278000730683 222780008055844222780008804858 222780009553872 22278001017805 222780010677393222788257112198 222788257486705 222788257861212 222788258235719222788258610226 222788258984733 222788259359239 222788259733746222788260108253 22278826048276
mean_profile_point_index =1872 1878 1884 1890 1896 1902 1908 19141920 1926 1932 1938 1944 1949 1953 1957 1961 1965 1969 19732306 2309 2312 2315 2318 2321 2327 2330 2333 2336 2339 23422345 2348 2351 2354 2357 2360 2363 2366
flag =0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
latitude =-16225506 -16539731 -16853833 -17167810 -17481660 -17795380-18108966 -18422418 -18735729 -19048899 -19361924 -19674801-19987527 -20248015 -20456329 -20664569 -20872739 -2108083739481297 39628277 39775133 39921866 40068472 40214953 4036130840507533 40653629 40799592 40945423 41091120 41236684 41382111
cycle =331 331 331 331 331 331 331 331 331 331 331 331 331
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331 331 331 331 331 331 331 331 331 331 331 331 331 331331 331 331 331 331 331 331 331 331 331 331 331
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VIII HOW TO DOWNLOAD A PRODUCT
VIII1 Download a product through the MyOcean Web Portal DirectgetfileService
You first need to register Please find below the registration stepshttpwwwmyoceaneuweb34-products-and-services-faqphp1Once registered the MyOcean FAQ httpwwwmyoceaneuweb34-products-and-services-faqwill guide you on How to download a product through the MyOcean Web Portal Directgetfile Service
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IX NEWS AND UPDATES
IX1 [Duacs] Operational news
To be kept informed on events occurring on the satellites and on the eventual interruption of the services of the DUACSprocessing system see the [Duacs] operational news on the Aviso websitehttpwwwavisooceanobscomendataoperational-newsindexhtml
IX2 Updates
To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtmlSince 2010 a complete reprocessing of all altimetry data (cumulated total of about 55 years of data) is available Themain changes introduced in the Duacs DT v300 reprocessed data set in SSALTODUACS reprocessed DT data setare listed herehttpwwwavisooceanobscomfileadmindocumentsdataduacsduacs_DT_2010_reprocessing_impactpdf
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For this new phase of the Jason-1 mission (called j1g) the cycle numbering will restart at 500 Off-lineproducts will be produced once a day for the IGDR and every 11 days for the GDRrsquos The integration ofJason-1 data in the DUACS system is available since May 25th 2012
II3 Envisat has stopped sending data (April 2012)
Since April 8th 2012 Envisat has stopped sending data to Earth Esarsquos mission control has worked tore-establish contact with the satellite but there has been no reaction from the satellite Thus Esa has de-clared officially the end of mission for Envisat (see httpwwwesaintesaCPSEM1SXSWT1H_index_0html) Therefore no SL TAC NRT data from Envisat can be released since this date
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II4 Integration of the Cryosat2 Mission (February 2012)
Since February 6th 2012 Cryosat-2 mission has been integrated in the DUACS sytem This mission isdedicated to the observation of the floating sea-ice as well as the continental ice sheets but all data acquiredover ocean are valuable for the observation of oceanic circulation and mesoscale variations This majorchange is the result of the long-standing and fruitful partnership between ESA and CNES and a responseto the request from scientific and operational oceanography users [7] The integration of Cryosat-2 impactsthe delivering of Near real time Sea Level Anomalies (SLA)
II41 Generalities about the mission
A Cryosat-2 Processing Prototype (C2P) (described in Boy et al 2011 [2]) has been developed on CNESside to lay the ground for various SAR processing studies The processing chains ingest Level-0 telemetryfiles distributed by ESA and perform the following steps to generate Sea Level Anomalies (SLA) values foreach altimeter measurements
bull Level-1 Decommutation time-tagging and localization of measurements
bull Level-1b Calculation of instrumental corrections and geophysicalmeteorological corrections
bull Level-2 MLE4 waveforms Retracking and calculation of SLA
The prototype processes data almost continuously over ocean either in Low Resolution Mode (LRM) or inthe DopplerSAR mode processed as pseudo-LRM mode allowing to increase the coverage (figure 2)
Figure 2 SSH-MSS for Cryosat-2 with LRM mode only (left) or LRM+pseudo-LRM modes (right)
Although Cryosat-2 raw SSH can be only corrected with GPS-derived ionospheric correction and ECMWFwet troposphere correction validation activities showed (Labroue et al 2011 [25]) that C2P outputs have anaccuracy roughly equivalent to Envisatrsquos Level 2 products if the latter are processed with the same standards
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II42 Integration in DUACS
The Cryosat-2 data are included in the Near Real time process The chain delivers now (for global coverageMediterranean and Black Seas) along track data from Cryosat-2 (SLAs) Note that the products distributedare of Level-3 and donrsquot replace Level-2 products distributed by agenciesThe details of the processing are given in Dibarboure et al 2011 [8]Here we just give an overview the data are computed with the corrections given in section III21 Thefiltering and sub-sampling of SLAs (section III263) are detailed in [8]
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II5 Addition of Europe and Arctic products (January 2012)
Since the MyOcean V2 two new along-track products are computed in Near Real Time intended foraddressing the needs of data assmilation and validation in regional models
bull Following the TAPAS (Tailored Altimeter Product for Assimilation Systems) initiative launched bySL TAC with all the Modeling and Forecasting Centers (MFCs) the Europe regional products (PLSEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004) have been proposed (figure 3) They areavailable in Near Real Time onlyThey are studied to partly fulfil the needs of the Centers with adapted filtering and resolution Thoseparameters have been tuned in order to provide boundary conditions for the Atlantic assimilationmodels They are different from the ones used for Mediterranean and Black Seas products If you needto study the Mediterranean Sea or the Black Sea yoursquod better use the dedicated products describedabove since the processing parameters have been fitted to be adapted to the dynamics of the ocean inthose regions
Figure 3 Coverage of the Europe product for Jason-1 Jason-2 and Envisat from August 18th to September9th 2011
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bull The Arctic along-track products (PL SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005) coverlatitudes between 45 and 82 degrees (figure 4) They are available in Near Real Time only
Figure 4 Coverage of the Arctic region with Envisat from October 28th 2011 to January 3rd 2012
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III SSALTODUACS SYSTEM
III1 Introduction
This chapter presents the input data used by SSALTODUACS system and an overview of the different pro-cessing steps necessary to produce the output dataSSALTODUACS system is made of two components a Near Real Time one (NRT) and a Delayed Time(DT) oneIn NRT the systemrsquos primary objective is to provide operational applications with directly usable high qual-ity altimeter data from all missions availableIn DT it is to maintain a consistent and user-friendly altimeter database using the state-of-the-art recom-mendations from the altimetry communityFollowing figure gives an overview of DUACS system where processing sequences can be divided into 7main steps
bull acquisition
bull homogenization
bull input data quality control
bull multi-mission cross-calibration
bull product generation
bull merging
bull final quality control
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Figure 5 SSALTODUACS processing sequences
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III2 Near Real Time processing steps
III21 Input data models and corrections applied
To produce SLA in near-real time the DUACS system uses two flows based on the same instrumental mea-surements but with a different quality
bull The IGDR that are the latest high-quality altimeter data produced in near-real-time
bull The OGDR that includes real time data (OSTMJason-2 and Jason-1 OSDR) to complete IGDR Thesefast delivery products do not always benefit from precise orbit determination nor from some exter-nal model-based corrections (Dynamic Atmospheric Correction (DAC) Global Ionospheric Maps(GIM))
Integration of OGDR data and the introduction of Jason-2Jason-1 tandem increased the resilience and pre-cision of the system A better restitution of ocean variability is observed especially in high energetic areas
Altimetric product Source Availability Type of orbit
Jason-2 IGDR CNES ~24h CNES MOE GDR-Cuntil 20120730
CNES MOE GDR-Dsince 20120731
OGDR NOAAEUMETSAT ~3 to 5 h
Jason-1 IGDR CNESNASA ~48 h CNES MOE GDR-Dsince 20120507
OGDR CNESNASA ~3 to 12 h
Envisat IGDR ESACNES not deliveredsince 20120408
CNES MOE GDR-Dsince 20120121
FDGDR ESA not deliveredsince 20120408
Cryosat-2 IGDR-like ESACNES ~48 h CNES MOE GDR-D
not delivered
Table 2 SSALTODUACS Near-Real Time Input data overview
See Figure 6 Overview of the near real time system data flow management
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DUACS 2011 NRT product from IGDR1
j2 j1nj1g enn c2Productstandard ref
version C until20120730 and D after
version C version 21 CPP [2]
Orbit CNES MOE GDR-Cuntil 20120730
GDR-D after
CNES MOE GDR-C forj1n and CNES MOE
GDR-D for j1g
CNES MOE GDR-Dfrom 20120121 to
20120408
CNES MOE GDR-D
Ionopheric bi-frequency altimeter range measurements GIM model for cgt64 (Iijima et al1998[24])Dry tropo Model computed from ECMWF Gaussian grids (new S1 and S2 atm tides applied)Wet tropo-sphere
AMR radiometer(enhancement in coastal
regions since20120730)
JMR radiometer MWR radiometer andcorrected from side
lobes
Model computed fromECMWF Gaussian
grids
DAC MOG2D High Resolution forced with ECMWF pressure and wind fields (S1 and S2 wereexcluded) (Carrere and Lyard 2003[3])+ inverse barometer Filtering temporal window is
un-centered (no data in the future)Ocean tide GOT4v8 (S1 and S2 are included) and TPX 072 [16] for Arctic productsPole tide [Wahr 1985 [53]]Solid earthtide
Elastic response to tidal potential [Cartwright and Tayler 1971[5]] [Cartwright andEdden 1973[6]]
Loading tide GOT4v8 (S1 and S2 are included)Sea statebias
Non parametric SSB[Labroue 2004[27]](with cycles J1 1 to 11
using GDR-B standardsuntil 20120730 andderived from Jason-2
after)
Non parametric SSB[Labroue 2004[27]](with cycles 1 to 21
using GDR-Bstandards)
Non parametric SSB[Labroue 2004[27]](with cycles 41 to 60
using GDR-Bstandards)
Same as Jason-2 SSB
Orbit error Global multi-mission crossover minimization (Le Traon and Ogor1998[32])
Long wave-lengh errors
Optimal Interpolation [Le Traon et al 1998[31]]
Intercalibration Reference from cycle20
Mean pro-file (seeIII261)
Computed with cycles11-353 TP data andwith cycles 11-250J1 data referenced[19931999]
TPNJ1N computedwith cycles 369-479TPN data refer-enced [19931999]J1G No MP can beused instead theMSS_CNES_CLS11[39] is used
No Mean Profilecan be used forEnvisat on its neworbit Instead theMSS_CNES_CLS11[39] is used
No Mean Profilecan be used forCryosat-2 Instead theMSS_CNES_CLS11[39] is used
(1) A flag included in the along-track files indicates the source of the production (OGDRFDGDR orIGDR) If flag=0 the processed data comes from OGDRsFDGDRs if flag=1 the processed data comesfrom IGDRs
Table 3 Corrections and models applied in SSALTODUACS NRT products produced from IGDRs
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DUACS 2011 NRT product from OGDR or FDGDR2
j2 j1nj1g ennProduct stan-dard ref
version C until 20120730and D after
version C version 21
Orbit Navigator Extrapolated CNES MOEGDR-D since 20120121
Ionopheric From-dual frequency altimeter range measurements From GIM model fromcycle 65 (Iijima et al1998 [24])
Dry troposphere Model computed from ECMWF Gaussian grids (new S1 and S2 atmospherictides are applied)
Wet tropo-sphere
AMR radiometer(enhancement in coastal
regions since 20120730)
JMR radiometer MWR radiometer andcorrected from side lobes
DAC Inverse Barometer forecastedOcean tide GOT4v8 (S1 and S2 are included) and TPX 072 [16] for Arctic productsPole tide [Wahr 1985 [53]]Solid earth tide Elastic response to tidal potential [Cartwright and Tayler 1971[5]]
[Cartwright and Edden 1973[6]]Loading tide GOT4v8 (S1 and S2 are included)Sea state bias Non parametric SSB
[Labroue 2004[27]] (withcycles J1 1 to 11 usingGDR-B standards until20120730 and derivedfrom Jason-2 after)
Non parametric SSB[Labroue 2004[27]](with cycles 1 to 21 usingGDR-B standards)
Non parametric SSB[Labroue 2004[27]](with cycles 41 to 60using GDR-B standards)
Orbit error Specific filtering of long-wavelength signal3
Long wave-lengh errors
Optimal Interpolation [Le Traon et al 1998[31]]
Intercalibration Reference from cycle 20Mean profile(see III261)
Computed with cycles 11-353 TP data and with cy-cles 11-250 J1 data refer-enced [19931999]
TPNJ1N computedwith cycles 369-479TPN data referenced[19931999] J1G NoMP can be used insteadthe MSS_CNES_CLS11[39] is used
No Mean Profile can beused for Envisat on itsnew orbit Instead theMSS_CNES_CLS11 [39]is used
(2) A flag included in the along-track files indicates the source of the production (OGDRFDGDR orIGDR) If flag=0 the processed data comes from OGDRsFDGDRs if flag=1 the processed data comesfrom IGDRs(3) Specific data processing was applied on long wave-length signal (sectIII23 of the user manual)
Table 4 Corrections and models applied in SSALTODUACS NRT products produced from OG-DRsFDGDRs
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III22 Acquisition
The acquisition process is twofold
bull straightforward retrieval and reformatting of altimeter data and dynamic auxiliary data (pressure andwet troposphere correction grids from ECMWF are provided by Meteo France TEC grids from JPLNRT MOG2D corrections) from external repositories
bull synchronisation process
To be homogenized properly altimeter data sets require various auxiliary data The acquisition softwaredetects downloads and processes incoming data as soon as they are available on remote sites (externaldatabase FTP site) Data are split into passes if necessary If data flows are missing or late the synchroni-sation engine put unusable data in waiting queues and automatically unfreezes them upon reception of themissing auxiliary data This processing step delivers raw data that is to say data that have been dividedinto cycles and passes and ordered chronologicallyFrom SSALTODUACS V80 the acquisition step uses two different data flows in near-real time the OGDRflow (within a few hours) and the IGDR flow (within a few days)For each OGDR input the system checks that no equivalent IGDR entry is available in the data base beforeacquisition for each IGDR input the system checks and delete the equivalent OGDR entry in the data baseThese operations aim to avoid duplicates in SSALTODUACS system
Figure 6 Overview of the near real time system data flow management
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III23 Homogenization
The Homogenization process consists in applying the most recent corrections models and references rec-ommended for altimeter products Each mission is processed separately as its needs depend on the baseinput data The list of corrections and models currently applied is provided in tables 3 and 4 for NRT dataThe system includes SLA filtering to process OGDR data DUACS extract from these data sets the shortscales (space and time) which are useful to better describe the ocean variability in real time and merge thisinformation with a fair description of large scale signals provided by the multi-satellite observation in nearreal time (read IGDR-based DUACS data) Finally an hybrid SLA is computed
Figure 7 Merging pertinent information from IGDR and OGDR processing
III24 Input data quality control
The Input Data Quality Control is a critical process applied to guarantee that DUACS uses only the mostaccurate altimeter data Thanks to the high quality of current missions this process rejects a small percent-age of altimeter measurements but these erroneous data could be the cause of a significant quality lossThe quality control relies on standard raw data editing with quality flags or parameter thresholds but alsoon complex data editing algorithms based on the detection of erroneous artefacts mono and multi-missioncrossover validation and macroscopic statistics to edit out large data flows that do not meet the systemrsquosrequirements
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III25 Multi-mission cross-calibration
The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistentand accurate information It removes any residual orbit error (OE Le Traon and Ogor 1998[32]) or longwavelength error (LWE Le Traon et al 1998[31]) as well as large scale biases and discrepancies betweenvarious data flows
This process is based on two very different algorithms a global multi-mission crossover minimization fororbit error reduction (OER) and Optimal Interpolation (OI) for LWE
Multi-satellite crossover determination is performed on a daily basis All altimeter fields (measurementcorrections and other fields such as bathymetry MSS) are interpolated at crossover locations and datesCrossovers are then appended to the existing crossover database as more altimeter data become availableThis crossover data set is the input of the Orbit Error Reduction (OER) method Using the precision of thereference mission orbit a very accurate orbit error can be estimated This processing step does not concernOGDR dataLWE is mostly due to residual tidal or inverse barometer errors and high frequency ocean signals The OIused for LWE reduction uses precise parameters derived from
bull accurate statistical description of sea level variability
bull localized correlation scales
bull mission-specific noise and precise assumptions on the long wavelength errors to be removed (from arecent analysis of one year of data from each mission)
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III26 Product generation
The product generation process is composed of four steps computation of raw SLA cross-validationfilteringampsub-sampling and generation of by-products
III261 Computation of raw SLA
Since the geoid is not well known yet the SSH cannot be used directly the SSH anomalies are used insteadThey are computed from the difference of the instantaneous SSH - a temporal reference This temporalreference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeattrack analysis cannot be used The errors affecting the SLAs MPs and MSS have different magnitudes andwavelengths The computation of the SLAs and their errors associated are detailed in Dibarboure et al 2010[9]
Use of a Mean ProfileIn the repeat track analysis (when the satellites flies over a repetitive orbit) measurements are re-sampledalong a theoretical ground track (or mean track) associated to each mission Then a Mean Profile (MP) issubtracted from the re-sampled data to obtain SLA The MP is a time average of similarly re-sampled dataover a long period
bull The Mean Profile used for Jason-2 is computed with 10 years of TP (cycles 11 to 353) and 6 years ofJason-1 (cycles 11 to 250)
bull The Mean Profile used from Jason-1 cycle 262 to 374 (where satellites are on interleaved ground-tracks) is computed with 3 years of TP (cycles 369 to 479)
bull No Mean Profile can be used for Envisat on its new orbit (enn) Jason-1 on its geodetic orbit (j1g) norfor Cryosat-2 mission (c2) because there is no repetitive track The MSS must be used instead (seebelow)
Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible
bull Indeed as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide precise cross-track projection andor interpolation schemes are required to avoid errors
bull The mesoscale variability error (which is lt35 cm for MP between 3 to 5 years and lt1cm for WLof 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a prioriknowledge from Sea Level maps derived from previous iterations or from other missions
bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for Envisat since november 2010 and for Cryosat-2 mission (c2)because the satellite is not in a repetitive orbit phase The alternative is to use the MSS instead The griddedMSS is derived from along track MPs and data from geodetic phases Thus any error on the MP is alsocontained in the MSS There are essentially 4 types of additional errors on gridded MSS which are hard toquantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
Note that for the Arctic regional products the DTU10 MSS [1] is taken into account instead of the CLS01MSS Indeed the accuracy of DTU10 compared to CLS01 is further demonstrated by the significant sealevel anomaly variance reduction found over the whole Arctic Ocean as shown in Prandi et al [42]
III262 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III263 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
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III27 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III271 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
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III272 Performance indicators
To appreciate the quality situation of the DUACS system new performance indicators are computed dailyThey aim at evaluate the status of the main processing steps of the system the input data availability theinput data coverage the input data quality and the output product quality These indicators are computed foreach and every currently working satellite and combined to obtain the overall status
Figure 8 Example with the key performance indicator on 20090627
See the description the latest and previous indicators on Aviso websitehttpwwwavisooceanobscomindexphpid=1516
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III3 Delayed Time processing steps
III31 Input data models and corrections applied
Delayed Time MyOcean products are generated
bull from Aviso GDR products for TP Jason-1 Jason-2 and Envisat (GDR-A cycles 1 to 22 GDR-Bcycles 23 to 85 GDR-C from cycle 86)
bull from NOAA GDR for GFO and from CERSAT (IFREMER) OPR for ERS-1 and ERS-2 (phases C(1st 35-day repeat orbit period) phase E and F (geodetic phases) phase G for ERS-1 (last 35-dayrepeat orbit period tandem phase with ERS-2 phase A for ERS-2 (1st 35-day repeat orbit periodtandem phase with ERS-1))
All GDR products are computed with a Precise Orbit Ephemeris (POE) and are delivered within 2 to 3months depending on the mission For several missions an updated orbit is used
bull For ERS-1amp-2 the orbit used is DGME-04 provided by Delft Institute (httpwwwdeostudelftnl)until June 2003
bull For TopexPoseidon the orbit used is GSFC (std0809) for the whole mission
bull For Envisat CNES POE of GDR-C standard is used for the whole mission
bull For the whole GFO mission the orbit used is GSFC (std0809) and when not available NASA POE isused
Altimetric product Source Availability Type of orbit
TopexPoseidon GDR NASACNES - GSFC POE
Jason-1 GDR (GDR-C) CNESNASA ~40 days CNES POE
Jason-2 GDR (GDR-C) CNESNASA ~60 days CNES POE
GFO GDR NOAA - GSFCNASA POE
ERS-1amp2 IFREMERESA - DGME-04
Envisat (GDR-A GDR-B andGDR-C from cycle 86)
ESA ~2 months CNES POE
Table 5 SSALTODUACS Delayed Time Input data overview
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
DU
AC
S20
11D
Tpr
oduc
t(gtV
30
0)j2
j1j1
ntp
tpn
e1e2
ene
nng2
Prod
uct
stan
dard
ref
GD
R-C
OPR
GD
R-A
(Cyc
les
1to
22)
GD
R-B
(cyc
les
23-8
5)
GD
R(N
OA
A)
Orb
itC
nes
POE
GSF
C(I
TR
F20
05G
RA
CE
last
stan
dard
s)
DG
ME
-04
(Sch
arro
oan
dV
isse
r19
98[4
8]C
NE
SPO
E(G
DR
-1st
anda
rds
forc
ycle
s9
to22
GD
R-C
stan
dard
sfr
omcy
cle
23)
GSF
C(I
TR
F20
05
GR
AC
Ela
stst
anda
rds
Iono
pher
icD
ual f
requ
ency
altim
eter
rang
em
easu
rem
ents
Dua
l fre
quen
cyal
timet
erra
nge
mea
sure
men
ts(T
opex
)D
OR
IS(P
OSE
IDO
N)
Ben
t mod
elB
ent m
odel
(cyc
les
1-36
)G
IMm
odem
from
cycl
e37
((Ii
jima
etal
19
98[2
4])
Dua
l-fr
eque
ncy
altim
eter
rang
em
easu
rem
ent(
cycl
e9-
64)a
ndG
IMm
odel
gtcyc
le65
(Iiji
ma
etal
19
99[2
4])c
orre
cted
from
8m
mbi
as
From
GIM
mod
el(I
ijim
aet
al1
998
[24]
)
Dry
trop
o-sp
here
Mod
elco
mpu
ted
from
EC
MW
FG
auss
ian
grid
s(n
ewS1
and
S2at
mos
pher
ictid
esar
eap
plie
d)
Mod
elco
mpu
ted
from
EC
MW
Fre
ctan
gula
rgri
ds(n
ewS1
and
S2at
mos
pher
ictid
esar
ein
clud
ed)
Wet
trop
o-sp
here
JMR
AM
Rra
diom
eter
furt
hert
han
50km
from
the
coas
tsF
rom
EC
MW
Fm
odel
ford
ista
nces
betw
een
10an
d50
km
TM
Rra
diom
eter
(Sch
aroo
etal
20
04[4
9])
MW
RC
orre
ctio
nof
the
drif
ton
the
236
GH
zbr
ight
ness
tem
pera
ture
(Sch
arro
oet
al
2004
[49]
)Neu
ral
Net
wor
kal
gori
thm
(Tra
nan
dO
blig
is
2003
[50]
MW
Rra
diom
eter
furt
hert
han
50km
from
the
coas
tsan
dco
rrec
ted
from
side
lobe
s(f
rom
cycl
e41
)E
CM
WF
mod
elfo
rdis
tanc
esbe
twee
n10
and
50km
GFO
radi
omet
er
DA
CM
OG
2DH
igh
Res
olut
ion
forc
edw
ithE
CM
WF
pres
sure
and
win
gfie
lds
(S1
and
S2w
ere
excl
uded
)+in
vers
eba
rom
eter
com
pute
dfr
omre
ctan
gula
rgri
ds
Tabl
e6
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(1
2)
Page 33
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
j2j1
j1n
tptp
ne1
e2en
enn
g2O
cean
tide
GO
T4v
7(S
1an
dS2
are
incl
uded
)Po
letid
e[W
ahr
1985
[53]
]So
lidea
rth
tide
Ela
stic
resp
onse
totid
alpo
tent
ial[
Car
twri
ghta
ndTa
yler
197
1[5]
][C
artw
righ
tand
Edd
en1
973[
6]]
Loa
ding
tide
GO
T4v
7(S
1pa
ram
eter
isin
clud
ed)
Sea
stat
ebi
asN
onpa
ram
etri
cSS
B[G
aspa
reta
l20
02[2
0]]
Non
para
met
ric
SSB
[NT
ran
and
al2
010[
51]]
BM
3[G
aspa
ran
dO
gor
1994
[17]
]
Non
para
met
ric
SSB
[Mer
tzet
al
2005
[38]
]
Non
para
met
ric
SSB
[Gas
pare
tal
2002
]w
ithG
DR
-Bst
anda
rds
forc
ycle
s9
to85
and
with
GD
R-C
stan
dard
sfr
omcy
cle
86
Non
para
met
ric
SSB
[NT
ran
etal
20
10[5
1]]
Orb
iter
ror
Glo
bal m
ulti-
mis
sion
cros
sove
rmin
imiz
atio
n(L
eTr
aon
and
Ogo
r19
98[3
2])
Lon
gw
ave-
leng
her
rors
Opt
imal
Inte
rpol
atio
n(L
eTr
aon
etal
19
98[3
1])
Inte
rcal
ibra
tion
Ref
eren
cefr
omcy
cle
11R
efer
ence
from
cycl
e1
to35
4C
orre
ctio
nof
regi
onal
bias
J2J
1de
duce
dfr
omin
terc
alib
ratio
nph
ase
(cyc
le11
J2)
Cor
rect
ion
ofgl
obal
biai
sJ1
TP
deacutedu
ced
from
inte
rcal
ibra
tion
phas
e(c
ycle
s11
J1)
Mea
npr
o-fil
e(s
eeII
I36
1)
Com
pute
dw
ithcy
cles
11-3
53T
Pda
taan
dw
ithcy
cles
11-2
50J1
data
ref
eren
ced
[199
319
99]
TP
J1 c
ompu
ted
with
cycl
es11
-353
TP
data
and
with
cycl
es11
-250
J1da
tar
efer
ence
d[1
993
1999
]T
PNJ
1Nc
ompu
ted
with
cycl
es36
9-47
9T
PNda
tar
efer
ence
d[1
993
1999
]
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
ref
eren
ced
[199
319
99]
EN
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
re
fere
nced
[199
319
99]
EN
Nu
seof
MSS
_CN
ES_
CL
S11
[39]
Com
pute
dw
ithcy
cles
37-1
87G
2da
ta
refe
renc
ed[1
993
1999
]
Peri
odof
use
from
cycl
e9
from
cycl
e9
cycl
es1
to48
1cy
cles
15to
43In
clud
ing
E-F
geod
etic
phas
es
cycl
es1
to83
from
cycl
e9
cycl
es37
to22
2
Tabl
e7
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(2
2)
Page 34
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III32 Acquisition
The acqusition process in Delayed time is much simpler than in Near Real time it consists in a synchronisa-tion process of all the auxiliary data required to homogenize propely the altimeter data sets The acquisitionstep uses the GDRs or the OPRs provided by the agencies
III33 Homogenization
The Homogenization process consists in applying the most recent corrections models and references rec-ommended for altimeter products Each mission is processed separately as its needs depend on the baseinput data The list of corrections and models currently applied is provided in tables 6 and 7 for DT data
III34 Input data quality control
The Input Data Quality Control is a critical process applied to guarantee that DUACS uses only the mostaccurate altimeter data Thanks to the high quality of current missions this process rejects a small percent-age of altimeter measurements but these erroneous data could be the cause of a significant quality lossThe quality control relies on standard raw data editing with quality flags or parameter thresholds but alsoon complex data editing algorithms based on the detection of erroneous artefacts mono and multi-missioncrossover validation and macroscopic statistics to edit out large data flows that do not meet the systemrsquosrequirements
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PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III35 Multi-mission cross-calibration
The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistentand accurate information It removes any residual orbit error (OE Le Traon and Ogor 1998[32]) or longwavelength error (LWE Le Traon et al 1998[31]) as well as large scale biases and discrepancies betweenvarious data flows
This process is based on two very different algorithms a global multi-mission crossover minimization fororbit error reduction (OER) and Optimal Interpolation (OI) for LWE
Multi-satellite crossover determination is performed on a daily basis All altimeter fields (measurementcorrections and other fields such as bathymetry MSS) are interpolated at crossover locations and datesCrossovers are then appended to the existing crossover database as more altimeter data become availableThis crossover data set is the input of the Orbit Error Reduction (OER) method Using the precision of thereference mission orbit a very accurate orbit error can be estimated LWE is mostly due to residual tidalor inverse barometer errors and high frequency ocean signals The OI used for LWE reduction uses preciseparameters derived from
bull accurate statistical description of sea level variability
bull localized correlation scales
bull mission-specific noise and precise assumptions on the long wavelength errors to be removed (from arecent analysis of one year of data from each mission)
Page 36
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III36 Product generation
The product generation process is composed of four steps computation of raw SLA cross-validationfilteringampsub-sampling and generation of by-products
III361 Computation of raw SLA
Since the geoid is not well known yet the SSH cannot be used directly the SSH anomalies are used insteadThey are computed from the difference of the instantaneous SSH - a temporal reference This temporalreference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeattrack analysis cannot be used The errors affecting the SLAs MPs and MSS have different magnitudes andwavelengths The computation of the SLAs and their errors associated are detailed in Dibarboure et al 2010[9]
Use of a Mean ProfileIn the repeat track analysis (when the satellites flies over a repetitive orbit) measurements are re-sampledalong a theoretical ground track (or mean track) associated to each mission Then a Mean Profile (MP) issubtracted from the re-sampled data to obtain SLA The MP is a time average of similarly re-sampled dataover a long period
bull The Mean Profile used for TP (cycles 1 to 364) Jason-1 (cycles 1 to 259) and Jason-2 is computedwith 10 years of TP (cycles 11 to 353) and 6 years of Jason-1 (cycles 11 to 250)
bull The Mean Profile used for TP (cycles 368 to 481) and from Jason-1 cycle 262 to 374 (where satellitesare on interleaved ground-tracks) is computed with 3 years of TP (cycles 369 to 479)
bull The Mean Profile used for ERS-1 in its 35 days repetitive orbit mission ERS-2 and Envisat (only forthe first orbit before November 2010) is computed with 8 years of ERS-2 (cycles 1 to 85) and 6 yearsof Envisat (cycles 10 to 72)
bull No Mean Profile can be used for Envisat on its new orbit (enn) Jason-1 on its geodetic orbit (j1g)because there is no repetitive track The MSS must be used instead (see below)
bull The Mean Profile used for GFO is computed with 7 years of GFO cycles 37 to 187
Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible
bull Indeed as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide precise cross-track projection andor interpolation schemes are required to avoid errors
bull The mesoscale variability error (which is lt35 cm for MP between 3 to 5 years and lt1cm for WLof 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a prioriknowledge from Sea Level maps derived from previous iterations or from other missions
Page 37
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for ERS-1 for its 168 days geodetic mission (phases E-F from April1994 to March 1995) or for Envisat since november 2010 because the satellite is not in a repetitive orbitphase The alternative is to use the MSS instead The gridded MSS is derived from along track MPs anddata from geodetic phases Thus any error on the MP is also contained in the MSS There are essentially 4types of additional errors on gridded MSS which are hard to quantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
III362 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III363 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
Page 38
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III37 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III371 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
Page 39
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
IV MYOCEAN PRODUCTS
IV1 Near Real Time Products
The purpose of the NRT DUACS component is the acquisition of altimeter data from various altimeter mis-sions in near-real time (ie within a few days at most) the validation and correction of these altimeter datasets (ie edition and selection update of corrections and homogenization orbit error reduction) in order toproduce each day along-track productsProducts are as follows
Along-track products global and regional (Mediterranean and Black Seas Arctic Ocean and Europeareas)
bull Sea Level Anomaly (NRT-SLA) for each mission with NRT-SLA ephemeris
IV11 Delay of the products
The availability of the products in near real time is three to twelve hours after the measurement for along-track products Those products are delivered every day
IV12 Temporal availibility
The following table presents the available products by mission and by data periodNear real time products
NRT Jason-2 Jason-1 and Jason-1geodetic
Envisat new Cryosat-2
Temporal Time availability ymlowast
ongoingymlowast-20120303 for
repeat track and20120507-ongoing for
geodetic track
ymlowast
2012040820120101
ongoing
NRT-SLA X X X X
lowastym the temporal coverage for NRT products is fluctuating and depends on updates of Delayed Time prod-ucts When DT products are updated (3 to 4 times per year) the oldest NRT products are replaced by thebetter quality DT products so that the 2 series are overlapping on few weeks or few months
IV2 Delayed Time Products
The Delayed Time component of SSALTODUACS system is responsible for the production of processedJason-1 Jason-2 TP Envisat GFO ERS12 and even Geosat data in order to provide a homogeneousinter-calibrated and highly accurate long time series of SLA DT products are more precise than NRT products Two reasons explain this quality difference The firstone is the better intrinsic quality of the POE orbit used in the GDR processing The second reason is that
Page 40
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
in the DT DUACS processing the products can be computed optimally with a centred computation timewindow for OER LWE On the contrary in NRT case future data are not available so the computationtime window is not centred and therefore not optimalAs for NRT products improved altimeter corrections and processing algorithms are used ocean tide modelto correct altimeter data improved methods for orbit error reduction and mapping
Along-Track products global and regional (Mediterranean and Black Seas)
bull Sea Level Anomaly (DT-SLA) for each mission
IV21 Delay of the products
Weekly products are delivered The availability of the products in delayed time is at the best two monthsafter the date of the measurement The product generation needs all the GDR data of all the missions to takeinto account the best corrections as possible The time delay can be longer in the case of a missing mission
IV22 Temporal availibility
The following table presents the available products by mission and by data periodDelayed time SSALTODUACS products
Upd Jason-2 Jason-1new6
Jason-1 GFO Envisatnew6
Envisat ERS-16
ERS-2Topexnew6
Topex
TemporalTimeavailabil-ity
200810ymlowast
200902ymlowast
200204200810
200001200809
201010ymlowast
200210201010
199210200304
200209200510
199209200204
DT-SLA X X X X X X X X X
lowast ym those dates are updated regularly (3 to 4 times per year) and are avalaible when you download thedata at httpwwwmyoceaneuweb24-cataloguephp6 Jason-1 new orbit starting 200809 Envisat new orbit starting 201010 TP new orbit starting 200209 ERS-1The geodetic phases (E-F) are included There are no ERS-1 data between December 23 1993 and April 10 1994(ERS-1 phase D - 2nd ice phase) Note that during that time products are based only on TopexPoseidon data
Page 41
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
V DESCRIPTION OF THE PRODUCT SPECIFICATION
V1 General information
Product Specification SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001
Geographical coverage global
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 20-50km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001 Product Specification
Page 42
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
Product Specification SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002
Geographical coverage 55˚W-35˚E 30˚N-46˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002 Product Specification
Page 43
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
Product Specification SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003
Geographical coverage 27˚E-42˚E 40˚N-47˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003 Product Specification
Page 44
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
Product Specification SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004
Geographical coverage 25˚W-42˚E 21˚N-66˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004 Product Specification
Page 45
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
Product Specification SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005
Geographical coverage 0˚W-360˚E 50˚N-82˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005 Product Specification
Page 46
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
VI NOMENCLATURE OF FILES
VI1 Nomenclature of files downloaded through the MyOcean Web PortalDirectgetfile Service
VI11 Nomenclature of the product line
The description of the syntax for the SL TAC SLA products line is given by
SEALEVEL_ltREGIONgt_SLA_L3_ltDELAYgt_OBSERVATIONS_008_ltZONEgt_ltLETTERgtwhere
REGION GLO global geographic coverage product
BS Black Sea products
MED Mediterranean products
ARC Arctic products (for NRT products)
EUROPE Europe products (for NRT products)
DELAY NRT near real time products
RAN delayed time or reanalysis products
ZONE 001 number on 3 digits
002
003
004
LETTER a letter on 1 digit
b
Page 47
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VI12 Nomenclature of the datasets
The nomenclature used is
dataset-duacs-ltdelaygt-ltzonegt-ltmissiongt-lttype of slagt-l3where the fileds in ltgt are described below
delay nrt near-real time productsran delayed time products
zone global global geographic coverage productmedsea Mediterranean productsblacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1 (only for ran)e2 ERS-2 (only for ran)tp TOPEXPoseidon (only for ran)tpn TOPEXPoseidon on its new orbit (only for
ran)g2 GFO (only for ran)j1 Jason-1 (only for ran)j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisat (only for ran)enn Envisat on its new orbitc2 Cryosat-2 (only for nrt)
type of sla sla filtered slasla_unfiltered non filtered sla (only for ran products)
Page 48
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
VI13 Nomenclature of the NetCdf files
The nomenclature used is
ltdelaygt_ltzonegt_ltmissiongt_sla_ltvariablegt_ltdatebegingt_ltdateendgt_ltdateprodgtnc where the fileds in ltgt are de-scribed below
delay nrt near-real time productsdt delayed time products
zone global global geographic coverage productmed Mediterranean products (for dt)mfstep Mediterranean products (for nrt)blacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1e2 ERS-2tp TOPEXPoseidontpn TOPEXPoseidon on its new orbitg2 GFOj1 Jason-1j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisatenn Envisat on its new orbitc2 Cryosat-2
variable vfec filtered and sub-sampled slavxxc non filtered and non sub-sampled sla (only
for dt)datebegin YYYYMMDD() beginning date of the datasetdateend YYYYMMDD() end date of the datasetdateprod YYYYMMDD production date of the dataset
() For dt data as the dates in the file names are rounded the user wanting data for date T has to read the filescontaining dates T+1 and T-1 in their name and check inside the files if there are some data for date T
Page 49
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
VII DATA FORMAT
This chapter presents the data storage format used for MyOcean products
VII1 NetCdf
The products are stored using the NetCDF format NetCDF (network Common Data Form) is an interface for array-oriented data access and a library that provides an implementation of the interface The netCDF library also definesa machine-independent format for representing scientific data Together the interface library and format support thecreation access and sharing of scientific data The netCDF software was developed at the Unidata Program Center inBoulder Colorado The netCDF libraries define a machine-independent format for representing scientific data Pleasesee Unidata NetCDF pages for more information and to retreive NetCDF software package onhttpwwwunidataucaredupackagesnetcdfindexhtml
NetCDF data is
bull Self-Describing A netCDF file includes information about the data it contains
bull Architecture-independent A netCDF file is represented in a form that can be accessed by computers with dif-ferent ways of storing integers characters and floating-point numbers
bull Direct-access A small subset of a large dataset may be accessed efficiently without first reading through allthe preceding data
bull Appendable Data can be appended to a netCDF dataset along one dimension without copying the dataset orredefining its structure The structure of a netCDF dataset can be changed though this sometimes causes thedataset to be copied
bull Sharable One writer and multiple readers may simultaneously access the same netCDF file
Page 50
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
VII2 Structure and semantic of NetCDF along-track files
The NetCDF Sea Level TAC files are based on the attribute data tags defined by the Cooperative OceanAtmosphereResearch Data Service (COARDS) and Climate and Forecast (CF) metadata conventions The CF convention gener-alises and extends the COARDS convention but relaxes the COARDS constraints on dimension and order and specifiesmethods for reducing the size of datasetsA wide range of software are available to write or read NetCDFCF files API are made available by UNIDATA(httpwwwunidataucaredusoftwarenetcdf)
bull CC++Fortran
bull Java
bull MATLAB Objective-C Perl Python R Ruby TclTk
In addition to these conventions the files are using a common structure and semantic
bull 1 dimension is defined
ndash time it is used to check NetCDF variables depending on time
bull 8 variables are defined
ndash short SLA contains the Sea Level Anomaly values for each time given
ndash int longitude contains the longitude for each measurement
ndash short track contains the track number for each measurement
ndash double time contains the time in days since 1950-01-01 000000 UTC for each measurement
ndash short mean_profile_point_index index of the corrsponding point in the track of the mean profile
ndash byte flag flag=0 the processed data comes from OGDR if flag=1 the processed data comes from theIGDR
ndash int latitude contains the latitude for each measurement
ndash short cycle contains the cycle number for each measurement
bull global attributes
ndash the global attributes gives information about the creation of the file
Example of a NetCDF sla file
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
netcdf nrt_global_j1_sla_vfec_20101230_20101230_20101230 dimensions
time = 10385 variables
short SLA(time) SLAcoordinates = longitude latitude SLAlong_name = Sea Level Anomaly SLA_FillValue = 32767s SLAadd_offset = 0 SLAscale_factor = 0001 SLAunits = m SLAstandard_name = sea_surface_height_above_sea_level
int longitude(time) longitudelong_name = Longitude of measurement longitude_FillValue = 2147483647 longitudeadd_offset = 0 longitudestandard_name = longitude longitudescale_factor = 1e-06 longitudeunits = degrees_east
short track(time) tracklong_name = Track in cycle the measurement belongs to track_FillValue = 32767s trackunits = 1 trackcoordinates = longitude latitude
double time(time) timelong_name = Time of measurement time_FillValue = 184467440737096e+19 timeaxis = T timestandard_name = time timeunits = days since 1950-01-01 000000 UTC
int latitude(time) latitudelong_name = Latitude of measurement latitude_FillValue = 2147483647 latitudeadd_offset = 0 latitudestandard_name = latitude latitudescale_factor = 1e-06 latitudeunits = degrees_north
short flag(time) flagcoordinates = longitude latitude flag_FillValue = 3267s flaglong_name = data origin flagflag_values = 1s 0s flagflag_meanings = igdr_like non_igdr_like flagcomment = The origin of the data is determined by the types of geophysical datarecords (GDR) used in computation of the SLA 1 for the Interim GDR (IGDR) and0 for Operational GDR (OGDR)
short cycle(time) cyclelong_name = Cycle the measurement belongs to cycle_FillValue = 32767s cycleunits = 1 cyclecoordinates = longitude latitude
global attributeshistory = 22-Feb-2011 155243 CET File created by the SSLATODUACS system version 1001 comment = Produce from ENVISAT Extension Phase satellite altimetry data institution = CLSCNES
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references = httpwwwavisooceanobscomfileadmindocumentsdatatoolshdbk_duacspdf source = satellite altimetry title = along track Sea Level Anomaly Conventions = CF-14
dataSLA =
7 7 11 10 -2 -22 -39 -41 -30 -13 -3 -5 -16 -26 -32 -35-35 -35 -37 -35 -31 -29 -31 -35 -32 -21 -10 -10 -19 -20 -1-69 -57 -49 -45 -39 -30 -28 -31 -27 -13 -2 -5 -15 -3 1112 3 -7 -10 -14 -15 -22 -31 -37 -32 -17 -10
longitude =74743328 74868400 74993968 75120040 75246616 7537372875501368 75629568 75758320 75887656 76017568 76148080 7627920876388952 76477056 76565456 76654144 76743128 76832400 76921984329429568 329535424 329641792 329748672 329856096 329964032330072512 330181536 330291072 330401184
track =92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 9292 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92113 113 113 113 113 113 113 113 113 113 113 113 113 113113 113 113 113 113 113 113 113 113
time =222780000565705 222780001314719 222780002063733222780002812747 222780003561761 222780004310775 222780005059788222780005808802 222780006557816 22278000730683 222780008055844222780008804858 222780009553872 22278001017805 222780010677393222788257112198 222788257486705 222788257861212 222788258235719222788258610226 222788258984733 222788259359239 222788259733746222788260108253 22278826048276
mean_profile_point_index =1872 1878 1884 1890 1896 1902 1908 19141920 1926 1932 1938 1944 1949 1953 1957 1961 1965 1969 19732306 2309 2312 2315 2318 2321 2327 2330 2333 2336 2339 23422345 2348 2351 2354 2357 2360 2363 2366
flag =0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
latitude =-16225506 -16539731 -16853833 -17167810 -17481660 -17795380-18108966 -18422418 -18735729 -19048899 -19361924 -19674801-19987527 -20248015 -20456329 -20664569 -20872739 -2108083739481297 39628277 39775133 39921866 40068472 40214953 4036130840507533 40653629 40799592 40945423 41091120 41236684 41382111
cycle =331 331 331 331 331 331 331 331 331 331 331 331 331
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331 331 331 331 331 331 331 331 331 331 331 331 331 331331 331 331 331 331 331 331 331 331 331 331 331
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VIII HOW TO DOWNLOAD A PRODUCT
VIII1 Download a product through the MyOcean Web Portal DirectgetfileService
You first need to register Please find below the registration stepshttpwwwmyoceaneuweb34-products-and-services-faqphp1Once registered the MyOcean FAQ httpwwwmyoceaneuweb34-products-and-services-faqwill guide you on How to download a product through the MyOcean Web Portal Directgetfile Service
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IX NEWS AND UPDATES
IX1 [Duacs] Operational news
To be kept informed on events occurring on the satellites and on the eventual interruption of the services of the DUACSprocessing system see the [Duacs] operational news on the Aviso websitehttpwwwavisooceanobscomendataoperational-newsindexhtml
IX2 Updates
To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtmlSince 2010 a complete reprocessing of all altimetry data (cumulated total of about 55 years of data) is available Themain changes introduced in the Duacs DT v300 reprocessed data set in SSALTODUACS reprocessed DT data setare listed herehttpwwwavisooceanobscomfileadmindocumentsdataduacsduacs_DT_2010_reprocessing_impactpdf
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II4 Integration of the Cryosat2 Mission (February 2012)
Since February 6th 2012 Cryosat-2 mission has been integrated in the DUACS sytem This mission isdedicated to the observation of the floating sea-ice as well as the continental ice sheets but all data acquiredover ocean are valuable for the observation of oceanic circulation and mesoscale variations This majorchange is the result of the long-standing and fruitful partnership between ESA and CNES and a responseto the request from scientific and operational oceanography users [7] The integration of Cryosat-2 impactsthe delivering of Near real time Sea Level Anomalies (SLA)
II41 Generalities about the mission
A Cryosat-2 Processing Prototype (C2P) (described in Boy et al 2011 [2]) has been developed on CNESside to lay the ground for various SAR processing studies The processing chains ingest Level-0 telemetryfiles distributed by ESA and perform the following steps to generate Sea Level Anomalies (SLA) values foreach altimeter measurements
bull Level-1 Decommutation time-tagging and localization of measurements
bull Level-1b Calculation of instrumental corrections and geophysicalmeteorological corrections
bull Level-2 MLE4 waveforms Retracking and calculation of SLA
The prototype processes data almost continuously over ocean either in Low Resolution Mode (LRM) or inthe DopplerSAR mode processed as pseudo-LRM mode allowing to increase the coverage (figure 2)
Figure 2 SSH-MSS for Cryosat-2 with LRM mode only (left) or LRM+pseudo-LRM modes (right)
Although Cryosat-2 raw SSH can be only corrected with GPS-derived ionospheric correction and ECMWFwet troposphere correction validation activities showed (Labroue et al 2011 [25]) that C2P outputs have anaccuracy roughly equivalent to Envisatrsquos Level 2 products if the latter are processed with the same standards
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II42 Integration in DUACS
The Cryosat-2 data are included in the Near Real time process The chain delivers now (for global coverageMediterranean and Black Seas) along track data from Cryosat-2 (SLAs) Note that the products distributedare of Level-3 and donrsquot replace Level-2 products distributed by agenciesThe details of the processing are given in Dibarboure et al 2011 [8]Here we just give an overview the data are computed with the corrections given in section III21 Thefiltering and sub-sampling of SLAs (section III263) are detailed in [8]
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II5 Addition of Europe and Arctic products (January 2012)
Since the MyOcean V2 two new along-track products are computed in Near Real Time intended foraddressing the needs of data assmilation and validation in regional models
bull Following the TAPAS (Tailored Altimeter Product for Assimilation Systems) initiative launched bySL TAC with all the Modeling and Forecasting Centers (MFCs) the Europe regional products (PLSEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004) have been proposed (figure 3) They areavailable in Near Real Time onlyThey are studied to partly fulfil the needs of the Centers with adapted filtering and resolution Thoseparameters have been tuned in order to provide boundary conditions for the Atlantic assimilationmodels They are different from the ones used for Mediterranean and Black Seas products If you needto study the Mediterranean Sea or the Black Sea yoursquod better use the dedicated products describedabove since the processing parameters have been fitted to be adapted to the dynamics of the ocean inthose regions
Figure 3 Coverage of the Europe product for Jason-1 Jason-2 and Envisat from August 18th to September9th 2011
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bull The Arctic along-track products (PL SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005) coverlatitudes between 45 and 82 degrees (figure 4) They are available in Near Real Time only
Figure 4 Coverage of the Arctic region with Envisat from October 28th 2011 to January 3rd 2012
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III SSALTODUACS SYSTEM
III1 Introduction
This chapter presents the input data used by SSALTODUACS system and an overview of the different pro-cessing steps necessary to produce the output dataSSALTODUACS system is made of two components a Near Real Time one (NRT) and a Delayed Time(DT) oneIn NRT the systemrsquos primary objective is to provide operational applications with directly usable high qual-ity altimeter data from all missions availableIn DT it is to maintain a consistent and user-friendly altimeter database using the state-of-the-art recom-mendations from the altimetry communityFollowing figure gives an overview of DUACS system where processing sequences can be divided into 7main steps
bull acquisition
bull homogenization
bull input data quality control
bull multi-mission cross-calibration
bull product generation
bull merging
bull final quality control
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Figure 5 SSALTODUACS processing sequences
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III2 Near Real Time processing steps
III21 Input data models and corrections applied
To produce SLA in near-real time the DUACS system uses two flows based on the same instrumental mea-surements but with a different quality
bull The IGDR that are the latest high-quality altimeter data produced in near-real-time
bull The OGDR that includes real time data (OSTMJason-2 and Jason-1 OSDR) to complete IGDR Thesefast delivery products do not always benefit from precise orbit determination nor from some exter-nal model-based corrections (Dynamic Atmospheric Correction (DAC) Global Ionospheric Maps(GIM))
Integration of OGDR data and the introduction of Jason-2Jason-1 tandem increased the resilience and pre-cision of the system A better restitution of ocean variability is observed especially in high energetic areas
Altimetric product Source Availability Type of orbit
Jason-2 IGDR CNES ~24h CNES MOE GDR-Cuntil 20120730
CNES MOE GDR-Dsince 20120731
OGDR NOAAEUMETSAT ~3 to 5 h
Jason-1 IGDR CNESNASA ~48 h CNES MOE GDR-Dsince 20120507
OGDR CNESNASA ~3 to 12 h
Envisat IGDR ESACNES not deliveredsince 20120408
CNES MOE GDR-Dsince 20120121
FDGDR ESA not deliveredsince 20120408
Cryosat-2 IGDR-like ESACNES ~48 h CNES MOE GDR-D
not delivered
Table 2 SSALTODUACS Near-Real Time Input data overview
See Figure 6 Overview of the near real time system data flow management
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DUACS 2011 NRT product from IGDR1
j2 j1nj1g enn c2Productstandard ref
version C until20120730 and D after
version C version 21 CPP [2]
Orbit CNES MOE GDR-Cuntil 20120730
GDR-D after
CNES MOE GDR-C forj1n and CNES MOE
GDR-D for j1g
CNES MOE GDR-Dfrom 20120121 to
20120408
CNES MOE GDR-D
Ionopheric bi-frequency altimeter range measurements GIM model for cgt64 (Iijima et al1998[24])Dry tropo Model computed from ECMWF Gaussian grids (new S1 and S2 atm tides applied)Wet tropo-sphere
AMR radiometer(enhancement in coastal
regions since20120730)
JMR radiometer MWR radiometer andcorrected from side
lobes
Model computed fromECMWF Gaussian
grids
DAC MOG2D High Resolution forced with ECMWF pressure and wind fields (S1 and S2 wereexcluded) (Carrere and Lyard 2003[3])+ inverse barometer Filtering temporal window is
un-centered (no data in the future)Ocean tide GOT4v8 (S1 and S2 are included) and TPX 072 [16] for Arctic productsPole tide [Wahr 1985 [53]]Solid earthtide
Elastic response to tidal potential [Cartwright and Tayler 1971[5]] [Cartwright andEdden 1973[6]]
Loading tide GOT4v8 (S1 and S2 are included)Sea statebias
Non parametric SSB[Labroue 2004[27]](with cycles J1 1 to 11
using GDR-B standardsuntil 20120730 andderived from Jason-2
after)
Non parametric SSB[Labroue 2004[27]](with cycles 1 to 21
using GDR-Bstandards)
Non parametric SSB[Labroue 2004[27]](with cycles 41 to 60
using GDR-Bstandards)
Same as Jason-2 SSB
Orbit error Global multi-mission crossover minimization (Le Traon and Ogor1998[32])
Long wave-lengh errors
Optimal Interpolation [Le Traon et al 1998[31]]
Intercalibration Reference from cycle20
Mean pro-file (seeIII261)
Computed with cycles11-353 TP data andwith cycles 11-250J1 data referenced[19931999]
TPNJ1N computedwith cycles 369-479TPN data refer-enced [19931999]J1G No MP can beused instead theMSS_CNES_CLS11[39] is used
No Mean Profilecan be used forEnvisat on its neworbit Instead theMSS_CNES_CLS11[39] is used
No Mean Profilecan be used forCryosat-2 Instead theMSS_CNES_CLS11[39] is used
(1) A flag included in the along-track files indicates the source of the production (OGDRFDGDR orIGDR) If flag=0 the processed data comes from OGDRsFDGDRs if flag=1 the processed data comesfrom IGDRs
Table 3 Corrections and models applied in SSALTODUACS NRT products produced from IGDRs
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DUACS 2011 NRT product from OGDR or FDGDR2
j2 j1nj1g ennProduct stan-dard ref
version C until 20120730and D after
version C version 21
Orbit Navigator Extrapolated CNES MOEGDR-D since 20120121
Ionopheric From-dual frequency altimeter range measurements From GIM model fromcycle 65 (Iijima et al1998 [24])
Dry troposphere Model computed from ECMWF Gaussian grids (new S1 and S2 atmospherictides are applied)
Wet tropo-sphere
AMR radiometer(enhancement in coastal
regions since 20120730)
JMR radiometer MWR radiometer andcorrected from side lobes
DAC Inverse Barometer forecastedOcean tide GOT4v8 (S1 and S2 are included) and TPX 072 [16] for Arctic productsPole tide [Wahr 1985 [53]]Solid earth tide Elastic response to tidal potential [Cartwright and Tayler 1971[5]]
[Cartwright and Edden 1973[6]]Loading tide GOT4v8 (S1 and S2 are included)Sea state bias Non parametric SSB
[Labroue 2004[27]] (withcycles J1 1 to 11 usingGDR-B standards until20120730 and derivedfrom Jason-2 after)
Non parametric SSB[Labroue 2004[27]](with cycles 1 to 21 usingGDR-B standards)
Non parametric SSB[Labroue 2004[27]](with cycles 41 to 60using GDR-B standards)
Orbit error Specific filtering of long-wavelength signal3
Long wave-lengh errors
Optimal Interpolation [Le Traon et al 1998[31]]
Intercalibration Reference from cycle 20Mean profile(see III261)
Computed with cycles 11-353 TP data and with cy-cles 11-250 J1 data refer-enced [19931999]
TPNJ1N computedwith cycles 369-479TPN data referenced[19931999] J1G NoMP can be used insteadthe MSS_CNES_CLS11[39] is used
No Mean Profile can beused for Envisat on itsnew orbit Instead theMSS_CNES_CLS11 [39]is used
(2) A flag included in the along-track files indicates the source of the production (OGDRFDGDR orIGDR) If flag=0 the processed data comes from OGDRsFDGDRs if flag=1 the processed data comesfrom IGDRs(3) Specific data processing was applied on long wave-length signal (sectIII23 of the user manual)
Table 4 Corrections and models applied in SSALTODUACS NRT products produced from OG-DRsFDGDRs
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III22 Acquisition
The acquisition process is twofold
bull straightforward retrieval and reformatting of altimeter data and dynamic auxiliary data (pressure andwet troposphere correction grids from ECMWF are provided by Meteo France TEC grids from JPLNRT MOG2D corrections) from external repositories
bull synchronisation process
To be homogenized properly altimeter data sets require various auxiliary data The acquisition softwaredetects downloads and processes incoming data as soon as they are available on remote sites (externaldatabase FTP site) Data are split into passes if necessary If data flows are missing or late the synchroni-sation engine put unusable data in waiting queues and automatically unfreezes them upon reception of themissing auxiliary data This processing step delivers raw data that is to say data that have been dividedinto cycles and passes and ordered chronologicallyFrom SSALTODUACS V80 the acquisition step uses two different data flows in near-real time the OGDRflow (within a few hours) and the IGDR flow (within a few days)For each OGDR input the system checks that no equivalent IGDR entry is available in the data base beforeacquisition for each IGDR input the system checks and delete the equivalent OGDR entry in the data baseThese operations aim to avoid duplicates in SSALTODUACS system
Figure 6 Overview of the near real time system data flow management
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III23 Homogenization
The Homogenization process consists in applying the most recent corrections models and references rec-ommended for altimeter products Each mission is processed separately as its needs depend on the baseinput data The list of corrections and models currently applied is provided in tables 3 and 4 for NRT dataThe system includes SLA filtering to process OGDR data DUACS extract from these data sets the shortscales (space and time) which are useful to better describe the ocean variability in real time and merge thisinformation with a fair description of large scale signals provided by the multi-satellite observation in nearreal time (read IGDR-based DUACS data) Finally an hybrid SLA is computed
Figure 7 Merging pertinent information from IGDR and OGDR processing
III24 Input data quality control
The Input Data Quality Control is a critical process applied to guarantee that DUACS uses only the mostaccurate altimeter data Thanks to the high quality of current missions this process rejects a small percent-age of altimeter measurements but these erroneous data could be the cause of a significant quality lossThe quality control relies on standard raw data editing with quality flags or parameter thresholds but alsoon complex data editing algorithms based on the detection of erroneous artefacts mono and multi-missioncrossover validation and macroscopic statistics to edit out large data flows that do not meet the systemrsquosrequirements
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III25 Multi-mission cross-calibration
The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistentand accurate information It removes any residual orbit error (OE Le Traon and Ogor 1998[32]) or longwavelength error (LWE Le Traon et al 1998[31]) as well as large scale biases and discrepancies betweenvarious data flows
This process is based on two very different algorithms a global multi-mission crossover minimization fororbit error reduction (OER) and Optimal Interpolation (OI) for LWE
Multi-satellite crossover determination is performed on a daily basis All altimeter fields (measurementcorrections and other fields such as bathymetry MSS) are interpolated at crossover locations and datesCrossovers are then appended to the existing crossover database as more altimeter data become availableThis crossover data set is the input of the Orbit Error Reduction (OER) method Using the precision of thereference mission orbit a very accurate orbit error can be estimated This processing step does not concernOGDR dataLWE is mostly due to residual tidal or inverse barometer errors and high frequency ocean signals The OIused for LWE reduction uses precise parameters derived from
bull accurate statistical description of sea level variability
bull localized correlation scales
bull mission-specific noise and precise assumptions on the long wavelength errors to be removed (from arecent analysis of one year of data from each mission)
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III26 Product generation
The product generation process is composed of four steps computation of raw SLA cross-validationfilteringampsub-sampling and generation of by-products
III261 Computation of raw SLA
Since the geoid is not well known yet the SSH cannot be used directly the SSH anomalies are used insteadThey are computed from the difference of the instantaneous SSH - a temporal reference This temporalreference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeattrack analysis cannot be used The errors affecting the SLAs MPs and MSS have different magnitudes andwavelengths The computation of the SLAs and their errors associated are detailed in Dibarboure et al 2010[9]
Use of a Mean ProfileIn the repeat track analysis (when the satellites flies over a repetitive orbit) measurements are re-sampledalong a theoretical ground track (or mean track) associated to each mission Then a Mean Profile (MP) issubtracted from the re-sampled data to obtain SLA The MP is a time average of similarly re-sampled dataover a long period
bull The Mean Profile used for Jason-2 is computed with 10 years of TP (cycles 11 to 353) and 6 years ofJason-1 (cycles 11 to 250)
bull The Mean Profile used from Jason-1 cycle 262 to 374 (where satellites are on interleaved ground-tracks) is computed with 3 years of TP (cycles 369 to 479)
bull No Mean Profile can be used for Envisat on its new orbit (enn) Jason-1 on its geodetic orbit (j1g) norfor Cryosat-2 mission (c2) because there is no repetitive track The MSS must be used instead (seebelow)
Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible
bull Indeed as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide precise cross-track projection andor interpolation schemes are required to avoid errors
bull The mesoscale variability error (which is lt35 cm for MP between 3 to 5 years and lt1cm for WLof 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a prioriknowledge from Sea Level maps derived from previous iterations or from other missions
bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
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bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for Envisat since november 2010 and for Cryosat-2 mission (c2)because the satellite is not in a repetitive orbit phase The alternative is to use the MSS instead The griddedMSS is derived from along track MPs and data from geodetic phases Thus any error on the MP is alsocontained in the MSS There are essentially 4 types of additional errors on gridded MSS which are hard toquantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
Note that for the Arctic regional products the DTU10 MSS [1] is taken into account instead of the CLS01MSS Indeed the accuracy of DTU10 compared to CLS01 is further demonstrated by the significant sealevel anomaly variance reduction found over the whole Arctic Ocean as shown in Prandi et al [42]
III262 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III263 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
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III27 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III271 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
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III272 Performance indicators
To appreciate the quality situation of the DUACS system new performance indicators are computed dailyThey aim at evaluate the status of the main processing steps of the system the input data availability theinput data coverage the input data quality and the output product quality These indicators are computed foreach and every currently working satellite and combined to obtain the overall status
Figure 8 Example with the key performance indicator on 20090627
See the description the latest and previous indicators on Aviso websitehttpwwwavisooceanobscomindexphpid=1516
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III3 Delayed Time processing steps
III31 Input data models and corrections applied
Delayed Time MyOcean products are generated
bull from Aviso GDR products for TP Jason-1 Jason-2 and Envisat (GDR-A cycles 1 to 22 GDR-Bcycles 23 to 85 GDR-C from cycle 86)
bull from NOAA GDR for GFO and from CERSAT (IFREMER) OPR for ERS-1 and ERS-2 (phases C(1st 35-day repeat orbit period) phase E and F (geodetic phases) phase G for ERS-1 (last 35-dayrepeat orbit period tandem phase with ERS-2 phase A for ERS-2 (1st 35-day repeat orbit periodtandem phase with ERS-1))
All GDR products are computed with a Precise Orbit Ephemeris (POE) and are delivered within 2 to 3months depending on the mission For several missions an updated orbit is used
bull For ERS-1amp-2 the orbit used is DGME-04 provided by Delft Institute (httpwwwdeostudelftnl)until June 2003
bull For TopexPoseidon the orbit used is GSFC (std0809) for the whole mission
bull For Envisat CNES POE of GDR-C standard is used for the whole mission
bull For the whole GFO mission the orbit used is GSFC (std0809) and when not available NASA POE isused
Altimetric product Source Availability Type of orbit
TopexPoseidon GDR NASACNES - GSFC POE
Jason-1 GDR (GDR-C) CNESNASA ~40 days CNES POE
Jason-2 GDR (GDR-C) CNESNASA ~60 days CNES POE
GFO GDR NOAA - GSFCNASA POE
ERS-1amp2 IFREMERESA - DGME-04
Envisat (GDR-A GDR-B andGDR-C from cycle 86)
ESA ~2 months CNES POE
Table 5 SSALTODUACS Delayed Time Input data overview
Page 32
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
DU
AC
S20
11D
Tpr
oduc
t(gtV
30
0)j2
j1j1
ntp
tpn
e1e2
ene
nng2
Prod
uct
stan
dard
ref
GD
R-C
OPR
GD
R-A
(Cyc
les
1to
22)
GD
R-B
(cyc
les
23-8
5)
GD
R(N
OA
A)
Orb
itC
nes
POE
GSF
C(I
TR
F20
05G
RA
CE
last
stan
dard
s)
DG
ME
-04
(Sch
arro
oan
dV
isse
r19
98[4
8]C
NE
SPO
E(G
DR
-1st
anda
rds
forc
ycle
s9
to22
GD
R-C
stan
dard
sfr
omcy
cle
23)
GSF
C(I
TR
F20
05
GR
AC
Ela
stst
anda
rds
Iono
pher
icD
ual f
requ
ency
altim
eter
rang
em
easu
rem
ents
Dua
l fre
quen
cyal
timet
erra
nge
mea
sure
men
ts(T
opex
)D
OR
IS(P
OSE
IDO
N)
Ben
t mod
elB
ent m
odel
(cyc
les
1-36
)G
IMm
odem
from
cycl
e37
((Ii
jima
etal
19
98[2
4])
Dua
l-fr
eque
ncy
altim
eter
rang
em
easu
rem
ent(
cycl
e9-
64)a
ndG
IMm
odel
gtcyc
le65
(Iiji
ma
etal
19
99[2
4])c
orre
cted
from
8m
mbi
as
From
GIM
mod
el(I
ijim
aet
al1
998
[24]
)
Dry
trop
o-sp
here
Mod
elco
mpu
ted
from
EC
MW
FG
auss
ian
grid
s(n
ewS1
and
S2at
mos
pher
ictid
esar
eap
plie
d)
Mod
elco
mpu
ted
from
EC
MW
Fre
ctan
gula
rgri
ds(n
ewS1
and
S2at
mos
pher
ictid
esar
ein
clud
ed)
Wet
trop
o-sp
here
JMR
AM
Rra
diom
eter
furt
hert
han
50km
from
the
coas
tsF
rom
EC
MW
Fm
odel
ford
ista
nces
betw
een
10an
d50
km
TM
Rra
diom
eter
(Sch
aroo
etal
20
04[4
9])
MW
RC
orre
ctio
nof
the
drif
ton
the
236
GH
zbr
ight
ness
tem
pera
ture
(Sch
arro
oet
al
2004
[49]
)Neu
ral
Net
wor
kal
gori
thm
(Tra
nan
dO
blig
is
2003
[50]
MW
Rra
diom
eter
furt
hert
han
50km
from
the
coas
tsan
dco
rrec
ted
from
side
lobe
s(f
rom
cycl
e41
)E
CM
WF
mod
elfo
rdis
tanc
esbe
twee
n10
and
50km
GFO
radi
omet
er
DA
CM
OG
2DH
igh
Res
olut
ion
forc
edw
ithE
CM
WF
pres
sure
and
win
gfie
lds
(S1
and
S2w
ere
excl
uded
)+in
vers
eba
rom
eter
com
pute
dfr
omre
ctan
gula
rgri
ds
Tabl
e6
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(1
2)
Page 33
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
j2j1
j1n
tptp
ne1
e2en
enn
g2O
cean
tide
GO
T4v
7(S
1an
dS2
are
incl
uded
)Po
letid
e[W
ahr
1985
[53]
]So
lidea
rth
tide
Ela
stic
resp
onse
totid
alpo
tent
ial[
Car
twri
ghta
ndTa
yler
197
1[5]
][C
artw
righ
tand
Edd
en1
973[
6]]
Loa
ding
tide
GO
T4v
7(S
1pa
ram
eter
isin
clud
ed)
Sea
stat
ebi
asN
onpa
ram
etri
cSS
B[G
aspa
reta
l20
02[2
0]]
Non
para
met
ric
SSB
[NT
ran
and
al2
010[
51]]
BM
3[G
aspa
ran
dO
gor
1994
[17]
]
Non
para
met
ric
SSB
[Mer
tzet
al
2005
[38]
]
Non
para
met
ric
SSB
[Gas
pare
tal
2002
]w
ithG
DR
-Bst
anda
rds
forc
ycle
s9
to85
and
with
GD
R-C
stan
dard
sfr
omcy
cle
86
Non
para
met
ric
SSB
[NT
ran
etal
20
10[5
1]]
Orb
iter
ror
Glo
bal m
ulti-
mis
sion
cros
sove
rmin
imiz
atio
n(L
eTr
aon
and
Ogo
r19
98[3
2])
Lon
gw
ave-
leng
her
rors
Opt
imal
Inte
rpol
atio
n(L
eTr
aon
etal
19
98[3
1])
Inte
rcal
ibra
tion
Ref
eren
cefr
omcy
cle
11R
efer
ence
from
cycl
e1
to35
4C
orre
ctio
nof
regi
onal
bias
J2J
1de
duce
dfr
omin
terc
alib
ratio
nph
ase
(cyc
le11
J2)
Cor
rect
ion
ofgl
obal
biai
sJ1
TP
deacutedu
ced
from
inte
rcal
ibra
tion
phas
e(c
ycle
s11
J1)
Mea
npr
o-fil
e(s
eeII
I36
1)
Com
pute
dw
ithcy
cles
11-3
53T
Pda
taan
dw
ithcy
cles
11-2
50J1
data
ref
eren
ced
[199
319
99]
TP
J1 c
ompu
ted
with
cycl
es11
-353
TP
data
and
with
cycl
es11
-250
J1da
tar
efer
ence
d[1
993
1999
]T
PNJ
1Nc
ompu
ted
with
cycl
es36
9-47
9T
PNda
tar
efer
ence
d[1
993
1999
]
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
ref
eren
ced
[199
319
99]
EN
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
re
fere
nced
[199
319
99]
EN
Nu
seof
MSS
_CN
ES_
CL
S11
[39]
Com
pute
dw
ithcy
cles
37-1
87G
2da
ta
refe
renc
ed[1
993
1999
]
Peri
odof
use
from
cycl
e9
from
cycl
e9
cycl
es1
to48
1cy
cles
15to
43In
clud
ing
E-F
geod
etic
phas
es
cycl
es1
to83
from
cycl
e9
cycl
es37
to22
2
Tabl
e7
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(2
2)
Page 34
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III32 Acquisition
The acqusition process in Delayed time is much simpler than in Near Real time it consists in a synchronisa-tion process of all the auxiliary data required to homogenize propely the altimeter data sets The acquisitionstep uses the GDRs or the OPRs provided by the agencies
III33 Homogenization
The Homogenization process consists in applying the most recent corrections models and references rec-ommended for altimeter products Each mission is processed separately as its needs depend on the baseinput data The list of corrections and models currently applied is provided in tables 6 and 7 for DT data
III34 Input data quality control
The Input Data Quality Control is a critical process applied to guarantee that DUACS uses only the mostaccurate altimeter data Thanks to the high quality of current missions this process rejects a small percent-age of altimeter measurements but these erroneous data could be the cause of a significant quality lossThe quality control relies on standard raw data editing with quality flags or parameter thresholds but alsoon complex data editing algorithms based on the detection of erroneous artefacts mono and multi-missioncrossover validation and macroscopic statistics to edit out large data flows that do not meet the systemrsquosrequirements
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PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III35 Multi-mission cross-calibration
The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistentand accurate information It removes any residual orbit error (OE Le Traon and Ogor 1998[32]) or longwavelength error (LWE Le Traon et al 1998[31]) as well as large scale biases and discrepancies betweenvarious data flows
This process is based on two very different algorithms a global multi-mission crossover minimization fororbit error reduction (OER) and Optimal Interpolation (OI) for LWE
Multi-satellite crossover determination is performed on a daily basis All altimeter fields (measurementcorrections and other fields such as bathymetry MSS) are interpolated at crossover locations and datesCrossovers are then appended to the existing crossover database as more altimeter data become availableThis crossover data set is the input of the Orbit Error Reduction (OER) method Using the precision of thereference mission orbit a very accurate orbit error can be estimated LWE is mostly due to residual tidalor inverse barometer errors and high frequency ocean signals The OI used for LWE reduction uses preciseparameters derived from
bull accurate statistical description of sea level variability
bull localized correlation scales
bull mission-specific noise and precise assumptions on the long wavelength errors to be removed (from arecent analysis of one year of data from each mission)
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III36 Product generation
The product generation process is composed of four steps computation of raw SLA cross-validationfilteringampsub-sampling and generation of by-products
III361 Computation of raw SLA
Since the geoid is not well known yet the SSH cannot be used directly the SSH anomalies are used insteadThey are computed from the difference of the instantaneous SSH - a temporal reference This temporalreference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeattrack analysis cannot be used The errors affecting the SLAs MPs and MSS have different magnitudes andwavelengths The computation of the SLAs and their errors associated are detailed in Dibarboure et al 2010[9]
Use of a Mean ProfileIn the repeat track analysis (when the satellites flies over a repetitive orbit) measurements are re-sampledalong a theoretical ground track (or mean track) associated to each mission Then a Mean Profile (MP) issubtracted from the re-sampled data to obtain SLA The MP is a time average of similarly re-sampled dataover a long period
bull The Mean Profile used for TP (cycles 1 to 364) Jason-1 (cycles 1 to 259) and Jason-2 is computedwith 10 years of TP (cycles 11 to 353) and 6 years of Jason-1 (cycles 11 to 250)
bull The Mean Profile used for TP (cycles 368 to 481) and from Jason-1 cycle 262 to 374 (where satellitesare on interleaved ground-tracks) is computed with 3 years of TP (cycles 369 to 479)
bull The Mean Profile used for ERS-1 in its 35 days repetitive orbit mission ERS-2 and Envisat (only forthe first orbit before November 2010) is computed with 8 years of ERS-2 (cycles 1 to 85) and 6 yearsof Envisat (cycles 10 to 72)
bull No Mean Profile can be used for Envisat on its new orbit (enn) Jason-1 on its geodetic orbit (j1g)because there is no repetitive track The MSS must be used instead (see below)
bull The Mean Profile used for GFO is computed with 7 years of GFO cycles 37 to 187
Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible
bull Indeed as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide precise cross-track projection andor interpolation schemes are required to avoid errors
bull The mesoscale variability error (which is lt35 cm for MP between 3 to 5 years and lt1cm for WLof 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a prioriknowledge from Sea Level maps derived from previous iterations or from other missions
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PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for ERS-1 for its 168 days geodetic mission (phases E-F from April1994 to March 1995) or for Envisat since november 2010 because the satellite is not in a repetitive orbitphase The alternative is to use the MSS instead The gridded MSS is derived from along track MPs anddata from geodetic phases Thus any error on the MP is also contained in the MSS There are essentially 4types of additional errors on gridded MSS which are hard to quantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
III362 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III363 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
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PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III37 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III371 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
Page 39
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
IV MYOCEAN PRODUCTS
IV1 Near Real Time Products
The purpose of the NRT DUACS component is the acquisition of altimeter data from various altimeter mis-sions in near-real time (ie within a few days at most) the validation and correction of these altimeter datasets (ie edition and selection update of corrections and homogenization orbit error reduction) in order toproduce each day along-track productsProducts are as follows
Along-track products global and regional (Mediterranean and Black Seas Arctic Ocean and Europeareas)
bull Sea Level Anomaly (NRT-SLA) for each mission with NRT-SLA ephemeris
IV11 Delay of the products
The availability of the products in near real time is three to twelve hours after the measurement for along-track products Those products are delivered every day
IV12 Temporal availibility
The following table presents the available products by mission and by data periodNear real time products
NRT Jason-2 Jason-1 and Jason-1geodetic
Envisat new Cryosat-2
Temporal Time availability ymlowast
ongoingymlowast-20120303 for
repeat track and20120507-ongoing for
geodetic track
ymlowast
2012040820120101
ongoing
NRT-SLA X X X X
lowastym the temporal coverage for NRT products is fluctuating and depends on updates of Delayed Time prod-ucts When DT products are updated (3 to 4 times per year) the oldest NRT products are replaced by thebetter quality DT products so that the 2 series are overlapping on few weeks or few months
IV2 Delayed Time Products
The Delayed Time component of SSALTODUACS system is responsible for the production of processedJason-1 Jason-2 TP Envisat GFO ERS12 and even Geosat data in order to provide a homogeneousinter-calibrated and highly accurate long time series of SLA DT products are more precise than NRT products Two reasons explain this quality difference The firstone is the better intrinsic quality of the POE orbit used in the GDR processing The second reason is that
Page 40
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
in the DT DUACS processing the products can be computed optimally with a centred computation timewindow for OER LWE On the contrary in NRT case future data are not available so the computationtime window is not centred and therefore not optimalAs for NRT products improved altimeter corrections and processing algorithms are used ocean tide modelto correct altimeter data improved methods for orbit error reduction and mapping
Along-Track products global and regional (Mediterranean and Black Seas)
bull Sea Level Anomaly (DT-SLA) for each mission
IV21 Delay of the products
Weekly products are delivered The availability of the products in delayed time is at the best two monthsafter the date of the measurement The product generation needs all the GDR data of all the missions to takeinto account the best corrections as possible The time delay can be longer in the case of a missing mission
IV22 Temporal availibility
The following table presents the available products by mission and by data periodDelayed time SSALTODUACS products
Upd Jason-2 Jason-1new6
Jason-1 GFO Envisatnew6
Envisat ERS-16
ERS-2Topexnew6
Topex
TemporalTimeavailabil-ity
200810ymlowast
200902ymlowast
200204200810
200001200809
201010ymlowast
200210201010
199210200304
200209200510
199209200204
DT-SLA X X X X X X X X X
lowast ym those dates are updated regularly (3 to 4 times per year) and are avalaible when you download thedata at httpwwwmyoceaneuweb24-cataloguephp6 Jason-1 new orbit starting 200809 Envisat new orbit starting 201010 TP new orbit starting 200209 ERS-1The geodetic phases (E-F) are included There are no ERS-1 data between December 23 1993 and April 10 1994(ERS-1 phase D - 2nd ice phase) Note that during that time products are based only on TopexPoseidon data
Page 41
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
V DESCRIPTION OF THE PRODUCT SPECIFICATION
V1 General information
Product Specification SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001
Geographical coverage global
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 20-50km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001 Product Specification
Page 42
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
Product Specification SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002
Geographical coverage 55˚W-35˚E 30˚N-46˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002 Product Specification
Page 43
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
Product Specification SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003
Geographical coverage 27˚E-42˚E 40˚N-47˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003 Product Specification
Page 44
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
Product Specification SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004
Geographical coverage 25˚W-42˚E 21˚N-66˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004 Product Specification
Page 45
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
Product Specification SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005
Geographical coverage 0˚W-360˚E 50˚N-82˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005 Product Specification
Page 46
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
VI NOMENCLATURE OF FILES
VI1 Nomenclature of files downloaded through the MyOcean Web PortalDirectgetfile Service
VI11 Nomenclature of the product line
The description of the syntax for the SL TAC SLA products line is given by
SEALEVEL_ltREGIONgt_SLA_L3_ltDELAYgt_OBSERVATIONS_008_ltZONEgt_ltLETTERgtwhere
REGION GLO global geographic coverage product
BS Black Sea products
MED Mediterranean products
ARC Arctic products (for NRT products)
EUROPE Europe products (for NRT products)
DELAY NRT near real time products
RAN delayed time or reanalysis products
ZONE 001 number on 3 digits
002
003
004
LETTER a letter on 1 digit
b
Page 47
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
VI12 Nomenclature of the datasets
The nomenclature used is
dataset-duacs-ltdelaygt-ltzonegt-ltmissiongt-lttype of slagt-l3where the fileds in ltgt are described below
delay nrt near-real time productsran delayed time products
zone global global geographic coverage productmedsea Mediterranean productsblacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1 (only for ran)e2 ERS-2 (only for ran)tp TOPEXPoseidon (only for ran)tpn TOPEXPoseidon on its new orbit (only for
ran)g2 GFO (only for ran)j1 Jason-1 (only for ran)j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisat (only for ran)enn Envisat on its new orbitc2 Cryosat-2 (only for nrt)
type of sla sla filtered slasla_unfiltered non filtered sla (only for ran products)
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VI13 Nomenclature of the NetCdf files
The nomenclature used is
ltdelaygt_ltzonegt_ltmissiongt_sla_ltvariablegt_ltdatebegingt_ltdateendgt_ltdateprodgtnc where the fileds in ltgt are de-scribed below
delay nrt near-real time productsdt delayed time products
zone global global geographic coverage productmed Mediterranean products (for dt)mfstep Mediterranean products (for nrt)blacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1e2 ERS-2tp TOPEXPoseidontpn TOPEXPoseidon on its new orbitg2 GFOj1 Jason-1j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisatenn Envisat on its new orbitc2 Cryosat-2
variable vfec filtered and sub-sampled slavxxc non filtered and non sub-sampled sla (only
for dt)datebegin YYYYMMDD() beginning date of the datasetdateend YYYYMMDD() end date of the datasetdateprod YYYYMMDD production date of the dataset
() For dt data as the dates in the file names are rounded the user wanting data for date T has to read the filescontaining dates T+1 and T-1 in their name and check inside the files if there are some data for date T
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VII DATA FORMAT
This chapter presents the data storage format used for MyOcean products
VII1 NetCdf
The products are stored using the NetCDF format NetCDF (network Common Data Form) is an interface for array-oriented data access and a library that provides an implementation of the interface The netCDF library also definesa machine-independent format for representing scientific data Together the interface library and format support thecreation access and sharing of scientific data The netCDF software was developed at the Unidata Program Center inBoulder Colorado The netCDF libraries define a machine-independent format for representing scientific data Pleasesee Unidata NetCDF pages for more information and to retreive NetCDF software package onhttpwwwunidataucaredupackagesnetcdfindexhtml
NetCDF data is
bull Self-Describing A netCDF file includes information about the data it contains
bull Architecture-independent A netCDF file is represented in a form that can be accessed by computers with dif-ferent ways of storing integers characters and floating-point numbers
bull Direct-access A small subset of a large dataset may be accessed efficiently without first reading through allthe preceding data
bull Appendable Data can be appended to a netCDF dataset along one dimension without copying the dataset orredefining its structure The structure of a netCDF dataset can be changed though this sometimes causes thedataset to be copied
bull Sharable One writer and multiple readers may simultaneously access the same netCDF file
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VII2 Structure and semantic of NetCDF along-track files
The NetCDF Sea Level TAC files are based on the attribute data tags defined by the Cooperative OceanAtmosphereResearch Data Service (COARDS) and Climate and Forecast (CF) metadata conventions The CF convention gener-alises and extends the COARDS convention but relaxes the COARDS constraints on dimension and order and specifiesmethods for reducing the size of datasetsA wide range of software are available to write or read NetCDFCF files API are made available by UNIDATA(httpwwwunidataucaredusoftwarenetcdf)
bull CC++Fortran
bull Java
bull MATLAB Objective-C Perl Python R Ruby TclTk
In addition to these conventions the files are using a common structure and semantic
bull 1 dimension is defined
ndash time it is used to check NetCDF variables depending on time
bull 8 variables are defined
ndash short SLA contains the Sea Level Anomaly values for each time given
ndash int longitude contains the longitude for each measurement
ndash short track contains the track number for each measurement
ndash double time contains the time in days since 1950-01-01 000000 UTC for each measurement
ndash short mean_profile_point_index index of the corrsponding point in the track of the mean profile
ndash byte flag flag=0 the processed data comes from OGDR if flag=1 the processed data comes from theIGDR
ndash int latitude contains the latitude for each measurement
ndash short cycle contains the cycle number for each measurement
bull global attributes
ndash the global attributes gives information about the creation of the file
Example of a NetCDF sla file
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netcdf nrt_global_j1_sla_vfec_20101230_20101230_20101230 dimensions
time = 10385 variables
short SLA(time) SLAcoordinates = longitude latitude SLAlong_name = Sea Level Anomaly SLA_FillValue = 32767s SLAadd_offset = 0 SLAscale_factor = 0001 SLAunits = m SLAstandard_name = sea_surface_height_above_sea_level
int longitude(time) longitudelong_name = Longitude of measurement longitude_FillValue = 2147483647 longitudeadd_offset = 0 longitudestandard_name = longitude longitudescale_factor = 1e-06 longitudeunits = degrees_east
short track(time) tracklong_name = Track in cycle the measurement belongs to track_FillValue = 32767s trackunits = 1 trackcoordinates = longitude latitude
double time(time) timelong_name = Time of measurement time_FillValue = 184467440737096e+19 timeaxis = T timestandard_name = time timeunits = days since 1950-01-01 000000 UTC
int latitude(time) latitudelong_name = Latitude of measurement latitude_FillValue = 2147483647 latitudeadd_offset = 0 latitudestandard_name = latitude latitudescale_factor = 1e-06 latitudeunits = degrees_north
short flag(time) flagcoordinates = longitude latitude flag_FillValue = 3267s flaglong_name = data origin flagflag_values = 1s 0s flagflag_meanings = igdr_like non_igdr_like flagcomment = The origin of the data is determined by the types of geophysical datarecords (GDR) used in computation of the SLA 1 for the Interim GDR (IGDR) and0 for Operational GDR (OGDR)
short cycle(time) cyclelong_name = Cycle the measurement belongs to cycle_FillValue = 32767s cycleunits = 1 cyclecoordinates = longitude latitude
global attributeshistory = 22-Feb-2011 155243 CET File created by the SSLATODUACS system version 1001 comment = Produce from ENVISAT Extension Phase satellite altimetry data institution = CLSCNES
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references = httpwwwavisooceanobscomfileadmindocumentsdatatoolshdbk_duacspdf source = satellite altimetry title = along track Sea Level Anomaly Conventions = CF-14
dataSLA =
7 7 11 10 -2 -22 -39 -41 -30 -13 -3 -5 -16 -26 -32 -35-35 -35 -37 -35 -31 -29 -31 -35 -32 -21 -10 -10 -19 -20 -1-69 -57 -49 -45 -39 -30 -28 -31 -27 -13 -2 -5 -15 -3 1112 3 -7 -10 -14 -15 -22 -31 -37 -32 -17 -10
longitude =74743328 74868400 74993968 75120040 75246616 7537372875501368 75629568 75758320 75887656 76017568 76148080 7627920876388952 76477056 76565456 76654144 76743128 76832400 76921984329429568 329535424 329641792 329748672 329856096 329964032330072512 330181536 330291072 330401184
track =92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 9292 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92113 113 113 113 113 113 113 113 113 113 113 113 113 113113 113 113 113 113 113 113 113 113
time =222780000565705 222780001314719 222780002063733222780002812747 222780003561761 222780004310775 222780005059788222780005808802 222780006557816 22278000730683 222780008055844222780008804858 222780009553872 22278001017805 222780010677393222788257112198 222788257486705 222788257861212 222788258235719222788258610226 222788258984733 222788259359239 222788259733746222788260108253 22278826048276
mean_profile_point_index =1872 1878 1884 1890 1896 1902 1908 19141920 1926 1932 1938 1944 1949 1953 1957 1961 1965 1969 19732306 2309 2312 2315 2318 2321 2327 2330 2333 2336 2339 23422345 2348 2351 2354 2357 2360 2363 2366
flag =0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
latitude =-16225506 -16539731 -16853833 -17167810 -17481660 -17795380-18108966 -18422418 -18735729 -19048899 -19361924 -19674801-19987527 -20248015 -20456329 -20664569 -20872739 -2108083739481297 39628277 39775133 39921866 40068472 40214953 4036130840507533 40653629 40799592 40945423 41091120 41236684 41382111
cycle =331 331 331 331 331 331 331 331 331 331 331 331 331
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331 331 331 331 331 331 331 331 331 331 331 331 331 331331 331 331 331 331 331 331 331 331 331 331 331
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VIII HOW TO DOWNLOAD A PRODUCT
VIII1 Download a product through the MyOcean Web Portal DirectgetfileService
You first need to register Please find below the registration stepshttpwwwmyoceaneuweb34-products-and-services-faqphp1Once registered the MyOcean FAQ httpwwwmyoceaneuweb34-products-and-services-faqwill guide you on How to download a product through the MyOcean Web Portal Directgetfile Service
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IX NEWS AND UPDATES
IX1 [Duacs] Operational news
To be kept informed on events occurring on the satellites and on the eventual interruption of the services of the DUACSprocessing system see the [Duacs] operational news on the Aviso websitehttpwwwavisooceanobscomendataoperational-newsindexhtml
IX2 Updates
To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtmlSince 2010 a complete reprocessing of all altimetry data (cumulated total of about 55 years of data) is available Themain changes introduced in the Duacs DT v300 reprocessed data set in SSALTODUACS reprocessed DT data setare listed herehttpwwwavisooceanobscomfileadmindocumentsdataduacsduacs_DT_2010_reprocessing_impactpdf
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II42 Integration in DUACS
The Cryosat-2 data are included in the Near Real time process The chain delivers now (for global coverageMediterranean and Black Seas) along track data from Cryosat-2 (SLAs) Note that the products distributedare of Level-3 and donrsquot replace Level-2 products distributed by agenciesThe details of the processing are given in Dibarboure et al 2011 [8]Here we just give an overview the data are computed with the corrections given in section III21 Thefiltering and sub-sampling of SLAs (section III263) are detailed in [8]
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II5 Addition of Europe and Arctic products (January 2012)
Since the MyOcean V2 two new along-track products are computed in Near Real Time intended foraddressing the needs of data assmilation and validation in regional models
bull Following the TAPAS (Tailored Altimeter Product for Assimilation Systems) initiative launched bySL TAC with all the Modeling and Forecasting Centers (MFCs) the Europe regional products (PLSEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004) have been proposed (figure 3) They areavailable in Near Real Time onlyThey are studied to partly fulfil the needs of the Centers with adapted filtering and resolution Thoseparameters have been tuned in order to provide boundary conditions for the Atlantic assimilationmodels They are different from the ones used for Mediterranean and Black Seas products If you needto study the Mediterranean Sea or the Black Sea yoursquod better use the dedicated products describedabove since the processing parameters have been fitted to be adapted to the dynamics of the ocean inthose regions
Figure 3 Coverage of the Europe product for Jason-1 Jason-2 and Envisat from August 18th to September9th 2011
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bull The Arctic along-track products (PL SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005) coverlatitudes between 45 and 82 degrees (figure 4) They are available in Near Real Time only
Figure 4 Coverage of the Arctic region with Envisat from October 28th 2011 to January 3rd 2012
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III SSALTODUACS SYSTEM
III1 Introduction
This chapter presents the input data used by SSALTODUACS system and an overview of the different pro-cessing steps necessary to produce the output dataSSALTODUACS system is made of two components a Near Real Time one (NRT) and a Delayed Time(DT) oneIn NRT the systemrsquos primary objective is to provide operational applications with directly usable high qual-ity altimeter data from all missions availableIn DT it is to maintain a consistent and user-friendly altimeter database using the state-of-the-art recom-mendations from the altimetry communityFollowing figure gives an overview of DUACS system where processing sequences can be divided into 7main steps
bull acquisition
bull homogenization
bull input data quality control
bull multi-mission cross-calibration
bull product generation
bull merging
bull final quality control
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Figure 5 SSALTODUACS processing sequences
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III2 Near Real Time processing steps
III21 Input data models and corrections applied
To produce SLA in near-real time the DUACS system uses two flows based on the same instrumental mea-surements but with a different quality
bull The IGDR that are the latest high-quality altimeter data produced in near-real-time
bull The OGDR that includes real time data (OSTMJason-2 and Jason-1 OSDR) to complete IGDR Thesefast delivery products do not always benefit from precise orbit determination nor from some exter-nal model-based corrections (Dynamic Atmospheric Correction (DAC) Global Ionospheric Maps(GIM))
Integration of OGDR data and the introduction of Jason-2Jason-1 tandem increased the resilience and pre-cision of the system A better restitution of ocean variability is observed especially in high energetic areas
Altimetric product Source Availability Type of orbit
Jason-2 IGDR CNES ~24h CNES MOE GDR-Cuntil 20120730
CNES MOE GDR-Dsince 20120731
OGDR NOAAEUMETSAT ~3 to 5 h
Jason-1 IGDR CNESNASA ~48 h CNES MOE GDR-Dsince 20120507
OGDR CNESNASA ~3 to 12 h
Envisat IGDR ESACNES not deliveredsince 20120408
CNES MOE GDR-Dsince 20120121
FDGDR ESA not deliveredsince 20120408
Cryosat-2 IGDR-like ESACNES ~48 h CNES MOE GDR-D
not delivered
Table 2 SSALTODUACS Near-Real Time Input data overview
See Figure 6 Overview of the near real time system data flow management
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DUACS 2011 NRT product from IGDR1
j2 j1nj1g enn c2Productstandard ref
version C until20120730 and D after
version C version 21 CPP [2]
Orbit CNES MOE GDR-Cuntil 20120730
GDR-D after
CNES MOE GDR-C forj1n and CNES MOE
GDR-D for j1g
CNES MOE GDR-Dfrom 20120121 to
20120408
CNES MOE GDR-D
Ionopheric bi-frequency altimeter range measurements GIM model for cgt64 (Iijima et al1998[24])Dry tropo Model computed from ECMWF Gaussian grids (new S1 and S2 atm tides applied)Wet tropo-sphere
AMR radiometer(enhancement in coastal
regions since20120730)
JMR radiometer MWR radiometer andcorrected from side
lobes
Model computed fromECMWF Gaussian
grids
DAC MOG2D High Resolution forced with ECMWF pressure and wind fields (S1 and S2 wereexcluded) (Carrere and Lyard 2003[3])+ inverse barometer Filtering temporal window is
un-centered (no data in the future)Ocean tide GOT4v8 (S1 and S2 are included) and TPX 072 [16] for Arctic productsPole tide [Wahr 1985 [53]]Solid earthtide
Elastic response to tidal potential [Cartwright and Tayler 1971[5]] [Cartwright andEdden 1973[6]]
Loading tide GOT4v8 (S1 and S2 are included)Sea statebias
Non parametric SSB[Labroue 2004[27]](with cycles J1 1 to 11
using GDR-B standardsuntil 20120730 andderived from Jason-2
after)
Non parametric SSB[Labroue 2004[27]](with cycles 1 to 21
using GDR-Bstandards)
Non parametric SSB[Labroue 2004[27]](with cycles 41 to 60
using GDR-Bstandards)
Same as Jason-2 SSB
Orbit error Global multi-mission crossover minimization (Le Traon and Ogor1998[32])
Long wave-lengh errors
Optimal Interpolation [Le Traon et al 1998[31]]
Intercalibration Reference from cycle20
Mean pro-file (seeIII261)
Computed with cycles11-353 TP data andwith cycles 11-250J1 data referenced[19931999]
TPNJ1N computedwith cycles 369-479TPN data refer-enced [19931999]J1G No MP can beused instead theMSS_CNES_CLS11[39] is used
No Mean Profilecan be used forEnvisat on its neworbit Instead theMSS_CNES_CLS11[39] is used
No Mean Profilecan be used forCryosat-2 Instead theMSS_CNES_CLS11[39] is used
(1) A flag included in the along-track files indicates the source of the production (OGDRFDGDR orIGDR) If flag=0 the processed data comes from OGDRsFDGDRs if flag=1 the processed data comesfrom IGDRs
Table 3 Corrections and models applied in SSALTODUACS NRT products produced from IGDRs
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DUACS 2011 NRT product from OGDR or FDGDR2
j2 j1nj1g ennProduct stan-dard ref
version C until 20120730and D after
version C version 21
Orbit Navigator Extrapolated CNES MOEGDR-D since 20120121
Ionopheric From-dual frequency altimeter range measurements From GIM model fromcycle 65 (Iijima et al1998 [24])
Dry troposphere Model computed from ECMWF Gaussian grids (new S1 and S2 atmospherictides are applied)
Wet tropo-sphere
AMR radiometer(enhancement in coastal
regions since 20120730)
JMR radiometer MWR radiometer andcorrected from side lobes
DAC Inverse Barometer forecastedOcean tide GOT4v8 (S1 and S2 are included) and TPX 072 [16] for Arctic productsPole tide [Wahr 1985 [53]]Solid earth tide Elastic response to tidal potential [Cartwright and Tayler 1971[5]]
[Cartwright and Edden 1973[6]]Loading tide GOT4v8 (S1 and S2 are included)Sea state bias Non parametric SSB
[Labroue 2004[27]] (withcycles J1 1 to 11 usingGDR-B standards until20120730 and derivedfrom Jason-2 after)
Non parametric SSB[Labroue 2004[27]](with cycles 1 to 21 usingGDR-B standards)
Non parametric SSB[Labroue 2004[27]](with cycles 41 to 60using GDR-B standards)
Orbit error Specific filtering of long-wavelength signal3
Long wave-lengh errors
Optimal Interpolation [Le Traon et al 1998[31]]
Intercalibration Reference from cycle 20Mean profile(see III261)
Computed with cycles 11-353 TP data and with cy-cles 11-250 J1 data refer-enced [19931999]
TPNJ1N computedwith cycles 369-479TPN data referenced[19931999] J1G NoMP can be used insteadthe MSS_CNES_CLS11[39] is used
No Mean Profile can beused for Envisat on itsnew orbit Instead theMSS_CNES_CLS11 [39]is used
(2) A flag included in the along-track files indicates the source of the production (OGDRFDGDR orIGDR) If flag=0 the processed data comes from OGDRsFDGDRs if flag=1 the processed data comesfrom IGDRs(3) Specific data processing was applied on long wave-length signal (sectIII23 of the user manual)
Table 4 Corrections and models applied in SSALTODUACS NRT products produced from OG-DRsFDGDRs
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III22 Acquisition
The acquisition process is twofold
bull straightforward retrieval and reformatting of altimeter data and dynamic auxiliary data (pressure andwet troposphere correction grids from ECMWF are provided by Meteo France TEC grids from JPLNRT MOG2D corrections) from external repositories
bull synchronisation process
To be homogenized properly altimeter data sets require various auxiliary data The acquisition softwaredetects downloads and processes incoming data as soon as they are available on remote sites (externaldatabase FTP site) Data are split into passes if necessary If data flows are missing or late the synchroni-sation engine put unusable data in waiting queues and automatically unfreezes them upon reception of themissing auxiliary data This processing step delivers raw data that is to say data that have been dividedinto cycles and passes and ordered chronologicallyFrom SSALTODUACS V80 the acquisition step uses two different data flows in near-real time the OGDRflow (within a few hours) and the IGDR flow (within a few days)For each OGDR input the system checks that no equivalent IGDR entry is available in the data base beforeacquisition for each IGDR input the system checks and delete the equivalent OGDR entry in the data baseThese operations aim to avoid duplicates in SSALTODUACS system
Figure 6 Overview of the near real time system data flow management
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III23 Homogenization
The Homogenization process consists in applying the most recent corrections models and references rec-ommended for altimeter products Each mission is processed separately as its needs depend on the baseinput data The list of corrections and models currently applied is provided in tables 3 and 4 for NRT dataThe system includes SLA filtering to process OGDR data DUACS extract from these data sets the shortscales (space and time) which are useful to better describe the ocean variability in real time and merge thisinformation with a fair description of large scale signals provided by the multi-satellite observation in nearreal time (read IGDR-based DUACS data) Finally an hybrid SLA is computed
Figure 7 Merging pertinent information from IGDR and OGDR processing
III24 Input data quality control
The Input Data Quality Control is a critical process applied to guarantee that DUACS uses only the mostaccurate altimeter data Thanks to the high quality of current missions this process rejects a small percent-age of altimeter measurements but these erroneous data could be the cause of a significant quality lossThe quality control relies on standard raw data editing with quality flags or parameter thresholds but alsoon complex data editing algorithms based on the detection of erroneous artefacts mono and multi-missioncrossover validation and macroscopic statistics to edit out large data flows that do not meet the systemrsquosrequirements
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III25 Multi-mission cross-calibration
The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistentand accurate information It removes any residual orbit error (OE Le Traon and Ogor 1998[32]) or longwavelength error (LWE Le Traon et al 1998[31]) as well as large scale biases and discrepancies betweenvarious data flows
This process is based on two very different algorithms a global multi-mission crossover minimization fororbit error reduction (OER) and Optimal Interpolation (OI) for LWE
Multi-satellite crossover determination is performed on a daily basis All altimeter fields (measurementcorrections and other fields such as bathymetry MSS) are interpolated at crossover locations and datesCrossovers are then appended to the existing crossover database as more altimeter data become availableThis crossover data set is the input of the Orbit Error Reduction (OER) method Using the precision of thereference mission orbit a very accurate orbit error can be estimated This processing step does not concernOGDR dataLWE is mostly due to residual tidal or inverse barometer errors and high frequency ocean signals The OIused for LWE reduction uses precise parameters derived from
bull accurate statistical description of sea level variability
bull localized correlation scales
bull mission-specific noise and precise assumptions on the long wavelength errors to be removed (from arecent analysis of one year of data from each mission)
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III26 Product generation
The product generation process is composed of four steps computation of raw SLA cross-validationfilteringampsub-sampling and generation of by-products
III261 Computation of raw SLA
Since the geoid is not well known yet the SSH cannot be used directly the SSH anomalies are used insteadThey are computed from the difference of the instantaneous SSH - a temporal reference This temporalreference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeattrack analysis cannot be used The errors affecting the SLAs MPs and MSS have different magnitudes andwavelengths The computation of the SLAs and their errors associated are detailed in Dibarboure et al 2010[9]
Use of a Mean ProfileIn the repeat track analysis (when the satellites flies over a repetitive orbit) measurements are re-sampledalong a theoretical ground track (or mean track) associated to each mission Then a Mean Profile (MP) issubtracted from the re-sampled data to obtain SLA The MP is a time average of similarly re-sampled dataover a long period
bull The Mean Profile used for Jason-2 is computed with 10 years of TP (cycles 11 to 353) and 6 years ofJason-1 (cycles 11 to 250)
bull The Mean Profile used from Jason-1 cycle 262 to 374 (where satellites are on interleaved ground-tracks) is computed with 3 years of TP (cycles 369 to 479)
bull No Mean Profile can be used for Envisat on its new orbit (enn) Jason-1 on its geodetic orbit (j1g) norfor Cryosat-2 mission (c2) because there is no repetitive track The MSS must be used instead (seebelow)
Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible
bull Indeed as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide precise cross-track projection andor interpolation schemes are required to avoid errors
bull The mesoscale variability error (which is lt35 cm for MP between 3 to 5 years and lt1cm for WLof 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a prioriknowledge from Sea Level maps derived from previous iterations or from other missions
bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
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bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for Envisat since november 2010 and for Cryosat-2 mission (c2)because the satellite is not in a repetitive orbit phase The alternative is to use the MSS instead The griddedMSS is derived from along track MPs and data from geodetic phases Thus any error on the MP is alsocontained in the MSS There are essentially 4 types of additional errors on gridded MSS which are hard toquantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
Note that for the Arctic regional products the DTU10 MSS [1] is taken into account instead of the CLS01MSS Indeed the accuracy of DTU10 compared to CLS01 is further demonstrated by the significant sealevel anomaly variance reduction found over the whole Arctic Ocean as shown in Prandi et al [42]
III262 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III263 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
Page 29
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III27 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III271 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
Page 30
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III272 Performance indicators
To appreciate the quality situation of the DUACS system new performance indicators are computed dailyThey aim at evaluate the status of the main processing steps of the system the input data availability theinput data coverage the input data quality and the output product quality These indicators are computed foreach and every currently working satellite and combined to obtain the overall status
Figure 8 Example with the key performance indicator on 20090627
See the description the latest and previous indicators on Aviso websitehttpwwwavisooceanobscomindexphpid=1516
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III3 Delayed Time processing steps
III31 Input data models and corrections applied
Delayed Time MyOcean products are generated
bull from Aviso GDR products for TP Jason-1 Jason-2 and Envisat (GDR-A cycles 1 to 22 GDR-Bcycles 23 to 85 GDR-C from cycle 86)
bull from NOAA GDR for GFO and from CERSAT (IFREMER) OPR for ERS-1 and ERS-2 (phases C(1st 35-day repeat orbit period) phase E and F (geodetic phases) phase G for ERS-1 (last 35-dayrepeat orbit period tandem phase with ERS-2 phase A for ERS-2 (1st 35-day repeat orbit periodtandem phase with ERS-1))
All GDR products are computed with a Precise Orbit Ephemeris (POE) and are delivered within 2 to 3months depending on the mission For several missions an updated orbit is used
bull For ERS-1amp-2 the orbit used is DGME-04 provided by Delft Institute (httpwwwdeostudelftnl)until June 2003
bull For TopexPoseidon the orbit used is GSFC (std0809) for the whole mission
bull For Envisat CNES POE of GDR-C standard is used for the whole mission
bull For the whole GFO mission the orbit used is GSFC (std0809) and when not available NASA POE isused
Altimetric product Source Availability Type of orbit
TopexPoseidon GDR NASACNES - GSFC POE
Jason-1 GDR (GDR-C) CNESNASA ~40 days CNES POE
Jason-2 GDR (GDR-C) CNESNASA ~60 days CNES POE
GFO GDR NOAA - GSFCNASA POE
ERS-1amp2 IFREMERESA - DGME-04
Envisat (GDR-A GDR-B andGDR-C from cycle 86)
ESA ~2 months CNES POE
Table 5 SSALTODUACS Delayed Time Input data overview
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
DU
AC
S20
11D
Tpr
oduc
t(gtV
30
0)j2
j1j1
ntp
tpn
e1e2
ene
nng2
Prod
uct
stan
dard
ref
GD
R-C
OPR
GD
R-A
(Cyc
les
1to
22)
GD
R-B
(cyc
les
23-8
5)
GD
R(N
OA
A)
Orb
itC
nes
POE
GSF
C(I
TR
F20
05G
RA
CE
last
stan
dard
s)
DG
ME
-04
(Sch
arro
oan
dV
isse
r19
98[4
8]C
NE
SPO
E(G
DR
-1st
anda
rds
forc
ycle
s9
to22
GD
R-C
stan
dard
sfr
omcy
cle
23)
GSF
C(I
TR
F20
05
GR
AC
Ela
stst
anda
rds
Iono
pher
icD
ual f
requ
ency
altim
eter
rang
em
easu
rem
ents
Dua
l fre
quen
cyal
timet
erra
nge
mea
sure
men
ts(T
opex
)D
OR
IS(P
OSE
IDO
N)
Ben
t mod
elB
ent m
odel
(cyc
les
1-36
)G
IMm
odem
from
cycl
e37
((Ii
jima
etal
19
98[2
4])
Dua
l-fr
eque
ncy
altim
eter
rang
em
easu
rem
ent(
cycl
e9-
64)a
ndG
IMm
odel
gtcyc
le65
(Iiji
ma
etal
19
99[2
4])c
orre
cted
from
8m
mbi
as
From
GIM
mod
el(I
ijim
aet
al1
998
[24]
)
Dry
trop
o-sp
here
Mod
elco
mpu
ted
from
EC
MW
FG
auss
ian
grid
s(n
ewS1
and
S2at
mos
pher
ictid
esar
eap
plie
d)
Mod
elco
mpu
ted
from
EC
MW
Fre
ctan
gula
rgri
ds(n
ewS1
and
S2at
mos
pher
ictid
esar
ein
clud
ed)
Wet
trop
o-sp
here
JMR
AM
Rra
diom
eter
furt
hert
han
50km
from
the
coas
tsF
rom
EC
MW
Fm
odel
ford
ista
nces
betw
een
10an
d50
km
TM
Rra
diom
eter
(Sch
aroo
etal
20
04[4
9])
MW
RC
orre
ctio
nof
the
drif
ton
the
236
GH
zbr
ight
ness
tem
pera
ture
(Sch
arro
oet
al
2004
[49]
)Neu
ral
Net
wor
kal
gori
thm
(Tra
nan
dO
blig
is
2003
[50]
MW
Rra
diom
eter
furt
hert
han
50km
from
the
coas
tsan
dco
rrec
ted
from
side
lobe
s(f
rom
cycl
e41
)E
CM
WF
mod
elfo
rdis
tanc
esbe
twee
n10
and
50km
GFO
radi
omet
er
DA
CM
OG
2DH
igh
Res
olut
ion
forc
edw
ithE
CM
WF
pres
sure
and
win
gfie
lds
(S1
and
S2w
ere
excl
uded
)+in
vers
eba
rom
eter
com
pute
dfr
omre
ctan
gula
rgri
ds
Tabl
e6
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(1
2)
Page 33
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
j2j1
j1n
tptp
ne1
e2en
enn
g2O
cean
tide
GO
T4v
7(S
1an
dS2
are
incl
uded
)Po
letid
e[W
ahr
1985
[53]
]So
lidea
rth
tide
Ela
stic
resp
onse
totid
alpo
tent
ial[
Car
twri
ghta
ndTa
yler
197
1[5]
][C
artw
righ
tand
Edd
en1
973[
6]]
Loa
ding
tide
GO
T4v
7(S
1pa
ram
eter
isin
clud
ed)
Sea
stat
ebi
asN
onpa
ram
etri
cSS
B[G
aspa
reta
l20
02[2
0]]
Non
para
met
ric
SSB
[NT
ran
and
al2
010[
51]]
BM
3[G
aspa
ran
dO
gor
1994
[17]
]
Non
para
met
ric
SSB
[Mer
tzet
al
2005
[38]
]
Non
para
met
ric
SSB
[Gas
pare
tal
2002
]w
ithG
DR
-Bst
anda
rds
forc
ycle
s9
to85
and
with
GD
R-C
stan
dard
sfr
omcy
cle
86
Non
para
met
ric
SSB
[NT
ran
etal
20
10[5
1]]
Orb
iter
ror
Glo
bal m
ulti-
mis
sion
cros
sove
rmin
imiz
atio
n(L
eTr
aon
and
Ogo
r19
98[3
2])
Lon
gw
ave-
leng
her
rors
Opt
imal
Inte
rpol
atio
n(L
eTr
aon
etal
19
98[3
1])
Inte
rcal
ibra
tion
Ref
eren
cefr
omcy
cle
11R
efer
ence
from
cycl
e1
to35
4C
orre
ctio
nof
regi
onal
bias
J2J
1de
duce
dfr
omin
terc
alib
ratio
nph
ase
(cyc
le11
J2)
Cor
rect
ion
ofgl
obal
biai
sJ1
TP
deacutedu
ced
from
inte
rcal
ibra
tion
phas
e(c
ycle
s11
J1)
Mea
npr
o-fil
e(s
eeII
I36
1)
Com
pute
dw
ithcy
cles
11-3
53T
Pda
taan
dw
ithcy
cles
11-2
50J1
data
ref
eren
ced
[199
319
99]
TP
J1 c
ompu
ted
with
cycl
es11
-353
TP
data
and
with
cycl
es11
-250
J1da
tar
efer
ence
d[1
993
1999
]T
PNJ
1Nc
ompu
ted
with
cycl
es36
9-47
9T
PNda
tar
efer
ence
d[1
993
1999
]
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
ref
eren
ced
[199
319
99]
EN
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
re
fere
nced
[199
319
99]
EN
Nu
seof
MSS
_CN
ES_
CL
S11
[39]
Com
pute
dw
ithcy
cles
37-1
87G
2da
ta
refe
renc
ed[1
993
1999
]
Peri
odof
use
from
cycl
e9
from
cycl
e9
cycl
es1
to48
1cy
cles
15to
43In
clud
ing
E-F
geod
etic
phas
es
cycl
es1
to83
from
cycl
e9
cycl
es37
to22
2
Tabl
e7
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(2
2)
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III32 Acquisition
The acqusition process in Delayed time is much simpler than in Near Real time it consists in a synchronisa-tion process of all the auxiliary data required to homogenize propely the altimeter data sets The acquisitionstep uses the GDRs or the OPRs provided by the agencies
III33 Homogenization
The Homogenization process consists in applying the most recent corrections models and references rec-ommended for altimeter products Each mission is processed separately as its needs depend on the baseinput data The list of corrections and models currently applied is provided in tables 6 and 7 for DT data
III34 Input data quality control
The Input Data Quality Control is a critical process applied to guarantee that DUACS uses only the mostaccurate altimeter data Thanks to the high quality of current missions this process rejects a small percent-age of altimeter measurements but these erroneous data could be the cause of a significant quality lossThe quality control relies on standard raw data editing with quality flags or parameter thresholds but alsoon complex data editing algorithms based on the detection of erroneous artefacts mono and multi-missioncrossover validation and macroscopic statistics to edit out large data flows that do not meet the systemrsquosrequirements
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III35 Multi-mission cross-calibration
The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistentand accurate information It removes any residual orbit error (OE Le Traon and Ogor 1998[32]) or longwavelength error (LWE Le Traon et al 1998[31]) as well as large scale biases and discrepancies betweenvarious data flows
This process is based on two very different algorithms a global multi-mission crossover minimization fororbit error reduction (OER) and Optimal Interpolation (OI) for LWE
Multi-satellite crossover determination is performed on a daily basis All altimeter fields (measurementcorrections and other fields such as bathymetry MSS) are interpolated at crossover locations and datesCrossovers are then appended to the existing crossover database as more altimeter data become availableThis crossover data set is the input of the Orbit Error Reduction (OER) method Using the precision of thereference mission orbit a very accurate orbit error can be estimated LWE is mostly due to residual tidalor inverse barometer errors and high frequency ocean signals The OI used for LWE reduction uses preciseparameters derived from
bull accurate statistical description of sea level variability
bull localized correlation scales
bull mission-specific noise and precise assumptions on the long wavelength errors to be removed (from arecent analysis of one year of data from each mission)
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III36 Product generation
The product generation process is composed of four steps computation of raw SLA cross-validationfilteringampsub-sampling and generation of by-products
III361 Computation of raw SLA
Since the geoid is not well known yet the SSH cannot be used directly the SSH anomalies are used insteadThey are computed from the difference of the instantaneous SSH - a temporal reference This temporalreference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeattrack analysis cannot be used The errors affecting the SLAs MPs and MSS have different magnitudes andwavelengths The computation of the SLAs and their errors associated are detailed in Dibarboure et al 2010[9]
Use of a Mean ProfileIn the repeat track analysis (when the satellites flies over a repetitive orbit) measurements are re-sampledalong a theoretical ground track (or mean track) associated to each mission Then a Mean Profile (MP) issubtracted from the re-sampled data to obtain SLA The MP is a time average of similarly re-sampled dataover a long period
bull The Mean Profile used for TP (cycles 1 to 364) Jason-1 (cycles 1 to 259) and Jason-2 is computedwith 10 years of TP (cycles 11 to 353) and 6 years of Jason-1 (cycles 11 to 250)
bull The Mean Profile used for TP (cycles 368 to 481) and from Jason-1 cycle 262 to 374 (where satellitesare on interleaved ground-tracks) is computed with 3 years of TP (cycles 369 to 479)
bull The Mean Profile used for ERS-1 in its 35 days repetitive orbit mission ERS-2 and Envisat (only forthe first orbit before November 2010) is computed with 8 years of ERS-2 (cycles 1 to 85) and 6 yearsof Envisat (cycles 10 to 72)
bull No Mean Profile can be used for Envisat on its new orbit (enn) Jason-1 on its geodetic orbit (j1g)because there is no repetitive track The MSS must be used instead (see below)
bull The Mean Profile used for GFO is computed with 7 years of GFO cycles 37 to 187
Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible
bull Indeed as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide precise cross-track projection andor interpolation schemes are required to avoid errors
bull The mesoscale variability error (which is lt35 cm for MP between 3 to 5 years and lt1cm for WLof 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a prioriknowledge from Sea Level maps derived from previous iterations or from other missions
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bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for ERS-1 for its 168 days geodetic mission (phases E-F from April1994 to March 1995) or for Envisat since november 2010 because the satellite is not in a repetitive orbitphase The alternative is to use the MSS instead The gridded MSS is derived from along track MPs anddata from geodetic phases Thus any error on the MP is also contained in the MSS There are essentially 4types of additional errors on gridded MSS which are hard to quantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
III362 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III363 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
Page 38
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III37 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III371 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
Page 39
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
IV MYOCEAN PRODUCTS
IV1 Near Real Time Products
The purpose of the NRT DUACS component is the acquisition of altimeter data from various altimeter mis-sions in near-real time (ie within a few days at most) the validation and correction of these altimeter datasets (ie edition and selection update of corrections and homogenization orbit error reduction) in order toproduce each day along-track productsProducts are as follows
Along-track products global and regional (Mediterranean and Black Seas Arctic Ocean and Europeareas)
bull Sea Level Anomaly (NRT-SLA) for each mission with NRT-SLA ephemeris
IV11 Delay of the products
The availability of the products in near real time is three to twelve hours after the measurement for along-track products Those products are delivered every day
IV12 Temporal availibility
The following table presents the available products by mission and by data periodNear real time products
NRT Jason-2 Jason-1 and Jason-1geodetic
Envisat new Cryosat-2
Temporal Time availability ymlowast
ongoingymlowast-20120303 for
repeat track and20120507-ongoing for
geodetic track
ymlowast
2012040820120101
ongoing
NRT-SLA X X X X
lowastym the temporal coverage for NRT products is fluctuating and depends on updates of Delayed Time prod-ucts When DT products are updated (3 to 4 times per year) the oldest NRT products are replaced by thebetter quality DT products so that the 2 series are overlapping on few weeks or few months
IV2 Delayed Time Products
The Delayed Time component of SSALTODUACS system is responsible for the production of processedJason-1 Jason-2 TP Envisat GFO ERS12 and even Geosat data in order to provide a homogeneousinter-calibrated and highly accurate long time series of SLA DT products are more precise than NRT products Two reasons explain this quality difference The firstone is the better intrinsic quality of the POE orbit used in the GDR processing The second reason is that
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in the DT DUACS processing the products can be computed optimally with a centred computation timewindow for OER LWE On the contrary in NRT case future data are not available so the computationtime window is not centred and therefore not optimalAs for NRT products improved altimeter corrections and processing algorithms are used ocean tide modelto correct altimeter data improved methods for orbit error reduction and mapping
Along-Track products global and regional (Mediterranean and Black Seas)
bull Sea Level Anomaly (DT-SLA) for each mission
IV21 Delay of the products
Weekly products are delivered The availability of the products in delayed time is at the best two monthsafter the date of the measurement The product generation needs all the GDR data of all the missions to takeinto account the best corrections as possible The time delay can be longer in the case of a missing mission
IV22 Temporal availibility
The following table presents the available products by mission and by data periodDelayed time SSALTODUACS products
Upd Jason-2 Jason-1new6
Jason-1 GFO Envisatnew6
Envisat ERS-16
ERS-2Topexnew6
Topex
TemporalTimeavailabil-ity
200810ymlowast
200902ymlowast
200204200810
200001200809
201010ymlowast
200210201010
199210200304
200209200510
199209200204
DT-SLA X X X X X X X X X
lowast ym those dates are updated regularly (3 to 4 times per year) and are avalaible when you download thedata at httpwwwmyoceaneuweb24-cataloguephp6 Jason-1 new orbit starting 200809 Envisat new orbit starting 201010 TP new orbit starting 200209 ERS-1The geodetic phases (E-F) are included There are no ERS-1 data between December 23 1993 and April 10 1994(ERS-1 phase D - 2nd ice phase) Note that during that time products are based only on TopexPoseidon data
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
V DESCRIPTION OF THE PRODUCT SPECIFICATION
V1 General information
Product Specification SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001
Geographical coverage global
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 20-50km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001 Product Specification
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Product Specification SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002
Geographical coverage 55˚W-35˚E 30˚N-46˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002 Product Specification
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Product Specification SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003
Geographical coverage 27˚E-42˚E 40˚N-47˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003 Product Specification
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Product Specification SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004
Geographical coverage 25˚W-42˚E 21˚N-66˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004 Product Specification
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Product Specification SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005
Geographical coverage 0˚W-360˚E 50˚N-82˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005 Product Specification
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VI NOMENCLATURE OF FILES
VI1 Nomenclature of files downloaded through the MyOcean Web PortalDirectgetfile Service
VI11 Nomenclature of the product line
The description of the syntax for the SL TAC SLA products line is given by
SEALEVEL_ltREGIONgt_SLA_L3_ltDELAYgt_OBSERVATIONS_008_ltZONEgt_ltLETTERgtwhere
REGION GLO global geographic coverage product
BS Black Sea products
MED Mediterranean products
ARC Arctic products (for NRT products)
EUROPE Europe products (for NRT products)
DELAY NRT near real time products
RAN delayed time or reanalysis products
ZONE 001 number on 3 digits
002
003
004
LETTER a letter on 1 digit
b
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VI12 Nomenclature of the datasets
The nomenclature used is
dataset-duacs-ltdelaygt-ltzonegt-ltmissiongt-lttype of slagt-l3where the fileds in ltgt are described below
delay nrt near-real time productsran delayed time products
zone global global geographic coverage productmedsea Mediterranean productsblacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1 (only for ran)e2 ERS-2 (only for ran)tp TOPEXPoseidon (only for ran)tpn TOPEXPoseidon on its new orbit (only for
ran)g2 GFO (only for ran)j1 Jason-1 (only for ran)j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisat (only for ran)enn Envisat on its new orbitc2 Cryosat-2 (only for nrt)
type of sla sla filtered slasla_unfiltered non filtered sla (only for ran products)
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VI13 Nomenclature of the NetCdf files
The nomenclature used is
ltdelaygt_ltzonegt_ltmissiongt_sla_ltvariablegt_ltdatebegingt_ltdateendgt_ltdateprodgtnc where the fileds in ltgt are de-scribed below
delay nrt near-real time productsdt delayed time products
zone global global geographic coverage productmed Mediterranean products (for dt)mfstep Mediterranean products (for nrt)blacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1e2 ERS-2tp TOPEXPoseidontpn TOPEXPoseidon on its new orbitg2 GFOj1 Jason-1j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisatenn Envisat on its new orbitc2 Cryosat-2
variable vfec filtered and sub-sampled slavxxc non filtered and non sub-sampled sla (only
for dt)datebegin YYYYMMDD() beginning date of the datasetdateend YYYYMMDD() end date of the datasetdateprod YYYYMMDD production date of the dataset
() For dt data as the dates in the file names are rounded the user wanting data for date T has to read the filescontaining dates T+1 and T-1 in their name and check inside the files if there are some data for date T
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VII DATA FORMAT
This chapter presents the data storage format used for MyOcean products
VII1 NetCdf
The products are stored using the NetCDF format NetCDF (network Common Data Form) is an interface for array-oriented data access and a library that provides an implementation of the interface The netCDF library also definesa machine-independent format for representing scientific data Together the interface library and format support thecreation access and sharing of scientific data The netCDF software was developed at the Unidata Program Center inBoulder Colorado The netCDF libraries define a machine-independent format for representing scientific data Pleasesee Unidata NetCDF pages for more information and to retreive NetCDF software package onhttpwwwunidataucaredupackagesnetcdfindexhtml
NetCDF data is
bull Self-Describing A netCDF file includes information about the data it contains
bull Architecture-independent A netCDF file is represented in a form that can be accessed by computers with dif-ferent ways of storing integers characters and floating-point numbers
bull Direct-access A small subset of a large dataset may be accessed efficiently without first reading through allthe preceding data
bull Appendable Data can be appended to a netCDF dataset along one dimension without copying the dataset orredefining its structure The structure of a netCDF dataset can be changed though this sometimes causes thedataset to be copied
bull Sharable One writer and multiple readers may simultaneously access the same netCDF file
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VII2 Structure and semantic of NetCDF along-track files
The NetCDF Sea Level TAC files are based on the attribute data tags defined by the Cooperative OceanAtmosphereResearch Data Service (COARDS) and Climate and Forecast (CF) metadata conventions The CF convention gener-alises and extends the COARDS convention but relaxes the COARDS constraints on dimension and order and specifiesmethods for reducing the size of datasetsA wide range of software are available to write or read NetCDFCF files API are made available by UNIDATA(httpwwwunidataucaredusoftwarenetcdf)
bull CC++Fortran
bull Java
bull MATLAB Objective-C Perl Python R Ruby TclTk
In addition to these conventions the files are using a common structure and semantic
bull 1 dimension is defined
ndash time it is used to check NetCDF variables depending on time
bull 8 variables are defined
ndash short SLA contains the Sea Level Anomaly values for each time given
ndash int longitude contains the longitude for each measurement
ndash short track contains the track number for each measurement
ndash double time contains the time in days since 1950-01-01 000000 UTC for each measurement
ndash short mean_profile_point_index index of the corrsponding point in the track of the mean profile
ndash byte flag flag=0 the processed data comes from OGDR if flag=1 the processed data comes from theIGDR
ndash int latitude contains the latitude for each measurement
ndash short cycle contains the cycle number for each measurement
bull global attributes
ndash the global attributes gives information about the creation of the file
Example of a NetCDF sla file
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netcdf nrt_global_j1_sla_vfec_20101230_20101230_20101230 dimensions
time = 10385 variables
short SLA(time) SLAcoordinates = longitude latitude SLAlong_name = Sea Level Anomaly SLA_FillValue = 32767s SLAadd_offset = 0 SLAscale_factor = 0001 SLAunits = m SLAstandard_name = sea_surface_height_above_sea_level
int longitude(time) longitudelong_name = Longitude of measurement longitude_FillValue = 2147483647 longitudeadd_offset = 0 longitudestandard_name = longitude longitudescale_factor = 1e-06 longitudeunits = degrees_east
short track(time) tracklong_name = Track in cycle the measurement belongs to track_FillValue = 32767s trackunits = 1 trackcoordinates = longitude latitude
double time(time) timelong_name = Time of measurement time_FillValue = 184467440737096e+19 timeaxis = T timestandard_name = time timeunits = days since 1950-01-01 000000 UTC
int latitude(time) latitudelong_name = Latitude of measurement latitude_FillValue = 2147483647 latitudeadd_offset = 0 latitudestandard_name = latitude latitudescale_factor = 1e-06 latitudeunits = degrees_north
short flag(time) flagcoordinates = longitude latitude flag_FillValue = 3267s flaglong_name = data origin flagflag_values = 1s 0s flagflag_meanings = igdr_like non_igdr_like flagcomment = The origin of the data is determined by the types of geophysical datarecords (GDR) used in computation of the SLA 1 for the Interim GDR (IGDR) and0 for Operational GDR (OGDR)
short cycle(time) cyclelong_name = Cycle the measurement belongs to cycle_FillValue = 32767s cycleunits = 1 cyclecoordinates = longitude latitude
global attributeshistory = 22-Feb-2011 155243 CET File created by the SSLATODUACS system version 1001 comment = Produce from ENVISAT Extension Phase satellite altimetry data institution = CLSCNES
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references = httpwwwavisooceanobscomfileadmindocumentsdatatoolshdbk_duacspdf source = satellite altimetry title = along track Sea Level Anomaly Conventions = CF-14
dataSLA =
7 7 11 10 -2 -22 -39 -41 -30 -13 -3 -5 -16 -26 -32 -35-35 -35 -37 -35 -31 -29 -31 -35 -32 -21 -10 -10 -19 -20 -1-69 -57 -49 -45 -39 -30 -28 -31 -27 -13 -2 -5 -15 -3 1112 3 -7 -10 -14 -15 -22 -31 -37 -32 -17 -10
longitude =74743328 74868400 74993968 75120040 75246616 7537372875501368 75629568 75758320 75887656 76017568 76148080 7627920876388952 76477056 76565456 76654144 76743128 76832400 76921984329429568 329535424 329641792 329748672 329856096 329964032330072512 330181536 330291072 330401184
track =92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 9292 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92113 113 113 113 113 113 113 113 113 113 113 113 113 113113 113 113 113 113 113 113 113 113
time =222780000565705 222780001314719 222780002063733222780002812747 222780003561761 222780004310775 222780005059788222780005808802 222780006557816 22278000730683 222780008055844222780008804858 222780009553872 22278001017805 222780010677393222788257112198 222788257486705 222788257861212 222788258235719222788258610226 222788258984733 222788259359239 222788259733746222788260108253 22278826048276
mean_profile_point_index =1872 1878 1884 1890 1896 1902 1908 19141920 1926 1932 1938 1944 1949 1953 1957 1961 1965 1969 19732306 2309 2312 2315 2318 2321 2327 2330 2333 2336 2339 23422345 2348 2351 2354 2357 2360 2363 2366
flag =0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
latitude =-16225506 -16539731 -16853833 -17167810 -17481660 -17795380-18108966 -18422418 -18735729 -19048899 -19361924 -19674801-19987527 -20248015 -20456329 -20664569 -20872739 -2108083739481297 39628277 39775133 39921866 40068472 40214953 4036130840507533 40653629 40799592 40945423 41091120 41236684 41382111
cycle =331 331 331 331 331 331 331 331 331 331 331 331 331
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331 331 331 331 331 331 331 331 331 331 331 331 331 331331 331 331 331 331 331 331 331 331 331 331 331
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VIII HOW TO DOWNLOAD A PRODUCT
VIII1 Download a product through the MyOcean Web Portal DirectgetfileService
You first need to register Please find below the registration stepshttpwwwmyoceaneuweb34-products-and-services-faqphp1Once registered the MyOcean FAQ httpwwwmyoceaneuweb34-products-and-services-faqwill guide you on How to download a product through the MyOcean Web Portal Directgetfile Service
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IX NEWS AND UPDATES
IX1 [Duacs] Operational news
To be kept informed on events occurring on the satellites and on the eventual interruption of the services of the DUACSprocessing system see the [Duacs] operational news on the Aviso websitehttpwwwavisooceanobscomendataoperational-newsindexhtml
IX2 Updates
To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtmlSince 2010 a complete reprocessing of all altimetry data (cumulated total of about 55 years of data) is available Themain changes introduced in the Duacs DT v300 reprocessed data set in SSALTODUACS reprocessed DT data setare listed herehttpwwwavisooceanobscomfileadmindocumentsdataduacsduacs_DT_2010_reprocessing_impactpdf
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II5 Addition of Europe and Arctic products (January 2012)
Since the MyOcean V2 two new along-track products are computed in Near Real Time intended foraddressing the needs of data assmilation and validation in regional models
bull Following the TAPAS (Tailored Altimeter Product for Assimilation Systems) initiative launched bySL TAC with all the Modeling and Forecasting Centers (MFCs) the Europe regional products (PLSEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004) have been proposed (figure 3) They areavailable in Near Real Time onlyThey are studied to partly fulfil the needs of the Centers with adapted filtering and resolution Thoseparameters have been tuned in order to provide boundary conditions for the Atlantic assimilationmodels They are different from the ones used for Mediterranean and Black Seas products If you needto study the Mediterranean Sea or the Black Sea yoursquod better use the dedicated products describedabove since the processing parameters have been fitted to be adapted to the dynamics of the ocean inthose regions
Figure 3 Coverage of the Europe product for Jason-1 Jason-2 and Envisat from August 18th to September9th 2011
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bull The Arctic along-track products (PL SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005) coverlatitudes between 45 and 82 degrees (figure 4) They are available in Near Real Time only
Figure 4 Coverage of the Arctic region with Envisat from October 28th 2011 to January 3rd 2012
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III SSALTODUACS SYSTEM
III1 Introduction
This chapter presents the input data used by SSALTODUACS system and an overview of the different pro-cessing steps necessary to produce the output dataSSALTODUACS system is made of two components a Near Real Time one (NRT) and a Delayed Time(DT) oneIn NRT the systemrsquos primary objective is to provide operational applications with directly usable high qual-ity altimeter data from all missions availableIn DT it is to maintain a consistent and user-friendly altimeter database using the state-of-the-art recom-mendations from the altimetry communityFollowing figure gives an overview of DUACS system where processing sequences can be divided into 7main steps
bull acquisition
bull homogenization
bull input data quality control
bull multi-mission cross-calibration
bull product generation
bull merging
bull final quality control
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Figure 5 SSALTODUACS processing sequences
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III2 Near Real Time processing steps
III21 Input data models and corrections applied
To produce SLA in near-real time the DUACS system uses two flows based on the same instrumental mea-surements but with a different quality
bull The IGDR that are the latest high-quality altimeter data produced in near-real-time
bull The OGDR that includes real time data (OSTMJason-2 and Jason-1 OSDR) to complete IGDR Thesefast delivery products do not always benefit from precise orbit determination nor from some exter-nal model-based corrections (Dynamic Atmospheric Correction (DAC) Global Ionospheric Maps(GIM))
Integration of OGDR data and the introduction of Jason-2Jason-1 tandem increased the resilience and pre-cision of the system A better restitution of ocean variability is observed especially in high energetic areas
Altimetric product Source Availability Type of orbit
Jason-2 IGDR CNES ~24h CNES MOE GDR-Cuntil 20120730
CNES MOE GDR-Dsince 20120731
OGDR NOAAEUMETSAT ~3 to 5 h
Jason-1 IGDR CNESNASA ~48 h CNES MOE GDR-Dsince 20120507
OGDR CNESNASA ~3 to 12 h
Envisat IGDR ESACNES not deliveredsince 20120408
CNES MOE GDR-Dsince 20120121
FDGDR ESA not deliveredsince 20120408
Cryosat-2 IGDR-like ESACNES ~48 h CNES MOE GDR-D
not delivered
Table 2 SSALTODUACS Near-Real Time Input data overview
See Figure 6 Overview of the near real time system data flow management
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DUACS 2011 NRT product from IGDR1
j2 j1nj1g enn c2Productstandard ref
version C until20120730 and D after
version C version 21 CPP [2]
Orbit CNES MOE GDR-Cuntil 20120730
GDR-D after
CNES MOE GDR-C forj1n and CNES MOE
GDR-D for j1g
CNES MOE GDR-Dfrom 20120121 to
20120408
CNES MOE GDR-D
Ionopheric bi-frequency altimeter range measurements GIM model for cgt64 (Iijima et al1998[24])Dry tropo Model computed from ECMWF Gaussian grids (new S1 and S2 atm tides applied)Wet tropo-sphere
AMR radiometer(enhancement in coastal
regions since20120730)
JMR radiometer MWR radiometer andcorrected from side
lobes
Model computed fromECMWF Gaussian
grids
DAC MOG2D High Resolution forced with ECMWF pressure and wind fields (S1 and S2 wereexcluded) (Carrere and Lyard 2003[3])+ inverse barometer Filtering temporal window is
un-centered (no data in the future)Ocean tide GOT4v8 (S1 and S2 are included) and TPX 072 [16] for Arctic productsPole tide [Wahr 1985 [53]]Solid earthtide
Elastic response to tidal potential [Cartwright and Tayler 1971[5]] [Cartwright andEdden 1973[6]]
Loading tide GOT4v8 (S1 and S2 are included)Sea statebias
Non parametric SSB[Labroue 2004[27]](with cycles J1 1 to 11
using GDR-B standardsuntil 20120730 andderived from Jason-2
after)
Non parametric SSB[Labroue 2004[27]](with cycles 1 to 21
using GDR-Bstandards)
Non parametric SSB[Labroue 2004[27]](with cycles 41 to 60
using GDR-Bstandards)
Same as Jason-2 SSB
Orbit error Global multi-mission crossover minimization (Le Traon and Ogor1998[32])
Long wave-lengh errors
Optimal Interpolation [Le Traon et al 1998[31]]
Intercalibration Reference from cycle20
Mean pro-file (seeIII261)
Computed with cycles11-353 TP data andwith cycles 11-250J1 data referenced[19931999]
TPNJ1N computedwith cycles 369-479TPN data refer-enced [19931999]J1G No MP can beused instead theMSS_CNES_CLS11[39] is used
No Mean Profilecan be used forEnvisat on its neworbit Instead theMSS_CNES_CLS11[39] is used
No Mean Profilecan be used forCryosat-2 Instead theMSS_CNES_CLS11[39] is used
(1) A flag included in the along-track files indicates the source of the production (OGDRFDGDR orIGDR) If flag=0 the processed data comes from OGDRsFDGDRs if flag=1 the processed data comesfrom IGDRs
Table 3 Corrections and models applied in SSALTODUACS NRT products produced from IGDRs
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DUACS 2011 NRT product from OGDR or FDGDR2
j2 j1nj1g ennProduct stan-dard ref
version C until 20120730and D after
version C version 21
Orbit Navigator Extrapolated CNES MOEGDR-D since 20120121
Ionopheric From-dual frequency altimeter range measurements From GIM model fromcycle 65 (Iijima et al1998 [24])
Dry troposphere Model computed from ECMWF Gaussian grids (new S1 and S2 atmospherictides are applied)
Wet tropo-sphere
AMR radiometer(enhancement in coastal
regions since 20120730)
JMR radiometer MWR radiometer andcorrected from side lobes
DAC Inverse Barometer forecastedOcean tide GOT4v8 (S1 and S2 are included) and TPX 072 [16] for Arctic productsPole tide [Wahr 1985 [53]]Solid earth tide Elastic response to tidal potential [Cartwright and Tayler 1971[5]]
[Cartwright and Edden 1973[6]]Loading tide GOT4v8 (S1 and S2 are included)Sea state bias Non parametric SSB
[Labroue 2004[27]] (withcycles J1 1 to 11 usingGDR-B standards until20120730 and derivedfrom Jason-2 after)
Non parametric SSB[Labroue 2004[27]](with cycles 1 to 21 usingGDR-B standards)
Non parametric SSB[Labroue 2004[27]](with cycles 41 to 60using GDR-B standards)
Orbit error Specific filtering of long-wavelength signal3
Long wave-lengh errors
Optimal Interpolation [Le Traon et al 1998[31]]
Intercalibration Reference from cycle 20Mean profile(see III261)
Computed with cycles 11-353 TP data and with cy-cles 11-250 J1 data refer-enced [19931999]
TPNJ1N computedwith cycles 369-479TPN data referenced[19931999] J1G NoMP can be used insteadthe MSS_CNES_CLS11[39] is used
No Mean Profile can beused for Envisat on itsnew orbit Instead theMSS_CNES_CLS11 [39]is used
(2) A flag included in the along-track files indicates the source of the production (OGDRFDGDR orIGDR) If flag=0 the processed data comes from OGDRsFDGDRs if flag=1 the processed data comesfrom IGDRs(3) Specific data processing was applied on long wave-length signal (sectIII23 of the user manual)
Table 4 Corrections and models applied in SSALTODUACS NRT products produced from OG-DRsFDGDRs
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III22 Acquisition
The acquisition process is twofold
bull straightforward retrieval and reformatting of altimeter data and dynamic auxiliary data (pressure andwet troposphere correction grids from ECMWF are provided by Meteo France TEC grids from JPLNRT MOG2D corrections) from external repositories
bull synchronisation process
To be homogenized properly altimeter data sets require various auxiliary data The acquisition softwaredetects downloads and processes incoming data as soon as they are available on remote sites (externaldatabase FTP site) Data are split into passes if necessary If data flows are missing or late the synchroni-sation engine put unusable data in waiting queues and automatically unfreezes them upon reception of themissing auxiliary data This processing step delivers raw data that is to say data that have been dividedinto cycles and passes and ordered chronologicallyFrom SSALTODUACS V80 the acquisition step uses two different data flows in near-real time the OGDRflow (within a few hours) and the IGDR flow (within a few days)For each OGDR input the system checks that no equivalent IGDR entry is available in the data base beforeacquisition for each IGDR input the system checks and delete the equivalent OGDR entry in the data baseThese operations aim to avoid duplicates in SSALTODUACS system
Figure 6 Overview of the near real time system data flow management
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III23 Homogenization
The Homogenization process consists in applying the most recent corrections models and references rec-ommended for altimeter products Each mission is processed separately as its needs depend on the baseinput data The list of corrections and models currently applied is provided in tables 3 and 4 for NRT dataThe system includes SLA filtering to process OGDR data DUACS extract from these data sets the shortscales (space and time) which are useful to better describe the ocean variability in real time and merge thisinformation with a fair description of large scale signals provided by the multi-satellite observation in nearreal time (read IGDR-based DUACS data) Finally an hybrid SLA is computed
Figure 7 Merging pertinent information from IGDR and OGDR processing
III24 Input data quality control
The Input Data Quality Control is a critical process applied to guarantee that DUACS uses only the mostaccurate altimeter data Thanks to the high quality of current missions this process rejects a small percent-age of altimeter measurements but these erroneous data could be the cause of a significant quality lossThe quality control relies on standard raw data editing with quality flags or parameter thresholds but alsoon complex data editing algorithms based on the detection of erroneous artefacts mono and multi-missioncrossover validation and macroscopic statistics to edit out large data flows that do not meet the systemrsquosrequirements
Page 26
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III25 Multi-mission cross-calibration
The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistentand accurate information It removes any residual orbit error (OE Le Traon and Ogor 1998[32]) or longwavelength error (LWE Le Traon et al 1998[31]) as well as large scale biases and discrepancies betweenvarious data flows
This process is based on two very different algorithms a global multi-mission crossover minimization fororbit error reduction (OER) and Optimal Interpolation (OI) for LWE
Multi-satellite crossover determination is performed on a daily basis All altimeter fields (measurementcorrections and other fields such as bathymetry MSS) are interpolated at crossover locations and datesCrossovers are then appended to the existing crossover database as more altimeter data become availableThis crossover data set is the input of the Orbit Error Reduction (OER) method Using the precision of thereference mission orbit a very accurate orbit error can be estimated This processing step does not concernOGDR dataLWE is mostly due to residual tidal or inverse barometer errors and high frequency ocean signals The OIused for LWE reduction uses precise parameters derived from
bull accurate statistical description of sea level variability
bull localized correlation scales
bull mission-specific noise and precise assumptions on the long wavelength errors to be removed (from arecent analysis of one year of data from each mission)
Page 27
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III26 Product generation
The product generation process is composed of four steps computation of raw SLA cross-validationfilteringampsub-sampling and generation of by-products
III261 Computation of raw SLA
Since the geoid is not well known yet the SSH cannot be used directly the SSH anomalies are used insteadThey are computed from the difference of the instantaneous SSH - a temporal reference This temporalreference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeattrack analysis cannot be used The errors affecting the SLAs MPs and MSS have different magnitudes andwavelengths The computation of the SLAs and their errors associated are detailed in Dibarboure et al 2010[9]
Use of a Mean ProfileIn the repeat track analysis (when the satellites flies over a repetitive orbit) measurements are re-sampledalong a theoretical ground track (or mean track) associated to each mission Then a Mean Profile (MP) issubtracted from the re-sampled data to obtain SLA The MP is a time average of similarly re-sampled dataover a long period
bull The Mean Profile used for Jason-2 is computed with 10 years of TP (cycles 11 to 353) and 6 years ofJason-1 (cycles 11 to 250)
bull The Mean Profile used from Jason-1 cycle 262 to 374 (where satellites are on interleaved ground-tracks) is computed with 3 years of TP (cycles 369 to 479)
bull No Mean Profile can be used for Envisat on its new orbit (enn) Jason-1 on its geodetic orbit (j1g) norfor Cryosat-2 mission (c2) because there is no repetitive track The MSS must be used instead (seebelow)
Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible
bull Indeed as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide precise cross-track projection andor interpolation schemes are required to avoid errors
bull The mesoscale variability error (which is lt35 cm for MP between 3 to 5 years and lt1cm for WLof 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a prioriknowledge from Sea Level maps derived from previous iterations or from other missions
bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
Page 28
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for Envisat since november 2010 and for Cryosat-2 mission (c2)because the satellite is not in a repetitive orbit phase The alternative is to use the MSS instead The griddedMSS is derived from along track MPs and data from geodetic phases Thus any error on the MP is alsocontained in the MSS There are essentially 4 types of additional errors on gridded MSS which are hard toquantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
Note that for the Arctic regional products the DTU10 MSS [1] is taken into account instead of the CLS01MSS Indeed the accuracy of DTU10 compared to CLS01 is further demonstrated by the significant sealevel anomaly variance reduction found over the whole Arctic Ocean as shown in Prandi et al [42]
III262 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III263 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
Page 29
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III27 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III271 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
Page 30
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III272 Performance indicators
To appreciate the quality situation of the DUACS system new performance indicators are computed dailyThey aim at evaluate the status of the main processing steps of the system the input data availability theinput data coverage the input data quality and the output product quality These indicators are computed foreach and every currently working satellite and combined to obtain the overall status
Figure 8 Example with the key performance indicator on 20090627
See the description the latest and previous indicators on Aviso websitehttpwwwavisooceanobscomindexphpid=1516
Page 31
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III3 Delayed Time processing steps
III31 Input data models and corrections applied
Delayed Time MyOcean products are generated
bull from Aviso GDR products for TP Jason-1 Jason-2 and Envisat (GDR-A cycles 1 to 22 GDR-Bcycles 23 to 85 GDR-C from cycle 86)
bull from NOAA GDR for GFO and from CERSAT (IFREMER) OPR for ERS-1 and ERS-2 (phases C(1st 35-day repeat orbit period) phase E and F (geodetic phases) phase G for ERS-1 (last 35-dayrepeat orbit period tandem phase with ERS-2 phase A for ERS-2 (1st 35-day repeat orbit periodtandem phase with ERS-1))
All GDR products are computed with a Precise Orbit Ephemeris (POE) and are delivered within 2 to 3months depending on the mission For several missions an updated orbit is used
bull For ERS-1amp-2 the orbit used is DGME-04 provided by Delft Institute (httpwwwdeostudelftnl)until June 2003
bull For TopexPoseidon the orbit used is GSFC (std0809) for the whole mission
bull For Envisat CNES POE of GDR-C standard is used for the whole mission
bull For the whole GFO mission the orbit used is GSFC (std0809) and when not available NASA POE isused
Altimetric product Source Availability Type of orbit
TopexPoseidon GDR NASACNES - GSFC POE
Jason-1 GDR (GDR-C) CNESNASA ~40 days CNES POE
Jason-2 GDR (GDR-C) CNESNASA ~60 days CNES POE
GFO GDR NOAA - GSFCNASA POE
ERS-1amp2 IFREMERESA - DGME-04
Envisat (GDR-A GDR-B andGDR-C from cycle 86)
ESA ~2 months CNES POE
Table 5 SSALTODUACS Delayed Time Input data overview
Page 32
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
DU
AC
S20
11D
Tpr
oduc
t(gtV
30
0)j2
j1j1
ntp
tpn
e1e2
ene
nng2
Prod
uct
stan
dard
ref
GD
R-C
OPR
GD
R-A
(Cyc
les
1to
22)
GD
R-B
(cyc
les
23-8
5)
GD
R(N
OA
A)
Orb
itC
nes
POE
GSF
C(I
TR
F20
05G
RA
CE
last
stan
dard
s)
DG
ME
-04
(Sch
arro
oan
dV
isse
r19
98[4
8]C
NE
SPO
E(G
DR
-1st
anda
rds
forc
ycle
s9
to22
GD
R-C
stan
dard
sfr
omcy
cle
23)
GSF
C(I
TR
F20
05
GR
AC
Ela
stst
anda
rds
Iono
pher
icD
ual f
requ
ency
altim
eter
rang
em
easu
rem
ents
Dua
l fre
quen
cyal
timet
erra
nge
mea
sure
men
ts(T
opex
)D
OR
IS(P
OSE
IDO
N)
Ben
t mod
elB
ent m
odel
(cyc
les
1-36
)G
IMm
odem
from
cycl
e37
((Ii
jima
etal
19
98[2
4])
Dua
l-fr
eque
ncy
altim
eter
rang
em
easu
rem
ent(
cycl
e9-
64)a
ndG
IMm
odel
gtcyc
le65
(Iiji
ma
etal
19
99[2
4])c
orre
cted
from
8m
mbi
as
From
GIM
mod
el(I
ijim
aet
al1
998
[24]
)
Dry
trop
o-sp
here
Mod
elco
mpu
ted
from
EC
MW
FG
auss
ian
grid
s(n
ewS1
and
S2at
mos
pher
ictid
esar
eap
plie
d)
Mod
elco
mpu
ted
from
EC
MW
Fre
ctan
gula
rgri
ds(n
ewS1
and
S2at
mos
pher
ictid
esar
ein
clud
ed)
Wet
trop
o-sp
here
JMR
AM
Rra
diom
eter
furt
hert
han
50km
from
the
coas
tsF
rom
EC
MW
Fm
odel
ford
ista
nces
betw
een
10an
d50
km
TM
Rra
diom
eter
(Sch
aroo
etal
20
04[4
9])
MW
RC
orre
ctio
nof
the
drif
ton
the
236
GH
zbr
ight
ness
tem
pera
ture
(Sch
arro
oet
al
2004
[49]
)Neu
ral
Net
wor
kal
gori
thm
(Tra
nan
dO
blig
is
2003
[50]
MW
Rra
diom
eter
furt
hert
han
50km
from
the
coas
tsan
dco
rrec
ted
from
side
lobe
s(f
rom
cycl
e41
)E
CM
WF
mod
elfo
rdis
tanc
esbe
twee
n10
and
50km
GFO
radi
omet
er
DA
CM
OG
2DH
igh
Res
olut
ion
forc
edw
ithE
CM
WF
pres
sure
and
win
gfie
lds
(S1
and
S2w
ere
excl
uded
)+in
vers
eba
rom
eter
com
pute
dfr
omre
ctan
gula
rgri
ds
Tabl
e6
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(1
2)
Page 33
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
j2j1
j1n
tptp
ne1
e2en
enn
g2O
cean
tide
GO
T4v
7(S
1an
dS2
are
incl
uded
)Po
letid
e[W
ahr
1985
[53]
]So
lidea
rth
tide
Ela
stic
resp
onse
totid
alpo
tent
ial[
Car
twri
ghta
ndTa
yler
197
1[5]
][C
artw
righ
tand
Edd
en1
973[
6]]
Loa
ding
tide
GO
T4v
7(S
1pa
ram
eter
isin
clud
ed)
Sea
stat
ebi
asN
onpa
ram
etri
cSS
B[G
aspa
reta
l20
02[2
0]]
Non
para
met
ric
SSB
[NT
ran
and
al2
010[
51]]
BM
3[G
aspa
ran
dO
gor
1994
[17]
]
Non
para
met
ric
SSB
[Mer
tzet
al
2005
[38]
]
Non
para
met
ric
SSB
[Gas
pare
tal
2002
]w
ithG
DR
-Bst
anda
rds
forc
ycle
s9
to85
and
with
GD
R-C
stan
dard
sfr
omcy
cle
86
Non
para
met
ric
SSB
[NT
ran
etal
20
10[5
1]]
Orb
iter
ror
Glo
bal m
ulti-
mis
sion
cros
sove
rmin
imiz
atio
n(L
eTr
aon
and
Ogo
r19
98[3
2])
Lon
gw
ave-
leng
her
rors
Opt
imal
Inte
rpol
atio
n(L
eTr
aon
etal
19
98[3
1])
Inte
rcal
ibra
tion
Ref
eren
cefr
omcy
cle
11R
efer
ence
from
cycl
e1
to35
4C
orre
ctio
nof
regi
onal
bias
J2J
1de
duce
dfr
omin
terc
alib
ratio
nph
ase
(cyc
le11
J2)
Cor
rect
ion
ofgl
obal
biai
sJ1
TP
deacutedu
ced
from
inte
rcal
ibra
tion
phas
e(c
ycle
s11
J1)
Mea
npr
o-fil
e(s
eeII
I36
1)
Com
pute
dw
ithcy
cles
11-3
53T
Pda
taan
dw
ithcy
cles
11-2
50J1
data
ref
eren
ced
[199
319
99]
TP
J1 c
ompu
ted
with
cycl
es11
-353
TP
data
and
with
cycl
es11
-250
J1da
tar
efer
ence
d[1
993
1999
]T
PNJ
1Nc
ompu
ted
with
cycl
es36
9-47
9T
PNda
tar
efer
ence
d[1
993
1999
]
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
ref
eren
ced
[199
319
99]
EN
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
re
fere
nced
[199
319
99]
EN
Nu
seof
MSS
_CN
ES_
CL
S11
[39]
Com
pute
dw
ithcy
cles
37-1
87G
2da
ta
refe
renc
ed[1
993
1999
]
Peri
odof
use
from
cycl
e9
from
cycl
e9
cycl
es1
to48
1cy
cles
15to
43In
clud
ing
E-F
geod
etic
phas
es
cycl
es1
to83
from
cycl
e9
cycl
es37
to22
2
Tabl
e7
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(2
2)
Page 34
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III32 Acquisition
The acqusition process in Delayed time is much simpler than in Near Real time it consists in a synchronisa-tion process of all the auxiliary data required to homogenize propely the altimeter data sets The acquisitionstep uses the GDRs or the OPRs provided by the agencies
III33 Homogenization
The Homogenization process consists in applying the most recent corrections models and references rec-ommended for altimeter products Each mission is processed separately as its needs depend on the baseinput data The list of corrections and models currently applied is provided in tables 6 and 7 for DT data
III34 Input data quality control
The Input Data Quality Control is a critical process applied to guarantee that DUACS uses only the mostaccurate altimeter data Thanks to the high quality of current missions this process rejects a small percent-age of altimeter measurements but these erroneous data could be the cause of a significant quality lossThe quality control relies on standard raw data editing with quality flags or parameter thresholds but alsoon complex data editing algorithms based on the detection of erroneous artefacts mono and multi-missioncrossover validation and macroscopic statistics to edit out large data flows that do not meet the systemrsquosrequirements
Page 35
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III35 Multi-mission cross-calibration
The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistentand accurate information It removes any residual orbit error (OE Le Traon and Ogor 1998[32]) or longwavelength error (LWE Le Traon et al 1998[31]) as well as large scale biases and discrepancies betweenvarious data flows
This process is based on two very different algorithms a global multi-mission crossover minimization fororbit error reduction (OER) and Optimal Interpolation (OI) for LWE
Multi-satellite crossover determination is performed on a daily basis All altimeter fields (measurementcorrections and other fields such as bathymetry MSS) are interpolated at crossover locations and datesCrossovers are then appended to the existing crossover database as more altimeter data become availableThis crossover data set is the input of the Orbit Error Reduction (OER) method Using the precision of thereference mission orbit a very accurate orbit error can be estimated LWE is mostly due to residual tidalor inverse barometer errors and high frequency ocean signals The OI used for LWE reduction uses preciseparameters derived from
bull accurate statistical description of sea level variability
bull localized correlation scales
bull mission-specific noise and precise assumptions on the long wavelength errors to be removed (from arecent analysis of one year of data from each mission)
Page 36
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III36 Product generation
The product generation process is composed of four steps computation of raw SLA cross-validationfilteringampsub-sampling and generation of by-products
III361 Computation of raw SLA
Since the geoid is not well known yet the SSH cannot be used directly the SSH anomalies are used insteadThey are computed from the difference of the instantaneous SSH - a temporal reference This temporalreference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeattrack analysis cannot be used The errors affecting the SLAs MPs and MSS have different magnitudes andwavelengths The computation of the SLAs and their errors associated are detailed in Dibarboure et al 2010[9]
Use of a Mean ProfileIn the repeat track analysis (when the satellites flies over a repetitive orbit) measurements are re-sampledalong a theoretical ground track (or mean track) associated to each mission Then a Mean Profile (MP) issubtracted from the re-sampled data to obtain SLA The MP is a time average of similarly re-sampled dataover a long period
bull The Mean Profile used for TP (cycles 1 to 364) Jason-1 (cycles 1 to 259) and Jason-2 is computedwith 10 years of TP (cycles 11 to 353) and 6 years of Jason-1 (cycles 11 to 250)
bull The Mean Profile used for TP (cycles 368 to 481) and from Jason-1 cycle 262 to 374 (where satellitesare on interleaved ground-tracks) is computed with 3 years of TP (cycles 369 to 479)
bull The Mean Profile used for ERS-1 in its 35 days repetitive orbit mission ERS-2 and Envisat (only forthe first orbit before November 2010) is computed with 8 years of ERS-2 (cycles 1 to 85) and 6 yearsof Envisat (cycles 10 to 72)
bull No Mean Profile can be used for Envisat on its new orbit (enn) Jason-1 on its geodetic orbit (j1g)because there is no repetitive track The MSS must be used instead (see below)
bull The Mean Profile used for GFO is computed with 7 years of GFO cycles 37 to 187
Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible
bull Indeed as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide precise cross-track projection andor interpolation schemes are required to avoid errors
bull The mesoscale variability error (which is lt35 cm for MP between 3 to 5 years and lt1cm for WLof 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a prioriknowledge from Sea Level maps derived from previous iterations or from other missions
Page 37
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for ERS-1 for its 168 days geodetic mission (phases E-F from April1994 to March 1995) or for Envisat since november 2010 because the satellite is not in a repetitive orbitphase The alternative is to use the MSS instead The gridded MSS is derived from along track MPs anddata from geodetic phases Thus any error on the MP is also contained in the MSS There are essentially 4types of additional errors on gridded MSS which are hard to quantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
III362 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III363 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
Page 38
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III37 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III371 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
Page 39
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
IV MYOCEAN PRODUCTS
IV1 Near Real Time Products
The purpose of the NRT DUACS component is the acquisition of altimeter data from various altimeter mis-sions in near-real time (ie within a few days at most) the validation and correction of these altimeter datasets (ie edition and selection update of corrections and homogenization orbit error reduction) in order toproduce each day along-track productsProducts are as follows
Along-track products global and regional (Mediterranean and Black Seas Arctic Ocean and Europeareas)
bull Sea Level Anomaly (NRT-SLA) for each mission with NRT-SLA ephemeris
IV11 Delay of the products
The availability of the products in near real time is three to twelve hours after the measurement for along-track products Those products are delivered every day
IV12 Temporal availibility
The following table presents the available products by mission and by data periodNear real time products
NRT Jason-2 Jason-1 and Jason-1geodetic
Envisat new Cryosat-2
Temporal Time availability ymlowast
ongoingymlowast-20120303 for
repeat track and20120507-ongoing for
geodetic track
ymlowast
2012040820120101
ongoing
NRT-SLA X X X X
lowastym the temporal coverage for NRT products is fluctuating and depends on updates of Delayed Time prod-ucts When DT products are updated (3 to 4 times per year) the oldest NRT products are replaced by thebetter quality DT products so that the 2 series are overlapping on few weeks or few months
IV2 Delayed Time Products
The Delayed Time component of SSALTODUACS system is responsible for the production of processedJason-1 Jason-2 TP Envisat GFO ERS12 and even Geosat data in order to provide a homogeneousinter-calibrated and highly accurate long time series of SLA DT products are more precise than NRT products Two reasons explain this quality difference The firstone is the better intrinsic quality of the POE orbit used in the GDR processing The second reason is that
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in the DT DUACS processing the products can be computed optimally with a centred computation timewindow for OER LWE On the contrary in NRT case future data are not available so the computationtime window is not centred and therefore not optimalAs for NRT products improved altimeter corrections and processing algorithms are used ocean tide modelto correct altimeter data improved methods for orbit error reduction and mapping
Along-Track products global and regional (Mediterranean and Black Seas)
bull Sea Level Anomaly (DT-SLA) for each mission
IV21 Delay of the products
Weekly products are delivered The availability of the products in delayed time is at the best two monthsafter the date of the measurement The product generation needs all the GDR data of all the missions to takeinto account the best corrections as possible The time delay can be longer in the case of a missing mission
IV22 Temporal availibility
The following table presents the available products by mission and by data periodDelayed time SSALTODUACS products
Upd Jason-2 Jason-1new6
Jason-1 GFO Envisatnew6
Envisat ERS-16
ERS-2Topexnew6
Topex
TemporalTimeavailabil-ity
200810ymlowast
200902ymlowast
200204200810
200001200809
201010ymlowast
200210201010
199210200304
200209200510
199209200204
DT-SLA X X X X X X X X X
lowast ym those dates are updated regularly (3 to 4 times per year) and are avalaible when you download thedata at httpwwwmyoceaneuweb24-cataloguephp6 Jason-1 new orbit starting 200809 Envisat new orbit starting 201010 TP new orbit starting 200209 ERS-1The geodetic phases (E-F) are included There are no ERS-1 data between December 23 1993 and April 10 1994(ERS-1 phase D - 2nd ice phase) Note that during that time products are based only on TopexPoseidon data
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V DESCRIPTION OF THE PRODUCT SPECIFICATION
V1 General information
Product Specification SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001
Geographical coverage global
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 20-50km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001 Product Specification
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Product Specification SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002
Geographical coverage 55˚W-35˚E 30˚N-46˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002 Product Specification
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Product Specification SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003
Geographical coverage 27˚E-42˚E 40˚N-47˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003 Product Specification
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Product Specification SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004
Geographical coverage 25˚W-42˚E 21˚N-66˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004 Product Specification
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Product Specification SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005
Geographical coverage 0˚W-360˚E 50˚N-82˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005 Product Specification
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VI NOMENCLATURE OF FILES
VI1 Nomenclature of files downloaded through the MyOcean Web PortalDirectgetfile Service
VI11 Nomenclature of the product line
The description of the syntax for the SL TAC SLA products line is given by
SEALEVEL_ltREGIONgt_SLA_L3_ltDELAYgt_OBSERVATIONS_008_ltZONEgt_ltLETTERgtwhere
REGION GLO global geographic coverage product
BS Black Sea products
MED Mediterranean products
ARC Arctic products (for NRT products)
EUROPE Europe products (for NRT products)
DELAY NRT near real time products
RAN delayed time or reanalysis products
ZONE 001 number on 3 digits
002
003
004
LETTER a letter on 1 digit
b
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VI12 Nomenclature of the datasets
The nomenclature used is
dataset-duacs-ltdelaygt-ltzonegt-ltmissiongt-lttype of slagt-l3where the fileds in ltgt are described below
delay nrt near-real time productsran delayed time products
zone global global geographic coverage productmedsea Mediterranean productsblacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1 (only for ran)e2 ERS-2 (only for ran)tp TOPEXPoseidon (only for ran)tpn TOPEXPoseidon on its new orbit (only for
ran)g2 GFO (only for ran)j1 Jason-1 (only for ran)j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisat (only for ran)enn Envisat on its new orbitc2 Cryosat-2 (only for nrt)
type of sla sla filtered slasla_unfiltered non filtered sla (only for ran products)
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VI13 Nomenclature of the NetCdf files
The nomenclature used is
ltdelaygt_ltzonegt_ltmissiongt_sla_ltvariablegt_ltdatebegingt_ltdateendgt_ltdateprodgtnc where the fileds in ltgt are de-scribed below
delay nrt near-real time productsdt delayed time products
zone global global geographic coverage productmed Mediterranean products (for dt)mfstep Mediterranean products (for nrt)blacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1e2 ERS-2tp TOPEXPoseidontpn TOPEXPoseidon on its new orbitg2 GFOj1 Jason-1j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisatenn Envisat on its new orbitc2 Cryosat-2
variable vfec filtered and sub-sampled slavxxc non filtered and non sub-sampled sla (only
for dt)datebegin YYYYMMDD() beginning date of the datasetdateend YYYYMMDD() end date of the datasetdateprod YYYYMMDD production date of the dataset
() For dt data as the dates in the file names are rounded the user wanting data for date T has to read the filescontaining dates T+1 and T-1 in their name and check inside the files if there are some data for date T
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VII DATA FORMAT
This chapter presents the data storage format used for MyOcean products
VII1 NetCdf
The products are stored using the NetCDF format NetCDF (network Common Data Form) is an interface for array-oriented data access and a library that provides an implementation of the interface The netCDF library also definesa machine-independent format for representing scientific data Together the interface library and format support thecreation access and sharing of scientific data The netCDF software was developed at the Unidata Program Center inBoulder Colorado The netCDF libraries define a machine-independent format for representing scientific data Pleasesee Unidata NetCDF pages for more information and to retreive NetCDF software package onhttpwwwunidataucaredupackagesnetcdfindexhtml
NetCDF data is
bull Self-Describing A netCDF file includes information about the data it contains
bull Architecture-independent A netCDF file is represented in a form that can be accessed by computers with dif-ferent ways of storing integers characters and floating-point numbers
bull Direct-access A small subset of a large dataset may be accessed efficiently without first reading through allthe preceding data
bull Appendable Data can be appended to a netCDF dataset along one dimension without copying the dataset orredefining its structure The structure of a netCDF dataset can be changed though this sometimes causes thedataset to be copied
bull Sharable One writer and multiple readers may simultaneously access the same netCDF file
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VII2 Structure and semantic of NetCDF along-track files
The NetCDF Sea Level TAC files are based on the attribute data tags defined by the Cooperative OceanAtmosphereResearch Data Service (COARDS) and Climate and Forecast (CF) metadata conventions The CF convention gener-alises and extends the COARDS convention but relaxes the COARDS constraints on dimension and order and specifiesmethods for reducing the size of datasetsA wide range of software are available to write or read NetCDFCF files API are made available by UNIDATA(httpwwwunidataucaredusoftwarenetcdf)
bull CC++Fortran
bull Java
bull MATLAB Objective-C Perl Python R Ruby TclTk
In addition to these conventions the files are using a common structure and semantic
bull 1 dimension is defined
ndash time it is used to check NetCDF variables depending on time
bull 8 variables are defined
ndash short SLA contains the Sea Level Anomaly values for each time given
ndash int longitude contains the longitude for each measurement
ndash short track contains the track number for each measurement
ndash double time contains the time in days since 1950-01-01 000000 UTC for each measurement
ndash short mean_profile_point_index index of the corrsponding point in the track of the mean profile
ndash byte flag flag=0 the processed data comes from OGDR if flag=1 the processed data comes from theIGDR
ndash int latitude contains the latitude for each measurement
ndash short cycle contains the cycle number for each measurement
bull global attributes
ndash the global attributes gives information about the creation of the file
Example of a NetCDF sla file
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netcdf nrt_global_j1_sla_vfec_20101230_20101230_20101230 dimensions
time = 10385 variables
short SLA(time) SLAcoordinates = longitude latitude SLAlong_name = Sea Level Anomaly SLA_FillValue = 32767s SLAadd_offset = 0 SLAscale_factor = 0001 SLAunits = m SLAstandard_name = sea_surface_height_above_sea_level
int longitude(time) longitudelong_name = Longitude of measurement longitude_FillValue = 2147483647 longitudeadd_offset = 0 longitudestandard_name = longitude longitudescale_factor = 1e-06 longitudeunits = degrees_east
short track(time) tracklong_name = Track in cycle the measurement belongs to track_FillValue = 32767s trackunits = 1 trackcoordinates = longitude latitude
double time(time) timelong_name = Time of measurement time_FillValue = 184467440737096e+19 timeaxis = T timestandard_name = time timeunits = days since 1950-01-01 000000 UTC
int latitude(time) latitudelong_name = Latitude of measurement latitude_FillValue = 2147483647 latitudeadd_offset = 0 latitudestandard_name = latitude latitudescale_factor = 1e-06 latitudeunits = degrees_north
short flag(time) flagcoordinates = longitude latitude flag_FillValue = 3267s flaglong_name = data origin flagflag_values = 1s 0s flagflag_meanings = igdr_like non_igdr_like flagcomment = The origin of the data is determined by the types of geophysical datarecords (GDR) used in computation of the SLA 1 for the Interim GDR (IGDR) and0 for Operational GDR (OGDR)
short cycle(time) cyclelong_name = Cycle the measurement belongs to cycle_FillValue = 32767s cycleunits = 1 cyclecoordinates = longitude latitude
global attributeshistory = 22-Feb-2011 155243 CET File created by the SSLATODUACS system version 1001 comment = Produce from ENVISAT Extension Phase satellite altimetry data institution = CLSCNES
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references = httpwwwavisooceanobscomfileadmindocumentsdatatoolshdbk_duacspdf source = satellite altimetry title = along track Sea Level Anomaly Conventions = CF-14
dataSLA =
7 7 11 10 -2 -22 -39 -41 -30 -13 -3 -5 -16 -26 -32 -35-35 -35 -37 -35 -31 -29 -31 -35 -32 -21 -10 -10 -19 -20 -1-69 -57 -49 -45 -39 -30 -28 -31 -27 -13 -2 -5 -15 -3 1112 3 -7 -10 -14 -15 -22 -31 -37 -32 -17 -10
longitude =74743328 74868400 74993968 75120040 75246616 7537372875501368 75629568 75758320 75887656 76017568 76148080 7627920876388952 76477056 76565456 76654144 76743128 76832400 76921984329429568 329535424 329641792 329748672 329856096 329964032330072512 330181536 330291072 330401184
track =92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 9292 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92113 113 113 113 113 113 113 113 113 113 113 113 113 113113 113 113 113 113 113 113 113 113
time =222780000565705 222780001314719 222780002063733222780002812747 222780003561761 222780004310775 222780005059788222780005808802 222780006557816 22278000730683 222780008055844222780008804858 222780009553872 22278001017805 222780010677393222788257112198 222788257486705 222788257861212 222788258235719222788258610226 222788258984733 222788259359239 222788259733746222788260108253 22278826048276
mean_profile_point_index =1872 1878 1884 1890 1896 1902 1908 19141920 1926 1932 1938 1944 1949 1953 1957 1961 1965 1969 19732306 2309 2312 2315 2318 2321 2327 2330 2333 2336 2339 23422345 2348 2351 2354 2357 2360 2363 2366
flag =0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
latitude =-16225506 -16539731 -16853833 -17167810 -17481660 -17795380-18108966 -18422418 -18735729 -19048899 -19361924 -19674801-19987527 -20248015 -20456329 -20664569 -20872739 -2108083739481297 39628277 39775133 39921866 40068472 40214953 4036130840507533 40653629 40799592 40945423 41091120 41236684 41382111
cycle =331 331 331 331 331 331 331 331 331 331 331 331 331
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331 331 331 331 331 331 331 331 331 331 331 331 331 331331 331 331 331 331 331 331 331 331 331 331 331
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VIII HOW TO DOWNLOAD A PRODUCT
VIII1 Download a product through the MyOcean Web Portal DirectgetfileService
You first need to register Please find below the registration stepshttpwwwmyoceaneuweb34-products-and-services-faqphp1Once registered the MyOcean FAQ httpwwwmyoceaneuweb34-products-and-services-faqwill guide you on How to download a product through the MyOcean Web Portal Directgetfile Service
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IX NEWS AND UPDATES
IX1 [Duacs] Operational news
To be kept informed on events occurring on the satellites and on the eventual interruption of the services of the DUACSprocessing system see the [Duacs] operational news on the Aviso websitehttpwwwavisooceanobscomendataoperational-newsindexhtml
IX2 Updates
To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtmlSince 2010 a complete reprocessing of all altimetry data (cumulated total of about 55 years of data) is available Themain changes introduced in the Duacs DT v300 reprocessed data set in SSALTODUACS reprocessed DT data setare listed herehttpwwwavisooceanobscomfileadmindocumentsdataduacsduacs_DT_2010_reprocessing_impactpdf
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bull The Arctic along-track products (PL SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005) coverlatitudes between 45 and 82 degrees (figure 4) They are available in Near Real Time only
Figure 4 Coverage of the Arctic region with Envisat from October 28th 2011 to January 3rd 2012
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III SSALTODUACS SYSTEM
III1 Introduction
This chapter presents the input data used by SSALTODUACS system and an overview of the different pro-cessing steps necessary to produce the output dataSSALTODUACS system is made of two components a Near Real Time one (NRT) and a Delayed Time(DT) oneIn NRT the systemrsquos primary objective is to provide operational applications with directly usable high qual-ity altimeter data from all missions availableIn DT it is to maintain a consistent and user-friendly altimeter database using the state-of-the-art recom-mendations from the altimetry communityFollowing figure gives an overview of DUACS system where processing sequences can be divided into 7main steps
bull acquisition
bull homogenization
bull input data quality control
bull multi-mission cross-calibration
bull product generation
bull merging
bull final quality control
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Figure 5 SSALTODUACS processing sequences
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III2 Near Real Time processing steps
III21 Input data models and corrections applied
To produce SLA in near-real time the DUACS system uses two flows based on the same instrumental mea-surements but with a different quality
bull The IGDR that are the latest high-quality altimeter data produced in near-real-time
bull The OGDR that includes real time data (OSTMJason-2 and Jason-1 OSDR) to complete IGDR Thesefast delivery products do not always benefit from precise orbit determination nor from some exter-nal model-based corrections (Dynamic Atmospheric Correction (DAC) Global Ionospheric Maps(GIM))
Integration of OGDR data and the introduction of Jason-2Jason-1 tandem increased the resilience and pre-cision of the system A better restitution of ocean variability is observed especially in high energetic areas
Altimetric product Source Availability Type of orbit
Jason-2 IGDR CNES ~24h CNES MOE GDR-Cuntil 20120730
CNES MOE GDR-Dsince 20120731
OGDR NOAAEUMETSAT ~3 to 5 h
Jason-1 IGDR CNESNASA ~48 h CNES MOE GDR-Dsince 20120507
OGDR CNESNASA ~3 to 12 h
Envisat IGDR ESACNES not deliveredsince 20120408
CNES MOE GDR-Dsince 20120121
FDGDR ESA not deliveredsince 20120408
Cryosat-2 IGDR-like ESACNES ~48 h CNES MOE GDR-D
not delivered
Table 2 SSALTODUACS Near-Real Time Input data overview
See Figure 6 Overview of the near real time system data flow management
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DUACS 2011 NRT product from IGDR1
j2 j1nj1g enn c2Productstandard ref
version C until20120730 and D after
version C version 21 CPP [2]
Orbit CNES MOE GDR-Cuntil 20120730
GDR-D after
CNES MOE GDR-C forj1n and CNES MOE
GDR-D for j1g
CNES MOE GDR-Dfrom 20120121 to
20120408
CNES MOE GDR-D
Ionopheric bi-frequency altimeter range measurements GIM model for cgt64 (Iijima et al1998[24])Dry tropo Model computed from ECMWF Gaussian grids (new S1 and S2 atm tides applied)Wet tropo-sphere
AMR radiometer(enhancement in coastal
regions since20120730)
JMR radiometer MWR radiometer andcorrected from side
lobes
Model computed fromECMWF Gaussian
grids
DAC MOG2D High Resolution forced with ECMWF pressure and wind fields (S1 and S2 wereexcluded) (Carrere and Lyard 2003[3])+ inverse barometer Filtering temporal window is
un-centered (no data in the future)Ocean tide GOT4v8 (S1 and S2 are included) and TPX 072 [16] for Arctic productsPole tide [Wahr 1985 [53]]Solid earthtide
Elastic response to tidal potential [Cartwright and Tayler 1971[5]] [Cartwright andEdden 1973[6]]
Loading tide GOT4v8 (S1 and S2 are included)Sea statebias
Non parametric SSB[Labroue 2004[27]](with cycles J1 1 to 11
using GDR-B standardsuntil 20120730 andderived from Jason-2
after)
Non parametric SSB[Labroue 2004[27]](with cycles 1 to 21
using GDR-Bstandards)
Non parametric SSB[Labroue 2004[27]](with cycles 41 to 60
using GDR-Bstandards)
Same as Jason-2 SSB
Orbit error Global multi-mission crossover minimization (Le Traon and Ogor1998[32])
Long wave-lengh errors
Optimal Interpolation [Le Traon et al 1998[31]]
Intercalibration Reference from cycle20
Mean pro-file (seeIII261)
Computed with cycles11-353 TP data andwith cycles 11-250J1 data referenced[19931999]
TPNJ1N computedwith cycles 369-479TPN data refer-enced [19931999]J1G No MP can beused instead theMSS_CNES_CLS11[39] is used
No Mean Profilecan be used forEnvisat on its neworbit Instead theMSS_CNES_CLS11[39] is used
No Mean Profilecan be used forCryosat-2 Instead theMSS_CNES_CLS11[39] is used
(1) A flag included in the along-track files indicates the source of the production (OGDRFDGDR orIGDR) If flag=0 the processed data comes from OGDRsFDGDRs if flag=1 the processed data comesfrom IGDRs
Table 3 Corrections and models applied in SSALTODUACS NRT products produced from IGDRs
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DUACS 2011 NRT product from OGDR or FDGDR2
j2 j1nj1g ennProduct stan-dard ref
version C until 20120730and D after
version C version 21
Orbit Navigator Extrapolated CNES MOEGDR-D since 20120121
Ionopheric From-dual frequency altimeter range measurements From GIM model fromcycle 65 (Iijima et al1998 [24])
Dry troposphere Model computed from ECMWF Gaussian grids (new S1 and S2 atmospherictides are applied)
Wet tropo-sphere
AMR radiometer(enhancement in coastal
regions since 20120730)
JMR radiometer MWR radiometer andcorrected from side lobes
DAC Inverse Barometer forecastedOcean tide GOT4v8 (S1 and S2 are included) and TPX 072 [16] for Arctic productsPole tide [Wahr 1985 [53]]Solid earth tide Elastic response to tidal potential [Cartwright and Tayler 1971[5]]
[Cartwright and Edden 1973[6]]Loading tide GOT4v8 (S1 and S2 are included)Sea state bias Non parametric SSB
[Labroue 2004[27]] (withcycles J1 1 to 11 usingGDR-B standards until20120730 and derivedfrom Jason-2 after)
Non parametric SSB[Labroue 2004[27]](with cycles 1 to 21 usingGDR-B standards)
Non parametric SSB[Labroue 2004[27]](with cycles 41 to 60using GDR-B standards)
Orbit error Specific filtering of long-wavelength signal3
Long wave-lengh errors
Optimal Interpolation [Le Traon et al 1998[31]]
Intercalibration Reference from cycle 20Mean profile(see III261)
Computed with cycles 11-353 TP data and with cy-cles 11-250 J1 data refer-enced [19931999]
TPNJ1N computedwith cycles 369-479TPN data referenced[19931999] J1G NoMP can be used insteadthe MSS_CNES_CLS11[39] is used
No Mean Profile can beused for Envisat on itsnew orbit Instead theMSS_CNES_CLS11 [39]is used
(2) A flag included in the along-track files indicates the source of the production (OGDRFDGDR orIGDR) If flag=0 the processed data comes from OGDRsFDGDRs if flag=1 the processed data comesfrom IGDRs(3) Specific data processing was applied on long wave-length signal (sectIII23 of the user manual)
Table 4 Corrections and models applied in SSALTODUACS NRT products produced from OG-DRsFDGDRs
Page 24
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III22 Acquisition
The acquisition process is twofold
bull straightforward retrieval and reformatting of altimeter data and dynamic auxiliary data (pressure andwet troposphere correction grids from ECMWF are provided by Meteo France TEC grids from JPLNRT MOG2D corrections) from external repositories
bull synchronisation process
To be homogenized properly altimeter data sets require various auxiliary data The acquisition softwaredetects downloads and processes incoming data as soon as they are available on remote sites (externaldatabase FTP site) Data are split into passes if necessary If data flows are missing or late the synchroni-sation engine put unusable data in waiting queues and automatically unfreezes them upon reception of themissing auxiliary data This processing step delivers raw data that is to say data that have been dividedinto cycles and passes and ordered chronologicallyFrom SSALTODUACS V80 the acquisition step uses two different data flows in near-real time the OGDRflow (within a few hours) and the IGDR flow (within a few days)For each OGDR input the system checks that no equivalent IGDR entry is available in the data base beforeacquisition for each IGDR input the system checks and delete the equivalent OGDR entry in the data baseThese operations aim to avoid duplicates in SSALTODUACS system
Figure 6 Overview of the near real time system data flow management
Page 25
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III23 Homogenization
The Homogenization process consists in applying the most recent corrections models and references rec-ommended for altimeter products Each mission is processed separately as its needs depend on the baseinput data The list of corrections and models currently applied is provided in tables 3 and 4 for NRT dataThe system includes SLA filtering to process OGDR data DUACS extract from these data sets the shortscales (space and time) which are useful to better describe the ocean variability in real time and merge thisinformation with a fair description of large scale signals provided by the multi-satellite observation in nearreal time (read IGDR-based DUACS data) Finally an hybrid SLA is computed
Figure 7 Merging pertinent information from IGDR and OGDR processing
III24 Input data quality control
The Input Data Quality Control is a critical process applied to guarantee that DUACS uses only the mostaccurate altimeter data Thanks to the high quality of current missions this process rejects a small percent-age of altimeter measurements but these erroneous data could be the cause of a significant quality lossThe quality control relies on standard raw data editing with quality flags or parameter thresholds but alsoon complex data editing algorithms based on the detection of erroneous artefacts mono and multi-missioncrossover validation and macroscopic statistics to edit out large data flows that do not meet the systemrsquosrequirements
Page 26
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III25 Multi-mission cross-calibration
The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistentand accurate information It removes any residual orbit error (OE Le Traon and Ogor 1998[32]) or longwavelength error (LWE Le Traon et al 1998[31]) as well as large scale biases and discrepancies betweenvarious data flows
This process is based on two very different algorithms a global multi-mission crossover minimization fororbit error reduction (OER) and Optimal Interpolation (OI) for LWE
Multi-satellite crossover determination is performed on a daily basis All altimeter fields (measurementcorrections and other fields such as bathymetry MSS) are interpolated at crossover locations and datesCrossovers are then appended to the existing crossover database as more altimeter data become availableThis crossover data set is the input of the Orbit Error Reduction (OER) method Using the precision of thereference mission orbit a very accurate orbit error can be estimated This processing step does not concernOGDR dataLWE is mostly due to residual tidal or inverse barometer errors and high frequency ocean signals The OIused for LWE reduction uses precise parameters derived from
bull accurate statistical description of sea level variability
bull localized correlation scales
bull mission-specific noise and precise assumptions on the long wavelength errors to be removed (from arecent analysis of one year of data from each mission)
Page 27
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III26 Product generation
The product generation process is composed of four steps computation of raw SLA cross-validationfilteringampsub-sampling and generation of by-products
III261 Computation of raw SLA
Since the geoid is not well known yet the SSH cannot be used directly the SSH anomalies are used insteadThey are computed from the difference of the instantaneous SSH - a temporal reference This temporalreference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeattrack analysis cannot be used The errors affecting the SLAs MPs and MSS have different magnitudes andwavelengths The computation of the SLAs and their errors associated are detailed in Dibarboure et al 2010[9]
Use of a Mean ProfileIn the repeat track analysis (when the satellites flies over a repetitive orbit) measurements are re-sampledalong a theoretical ground track (or mean track) associated to each mission Then a Mean Profile (MP) issubtracted from the re-sampled data to obtain SLA The MP is a time average of similarly re-sampled dataover a long period
bull The Mean Profile used for Jason-2 is computed with 10 years of TP (cycles 11 to 353) and 6 years ofJason-1 (cycles 11 to 250)
bull The Mean Profile used from Jason-1 cycle 262 to 374 (where satellites are on interleaved ground-tracks) is computed with 3 years of TP (cycles 369 to 479)
bull No Mean Profile can be used for Envisat on its new orbit (enn) Jason-1 on its geodetic orbit (j1g) norfor Cryosat-2 mission (c2) because there is no repetitive track The MSS must be used instead (seebelow)
Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible
bull Indeed as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide precise cross-track projection andor interpolation schemes are required to avoid errors
bull The mesoscale variability error (which is lt35 cm for MP between 3 to 5 years and lt1cm for WLof 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a prioriknowledge from Sea Level maps derived from previous iterations or from other missions
bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
Page 28
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for Envisat since november 2010 and for Cryosat-2 mission (c2)because the satellite is not in a repetitive orbit phase The alternative is to use the MSS instead The griddedMSS is derived from along track MPs and data from geodetic phases Thus any error on the MP is alsocontained in the MSS There are essentially 4 types of additional errors on gridded MSS which are hard toquantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
Note that for the Arctic regional products the DTU10 MSS [1] is taken into account instead of the CLS01MSS Indeed the accuracy of DTU10 compared to CLS01 is further demonstrated by the significant sealevel anomaly variance reduction found over the whole Arctic Ocean as shown in Prandi et al [42]
III262 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III263 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
Page 29
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III27 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III271 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
Page 30
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III272 Performance indicators
To appreciate the quality situation of the DUACS system new performance indicators are computed dailyThey aim at evaluate the status of the main processing steps of the system the input data availability theinput data coverage the input data quality and the output product quality These indicators are computed foreach and every currently working satellite and combined to obtain the overall status
Figure 8 Example with the key performance indicator on 20090627
See the description the latest and previous indicators on Aviso websitehttpwwwavisooceanobscomindexphpid=1516
Page 31
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III3 Delayed Time processing steps
III31 Input data models and corrections applied
Delayed Time MyOcean products are generated
bull from Aviso GDR products for TP Jason-1 Jason-2 and Envisat (GDR-A cycles 1 to 22 GDR-Bcycles 23 to 85 GDR-C from cycle 86)
bull from NOAA GDR for GFO and from CERSAT (IFREMER) OPR for ERS-1 and ERS-2 (phases C(1st 35-day repeat orbit period) phase E and F (geodetic phases) phase G for ERS-1 (last 35-dayrepeat orbit period tandem phase with ERS-2 phase A for ERS-2 (1st 35-day repeat orbit periodtandem phase with ERS-1))
All GDR products are computed with a Precise Orbit Ephemeris (POE) and are delivered within 2 to 3months depending on the mission For several missions an updated orbit is used
bull For ERS-1amp-2 the orbit used is DGME-04 provided by Delft Institute (httpwwwdeostudelftnl)until June 2003
bull For TopexPoseidon the orbit used is GSFC (std0809) for the whole mission
bull For Envisat CNES POE of GDR-C standard is used for the whole mission
bull For the whole GFO mission the orbit used is GSFC (std0809) and when not available NASA POE isused
Altimetric product Source Availability Type of orbit
TopexPoseidon GDR NASACNES - GSFC POE
Jason-1 GDR (GDR-C) CNESNASA ~40 days CNES POE
Jason-2 GDR (GDR-C) CNESNASA ~60 days CNES POE
GFO GDR NOAA - GSFCNASA POE
ERS-1amp2 IFREMERESA - DGME-04
Envisat (GDR-A GDR-B andGDR-C from cycle 86)
ESA ~2 months CNES POE
Table 5 SSALTODUACS Delayed Time Input data overview
Page 32
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
DU
AC
S20
11D
Tpr
oduc
t(gtV
30
0)j2
j1j1
ntp
tpn
e1e2
ene
nng2
Prod
uct
stan
dard
ref
GD
R-C
OPR
GD
R-A
(Cyc
les
1to
22)
GD
R-B
(cyc
les
23-8
5)
GD
R(N
OA
A)
Orb
itC
nes
POE
GSF
C(I
TR
F20
05G
RA
CE
last
stan
dard
s)
DG
ME
-04
(Sch
arro
oan
dV
isse
r19
98[4
8]C
NE
SPO
E(G
DR
-1st
anda
rds
forc
ycle
s9
to22
GD
R-C
stan
dard
sfr
omcy
cle
23)
GSF
C(I
TR
F20
05
GR
AC
Ela
stst
anda
rds
Iono
pher
icD
ual f
requ
ency
altim
eter
rang
em
easu
rem
ents
Dua
l fre
quen
cyal
timet
erra
nge
mea
sure
men
ts(T
opex
)D
OR
IS(P
OSE
IDO
N)
Ben
t mod
elB
ent m
odel
(cyc
les
1-36
)G
IMm
odem
from
cycl
e37
((Ii
jima
etal
19
98[2
4])
Dua
l-fr
eque
ncy
altim
eter
rang
em
easu
rem
ent(
cycl
e9-
64)a
ndG
IMm
odel
gtcyc
le65
(Iiji
ma
etal
19
99[2
4])c
orre
cted
from
8m
mbi
as
From
GIM
mod
el(I
ijim
aet
al1
998
[24]
)
Dry
trop
o-sp
here
Mod
elco
mpu
ted
from
EC
MW
FG
auss
ian
grid
s(n
ewS1
and
S2at
mos
pher
ictid
esar
eap
plie
d)
Mod
elco
mpu
ted
from
EC
MW
Fre
ctan
gula
rgri
ds(n
ewS1
and
S2at
mos
pher
ictid
esar
ein
clud
ed)
Wet
trop
o-sp
here
JMR
AM
Rra
diom
eter
furt
hert
han
50km
from
the
coas
tsF
rom
EC
MW
Fm
odel
ford
ista
nces
betw
een
10an
d50
km
TM
Rra
diom
eter
(Sch
aroo
etal
20
04[4
9])
MW
RC
orre
ctio
nof
the
drif
ton
the
236
GH
zbr
ight
ness
tem
pera
ture
(Sch
arro
oet
al
2004
[49]
)Neu
ral
Net
wor
kal
gori
thm
(Tra
nan
dO
blig
is
2003
[50]
MW
Rra
diom
eter
furt
hert
han
50km
from
the
coas
tsan
dco
rrec
ted
from
side
lobe
s(f
rom
cycl
e41
)E
CM
WF
mod
elfo
rdis
tanc
esbe
twee
n10
and
50km
GFO
radi
omet
er
DA
CM
OG
2DH
igh
Res
olut
ion
forc
edw
ithE
CM
WF
pres
sure
and
win
gfie
lds
(S1
and
S2w
ere
excl
uded
)+in
vers
eba
rom
eter
com
pute
dfr
omre
ctan
gula
rgri
ds
Tabl
e6
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(1
2)
Page 33
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
j2j1
j1n
tptp
ne1
e2en
enn
g2O
cean
tide
GO
T4v
7(S
1an
dS2
are
incl
uded
)Po
letid
e[W
ahr
1985
[53]
]So
lidea
rth
tide
Ela
stic
resp
onse
totid
alpo
tent
ial[
Car
twri
ghta
ndTa
yler
197
1[5]
][C
artw
righ
tand
Edd
en1
973[
6]]
Loa
ding
tide
GO
T4v
7(S
1pa
ram
eter
isin
clud
ed)
Sea
stat
ebi
asN
onpa
ram
etri
cSS
B[G
aspa
reta
l20
02[2
0]]
Non
para
met
ric
SSB
[NT
ran
and
al2
010[
51]]
BM
3[G
aspa
ran
dO
gor
1994
[17]
]
Non
para
met
ric
SSB
[Mer
tzet
al
2005
[38]
]
Non
para
met
ric
SSB
[Gas
pare
tal
2002
]w
ithG
DR
-Bst
anda
rds
forc
ycle
s9
to85
and
with
GD
R-C
stan
dard
sfr
omcy
cle
86
Non
para
met
ric
SSB
[NT
ran
etal
20
10[5
1]]
Orb
iter
ror
Glo
bal m
ulti-
mis
sion
cros
sove
rmin
imiz
atio
n(L
eTr
aon
and
Ogo
r19
98[3
2])
Lon
gw
ave-
leng
her
rors
Opt
imal
Inte
rpol
atio
n(L
eTr
aon
etal
19
98[3
1])
Inte
rcal
ibra
tion
Ref
eren
cefr
omcy
cle
11R
efer
ence
from
cycl
e1
to35
4C
orre
ctio
nof
regi
onal
bias
J2J
1de
duce
dfr
omin
terc
alib
ratio
nph
ase
(cyc
le11
J2)
Cor
rect
ion
ofgl
obal
biai
sJ1
TP
deacutedu
ced
from
inte
rcal
ibra
tion
phas
e(c
ycle
s11
J1)
Mea
npr
o-fil
e(s
eeII
I36
1)
Com
pute
dw
ithcy
cles
11-3
53T
Pda
taan
dw
ithcy
cles
11-2
50J1
data
ref
eren
ced
[199
319
99]
TP
J1 c
ompu
ted
with
cycl
es11
-353
TP
data
and
with
cycl
es11
-250
J1da
tar
efer
ence
d[1
993
1999
]T
PNJ
1Nc
ompu
ted
with
cycl
es36
9-47
9T
PNda
tar
efer
ence
d[1
993
1999
]
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
ref
eren
ced
[199
319
99]
EN
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
re
fere
nced
[199
319
99]
EN
Nu
seof
MSS
_CN
ES_
CL
S11
[39]
Com
pute
dw
ithcy
cles
37-1
87G
2da
ta
refe
renc
ed[1
993
1999
]
Peri
odof
use
from
cycl
e9
from
cycl
e9
cycl
es1
to48
1cy
cles
15to
43In
clud
ing
E-F
geod
etic
phas
es
cycl
es1
to83
from
cycl
e9
cycl
es37
to22
2
Tabl
e7
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(2
2)
Page 34
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III32 Acquisition
The acqusition process in Delayed time is much simpler than in Near Real time it consists in a synchronisa-tion process of all the auxiliary data required to homogenize propely the altimeter data sets The acquisitionstep uses the GDRs or the OPRs provided by the agencies
III33 Homogenization
The Homogenization process consists in applying the most recent corrections models and references rec-ommended for altimeter products Each mission is processed separately as its needs depend on the baseinput data The list of corrections and models currently applied is provided in tables 6 and 7 for DT data
III34 Input data quality control
The Input Data Quality Control is a critical process applied to guarantee that DUACS uses only the mostaccurate altimeter data Thanks to the high quality of current missions this process rejects a small percent-age of altimeter measurements but these erroneous data could be the cause of a significant quality lossThe quality control relies on standard raw data editing with quality flags or parameter thresholds but alsoon complex data editing algorithms based on the detection of erroneous artefacts mono and multi-missioncrossover validation and macroscopic statistics to edit out large data flows that do not meet the systemrsquosrequirements
Page 35
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III35 Multi-mission cross-calibration
The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistentand accurate information It removes any residual orbit error (OE Le Traon and Ogor 1998[32]) or longwavelength error (LWE Le Traon et al 1998[31]) as well as large scale biases and discrepancies betweenvarious data flows
This process is based on two very different algorithms a global multi-mission crossover minimization fororbit error reduction (OER) and Optimal Interpolation (OI) for LWE
Multi-satellite crossover determination is performed on a daily basis All altimeter fields (measurementcorrections and other fields such as bathymetry MSS) are interpolated at crossover locations and datesCrossovers are then appended to the existing crossover database as more altimeter data become availableThis crossover data set is the input of the Orbit Error Reduction (OER) method Using the precision of thereference mission orbit a very accurate orbit error can be estimated LWE is mostly due to residual tidalor inverse barometer errors and high frequency ocean signals The OI used for LWE reduction uses preciseparameters derived from
bull accurate statistical description of sea level variability
bull localized correlation scales
bull mission-specific noise and precise assumptions on the long wavelength errors to be removed (from arecent analysis of one year of data from each mission)
Page 36
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III36 Product generation
The product generation process is composed of four steps computation of raw SLA cross-validationfilteringampsub-sampling and generation of by-products
III361 Computation of raw SLA
Since the geoid is not well known yet the SSH cannot be used directly the SSH anomalies are used insteadThey are computed from the difference of the instantaneous SSH - a temporal reference This temporalreference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeattrack analysis cannot be used The errors affecting the SLAs MPs and MSS have different magnitudes andwavelengths The computation of the SLAs and their errors associated are detailed in Dibarboure et al 2010[9]
Use of a Mean ProfileIn the repeat track analysis (when the satellites flies over a repetitive orbit) measurements are re-sampledalong a theoretical ground track (or mean track) associated to each mission Then a Mean Profile (MP) issubtracted from the re-sampled data to obtain SLA The MP is a time average of similarly re-sampled dataover a long period
bull The Mean Profile used for TP (cycles 1 to 364) Jason-1 (cycles 1 to 259) and Jason-2 is computedwith 10 years of TP (cycles 11 to 353) and 6 years of Jason-1 (cycles 11 to 250)
bull The Mean Profile used for TP (cycles 368 to 481) and from Jason-1 cycle 262 to 374 (where satellitesare on interleaved ground-tracks) is computed with 3 years of TP (cycles 369 to 479)
bull The Mean Profile used for ERS-1 in its 35 days repetitive orbit mission ERS-2 and Envisat (only forthe first orbit before November 2010) is computed with 8 years of ERS-2 (cycles 1 to 85) and 6 yearsof Envisat (cycles 10 to 72)
bull No Mean Profile can be used for Envisat on its new orbit (enn) Jason-1 on its geodetic orbit (j1g)because there is no repetitive track The MSS must be used instead (see below)
bull The Mean Profile used for GFO is computed with 7 years of GFO cycles 37 to 187
Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible
bull Indeed as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide precise cross-track projection andor interpolation schemes are required to avoid errors
bull The mesoscale variability error (which is lt35 cm for MP between 3 to 5 years and lt1cm for WLof 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a prioriknowledge from Sea Level maps derived from previous iterations or from other missions
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bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for ERS-1 for its 168 days geodetic mission (phases E-F from April1994 to March 1995) or for Envisat since november 2010 because the satellite is not in a repetitive orbitphase The alternative is to use the MSS instead The gridded MSS is derived from along track MPs anddata from geodetic phases Thus any error on the MP is also contained in the MSS There are essentially 4types of additional errors on gridded MSS which are hard to quantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
III362 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III363 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
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III37 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III371 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
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IV MYOCEAN PRODUCTS
IV1 Near Real Time Products
The purpose of the NRT DUACS component is the acquisition of altimeter data from various altimeter mis-sions in near-real time (ie within a few days at most) the validation and correction of these altimeter datasets (ie edition and selection update of corrections and homogenization orbit error reduction) in order toproduce each day along-track productsProducts are as follows
Along-track products global and regional (Mediterranean and Black Seas Arctic Ocean and Europeareas)
bull Sea Level Anomaly (NRT-SLA) for each mission with NRT-SLA ephemeris
IV11 Delay of the products
The availability of the products in near real time is three to twelve hours after the measurement for along-track products Those products are delivered every day
IV12 Temporal availibility
The following table presents the available products by mission and by data periodNear real time products
NRT Jason-2 Jason-1 and Jason-1geodetic
Envisat new Cryosat-2
Temporal Time availability ymlowast
ongoingymlowast-20120303 for
repeat track and20120507-ongoing for
geodetic track
ymlowast
2012040820120101
ongoing
NRT-SLA X X X X
lowastym the temporal coverage for NRT products is fluctuating and depends on updates of Delayed Time prod-ucts When DT products are updated (3 to 4 times per year) the oldest NRT products are replaced by thebetter quality DT products so that the 2 series are overlapping on few weeks or few months
IV2 Delayed Time Products
The Delayed Time component of SSALTODUACS system is responsible for the production of processedJason-1 Jason-2 TP Envisat GFO ERS12 and even Geosat data in order to provide a homogeneousinter-calibrated and highly accurate long time series of SLA DT products are more precise than NRT products Two reasons explain this quality difference The firstone is the better intrinsic quality of the POE orbit used in the GDR processing The second reason is that
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in the DT DUACS processing the products can be computed optimally with a centred computation timewindow for OER LWE On the contrary in NRT case future data are not available so the computationtime window is not centred and therefore not optimalAs for NRT products improved altimeter corrections and processing algorithms are used ocean tide modelto correct altimeter data improved methods for orbit error reduction and mapping
Along-Track products global and regional (Mediterranean and Black Seas)
bull Sea Level Anomaly (DT-SLA) for each mission
IV21 Delay of the products
Weekly products are delivered The availability of the products in delayed time is at the best two monthsafter the date of the measurement The product generation needs all the GDR data of all the missions to takeinto account the best corrections as possible The time delay can be longer in the case of a missing mission
IV22 Temporal availibility
The following table presents the available products by mission and by data periodDelayed time SSALTODUACS products
Upd Jason-2 Jason-1new6
Jason-1 GFO Envisatnew6
Envisat ERS-16
ERS-2Topexnew6
Topex
TemporalTimeavailabil-ity
200810ymlowast
200902ymlowast
200204200810
200001200809
201010ymlowast
200210201010
199210200304
200209200510
199209200204
DT-SLA X X X X X X X X X
lowast ym those dates are updated regularly (3 to 4 times per year) and are avalaible when you download thedata at httpwwwmyoceaneuweb24-cataloguephp6 Jason-1 new orbit starting 200809 Envisat new orbit starting 201010 TP new orbit starting 200209 ERS-1The geodetic phases (E-F) are included There are no ERS-1 data between December 23 1993 and April 10 1994(ERS-1 phase D - 2nd ice phase) Note that during that time products are based only on TopexPoseidon data
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V DESCRIPTION OF THE PRODUCT SPECIFICATION
V1 General information
Product Specification SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001
Geographical coverage global
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 20-50km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001 Product Specification
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Product Specification SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002
Geographical coverage 55˚W-35˚E 30˚N-46˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002 Product Specification
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Product Specification SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003
Geographical coverage 27˚E-42˚E 40˚N-47˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003 Product Specification
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Product Specification SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004
Geographical coverage 25˚W-42˚E 21˚N-66˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004 Product Specification
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Product Specification SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005
Geographical coverage 0˚W-360˚E 50˚N-82˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005 Product Specification
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VI NOMENCLATURE OF FILES
VI1 Nomenclature of files downloaded through the MyOcean Web PortalDirectgetfile Service
VI11 Nomenclature of the product line
The description of the syntax for the SL TAC SLA products line is given by
SEALEVEL_ltREGIONgt_SLA_L3_ltDELAYgt_OBSERVATIONS_008_ltZONEgt_ltLETTERgtwhere
REGION GLO global geographic coverage product
BS Black Sea products
MED Mediterranean products
ARC Arctic products (for NRT products)
EUROPE Europe products (for NRT products)
DELAY NRT near real time products
RAN delayed time or reanalysis products
ZONE 001 number on 3 digits
002
003
004
LETTER a letter on 1 digit
b
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VI12 Nomenclature of the datasets
The nomenclature used is
dataset-duacs-ltdelaygt-ltzonegt-ltmissiongt-lttype of slagt-l3where the fileds in ltgt are described below
delay nrt near-real time productsran delayed time products
zone global global geographic coverage productmedsea Mediterranean productsblacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1 (only for ran)e2 ERS-2 (only for ran)tp TOPEXPoseidon (only for ran)tpn TOPEXPoseidon on its new orbit (only for
ran)g2 GFO (only for ran)j1 Jason-1 (only for ran)j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisat (only for ran)enn Envisat on its new orbitc2 Cryosat-2 (only for nrt)
type of sla sla filtered slasla_unfiltered non filtered sla (only for ran products)
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VI13 Nomenclature of the NetCdf files
The nomenclature used is
ltdelaygt_ltzonegt_ltmissiongt_sla_ltvariablegt_ltdatebegingt_ltdateendgt_ltdateprodgtnc where the fileds in ltgt are de-scribed below
delay nrt near-real time productsdt delayed time products
zone global global geographic coverage productmed Mediterranean products (for dt)mfstep Mediterranean products (for nrt)blacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1e2 ERS-2tp TOPEXPoseidontpn TOPEXPoseidon on its new orbitg2 GFOj1 Jason-1j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisatenn Envisat on its new orbitc2 Cryosat-2
variable vfec filtered and sub-sampled slavxxc non filtered and non sub-sampled sla (only
for dt)datebegin YYYYMMDD() beginning date of the datasetdateend YYYYMMDD() end date of the datasetdateprod YYYYMMDD production date of the dataset
() For dt data as the dates in the file names are rounded the user wanting data for date T has to read the filescontaining dates T+1 and T-1 in their name and check inside the files if there are some data for date T
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VII DATA FORMAT
This chapter presents the data storage format used for MyOcean products
VII1 NetCdf
The products are stored using the NetCDF format NetCDF (network Common Data Form) is an interface for array-oriented data access and a library that provides an implementation of the interface The netCDF library also definesa machine-independent format for representing scientific data Together the interface library and format support thecreation access and sharing of scientific data The netCDF software was developed at the Unidata Program Center inBoulder Colorado The netCDF libraries define a machine-independent format for representing scientific data Pleasesee Unidata NetCDF pages for more information and to retreive NetCDF software package onhttpwwwunidataucaredupackagesnetcdfindexhtml
NetCDF data is
bull Self-Describing A netCDF file includes information about the data it contains
bull Architecture-independent A netCDF file is represented in a form that can be accessed by computers with dif-ferent ways of storing integers characters and floating-point numbers
bull Direct-access A small subset of a large dataset may be accessed efficiently without first reading through allthe preceding data
bull Appendable Data can be appended to a netCDF dataset along one dimension without copying the dataset orredefining its structure The structure of a netCDF dataset can be changed though this sometimes causes thedataset to be copied
bull Sharable One writer and multiple readers may simultaneously access the same netCDF file
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VII2 Structure and semantic of NetCDF along-track files
The NetCDF Sea Level TAC files are based on the attribute data tags defined by the Cooperative OceanAtmosphereResearch Data Service (COARDS) and Climate and Forecast (CF) metadata conventions The CF convention gener-alises and extends the COARDS convention but relaxes the COARDS constraints on dimension and order and specifiesmethods for reducing the size of datasetsA wide range of software are available to write or read NetCDFCF files API are made available by UNIDATA(httpwwwunidataucaredusoftwarenetcdf)
bull CC++Fortran
bull Java
bull MATLAB Objective-C Perl Python R Ruby TclTk
In addition to these conventions the files are using a common structure and semantic
bull 1 dimension is defined
ndash time it is used to check NetCDF variables depending on time
bull 8 variables are defined
ndash short SLA contains the Sea Level Anomaly values for each time given
ndash int longitude contains the longitude for each measurement
ndash short track contains the track number for each measurement
ndash double time contains the time in days since 1950-01-01 000000 UTC for each measurement
ndash short mean_profile_point_index index of the corrsponding point in the track of the mean profile
ndash byte flag flag=0 the processed data comes from OGDR if flag=1 the processed data comes from theIGDR
ndash int latitude contains the latitude for each measurement
ndash short cycle contains the cycle number for each measurement
bull global attributes
ndash the global attributes gives information about the creation of the file
Example of a NetCDF sla file
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netcdf nrt_global_j1_sla_vfec_20101230_20101230_20101230 dimensions
time = 10385 variables
short SLA(time) SLAcoordinates = longitude latitude SLAlong_name = Sea Level Anomaly SLA_FillValue = 32767s SLAadd_offset = 0 SLAscale_factor = 0001 SLAunits = m SLAstandard_name = sea_surface_height_above_sea_level
int longitude(time) longitudelong_name = Longitude of measurement longitude_FillValue = 2147483647 longitudeadd_offset = 0 longitudestandard_name = longitude longitudescale_factor = 1e-06 longitudeunits = degrees_east
short track(time) tracklong_name = Track in cycle the measurement belongs to track_FillValue = 32767s trackunits = 1 trackcoordinates = longitude latitude
double time(time) timelong_name = Time of measurement time_FillValue = 184467440737096e+19 timeaxis = T timestandard_name = time timeunits = days since 1950-01-01 000000 UTC
int latitude(time) latitudelong_name = Latitude of measurement latitude_FillValue = 2147483647 latitudeadd_offset = 0 latitudestandard_name = latitude latitudescale_factor = 1e-06 latitudeunits = degrees_north
short flag(time) flagcoordinates = longitude latitude flag_FillValue = 3267s flaglong_name = data origin flagflag_values = 1s 0s flagflag_meanings = igdr_like non_igdr_like flagcomment = The origin of the data is determined by the types of geophysical datarecords (GDR) used in computation of the SLA 1 for the Interim GDR (IGDR) and0 for Operational GDR (OGDR)
short cycle(time) cyclelong_name = Cycle the measurement belongs to cycle_FillValue = 32767s cycleunits = 1 cyclecoordinates = longitude latitude
global attributeshistory = 22-Feb-2011 155243 CET File created by the SSLATODUACS system version 1001 comment = Produce from ENVISAT Extension Phase satellite altimetry data institution = CLSCNES
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references = httpwwwavisooceanobscomfileadmindocumentsdatatoolshdbk_duacspdf source = satellite altimetry title = along track Sea Level Anomaly Conventions = CF-14
dataSLA =
7 7 11 10 -2 -22 -39 -41 -30 -13 -3 -5 -16 -26 -32 -35-35 -35 -37 -35 -31 -29 -31 -35 -32 -21 -10 -10 -19 -20 -1-69 -57 -49 -45 -39 -30 -28 -31 -27 -13 -2 -5 -15 -3 1112 3 -7 -10 -14 -15 -22 -31 -37 -32 -17 -10
longitude =74743328 74868400 74993968 75120040 75246616 7537372875501368 75629568 75758320 75887656 76017568 76148080 7627920876388952 76477056 76565456 76654144 76743128 76832400 76921984329429568 329535424 329641792 329748672 329856096 329964032330072512 330181536 330291072 330401184
track =92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 9292 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92113 113 113 113 113 113 113 113 113 113 113 113 113 113113 113 113 113 113 113 113 113 113
time =222780000565705 222780001314719 222780002063733222780002812747 222780003561761 222780004310775 222780005059788222780005808802 222780006557816 22278000730683 222780008055844222780008804858 222780009553872 22278001017805 222780010677393222788257112198 222788257486705 222788257861212 222788258235719222788258610226 222788258984733 222788259359239 222788259733746222788260108253 22278826048276
mean_profile_point_index =1872 1878 1884 1890 1896 1902 1908 19141920 1926 1932 1938 1944 1949 1953 1957 1961 1965 1969 19732306 2309 2312 2315 2318 2321 2327 2330 2333 2336 2339 23422345 2348 2351 2354 2357 2360 2363 2366
flag =0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
latitude =-16225506 -16539731 -16853833 -17167810 -17481660 -17795380-18108966 -18422418 -18735729 -19048899 -19361924 -19674801-19987527 -20248015 -20456329 -20664569 -20872739 -2108083739481297 39628277 39775133 39921866 40068472 40214953 4036130840507533 40653629 40799592 40945423 41091120 41236684 41382111
cycle =331 331 331 331 331 331 331 331 331 331 331 331 331
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331 331 331 331 331 331 331 331 331 331 331 331 331 331331 331 331 331 331 331 331 331 331 331 331 331
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VIII HOW TO DOWNLOAD A PRODUCT
VIII1 Download a product through the MyOcean Web Portal DirectgetfileService
You first need to register Please find below the registration stepshttpwwwmyoceaneuweb34-products-and-services-faqphp1Once registered the MyOcean FAQ httpwwwmyoceaneuweb34-products-and-services-faqwill guide you on How to download a product through the MyOcean Web Portal Directgetfile Service
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IX NEWS AND UPDATES
IX1 [Duacs] Operational news
To be kept informed on events occurring on the satellites and on the eventual interruption of the services of the DUACSprocessing system see the [Duacs] operational news on the Aviso websitehttpwwwavisooceanobscomendataoperational-newsindexhtml
IX2 Updates
To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtmlSince 2010 a complete reprocessing of all altimetry data (cumulated total of about 55 years of data) is available Themain changes introduced in the Duacs DT v300 reprocessed data set in SSALTODUACS reprocessed DT data setare listed herehttpwwwavisooceanobscomfileadmindocumentsdataduacsduacs_DT_2010_reprocessing_impactpdf
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III SSALTODUACS SYSTEM
III1 Introduction
This chapter presents the input data used by SSALTODUACS system and an overview of the different pro-cessing steps necessary to produce the output dataSSALTODUACS system is made of two components a Near Real Time one (NRT) and a Delayed Time(DT) oneIn NRT the systemrsquos primary objective is to provide operational applications with directly usable high qual-ity altimeter data from all missions availableIn DT it is to maintain a consistent and user-friendly altimeter database using the state-of-the-art recom-mendations from the altimetry communityFollowing figure gives an overview of DUACS system where processing sequences can be divided into 7main steps
bull acquisition
bull homogenization
bull input data quality control
bull multi-mission cross-calibration
bull product generation
bull merging
bull final quality control
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Figure 5 SSALTODUACS processing sequences
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III2 Near Real Time processing steps
III21 Input data models and corrections applied
To produce SLA in near-real time the DUACS system uses two flows based on the same instrumental mea-surements but with a different quality
bull The IGDR that are the latest high-quality altimeter data produced in near-real-time
bull The OGDR that includes real time data (OSTMJason-2 and Jason-1 OSDR) to complete IGDR Thesefast delivery products do not always benefit from precise orbit determination nor from some exter-nal model-based corrections (Dynamic Atmospheric Correction (DAC) Global Ionospheric Maps(GIM))
Integration of OGDR data and the introduction of Jason-2Jason-1 tandem increased the resilience and pre-cision of the system A better restitution of ocean variability is observed especially in high energetic areas
Altimetric product Source Availability Type of orbit
Jason-2 IGDR CNES ~24h CNES MOE GDR-Cuntil 20120730
CNES MOE GDR-Dsince 20120731
OGDR NOAAEUMETSAT ~3 to 5 h
Jason-1 IGDR CNESNASA ~48 h CNES MOE GDR-Dsince 20120507
OGDR CNESNASA ~3 to 12 h
Envisat IGDR ESACNES not deliveredsince 20120408
CNES MOE GDR-Dsince 20120121
FDGDR ESA not deliveredsince 20120408
Cryosat-2 IGDR-like ESACNES ~48 h CNES MOE GDR-D
not delivered
Table 2 SSALTODUACS Near-Real Time Input data overview
See Figure 6 Overview of the near real time system data flow management
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DUACS 2011 NRT product from IGDR1
j2 j1nj1g enn c2Productstandard ref
version C until20120730 and D after
version C version 21 CPP [2]
Orbit CNES MOE GDR-Cuntil 20120730
GDR-D after
CNES MOE GDR-C forj1n and CNES MOE
GDR-D for j1g
CNES MOE GDR-Dfrom 20120121 to
20120408
CNES MOE GDR-D
Ionopheric bi-frequency altimeter range measurements GIM model for cgt64 (Iijima et al1998[24])Dry tropo Model computed from ECMWF Gaussian grids (new S1 and S2 atm tides applied)Wet tropo-sphere
AMR radiometer(enhancement in coastal
regions since20120730)
JMR radiometer MWR radiometer andcorrected from side
lobes
Model computed fromECMWF Gaussian
grids
DAC MOG2D High Resolution forced with ECMWF pressure and wind fields (S1 and S2 wereexcluded) (Carrere and Lyard 2003[3])+ inverse barometer Filtering temporal window is
un-centered (no data in the future)Ocean tide GOT4v8 (S1 and S2 are included) and TPX 072 [16] for Arctic productsPole tide [Wahr 1985 [53]]Solid earthtide
Elastic response to tidal potential [Cartwright and Tayler 1971[5]] [Cartwright andEdden 1973[6]]
Loading tide GOT4v8 (S1 and S2 are included)Sea statebias
Non parametric SSB[Labroue 2004[27]](with cycles J1 1 to 11
using GDR-B standardsuntil 20120730 andderived from Jason-2
after)
Non parametric SSB[Labroue 2004[27]](with cycles 1 to 21
using GDR-Bstandards)
Non parametric SSB[Labroue 2004[27]](with cycles 41 to 60
using GDR-Bstandards)
Same as Jason-2 SSB
Orbit error Global multi-mission crossover minimization (Le Traon and Ogor1998[32])
Long wave-lengh errors
Optimal Interpolation [Le Traon et al 1998[31]]
Intercalibration Reference from cycle20
Mean pro-file (seeIII261)
Computed with cycles11-353 TP data andwith cycles 11-250J1 data referenced[19931999]
TPNJ1N computedwith cycles 369-479TPN data refer-enced [19931999]J1G No MP can beused instead theMSS_CNES_CLS11[39] is used
No Mean Profilecan be used forEnvisat on its neworbit Instead theMSS_CNES_CLS11[39] is used
No Mean Profilecan be used forCryosat-2 Instead theMSS_CNES_CLS11[39] is used
(1) A flag included in the along-track files indicates the source of the production (OGDRFDGDR orIGDR) If flag=0 the processed data comes from OGDRsFDGDRs if flag=1 the processed data comesfrom IGDRs
Table 3 Corrections and models applied in SSALTODUACS NRT products produced from IGDRs
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
DUACS 2011 NRT product from OGDR or FDGDR2
j2 j1nj1g ennProduct stan-dard ref
version C until 20120730and D after
version C version 21
Orbit Navigator Extrapolated CNES MOEGDR-D since 20120121
Ionopheric From-dual frequency altimeter range measurements From GIM model fromcycle 65 (Iijima et al1998 [24])
Dry troposphere Model computed from ECMWF Gaussian grids (new S1 and S2 atmospherictides are applied)
Wet tropo-sphere
AMR radiometer(enhancement in coastal
regions since 20120730)
JMR radiometer MWR radiometer andcorrected from side lobes
DAC Inverse Barometer forecastedOcean tide GOT4v8 (S1 and S2 are included) and TPX 072 [16] for Arctic productsPole tide [Wahr 1985 [53]]Solid earth tide Elastic response to tidal potential [Cartwright and Tayler 1971[5]]
[Cartwright and Edden 1973[6]]Loading tide GOT4v8 (S1 and S2 are included)Sea state bias Non parametric SSB
[Labroue 2004[27]] (withcycles J1 1 to 11 usingGDR-B standards until20120730 and derivedfrom Jason-2 after)
Non parametric SSB[Labroue 2004[27]](with cycles 1 to 21 usingGDR-B standards)
Non parametric SSB[Labroue 2004[27]](with cycles 41 to 60using GDR-B standards)
Orbit error Specific filtering of long-wavelength signal3
Long wave-lengh errors
Optimal Interpolation [Le Traon et al 1998[31]]
Intercalibration Reference from cycle 20Mean profile(see III261)
Computed with cycles 11-353 TP data and with cy-cles 11-250 J1 data refer-enced [19931999]
TPNJ1N computedwith cycles 369-479TPN data referenced[19931999] J1G NoMP can be used insteadthe MSS_CNES_CLS11[39] is used
No Mean Profile can beused for Envisat on itsnew orbit Instead theMSS_CNES_CLS11 [39]is used
(2) A flag included in the along-track files indicates the source of the production (OGDRFDGDR orIGDR) If flag=0 the processed data comes from OGDRsFDGDRs if flag=1 the processed data comesfrom IGDRs(3) Specific data processing was applied on long wave-length signal (sectIII23 of the user manual)
Table 4 Corrections and models applied in SSALTODUACS NRT products produced from OG-DRsFDGDRs
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III22 Acquisition
The acquisition process is twofold
bull straightforward retrieval and reformatting of altimeter data and dynamic auxiliary data (pressure andwet troposphere correction grids from ECMWF are provided by Meteo France TEC grids from JPLNRT MOG2D corrections) from external repositories
bull synchronisation process
To be homogenized properly altimeter data sets require various auxiliary data The acquisition softwaredetects downloads and processes incoming data as soon as they are available on remote sites (externaldatabase FTP site) Data are split into passes if necessary If data flows are missing or late the synchroni-sation engine put unusable data in waiting queues and automatically unfreezes them upon reception of themissing auxiliary data This processing step delivers raw data that is to say data that have been dividedinto cycles and passes and ordered chronologicallyFrom SSALTODUACS V80 the acquisition step uses two different data flows in near-real time the OGDRflow (within a few hours) and the IGDR flow (within a few days)For each OGDR input the system checks that no equivalent IGDR entry is available in the data base beforeacquisition for each IGDR input the system checks and delete the equivalent OGDR entry in the data baseThese operations aim to avoid duplicates in SSALTODUACS system
Figure 6 Overview of the near real time system data flow management
Page 25
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III23 Homogenization
The Homogenization process consists in applying the most recent corrections models and references rec-ommended for altimeter products Each mission is processed separately as its needs depend on the baseinput data The list of corrections and models currently applied is provided in tables 3 and 4 for NRT dataThe system includes SLA filtering to process OGDR data DUACS extract from these data sets the shortscales (space and time) which are useful to better describe the ocean variability in real time and merge thisinformation with a fair description of large scale signals provided by the multi-satellite observation in nearreal time (read IGDR-based DUACS data) Finally an hybrid SLA is computed
Figure 7 Merging pertinent information from IGDR and OGDR processing
III24 Input data quality control
The Input Data Quality Control is a critical process applied to guarantee that DUACS uses only the mostaccurate altimeter data Thanks to the high quality of current missions this process rejects a small percent-age of altimeter measurements but these erroneous data could be the cause of a significant quality lossThe quality control relies on standard raw data editing with quality flags or parameter thresholds but alsoon complex data editing algorithms based on the detection of erroneous artefacts mono and multi-missioncrossover validation and macroscopic statistics to edit out large data flows that do not meet the systemrsquosrequirements
Page 26
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III25 Multi-mission cross-calibration
The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistentand accurate information It removes any residual orbit error (OE Le Traon and Ogor 1998[32]) or longwavelength error (LWE Le Traon et al 1998[31]) as well as large scale biases and discrepancies betweenvarious data flows
This process is based on two very different algorithms a global multi-mission crossover minimization fororbit error reduction (OER) and Optimal Interpolation (OI) for LWE
Multi-satellite crossover determination is performed on a daily basis All altimeter fields (measurementcorrections and other fields such as bathymetry MSS) are interpolated at crossover locations and datesCrossovers are then appended to the existing crossover database as more altimeter data become availableThis crossover data set is the input of the Orbit Error Reduction (OER) method Using the precision of thereference mission orbit a very accurate orbit error can be estimated This processing step does not concernOGDR dataLWE is mostly due to residual tidal or inverse barometer errors and high frequency ocean signals The OIused for LWE reduction uses precise parameters derived from
bull accurate statistical description of sea level variability
bull localized correlation scales
bull mission-specific noise and precise assumptions on the long wavelength errors to be removed (from arecent analysis of one year of data from each mission)
Page 27
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III26 Product generation
The product generation process is composed of four steps computation of raw SLA cross-validationfilteringampsub-sampling and generation of by-products
III261 Computation of raw SLA
Since the geoid is not well known yet the SSH cannot be used directly the SSH anomalies are used insteadThey are computed from the difference of the instantaneous SSH - a temporal reference This temporalreference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeattrack analysis cannot be used The errors affecting the SLAs MPs and MSS have different magnitudes andwavelengths The computation of the SLAs and their errors associated are detailed in Dibarboure et al 2010[9]
Use of a Mean ProfileIn the repeat track analysis (when the satellites flies over a repetitive orbit) measurements are re-sampledalong a theoretical ground track (or mean track) associated to each mission Then a Mean Profile (MP) issubtracted from the re-sampled data to obtain SLA The MP is a time average of similarly re-sampled dataover a long period
bull The Mean Profile used for Jason-2 is computed with 10 years of TP (cycles 11 to 353) and 6 years ofJason-1 (cycles 11 to 250)
bull The Mean Profile used from Jason-1 cycle 262 to 374 (where satellites are on interleaved ground-tracks) is computed with 3 years of TP (cycles 369 to 479)
bull No Mean Profile can be used for Envisat on its new orbit (enn) Jason-1 on its geodetic orbit (j1g) norfor Cryosat-2 mission (c2) because there is no repetitive track The MSS must be used instead (seebelow)
Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible
bull Indeed as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide precise cross-track projection andor interpolation schemes are required to avoid errors
bull The mesoscale variability error (which is lt35 cm for MP between 3 to 5 years and lt1cm for WLof 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a prioriknowledge from Sea Level maps derived from previous iterations or from other missions
bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
Page 28
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for Envisat since november 2010 and for Cryosat-2 mission (c2)because the satellite is not in a repetitive orbit phase The alternative is to use the MSS instead The griddedMSS is derived from along track MPs and data from geodetic phases Thus any error on the MP is alsocontained in the MSS There are essentially 4 types of additional errors on gridded MSS which are hard toquantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
Note that for the Arctic regional products the DTU10 MSS [1] is taken into account instead of the CLS01MSS Indeed the accuracy of DTU10 compared to CLS01 is further demonstrated by the significant sealevel anomaly variance reduction found over the whole Arctic Ocean as shown in Prandi et al [42]
III262 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III263 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
Page 29
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III27 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III271 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
Page 30
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III272 Performance indicators
To appreciate the quality situation of the DUACS system new performance indicators are computed dailyThey aim at evaluate the status of the main processing steps of the system the input data availability theinput data coverage the input data quality and the output product quality These indicators are computed foreach and every currently working satellite and combined to obtain the overall status
Figure 8 Example with the key performance indicator on 20090627
See the description the latest and previous indicators on Aviso websitehttpwwwavisooceanobscomindexphpid=1516
Page 31
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III3 Delayed Time processing steps
III31 Input data models and corrections applied
Delayed Time MyOcean products are generated
bull from Aviso GDR products for TP Jason-1 Jason-2 and Envisat (GDR-A cycles 1 to 22 GDR-Bcycles 23 to 85 GDR-C from cycle 86)
bull from NOAA GDR for GFO and from CERSAT (IFREMER) OPR for ERS-1 and ERS-2 (phases C(1st 35-day repeat orbit period) phase E and F (geodetic phases) phase G for ERS-1 (last 35-dayrepeat orbit period tandem phase with ERS-2 phase A for ERS-2 (1st 35-day repeat orbit periodtandem phase with ERS-1))
All GDR products are computed with a Precise Orbit Ephemeris (POE) and are delivered within 2 to 3months depending on the mission For several missions an updated orbit is used
bull For ERS-1amp-2 the orbit used is DGME-04 provided by Delft Institute (httpwwwdeostudelftnl)until June 2003
bull For TopexPoseidon the orbit used is GSFC (std0809) for the whole mission
bull For Envisat CNES POE of GDR-C standard is used for the whole mission
bull For the whole GFO mission the orbit used is GSFC (std0809) and when not available NASA POE isused
Altimetric product Source Availability Type of orbit
TopexPoseidon GDR NASACNES - GSFC POE
Jason-1 GDR (GDR-C) CNESNASA ~40 days CNES POE
Jason-2 GDR (GDR-C) CNESNASA ~60 days CNES POE
GFO GDR NOAA - GSFCNASA POE
ERS-1amp2 IFREMERESA - DGME-04
Envisat (GDR-A GDR-B andGDR-C from cycle 86)
ESA ~2 months CNES POE
Table 5 SSALTODUACS Delayed Time Input data overview
Page 32
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
DU
AC
S20
11D
Tpr
oduc
t(gtV
30
0)j2
j1j1
ntp
tpn
e1e2
ene
nng2
Prod
uct
stan
dard
ref
GD
R-C
OPR
GD
R-A
(Cyc
les
1to
22)
GD
R-B
(cyc
les
23-8
5)
GD
R(N
OA
A)
Orb
itC
nes
POE
GSF
C(I
TR
F20
05G
RA
CE
last
stan
dard
s)
DG
ME
-04
(Sch
arro
oan
dV
isse
r19
98[4
8]C
NE
SPO
E(G
DR
-1st
anda
rds
forc
ycle
s9
to22
GD
R-C
stan
dard
sfr
omcy
cle
23)
GSF
C(I
TR
F20
05
GR
AC
Ela
stst
anda
rds
Iono
pher
icD
ual f
requ
ency
altim
eter
rang
em
easu
rem
ents
Dua
l fre
quen
cyal
timet
erra
nge
mea
sure
men
ts(T
opex
)D
OR
IS(P
OSE
IDO
N)
Ben
t mod
elB
ent m
odel
(cyc
les
1-36
)G
IMm
odem
from
cycl
e37
((Ii
jima
etal
19
98[2
4])
Dua
l-fr
eque
ncy
altim
eter
rang
em
easu
rem
ent(
cycl
e9-
64)a
ndG
IMm
odel
gtcyc
le65
(Iiji
ma
etal
19
99[2
4])c
orre
cted
from
8m
mbi
as
From
GIM
mod
el(I
ijim
aet
al1
998
[24]
)
Dry
trop
o-sp
here
Mod
elco
mpu
ted
from
EC
MW
FG
auss
ian
grid
s(n
ewS1
and
S2at
mos
pher
ictid
esar
eap
plie
d)
Mod
elco
mpu
ted
from
EC
MW
Fre
ctan
gula
rgri
ds(n
ewS1
and
S2at
mos
pher
ictid
esar
ein
clud
ed)
Wet
trop
o-sp
here
JMR
AM
Rra
diom
eter
furt
hert
han
50km
from
the
coas
tsF
rom
EC
MW
Fm
odel
ford
ista
nces
betw
een
10an
d50
km
TM
Rra
diom
eter
(Sch
aroo
etal
20
04[4
9])
MW
RC
orre
ctio
nof
the
drif
ton
the
236
GH
zbr
ight
ness
tem
pera
ture
(Sch
arro
oet
al
2004
[49]
)Neu
ral
Net
wor
kal
gori
thm
(Tra
nan
dO
blig
is
2003
[50]
MW
Rra
diom
eter
furt
hert
han
50km
from
the
coas
tsan
dco
rrec
ted
from
side
lobe
s(f
rom
cycl
e41
)E
CM
WF
mod
elfo
rdis
tanc
esbe
twee
n10
and
50km
GFO
radi
omet
er
DA
CM
OG
2DH
igh
Res
olut
ion
forc
edw
ithE
CM
WF
pres
sure
and
win
gfie
lds
(S1
and
S2w
ere
excl
uded
)+in
vers
eba
rom
eter
com
pute
dfr
omre
ctan
gula
rgri
ds
Tabl
e6
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(1
2)
Page 33
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
j2j1
j1n
tptp
ne1
e2en
enn
g2O
cean
tide
GO
T4v
7(S
1an
dS2
are
incl
uded
)Po
letid
e[W
ahr
1985
[53]
]So
lidea
rth
tide
Ela
stic
resp
onse
totid
alpo
tent
ial[
Car
twri
ghta
ndTa
yler
197
1[5]
][C
artw
righ
tand
Edd
en1
973[
6]]
Loa
ding
tide
GO
T4v
7(S
1pa
ram
eter
isin
clud
ed)
Sea
stat
ebi
asN
onpa
ram
etri
cSS
B[G
aspa
reta
l20
02[2
0]]
Non
para
met
ric
SSB
[NT
ran
and
al2
010[
51]]
BM
3[G
aspa
ran
dO
gor
1994
[17]
]
Non
para
met
ric
SSB
[Mer
tzet
al
2005
[38]
]
Non
para
met
ric
SSB
[Gas
pare
tal
2002
]w
ithG
DR
-Bst
anda
rds
forc
ycle
s9
to85
and
with
GD
R-C
stan
dard
sfr
omcy
cle
86
Non
para
met
ric
SSB
[NT
ran
etal
20
10[5
1]]
Orb
iter
ror
Glo
bal m
ulti-
mis
sion
cros
sove
rmin
imiz
atio
n(L
eTr
aon
and
Ogo
r19
98[3
2])
Lon
gw
ave-
leng
her
rors
Opt
imal
Inte
rpol
atio
n(L
eTr
aon
etal
19
98[3
1])
Inte
rcal
ibra
tion
Ref
eren
cefr
omcy
cle
11R
efer
ence
from
cycl
e1
to35
4C
orre
ctio
nof
regi
onal
bias
J2J
1de
duce
dfr
omin
terc
alib
ratio
nph
ase
(cyc
le11
J2)
Cor
rect
ion
ofgl
obal
biai
sJ1
TP
deacutedu
ced
from
inte
rcal
ibra
tion
phas
e(c
ycle
s11
J1)
Mea
npr
o-fil
e(s
eeII
I36
1)
Com
pute
dw
ithcy
cles
11-3
53T
Pda
taan
dw
ithcy
cles
11-2
50J1
data
ref
eren
ced
[199
319
99]
TP
J1 c
ompu
ted
with
cycl
es11
-353
TP
data
and
with
cycl
es11
-250
J1da
tar
efer
ence
d[1
993
1999
]T
PNJ
1Nc
ompu
ted
with
cycl
es36
9-47
9T
PNda
tar
efer
ence
d[1
993
1999
]
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
ref
eren
ced
[199
319
99]
EN
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
re
fere
nced
[199
319
99]
EN
Nu
seof
MSS
_CN
ES_
CL
S11
[39]
Com
pute
dw
ithcy
cles
37-1
87G
2da
ta
refe
renc
ed[1
993
1999
]
Peri
odof
use
from
cycl
e9
from
cycl
e9
cycl
es1
to48
1cy
cles
15to
43In
clud
ing
E-F
geod
etic
phas
es
cycl
es1
to83
from
cycl
e9
cycl
es37
to22
2
Tabl
e7
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(2
2)
Page 34
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III32 Acquisition
The acqusition process in Delayed time is much simpler than in Near Real time it consists in a synchronisa-tion process of all the auxiliary data required to homogenize propely the altimeter data sets The acquisitionstep uses the GDRs or the OPRs provided by the agencies
III33 Homogenization
The Homogenization process consists in applying the most recent corrections models and references rec-ommended for altimeter products Each mission is processed separately as its needs depend on the baseinput data The list of corrections and models currently applied is provided in tables 6 and 7 for DT data
III34 Input data quality control
The Input Data Quality Control is a critical process applied to guarantee that DUACS uses only the mostaccurate altimeter data Thanks to the high quality of current missions this process rejects a small percent-age of altimeter measurements but these erroneous data could be the cause of a significant quality lossThe quality control relies on standard raw data editing with quality flags or parameter thresholds but alsoon complex data editing algorithms based on the detection of erroneous artefacts mono and multi-missioncrossover validation and macroscopic statistics to edit out large data flows that do not meet the systemrsquosrequirements
Page 35
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III35 Multi-mission cross-calibration
The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistentand accurate information It removes any residual orbit error (OE Le Traon and Ogor 1998[32]) or longwavelength error (LWE Le Traon et al 1998[31]) as well as large scale biases and discrepancies betweenvarious data flows
This process is based on two very different algorithms a global multi-mission crossover minimization fororbit error reduction (OER) and Optimal Interpolation (OI) for LWE
Multi-satellite crossover determination is performed on a daily basis All altimeter fields (measurementcorrections and other fields such as bathymetry MSS) are interpolated at crossover locations and datesCrossovers are then appended to the existing crossover database as more altimeter data become availableThis crossover data set is the input of the Orbit Error Reduction (OER) method Using the precision of thereference mission orbit a very accurate orbit error can be estimated LWE is mostly due to residual tidalor inverse barometer errors and high frequency ocean signals The OI used for LWE reduction uses preciseparameters derived from
bull accurate statistical description of sea level variability
bull localized correlation scales
bull mission-specific noise and precise assumptions on the long wavelength errors to be removed (from arecent analysis of one year of data from each mission)
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III36 Product generation
The product generation process is composed of four steps computation of raw SLA cross-validationfilteringampsub-sampling and generation of by-products
III361 Computation of raw SLA
Since the geoid is not well known yet the SSH cannot be used directly the SSH anomalies are used insteadThey are computed from the difference of the instantaneous SSH - a temporal reference This temporalreference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeattrack analysis cannot be used The errors affecting the SLAs MPs and MSS have different magnitudes andwavelengths The computation of the SLAs and their errors associated are detailed in Dibarboure et al 2010[9]
Use of a Mean ProfileIn the repeat track analysis (when the satellites flies over a repetitive orbit) measurements are re-sampledalong a theoretical ground track (or mean track) associated to each mission Then a Mean Profile (MP) issubtracted from the re-sampled data to obtain SLA The MP is a time average of similarly re-sampled dataover a long period
bull The Mean Profile used for TP (cycles 1 to 364) Jason-1 (cycles 1 to 259) and Jason-2 is computedwith 10 years of TP (cycles 11 to 353) and 6 years of Jason-1 (cycles 11 to 250)
bull The Mean Profile used for TP (cycles 368 to 481) and from Jason-1 cycle 262 to 374 (where satellitesare on interleaved ground-tracks) is computed with 3 years of TP (cycles 369 to 479)
bull The Mean Profile used for ERS-1 in its 35 days repetitive orbit mission ERS-2 and Envisat (only forthe first orbit before November 2010) is computed with 8 years of ERS-2 (cycles 1 to 85) and 6 yearsof Envisat (cycles 10 to 72)
bull No Mean Profile can be used for Envisat on its new orbit (enn) Jason-1 on its geodetic orbit (j1g)because there is no repetitive track The MSS must be used instead (see below)
bull The Mean Profile used for GFO is computed with 7 years of GFO cycles 37 to 187
Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible
bull Indeed as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide precise cross-track projection andor interpolation schemes are required to avoid errors
bull The mesoscale variability error (which is lt35 cm for MP between 3 to 5 years and lt1cm for WLof 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a prioriknowledge from Sea Level maps derived from previous iterations or from other missions
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bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for ERS-1 for its 168 days geodetic mission (phases E-F from April1994 to March 1995) or for Envisat since november 2010 because the satellite is not in a repetitive orbitphase The alternative is to use the MSS instead The gridded MSS is derived from along track MPs anddata from geodetic phases Thus any error on the MP is also contained in the MSS There are essentially 4types of additional errors on gridded MSS which are hard to quantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
III362 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III363 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
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III37 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III371 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
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IV MYOCEAN PRODUCTS
IV1 Near Real Time Products
The purpose of the NRT DUACS component is the acquisition of altimeter data from various altimeter mis-sions in near-real time (ie within a few days at most) the validation and correction of these altimeter datasets (ie edition and selection update of corrections and homogenization orbit error reduction) in order toproduce each day along-track productsProducts are as follows
Along-track products global and regional (Mediterranean and Black Seas Arctic Ocean and Europeareas)
bull Sea Level Anomaly (NRT-SLA) for each mission with NRT-SLA ephemeris
IV11 Delay of the products
The availability of the products in near real time is three to twelve hours after the measurement for along-track products Those products are delivered every day
IV12 Temporal availibility
The following table presents the available products by mission and by data periodNear real time products
NRT Jason-2 Jason-1 and Jason-1geodetic
Envisat new Cryosat-2
Temporal Time availability ymlowast
ongoingymlowast-20120303 for
repeat track and20120507-ongoing for
geodetic track
ymlowast
2012040820120101
ongoing
NRT-SLA X X X X
lowastym the temporal coverage for NRT products is fluctuating and depends on updates of Delayed Time prod-ucts When DT products are updated (3 to 4 times per year) the oldest NRT products are replaced by thebetter quality DT products so that the 2 series are overlapping on few weeks or few months
IV2 Delayed Time Products
The Delayed Time component of SSALTODUACS system is responsible for the production of processedJason-1 Jason-2 TP Envisat GFO ERS12 and even Geosat data in order to provide a homogeneousinter-calibrated and highly accurate long time series of SLA DT products are more precise than NRT products Two reasons explain this quality difference The firstone is the better intrinsic quality of the POE orbit used in the GDR processing The second reason is that
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in the DT DUACS processing the products can be computed optimally with a centred computation timewindow for OER LWE On the contrary in NRT case future data are not available so the computationtime window is not centred and therefore not optimalAs for NRT products improved altimeter corrections and processing algorithms are used ocean tide modelto correct altimeter data improved methods for orbit error reduction and mapping
Along-Track products global and regional (Mediterranean and Black Seas)
bull Sea Level Anomaly (DT-SLA) for each mission
IV21 Delay of the products
Weekly products are delivered The availability of the products in delayed time is at the best two monthsafter the date of the measurement The product generation needs all the GDR data of all the missions to takeinto account the best corrections as possible The time delay can be longer in the case of a missing mission
IV22 Temporal availibility
The following table presents the available products by mission and by data periodDelayed time SSALTODUACS products
Upd Jason-2 Jason-1new6
Jason-1 GFO Envisatnew6
Envisat ERS-16
ERS-2Topexnew6
Topex
TemporalTimeavailabil-ity
200810ymlowast
200902ymlowast
200204200810
200001200809
201010ymlowast
200210201010
199210200304
200209200510
199209200204
DT-SLA X X X X X X X X X
lowast ym those dates are updated regularly (3 to 4 times per year) and are avalaible when you download thedata at httpwwwmyoceaneuweb24-cataloguephp6 Jason-1 new orbit starting 200809 Envisat new orbit starting 201010 TP new orbit starting 200209 ERS-1The geodetic phases (E-F) are included There are no ERS-1 data between December 23 1993 and April 10 1994(ERS-1 phase D - 2nd ice phase) Note that during that time products are based only on TopexPoseidon data
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V DESCRIPTION OF THE PRODUCT SPECIFICATION
V1 General information
Product Specification SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001
Geographical coverage global
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 20-50km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001 Product Specification
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Product Specification SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002
Geographical coverage 55˚W-35˚E 30˚N-46˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002 Product Specification
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Product Specification SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003
Geographical coverage 27˚E-42˚E 40˚N-47˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003 Product Specification
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Product Specification SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004
Geographical coverage 25˚W-42˚E 21˚N-66˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004 Product Specification
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Product Specification SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005
Geographical coverage 0˚W-360˚E 50˚N-82˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005 Product Specification
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VI NOMENCLATURE OF FILES
VI1 Nomenclature of files downloaded through the MyOcean Web PortalDirectgetfile Service
VI11 Nomenclature of the product line
The description of the syntax for the SL TAC SLA products line is given by
SEALEVEL_ltREGIONgt_SLA_L3_ltDELAYgt_OBSERVATIONS_008_ltZONEgt_ltLETTERgtwhere
REGION GLO global geographic coverage product
BS Black Sea products
MED Mediterranean products
ARC Arctic products (for NRT products)
EUROPE Europe products (for NRT products)
DELAY NRT near real time products
RAN delayed time or reanalysis products
ZONE 001 number on 3 digits
002
003
004
LETTER a letter on 1 digit
b
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VI12 Nomenclature of the datasets
The nomenclature used is
dataset-duacs-ltdelaygt-ltzonegt-ltmissiongt-lttype of slagt-l3where the fileds in ltgt are described below
delay nrt near-real time productsran delayed time products
zone global global geographic coverage productmedsea Mediterranean productsblacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1 (only for ran)e2 ERS-2 (only for ran)tp TOPEXPoseidon (only for ran)tpn TOPEXPoseidon on its new orbit (only for
ran)g2 GFO (only for ran)j1 Jason-1 (only for ran)j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisat (only for ran)enn Envisat on its new orbitc2 Cryosat-2 (only for nrt)
type of sla sla filtered slasla_unfiltered non filtered sla (only for ran products)
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VI13 Nomenclature of the NetCdf files
The nomenclature used is
ltdelaygt_ltzonegt_ltmissiongt_sla_ltvariablegt_ltdatebegingt_ltdateendgt_ltdateprodgtnc where the fileds in ltgt are de-scribed below
delay nrt near-real time productsdt delayed time products
zone global global geographic coverage productmed Mediterranean products (for dt)mfstep Mediterranean products (for nrt)blacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1e2 ERS-2tp TOPEXPoseidontpn TOPEXPoseidon on its new orbitg2 GFOj1 Jason-1j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisatenn Envisat on its new orbitc2 Cryosat-2
variable vfec filtered and sub-sampled slavxxc non filtered and non sub-sampled sla (only
for dt)datebegin YYYYMMDD() beginning date of the datasetdateend YYYYMMDD() end date of the datasetdateprod YYYYMMDD production date of the dataset
() For dt data as the dates in the file names are rounded the user wanting data for date T has to read the filescontaining dates T+1 and T-1 in their name and check inside the files if there are some data for date T
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VII DATA FORMAT
This chapter presents the data storage format used for MyOcean products
VII1 NetCdf
The products are stored using the NetCDF format NetCDF (network Common Data Form) is an interface for array-oriented data access and a library that provides an implementation of the interface The netCDF library also definesa machine-independent format for representing scientific data Together the interface library and format support thecreation access and sharing of scientific data The netCDF software was developed at the Unidata Program Center inBoulder Colorado The netCDF libraries define a machine-independent format for representing scientific data Pleasesee Unidata NetCDF pages for more information and to retreive NetCDF software package onhttpwwwunidataucaredupackagesnetcdfindexhtml
NetCDF data is
bull Self-Describing A netCDF file includes information about the data it contains
bull Architecture-independent A netCDF file is represented in a form that can be accessed by computers with dif-ferent ways of storing integers characters and floating-point numbers
bull Direct-access A small subset of a large dataset may be accessed efficiently without first reading through allthe preceding data
bull Appendable Data can be appended to a netCDF dataset along one dimension without copying the dataset orredefining its structure The structure of a netCDF dataset can be changed though this sometimes causes thedataset to be copied
bull Sharable One writer and multiple readers may simultaneously access the same netCDF file
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VII2 Structure and semantic of NetCDF along-track files
The NetCDF Sea Level TAC files are based on the attribute data tags defined by the Cooperative OceanAtmosphereResearch Data Service (COARDS) and Climate and Forecast (CF) metadata conventions The CF convention gener-alises and extends the COARDS convention but relaxes the COARDS constraints on dimension and order and specifiesmethods for reducing the size of datasetsA wide range of software are available to write or read NetCDFCF files API are made available by UNIDATA(httpwwwunidataucaredusoftwarenetcdf)
bull CC++Fortran
bull Java
bull MATLAB Objective-C Perl Python R Ruby TclTk
In addition to these conventions the files are using a common structure and semantic
bull 1 dimension is defined
ndash time it is used to check NetCDF variables depending on time
bull 8 variables are defined
ndash short SLA contains the Sea Level Anomaly values for each time given
ndash int longitude contains the longitude for each measurement
ndash short track contains the track number for each measurement
ndash double time contains the time in days since 1950-01-01 000000 UTC for each measurement
ndash short mean_profile_point_index index of the corrsponding point in the track of the mean profile
ndash byte flag flag=0 the processed data comes from OGDR if flag=1 the processed data comes from theIGDR
ndash int latitude contains the latitude for each measurement
ndash short cycle contains the cycle number for each measurement
bull global attributes
ndash the global attributes gives information about the creation of the file
Example of a NetCDF sla file
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netcdf nrt_global_j1_sla_vfec_20101230_20101230_20101230 dimensions
time = 10385 variables
short SLA(time) SLAcoordinates = longitude latitude SLAlong_name = Sea Level Anomaly SLA_FillValue = 32767s SLAadd_offset = 0 SLAscale_factor = 0001 SLAunits = m SLAstandard_name = sea_surface_height_above_sea_level
int longitude(time) longitudelong_name = Longitude of measurement longitude_FillValue = 2147483647 longitudeadd_offset = 0 longitudestandard_name = longitude longitudescale_factor = 1e-06 longitudeunits = degrees_east
short track(time) tracklong_name = Track in cycle the measurement belongs to track_FillValue = 32767s trackunits = 1 trackcoordinates = longitude latitude
double time(time) timelong_name = Time of measurement time_FillValue = 184467440737096e+19 timeaxis = T timestandard_name = time timeunits = days since 1950-01-01 000000 UTC
int latitude(time) latitudelong_name = Latitude of measurement latitude_FillValue = 2147483647 latitudeadd_offset = 0 latitudestandard_name = latitude latitudescale_factor = 1e-06 latitudeunits = degrees_north
short flag(time) flagcoordinates = longitude latitude flag_FillValue = 3267s flaglong_name = data origin flagflag_values = 1s 0s flagflag_meanings = igdr_like non_igdr_like flagcomment = The origin of the data is determined by the types of geophysical datarecords (GDR) used in computation of the SLA 1 for the Interim GDR (IGDR) and0 for Operational GDR (OGDR)
short cycle(time) cyclelong_name = Cycle the measurement belongs to cycle_FillValue = 32767s cycleunits = 1 cyclecoordinates = longitude latitude
global attributeshistory = 22-Feb-2011 155243 CET File created by the SSLATODUACS system version 1001 comment = Produce from ENVISAT Extension Phase satellite altimetry data institution = CLSCNES
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references = httpwwwavisooceanobscomfileadmindocumentsdatatoolshdbk_duacspdf source = satellite altimetry title = along track Sea Level Anomaly Conventions = CF-14
dataSLA =
7 7 11 10 -2 -22 -39 -41 -30 -13 -3 -5 -16 -26 -32 -35-35 -35 -37 -35 -31 -29 -31 -35 -32 -21 -10 -10 -19 -20 -1-69 -57 -49 -45 -39 -30 -28 -31 -27 -13 -2 -5 -15 -3 1112 3 -7 -10 -14 -15 -22 -31 -37 -32 -17 -10
longitude =74743328 74868400 74993968 75120040 75246616 7537372875501368 75629568 75758320 75887656 76017568 76148080 7627920876388952 76477056 76565456 76654144 76743128 76832400 76921984329429568 329535424 329641792 329748672 329856096 329964032330072512 330181536 330291072 330401184
track =92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 9292 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92113 113 113 113 113 113 113 113 113 113 113 113 113 113113 113 113 113 113 113 113 113 113
time =222780000565705 222780001314719 222780002063733222780002812747 222780003561761 222780004310775 222780005059788222780005808802 222780006557816 22278000730683 222780008055844222780008804858 222780009553872 22278001017805 222780010677393222788257112198 222788257486705 222788257861212 222788258235719222788258610226 222788258984733 222788259359239 222788259733746222788260108253 22278826048276
mean_profile_point_index =1872 1878 1884 1890 1896 1902 1908 19141920 1926 1932 1938 1944 1949 1953 1957 1961 1965 1969 19732306 2309 2312 2315 2318 2321 2327 2330 2333 2336 2339 23422345 2348 2351 2354 2357 2360 2363 2366
flag =0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
latitude =-16225506 -16539731 -16853833 -17167810 -17481660 -17795380-18108966 -18422418 -18735729 -19048899 -19361924 -19674801-19987527 -20248015 -20456329 -20664569 -20872739 -2108083739481297 39628277 39775133 39921866 40068472 40214953 4036130840507533 40653629 40799592 40945423 41091120 41236684 41382111
cycle =331 331 331 331 331 331 331 331 331 331 331 331 331
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331 331 331 331 331 331 331 331 331 331 331 331 331 331331 331 331 331 331 331 331 331 331 331 331 331
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VIII HOW TO DOWNLOAD A PRODUCT
VIII1 Download a product through the MyOcean Web Portal DirectgetfileService
You first need to register Please find below the registration stepshttpwwwmyoceaneuweb34-products-and-services-faqphp1Once registered the MyOcean FAQ httpwwwmyoceaneuweb34-products-and-services-faqwill guide you on How to download a product through the MyOcean Web Portal Directgetfile Service
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IX NEWS AND UPDATES
IX1 [Duacs] Operational news
To be kept informed on events occurring on the satellites and on the eventual interruption of the services of the DUACSprocessing system see the [Duacs] operational news on the Aviso websitehttpwwwavisooceanobscomendataoperational-newsindexhtml
IX2 Updates
To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtmlSince 2010 a complete reprocessing of all altimetry data (cumulated total of about 55 years of data) is available Themain changes introduced in the Duacs DT v300 reprocessed data set in SSALTODUACS reprocessed DT data setare listed herehttpwwwavisooceanobscomfileadmindocumentsdataduacsduacs_DT_2010_reprocessing_impactpdf
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Figure 5 SSALTODUACS processing sequences
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III2 Near Real Time processing steps
III21 Input data models and corrections applied
To produce SLA in near-real time the DUACS system uses two flows based on the same instrumental mea-surements but with a different quality
bull The IGDR that are the latest high-quality altimeter data produced in near-real-time
bull The OGDR that includes real time data (OSTMJason-2 and Jason-1 OSDR) to complete IGDR Thesefast delivery products do not always benefit from precise orbit determination nor from some exter-nal model-based corrections (Dynamic Atmospheric Correction (DAC) Global Ionospheric Maps(GIM))
Integration of OGDR data and the introduction of Jason-2Jason-1 tandem increased the resilience and pre-cision of the system A better restitution of ocean variability is observed especially in high energetic areas
Altimetric product Source Availability Type of orbit
Jason-2 IGDR CNES ~24h CNES MOE GDR-Cuntil 20120730
CNES MOE GDR-Dsince 20120731
OGDR NOAAEUMETSAT ~3 to 5 h
Jason-1 IGDR CNESNASA ~48 h CNES MOE GDR-Dsince 20120507
OGDR CNESNASA ~3 to 12 h
Envisat IGDR ESACNES not deliveredsince 20120408
CNES MOE GDR-Dsince 20120121
FDGDR ESA not deliveredsince 20120408
Cryosat-2 IGDR-like ESACNES ~48 h CNES MOE GDR-D
not delivered
Table 2 SSALTODUACS Near-Real Time Input data overview
See Figure 6 Overview of the near real time system data flow management
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DUACS 2011 NRT product from IGDR1
j2 j1nj1g enn c2Productstandard ref
version C until20120730 and D after
version C version 21 CPP [2]
Orbit CNES MOE GDR-Cuntil 20120730
GDR-D after
CNES MOE GDR-C forj1n and CNES MOE
GDR-D for j1g
CNES MOE GDR-Dfrom 20120121 to
20120408
CNES MOE GDR-D
Ionopheric bi-frequency altimeter range measurements GIM model for cgt64 (Iijima et al1998[24])Dry tropo Model computed from ECMWF Gaussian grids (new S1 and S2 atm tides applied)Wet tropo-sphere
AMR radiometer(enhancement in coastal
regions since20120730)
JMR radiometer MWR radiometer andcorrected from side
lobes
Model computed fromECMWF Gaussian
grids
DAC MOG2D High Resolution forced with ECMWF pressure and wind fields (S1 and S2 wereexcluded) (Carrere and Lyard 2003[3])+ inverse barometer Filtering temporal window is
un-centered (no data in the future)Ocean tide GOT4v8 (S1 and S2 are included) and TPX 072 [16] for Arctic productsPole tide [Wahr 1985 [53]]Solid earthtide
Elastic response to tidal potential [Cartwright and Tayler 1971[5]] [Cartwright andEdden 1973[6]]
Loading tide GOT4v8 (S1 and S2 are included)Sea statebias
Non parametric SSB[Labroue 2004[27]](with cycles J1 1 to 11
using GDR-B standardsuntil 20120730 andderived from Jason-2
after)
Non parametric SSB[Labroue 2004[27]](with cycles 1 to 21
using GDR-Bstandards)
Non parametric SSB[Labroue 2004[27]](with cycles 41 to 60
using GDR-Bstandards)
Same as Jason-2 SSB
Orbit error Global multi-mission crossover minimization (Le Traon and Ogor1998[32])
Long wave-lengh errors
Optimal Interpolation [Le Traon et al 1998[31]]
Intercalibration Reference from cycle20
Mean pro-file (seeIII261)
Computed with cycles11-353 TP data andwith cycles 11-250J1 data referenced[19931999]
TPNJ1N computedwith cycles 369-479TPN data refer-enced [19931999]J1G No MP can beused instead theMSS_CNES_CLS11[39] is used
No Mean Profilecan be used forEnvisat on its neworbit Instead theMSS_CNES_CLS11[39] is used
No Mean Profilecan be used forCryosat-2 Instead theMSS_CNES_CLS11[39] is used
(1) A flag included in the along-track files indicates the source of the production (OGDRFDGDR orIGDR) If flag=0 the processed data comes from OGDRsFDGDRs if flag=1 the processed data comesfrom IGDRs
Table 3 Corrections and models applied in SSALTODUACS NRT products produced from IGDRs
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DUACS 2011 NRT product from OGDR or FDGDR2
j2 j1nj1g ennProduct stan-dard ref
version C until 20120730and D after
version C version 21
Orbit Navigator Extrapolated CNES MOEGDR-D since 20120121
Ionopheric From-dual frequency altimeter range measurements From GIM model fromcycle 65 (Iijima et al1998 [24])
Dry troposphere Model computed from ECMWF Gaussian grids (new S1 and S2 atmospherictides are applied)
Wet tropo-sphere
AMR radiometer(enhancement in coastal
regions since 20120730)
JMR radiometer MWR radiometer andcorrected from side lobes
DAC Inverse Barometer forecastedOcean tide GOT4v8 (S1 and S2 are included) and TPX 072 [16] for Arctic productsPole tide [Wahr 1985 [53]]Solid earth tide Elastic response to tidal potential [Cartwright and Tayler 1971[5]]
[Cartwright and Edden 1973[6]]Loading tide GOT4v8 (S1 and S2 are included)Sea state bias Non parametric SSB
[Labroue 2004[27]] (withcycles J1 1 to 11 usingGDR-B standards until20120730 and derivedfrom Jason-2 after)
Non parametric SSB[Labroue 2004[27]](with cycles 1 to 21 usingGDR-B standards)
Non parametric SSB[Labroue 2004[27]](with cycles 41 to 60using GDR-B standards)
Orbit error Specific filtering of long-wavelength signal3
Long wave-lengh errors
Optimal Interpolation [Le Traon et al 1998[31]]
Intercalibration Reference from cycle 20Mean profile(see III261)
Computed with cycles 11-353 TP data and with cy-cles 11-250 J1 data refer-enced [19931999]
TPNJ1N computedwith cycles 369-479TPN data referenced[19931999] J1G NoMP can be used insteadthe MSS_CNES_CLS11[39] is used
No Mean Profile can beused for Envisat on itsnew orbit Instead theMSS_CNES_CLS11 [39]is used
(2) A flag included in the along-track files indicates the source of the production (OGDRFDGDR orIGDR) If flag=0 the processed data comes from OGDRsFDGDRs if flag=1 the processed data comesfrom IGDRs(3) Specific data processing was applied on long wave-length signal (sectIII23 of the user manual)
Table 4 Corrections and models applied in SSALTODUACS NRT products produced from OG-DRsFDGDRs
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III22 Acquisition
The acquisition process is twofold
bull straightforward retrieval and reformatting of altimeter data and dynamic auxiliary data (pressure andwet troposphere correction grids from ECMWF are provided by Meteo France TEC grids from JPLNRT MOG2D corrections) from external repositories
bull synchronisation process
To be homogenized properly altimeter data sets require various auxiliary data The acquisition softwaredetects downloads and processes incoming data as soon as they are available on remote sites (externaldatabase FTP site) Data are split into passes if necessary If data flows are missing or late the synchroni-sation engine put unusable data in waiting queues and automatically unfreezes them upon reception of themissing auxiliary data This processing step delivers raw data that is to say data that have been dividedinto cycles and passes and ordered chronologicallyFrom SSALTODUACS V80 the acquisition step uses two different data flows in near-real time the OGDRflow (within a few hours) and the IGDR flow (within a few days)For each OGDR input the system checks that no equivalent IGDR entry is available in the data base beforeacquisition for each IGDR input the system checks and delete the equivalent OGDR entry in the data baseThese operations aim to avoid duplicates in SSALTODUACS system
Figure 6 Overview of the near real time system data flow management
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III23 Homogenization
The Homogenization process consists in applying the most recent corrections models and references rec-ommended for altimeter products Each mission is processed separately as its needs depend on the baseinput data The list of corrections and models currently applied is provided in tables 3 and 4 for NRT dataThe system includes SLA filtering to process OGDR data DUACS extract from these data sets the shortscales (space and time) which are useful to better describe the ocean variability in real time and merge thisinformation with a fair description of large scale signals provided by the multi-satellite observation in nearreal time (read IGDR-based DUACS data) Finally an hybrid SLA is computed
Figure 7 Merging pertinent information from IGDR and OGDR processing
III24 Input data quality control
The Input Data Quality Control is a critical process applied to guarantee that DUACS uses only the mostaccurate altimeter data Thanks to the high quality of current missions this process rejects a small percent-age of altimeter measurements but these erroneous data could be the cause of a significant quality lossThe quality control relies on standard raw data editing with quality flags or parameter thresholds but alsoon complex data editing algorithms based on the detection of erroneous artefacts mono and multi-missioncrossover validation and macroscopic statistics to edit out large data flows that do not meet the systemrsquosrequirements
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III25 Multi-mission cross-calibration
The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistentand accurate information It removes any residual orbit error (OE Le Traon and Ogor 1998[32]) or longwavelength error (LWE Le Traon et al 1998[31]) as well as large scale biases and discrepancies betweenvarious data flows
This process is based on two very different algorithms a global multi-mission crossover minimization fororbit error reduction (OER) and Optimal Interpolation (OI) for LWE
Multi-satellite crossover determination is performed on a daily basis All altimeter fields (measurementcorrections and other fields such as bathymetry MSS) are interpolated at crossover locations and datesCrossovers are then appended to the existing crossover database as more altimeter data become availableThis crossover data set is the input of the Orbit Error Reduction (OER) method Using the precision of thereference mission orbit a very accurate orbit error can be estimated This processing step does not concernOGDR dataLWE is mostly due to residual tidal or inverse barometer errors and high frequency ocean signals The OIused for LWE reduction uses precise parameters derived from
bull accurate statistical description of sea level variability
bull localized correlation scales
bull mission-specific noise and precise assumptions on the long wavelength errors to be removed (from arecent analysis of one year of data from each mission)
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III26 Product generation
The product generation process is composed of four steps computation of raw SLA cross-validationfilteringampsub-sampling and generation of by-products
III261 Computation of raw SLA
Since the geoid is not well known yet the SSH cannot be used directly the SSH anomalies are used insteadThey are computed from the difference of the instantaneous SSH - a temporal reference This temporalreference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeattrack analysis cannot be used The errors affecting the SLAs MPs and MSS have different magnitudes andwavelengths The computation of the SLAs and their errors associated are detailed in Dibarboure et al 2010[9]
Use of a Mean ProfileIn the repeat track analysis (when the satellites flies over a repetitive orbit) measurements are re-sampledalong a theoretical ground track (or mean track) associated to each mission Then a Mean Profile (MP) issubtracted from the re-sampled data to obtain SLA The MP is a time average of similarly re-sampled dataover a long period
bull The Mean Profile used for Jason-2 is computed with 10 years of TP (cycles 11 to 353) and 6 years ofJason-1 (cycles 11 to 250)
bull The Mean Profile used from Jason-1 cycle 262 to 374 (where satellites are on interleaved ground-tracks) is computed with 3 years of TP (cycles 369 to 479)
bull No Mean Profile can be used for Envisat on its new orbit (enn) Jason-1 on its geodetic orbit (j1g) norfor Cryosat-2 mission (c2) because there is no repetitive track The MSS must be used instead (seebelow)
Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible
bull Indeed as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide precise cross-track projection andor interpolation schemes are required to avoid errors
bull The mesoscale variability error (which is lt35 cm for MP between 3 to 5 years and lt1cm for WLof 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a prioriknowledge from Sea Level maps derived from previous iterations or from other missions
bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
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PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for Envisat since november 2010 and for Cryosat-2 mission (c2)because the satellite is not in a repetitive orbit phase The alternative is to use the MSS instead The griddedMSS is derived from along track MPs and data from geodetic phases Thus any error on the MP is alsocontained in the MSS There are essentially 4 types of additional errors on gridded MSS which are hard toquantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
Note that for the Arctic regional products the DTU10 MSS [1] is taken into account instead of the CLS01MSS Indeed the accuracy of DTU10 compared to CLS01 is further demonstrated by the significant sealevel anomaly variance reduction found over the whole Arctic Ocean as shown in Prandi et al [42]
III262 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III263 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
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III27 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III271 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
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III272 Performance indicators
To appreciate the quality situation of the DUACS system new performance indicators are computed dailyThey aim at evaluate the status of the main processing steps of the system the input data availability theinput data coverage the input data quality and the output product quality These indicators are computed foreach and every currently working satellite and combined to obtain the overall status
Figure 8 Example with the key performance indicator on 20090627
See the description the latest and previous indicators on Aviso websitehttpwwwavisooceanobscomindexphpid=1516
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PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III3 Delayed Time processing steps
III31 Input data models and corrections applied
Delayed Time MyOcean products are generated
bull from Aviso GDR products for TP Jason-1 Jason-2 and Envisat (GDR-A cycles 1 to 22 GDR-Bcycles 23 to 85 GDR-C from cycle 86)
bull from NOAA GDR for GFO and from CERSAT (IFREMER) OPR for ERS-1 and ERS-2 (phases C(1st 35-day repeat orbit period) phase E and F (geodetic phases) phase G for ERS-1 (last 35-dayrepeat orbit period tandem phase with ERS-2 phase A for ERS-2 (1st 35-day repeat orbit periodtandem phase with ERS-1))
All GDR products are computed with a Precise Orbit Ephemeris (POE) and are delivered within 2 to 3months depending on the mission For several missions an updated orbit is used
bull For ERS-1amp-2 the orbit used is DGME-04 provided by Delft Institute (httpwwwdeostudelftnl)until June 2003
bull For TopexPoseidon the orbit used is GSFC (std0809) for the whole mission
bull For Envisat CNES POE of GDR-C standard is used for the whole mission
bull For the whole GFO mission the orbit used is GSFC (std0809) and when not available NASA POE isused
Altimetric product Source Availability Type of orbit
TopexPoseidon GDR NASACNES - GSFC POE
Jason-1 GDR (GDR-C) CNESNASA ~40 days CNES POE
Jason-2 GDR (GDR-C) CNESNASA ~60 days CNES POE
GFO GDR NOAA - GSFCNASA POE
ERS-1amp2 IFREMERESA - DGME-04
Envisat (GDR-A GDR-B andGDR-C from cycle 86)
ESA ~2 months CNES POE
Table 5 SSALTODUACS Delayed Time Input data overview
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DU
AC
S20
11D
Tpr
oduc
t(gtV
30
0)j2
j1j1
ntp
tpn
e1e2
ene
nng2
Prod
uct
stan
dard
ref
GD
R-C
OPR
GD
R-A
(Cyc
les
1to
22)
GD
R-B
(cyc
les
23-8
5)
GD
R(N
OA
A)
Orb
itC
nes
POE
GSF
C(I
TR
F20
05G
RA
CE
last
stan
dard
s)
DG
ME
-04
(Sch
arro
oan
dV
isse
r19
98[4
8]C
NE
SPO
E(G
DR
-1st
anda
rds
forc
ycle
s9
to22
GD
R-C
stan
dard
sfr
omcy
cle
23)
GSF
C(I
TR
F20
05
GR
AC
Ela
stst
anda
rds
Iono
pher
icD
ual f
requ
ency
altim
eter
rang
em
easu
rem
ents
Dua
l fre
quen
cyal
timet
erra
nge
mea
sure
men
ts(T
opex
)D
OR
IS(P
OSE
IDO
N)
Ben
t mod
elB
ent m
odel
(cyc
les
1-36
)G
IMm
odem
from
cycl
e37
((Ii
jima
etal
19
98[2
4])
Dua
l-fr
eque
ncy
altim
eter
rang
em
easu
rem
ent(
cycl
e9-
64)a
ndG
IMm
odel
gtcyc
le65
(Iiji
ma
etal
19
99[2
4])c
orre
cted
from
8m
mbi
as
From
GIM
mod
el(I
ijim
aet
al1
998
[24]
)
Dry
trop
o-sp
here
Mod
elco
mpu
ted
from
EC
MW
FG
auss
ian
grid
s(n
ewS1
and
S2at
mos
pher
ictid
esar
eap
plie
d)
Mod
elco
mpu
ted
from
EC
MW
Fre
ctan
gula
rgri
ds(n
ewS1
and
S2at
mos
pher
ictid
esar
ein
clud
ed)
Wet
trop
o-sp
here
JMR
AM
Rra
diom
eter
furt
hert
han
50km
from
the
coas
tsF
rom
EC
MW
Fm
odel
ford
ista
nces
betw
een
10an
d50
km
TM
Rra
diom
eter
(Sch
aroo
etal
20
04[4
9])
MW
RC
orre
ctio
nof
the
drif
ton
the
236
GH
zbr
ight
ness
tem
pera
ture
(Sch
arro
oet
al
2004
[49]
)Neu
ral
Net
wor
kal
gori
thm
(Tra
nan
dO
blig
is
2003
[50]
MW
Rra
diom
eter
furt
hert
han
50km
from
the
coas
tsan
dco
rrec
ted
from
side
lobe
s(f
rom
cycl
e41
)E
CM
WF
mod
elfo
rdis
tanc
esbe
twee
n10
and
50km
GFO
radi
omet
er
DA
CM
OG
2DH
igh
Res
olut
ion
forc
edw
ithE
CM
WF
pres
sure
and
win
gfie
lds
(S1
and
S2w
ere
excl
uded
)+in
vers
eba
rom
eter
com
pute
dfr
omre
ctan
gula
rgri
ds
Tabl
e6
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(1
2)
Page 33
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
j2j1
j1n
tptp
ne1
e2en
enn
g2O
cean
tide
GO
T4v
7(S
1an
dS2
are
incl
uded
)Po
letid
e[W
ahr
1985
[53]
]So
lidea
rth
tide
Ela
stic
resp
onse
totid
alpo
tent
ial[
Car
twri
ghta
ndTa
yler
197
1[5]
][C
artw
righ
tand
Edd
en1
973[
6]]
Loa
ding
tide
GO
T4v
7(S
1pa
ram
eter
isin
clud
ed)
Sea
stat
ebi
asN
onpa
ram
etri
cSS
B[G
aspa
reta
l20
02[2
0]]
Non
para
met
ric
SSB
[NT
ran
and
al2
010[
51]]
BM
3[G
aspa
ran
dO
gor
1994
[17]
]
Non
para
met
ric
SSB
[Mer
tzet
al
2005
[38]
]
Non
para
met
ric
SSB
[Gas
pare
tal
2002
]w
ithG
DR
-Bst
anda
rds
forc
ycle
s9
to85
and
with
GD
R-C
stan
dard
sfr
omcy
cle
86
Non
para
met
ric
SSB
[NT
ran
etal
20
10[5
1]]
Orb
iter
ror
Glo
bal m
ulti-
mis
sion
cros
sove
rmin
imiz
atio
n(L
eTr
aon
and
Ogo
r19
98[3
2])
Lon
gw
ave-
leng
her
rors
Opt
imal
Inte
rpol
atio
n(L
eTr
aon
etal
19
98[3
1])
Inte
rcal
ibra
tion
Ref
eren
cefr
omcy
cle
11R
efer
ence
from
cycl
e1
to35
4C
orre
ctio
nof
regi
onal
bias
J2J
1de
duce
dfr
omin
terc
alib
ratio
nph
ase
(cyc
le11
J2)
Cor
rect
ion
ofgl
obal
biai
sJ1
TP
deacutedu
ced
from
inte
rcal
ibra
tion
phas
e(c
ycle
s11
J1)
Mea
npr
o-fil
e(s
eeII
I36
1)
Com
pute
dw
ithcy
cles
11-3
53T
Pda
taan
dw
ithcy
cles
11-2
50J1
data
ref
eren
ced
[199
319
99]
TP
J1 c
ompu
ted
with
cycl
es11
-353
TP
data
and
with
cycl
es11
-250
J1da
tar
efer
ence
d[1
993
1999
]T
PNJ
1Nc
ompu
ted
with
cycl
es36
9-47
9T
PNda
tar
efer
ence
d[1
993
1999
]
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
ref
eren
ced
[199
319
99]
EN
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
re
fere
nced
[199
319
99]
EN
Nu
seof
MSS
_CN
ES_
CL
S11
[39]
Com
pute
dw
ithcy
cles
37-1
87G
2da
ta
refe
renc
ed[1
993
1999
]
Peri
odof
use
from
cycl
e9
from
cycl
e9
cycl
es1
to48
1cy
cles
15to
43In
clud
ing
E-F
geod
etic
phas
es
cycl
es1
to83
from
cycl
e9
cycl
es37
to22
2
Tabl
e7
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(2
2)
Page 34
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III32 Acquisition
The acqusition process in Delayed time is much simpler than in Near Real time it consists in a synchronisa-tion process of all the auxiliary data required to homogenize propely the altimeter data sets The acquisitionstep uses the GDRs or the OPRs provided by the agencies
III33 Homogenization
The Homogenization process consists in applying the most recent corrections models and references rec-ommended for altimeter products Each mission is processed separately as its needs depend on the baseinput data The list of corrections and models currently applied is provided in tables 6 and 7 for DT data
III34 Input data quality control
The Input Data Quality Control is a critical process applied to guarantee that DUACS uses only the mostaccurate altimeter data Thanks to the high quality of current missions this process rejects a small percent-age of altimeter measurements but these erroneous data could be the cause of a significant quality lossThe quality control relies on standard raw data editing with quality flags or parameter thresholds but alsoon complex data editing algorithms based on the detection of erroneous artefacts mono and multi-missioncrossover validation and macroscopic statistics to edit out large data flows that do not meet the systemrsquosrequirements
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III35 Multi-mission cross-calibration
The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistentand accurate information It removes any residual orbit error (OE Le Traon and Ogor 1998[32]) or longwavelength error (LWE Le Traon et al 1998[31]) as well as large scale biases and discrepancies betweenvarious data flows
This process is based on two very different algorithms a global multi-mission crossover minimization fororbit error reduction (OER) and Optimal Interpolation (OI) for LWE
Multi-satellite crossover determination is performed on a daily basis All altimeter fields (measurementcorrections and other fields such as bathymetry MSS) are interpolated at crossover locations and datesCrossovers are then appended to the existing crossover database as more altimeter data become availableThis crossover data set is the input of the Orbit Error Reduction (OER) method Using the precision of thereference mission orbit a very accurate orbit error can be estimated LWE is mostly due to residual tidalor inverse barometer errors and high frequency ocean signals The OI used for LWE reduction uses preciseparameters derived from
bull accurate statistical description of sea level variability
bull localized correlation scales
bull mission-specific noise and precise assumptions on the long wavelength errors to be removed (from arecent analysis of one year of data from each mission)
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III36 Product generation
The product generation process is composed of four steps computation of raw SLA cross-validationfilteringampsub-sampling and generation of by-products
III361 Computation of raw SLA
Since the geoid is not well known yet the SSH cannot be used directly the SSH anomalies are used insteadThey are computed from the difference of the instantaneous SSH - a temporal reference This temporalreference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeattrack analysis cannot be used The errors affecting the SLAs MPs and MSS have different magnitudes andwavelengths The computation of the SLAs and their errors associated are detailed in Dibarboure et al 2010[9]
Use of a Mean ProfileIn the repeat track analysis (when the satellites flies over a repetitive orbit) measurements are re-sampledalong a theoretical ground track (or mean track) associated to each mission Then a Mean Profile (MP) issubtracted from the re-sampled data to obtain SLA The MP is a time average of similarly re-sampled dataover a long period
bull The Mean Profile used for TP (cycles 1 to 364) Jason-1 (cycles 1 to 259) and Jason-2 is computedwith 10 years of TP (cycles 11 to 353) and 6 years of Jason-1 (cycles 11 to 250)
bull The Mean Profile used for TP (cycles 368 to 481) and from Jason-1 cycle 262 to 374 (where satellitesare on interleaved ground-tracks) is computed with 3 years of TP (cycles 369 to 479)
bull The Mean Profile used for ERS-1 in its 35 days repetitive orbit mission ERS-2 and Envisat (only forthe first orbit before November 2010) is computed with 8 years of ERS-2 (cycles 1 to 85) and 6 yearsof Envisat (cycles 10 to 72)
bull No Mean Profile can be used for Envisat on its new orbit (enn) Jason-1 on its geodetic orbit (j1g)because there is no repetitive track The MSS must be used instead (see below)
bull The Mean Profile used for GFO is computed with 7 years of GFO cycles 37 to 187
Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible
bull Indeed as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide precise cross-track projection andor interpolation schemes are required to avoid errors
bull The mesoscale variability error (which is lt35 cm for MP between 3 to 5 years and lt1cm for WLof 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a prioriknowledge from Sea Level maps derived from previous iterations or from other missions
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bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for ERS-1 for its 168 days geodetic mission (phases E-F from April1994 to March 1995) or for Envisat since november 2010 because the satellite is not in a repetitive orbitphase The alternative is to use the MSS instead The gridded MSS is derived from along track MPs anddata from geodetic phases Thus any error on the MP is also contained in the MSS There are essentially 4types of additional errors on gridded MSS which are hard to quantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
III362 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III363 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
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III37 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III371 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
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IV MYOCEAN PRODUCTS
IV1 Near Real Time Products
The purpose of the NRT DUACS component is the acquisition of altimeter data from various altimeter mis-sions in near-real time (ie within a few days at most) the validation and correction of these altimeter datasets (ie edition and selection update of corrections and homogenization orbit error reduction) in order toproduce each day along-track productsProducts are as follows
Along-track products global and regional (Mediterranean and Black Seas Arctic Ocean and Europeareas)
bull Sea Level Anomaly (NRT-SLA) for each mission with NRT-SLA ephemeris
IV11 Delay of the products
The availability of the products in near real time is three to twelve hours after the measurement for along-track products Those products are delivered every day
IV12 Temporal availibility
The following table presents the available products by mission and by data periodNear real time products
NRT Jason-2 Jason-1 and Jason-1geodetic
Envisat new Cryosat-2
Temporal Time availability ymlowast
ongoingymlowast-20120303 for
repeat track and20120507-ongoing for
geodetic track
ymlowast
2012040820120101
ongoing
NRT-SLA X X X X
lowastym the temporal coverage for NRT products is fluctuating and depends on updates of Delayed Time prod-ucts When DT products are updated (3 to 4 times per year) the oldest NRT products are replaced by thebetter quality DT products so that the 2 series are overlapping on few weeks or few months
IV2 Delayed Time Products
The Delayed Time component of SSALTODUACS system is responsible for the production of processedJason-1 Jason-2 TP Envisat GFO ERS12 and even Geosat data in order to provide a homogeneousinter-calibrated and highly accurate long time series of SLA DT products are more precise than NRT products Two reasons explain this quality difference The firstone is the better intrinsic quality of the POE orbit used in the GDR processing The second reason is that
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in the DT DUACS processing the products can be computed optimally with a centred computation timewindow for OER LWE On the contrary in NRT case future data are not available so the computationtime window is not centred and therefore not optimalAs for NRT products improved altimeter corrections and processing algorithms are used ocean tide modelto correct altimeter data improved methods for orbit error reduction and mapping
Along-Track products global and regional (Mediterranean and Black Seas)
bull Sea Level Anomaly (DT-SLA) for each mission
IV21 Delay of the products
Weekly products are delivered The availability of the products in delayed time is at the best two monthsafter the date of the measurement The product generation needs all the GDR data of all the missions to takeinto account the best corrections as possible The time delay can be longer in the case of a missing mission
IV22 Temporal availibility
The following table presents the available products by mission and by data periodDelayed time SSALTODUACS products
Upd Jason-2 Jason-1new6
Jason-1 GFO Envisatnew6
Envisat ERS-16
ERS-2Topexnew6
Topex
TemporalTimeavailabil-ity
200810ymlowast
200902ymlowast
200204200810
200001200809
201010ymlowast
200210201010
199210200304
200209200510
199209200204
DT-SLA X X X X X X X X X
lowast ym those dates are updated regularly (3 to 4 times per year) and are avalaible when you download thedata at httpwwwmyoceaneuweb24-cataloguephp6 Jason-1 new orbit starting 200809 Envisat new orbit starting 201010 TP new orbit starting 200209 ERS-1The geodetic phases (E-F) are included There are no ERS-1 data between December 23 1993 and April 10 1994(ERS-1 phase D - 2nd ice phase) Note that during that time products are based only on TopexPoseidon data
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V DESCRIPTION OF THE PRODUCT SPECIFICATION
V1 General information
Product Specification SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001
Geographical coverage global
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 20-50km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001 Product Specification
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Product Specification SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002
Geographical coverage 55˚W-35˚E 30˚N-46˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002 Product Specification
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Product Specification SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003
Geographical coverage 27˚E-42˚E 40˚N-47˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003 Product Specification
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Product Specification SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004
Geographical coverage 25˚W-42˚E 21˚N-66˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004 Product Specification
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Product Specification SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005
Geographical coverage 0˚W-360˚E 50˚N-82˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005 Product Specification
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VI NOMENCLATURE OF FILES
VI1 Nomenclature of files downloaded through the MyOcean Web PortalDirectgetfile Service
VI11 Nomenclature of the product line
The description of the syntax for the SL TAC SLA products line is given by
SEALEVEL_ltREGIONgt_SLA_L3_ltDELAYgt_OBSERVATIONS_008_ltZONEgt_ltLETTERgtwhere
REGION GLO global geographic coverage product
BS Black Sea products
MED Mediterranean products
ARC Arctic products (for NRT products)
EUROPE Europe products (for NRT products)
DELAY NRT near real time products
RAN delayed time or reanalysis products
ZONE 001 number on 3 digits
002
003
004
LETTER a letter on 1 digit
b
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VI12 Nomenclature of the datasets
The nomenclature used is
dataset-duacs-ltdelaygt-ltzonegt-ltmissiongt-lttype of slagt-l3where the fileds in ltgt are described below
delay nrt near-real time productsran delayed time products
zone global global geographic coverage productmedsea Mediterranean productsblacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1 (only for ran)e2 ERS-2 (only for ran)tp TOPEXPoseidon (only for ran)tpn TOPEXPoseidon on its new orbit (only for
ran)g2 GFO (only for ran)j1 Jason-1 (only for ran)j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisat (only for ran)enn Envisat on its new orbitc2 Cryosat-2 (only for nrt)
type of sla sla filtered slasla_unfiltered non filtered sla (only for ran products)
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VI13 Nomenclature of the NetCdf files
The nomenclature used is
ltdelaygt_ltzonegt_ltmissiongt_sla_ltvariablegt_ltdatebegingt_ltdateendgt_ltdateprodgtnc where the fileds in ltgt are de-scribed below
delay nrt near-real time productsdt delayed time products
zone global global geographic coverage productmed Mediterranean products (for dt)mfstep Mediterranean products (for nrt)blacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1e2 ERS-2tp TOPEXPoseidontpn TOPEXPoseidon on its new orbitg2 GFOj1 Jason-1j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisatenn Envisat on its new orbitc2 Cryosat-2
variable vfec filtered and sub-sampled slavxxc non filtered and non sub-sampled sla (only
for dt)datebegin YYYYMMDD() beginning date of the datasetdateend YYYYMMDD() end date of the datasetdateprod YYYYMMDD production date of the dataset
() For dt data as the dates in the file names are rounded the user wanting data for date T has to read the filescontaining dates T+1 and T-1 in their name and check inside the files if there are some data for date T
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VII DATA FORMAT
This chapter presents the data storage format used for MyOcean products
VII1 NetCdf
The products are stored using the NetCDF format NetCDF (network Common Data Form) is an interface for array-oriented data access and a library that provides an implementation of the interface The netCDF library also definesa machine-independent format for representing scientific data Together the interface library and format support thecreation access and sharing of scientific data The netCDF software was developed at the Unidata Program Center inBoulder Colorado The netCDF libraries define a machine-independent format for representing scientific data Pleasesee Unidata NetCDF pages for more information and to retreive NetCDF software package onhttpwwwunidataucaredupackagesnetcdfindexhtml
NetCDF data is
bull Self-Describing A netCDF file includes information about the data it contains
bull Architecture-independent A netCDF file is represented in a form that can be accessed by computers with dif-ferent ways of storing integers characters and floating-point numbers
bull Direct-access A small subset of a large dataset may be accessed efficiently without first reading through allthe preceding data
bull Appendable Data can be appended to a netCDF dataset along one dimension without copying the dataset orredefining its structure The structure of a netCDF dataset can be changed though this sometimes causes thedataset to be copied
bull Sharable One writer and multiple readers may simultaneously access the same netCDF file
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VII2 Structure and semantic of NetCDF along-track files
The NetCDF Sea Level TAC files are based on the attribute data tags defined by the Cooperative OceanAtmosphereResearch Data Service (COARDS) and Climate and Forecast (CF) metadata conventions The CF convention gener-alises and extends the COARDS convention but relaxes the COARDS constraints on dimension and order and specifiesmethods for reducing the size of datasetsA wide range of software are available to write or read NetCDFCF files API are made available by UNIDATA(httpwwwunidataucaredusoftwarenetcdf)
bull CC++Fortran
bull Java
bull MATLAB Objective-C Perl Python R Ruby TclTk
In addition to these conventions the files are using a common structure and semantic
bull 1 dimension is defined
ndash time it is used to check NetCDF variables depending on time
bull 8 variables are defined
ndash short SLA contains the Sea Level Anomaly values for each time given
ndash int longitude contains the longitude for each measurement
ndash short track contains the track number for each measurement
ndash double time contains the time in days since 1950-01-01 000000 UTC for each measurement
ndash short mean_profile_point_index index of the corrsponding point in the track of the mean profile
ndash byte flag flag=0 the processed data comes from OGDR if flag=1 the processed data comes from theIGDR
ndash int latitude contains the latitude for each measurement
ndash short cycle contains the cycle number for each measurement
bull global attributes
ndash the global attributes gives information about the creation of the file
Example of a NetCDF sla file
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netcdf nrt_global_j1_sla_vfec_20101230_20101230_20101230 dimensions
time = 10385 variables
short SLA(time) SLAcoordinates = longitude latitude SLAlong_name = Sea Level Anomaly SLA_FillValue = 32767s SLAadd_offset = 0 SLAscale_factor = 0001 SLAunits = m SLAstandard_name = sea_surface_height_above_sea_level
int longitude(time) longitudelong_name = Longitude of measurement longitude_FillValue = 2147483647 longitudeadd_offset = 0 longitudestandard_name = longitude longitudescale_factor = 1e-06 longitudeunits = degrees_east
short track(time) tracklong_name = Track in cycle the measurement belongs to track_FillValue = 32767s trackunits = 1 trackcoordinates = longitude latitude
double time(time) timelong_name = Time of measurement time_FillValue = 184467440737096e+19 timeaxis = T timestandard_name = time timeunits = days since 1950-01-01 000000 UTC
int latitude(time) latitudelong_name = Latitude of measurement latitude_FillValue = 2147483647 latitudeadd_offset = 0 latitudestandard_name = latitude latitudescale_factor = 1e-06 latitudeunits = degrees_north
short flag(time) flagcoordinates = longitude latitude flag_FillValue = 3267s flaglong_name = data origin flagflag_values = 1s 0s flagflag_meanings = igdr_like non_igdr_like flagcomment = The origin of the data is determined by the types of geophysical datarecords (GDR) used in computation of the SLA 1 for the Interim GDR (IGDR) and0 for Operational GDR (OGDR)
short cycle(time) cyclelong_name = Cycle the measurement belongs to cycle_FillValue = 32767s cycleunits = 1 cyclecoordinates = longitude latitude
global attributeshistory = 22-Feb-2011 155243 CET File created by the SSLATODUACS system version 1001 comment = Produce from ENVISAT Extension Phase satellite altimetry data institution = CLSCNES
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references = httpwwwavisooceanobscomfileadmindocumentsdatatoolshdbk_duacspdf source = satellite altimetry title = along track Sea Level Anomaly Conventions = CF-14
dataSLA =
7 7 11 10 -2 -22 -39 -41 -30 -13 -3 -5 -16 -26 -32 -35-35 -35 -37 -35 -31 -29 -31 -35 -32 -21 -10 -10 -19 -20 -1-69 -57 -49 -45 -39 -30 -28 -31 -27 -13 -2 -5 -15 -3 1112 3 -7 -10 -14 -15 -22 -31 -37 -32 -17 -10
longitude =74743328 74868400 74993968 75120040 75246616 7537372875501368 75629568 75758320 75887656 76017568 76148080 7627920876388952 76477056 76565456 76654144 76743128 76832400 76921984329429568 329535424 329641792 329748672 329856096 329964032330072512 330181536 330291072 330401184
track =92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 9292 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92113 113 113 113 113 113 113 113 113 113 113 113 113 113113 113 113 113 113 113 113 113 113
time =222780000565705 222780001314719 222780002063733222780002812747 222780003561761 222780004310775 222780005059788222780005808802 222780006557816 22278000730683 222780008055844222780008804858 222780009553872 22278001017805 222780010677393222788257112198 222788257486705 222788257861212 222788258235719222788258610226 222788258984733 222788259359239 222788259733746222788260108253 22278826048276
mean_profile_point_index =1872 1878 1884 1890 1896 1902 1908 19141920 1926 1932 1938 1944 1949 1953 1957 1961 1965 1969 19732306 2309 2312 2315 2318 2321 2327 2330 2333 2336 2339 23422345 2348 2351 2354 2357 2360 2363 2366
flag =0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
latitude =-16225506 -16539731 -16853833 -17167810 -17481660 -17795380-18108966 -18422418 -18735729 -19048899 -19361924 -19674801-19987527 -20248015 -20456329 -20664569 -20872739 -2108083739481297 39628277 39775133 39921866 40068472 40214953 4036130840507533 40653629 40799592 40945423 41091120 41236684 41382111
cycle =331 331 331 331 331 331 331 331 331 331 331 331 331
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331 331 331 331 331 331 331 331 331 331 331 331 331 331331 331 331 331 331 331 331 331 331 331 331 331
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VIII HOW TO DOWNLOAD A PRODUCT
VIII1 Download a product through the MyOcean Web Portal DirectgetfileService
You first need to register Please find below the registration stepshttpwwwmyoceaneuweb34-products-and-services-faqphp1Once registered the MyOcean FAQ httpwwwmyoceaneuweb34-products-and-services-faqwill guide you on How to download a product through the MyOcean Web Portal Directgetfile Service
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IX NEWS AND UPDATES
IX1 [Duacs] Operational news
To be kept informed on events occurring on the satellites and on the eventual interruption of the services of the DUACSprocessing system see the [Duacs] operational news on the Aviso websitehttpwwwavisooceanobscomendataoperational-newsindexhtml
IX2 Updates
To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtmlSince 2010 a complete reprocessing of all altimetry data (cumulated total of about 55 years of data) is available Themain changes introduced in the Duacs DT v300 reprocessed data set in SSALTODUACS reprocessed DT data setare listed herehttpwwwavisooceanobscomfileadmindocumentsdataduacsduacs_DT_2010_reprocessing_impactpdf
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III2 Near Real Time processing steps
III21 Input data models and corrections applied
To produce SLA in near-real time the DUACS system uses two flows based on the same instrumental mea-surements but with a different quality
bull The IGDR that are the latest high-quality altimeter data produced in near-real-time
bull The OGDR that includes real time data (OSTMJason-2 and Jason-1 OSDR) to complete IGDR Thesefast delivery products do not always benefit from precise orbit determination nor from some exter-nal model-based corrections (Dynamic Atmospheric Correction (DAC) Global Ionospheric Maps(GIM))
Integration of OGDR data and the introduction of Jason-2Jason-1 tandem increased the resilience and pre-cision of the system A better restitution of ocean variability is observed especially in high energetic areas
Altimetric product Source Availability Type of orbit
Jason-2 IGDR CNES ~24h CNES MOE GDR-Cuntil 20120730
CNES MOE GDR-Dsince 20120731
OGDR NOAAEUMETSAT ~3 to 5 h
Jason-1 IGDR CNESNASA ~48 h CNES MOE GDR-Dsince 20120507
OGDR CNESNASA ~3 to 12 h
Envisat IGDR ESACNES not deliveredsince 20120408
CNES MOE GDR-Dsince 20120121
FDGDR ESA not deliveredsince 20120408
Cryosat-2 IGDR-like ESACNES ~48 h CNES MOE GDR-D
not delivered
Table 2 SSALTODUACS Near-Real Time Input data overview
See Figure 6 Overview of the near real time system data flow management
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DUACS 2011 NRT product from IGDR1
j2 j1nj1g enn c2Productstandard ref
version C until20120730 and D after
version C version 21 CPP [2]
Orbit CNES MOE GDR-Cuntil 20120730
GDR-D after
CNES MOE GDR-C forj1n and CNES MOE
GDR-D for j1g
CNES MOE GDR-Dfrom 20120121 to
20120408
CNES MOE GDR-D
Ionopheric bi-frequency altimeter range measurements GIM model for cgt64 (Iijima et al1998[24])Dry tropo Model computed from ECMWF Gaussian grids (new S1 and S2 atm tides applied)Wet tropo-sphere
AMR radiometer(enhancement in coastal
regions since20120730)
JMR radiometer MWR radiometer andcorrected from side
lobes
Model computed fromECMWF Gaussian
grids
DAC MOG2D High Resolution forced with ECMWF pressure and wind fields (S1 and S2 wereexcluded) (Carrere and Lyard 2003[3])+ inverse barometer Filtering temporal window is
un-centered (no data in the future)Ocean tide GOT4v8 (S1 and S2 are included) and TPX 072 [16] for Arctic productsPole tide [Wahr 1985 [53]]Solid earthtide
Elastic response to tidal potential [Cartwright and Tayler 1971[5]] [Cartwright andEdden 1973[6]]
Loading tide GOT4v8 (S1 and S2 are included)Sea statebias
Non parametric SSB[Labroue 2004[27]](with cycles J1 1 to 11
using GDR-B standardsuntil 20120730 andderived from Jason-2
after)
Non parametric SSB[Labroue 2004[27]](with cycles 1 to 21
using GDR-Bstandards)
Non parametric SSB[Labroue 2004[27]](with cycles 41 to 60
using GDR-Bstandards)
Same as Jason-2 SSB
Orbit error Global multi-mission crossover minimization (Le Traon and Ogor1998[32])
Long wave-lengh errors
Optimal Interpolation [Le Traon et al 1998[31]]
Intercalibration Reference from cycle20
Mean pro-file (seeIII261)
Computed with cycles11-353 TP data andwith cycles 11-250J1 data referenced[19931999]
TPNJ1N computedwith cycles 369-479TPN data refer-enced [19931999]J1G No MP can beused instead theMSS_CNES_CLS11[39] is used
No Mean Profilecan be used forEnvisat on its neworbit Instead theMSS_CNES_CLS11[39] is used
No Mean Profilecan be used forCryosat-2 Instead theMSS_CNES_CLS11[39] is used
(1) A flag included in the along-track files indicates the source of the production (OGDRFDGDR orIGDR) If flag=0 the processed data comes from OGDRsFDGDRs if flag=1 the processed data comesfrom IGDRs
Table 3 Corrections and models applied in SSALTODUACS NRT products produced from IGDRs
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DUACS 2011 NRT product from OGDR or FDGDR2
j2 j1nj1g ennProduct stan-dard ref
version C until 20120730and D after
version C version 21
Orbit Navigator Extrapolated CNES MOEGDR-D since 20120121
Ionopheric From-dual frequency altimeter range measurements From GIM model fromcycle 65 (Iijima et al1998 [24])
Dry troposphere Model computed from ECMWF Gaussian grids (new S1 and S2 atmospherictides are applied)
Wet tropo-sphere
AMR radiometer(enhancement in coastal
regions since 20120730)
JMR radiometer MWR radiometer andcorrected from side lobes
DAC Inverse Barometer forecastedOcean tide GOT4v8 (S1 and S2 are included) and TPX 072 [16] for Arctic productsPole tide [Wahr 1985 [53]]Solid earth tide Elastic response to tidal potential [Cartwright and Tayler 1971[5]]
[Cartwright and Edden 1973[6]]Loading tide GOT4v8 (S1 and S2 are included)Sea state bias Non parametric SSB
[Labroue 2004[27]] (withcycles J1 1 to 11 usingGDR-B standards until20120730 and derivedfrom Jason-2 after)
Non parametric SSB[Labroue 2004[27]](with cycles 1 to 21 usingGDR-B standards)
Non parametric SSB[Labroue 2004[27]](with cycles 41 to 60using GDR-B standards)
Orbit error Specific filtering of long-wavelength signal3
Long wave-lengh errors
Optimal Interpolation [Le Traon et al 1998[31]]
Intercalibration Reference from cycle 20Mean profile(see III261)
Computed with cycles 11-353 TP data and with cy-cles 11-250 J1 data refer-enced [19931999]
TPNJ1N computedwith cycles 369-479TPN data referenced[19931999] J1G NoMP can be used insteadthe MSS_CNES_CLS11[39] is used
No Mean Profile can beused for Envisat on itsnew orbit Instead theMSS_CNES_CLS11 [39]is used
(2) A flag included in the along-track files indicates the source of the production (OGDRFDGDR orIGDR) If flag=0 the processed data comes from OGDRsFDGDRs if flag=1 the processed data comesfrom IGDRs(3) Specific data processing was applied on long wave-length signal (sectIII23 of the user manual)
Table 4 Corrections and models applied in SSALTODUACS NRT products produced from OG-DRsFDGDRs
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III22 Acquisition
The acquisition process is twofold
bull straightforward retrieval and reformatting of altimeter data and dynamic auxiliary data (pressure andwet troposphere correction grids from ECMWF are provided by Meteo France TEC grids from JPLNRT MOG2D corrections) from external repositories
bull synchronisation process
To be homogenized properly altimeter data sets require various auxiliary data The acquisition softwaredetects downloads and processes incoming data as soon as they are available on remote sites (externaldatabase FTP site) Data are split into passes if necessary If data flows are missing or late the synchroni-sation engine put unusable data in waiting queues and automatically unfreezes them upon reception of themissing auxiliary data This processing step delivers raw data that is to say data that have been dividedinto cycles and passes and ordered chronologicallyFrom SSALTODUACS V80 the acquisition step uses two different data flows in near-real time the OGDRflow (within a few hours) and the IGDR flow (within a few days)For each OGDR input the system checks that no equivalent IGDR entry is available in the data base beforeacquisition for each IGDR input the system checks and delete the equivalent OGDR entry in the data baseThese operations aim to avoid duplicates in SSALTODUACS system
Figure 6 Overview of the near real time system data flow management
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III23 Homogenization
The Homogenization process consists in applying the most recent corrections models and references rec-ommended for altimeter products Each mission is processed separately as its needs depend on the baseinput data The list of corrections and models currently applied is provided in tables 3 and 4 for NRT dataThe system includes SLA filtering to process OGDR data DUACS extract from these data sets the shortscales (space and time) which are useful to better describe the ocean variability in real time and merge thisinformation with a fair description of large scale signals provided by the multi-satellite observation in nearreal time (read IGDR-based DUACS data) Finally an hybrid SLA is computed
Figure 7 Merging pertinent information from IGDR and OGDR processing
III24 Input data quality control
The Input Data Quality Control is a critical process applied to guarantee that DUACS uses only the mostaccurate altimeter data Thanks to the high quality of current missions this process rejects a small percent-age of altimeter measurements but these erroneous data could be the cause of a significant quality lossThe quality control relies on standard raw data editing with quality flags or parameter thresholds but alsoon complex data editing algorithms based on the detection of erroneous artefacts mono and multi-missioncrossover validation and macroscopic statistics to edit out large data flows that do not meet the systemrsquosrequirements
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III25 Multi-mission cross-calibration
The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistentand accurate information It removes any residual orbit error (OE Le Traon and Ogor 1998[32]) or longwavelength error (LWE Le Traon et al 1998[31]) as well as large scale biases and discrepancies betweenvarious data flows
This process is based on two very different algorithms a global multi-mission crossover minimization fororbit error reduction (OER) and Optimal Interpolation (OI) for LWE
Multi-satellite crossover determination is performed on a daily basis All altimeter fields (measurementcorrections and other fields such as bathymetry MSS) are interpolated at crossover locations and datesCrossovers are then appended to the existing crossover database as more altimeter data become availableThis crossover data set is the input of the Orbit Error Reduction (OER) method Using the precision of thereference mission orbit a very accurate orbit error can be estimated This processing step does not concernOGDR dataLWE is mostly due to residual tidal or inverse barometer errors and high frequency ocean signals The OIused for LWE reduction uses precise parameters derived from
bull accurate statistical description of sea level variability
bull localized correlation scales
bull mission-specific noise and precise assumptions on the long wavelength errors to be removed (from arecent analysis of one year of data from each mission)
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III26 Product generation
The product generation process is composed of four steps computation of raw SLA cross-validationfilteringampsub-sampling and generation of by-products
III261 Computation of raw SLA
Since the geoid is not well known yet the SSH cannot be used directly the SSH anomalies are used insteadThey are computed from the difference of the instantaneous SSH - a temporal reference This temporalreference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeattrack analysis cannot be used The errors affecting the SLAs MPs and MSS have different magnitudes andwavelengths The computation of the SLAs and their errors associated are detailed in Dibarboure et al 2010[9]
Use of a Mean ProfileIn the repeat track analysis (when the satellites flies over a repetitive orbit) measurements are re-sampledalong a theoretical ground track (or mean track) associated to each mission Then a Mean Profile (MP) issubtracted from the re-sampled data to obtain SLA The MP is a time average of similarly re-sampled dataover a long period
bull The Mean Profile used for Jason-2 is computed with 10 years of TP (cycles 11 to 353) and 6 years ofJason-1 (cycles 11 to 250)
bull The Mean Profile used from Jason-1 cycle 262 to 374 (where satellites are on interleaved ground-tracks) is computed with 3 years of TP (cycles 369 to 479)
bull No Mean Profile can be used for Envisat on its new orbit (enn) Jason-1 on its geodetic orbit (j1g) norfor Cryosat-2 mission (c2) because there is no repetitive track The MSS must be used instead (seebelow)
Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible
bull Indeed as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide precise cross-track projection andor interpolation schemes are required to avoid errors
bull The mesoscale variability error (which is lt35 cm for MP between 3 to 5 years and lt1cm for WLof 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a prioriknowledge from Sea Level maps derived from previous iterations or from other missions
bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for Envisat since november 2010 and for Cryosat-2 mission (c2)because the satellite is not in a repetitive orbit phase The alternative is to use the MSS instead The griddedMSS is derived from along track MPs and data from geodetic phases Thus any error on the MP is alsocontained in the MSS There are essentially 4 types of additional errors on gridded MSS which are hard toquantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
Note that for the Arctic regional products the DTU10 MSS [1] is taken into account instead of the CLS01MSS Indeed the accuracy of DTU10 compared to CLS01 is further demonstrated by the significant sealevel anomaly variance reduction found over the whole Arctic Ocean as shown in Prandi et al [42]
III262 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III263 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
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III27 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III271 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
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III272 Performance indicators
To appreciate the quality situation of the DUACS system new performance indicators are computed dailyThey aim at evaluate the status of the main processing steps of the system the input data availability theinput data coverage the input data quality and the output product quality These indicators are computed foreach and every currently working satellite and combined to obtain the overall status
Figure 8 Example with the key performance indicator on 20090627
See the description the latest and previous indicators on Aviso websitehttpwwwavisooceanobscomindexphpid=1516
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III3 Delayed Time processing steps
III31 Input data models and corrections applied
Delayed Time MyOcean products are generated
bull from Aviso GDR products for TP Jason-1 Jason-2 and Envisat (GDR-A cycles 1 to 22 GDR-Bcycles 23 to 85 GDR-C from cycle 86)
bull from NOAA GDR for GFO and from CERSAT (IFREMER) OPR for ERS-1 and ERS-2 (phases C(1st 35-day repeat orbit period) phase E and F (geodetic phases) phase G for ERS-1 (last 35-dayrepeat orbit period tandem phase with ERS-2 phase A for ERS-2 (1st 35-day repeat orbit periodtandem phase with ERS-1))
All GDR products are computed with a Precise Orbit Ephemeris (POE) and are delivered within 2 to 3months depending on the mission For several missions an updated orbit is used
bull For ERS-1amp-2 the orbit used is DGME-04 provided by Delft Institute (httpwwwdeostudelftnl)until June 2003
bull For TopexPoseidon the orbit used is GSFC (std0809) for the whole mission
bull For Envisat CNES POE of GDR-C standard is used for the whole mission
bull For the whole GFO mission the orbit used is GSFC (std0809) and when not available NASA POE isused
Altimetric product Source Availability Type of orbit
TopexPoseidon GDR NASACNES - GSFC POE
Jason-1 GDR (GDR-C) CNESNASA ~40 days CNES POE
Jason-2 GDR (GDR-C) CNESNASA ~60 days CNES POE
GFO GDR NOAA - GSFCNASA POE
ERS-1amp2 IFREMERESA - DGME-04
Envisat (GDR-A GDR-B andGDR-C from cycle 86)
ESA ~2 months CNES POE
Table 5 SSALTODUACS Delayed Time Input data overview
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DU
AC
S20
11D
Tpr
oduc
t(gtV
30
0)j2
j1j1
ntp
tpn
e1e2
ene
nng2
Prod
uct
stan
dard
ref
GD
R-C
OPR
GD
R-A
(Cyc
les
1to
22)
GD
R-B
(cyc
les
23-8
5)
GD
R(N
OA
A)
Orb
itC
nes
POE
GSF
C(I
TR
F20
05G
RA
CE
last
stan
dard
s)
DG
ME
-04
(Sch
arro
oan
dV
isse
r19
98[4
8]C
NE
SPO
E(G
DR
-1st
anda
rds
forc
ycle
s9
to22
GD
R-C
stan
dard
sfr
omcy
cle
23)
GSF
C(I
TR
F20
05
GR
AC
Ela
stst
anda
rds
Iono
pher
icD
ual f
requ
ency
altim
eter
rang
em
easu
rem
ents
Dua
l fre
quen
cyal
timet
erra
nge
mea
sure
men
ts(T
opex
)D
OR
IS(P
OSE
IDO
N)
Ben
t mod
elB
ent m
odel
(cyc
les
1-36
)G
IMm
odem
from
cycl
e37
((Ii
jima
etal
19
98[2
4])
Dua
l-fr
eque
ncy
altim
eter
rang
em
easu
rem
ent(
cycl
e9-
64)a
ndG
IMm
odel
gtcyc
le65
(Iiji
ma
etal
19
99[2
4])c
orre
cted
from
8m
mbi
as
From
GIM
mod
el(I
ijim
aet
al1
998
[24]
)
Dry
trop
o-sp
here
Mod
elco
mpu
ted
from
EC
MW
FG
auss
ian
grid
s(n
ewS1
and
S2at
mos
pher
ictid
esar
eap
plie
d)
Mod
elco
mpu
ted
from
EC
MW
Fre
ctan
gula
rgri
ds(n
ewS1
and
S2at
mos
pher
ictid
esar
ein
clud
ed)
Wet
trop
o-sp
here
JMR
AM
Rra
diom
eter
furt
hert
han
50km
from
the
coas
tsF
rom
EC
MW
Fm
odel
ford
ista
nces
betw
een
10an
d50
km
TM
Rra
diom
eter
(Sch
aroo
etal
20
04[4
9])
MW
RC
orre
ctio
nof
the
drif
ton
the
236
GH
zbr
ight
ness
tem
pera
ture
(Sch
arro
oet
al
2004
[49]
)Neu
ral
Net
wor
kal
gori
thm
(Tra
nan
dO
blig
is
2003
[50]
MW
Rra
diom
eter
furt
hert
han
50km
from
the
coas
tsan
dco
rrec
ted
from
side
lobe
s(f
rom
cycl
e41
)E
CM
WF
mod
elfo
rdis
tanc
esbe
twee
n10
and
50km
GFO
radi
omet
er
DA
CM
OG
2DH
igh
Res
olut
ion
forc
edw
ithE
CM
WF
pres
sure
and
win
gfie
lds
(S1
and
S2w
ere
excl
uded
)+in
vers
eba
rom
eter
com
pute
dfr
omre
ctan
gula
rgri
ds
Tabl
e6
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(1
2)
Page 33
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
j2j1
j1n
tptp
ne1
e2en
enn
g2O
cean
tide
GO
T4v
7(S
1an
dS2
are
incl
uded
)Po
letid
e[W
ahr
1985
[53]
]So
lidea
rth
tide
Ela
stic
resp
onse
totid
alpo
tent
ial[
Car
twri
ghta
ndTa
yler
197
1[5]
][C
artw
righ
tand
Edd
en1
973[
6]]
Loa
ding
tide
GO
T4v
7(S
1pa
ram
eter
isin
clud
ed)
Sea
stat
ebi
asN
onpa
ram
etri
cSS
B[G
aspa
reta
l20
02[2
0]]
Non
para
met
ric
SSB
[NT
ran
and
al2
010[
51]]
BM
3[G
aspa
ran
dO
gor
1994
[17]
]
Non
para
met
ric
SSB
[Mer
tzet
al
2005
[38]
]
Non
para
met
ric
SSB
[Gas
pare
tal
2002
]w
ithG
DR
-Bst
anda
rds
forc
ycle
s9
to85
and
with
GD
R-C
stan
dard
sfr
omcy
cle
86
Non
para
met
ric
SSB
[NT
ran
etal
20
10[5
1]]
Orb
iter
ror
Glo
bal m
ulti-
mis
sion
cros
sove
rmin
imiz
atio
n(L
eTr
aon
and
Ogo
r19
98[3
2])
Lon
gw
ave-
leng
her
rors
Opt
imal
Inte
rpol
atio
n(L
eTr
aon
etal
19
98[3
1])
Inte
rcal
ibra
tion
Ref
eren
cefr
omcy
cle
11R
efer
ence
from
cycl
e1
to35
4C
orre
ctio
nof
regi
onal
bias
J2J
1de
duce
dfr
omin
terc
alib
ratio
nph
ase
(cyc
le11
J2)
Cor
rect
ion
ofgl
obal
biai
sJ1
TP
deacutedu
ced
from
inte
rcal
ibra
tion
phas
e(c
ycle
s11
J1)
Mea
npr
o-fil
e(s
eeII
I36
1)
Com
pute
dw
ithcy
cles
11-3
53T
Pda
taan
dw
ithcy
cles
11-2
50J1
data
ref
eren
ced
[199
319
99]
TP
J1 c
ompu
ted
with
cycl
es11
-353
TP
data
and
with
cycl
es11
-250
J1da
tar
efer
ence
d[1
993
1999
]T
PNJ
1Nc
ompu
ted
with
cycl
es36
9-47
9T
PNda
tar
efer
ence
d[1
993
1999
]
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
ref
eren
ced
[199
319
99]
EN
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
re
fere
nced
[199
319
99]
EN
Nu
seof
MSS
_CN
ES_
CL
S11
[39]
Com
pute
dw
ithcy
cles
37-1
87G
2da
ta
refe
renc
ed[1
993
1999
]
Peri
odof
use
from
cycl
e9
from
cycl
e9
cycl
es1
to48
1cy
cles
15to
43In
clud
ing
E-F
geod
etic
phas
es
cycl
es1
to83
from
cycl
e9
cycl
es37
to22
2
Tabl
e7
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(2
2)
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III32 Acquisition
The acqusition process in Delayed time is much simpler than in Near Real time it consists in a synchronisa-tion process of all the auxiliary data required to homogenize propely the altimeter data sets The acquisitionstep uses the GDRs or the OPRs provided by the agencies
III33 Homogenization
The Homogenization process consists in applying the most recent corrections models and references rec-ommended for altimeter products Each mission is processed separately as its needs depend on the baseinput data The list of corrections and models currently applied is provided in tables 6 and 7 for DT data
III34 Input data quality control
The Input Data Quality Control is a critical process applied to guarantee that DUACS uses only the mostaccurate altimeter data Thanks to the high quality of current missions this process rejects a small percent-age of altimeter measurements but these erroneous data could be the cause of a significant quality lossThe quality control relies on standard raw data editing with quality flags or parameter thresholds but alsoon complex data editing algorithms based on the detection of erroneous artefacts mono and multi-missioncrossover validation and macroscopic statistics to edit out large data flows that do not meet the systemrsquosrequirements
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III35 Multi-mission cross-calibration
The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistentand accurate information It removes any residual orbit error (OE Le Traon and Ogor 1998[32]) or longwavelength error (LWE Le Traon et al 1998[31]) as well as large scale biases and discrepancies betweenvarious data flows
This process is based on two very different algorithms a global multi-mission crossover minimization fororbit error reduction (OER) and Optimal Interpolation (OI) for LWE
Multi-satellite crossover determination is performed on a daily basis All altimeter fields (measurementcorrections and other fields such as bathymetry MSS) are interpolated at crossover locations and datesCrossovers are then appended to the existing crossover database as more altimeter data become availableThis crossover data set is the input of the Orbit Error Reduction (OER) method Using the precision of thereference mission orbit a very accurate orbit error can be estimated LWE is mostly due to residual tidalor inverse barometer errors and high frequency ocean signals The OI used for LWE reduction uses preciseparameters derived from
bull accurate statistical description of sea level variability
bull localized correlation scales
bull mission-specific noise and precise assumptions on the long wavelength errors to be removed (from arecent analysis of one year of data from each mission)
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III36 Product generation
The product generation process is composed of four steps computation of raw SLA cross-validationfilteringampsub-sampling and generation of by-products
III361 Computation of raw SLA
Since the geoid is not well known yet the SSH cannot be used directly the SSH anomalies are used insteadThey are computed from the difference of the instantaneous SSH - a temporal reference This temporalreference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeattrack analysis cannot be used The errors affecting the SLAs MPs and MSS have different magnitudes andwavelengths The computation of the SLAs and their errors associated are detailed in Dibarboure et al 2010[9]
Use of a Mean ProfileIn the repeat track analysis (when the satellites flies over a repetitive orbit) measurements are re-sampledalong a theoretical ground track (or mean track) associated to each mission Then a Mean Profile (MP) issubtracted from the re-sampled data to obtain SLA The MP is a time average of similarly re-sampled dataover a long period
bull The Mean Profile used for TP (cycles 1 to 364) Jason-1 (cycles 1 to 259) and Jason-2 is computedwith 10 years of TP (cycles 11 to 353) and 6 years of Jason-1 (cycles 11 to 250)
bull The Mean Profile used for TP (cycles 368 to 481) and from Jason-1 cycle 262 to 374 (where satellitesare on interleaved ground-tracks) is computed with 3 years of TP (cycles 369 to 479)
bull The Mean Profile used for ERS-1 in its 35 days repetitive orbit mission ERS-2 and Envisat (only forthe first orbit before November 2010) is computed with 8 years of ERS-2 (cycles 1 to 85) and 6 yearsof Envisat (cycles 10 to 72)
bull No Mean Profile can be used for Envisat on its new orbit (enn) Jason-1 on its geodetic orbit (j1g)because there is no repetitive track The MSS must be used instead (see below)
bull The Mean Profile used for GFO is computed with 7 years of GFO cycles 37 to 187
Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible
bull Indeed as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide precise cross-track projection andor interpolation schemes are required to avoid errors
bull The mesoscale variability error (which is lt35 cm for MP between 3 to 5 years and lt1cm for WLof 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a prioriknowledge from Sea Level maps derived from previous iterations or from other missions
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for ERS-1 for its 168 days geodetic mission (phases E-F from April1994 to March 1995) or for Envisat since november 2010 because the satellite is not in a repetitive orbitphase The alternative is to use the MSS instead The gridded MSS is derived from along track MPs anddata from geodetic phases Thus any error on the MP is also contained in the MSS There are essentially 4types of additional errors on gridded MSS which are hard to quantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
III362 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III363 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
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III37 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III371 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
Page 39
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
IV MYOCEAN PRODUCTS
IV1 Near Real Time Products
The purpose of the NRT DUACS component is the acquisition of altimeter data from various altimeter mis-sions in near-real time (ie within a few days at most) the validation and correction of these altimeter datasets (ie edition and selection update of corrections and homogenization orbit error reduction) in order toproduce each day along-track productsProducts are as follows
Along-track products global and regional (Mediterranean and Black Seas Arctic Ocean and Europeareas)
bull Sea Level Anomaly (NRT-SLA) for each mission with NRT-SLA ephemeris
IV11 Delay of the products
The availability of the products in near real time is three to twelve hours after the measurement for along-track products Those products are delivered every day
IV12 Temporal availibility
The following table presents the available products by mission and by data periodNear real time products
NRT Jason-2 Jason-1 and Jason-1geodetic
Envisat new Cryosat-2
Temporal Time availability ymlowast
ongoingymlowast-20120303 for
repeat track and20120507-ongoing for
geodetic track
ymlowast
2012040820120101
ongoing
NRT-SLA X X X X
lowastym the temporal coverage for NRT products is fluctuating and depends on updates of Delayed Time prod-ucts When DT products are updated (3 to 4 times per year) the oldest NRT products are replaced by thebetter quality DT products so that the 2 series are overlapping on few weeks or few months
IV2 Delayed Time Products
The Delayed Time component of SSALTODUACS system is responsible for the production of processedJason-1 Jason-2 TP Envisat GFO ERS12 and even Geosat data in order to provide a homogeneousinter-calibrated and highly accurate long time series of SLA DT products are more precise than NRT products Two reasons explain this quality difference The firstone is the better intrinsic quality of the POE orbit used in the GDR processing The second reason is that
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in the DT DUACS processing the products can be computed optimally with a centred computation timewindow for OER LWE On the contrary in NRT case future data are not available so the computationtime window is not centred and therefore not optimalAs for NRT products improved altimeter corrections and processing algorithms are used ocean tide modelto correct altimeter data improved methods for orbit error reduction and mapping
Along-Track products global and regional (Mediterranean and Black Seas)
bull Sea Level Anomaly (DT-SLA) for each mission
IV21 Delay of the products
Weekly products are delivered The availability of the products in delayed time is at the best two monthsafter the date of the measurement The product generation needs all the GDR data of all the missions to takeinto account the best corrections as possible The time delay can be longer in the case of a missing mission
IV22 Temporal availibility
The following table presents the available products by mission and by data periodDelayed time SSALTODUACS products
Upd Jason-2 Jason-1new6
Jason-1 GFO Envisatnew6
Envisat ERS-16
ERS-2Topexnew6
Topex
TemporalTimeavailabil-ity
200810ymlowast
200902ymlowast
200204200810
200001200809
201010ymlowast
200210201010
199210200304
200209200510
199209200204
DT-SLA X X X X X X X X X
lowast ym those dates are updated regularly (3 to 4 times per year) and are avalaible when you download thedata at httpwwwmyoceaneuweb24-cataloguephp6 Jason-1 new orbit starting 200809 Envisat new orbit starting 201010 TP new orbit starting 200209 ERS-1The geodetic phases (E-F) are included There are no ERS-1 data between December 23 1993 and April 10 1994(ERS-1 phase D - 2nd ice phase) Note that during that time products are based only on TopexPoseidon data
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V DESCRIPTION OF THE PRODUCT SPECIFICATION
V1 General information
Product Specification SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001
Geographical coverage global
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 20-50km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001 Product Specification
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Product Specification SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002
Geographical coverage 55˚W-35˚E 30˚N-46˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002 Product Specification
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Product Specification SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003
Geographical coverage 27˚E-42˚E 40˚N-47˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003 Product Specification
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Product Specification SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004
Geographical coverage 25˚W-42˚E 21˚N-66˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004 Product Specification
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Product Specification SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005
Geographical coverage 0˚W-360˚E 50˚N-82˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005 Product Specification
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VI NOMENCLATURE OF FILES
VI1 Nomenclature of files downloaded through the MyOcean Web PortalDirectgetfile Service
VI11 Nomenclature of the product line
The description of the syntax for the SL TAC SLA products line is given by
SEALEVEL_ltREGIONgt_SLA_L3_ltDELAYgt_OBSERVATIONS_008_ltZONEgt_ltLETTERgtwhere
REGION GLO global geographic coverage product
BS Black Sea products
MED Mediterranean products
ARC Arctic products (for NRT products)
EUROPE Europe products (for NRT products)
DELAY NRT near real time products
RAN delayed time or reanalysis products
ZONE 001 number on 3 digits
002
003
004
LETTER a letter on 1 digit
b
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VI12 Nomenclature of the datasets
The nomenclature used is
dataset-duacs-ltdelaygt-ltzonegt-ltmissiongt-lttype of slagt-l3where the fileds in ltgt are described below
delay nrt near-real time productsran delayed time products
zone global global geographic coverage productmedsea Mediterranean productsblacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1 (only for ran)e2 ERS-2 (only for ran)tp TOPEXPoseidon (only for ran)tpn TOPEXPoseidon on its new orbit (only for
ran)g2 GFO (only for ran)j1 Jason-1 (only for ran)j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisat (only for ran)enn Envisat on its new orbitc2 Cryosat-2 (only for nrt)
type of sla sla filtered slasla_unfiltered non filtered sla (only for ran products)
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VI13 Nomenclature of the NetCdf files
The nomenclature used is
ltdelaygt_ltzonegt_ltmissiongt_sla_ltvariablegt_ltdatebegingt_ltdateendgt_ltdateprodgtnc where the fileds in ltgt are de-scribed below
delay nrt near-real time productsdt delayed time products
zone global global geographic coverage productmed Mediterranean products (for dt)mfstep Mediterranean products (for nrt)blacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1e2 ERS-2tp TOPEXPoseidontpn TOPEXPoseidon on its new orbitg2 GFOj1 Jason-1j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisatenn Envisat on its new orbitc2 Cryosat-2
variable vfec filtered and sub-sampled slavxxc non filtered and non sub-sampled sla (only
for dt)datebegin YYYYMMDD() beginning date of the datasetdateend YYYYMMDD() end date of the datasetdateprod YYYYMMDD production date of the dataset
() For dt data as the dates in the file names are rounded the user wanting data for date T has to read the filescontaining dates T+1 and T-1 in their name and check inside the files if there are some data for date T
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VII DATA FORMAT
This chapter presents the data storage format used for MyOcean products
VII1 NetCdf
The products are stored using the NetCDF format NetCDF (network Common Data Form) is an interface for array-oriented data access and a library that provides an implementation of the interface The netCDF library also definesa machine-independent format for representing scientific data Together the interface library and format support thecreation access and sharing of scientific data The netCDF software was developed at the Unidata Program Center inBoulder Colorado The netCDF libraries define a machine-independent format for representing scientific data Pleasesee Unidata NetCDF pages for more information and to retreive NetCDF software package onhttpwwwunidataucaredupackagesnetcdfindexhtml
NetCDF data is
bull Self-Describing A netCDF file includes information about the data it contains
bull Architecture-independent A netCDF file is represented in a form that can be accessed by computers with dif-ferent ways of storing integers characters and floating-point numbers
bull Direct-access A small subset of a large dataset may be accessed efficiently without first reading through allthe preceding data
bull Appendable Data can be appended to a netCDF dataset along one dimension without copying the dataset orredefining its structure The structure of a netCDF dataset can be changed though this sometimes causes thedataset to be copied
bull Sharable One writer and multiple readers may simultaneously access the same netCDF file
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VII2 Structure and semantic of NetCDF along-track files
The NetCDF Sea Level TAC files are based on the attribute data tags defined by the Cooperative OceanAtmosphereResearch Data Service (COARDS) and Climate and Forecast (CF) metadata conventions The CF convention gener-alises and extends the COARDS convention but relaxes the COARDS constraints on dimension and order and specifiesmethods for reducing the size of datasetsA wide range of software are available to write or read NetCDFCF files API are made available by UNIDATA(httpwwwunidataucaredusoftwarenetcdf)
bull CC++Fortran
bull Java
bull MATLAB Objective-C Perl Python R Ruby TclTk
In addition to these conventions the files are using a common structure and semantic
bull 1 dimension is defined
ndash time it is used to check NetCDF variables depending on time
bull 8 variables are defined
ndash short SLA contains the Sea Level Anomaly values for each time given
ndash int longitude contains the longitude for each measurement
ndash short track contains the track number for each measurement
ndash double time contains the time in days since 1950-01-01 000000 UTC for each measurement
ndash short mean_profile_point_index index of the corrsponding point in the track of the mean profile
ndash byte flag flag=0 the processed data comes from OGDR if flag=1 the processed data comes from theIGDR
ndash int latitude contains the latitude for each measurement
ndash short cycle contains the cycle number for each measurement
bull global attributes
ndash the global attributes gives information about the creation of the file
Example of a NetCDF sla file
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netcdf nrt_global_j1_sla_vfec_20101230_20101230_20101230 dimensions
time = 10385 variables
short SLA(time) SLAcoordinates = longitude latitude SLAlong_name = Sea Level Anomaly SLA_FillValue = 32767s SLAadd_offset = 0 SLAscale_factor = 0001 SLAunits = m SLAstandard_name = sea_surface_height_above_sea_level
int longitude(time) longitudelong_name = Longitude of measurement longitude_FillValue = 2147483647 longitudeadd_offset = 0 longitudestandard_name = longitude longitudescale_factor = 1e-06 longitudeunits = degrees_east
short track(time) tracklong_name = Track in cycle the measurement belongs to track_FillValue = 32767s trackunits = 1 trackcoordinates = longitude latitude
double time(time) timelong_name = Time of measurement time_FillValue = 184467440737096e+19 timeaxis = T timestandard_name = time timeunits = days since 1950-01-01 000000 UTC
int latitude(time) latitudelong_name = Latitude of measurement latitude_FillValue = 2147483647 latitudeadd_offset = 0 latitudestandard_name = latitude latitudescale_factor = 1e-06 latitudeunits = degrees_north
short flag(time) flagcoordinates = longitude latitude flag_FillValue = 3267s flaglong_name = data origin flagflag_values = 1s 0s flagflag_meanings = igdr_like non_igdr_like flagcomment = The origin of the data is determined by the types of geophysical datarecords (GDR) used in computation of the SLA 1 for the Interim GDR (IGDR) and0 for Operational GDR (OGDR)
short cycle(time) cyclelong_name = Cycle the measurement belongs to cycle_FillValue = 32767s cycleunits = 1 cyclecoordinates = longitude latitude
global attributeshistory = 22-Feb-2011 155243 CET File created by the SSLATODUACS system version 1001 comment = Produce from ENVISAT Extension Phase satellite altimetry data institution = CLSCNES
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references = httpwwwavisooceanobscomfileadmindocumentsdatatoolshdbk_duacspdf source = satellite altimetry title = along track Sea Level Anomaly Conventions = CF-14
dataSLA =
7 7 11 10 -2 -22 -39 -41 -30 -13 -3 -5 -16 -26 -32 -35-35 -35 -37 -35 -31 -29 -31 -35 -32 -21 -10 -10 -19 -20 -1-69 -57 -49 -45 -39 -30 -28 -31 -27 -13 -2 -5 -15 -3 1112 3 -7 -10 -14 -15 -22 -31 -37 -32 -17 -10
longitude =74743328 74868400 74993968 75120040 75246616 7537372875501368 75629568 75758320 75887656 76017568 76148080 7627920876388952 76477056 76565456 76654144 76743128 76832400 76921984329429568 329535424 329641792 329748672 329856096 329964032330072512 330181536 330291072 330401184
track =92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 9292 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92113 113 113 113 113 113 113 113 113 113 113 113 113 113113 113 113 113 113 113 113 113 113
time =222780000565705 222780001314719 222780002063733222780002812747 222780003561761 222780004310775 222780005059788222780005808802 222780006557816 22278000730683 222780008055844222780008804858 222780009553872 22278001017805 222780010677393222788257112198 222788257486705 222788257861212 222788258235719222788258610226 222788258984733 222788259359239 222788259733746222788260108253 22278826048276
mean_profile_point_index =1872 1878 1884 1890 1896 1902 1908 19141920 1926 1932 1938 1944 1949 1953 1957 1961 1965 1969 19732306 2309 2312 2315 2318 2321 2327 2330 2333 2336 2339 23422345 2348 2351 2354 2357 2360 2363 2366
flag =0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
latitude =-16225506 -16539731 -16853833 -17167810 -17481660 -17795380-18108966 -18422418 -18735729 -19048899 -19361924 -19674801-19987527 -20248015 -20456329 -20664569 -20872739 -2108083739481297 39628277 39775133 39921866 40068472 40214953 4036130840507533 40653629 40799592 40945423 41091120 41236684 41382111
cycle =331 331 331 331 331 331 331 331 331 331 331 331 331
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331 331 331 331 331 331 331 331 331 331 331 331 331 331331 331 331 331 331 331 331 331 331 331 331 331
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VIII HOW TO DOWNLOAD A PRODUCT
VIII1 Download a product through the MyOcean Web Portal DirectgetfileService
You first need to register Please find below the registration stepshttpwwwmyoceaneuweb34-products-and-services-faqphp1Once registered the MyOcean FAQ httpwwwmyoceaneuweb34-products-and-services-faqwill guide you on How to download a product through the MyOcean Web Portal Directgetfile Service
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IX NEWS AND UPDATES
IX1 [Duacs] Operational news
To be kept informed on events occurring on the satellites and on the eventual interruption of the services of the DUACSprocessing system see the [Duacs] operational news on the Aviso websitehttpwwwavisooceanobscomendataoperational-newsindexhtml
IX2 Updates
To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtmlSince 2010 a complete reprocessing of all altimetry data (cumulated total of about 55 years of data) is available Themain changes introduced in the Duacs DT v300 reprocessed data set in SSALTODUACS reprocessed DT data setare listed herehttpwwwavisooceanobscomfileadmindocumentsdataduacsduacs_DT_2010_reprocessing_impactpdf
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DUACS 2011 NRT product from IGDR1
j2 j1nj1g enn c2Productstandard ref
version C until20120730 and D after
version C version 21 CPP [2]
Orbit CNES MOE GDR-Cuntil 20120730
GDR-D after
CNES MOE GDR-C forj1n and CNES MOE
GDR-D for j1g
CNES MOE GDR-Dfrom 20120121 to
20120408
CNES MOE GDR-D
Ionopheric bi-frequency altimeter range measurements GIM model for cgt64 (Iijima et al1998[24])Dry tropo Model computed from ECMWF Gaussian grids (new S1 and S2 atm tides applied)Wet tropo-sphere
AMR radiometer(enhancement in coastal
regions since20120730)
JMR radiometer MWR radiometer andcorrected from side
lobes
Model computed fromECMWF Gaussian
grids
DAC MOG2D High Resolution forced with ECMWF pressure and wind fields (S1 and S2 wereexcluded) (Carrere and Lyard 2003[3])+ inverse barometer Filtering temporal window is
un-centered (no data in the future)Ocean tide GOT4v8 (S1 and S2 are included) and TPX 072 [16] for Arctic productsPole tide [Wahr 1985 [53]]Solid earthtide
Elastic response to tidal potential [Cartwright and Tayler 1971[5]] [Cartwright andEdden 1973[6]]
Loading tide GOT4v8 (S1 and S2 are included)Sea statebias
Non parametric SSB[Labroue 2004[27]](with cycles J1 1 to 11
using GDR-B standardsuntil 20120730 andderived from Jason-2
after)
Non parametric SSB[Labroue 2004[27]](with cycles 1 to 21
using GDR-Bstandards)
Non parametric SSB[Labroue 2004[27]](with cycles 41 to 60
using GDR-Bstandards)
Same as Jason-2 SSB
Orbit error Global multi-mission crossover minimization (Le Traon and Ogor1998[32])
Long wave-lengh errors
Optimal Interpolation [Le Traon et al 1998[31]]
Intercalibration Reference from cycle20
Mean pro-file (seeIII261)
Computed with cycles11-353 TP data andwith cycles 11-250J1 data referenced[19931999]
TPNJ1N computedwith cycles 369-479TPN data refer-enced [19931999]J1G No MP can beused instead theMSS_CNES_CLS11[39] is used
No Mean Profilecan be used forEnvisat on its neworbit Instead theMSS_CNES_CLS11[39] is used
No Mean Profilecan be used forCryosat-2 Instead theMSS_CNES_CLS11[39] is used
(1) A flag included in the along-track files indicates the source of the production (OGDRFDGDR orIGDR) If flag=0 the processed data comes from OGDRsFDGDRs if flag=1 the processed data comesfrom IGDRs
Table 3 Corrections and models applied in SSALTODUACS NRT products produced from IGDRs
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DUACS 2011 NRT product from OGDR or FDGDR2
j2 j1nj1g ennProduct stan-dard ref
version C until 20120730and D after
version C version 21
Orbit Navigator Extrapolated CNES MOEGDR-D since 20120121
Ionopheric From-dual frequency altimeter range measurements From GIM model fromcycle 65 (Iijima et al1998 [24])
Dry troposphere Model computed from ECMWF Gaussian grids (new S1 and S2 atmospherictides are applied)
Wet tropo-sphere
AMR radiometer(enhancement in coastal
regions since 20120730)
JMR radiometer MWR radiometer andcorrected from side lobes
DAC Inverse Barometer forecastedOcean tide GOT4v8 (S1 and S2 are included) and TPX 072 [16] for Arctic productsPole tide [Wahr 1985 [53]]Solid earth tide Elastic response to tidal potential [Cartwright and Tayler 1971[5]]
[Cartwright and Edden 1973[6]]Loading tide GOT4v8 (S1 and S2 are included)Sea state bias Non parametric SSB
[Labroue 2004[27]] (withcycles J1 1 to 11 usingGDR-B standards until20120730 and derivedfrom Jason-2 after)
Non parametric SSB[Labroue 2004[27]](with cycles 1 to 21 usingGDR-B standards)
Non parametric SSB[Labroue 2004[27]](with cycles 41 to 60using GDR-B standards)
Orbit error Specific filtering of long-wavelength signal3
Long wave-lengh errors
Optimal Interpolation [Le Traon et al 1998[31]]
Intercalibration Reference from cycle 20Mean profile(see III261)
Computed with cycles 11-353 TP data and with cy-cles 11-250 J1 data refer-enced [19931999]
TPNJ1N computedwith cycles 369-479TPN data referenced[19931999] J1G NoMP can be used insteadthe MSS_CNES_CLS11[39] is used
No Mean Profile can beused for Envisat on itsnew orbit Instead theMSS_CNES_CLS11 [39]is used
(2) A flag included in the along-track files indicates the source of the production (OGDRFDGDR orIGDR) If flag=0 the processed data comes from OGDRsFDGDRs if flag=1 the processed data comesfrom IGDRs(3) Specific data processing was applied on long wave-length signal (sectIII23 of the user manual)
Table 4 Corrections and models applied in SSALTODUACS NRT products produced from OG-DRsFDGDRs
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III22 Acquisition
The acquisition process is twofold
bull straightforward retrieval and reformatting of altimeter data and dynamic auxiliary data (pressure andwet troposphere correction grids from ECMWF are provided by Meteo France TEC grids from JPLNRT MOG2D corrections) from external repositories
bull synchronisation process
To be homogenized properly altimeter data sets require various auxiliary data The acquisition softwaredetects downloads and processes incoming data as soon as they are available on remote sites (externaldatabase FTP site) Data are split into passes if necessary If data flows are missing or late the synchroni-sation engine put unusable data in waiting queues and automatically unfreezes them upon reception of themissing auxiliary data This processing step delivers raw data that is to say data that have been dividedinto cycles and passes and ordered chronologicallyFrom SSALTODUACS V80 the acquisition step uses two different data flows in near-real time the OGDRflow (within a few hours) and the IGDR flow (within a few days)For each OGDR input the system checks that no equivalent IGDR entry is available in the data base beforeacquisition for each IGDR input the system checks and delete the equivalent OGDR entry in the data baseThese operations aim to avoid duplicates in SSALTODUACS system
Figure 6 Overview of the near real time system data flow management
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III23 Homogenization
The Homogenization process consists in applying the most recent corrections models and references rec-ommended for altimeter products Each mission is processed separately as its needs depend on the baseinput data The list of corrections and models currently applied is provided in tables 3 and 4 for NRT dataThe system includes SLA filtering to process OGDR data DUACS extract from these data sets the shortscales (space and time) which are useful to better describe the ocean variability in real time and merge thisinformation with a fair description of large scale signals provided by the multi-satellite observation in nearreal time (read IGDR-based DUACS data) Finally an hybrid SLA is computed
Figure 7 Merging pertinent information from IGDR and OGDR processing
III24 Input data quality control
The Input Data Quality Control is a critical process applied to guarantee that DUACS uses only the mostaccurate altimeter data Thanks to the high quality of current missions this process rejects a small percent-age of altimeter measurements but these erroneous data could be the cause of a significant quality lossThe quality control relies on standard raw data editing with quality flags or parameter thresholds but alsoon complex data editing algorithms based on the detection of erroneous artefacts mono and multi-missioncrossover validation and macroscopic statistics to edit out large data flows that do not meet the systemrsquosrequirements
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III25 Multi-mission cross-calibration
The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistentand accurate information It removes any residual orbit error (OE Le Traon and Ogor 1998[32]) or longwavelength error (LWE Le Traon et al 1998[31]) as well as large scale biases and discrepancies betweenvarious data flows
This process is based on two very different algorithms a global multi-mission crossover minimization fororbit error reduction (OER) and Optimal Interpolation (OI) for LWE
Multi-satellite crossover determination is performed on a daily basis All altimeter fields (measurementcorrections and other fields such as bathymetry MSS) are interpolated at crossover locations and datesCrossovers are then appended to the existing crossover database as more altimeter data become availableThis crossover data set is the input of the Orbit Error Reduction (OER) method Using the precision of thereference mission orbit a very accurate orbit error can be estimated This processing step does not concernOGDR dataLWE is mostly due to residual tidal or inverse barometer errors and high frequency ocean signals The OIused for LWE reduction uses precise parameters derived from
bull accurate statistical description of sea level variability
bull localized correlation scales
bull mission-specific noise and precise assumptions on the long wavelength errors to be removed (from arecent analysis of one year of data from each mission)
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III26 Product generation
The product generation process is composed of four steps computation of raw SLA cross-validationfilteringampsub-sampling and generation of by-products
III261 Computation of raw SLA
Since the geoid is not well known yet the SSH cannot be used directly the SSH anomalies are used insteadThey are computed from the difference of the instantaneous SSH - a temporal reference This temporalreference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeattrack analysis cannot be used The errors affecting the SLAs MPs and MSS have different magnitudes andwavelengths The computation of the SLAs and their errors associated are detailed in Dibarboure et al 2010[9]
Use of a Mean ProfileIn the repeat track analysis (when the satellites flies over a repetitive orbit) measurements are re-sampledalong a theoretical ground track (or mean track) associated to each mission Then a Mean Profile (MP) issubtracted from the re-sampled data to obtain SLA The MP is a time average of similarly re-sampled dataover a long period
bull The Mean Profile used for Jason-2 is computed with 10 years of TP (cycles 11 to 353) and 6 years ofJason-1 (cycles 11 to 250)
bull The Mean Profile used from Jason-1 cycle 262 to 374 (where satellites are on interleaved ground-tracks) is computed with 3 years of TP (cycles 369 to 479)
bull No Mean Profile can be used for Envisat on its new orbit (enn) Jason-1 on its geodetic orbit (j1g) norfor Cryosat-2 mission (c2) because there is no repetitive track The MSS must be used instead (seebelow)
Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible
bull Indeed as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide precise cross-track projection andor interpolation schemes are required to avoid errors
bull The mesoscale variability error (which is lt35 cm for MP between 3 to 5 years and lt1cm for WLof 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a prioriknowledge from Sea Level maps derived from previous iterations or from other missions
bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for Envisat since november 2010 and for Cryosat-2 mission (c2)because the satellite is not in a repetitive orbit phase The alternative is to use the MSS instead The griddedMSS is derived from along track MPs and data from geodetic phases Thus any error on the MP is alsocontained in the MSS There are essentially 4 types of additional errors on gridded MSS which are hard toquantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
Note that for the Arctic regional products the DTU10 MSS [1] is taken into account instead of the CLS01MSS Indeed the accuracy of DTU10 compared to CLS01 is further demonstrated by the significant sealevel anomaly variance reduction found over the whole Arctic Ocean as shown in Prandi et al [42]
III262 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III263 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
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III27 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III271 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
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III272 Performance indicators
To appreciate the quality situation of the DUACS system new performance indicators are computed dailyThey aim at evaluate the status of the main processing steps of the system the input data availability theinput data coverage the input data quality and the output product quality These indicators are computed foreach and every currently working satellite and combined to obtain the overall status
Figure 8 Example with the key performance indicator on 20090627
See the description the latest and previous indicators on Aviso websitehttpwwwavisooceanobscomindexphpid=1516
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III3 Delayed Time processing steps
III31 Input data models and corrections applied
Delayed Time MyOcean products are generated
bull from Aviso GDR products for TP Jason-1 Jason-2 and Envisat (GDR-A cycles 1 to 22 GDR-Bcycles 23 to 85 GDR-C from cycle 86)
bull from NOAA GDR for GFO and from CERSAT (IFREMER) OPR for ERS-1 and ERS-2 (phases C(1st 35-day repeat orbit period) phase E and F (geodetic phases) phase G for ERS-1 (last 35-dayrepeat orbit period tandem phase with ERS-2 phase A for ERS-2 (1st 35-day repeat orbit periodtandem phase with ERS-1))
All GDR products are computed with a Precise Orbit Ephemeris (POE) and are delivered within 2 to 3months depending on the mission For several missions an updated orbit is used
bull For ERS-1amp-2 the orbit used is DGME-04 provided by Delft Institute (httpwwwdeostudelftnl)until June 2003
bull For TopexPoseidon the orbit used is GSFC (std0809) for the whole mission
bull For Envisat CNES POE of GDR-C standard is used for the whole mission
bull For the whole GFO mission the orbit used is GSFC (std0809) and when not available NASA POE isused
Altimetric product Source Availability Type of orbit
TopexPoseidon GDR NASACNES - GSFC POE
Jason-1 GDR (GDR-C) CNESNASA ~40 days CNES POE
Jason-2 GDR (GDR-C) CNESNASA ~60 days CNES POE
GFO GDR NOAA - GSFCNASA POE
ERS-1amp2 IFREMERESA - DGME-04
Envisat (GDR-A GDR-B andGDR-C from cycle 86)
ESA ~2 months CNES POE
Table 5 SSALTODUACS Delayed Time Input data overview
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
DU
AC
S20
11D
Tpr
oduc
t(gtV
30
0)j2
j1j1
ntp
tpn
e1e2
ene
nng2
Prod
uct
stan
dard
ref
GD
R-C
OPR
GD
R-A
(Cyc
les
1to
22)
GD
R-B
(cyc
les
23-8
5)
GD
R(N
OA
A)
Orb
itC
nes
POE
GSF
C(I
TR
F20
05G
RA
CE
last
stan
dard
s)
DG
ME
-04
(Sch
arro
oan
dV
isse
r19
98[4
8]C
NE
SPO
E(G
DR
-1st
anda
rds
forc
ycle
s9
to22
GD
R-C
stan
dard
sfr
omcy
cle
23)
GSF
C(I
TR
F20
05
GR
AC
Ela
stst
anda
rds
Iono
pher
icD
ual f
requ
ency
altim
eter
rang
em
easu
rem
ents
Dua
l fre
quen
cyal
timet
erra
nge
mea
sure
men
ts(T
opex
)D
OR
IS(P
OSE
IDO
N)
Ben
t mod
elB
ent m
odel
(cyc
les
1-36
)G
IMm
odem
from
cycl
e37
((Ii
jima
etal
19
98[2
4])
Dua
l-fr
eque
ncy
altim
eter
rang
em
easu
rem
ent(
cycl
e9-
64)a
ndG
IMm
odel
gtcyc
le65
(Iiji
ma
etal
19
99[2
4])c
orre
cted
from
8m
mbi
as
From
GIM
mod
el(I
ijim
aet
al1
998
[24]
)
Dry
trop
o-sp
here
Mod
elco
mpu
ted
from
EC
MW
FG
auss
ian
grid
s(n
ewS1
and
S2at
mos
pher
ictid
esar
eap
plie
d)
Mod
elco
mpu
ted
from
EC
MW
Fre
ctan
gula
rgri
ds(n
ewS1
and
S2at
mos
pher
ictid
esar
ein
clud
ed)
Wet
trop
o-sp
here
JMR
AM
Rra
diom
eter
furt
hert
han
50km
from
the
coas
tsF
rom
EC
MW
Fm
odel
ford
ista
nces
betw
een
10an
d50
km
TM
Rra
diom
eter
(Sch
aroo
etal
20
04[4
9])
MW
RC
orre
ctio
nof
the
drif
ton
the
236
GH
zbr
ight
ness
tem
pera
ture
(Sch
arro
oet
al
2004
[49]
)Neu
ral
Net
wor
kal
gori
thm
(Tra
nan
dO
blig
is
2003
[50]
MW
Rra
diom
eter
furt
hert
han
50km
from
the
coas
tsan
dco
rrec
ted
from
side
lobe
s(f
rom
cycl
e41
)E
CM
WF
mod
elfo
rdis
tanc
esbe
twee
n10
and
50km
GFO
radi
omet
er
DA
CM
OG
2DH
igh
Res
olut
ion
forc
edw
ithE
CM
WF
pres
sure
and
win
gfie
lds
(S1
and
S2w
ere
excl
uded
)+in
vers
eba
rom
eter
com
pute
dfr
omre
ctan
gula
rgri
ds
Tabl
e6
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(1
2)
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
j2j1
j1n
tptp
ne1
e2en
enn
g2O
cean
tide
GO
T4v
7(S
1an
dS2
are
incl
uded
)Po
letid
e[W
ahr
1985
[53]
]So
lidea
rth
tide
Ela
stic
resp
onse
totid
alpo
tent
ial[
Car
twri
ghta
ndTa
yler
197
1[5]
][C
artw
righ
tand
Edd
en1
973[
6]]
Loa
ding
tide
GO
T4v
7(S
1pa
ram
eter
isin
clud
ed)
Sea
stat
ebi
asN
onpa
ram
etri
cSS
B[G
aspa
reta
l20
02[2
0]]
Non
para
met
ric
SSB
[NT
ran
and
al2
010[
51]]
BM
3[G
aspa
ran
dO
gor
1994
[17]
]
Non
para
met
ric
SSB
[Mer
tzet
al
2005
[38]
]
Non
para
met
ric
SSB
[Gas
pare
tal
2002
]w
ithG
DR
-Bst
anda
rds
forc
ycle
s9
to85
and
with
GD
R-C
stan
dard
sfr
omcy
cle
86
Non
para
met
ric
SSB
[NT
ran
etal
20
10[5
1]]
Orb
iter
ror
Glo
bal m
ulti-
mis
sion
cros
sove
rmin
imiz
atio
n(L
eTr
aon
and
Ogo
r19
98[3
2])
Lon
gw
ave-
leng
her
rors
Opt
imal
Inte
rpol
atio
n(L
eTr
aon
etal
19
98[3
1])
Inte
rcal
ibra
tion
Ref
eren
cefr
omcy
cle
11R
efer
ence
from
cycl
e1
to35
4C
orre
ctio
nof
regi
onal
bias
J2J
1de
duce
dfr
omin
terc
alib
ratio
nph
ase
(cyc
le11
J2)
Cor
rect
ion
ofgl
obal
biai
sJ1
TP
deacutedu
ced
from
inte
rcal
ibra
tion
phas
e(c
ycle
s11
J1)
Mea
npr
o-fil
e(s
eeII
I36
1)
Com
pute
dw
ithcy
cles
11-3
53T
Pda
taan
dw
ithcy
cles
11-2
50J1
data
ref
eren
ced
[199
319
99]
TP
J1 c
ompu
ted
with
cycl
es11
-353
TP
data
and
with
cycl
es11
-250
J1da
tar
efer
ence
d[1
993
1999
]T
PNJ
1Nc
ompu
ted
with
cycl
es36
9-47
9T
PNda
tar
efer
ence
d[1
993
1999
]
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
ref
eren
ced
[199
319
99]
EN
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
re
fere
nced
[199
319
99]
EN
Nu
seof
MSS
_CN
ES_
CL
S11
[39]
Com
pute
dw
ithcy
cles
37-1
87G
2da
ta
refe
renc
ed[1
993
1999
]
Peri
odof
use
from
cycl
e9
from
cycl
e9
cycl
es1
to48
1cy
cles
15to
43In
clud
ing
E-F
geod
etic
phas
es
cycl
es1
to83
from
cycl
e9
cycl
es37
to22
2
Tabl
e7
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(2
2)
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III32 Acquisition
The acqusition process in Delayed time is much simpler than in Near Real time it consists in a synchronisa-tion process of all the auxiliary data required to homogenize propely the altimeter data sets The acquisitionstep uses the GDRs or the OPRs provided by the agencies
III33 Homogenization
The Homogenization process consists in applying the most recent corrections models and references rec-ommended for altimeter products Each mission is processed separately as its needs depend on the baseinput data The list of corrections and models currently applied is provided in tables 6 and 7 for DT data
III34 Input data quality control
The Input Data Quality Control is a critical process applied to guarantee that DUACS uses only the mostaccurate altimeter data Thanks to the high quality of current missions this process rejects a small percent-age of altimeter measurements but these erroneous data could be the cause of a significant quality lossThe quality control relies on standard raw data editing with quality flags or parameter thresholds but alsoon complex data editing algorithms based on the detection of erroneous artefacts mono and multi-missioncrossover validation and macroscopic statistics to edit out large data flows that do not meet the systemrsquosrequirements
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III35 Multi-mission cross-calibration
The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistentand accurate information It removes any residual orbit error (OE Le Traon and Ogor 1998[32]) or longwavelength error (LWE Le Traon et al 1998[31]) as well as large scale biases and discrepancies betweenvarious data flows
This process is based on two very different algorithms a global multi-mission crossover minimization fororbit error reduction (OER) and Optimal Interpolation (OI) for LWE
Multi-satellite crossover determination is performed on a daily basis All altimeter fields (measurementcorrections and other fields such as bathymetry MSS) are interpolated at crossover locations and datesCrossovers are then appended to the existing crossover database as more altimeter data become availableThis crossover data set is the input of the Orbit Error Reduction (OER) method Using the precision of thereference mission orbit a very accurate orbit error can be estimated LWE is mostly due to residual tidalor inverse barometer errors and high frequency ocean signals The OI used for LWE reduction uses preciseparameters derived from
bull accurate statistical description of sea level variability
bull localized correlation scales
bull mission-specific noise and precise assumptions on the long wavelength errors to be removed (from arecent analysis of one year of data from each mission)
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III36 Product generation
The product generation process is composed of four steps computation of raw SLA cross-validationfilteringampsub-sampling and generation of by-products
III361 Computation of raw SLA
Since the geoid is not well known yet the SSH cannot be used directly the SSH anomalies are used insteadThey are computed from the difference of the instantaneous SSH - a temporal reference This temporalreference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeattrack analysis cannot be used The errors affecting the SLAs MPs and MSS have different magnitudes andwavelengths The computation of the SLAs and their errors associated are detailed in Dibarboure et al 2010[9]
Use of a Mean ProfileIn the repeat track analysis (when the satellites flies over a repetitive orbit) measurements are re-sampledalong a theoretical ground track (or mean track) associated to each mission Then a Mean Profile (MP) issubtracted from the re-sampled data to obtain SLA The MP is a time average of similarly re-sampled dataover a long period
bull The Mean Profile used for TP (cycles 1 to 364) Jason-1 (cycles 1 to 259) and Jason-2 is computedwith 10 years of TP (cycles 11 to 353) and 6 years of Jason-1 (cycles 11 to 250)
bull The Mean Profile used for TP (cycles 368 to 481) and from Jason-1 cycle 262 to 374 (where satellitesare on interleaved ground-tracks) is computed with 3 years of TP (cycles 369 to 479)
bull The Mean Profile used for ERS-1 in its 35 days repetitive orbit mission ERS-2 and Envisat (only forthe first orbit before November 2010) is computed with 8 years of ERS-2 (cycles 1 to 85) and 6 yearsof Envisat (cycles 10 to 72)
bull No Mean Profile can be used for Envisat on its new orbit (enn) Jason-1 on its geodetic orbit (j1g)because there is no repetitive track The MSS must be used instead (see below)
bull The Mean Profile used for GFO is computed with 7 years of GFO cycles 37 to 187
Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible
bull Indeed as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide precise cross-track projection andor interpolation schemes are required to avoid errors
bull The mesoscale variability error (which is lt35 cm for MP between 3 to 5 years and lt1cm for WLof 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a prioriknowledge from Sea Level maps derived from previous iterations or from other missions
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for ERS-1 for its 168 days geodetic mission (phases E-F from April1994 to March 1995) or for Envisat since november 2010 because the satellite is not in a repetitive orbitphase The alternative is to use the MSS instead The gridded MSS is derived from along track MPs anddata from geodetic phases Thus any error on the MP is also contained in the MSS There are essentially 4types of additional errors on gridded MSS which are hard to quantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
III362 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III363 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
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III37 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III371 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
Page 39
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
IV MYOCEAN PRODUCTS
IV1 Near Real Time Products
The purpose of the NRT DUACS component is the acquisition of altimeter data from various altimeter mis-sions in near-real time (ie within a few days at most) the validation and correction of these altimeter datasets (ie edition and selection update of corrections and homogenization orbit error reduction) in order toproduce each day along-track productsProducts are as follows
Along-track products global and regional (Mediterranean and Black Seas Arctic Ocean and Europeareas)
bull Sea Level Anomaly (NRT-SLA) for each mission with NRT-SLA ephemeris
IV11 Delay of the products
The availability of the products in near real time is three to twelve hours after the measurement for along-track products Those products are delivered every day
IV12 Temporal availibility
The following table presents the available products by mission and by data periodNear real time products
NRT Jason-2 Jason-1 and Jason-1geodetic
Envisat new Cryosat-2
Temporal Time availability ymlowast
ongoingymlowast-20120303 for
repeat track and20120507-ongoing for
geodetic track
ymlowast
2012040820120101
ongoing
NRT-SLA X X X X
lowastym the temporal coverage for NRT products is fluctuating and depends on updates of Delayed Time prod-ucts When DT products are updated (3 to 4 times per year) the oldest NRT products are replaced by thebetter quality DT products so that the 2 series are overlapping on few weeks or few months
IV2 Delayed Time Products
The Delayed Time component of SSALTODUACS system is responsible for the production of processedJason-1 Jason-2 TP Envisat GFO ERS12 and even Geosat data in order to provide a homogeneousinter-calibrated and highly accurate long time series of SLA DT products are more precise than NRT products Two reasons explain this quality difference The firstone is the better intrinsic quality of the POE orbit used in the GDR processing The second reason is that
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in the DT DUACS processing the products can be computed optimally with a centred computation timewindow for OER LWE On the contrary in NRT case future data are not available so the computationtime window is not centred and therefore not optimalAs for NRT products improved altimeter corrections and processing algorithms are used ocean tide modelto correct altimeter data improved methods for orbit error reduction and mapping
Along-Track products global and regional (Mediterranean and Black Seas)
bull Sea Level Anomaly (DT-SLA) for each mission
IV21 Delay of the products
Weekly products are delivered The availability of the products in delayed time is at the best two monthsafter the date of the measurement The product generation needs all the GDR data of all the missions to takeinto account the best corrections as possible The time delay can be longer in the case of a missing mission
IV22 Temporal availibility
The following table presents the available products by mission and by data periodDelayed time SSALTODUACS products
Upd Jason-2 Jason-1new6
Jason-1 GFO Envisatnew6
Envisat ERS-16
ERS-2Topexnew6
Topex
TemporalTimeavailabil-ity
200810ymlowast
200902ymlowast
200204200810
200001200809
201010ymlowast
200210201010
199210200304
200209200510
199209200204
DT-SLA X X X X X X X X X
lowast ym those dates are updated regularly (3 to 4 times per year) and are avalaible when you download thedata at httpwwwmyoceaneuweb24-cataloguephp6 Jason-1 new orbit starting 200809 Envisat new orbit starting 201010 TP new orbit starting 200209 ERS-1The geodetic phases (E-F) are included There are no ERS-1 data between December 23 1993 and April 10 1994(ERS-1 phase D - 2nd ice phase) Note that during that time products are based only on TopexPoseidon data
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V DESCRIPTION OF THE PRODUCT SPECIFICATION
V1 General information
Product Specification SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001
Geographical coverage global
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 20-50km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001 Product Specification
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Product Specification SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002
Geographical coverage 55˚W-35˚E 30˚N-46˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002 Product Specification
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Product Specification SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003
Geographical coverage 27˚E-42˚E 40˚N-47˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003 Product Specification
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Product Specification SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004
Geographical coverage 25˚W-42˚E 21˚N-66˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004 Product Specification
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Product Specification SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005
Geographical coverage 0˚W-360˚E 50˚N-82˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005 Product Specification
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
VI NOMENCLATURE OF FILES
VI1 Nomenclature of files downloaded through the MyOcean Web PortalDirectgetfile Service
VI11 Nomenclature of the product line
The description of the syntax for the SL TAC SLA products line is given by
SEALEVEL_ltREGIONgt_SLA_L3_ltDELAYgt_OBSERVATIONS_008_ltZONEgt_ltLETTERgtwhere
REGION GLO global geographic coverage product
BS Black Sea products
MED Mediterranean products
ARC Arctic products (for NRT products)
EUROPE Europe products (for NRT products)
DELAY NRT near real time products
RAN delayed time or reanalysis products
ZONE 001 number on 3 digits
002
003
004
LETTER a letter on 1 digit
b
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VI12 Nomenclature of the datasets
The nomenclature used is
dataset-duacs-ltdelaygt-ltzonegt-ltmissiongt-lttype of slagt-l3where the fileds in ltgt are described below
delay nrt near-real time productsran delayed time products
zone global global geographic coverage productmedsea Mediterranean productsblacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1 (only for ran)e2 ERS-2 (only for ran)tp TOPEXPoseidon (only for ran)tpn TOPEXPoseidon on its new orbit (only for
ran)g2 GFO (only for ran)j1 Jason-1 (only for ran)j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisat (only for ran)enn Envisat on its new orbitc2 Cryosat-2 (only for nrt)
type of sla sla filtered slasla_unfiltered non filtered sla (only for ran products)
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VI13 Nomenclature of the NetCdf files
The nomenclature used is
ltdelaygt_ltzonegt_ltmissiongt_sla_ltvariablegt_ltdatebegingt_ltdateendgt_ltdateprodgtnc where the fileds in ltgt are de-scribed below
delay nrt near-real time productsdt delayed time products
zone global global geographic coverage productmed Mediterranean products (for dt)mfstep Mediterranean products (for nrt)blacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1e2 ERS-2tp TOPEXPoseidontpn TOPEXPoseidon on its new orbitg2 GFOj1 Jason-1j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisatenn Envisat on its new orbitc2 Cryosat-2
variable vfec filtered and sub-sampled slavxxc non filtered and non sub-sampled sla (only
for dt)datebegin YYYYMMDD() beginning date of the datasetdateend YYYYMMDD() end date of the datasetdateprod YYYYMMDD production date of the dataset
() For dt data as the dates in the file names are rounded the user wanting data for date T has to read the filescontaining dates T+1 and T-1 in their name and check inside the files if there are some data for date T
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VII DATA FORMAT
This chapter presents the data storage format used for MyOcean products
VII1 NetCdf
The products are stored using the NetCDF format NetCDF (network Common Data Form) is an interface for array-oriented data access and a library that provides an implementation of the interface The netCDF library also definesa machine-independent format for representing scientific data Together the interface library and format support thecreation access and sharing of scientific data The netCDF software was developed at the Unidata Program Center inBoulder Colorado The netCDF libraries define a machine-independent format for representing scientific data Pleasesee Unidata NetCDF pages for more information and to retreive NetCDF software package onhttpwwwunidataucaredupackagesnetcdfindexhtml
NetCDF data is
bull Self-Describing A netCDF file includes information about the data it contains
bull Architecture-independent A netCDF file is represented in a form that can be accessed by computers with dif-ferent ways of storing integers characters and floating-point numbers
bull Direct-access A small subset of a large dataset may be accessed efficiently without first reading through allthe preceding data
bull Appendable Data can be appended to a netCDF dataset along one dimension without copying the dataset orredefining its structure The structure of a netCDF dataset can be changed though this sometimes causes thedataset to be copied
bull Sharable One writer and multiple readers may simultaneously access the same netCDF file
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VII2 Structure and semantic of NetCDF along-track files
The NetCDF Sea Level TAC files are based on the attribute data tags defined by the Cooperative OceanAtmosphereResearch Data Service (COARDS) and Climate and Forecast (CF) metadata conventions The CF convention gener-alises and extends the COARDS convention but relaxes the COARDS constraints on dimension and order and specifiesmethods for reducing the size of datasetsA wide range of software are available to write or read NetCDFCF files API are made available by UNIDATA(httpwwwunidataucaredusoftwarenetcdf)
bull CC++Fortran
bull Java
bull MATLAB Objective-C Perl Python R Ruby TclTk
In addition to these conventions the files are using a common structure and semantic
bull 1 dimension is defined
ndash time it is used to check NetCDF variables depending on time
bull 8 variables are defined
ndash short SLA contains the Sea Level Anomaly values for each time given
ndash int longitude contains the longitude for each measurement
ndash short track contains the track number for each measurement
ndash double time contains the time in days since 1950-01-01 000000 UTC for each measurement
ndash short mean_profile_point_index index of the corrsponding point in the track of the mean profile
ndash byte flag flag=0 the processed data comes from OGDR if flag=1 the processed data comes from theIGDR
ndash int latitude contains the latitude for each measurement
ndash short cycle contains the cycle number for each measurement
bull global attributes
ndash the global attributes gives information about the creation of the file
Example of a NetCDF sla file
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netcdf nrt_global_j1_sla_vfec_20101230_20101230_20101230 dimensions
time = 10385 variables
short SLA(time) SLAcoordinates = longitude latitude SLAlong_name = Sea Level Anomaly SLA_FillValue = 32767s SLAadd_offset = 0 SLAscale_factor = 0001 SLAunits = m SLAstandard_name = sea_surface_height_above_sea_level
int longitude(time) longitudelong_name = Longitude of measurement longitude_FillValue = 2147483647 longitudeadd_offset = 0 longitudestandard_name = longitude longitudescale_factor = 1e-06 longitudeunits = degrees_east
short track(time) tracklong_name = Track in cycle the measurement belongs to track_FillValue = 32767s trackunits = 1 trackcoordinates = longitude latitude
double time(time) timelong_name = Time of measurement time_FillValue = 184467440737096e+19 timeaxis = T timestandard_name = time timeunits = days since 1950-01-01 000000 UTC
int latitude(time) latitudelong_name = Latitude of measurement latitude_FillValue = 2147483647 latitudeadd_offset = 0 latitudestandard_name = latitude latitudescale_factor = 1e-06 latitudeunits = degrees_north
short flag(time) flagcoordinates = longitude latitude flag_FillValue = 3267s flaglong_name = data origin flagflag_values = 1s 0s flagflag_meanings = igdr_like non_igdr_like flagcomment = The origin of the data is determined by the types of geophysical datarecords (GDR) used in computation of the SLA 1 for the Interim GDR (IGDR) and0 for Operational GDR (OGDR)
short cycle(time) cyclelong_name = Cycle the measurement belongs to cycle_FillValue = 32767s cycleunits = 1 cyclecoordinates = longitude latitude
global attributeshistory = 22-Feb-2011 155243 CET File created by the SSLATODUACS system version 1001 comment = Produce from ENVISAT Extension Phase satellite altimetry data institution = CLSCNES
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references = httpwwwavisooceanobscomfileadmindocumentsdatatoolshdbk_duacspdf source = satellite altimetry title = along track Sea Level Anomaly Conventions = CF-14
dataSLA =
7 7 11 10 -2 -22 -39 -41 -30 -13 -3 -5 -16 -26 -32 -35-35 -35 -37 -35 -31 -29 -31 -35 -32 -21 -10 -10 -19 -20 -1-69 -57 -49 -45 -39 -30 -28 -31 -27 -13 -2 -5 -15 -3 1112 3 -7 -10 -14 -15 -22 -31 -37 -32 -17 -10
longitude =74743328 74868400 74993968 75120040 75246616 7537372875501368 75629568 75758320 75887656 76017568 76148080 7627920876388952 76477056 76565456 76654144 76743128 76832400 76921984329429568 329535424 329641792 329748672 329856096 329964032330072512 330181536 330291072 330401184
track =92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 9292 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92113 113 113 113 113 113 113 113 113 113 113 113 113 113113 113 113 113 113 113 113 113 113
time =222780000565705 222780001314719 222780002063733222780002812747 222780003561761 222780004310775 222780005059788222780005808802 222780006557816 22278000730683 222780008055844222780008804858 222780009553872 22278001017805 222780010677393222788257112198 222788257486705 222788257861212 222788258235719222788258610226 222788258984733 222788259359239 222788259733746222788260108253 22278826048276
mean_profile_point_index =1872 1878 1884 1890 1896 1902 1908 19141920 1926 1932 1938 1944 1949 1953 1957 1961 1965 1969 19732306 2309 2312 2315 2318 2321 2327 2330 2333 2336 2339 23422345 2348 2351 2354 2357 2360 2363 2366
flag =0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
latitude =-16225506 -16539731 -16853833 -17167810 -17481660 -17795380-18108966 -18422418 -18735729 -19048899 -19361924 -19674801-19987527 -20248015 -20456329 -20664569 -20872739 -2108083739481297 39628277 39775133 39921866 40068472 40214953 4036130840507533 40653629 40799592 40945423 41091120 41236684 41382111
cycle =331 331 331 331 331 331 331 331 331 331 331 331 331
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331 331 331 331 331 331 331 331 331 331 331 331 331 331331 331 331 331 331 331 331 331 331 331 331 331
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VIII HOW TO DOWNLOAD A PRODUCT
VIII1 Download a product through the MyOcean Web Portal DirectgetfileService
You first need to register Please find below the registration stepshttpwwwmyoceaneuweb34-products-and-services-faqphp1Once registered the MyOcean FAQ httpwwwmyoceaneuweb34-products-and-services-faqwill guide you on How to download a product through the MyOcean Web Portal Directgetfile Service
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IX NEWS AND UPDATES
IX1 [Duacs] Operational news
To be kept informed on events occurring on the satellites and on the eventual interruption of the services of the DUACSprocessing system see the [Duacs] operational news on the Aviso websitehttpwwwavisooceanobscomendataoperational-newsindexhtml
IX2 Updates
To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtmlSince 2010 a complete reprocessing of all altimetry data (cumulated total of about 55 years of data) is available Themain changes introduced in the Duacs DT v300 reprocessed data set in SSALTODUACS reprocessed DT data setare listed herehttpwwwavisooceanobscomfileadmindocumentsdataduacsduacs_DT_2010_reprocessing_impactpdf
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DUACS 2011 NRT product from OGDR or FDGDR2
j2 j1nj1g ennProduct stan-dard ref
version C until 20120730and D after
version C version 21
Orbit Navigator Extrapolated CNES MOEGDR-D since 20120121
Ionopheric From-dual frequency altimeter range measurements From GIM model fromcycle 65 (Iijima et al1998 [24])
Dry troposphere Model computed from ECMWF Gaussian grids (new S1 and S2 atmospherictides are applied)
Wet tropo-sphere
AMR radiometer(enhancement in coastal
regions since 20120730)
JMR radiometer MWR radiometer andcorrected from side lobes
DAC Inverse Barometer forecastedOcean tide GOT4v8 (S1 and S2 are included) and TPX 072 [16] for Arctic productsPole tide [Wahr 1985 [53]]Solid earth tide Elastic response to tidal potential [Cartwright and Tayler 1971[5]]
[Cartwright and Edden 1973[6]]Loading tide GOT4v8 (S1 and S2 are included)Sea state bias Non parametric SSB
[Labroue 2004[27]] (withcycles J1 1 to 11 usingGDR-B standards until20120730 and derivedfrom Jason-2 after)
Non parametric SSB[Labroue 2004[27]](with cycles 1 to 21 usingGDR-B standards)
Non parametric SSB[Labroue 2004[27]](with cycles 41 to 60using GDR-B standards)
Orbit error Specific filtering of long-wavelength signal3
Long wave-lengh errors
Optimal Interpolation [Le Traon et al 1998[31]]
Intercalibration Reference from cycle 20Mean profile(see III261)
Computed with cycles 11-353 TP data and with cy-cles 11-250 J1 data refer-enced [19931999]
TPNJ1N computedwith cycles 369-479TPN data referenced[19931999] J1G NoMP can be used insteadthe MSS_CNES_CLS11[39] is used
No Mean Profile can beused for Envisat on itsnew orbit Instead theMSS_CNES_CLS11 [39]is used
(2) A flag included in the along-track files indicates the source of the production (OGDRFDGDR orIGDR) If flag=0 the processed data comes from OGDRsFDGDRs if flag=1 the processed data comesfrom IGDRs(3) Specific data processing was applied on long wave-length signal (sectIII23 of the user manual)
Table 4 Corrections and models applied in SSALTODUACS NRT products produced from OG-DRsFDGDRs
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III22 Acquisition
The acquisition process is twofold
bull straightforward retrieval and reformatting of altimeter data and dynamic auxiliary data (pressure andwet troposphere correction grids from ECMWF are provided by Meteo France TEC grids from JPLNRT MOG2D corrections) from external repositories
bull synchronisation process
To be homogenized properly altimeter data sets require various auxiliary data The acquisition softwaredetects downloads and processes incoming data as soon as they are available on remote sites (externaldatabase FTP site) Data are split into passes if necessary If data flows are missing or late the synchroni-sation engine put unusable data in waiting queues and automatically unfreezes them upon reception of themissing auxiliary data This processing step delivers raw data that is to say data that have been dividedinto cycles and passes and ordered chronologicallyFrom SSALTODUACS V80 the acquisition step uses two different data flows in near-real time the OGDRflow (within a few hours) and the IGDR flow (within a few days)For each OGDR input the system checks that no equivalent IGDR entry is available in the data base beforeacquisition for each IGDR input the system checks and delete the equivalent OGDR entry in the data baseThese operations aim to avoid duplicates in SSALTODUACS system
Figure 6 Overview of the near real time system data flow management
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III23 Homogenization
The Homogenization process consists in applying the most recent corrections models and references rec-ommended for altimeter products Each mission is processed separately as its needs depend on the baseinput data The list of corrections and models currently applied is provided in tables 3 and 4 for NRT dataThe system includes SLA filtering to process OGDR data DUACS extract from these data sets the shortscales (space and time) which are useful to better describe the ocean variability in real time and merge thisinformation with a fair description of large scale signals provided by the multi-satellite observation in nearreal time (read IGDR-based DUACS data) Finally an hybrid SLA is computed
Figure 7 Merging pertinent information from IGDR and OGDR processing
III24 Input data quality control
The Input Data Quality Control is a critical process applied to guarantee that DUACS uses only the mostaccurate altimeter data Thanks to the high quality of current missions this process rejects a small percent-age of altimeter measurements but these erroneous data could be the cause of a significant quality lossThe quality control relies on standard raw data editing with quality flags or parameter thresholds but alsoon complex data editing algorithms based on the detection of erroneous artefacts mono and multi-missioncrossover validation and macroscopic statistics to edit out large data flows that do not meet the systemrsquosrequirements
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III25 Multi-mission cross-calibration
The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistentand accurate information It removes any residual orbit error (OE Le Traon and Ogor 1998[32]) or longwavelength error (LWE Le Traon et al 1998[31]) as well as large scale biases and discrepancies betweenvarious data flows
This process is based on two very different algorithms a global multi-mission crossover minimization fororbit error reduction (OER) and Optimal Interpolation (OI) for LWE
Multi-satellite crossover determination is performed on a daily basis All altimeter fields (measurementcorrections and other fields such as bathymetry MSS) are interpolated at crossover locations and datesCrossovers are then appended to the existing crossover database as more altimeter data become availableThis crossover data set is the input of the Orbit Error Reduction (OER) method Using the precision of thereference mission orbit a very accurate orbit error can be estimated This processing step does not concernOGDR dataLWE is mostly due to residual tidal or inverse barometer errors and high frequency ocean signals The OIused for LWE reduction uses precise parameters derived from
bull accurate statistical description of sea level variability
bull localized correlation scales
bull mission-specific noise and precise assumptions on the long wavelength errors to be removed (from arecent analysis of one year of data from each mission)
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III26 Product generation
The product generation process is composed of four steps computation of raw SLA cross-validationfilteringampsub-sampling and generation of by-products
III261 Computation of raw SLA
Since the geoid is not well known yet the SSH cannot be used directly the SSH anomalies are used insteadThey are computed from the difference of the instantaneous SSH - a temporal reference This temporalreference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeattrack analysis cannot be used The errors affecting the SLAs MPs and MSS have different magnitudes andwavelengths The computation of the SLAs and their errors associated are detailed in Dibarboure et al 2010[9]
Use of a Mean ProfileIn the repeat track analysis (when the satellites flies over a repetitive orbit) measurements are re-sampledalong a theoretical ground track (or mean track) associated to each mission Then a Mean Profile (MP) issubtracted from the re-sampled data to obtain SLA The MP is a time average of similarly re-sampled dataover a long period
bull The Mean Profile used for Jason-2 is computed with 10 years of TP (cycles 11 to 353) and 6 years ofJason-1 (cycles 11 to 250)
bull The Mean Profile used from Jason-1 cycle 262 to 374 (where satellites are on interleaved ground-tracks) is computed with 3 years of TP (cycles 369 to 479)
bull No Mean Profile can be used for Envisat on its new orbit (enn) Jason-1 on its geodetic orbit (j1g) norfor Cryosat-2 mission (c2) because there is no repetitive track The MSS must be used instead (seebelow)
Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible
bull Indeed as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide precise cross-track projection andor interpolation schemes are required to avoid errors
bull The mesoscale variability error (which is lt35 cm for MP between 3 to 5 years and lt1cm for WLof 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a prioriknowledge from Sea Level maps derived from previous iterations or from other missions
bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
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bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for Envisat since november 2010 and for Cryosat-2 mission (c2)because the satellite is not in a repetitive orbit phase The alternative is to use the MSS instead The griddedMSS is derived from along track MPs and data from geodetic phases Thus any error on the MP is alsocontained in the MSS There are essentially 4 types of additional errors on gridded MSS which are hard toquantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
Note that for the Arctic regional products the DTU10 MSS [1] is taken into account instead of the CLS01MSS Indeed the accuracy of DTU10 compared to CLS01 is further demonstrated by the significant sealevel anomaly variance reduction found over the whole Arctic Ocean as shown in Prandi et al [42]
III262 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III263 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
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III27 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III271 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
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III272 Performance indicators
To appreciate the quality situation of the DUACS system new performance indicators are computed dailyThey aim at evaluate the status of the main processing steps of the system the input data availability theinput data coverage the input data quality and the output product quality These indicators are computed foreach and every currently working satellite and combined to obtain the overall status
Figure 8 Example with the key performance indicator on 20090627
See the description the latest and previous indicators on Aviso websitehttpwwwavisooceanobscomindexphpid=1516
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III3 Delayed Time processing steps
III31 Input data models and corrections applied
Delayed Time MyOcean products are generated
bull from Aviso GDR products for TP Jason-1 Jason-2 and Envisat (GDR-A cycles 1 to 22 GDR-Bcycles 23 to 85 GDR-C from cycle 86)
bull from NOAA GDR for GFO and from CERSAT (IFREMER) OPR for ERS-1 and ERS-2 (phases C(1st 35-day repeat orbit period) phase E and F (geodetic phases) phase G for ERS-1 (last 35-dayrepeat orbit period tandem phase with ERS-2 phase A for ERS-2 (1st 35-day repeat orbit periodtandem phase with ERS-1))
All GDR products are computed with a Precise Orbit Ephemeris (POE) and are delivered within 2 to 3months depending on the mission For several missions an updated orbit is used
bull For ERS-1amp-2 the orbit used is DGME-04 provided by Delft Institute (httpwwwdeostudelftnl)until June 2003
bull For TopexPoseidon the orbit used is GSFC (std0809) for the whole mission
bull For Envisat CNES POE of GDR-C standard is used for the whole mission
bull For the whole GFO mission the orbit used is GSFC (std0809) and when not available NASA POE isused
Altimetric product Source Availability Type of orbit
TopexPoseidon GDR NASACNES - GSFC POE
Jason-1 GDR (GDR-C) CNESNASA ~40 days CNES POE
Jason-2 GDR (GDR-C) CNESNASA ~60 days CNES POE
GFO GDR NOAA - GSFCNASA POE
ERS-1amp2 IFREMERESA - DGME-04
Envisat (GDR-A GDR-B andGDR-C from cycle 86)
ESA ~2 months CNES POE
Table 5 SSALTODUACS Delayed Time Input data overview
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DU
AC
S20
11D
Tpr
oduc
t(gtV
30
0)j2
j1j1
ntp
tpn
e1e2
ene
nng2
Prod
uct
stan
dard
ref
GD
R-C
OPR
GD
R-A
(Cyc
les
1to
22)
GD
R-B
(cyc
les
23-8
5)
GD
R(N
OA
A)
Orb
itC
nes
POE
GSF
C(I
TR
F20
05G
RA
CE
last
stan
dard
s)
DG
ME
-04
(Sch
arro
oan
dV
isse
r19
98[4
8]C
NE
SPO
E(G
DR
-1st
anda
rds
forc
ycle
s9
to22
GD
R-C
stan
dard
sfr
omcy
cle
23)
GSF
C(I
TR
F20
05
GR
AC
Ela
stst
anda
rds
Iono
pher
icD
ual f
requ
ency
altim
eter
rang
em
easu
rem
ents
Dua
l fre
quen
cyal
timet
erra
nge
mea
sure
men
ts(T
opex
)D
OR
IS(P
OSE
IDO
N)
Ben
t mod
elB
ent m
odel
(cyc
les
1-36
)G
IMm
odem
from
cycl
e37
((Ii
jima
etal
19
98[2
4])
Dua
l-fr
eque
ncy
altim
eter
rang
em
easu
rem
ent(
cycl
e9-
64)a
ndG
IMm
odel
gtcyc
le65
(Iiji
ma
etal
19
99[2
4])c
orre
cted
from
8m
mbi
as
From
GIM
mod
el(I
ijim
aet
al1
998
[24]
)
Dry
trop
o-sp
here
Mod
elco
mpu
ted
from
EC
MW
FG
auss
ian
grid
s(n
ewS1
and
S2at
mos
pher
ictid
esar
eap
plie
d)
Mod
elco
mpu
ted
from
EC
MW
Fre
ctan
gula
rgri
ds(n
ewS1
and
S2at
mos
pher
ictid
esar
ein
clud
ed)
Wet
trop
o-sp
here
JMR
AM
Rra
diom
eter
furt
hert
han
50km
from
the
coas
tsF
rom
EC
MW
Fm
odel
ford
ista
nces
betw
een
10an
d50
km
TM
Rra
diom
eter
(Sch
aroo
etal
20
04[4
9])
MW
RC
orre
ctio
nof
the
drif
ton
the
236
GH
zbr
ight
ness
tem
pera
ture
(Sch
arro
oet
al
2004
[49]
)Neu
ral
Net
wor
kal
gori
thm
(Tra
nan
dO
blig
is
2003
[50]
MW
Rra
diom
eter
furt
hert
han
50km
from
the
coas
tsan
dco
rrec
ted
from
side
lobe
s(f
rom
cycl
e41
)E
CM
WF
mod
elfo
rdis
tanc
esbe
twee
n10
and
50km
GFO
radi
omet
er
DA
CM
OG
2DH
igh
Res
olut
ion
forc
edw
ithE
CM
WF
pres
sure
and
win
gfie
lds
(S1
and
S2w
ere
excl
uded
)+in
vers
eba
rom
eter
com
pute
dfr
omre
ctan
gula
rgri
ds
Tabl
e6
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(1
2)
Page 33
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
j2j1
j1n
tptp
ne1
e2en
enn
g2O
cean
tide
GO
T4v
7(S
1an
dS2
are
incl
uded
)Po
letid
e[W
ahr
1985
[53]
]So
lidea
rth
tide
Ela
stic
resp
onse
totid
alpo
tent
ial[
Car
twri
ghta
ndTa
yler
197
1[5]
][C
artw
righ
tand
Edd
en1
973[
6]]
Loa
ding
tide
GO
T4v
7(S
1pa
ram
eter
isin
clud
ed)
Sea
stat
ebi
asN
onpa
ram
etri
cSS
B[G
aspa
reta
l20
02[2
0]]
Non
para
met
ric
SSB
[NT
ran
and
al2
010[
51]]
BM
3[G
aspa
ran
dO
gor
1994
[17]
]
Non
para
met
ric
SSB
[Mer
tzet
al
2005
[38]
]
Non
para
met
ric
SSB
[Gas
pare
tal
2002
]w
ithG
DR
-Bst
anda
rds
forc
ycle
s9
to85
and
with
GD
R-C
stan
dard
sfr
omcy
cle
86
Non
para
met
ric
SSB
[NT
ran
etal
20
10[5
1]]
Orb
iter
ror
Glo
bal m
ulti-
mis
sion
cros
sove
rmin
imiz
atio
n(L
eTr
aon
and
Ogo
r19
98[3
2])
Lon
gw
ave-
leng
her
rors
Opt
imal
Inte
rpol
atio
n(L
eTr
aon
etal
19
98[3
1])
Inte
rcal
ibra
tion
Ref
eren
cefr
omcy
cle
11R
efer
ence
from
cycl
e1
to35
4C
orre
ctio
nof
regi
onal
bias
J2J
1de
duce
dfr
omin
terc
alib
ratio
nph
ase
(cyc
le11
J2)
Cor
rect
ion
ofgl
obal
biai
sJ1
TP
deacutedu
ced
from
inte
rcal
ibra
tion
phas
e(c
ycle
s11
J1)
Mea
npr
o-fil
e(s
eeII
I36
1)
Com
pute
dw
ithcy
cles
11-3
53T
Pda
taan
dw
ithcy
cles
11-2
50J1
data
ref
eren
ced
[199
319
99]
TP
J1 c
ompu
ted
with
cycl
es11
-353
TP
data
and
with
cycl
es11
-250
J1da
tar
efer
ence
d[1
993
1999
]T
PNJ
1Nc
ompu
ted
with
cycl
es36
9-47
9T
PNda
tar
efer
ence
d[1
993
1999
]
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
ref
eren
ced
[199
319
99]
EN
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
re
fere
nced
[199
319
99]
EN
Nu
seof
MSS
_CN
ES_
CL
S11
[39]
Com
pute
dw
ithcy
cles
37-1
87G
2da
ta
refe
renc
ed[1
993
1999
]
Peri
odof
use
from
cycl
e9
from
cycl
e9
cycl
es1
to48
1cy
cles
15to
43In
clud
ing
E-F
geod
etic
phas
es
cycl
es1
to83
from
cycl
e9
cycl
es37
to22
2
Tabl
e7
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(2
2)
Page 34
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III32 Acquisition
The acqusition process in Delayed time is much simpler than in Near Real time it consists in a synchronisa-tion process of all the auxiliary data required to homogenize propely the altimeter data sets The acquisitionstep uses the GDRs or the OPRs provided by the agencies
III33 Homogenization
The Homogenization process consists in applying the most recent corrections models and references rec-ommended for altimeter products Each mission is processed separately as its needs depend on the baseinput data The list of corrections and models currently applied is provided in tables 6 and 7 for DT data
III34 Input data quality control
The Input Data Quality Control is a critical process applied to guarantee that DUACS uses only the mostaccurate altimeter data Thanks to the high quality of current missions this process rejects a small percent-age of altimeter measurements but these erroneous data could be the cause of a significant quality lossThe quality control relies on standard raw data editing with quality flags or parameter thresholds but alsoon complex data editing algorithms based on the detection of erroneous artefacts mono and multi-missioncrossover validation and macroscopic statistics to edit out large data flows that do not meet the systemrsquosrequirements
Page 35
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III35 Multi-mission cross-calibration
The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistentand accurate information It removes any residual orbit error (OE Le Traon and Ogor 1998[32]) or longwavelength error (LWE Le Traon et al 1998[31]) as well as large scale biases and discrepancies betweenvarious data flows
This process is based on two very different algorithms a global multi-mission crossover minimization fororbit error reduction (OER) and Optimal Interpolation (OI) for LWE
Multi-satellite crossover determination is performed on a daily basis All altimeter fields (measurementcorrections and other fields such as bathymetry MSS) are interpolated at crossover locations and datesCrossovers are then appended to the existing crossover database as more altimeter data become availableThis crossover data set is the input of the Orbit Error Reduction (OER) method Using the precision of thereference mission orbit a very accurate orbit error can be estimated LWE is mostly due to residual tidalor inverse barometer errors and high frequency ocean signals The OI used for LWE reduction uses preciseparameters derived from
bull accurate statistical description of sea level variability
bull localized correlation scales
bull mission-specific noise and precise assumptions on the long wavelength errors to be removed (from arecent analysis of one year of data from each mission)
Page 36
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III36 Product generation
The product generation process is composed of four steps computation of raw SLA cross-validationfilteringampsub-sampling and generation of by-products
III361 Computation of raw SLA
Since the geoid is not well known yet the SSH cannot be used directly the SSH anomalies are used insteadThey are computed from the difference of the instantaneous SSH - a temporal reference This temporalreference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeattrack analysis cannot be used The errors affecting the SLAs MPs and MSS have different magnitudes andwavelengths The computation of the SLAs and their errors associated are detailed in Dibarboure et al 2010[9]
Use of a Mean ProfileIn the repeat track analysis (when the satellites flies over a repetitive orbit) measurements are re-sampledalong a theoretical ground track (or mean track) associated to each mission Then a Mean Profile (MP) issubtracted from the re-sampled data to obtain SLA The MP is a time average of similarly re-sampled dataover a long period
bull The Mean Profile used for TP (cycles 1 to 364) Jason-1 (cycles 1 to 259) and Jason-2 is computedwith 10 years of TP (cycles 11 to 353) and 6 years of Jason-1 (cycles 11 to 250)
bull The Mean Profile used for TP (cycles 368 to 481) and from Jason-1 cycle 262 to 374 (where satellitesare on interleaved ground-tracks) is computed with 3 years of TP (cycles 369 to 479)
bull The Mean Profile used for ERS-1 in its 35 days repetitive orbit mission ERS-2 and Envisat (only forthe first orbit before November 2010) is computed with 8 years of ERS-2 (cycles 1 to 85) and 6 yearsof Envisat (cycles 10 to 72)
bull No Mean Profile can be used for Envisat on its new orbit (enn) Jason-1 on its geodetic orbit (j1g)because there is no repetitive track The MSS must be used instead (see below)
bull The Mean Profile used for GFO is computed with 7 years of GFO cycles 37 to 187
Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible
bull Indeed as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide precise cross-track projection andor interpolation schemes are required to avoid errors
bull The mesoscale variability error (which is lt35 cm for MP between 3 to 5 years and lt1cm for WLof 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a prioriknowledge from Sea Level maps derived from previous iterations or from other missions
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bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for ERS-1 for its 168 days geodetic mission (phases E-F from April1994 to March 1995) or for Envisat since november 2010 because the satellite is not in a repetitive orbitphase The alternative is to use the MSS instead The gridded MSS is derived from along track MPs anddata from geodetic phases Thus any error on the MP is also contained in the MSS There are essentially 4types of additional errors on gridded MSS which are hard to quantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
III362 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III363 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
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III37 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III371 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
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IV MYOCEAN PRODUCTS
IV1 Near Real Time Products
The purpose of the NRT DUACS component is the acquisition of altimeter data from various altimeter mis-sions in near-real time (ie within a few days at most) the validation and correction of these altimeter datasets (ie edition and selection update of corrections and homogenization orbit error reduction) in order toproduce each day along-track productsProducts are as follows
Along-track products global and regional (Mediterranean and Black Seas Arctic Ocean and Europeareas)
bull Sea Level Anomaly (NRT-SLA) for each mission with NRT-SLA ephemeris
IV11 Delay of the products
The availability of the products in near real time is three to twelve hours after the measurement for along-track products Those products are delivered every day
IV12 Temporal availibility
The following table presents the available products by mission and by data periodNear real time products
NRT Jason-2 Jason-1 and Jason-1geodetic
Envisat new Cryosat-2
Temporal Time availability ymlowast
ongoingymlowast-20120303 for
repeat track and20120507-ongoing for
geodetic track
ymlowast
2012040820120101
ongoing
NRT-SLA X X X X
lowastym the temporal coverage for NRT products is fluctuating and depends on updates of Delayed Time prod-ucts When DT products are updated (3 to 4 times per year) the oldest NRT products are replaced by thebetter quality DT products so that the 2 series are overlapping on few weeks or few months
IV2 Delayed Time Products
The Delayed Time component of SSALTODUACS system is responsible for the production of processedJason-1 Jason-2 TP Envisat GFO ERS12 and even Geosat data in order to provide a homogeneousinter-calibrated and highly accurate long time series of SLA DT products are more precise than NRT products Two reasons explain this quality difference The firstone is the better intrinsic quality of the POE orbit used in the GDR processing The second reason is that
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in the DT DUACS processing the products can be computed optimally with a centred computation timewindow for OER LWE On the contrary in NRT case future data are not available so the computationtime window is not centred and therefore not optimalAs for NRT products improved altimeter corrections and processing algorithms are used ocean tide modelto correct altimeter data improved methods for orbit error reduction and mapping
Along-Track products global and regional (Mediterranean and Black Seas)
bull Sea Level Anomaly (DT-SLA) for each mission
IV21 Delay of the products
Weekly products are delivered The availability of the products in delayed time is at the best two monthsafter the date of the measurement The product generation needs all the GDR data of all the missions to takeinto account the best corrections as possible The time delay can be longer in the case of a missing mission
IV22 Temporal availibility
The following table presents the available products by mission and by data periodDelayed time SSALTODUACS products
Upd Jason-2 Jason-1new6
Jason-1 GFO Envisatnew6
Envisat ERS-16
ERS-2Topexnew6
Topex
TemporalTimeavailabil-ity
200810ymlowast
200902ymlowast
200204200810
200001200809
201010ymlowast
200210201010
199210200304
200209200510
199209200204
DT-SLA X X X X X X X X X
lowast ym those dates are updated regularly (3 to 4 times per year) and are avalaible when you download thedata at httpwwwmyoceaneuweb24-cataloguephp6 Jason-1 new orbit starting 200809 Envisat new orbit starting 201010 TP new orbit starting 200209 ERS-1The geodetic phases (E-F) are included There are no ERS-1 data between December 23 1993 and April 10 1994(ERS-1 phase D - 2nd ice phase) Note that during that time products are based only on TopexPoseidon data
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V DESCRIPTION OF THE PRODUCT SPECIFICATION
V1 General information
Product Specification SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001
Geographical coverage global
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 20-50km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001 Product Specification
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Product Specification SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002
Geographical coverage 55˚W-35˚E 30˚N-46˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002 Product Specification
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Product Specification SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003
Geographical coverage 27˚E-42˚E 40˚N-47˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003 Product Specification
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Product Specification SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004
Geographical coverage 25˚W-42˚E 21˚N-66˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004 Product Specification
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Product Specification SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005
Geographical coverage 0˚W-360˚E 50˚N-82˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005 Product Specification
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VI NOMENCLATURE OF FILES
VI1 Nomenclature of files downloaded through the MyOcean Web PortalDirectgetfile Service
VI11 Nomenclature of the product line
The description of the syntax for the SL TAC SLA products line is given by
SEALEVEL_ltREGIONgt_SLA_L3_ltDELAYgt_OBSERVATIONS_008_ltZONEgt_ltLETTERgtwhere
REGION GLO global geographic coverage product
BS Black Sea products
MED Mediterranean products
ARC Arctic products (for NRT products)
EUROPE Europe products (for NRT products)
DELAY NRT near real time products
RAN delayed time or reanalysis products
ZONE 001 number on 3 digits
002
003
004
LETTER a letter on 1 digit
b
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VI12 Nomenclature of the datasets
The nomenclature used is
dataset-duacs-ltdelaygt-ltzonegt-ltmissiongt-lttype of slagt-l3where the fileds in ltgt are described below
delay nrt near-real time productsran delayed time products
zone global global geographic coverage productmedsea Mediterranean productsblacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1 (only for ran)e2 ERS-2 (only for ran)tp TOPEXPoseidon (only for ran)tpn TOPEXPoseidon on its new orbit (only for
ran)g2 GFO (only for ran)j1 Jason-1 (only for ran)j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisat (only for ran)enn Envisat on its new orbitc2 Cryosat-2 (only for nrt)
type of sla sla filtered slasla_unfiltered non filtered sla (only for ran products)
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VI13 Nomenclature of the NetCdf files
The nomenclature used is
ltdelaygt_ltzonegt_ltmissiongt_sla_ltvariablegt_ltdatebegingt_ltdateendgt_ltdateprodgtnc where the fileds in ltgt are de-scribed below
delay nrt near-real time productsdt delayed time products
zone global global geographic coverage productmed Mediterranean products (for dt)mfstep Mediterranean products (for nrt)blacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1e2 ERS-2tp TOPEXPoseidontpn TOPEXPoseidon on its new orbitg2 GFOj1 Jason-1j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisatenn Envisat on its new orbitc2 Cryosat-2
variable vfec filtered and sub-sampled slavxxc non filtered and non sub-sampled sla (only
for dt)datebegin YYYYMMDD() beginning date of the datasetdateend YYYYMMDD() end date of the datasetdateprod YYYYMMDD production date of the dataset
() For dt data as the dates in the file names are rounded the user wanting data for date T has to read the filescontaining dates T+1 and T-1 in their name and check inside the files if there are some data for date T
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VII DATA FORMAT
This chapter presents the data storage format used for MyOcean products
VII1 NetCdf
The products are stored using the NetCDF format NetCDF (network Common Data Form) is an interface for array-oriented data access and a library that provides an implementation of the interface The netCDF library also definesa machine-independent format for representing scientific data Together the interface library and format support thecreation access and sharing of scientific data The netCDF software was developed at the Unidata Program Center inBoulder Colorado The netCDF libraries define a machine-independent format for representing scientific data Pleasesee Unidata NetCDF pages for more information and to retreive NetCDF software package onhttpwwwunidataucaredupackagesnetcdfindexhtml
NetCDF data is
bull Self-Describing A netCDF file includes information about the data it contains
bull Architecture-independent A netCDF file is represented in a form that can be accessed by computers with dif-ferent ways of storing integers characters and floating-point numbers
bull Direct-access A small subset of a large dataset may be accessed efficiently without first reading through allthe preceding data
bull Appendable Data can be appended to a netCDF dataset along one dimension without copying the dataset orredefining its structure The structure of a netCDF dataset can be changed though this sometimes causes thedataset to be copied
bull Sharable One writer and multiple readers may simultaneously access the same netCDF file
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VII2 Structure and semantic of NetCDF along-track files
The NetCDF Sea Level TAC files are based on the attribute data tags defined by the Cooperative OceanAtmosphereResearch Data Service (COARDS) and Climate and Forecast (CF) metadata conventions The CF convention gener-alises and extends the COARDS convention but relaxes the COARDS constraints on dimension and order and specifiesmethods for reducing the size of datasetsA wide range of software are available to write or read NetCDFCF files API are made available by UNIDATA(httpwwwunidataucaredusoftwarenetcdf)
bull CC++Fortran
bull Java
bull MATLAB Objective-C Perl Python R Ruby TclTk
In addition to these conventions the files are using a common structure and semantic
bull 1 dimension is defined
ndash time it is used to check NetCDF variables depending on time
bull 8 variables are defined
ndash short SLA contains the Sea Level Anomaly values for each time given
ndash int longitude contains the longitude for each measurement
ndash short track contains the track number for each measurement
ndash double time contains the time in days since 1950-01-01 000000 UTC for each measurement
ndash short mean_profile_point_index index of the corrsponding point in the track of the mean profile
ndash byte flag flag=0 the processed data comes from OGDR if flag=1 the processed data comes from theIGDR
ndash int latitude contains the latitude for each measurement
ndash short cycle contains the cycle number for each measurement
bull global attributes
ndash the global attributes gives information about the creation of the file
Example of a NetCDF sla file
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netcdf nrt_global_j1_sla_vfec_20101230_20101230_20101230 dimensions
time = 10385 variables
short SLA(time) SLAcoordinates = longitude latitude SLAlong_name = Sea Level Anomaly SLA_FillValue = 32767s SLAadd_offset = 0 SLAscale_factor = 0001 SLAunits = m SLAstandard_name = sea_surface_height_above_sea_level
int longitude(time) longitudelong_name = Longitude of measurement longitude_FillValue = 2147483647 longitudeadd_offset = 0 longitudestandard_name = longitude longitudescale_factor = 1e-06 longitudeunits = degrees_east
short track(time) tracklong_name = Track in cycle the measurement belongs to track_FillValue = 32767s trackunits = 1 trackcoordinates = longitude latitude
double time(time) timelong_name = Time of measurement time_FillValue = 184467440737096e+19 timeaxis = T timestandard_name = time timeunits = days since 1950-01-01 000000 UTC
int latitude(time) latitudelong_name = Latitude of measurement latitude_FillValue = 2147483647 latitudeadd_offset = 0 latitudestandard_name = latitude latitudescale_factor = 1e-06 latitudeunits = degrees_north
short flag(time) flagcoordinates = longitude latitude flag_FillValue = 3267s flaglong_name = data origin flagflag_values = 1s 0s flagflag_meanings = igdr_like non_igdr_like flagcomment = The origin of the data is determined by the types of geophysical datarecords (GDR) used in computation of the SLA 1 for the Interim GDR (IGDR) and0 for Operational GDR (OGDR)
short cycle(time) cyclelong_name = Cycle the measurement belongs to cycle_FillValue = 32767s cycleunits = 1 cyclecoordinates = longitude latitude
global attributeshistory = 22-Feb-2011 155243 CET File created by the SSLATODUACS system version 1001 comment = Produce from ENVISAT Extension Phase satellite altimetry data institution = CLSCNES
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references = httpwwwavisooceanobscomfileadmindocumentsdatatoolshdbk_duacspdf source = satellite altimetry title = along track Sea Level Anomaly Conventions = CF-14
dataSLA =
7 7 11 10 -2 -22 -39 -41 -30 -13 -3 -5 -16 -26 -32 -35-35 -35 -37 -35 -31 -29 -31 -35 -32 -21 -10 -10 -19 -20 -1-69 -57 -49 -45 -39 -30 -28 -31 -27 -13 -2 -5 -15 -3 1112 3 -7 -10 -14 -15 -22 -31 -37 -32 -17 -10
longitude =74743328 74868400 74993968 75120040 75246616 7537372875501368 75629568 75758320 75887656 76017568 76148080 7627920876388952 76477056 76565456 76654144 76743128 76832400 76921984329429568 329535424 329641792 329748672 329856096 329964032330072512 330181536 330291072 330401184
track =92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 9292 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92113 113 113 113 113 113 113 113 113 113 113 113 113 113113 113 113 113 113 113 113 113 113
time =222780000565705 222780001314719 222780002063733222780002812747 222780003561761 222780004310775 222780005059788222780005808802 222780006557816 22278000730683 222780008055844222780008804858 222780009553872 22278001017805 222780010677393222788257112198 222788257486705 222788257861212 222788258235719222788258610226 222788258984733 222788259359239 222788259733746222788260108253 22278826048276
mean_profile_point_index =1872 1878 1884 1890 1896 1902 1908 19141920 1926 1932 1938 1944 1949 1953 1957 1961 1965 1969 19732306 2309 2312 2315 2318 2321 2327 2330 2333 2336 2339 23422345 2348 2351 2354 2357 2360 2363 2366
flag =0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
latitude =-16225506 -16539731 -16853833 -17167810 -17481660 -17795380-18108966 -18422418 -18735729 -19048899 -19361924 -19674801-19987527 -20248015 -20456329 -20664569 -20872739 -2108083739481297 39628277 39775133 39921866 40068472 40214953 4036130840507533 40653629 40799592 40945423 41091120 41236684 41382111
cycle =331 331 331 331 331 331 331 331 331 331 331 331 331
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331 331 331 331 331 331 331 331 331 331 331 331 331 331331 331 331 331 331 331 331 331 331 331 331 331
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VIII HOW TO DOWNLOAD A PRODUCT
VIII1 Download a product through the MyOcean Web Portal DirectgetfileService
You first need to register Please find below the registration stepshttpwwwmyoceaneuweb34-products-and-services-faqphp1Once registered the MyOcean FAQ httpwwwmyoceaneuweb34-products-and-services-faqwill guide you on How to download a product through the MyOcean Web Portal Directgetfile Service
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IX NEWS AND UPDATES
IX1 [Duacs] Operational news
To be kept informed on events occurring on the satellites and on the eventual interruption of the services of the DUACSprocessing system see the [Duacs] operational news on the Aviso websitehttpwwwavisooceanobscomendataoperational-newsindexhtml
IX2 Updates
To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtmlSince 2010 a complete reprocessing of all altimetry data (cumulated total of about 55 years of data) is available Themain changes introduced in the Duacs DT v300 reprocessed data set in SSALTODUACS reprocessed DT data setare listed herehttpwwwavisooceanobscomfileadmindocumentsdataduacsduacs_DT_2010_reprocessing_impactpdf
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III22 Acquisition
The acquisition process is twofold
bull straightforward retrieval and reformatting of altimeter data and dynamic auxiliary data (pressure andwet troposphere correction grids from ECMWF are provided by Meteo France TEC grids from JPLNRT MOG2D corrections) from external repositories
bull synchronisation process
To be homogenized properly altimeter data sets require various auxiliary data The acquisition softwaredetects downloads and processes incoming data as soon as they are available on remote sites (externaldatabase FTP site) Data are split into passes if necessary If data flows are missing or late the synchroni-sation engine put unusable data in waiting queues and automatically unfreezes them upon reception of themissing auxiliary data This processing step delivers raw data that is to say data that have been dividedinto cycles and passes and ordered chronologicallyFrom SSALTODUACS V80 the acquisition step uses two different data flows in near-real time the OGDRflow (within a few hours) and the IGDR flow (within a few days)For each OGDR input the system checks that no equivalent IGDR entry is available in the data base beforeacquisition for each IGDR input the system checks and delete the equivalent OGDR entry in the data baseThese operations aim to avoid duplicates in SSALTODUACS system
Figure 6 Overview of the near real time system data flow management
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III23 Homogenization
The Homogenization process consists in applying the most recent corrections models and references rec-ommended for altimeter products Each mission is processed separately as its needs depend on the baseinput data The list of corrections and models currently applied is provided in tables 3 and 4 for NRT dataThe system includes SLA filtering to process OGDR data DUACS extract from these data sets the shortscales (space and time) which are useful to better describe the ocean variability in real time and merge thisinformation with a fair description of large scale signals provided by the multi-satellite observation in nearreal time (read IGDR-based DUACS data) Finally an hybrid SLA is computed
Figure 7 Merging pertinent information from IGDR and OGDR processing
III24 Input data quality control
The Input Data Quality Control is a critical process applied to guarantee that DUACS uses only the mostaccurate altimeter data Thanks to the high quality of current missions this process rejects a small percent-age of altimeter measurements but these erroneous data could be the cause of a significant quality lossThe quality control relies on standard raw data editing with quality flags or parameter thresholds but alsoon complex data editing algorithms based on the detection of erroneous artefacts mono and multi-missioncrossover validation and macroscopic statistics to edit out large data flows that do not meet the systemrsquosrequirements
Page 26
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III25 Multi-mission cross-calibration
The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistentand accurate information It removes any residual orbit error (OE Le Traon and Ogor 1998[32]) or longwavelength error (LWE Le Traon et al 1998[31]) as well as large scale biases and discrepancies betweenvarious data flows
This process is based on two very different algorithms a global multi-mission crossover minimization fororbit error reduction (OER) and Optimal Interpolation (OI) for LWE
Multi-satellite crossover determination is performed on a daily basis All altimeter fields (measurementcorrections and other fields such as bathymetry MSS) are interpolated at crossover locations and datesCrossovers are then appended to the existing crossover database as more altimeter data become availableThis crossover data set is the input of the Orbit Error Reduction (OER) method Using the precision of thereference mission orbit a very accurate orbit error can be estimated This processing step does not concernOGDR dataLWE is mostly due to residual tidal or inverse barometer errors and high frequency ocean signals The OIused for LWE reduction uses precise parameters derived from
bull accurate statistical description of sea level variability
bull localized correlation scales
bull mission-specific noise and precise assumptions on the long wavelength errors to be removed (from arecent analysis of one year of data from each mission)
Page 27
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III26 Product generation
The product generation process is composed of four steps computation of raw SLA cross-validationfilteringampsub-sampling and generation of by-products
III261 Computation of raw SLA
Since the geoid is not well known yet the SSH cannot be used directly the SSH anomalies are used insteadThey are computed from the difference of the instantaneous SSH - a temporal reference This temporalreference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeattrack analysis cannot be used The errors affecting the SLAs MPs and MSS have different magnitudes andwavelengths The computation of the SLAs and their errors associated are detailed in Dibarboure et al 2010[9]
Use of a Mean ProfileIn the repeat track analysis (when the satellites flies over a repetitive orbit) measurements are re-sampledalong a theoretical ground track (or mean track) associated to each mission Then a Mean Profile (MP) issubtracted from the re-sampled data to obtain SLA The MP is a time average of similarly re-sampled dataover a long period
bull The Mean Profile used for Jason-2 is computed with 10 years of TP (cycles 11 to 353) and 6 years ofJason-1 (cycles 11 to 250)
bull The Mean Profile used from Jason-1 cycle 262 to 374 (where satellites are on interleaved ground-tracks) is computed with 3 years of TP (cycles 369 to 479)
bull No Mean Profile can be used for Envisat on its new orbit (enn) Jason-1 on its geodetic orbit (j1g) norfor Cryosat-2 mission (c2) because there is no repetitive track The MSS must be used instead (seebelow)
Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible
bull Indeed as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide precise cross-track projection andor interpolation schemes are required to avoid errors
bull The mesoscale variability error (which is lt35 cm for MP between 3 to 5 years and lt1cm for WLof 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a prioriknowledge from Sea Level maps derived from previous iterations or from other missions
bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
Page 28
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for Envisat since november 2010 and for Cryosat-2 mission (c2)because the satellite is not in a repetitive orbit phase The alternative is to use the MSS instead The griddedMSS is derived from along track MPs and data from geodetic phases Thus any error on the MP is alsocontained in the MSS There are essentially 4 types of additional errors on gridded MSS which are hard toquantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
Note that for the Arctic regional products the DTU10 MSS [1] is taken into account instead of the CLS01MSS Indeed the accuracy of DTU10 compared to CLS01 is further demonstrated by the significant sealevel anomaly variance reduction found over the whole Arctic Ocean as shown in Prandi et al [42]
III262 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III263 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
Page 29
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III27 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III271 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
Page 30
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III272 Performance indicators
To appreciate the quality situation of the DUACS system new performance indicators are computed dailyThey aim at evaluate the status of the main processing steps of the system the input data availability theinput data coverage the input data quality and the output product quality These indicators are computed foreach and every currently working satellite and combined to obtain the overall status
Figure 8 Example with the key performance indicator on 20090627
See the description the latest and previous indicators on Aviso websitehttpwwwavisooceanobscomindexphpid=1516
Page 31
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III3 Delayed Time processing steps
III31 Input data models and corrections applied
Delayed Time MyOcean products are generated
bull from Aviso GDR products for TP Jason-1 Jason-2 and Envisat (GDR-A cycles 1 to 22 GDR-Bcycles 23 to 85 GDR-C from cycle 86)
bull from NOAA GDR for GFO and from CERSAT (IFREMER) OPR for ERS-1 and ERS-2 (phases C(1st 35-day repeat orbit period) phase E and F (geodetic phases) phase G for ERS-1 (last 35-dayrepeat orbit period tandem phase with ERS-2 phase A for ERS-2 (1st 35-day repeat orbit periodtandem phase with ERS-1))
All GDR products are computed with a Precise Orbit Ephemeris (POE) and are delivered within 2 to 3months depending on the mission For several missions an updated orbit is used
bull For ERS-1amp-2 the orbit used is DGME-04 provided by Delft Institute (httpwwwdeostudelftnl)until June 2003
bull For TopexPoseidon the orbit used is GSFC (std0809) for the whole mission
bull For Envisat CNES POE of GDR-C standard is used for the whole mission
bull For the whole GFO mission the orbit used is GSFC (std0809) and when not available NASA POE isused
Altimetric product Source Availability Type of orbit
TopexPoseidon GDR NASACNES - GSFC POE
Jason-1 GDR (GDR-C) CNESNASA ~40 days CNES POE
Jason-2 GDR (GDR-C) CNESNASA ~60 days CNES POE
GFO GDR NOAA - GSFCNASA POE
ERS-1amp2 IFREMERESA - DGME-04
Envisat (GDR-A GDR-B andGDR-C from cycle 86)
ESA ~2 months CNES POE
Table 5 SSALTODUACS Delayed Time Input data overview
Page 32
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
DU
AC
S20
11D
Tpr
oduc
t(gtV
30
0)j2
j1j1
ntp
tpn
e1e2
ene
nng2
Prod
uct
stan
dard
ref
GD
R-C
OPR
GD
R-A
(Cyc
les
1to
22)
GD
R-B
(cyc
les
23-8
5)
GD
R(N
OA
A)
Orb
itC
nes
POE
GSF
C(I
TR
F20
05G
RA
CE
last
stan
dard
s)
DG
ME
-04
(Sch
arro
oan
dV
isse
r19
98[4
8]C
NE
SPO
E(G
DR
-1st
anda
rds
forc
ycle
s9
to22
GD
R-C
stan
dard
sfr
omcy
cle
23)
GSF
C(I
TR
F20
05
GR
AC
Ela
stst
anda
rds
Iono
pher
icD
ual f
requ
ency
altim
eter
rang
em
easu
rem
ents
Dua
l fre
quen
cyal
timet
erra
nge
mea
sure
men
ts(T
opex
)D
OR
IS(P
OSE
IDO
N)
Ben
t mod
elB
ent m
odel
(cyc
les
1-36
)G
IMm
odem
from
cycl
e37
((Ii
jima
etal
19
98[2
4])
Dua
l-fr
eque
ncy
altim
eter
rang
em
easu
rem
ent(
cycl
e9-
64)a
ndG
IMm
odel
gtcyc
le65
(Iiji
ma
etal
19
99[2
4])c
orre
cted
from
8m
mbi
as
From
GIM
mod
el(I
ijim
aet
al1
998
[24]
)
Dry
trop
o-sp
here
Mod
elco
mpu
ted
from
EC
MW
FG
auss
ian
grid
s(n
ewS1
and
S2at
mos
pher
ictid
esar
eap
plie
d)
Mod
elco
mpu
ted
from
EC
MW
Fre
ctan
gula
rgri
ds(n
ewS1
and
S2at
mos
pher
ictid
esar
ein
clud
ed)
Wet
trop
o-sp
here
JMR
AM
Rra
diom
eter
furt
hert
han
50km
from
the
coas
tsF
rom
EC
MW
Fm
odel
ford
ista
nces
betw
een
10an
d50
km
TM
Rra
diom
eter
(Sch
aroo
etal
20
04[4
9])
MW
RC
orre
ctio
nof
the
drif
ton
the
236
GH
zbr
ight
ness
tem
pera
ture
(Sch
arro
oet
al
2004
[49]
)Neu
ral
Net
wor
kal
gori
thm
(Tra
nan
dO
blig
is
2003
[50]
MW
Rra
diom
eter
furt
hert
han
50km
from
the
coas
tsan
dco
rrec
ted
from
side
lobe
s(f
rom
cycl
e41
)E
CM
WF
mod
elfo
rdis
tanc
esbe
twee
n10
and
50km
GFO
radi
omet
er
DA
CM
OG
2DH
igh
Res
olut
ion
forc
edw
ithE
CM
WF
pres
sure
and
win
gfie
lds
(S1
and
S2w
ere
excl
uded
)+in
vers
eba
rom
eter
com
pute
dfr
omre
ctan
gula
rgri
ds
Tabl
e6
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(1
2)
Page 33
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
j2j1
j1n
tptp
ne1
e2en
enn
g2O
cean
tide
GO
T4v
7(S
1an
dS2
are
incl
uded
)Po
letid
e[W
ahr
1985
[53]
]So
lidea
rth
tide
Ela
stic
resp
onse
totid
alpo
tent
ial[
Car
twri
ghta
ndTa
yler
197
1[5]
][C
artw
righ
tand
Edd
en1
973[
6]]
Loa
ding
tide
GO
T4v
7(S
1pa
ram
eter
isin
clud
ed)
Sea
stat
ebi
asN
onpa
ram
etri
cSS
B[G
aspa
reta
l20
02[2
0]]
Non
para
met
ric
SSB
[NT
ran
and
al2
010[
51]]
BM
3[G
aspa
ran
dO
gor
1994
[17]
]
Non
para
met
ric
SSB
[Mer
tzet
al
2005
[38]
]
Non
para
met
ric
SSB
[Gas
pare
tal
2002
]w
ithG
DR
-Bst
anda
rds
forc
ycle
s9
to85
and
with
GD
R-C
stan
dard
sfr
omcy
cle
86
Non
para
met
ric
SSB
[NT
ran
etal
20
10[5
1]]
Orb
iter
ror
Glo
bal m
ulti-
mis
sion
cros
sove
rmin
imiz
atio
n(L
eTr
aon
and
Ogo
r19
98[3
2])
Lon
gw
ave-
leng
her
rors
Opt
imal
Inte
rpol
atio
n(L
eTr
aon
etal
19
98[3
1])
Inte
rcal
ibra
tion
Ref
eren
cefr
omcy
cle
11R
efer
ence
from
cycl
e1
to35
4C
orre
ctio
nof
regi
onal
bias
J2J
1de
duce
dfr
omin
terc
alib
ratio
nph
ase
(cyc
le11
J2)
Cor
rect
ion
ofgl
obal
biai
sJ1
TP
deacutedu
ced
from
inte
rcal
ibra
tion
phas
e(c
ycle
s11
J1)
Mea
npr
o-fil
e(s
eeII
I36
1)
Com
pute
dw
ithcy
cles
11-3
53T
Pda
taan
dw
ithcy
cles
11-2
50J1
data
ref
eren
ced
[199
319
99]
TP
J1 c
ompu
ted
with
cycl
es11
-353
TP
data
and
with
cycl
es11
-250
J1da
tar
efer
ence
d[1
993
1999
]T
PNJ
1Nc
ompu
ted
with
cycl
es36
9-47
9T
PNda
tar
efer
ence
d[1
993
1999
]
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
ref
eren
ced
[199
319
99]
EN
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
re
fere
nced
[199
319
99]
EN
Nu
seof
MSS
_CN
ES_
CL
S11
[39]
Com
pute
dw
ithcy
cles
37-1
87G
2da
ta
refe
renc
ed[1
993
1999
]
Peri
odof
use
from
cycl
e9
from
cycl
e9
cycl
es1
to48
1cy
cles
15to
43In
clud
ing
E-F
geod
etic
phas
es
cycl
es1
to83
from
cycl
e9
cycl
es37
to22
2
Tabl
e7
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(2
2)
Page 34
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III32 Acquisition
The acqusition process in Delayed time is much simpler than in Near Real time it consists in a synchronisa-tion process of all the auxiliary data required to homogenize propely the altimeter data sets The acquisitionstep uses the GDRs or the OPRs provided by the agencies
III33 Homogenization
The Homogenization process consists in applying the most recent corrections models and references rec-ommended for altimeter products Each mission is processed separately as its needs depend on the baseinput data The list of corrections and models currently applied is provided in tables 6 and 7 for DT data
III34 Input data quality control
The Input Data Quality Control is a critical process applied to guarantee that DUACS uses only the mostaccurate altimeter data Thanks to the high quality of current missions this process rejects a small percent-age of altimeter measurements but these erroneous data could be the cause of a significant quality lossThe quality control relies on standard raw data editing with quality flags or parameter thresholds but alsoon complex data editing algorithms based on the detection of erroneous artefacts mono and multi-missioncrossover validation and macroscopic statistics to edit out large data flows that do not meet the systemrsquosrequirements
Page 35
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III35 Multi-mission cross-calibration
The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistentand accurate information It removes any residual orbit error (OE Le Traon and Ogor 1998[32]) or longwavelength error (LWE Le Traon et al 1998[31]) as well as large scale biases and discrepancies betweenvarious data flows
This process is based on two very different algorithms a global multi-mission crossover minimization fororbit error reduction (OER) and Optimal Interpolation (OI) for LWE
Multi-satellite crossover determination is performed on a daily basis All altimeter fields (measurementcorrections and other fields such as bathymetry MSS) are interpolated at crossover locations and datesCrossovers are then appended to the existing crossover database as more altimeter data become availableThis crossover data set is the input of the Orbit Error Reduction (OER) method Using the precision of thereference mission orbit a very accurate orbit error can be estimated LWE is mostly due to residual tidalor inverse barometer errors and high frequency ocean signals The OI used for LWE reduction uses preciseparameters derived from
bull accurate statistical description of sea level variability
bull localized correlation scales
bull mission-specific noise and precise assumptions on the long wavelength errors to be removed (from arecent analysis of one year of data from each mission)
Page 36
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III36 Product generation
The product generation process is composed of four steps computation of raw SLA cross-validationfilteringampsub-sampling and generation of by-products
III361 Computation of raw SLA
Since the geoid is not well known yet the SSH cannot be used directly the SSH anomalies are used insteadThey are computed from the difference of the instantaneous SSH - a temporal reference This temporalreference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeattrack analysis cannot be used The errors affecting the SLAs MPs and MSS have different magnitudes andwavelengths The computation of the SLAs and their errors associated are detailed in Dibarboure et al 2010[9]
Use of a Mean ProfileIn the repeat track analysis (when the satellites flies over a repetitive orbit) measurements are re-sampledalong a theoretical ground track (or mean track) associated to each mission Then a Mean Profile (MP) issubtracted from the re-sampled data to obtain SLA The MP is a time average of similarly re-sampled dataover a long period
bull The Mean Profile used for TP (cycles 1 to 364) Jason-1 (cycles 1 to 259) and Jason-2 is computedwith 10 years of TP (cycles 11 to 353) and 6 years of Jason-1 (cycles 11 to 250)
bull The Mean Profile used for TP (cycles 368 to 481) and from Jason-1 cycle 262 to 374 (where satellitesare on interleaved ground-tracks) is computed with 3 years of TP (cycles 369 to 479)
bull The Mean Profile used for ERS-1 in its 35 days repetitive orbit mission ERS-2 and Envisat (only forthe first orbit before November 2010) is computed with 8 years of ERS-2 (cycles 1 to 85) and 6 yearsof Envisat (cycles 10 to 72)
bull No Mean Profile can be used for Envisat on its new orbit (enn) Jason-1 on its geodetic orbit (j1g)because there is no repetitive track The MSS must be used instead (see below)
bull The Mean Profile used for GFO is computed with 7 years of GFO cycles 37 to 187
Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible
bull Indeed as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide precise cross-track projection andor interpolation schemes are required to avoid errors
bull The mesoscale variability error (which is lt35 cm for MP between 3 to 5 years and lt1cm for WLof 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a prioriknowledge from Sea Level maps derived from previous iterations or from other missions
Page 37
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for ERS-1 for its 168 days geodetic mission (phases E-F from April1994 to March 1995) or for Envisat since november 2010 because the satellite is not in a repetitive orbitphase The alternative is to use the MSS instead The gridded MSS is derived from along track MPs anddata from geodetic phases Thus any error on the MP is also contained in the MSS There are essentially 4types of additional errors on gridded MSS which are hard to quantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
III362 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III363 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
Page 38
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III37 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III371 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
Page 39
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
IV MYOCEAN PRODUCTS
IV1 Near Real Time Products
The purpose of the NRT DUACS component is the acquisition of altimeter data from various altimeter mis-sions in near-real time (ie within a few days at most) the validation and correction of these altimeter datasets (ie edition and selection update of corrections and homogenization orbit error reduction) in order toproduce each day along-track productsProducts are as follows
Along-track products global and regional (Mediterranean and Black Seas Arctic Ocean and Europeareas)
bull Sea Level Anomaly (NRT-SLA) for each mission with NRT-SLA ephemeris
IV11 Delay of the products
The availability of the products in near real time is three to twelve hours after the measurement for along-track products Those products are delivered every day
IV12 Temporal availibility
The following table presents the available products by mission and by data periodNear real time products
NRT Jason-2 Jason-1 and Jason-1geodetic
Envisat new Cryosat-2
Temporal Time availability ymlowast
ongoingymlowast-20120303 for
repeat track and20120507-ongoing for
geodetic track
ymlowast
2012040820120101
ongoing
NRT-SLA X X X X
lowastym the temporal coverage for NRT products is fluctuating and depends on updates of Delayed Time prod-ucts When DT products are updated (3 to 4 times per year) the oldest NRT products are replaced by thebetter quality DT products so that the 2 series are overlapping on few weeks or few months
IV2 Delayed Time Products
The Delayed Time component of SSALTODUACS system is responsible for the production of processedJason-1 Jason-2 TP Envisat GFO ERS12 and even Geosat data in order to provide a homogeneousinter-calibrated and highly accurate long time series of SLA DT products are more precise than NRT products Two reasons explain this quality difference The firstone is the better intrinsic quality of the POE orbit used in the GDR processing The second reason is that
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in the DT DUACS processing the products can be computed optimally with a centred computation timewindow for OER LWE On the contrary in NRT case future data are not available so the computationtime window is not centred and therefore not optimalAs for NRT products improved altimeter corrections and processing algorithms are used ocean tide modelto correct altimeter data improved methods for orbit error reduction and mapping
Along-Track products global and regional (Mediterranean and Black Seas)
bull Sea Level Anomaly (DT-SLA) for each mission
IV21 Delay of the products
Weekly products are delivered The availability of the products in delayed time is at the best two monthsafter the date of the measurement The product generation needs all the GDR data of all the missions to takeinto account the best corrections as possible The time delay can be longer in the case of a missing mission
IV22 Temporal availibility
The following table presents the available products by mission and by data periodDelayed time SSALTODUACS products
Upd Jason-2 Jason-1new6
Jason-1 GFO Envisatnew6
Envisat ERS-16
ERS-2Topexnew6
Topex
TemporalTimeavailabil-ity
200810ymlowast
200902ymlowast
200204200810
200001200809
201010ymlowast
200210201010
199210200304
200209200510
199209200204
DT-SLA X X X X X X X X X
lowast ym those dates are updated regularly (3 to 4 times per year) and are avalaible when you download thedata at httpwwwmyoceaneuweb24-cataloguephp6 Jason-1 new orbit starting 200809 Envisat new orbit starting 201010 TP new orbit starting 200209 ERS-1The geodetic phases (E-F) are included There are no ERS-1 data between December 23 1993 and April 10 1994(ERS-1 phase D - 2nd ice phase) Note that during that time products are based only on TopexPoseidon data
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V DESCRIPTION OF THE PRODUCT SPECIFICATION
V1 General information
Product Specification SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001
Geographical coverage global
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 20-50km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001 Product Specification
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Product Specification SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002
Geographical coverage 55˚W-35˚E 30˚N-46˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002 Product Specification
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Product Specification SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003
Geographical coverage 27˚E-42˚E 40˚N-47˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003 Product Specification
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Product Specification SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004
Geographical coverage 25˚W-42˚E 21˚N-66˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004 Product Specification
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Product Specification SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005
Geographical coverage 0˚W-360˚E 50˚N-82˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005 Product Specification
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VI NOMENCLATURE OF FILES
VI1 Nomenclature of files downloaded through the MyOcean Web PortalDirectgetfile Service
VI11 Nomenclature of the product line
The description of the syntax for the SL TAC SLA products line is given by
SEALEVEL_ltREGIONgt_SLA_L3_ltDELAYgt_OBSERVATIONS_008_ltZONEgt_ltLETTERgtwhere
REGION GLO global geographic coverage product
BS Black Sea products
MED Mediterranean products
ARC Arctic products (for NRT products)
EUROPE Europe products (for NRT products)
DELAY NRT near real time products
RAN delayed time or reanalysis products
ZONE 001 number on 3 digits
002
003
004
LETTER a letter on 1 digit
b
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VI12 Nomenclature of the datasets
The nomenclature used is
dataset-duacs-ltdelaygt-ltzonegt-ltmissiongt-lttype of slagt-l3where the fileds in ltgt are described below
delay nrt near-real time productsran delayed time products
zone global global geographic coverage productmedsea Mediterranean productsblacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1 (only for ran)e2 ERS-2 (only for ran)tp TOPEXPoseidon (only for ran)tpn TOPEXPoseidon on its new orbit (only for
ran)g2 GFO (only for ran)j1 Jason-1 (only for ran)j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisat (only for ran)enn Envisat on its new orbitc2 Cryosat-2 (only for nrt)
type of sla sla filtered slasla_unfiltered non filtered sla (only for ran products)
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VI13 Nomenclature of the NetCdf files
The nomenclature used is
ltdelaygt_ltzonegt_ltmissiongt_sla_ltvariablegt_ltdatebegingt_ltdateendgt_ltdateprodgtnc where the fileds in ltgt are de-scribed below
delay nrt near-real time productsdt delayed time products
zone global global geographic coverage productmed Mediterranean products (for dt)mfstep Mediterranean products (for nrt)blacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1e2 ERS-2tp TOPEXPoseidontpn TOPEXPoseidon on its new orbitg2 GFOj1 Jason-1j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisatenn Envisat on its new orbitc2 Cryosat-2
variable vfec filtered and sub-sampled slavxxc non filtered and non sub-sampled sla (only
for dt)datebegin YYYYMMDD() beginning date of the datasetdateend YYYYMMDD() end date of the datasetdateprod YYYYMMDD production date of the dataset
() For dt data as the dates in the file names are rounded the user wanting data for date T has to read the filescontaining dates T+1 and T-1 in their name and check inside the files if there are some data for date T
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VII DATA FORMAT
This chapter presents the data storage format used for MyOcean products
VII1 NetCdf
The products are stored using the NetCDF format NetCDF (network Common Data Form) is an interface for array-oriented data access and a library that provides an implementation of the interface The netCDF library also definesa machine-independent format for representing scientific data Together the interface library and format support thecreation access and sharing of scientific data The netCDF software was developed at the Unidata Program Center inBoulder Colorado The netCDF libraries define a machine-independent format for representing scientific data Pleasesee Unidata NetCDF pages for more information and to retreive NetCDF software package onhttpwwwunidataucaredupackagesnetcdfindexhtml
NetCDF data is
bull Self-Describing A netCDF file includes information about the data it contains
bull Architecture-independent A netCDF file is represented in a form that can be accessed by computers with dif-ferent ways of storing integers characters and floating-point numbers
bull Direct-access A small subset of a large dataset may be accessed efficiently without first reading through allthe preceding data
bull Appendable Data can be appended to a netCDF dataset along one dimension without copying the dataset orredefining its structure The structure of a netCDF dataset can be changed though this sometimes causes thedataset to be copied
bull Sharable One writer and multiple readers may simultaneously access the same netCDF file
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VII2 Structure and semantic of NetCDF along-track files
The NetCDF Sea Level TAC files are based on the attribute data tags defined by the Cooperative OceanAtmosphereResearch Data Service (COARDS) and Climate and Forecast (CF) metadata conventions The CF convention gener-alises and extends the COARDS convention but relaxes the COARDS constraints on dimension and order and specifiesmethods for reducing the size of datasetsA wide range of software are available to write or read NetCDFCF files API are made available by UNIDATA(httpwwwunidataucaredusoftwarenetcdf)
bull CC++Fortran
bull Java
bull MATLAB Objective-C Perl Python R Ruby TclTk
In addition to these conventions the files are using a common structure and semantic
bull 1 dimension is defined
ndash time it is used to check NetCDF variables depending on time
bull 8 variables are defined
ndash short SLA contains the Sea Level Anomaly values for each time given
ndash int longitude contains the longitude for each measurement
ndash short track contains the track number for each measurement
ndash double time contains the time in days since 1950-01-01 000000 UTC for each measurement
ndash short mean_profile_point_index index of the corrsponding point in the track of the mean profile
ndash byte flag flag=0 the processed data comes from OGDR if flag=1 the processed data comes from theIGDR
ndash int latitude contains the latitude for each measurement
ndash short cycle contains the cycle number for each measurement
bull global attributes
ndash the global attributes gives information about the creation of the file
Example of a NetCDF sla file
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netcdf nrt_global_j1_sla_vfec_20101230_20101230_20101230 dimensions
time = 10385 variables
short SLA(time) SLAcoordinates = longitude latitude SLAlong_name = Sea Level Anomaly SLA_FillValue = 32767s SLAadd_offset = 0 SLAscale_factor = 0001 SLAunits = m SLAstandard_name = sea_surface_height_above_sea_level
int longitude(time) longitudelong_name = Longitude of measurement longitude_FillValue = 2147483647 longitudeadd_offset = 0 longitudestandard_name = longitude longitudescale_factor = 1e-06 longitudeunits = degrees_east
short track(time) tracklong_name = Track in cycle the measurement belongs to track_FillValue = 32767s trackunits = 1 trackcoordinates = longitude latitude
double time(time) timelong_name = Time of measurement time_FillValue = 184467440737096e+19 timeaxis = T timestandard_name = time timeunits = days since 1950-01-01 000000 UTC
int latitude(time) latitudelong_name = Latitude of measurement latitude_FillValue = 2147483647 latitudeadd_offset = 0 latitudestandard_name = latitude latitudescale_factor = 1e-06 latitudeunits = degrees_north
short flag(time) flagcoordinates = longitude latitude flag_FillValue = 3267s flaglong_name = data origin flagflag_values = 1s 0s flagflag_meanings = igdr_like non_igdr_like flagcomment = The origin of the data is determined by the types of geophysical datarecords (GDR) used in computation of the SLA 1 for the Interim GDR (IGDR) and0 for Operational GDR (OGDR)
short cycle(time) cyclelong_name = Cycle the measurement belongs to cycle_FillValue = 32767s cycleunits = 1 cyclecoordinates = longitude latitude
global attributeshistory = 22-Feb-2011 155243 CET File created by the SSLATODUACS system version 1001 comment = Produce from ENVISAT Extension Phase satellite altimetry data institution = CLSCNES
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references = httpwwwavisooceanobscomfileadmindocumentsdatatoolshdbk_duacspdf source = satellite altimetry title = along track Sea Level Anomaly Conventions = CF-14
dataSLA =
7 7 11 10 -2 -22 -39 -41 -30 -13 -3 -5 -16 -26 -32 -35-35 -35 -37 -35 -31 -29 -31 -35 -32 -21 -10 -10 -19 -20 -1-69 -57 -49 -45 -39 -30 -28 -31 -27 -13 -2 -5 -15 -3 1112 3 -7 -10 -14 -15 -22 -31 -37 -32 -17 -10
longitude =74743328 74868400 74993968 75120040 75246616 7537372875501368 75629568 75758320 75887656 76017568 76148080 7627920876388952 76477056 76565456 76654144 76743128 76832400 76921984329429568 329535424 329641792 329748672 329856096 329964032330072512 330181536 330291072 330401184
track =92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 9292 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92113 113 113 113 113 113 113 113 113 113 113 113 113 113113 113 113 113 113 113 113 113 113
time =222780000565705 222780001314719 222780002063733222780002812747 222780003561761 222780004310775 222780005059788222780005808802 222780006557816 22278000730683 222780008055844222780008804858 222780009553872 22278001017805 222780010677393222788257112198 222788257486705 222788257861212 222788258235719222788258610226 222788258984733 222788259359239 222788259733746222788260108253 22278826048276
mean_profile_point_index =1872 1878 1884 1890 1896 1902 1908 19141920 1926 1932 1938 1944 1949 1953 1957 1961 1965 1969 19732306 2309 2312 2315 2318 2321 2327 2330 2333 2336 2339 23422345 2348 2351 2354 2357 2360 2363 2366
flag =0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
latitude =-16225506 -16539731 -16853833 -17167810 -17481660 -17795380-18108966 -18422418 -18735729 -19048899 -19361924 -19674801-19987527 -20248015 -20456329 -20664569 -20872739 -2108083739481297 39628277 39775133 39921866 40068472 40214953 4036130840507533 40653629 40799592 40945423 41091120 41236684 41382111
cycle =331 331 331 331 331 331 331 331 331 331 331 331 331
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331 331 331 331 331 331 331 331 331 331 331 331 331 331331 331 331 331 331 331 331 331 331 331 331 331
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VIII HOW TO DOWNLOAD A PRODUCT
VIII1 Download a product through the MyOcean Web Portal DirectgetfileService
You first need to register Please find below the registration stepshttpwwwmyoceaneuweb34-products-and-services-faqphp1Once registered the MyOcean FAQ httpwwwmyoceaneuweb34-products-and-services-faqwill guide you on How to download a product through the MyOcean Web Portal Directgetfile Service
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IX NEWS AND UPDATES
IX1 [Duacs] Operational news
To be kept informed on events occurring on the satellites and on the eventual interruption of the services of the DUACSprocessing system see the [Duacs] operational news on the Aviso websitehttpwwwavisooceanobscomendataoperational-newsindexhtml
IX2 Updates
To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtmlSince 2010 a complete reprocessing of all altimetry data (cumulated total of about 55 years of data) is available Themain changes introduced in the Duacs DT v300 reprocessed data set in SSALTODUACS reprocessed DT data setare listed herehttpwwwavisooceanobscomfileadmindocumentsdataduacsduacs_DT_2010_reprocessing_impactpdf
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III23 Homogenization
The Homogenization process consists in applying the most recent corrections models and references rec-ommended for altimeter products Each mission is processed separately as its needs depend on the baseinput data The list of corrections and models currently applied is provided in tables 3 and 4 for NRT dataThe system includes SLA filtering to process OGDR data DUACS extract from these data sets the shortscales (space and time) which are useful to better describe the ocean variability in real time and merge thisinformation with a fair description of large scale signals provided by the multi-satellite observation in nearreal time (read IGDR-based DUACS data) Finally an hybrid SLA is computed
Figure 7 Merging pertinent information from IGDR and OGDR processing
III24 Input data quality control
The Input Data Quality Control is a critical process applied to guarantee that DUACS uses only the mostaccurate altimeter data Thanks to the high quality of current missions this process rejects a small percent-age of altimeter measurements but these erroneous data could be the cause of a significant quality lossThe quality control relies on standard raw data editing with quality flags or parameter thresholds but alsoon complex data editing algorithms based on the detection of erroneous artefacts mono and multi-missioncrossover validation and macroscopic statistics to edit out large data flows that do not meet the systemrsquosrequirements
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III25 Multi-mission cross-calibration
The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistentand accurate information It removes any residual orbit error (OE Le Traon and Ogor 1998[32]) or longwavelength error (LWE Le Traon et al 1998[31]) as well as large scale biases and discrepancies betweenvarious data flows
This process is based on two very different algorithms a global multi-mission crossover minimization fororbit error reduction (OER) and Optimal Interpolation (OI) for LWE
Multi-satellite crossover determination is performed on a daily basis All altimeter fields (measurementcorrections and other fields such as bathymetry MSS) are interpolated at crossover locations and datesCrossovers are then appended to the existing crossover database as more altimeter data become availableThis crossover data set is the input of the Orbit Error Reduction (OER) method Using the precision of thereference mission orbit a very accurate orbit error can be estimated This processing step does not concernOGDR dataLWE is mostly due to residual tidal or inverse barometer errors and high frequency ocean signals The OIused for LWE reduction uses precise parameters derived from
bull accurate statistical description of sea level variability
bull localized correlation scales
bull mission-specific noise and precise assumptions on the long wavelength errors to be removed (from arecent analysis of one year of data from each mission)
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III26 Product generation
The product generation process is composed of four steps computation of raw SLA cross-validationfilteringampsub-sampling and generation of by-products
III261 Computation of raw SLA
Since the geoid is not well known yet the SSH cannot be used directly the SSH anomalies are used insteadThey are computed from the difference of the instantaneous SSH - a temporal reference This temporalreference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeattrack analysis cannot be used The errors affecting the SLAs MPs and MSS have different magnitudes andwavelengths The computation of the SLAs and their errors associated are detailed in Dibarboure et al 2010[9]
Use of a Mean ProfileIn the repeat track analysis (when the satellites flies over a repetitive orbit) measurements are re-sampledalong a theoretical ground track (or mean track) associated to each mission Then a Mean Profile (MP) issubtracted from the re-sampled data to obtain SLA The MP is a time average of similarly re-sampled dataover a long period
bull The Mean Profile used for Jason-2 is computed with 10 years of TP (cycles 11 to 353) and 6 years ofJason-1 (cycles 11 to 250)
bull The Mean Profile used from Jason-1 cycle 262 to 374 (where satellites are on interleaved ground-tracks) is computed with 3 years of TP (cycles 369 to 479)
bull No Mean Profile can be used for Envisat on its new orbit (enn) Jason-1 on its geodetic orbit (j1g) norfor Cryosat-2 mission (c2) because there is no repetitive track The MSS must be used instead (seebelow)
Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible
bull Indeed as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide precise cross-track projection andor interpolation schemes are required to avoid errors
bull The mesoscale variability error (which is lt35 cm for MP between 3 to 5 years and lt1cm for WLof 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a prioriknowledge from Sea Level maps derived from previous iterations or from other missions
bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
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bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for Envisat since november 2010 and for Cryosat-2 mission (c2)because the satellite is not in a repetitive orbit phase The alternative is to use the MSS instead The griddedMSS is derived from along track MPs and data from geodetic phases Thus any error on the MP is alsocontained in the MSS There are essentially 4 types of additional errors on gridded MSS which are hard toquantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
Note that for the Arctic regional products the DTU10 MSS [1] is taken into account instead of the CLS01MSS Indeed the accuracy of DTU10 compared to CLS01 is further demonstrated by the significant sealevel anomaly variance reduction found over the whole Arctic Ocean as shown in Prandi et al [42]
III262 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III263 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
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III27 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III271 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III272 Performance indicators
To appreciate the quality situation of the DUACS system new performance indicators are computed dailyThey aim at evaluate the status of the main processing steps of the system the input data availability theinput data coverage the input data quality and the output product quality These indicators are computed foreach and every currently working satellite and combined to obtain the overall status
Figure 8 Example with the key performance indicator on 20090627
See the description the latest and previous indicators on Aviso websitehttpwwwavisooceanobscomindexphpid=1516
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III3 Delayed Time processing steps
III31 Input data models and corrections applied
Delayed Time MyOcean products are generated
bull from Aviso GDR products for TP Jason-1 Jason-2 and Envisat (GDR-A cycles 1 to 22 GDR-Bcycles 23 to 85 GDR-C from cycle 86)
bull from NOAA GDR for GFO and from CERSAT (IFREMER) OPR for ERS-1 and ERS-2 (phases C(1st 35-day repeat orbit period) phase E and F (geodetic phases) phase G for ERS-1 (last 35-dayrepeat orbit period tandem phase with ERS-2 phase A for ERS-2 (1st 35-day repeat orbit periodtandem phase with ERS-1))
All GDR products are computed with a Precise Orbit Ephemeris (POE) and are delivered within 2 to 3months depending on the mission For several missions an updated orbit is used
bull For ERS-1amp-2 the orbit used is DGME-04 provided by Delft Institute (httpwwwdeostudelftnl)until June 2003
bull For TopexPoseidon the orbit used is GSFC (std0809) for the whole mission
bull For Envisat CNES POE of GDR-C standard is used for the whole mission
bull For the whole GFO mission the orbit used is GSFC (std0809) and when not available NASA POE isused
Altimetric product Source Availability Type of orbit
TopexPoseidon GDR NASACNES - GSFC POE
Jason-1 GDR (GDR-C) CNESNASA ~40 days CNES POE
Jason-2 GDR (GDR-C) CNESNASA ~60 days CNES POE
GFO GDR NOAA - GSFCNASA POE
ERS-1amp2 IFREMERESA - DGME-04
Envisat (GDR-A GDR-B andGDR-C from cycle 86)
ESA ~2 months CNES POE
Table 5 SSALTODUACS Delayed Time Input data overview
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
DU
AC
S20
11D
Tpr
oduc
t(gtV
30
0)j2
j1j1
ntp
tpn
e1e2
ene
nng2
Prod
uct
stan
dard
ref
GD
R-C
OPR
GD
R-A
(Cyc
les
1to
22)
GD
R-B
(cyc
les
23-8
5)
GD
R(N
OA
A)
Orb
itC
nes
POE
GSF
C(I
TR
F20
05G
RA
CE
last
stan
dard
s)
DG
ME
-04
(Sch
arro
oan
dV
isse
r19
98[4
8]C
NE
SPO
E(G
DR
-1st
anda
rds
forc
ycle
s9
to22
GD
R-C
stan
dard
sfr
omcy
cle
23)
GSF
C(I
TR
F20
05
GR
AC
Ela
stst
anda
rds
Iono
pher
icD
ual f
requ
ency
altim
eter
rang
em
easu
rem
ents
Dua
l fre
quen
cyal
timet
erra
nge
mea
sure
men
ts(T
opex
)D
OR
IS(P
OSE
IDO
N)
Ben
t mod
elB
ent m
odel
(cyc
les
1-36
)G
IMm
odem
from
cycl
e37
((Ii
jima
etal
19
98[2
4])
Dua
l-fr
eque
ncy
altim
eter
rang
em
easu
rem
ent(
cycl
e9-
64)a
ndG
IMm
odel
gtcyc
le65
(Iiji
ma
etal
19
99[2
4])c
orre
cted
from
8m
mbi
as
From
GIM
mod
el(I
ijim
aet
al1
998
[24]
)
Dry
trop
o-sp
here
Mod
elco
mpu
ted
from
EC
MW
FG
auss
ian
grid
s(n
ewS1
and
S2at
mos
pher
ictid
esar
eap
plie
d)
Mod
elco
mpu
ted
from
EC
MW
Fre
ctan
gula
rgri
ds(n
ewS1
and
S2at
mos
pher
ictid
esar
ein
clud
ed)
Wet
trop
o-sp
here
JMR
AM
Rra
diom
eter
furt
hert
han
50km
from
the
coas
tsF
rom
EC
MW
Fm
odel
ford
ista
nces
betw
een
10an
d50
km
TM
Rra
diom
eter
(Sch
aroo
etal
20
04[4
9])
MW
RC
orre
ctio
nof
the
drif
ton
the
236
GH
zbr
ight
ness
tem
pera
ture
(Sch
arro
oet
al
2004
[49]
)Neu
ral
Net
wor
kal
gori
thm
(Tra
nan
dO
blig
is
2003
[50]
MW
Rra
diom
eter
furt
hert
han
50km
from
the
coas
tsan
dco
rrec
ted
from
side
lobe
s(f
rom
cycl
e41
)E
CM
WF
mod
elfo
rdis
tanc
esbe
twee
n10
and
50km
GFO
radi
omet
er
DA
CM
OG
2DH
igh
Res
olut
ion
forc
edw
ithE
CM
WF
pres
sure
and
win
gfie
lds
(S1
and
S2w
ere
excl
uded
)+in
vers
eba
rom
eter
com
pute
dfr
omre
ctan
gula
rgri
ds
Tabl
e6
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(1
2)
Page 33
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
j2j1
j1n
tptp
ne1
e2en
enn
g2O
cean
tide
GO
T4v
7(S
1an
dS2
are
incl
uded
)Po
letid
e[W
ahr
1985
[53]
]So
lidea
rth
tide
Ela
stic
resp
onse
totid
alpo
tent
ial[
Car
twri
ghta
ndTa
yler
197
1[5]
][C
artw
righ
tand
Edd
en1
973[
6]]
Loa
ding
tide
GO
T4v
7(S
1pa
ram
eter
isin
clud
ed)
Sea
stat
ebi
asN
onpa
ram
etri
cSS
B[G
aspa
reta
l20
02[2
0]]
Non
para
met
ric
SSB
[NT
ran
and
al2
010[
51]]
BM
3[G
aspa
ran
dO
gor
1994
[17]
]
Non
para
met
ric
SSB
[Mer
tzet
al
2005
[38]
]
Non
para
met
ric
SSB
[Gas
pare
tal
2002
]w
ithG
DR
-Bst
anda
rds
forc
ycle
s9
to85
and
with
GD
R-C
stan
dard
sfr
omcy
cle
86
Non
para
met
ric
SSB
[NT
ran
etal
20
10[5
1]]
Orb
iter
ror
Glo
bal m
ulti-
mis
sion
cros
sove
rmin
imiz
atio
n(L
eTr
aon
and
Ogo
r19
98[3
2])
Lon
gw
ave-
leng
her
rors
Opt
imal
Inte
rpol
atio
n(L
eTr
aon
etal
19
98[3
1])
Inte
rcal
ibra
tion
Ref
eren
cefr
omcy
cle
11R
efer
ence
from
cycl
e1
to35
4C
orre
ctio
nof
regi
onal
bias
J2J
1de
duce
dfr
omin
terc
alib
ratio
nph
ase
(cyc
le11
J2)
Cor
rect
ion
ofgl
obal
biai
sJ1
TP
deacutedu
ced
from
inte
rcal
ibra
tion
phas
e(c
ycle
s11
J1)
Mea
npr
o-fil
e(s
eeII
I36
1)
Com
pute
dw
ithcy
cles
11-3
53T
Pda
taan
dw
ithcy
cles
11-2
50J1
data
ref
eren
ced
[199
319
99]
TP
J1 c
ompu
ted
with
cycl
es11
-353
TP
data
and
with
cycl
es11
-250
J1da
tar
efer
ence
d[1
993
1999
]T
PNJ
1Nc
ompu
ted
with
cycl
es36
9-47
9T
PNda
tar
efer
ence
d[1
993
1999
]
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
ref
eren
ced
[199
319
99]
EN
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
re
fere
nced
[199
319
99]
EN
Nu
seof
MSS
_CN
ES_
CL
S11
[39]
Com
pute
dw
ithcy
cles
37-1
87G
2da
ta
refe
renc
ed[1
993
1999
]
Peri
odof
use
from
cycl
e9
from
cycl
e9
cycl
es1
to48
1cy
cles
15to
43In
clud
ing
E-F
geod
etic
phas
es
cycl
es1
to83
from
cycl
e9
cycl
es37
to22
2
Tabl
e7
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(2
2)
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III32 Acquisition
The acqusition process in Delayed time is much simpler than in Near Real time it consists in a synchronisa-tion process of all the auxiliary data required to homogenize propely the altimeter data sets The acquisitionstep uses the GDRs or the OPRs provided by the agencies
III33 Homogenization
The Homogenization process consists in applying the most recent corrections models and references rec-ommended for altimeter products Each mission is processed separately as its needs depend on the baseinput data The list of corrections and models currently applied is provided in tables 6 and 7 for DT data
III34 Input data quality control
The Input Data Quality Control is a critical process applied to guarantee that DUACS uses only the mostaccurate altimeter data Thanks to the high quality of current missions this process rejects a small percent-age of altimeter measurements but these erroneous data could be the cause of a significant quality lossThe quality control relies on standard raw data editing with quality flags or parameter thresholds but alsoon complex data editing algorithms based on the detection of erroneous artefacts mono and multi-missioncrossover validation and macroscopic statistics to edit out large data flows that do not meet the systemrsquosrequirements
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III35 Multi-mission cross-calibration
The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistentand accurate information It removes any residual orbit error (OE Le Traon and Ogor 1998[32]) or longwavelength error (LWE Le Traon et al 1998[31]) as well as large scale biases and discrepancies betweenvarious data flows
This process is based on two very different algorithms a global multi-mission crossover minimization fororbit error reduction (OER) and Optimal Interpolation (OI) for LWE
Multi-satellite crossover determination is performed on a daily basis All altimeter fields (measurementcorrections and other fields such as bathymetry MSS) are interpolated at crossover locations and datesCrossovers are then appended to the existing crossover database as more altimeter data become availableThis crossover data set is the input of the Orbit Error Reduction (OER) method Using the precision of thereference mission orbit a very accurate orbit error can be estimated LWE is mostly due to residual tidalor inverse barometer errors and high frequency ocean signals The OI used for LWE reduction uses preciseparameters derived from
bull accurate statistical description of sea level variability
bull localized correlation scales
bull mission-specific noise and precise assumptions on the long wavelength errors to be removed (from arecent analysis of one year of data from each mission)
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III36 Product generation
The product generation process is composed of four steps computation of raw SLA cross-validationfilteringampsub-sampling and generation of by-products
III361 Computation of raw SLA
Since the geoid is not well known yet the SSH cannot be used directly the SSH anomalies are used insteadThey are computed from the difference of the instantaneous SSH - a temporal reference This temporalreference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeattrack analysis cannot be used The errors affecting the SLAs MPs and MSS have different magnitudes andwavelengths The computation of the SLAs and their errors associated are detailed in Dibarboure et al 2010[9]
Use of a Mean ProfileIn the repeat track analysis (when the satellites flies over a repetitive orbit) measurements are re-sampledalong a theoretical ground track (or mean track) associated to each mission Then a Mean Profile (MP) issubtracted from the re-sampled data to obtain SLA The MP is a time average of similarly re-sampled dataover a long period
bull The Mean Profile used for TP (cycles 1 to 364) Jason-1 (cycles 1 to 259) and Jason-2 is computedwith 10 years of TP (cycles 11 to 353) and 6 years of Jason-1 (cycles 11 to 250)
bull The Mean Profile used for TP (cycles 368 to 481) and from Jason-1 cycle 262 to 374 (where satellitesare on interleaved ground-tracks) is computed with 3 years of TP (cycles 369 to 479)
bull The Mean Profile used for ERS-1 in its 35 days repetitive orbit mission ERS-2 and Envisat (only forthe first orbit before November 2010) is computed with 8 years of ERS-2 (cycles 1 to 85) and 6 yearsof Envisat (cycles 10 to 72)
bull No Mean Profile can be used for Envisat on its new orbit (enn) Jason-1 on its geodetic orbit (j1g)because there is no repetitive track The MSS must be used instead (see below)
bull The Mean Profile used for GFO is computed with 7 years of GFO cycles 37 to 187
Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible
bull Indeed as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide precise cross-track projection andor interpolation schemes are required to avoid errors
bull The mesoscale variability error (which is lt35 cm for MP between 3 to 5 years and lt1cm for WLof 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a prioriknowledge from Sea Level maps derived from previous iterations or from other missions
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bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for ERS-1 for its 168 days geodetic mission (phases E-F from April1994 to March 1995) or for Envisat since november 2010 because the satellite is not in a repetitive orbitphase The alternative is to use the MSS instead The gridded MSS is derived from along track MPs anddata from geodetic phases Thus any error on the MP is also contained in the MSS There are essentially 4types of additional errors on gridded MSS which are hard to quantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
III362 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III363 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
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III37 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III371 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
IV MYOCEAN PRODUCTS
IV1 Near Real Time Products
The purpose of the NRT DUACS component is the acquisition of altimeter data from various altimeter mis-sions in near-real time (ie within a few days at most) the validation and correction of these altimeter datasets (ie edition and selection update of corrections and homogenization orbit error reduction) in order toproduce each day along-track productsProducts are as follows
Along-track products global and regional (Mediterranean and Black Seas Arctic Ocean and Europeareas)
bull Sea Level Anomaly (NRT-SLA) for each mission with NRT-SLA ephemeris
IV11 Delay of the products
The availability of the products in near real time is three to twelve hours after the measurement for along-track products Those products are delivered every day
IV12 Temporal availibility
The following table presents the available products by mission and by data periodNear real time products
NRT Jason-2 Jason-1 and Jason-1geodetic
Envisat new Cryosat-2
Temporal Time availability ymlowast
ongoingymlowast-20120303 for
repeat track and20120507-ongoing for
geodetic track
ymlowast
2012040820120101
ongoing
NRT-SLA X X X X
lowastym the temporal coverage for NRT products is fluctuating and depends on updates of Delayed Time prod-ucts When DT products are updated (3 to 4 times per year) the oldest NRT products are replaced by thebetter quality DT products so that the 2 series are overlapping on few weeks or few months
IV2 Delayed Time Products
The Delayed Time component of SSALTODUACS system is responsible for the production of processedJason-1 Jason-2 TP Envisat GFO ERS12 and even Geosat data in order to provide a homogeneousinter-calibrated and highly accurate long time series of SLA DT products are more precise than NRT products Two reasons explain this quality difference The firstone is the better intrinsic quality of the POE orbit used in the GDR processing The second reason is that
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in the DT DUACS processing the products can be computed optimally with a centred computation timewindow for OER LWE On the contrary in NRT case future data are not available so the computationtime window is not centred and therefore not optimalAs for NRT products improved altimeter corrections and processing algorithms are used ocean tide modelto correct altimeter data improved methods for orbit error reduction and mapping
Along-Track products global and regional (Mediterranean and Black Seas)
bull Sea Level Anomaly (DT-SLA) for each mission
IV21 Delay of the products
Weekly products are delivered The availability of the products in delayed time is at the best two monthsafter the date of the measurement The product generation needs all the GDR data of all the missions to takeinto account the best corrections as possible The time delay can be longer in the case of a missing mission
IV22 Temporal availibility
The following table presents the available products by mission and by data periodDelayed time SSALTODUACS products
Upd Jason-2 Jason-1new6
Jason-1 GFO Envisatnew6
Envisat ERS-16
ERS-2Topexnew6
Topex
TemporalTimeavailabil-ity
200810ymlowast
200902ymlowast
200204200810
200001200809
201010ymlowast
200210201010
199210200304
200209200510
199209200204
DT-SLA X X X X X X X X X
lowast ym those dates are updated regularly (3 to 4 times per year) and are avalaible when you download thedata at httpwwwmyoceaneuweb24-cataloguephp6 Jason-1 new orbit starting 200809 Envisat new orbit starting 201010 TP new orbit starting 200209 ERS-1The geodetic phases (E-F) are included There are no ERS-1 data between December 23 1993 and April 10 1994(ERS-1 phase D - 2nd ice phase) Note that during that time products are based only on TopexPoseidon data
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V DESCRIPTION OF THE PRODUCT SPECIFICATION
V1 General information
Product Specification SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001
Geographical coverage global
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 20-50km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001 Product Specification
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
Product Specification SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002
Geographical coverage 55˚W-35˚E 30˚N-46˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002 Product Specification
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Product Specification SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003
Geographical coverage 27˚E-42˚E 40˚N-47˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003 Product Specification
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Product Specification SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004
Geographical coverage 25˚W-42˚E 21˚N-66˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004 Product Specification
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Product Specification SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005
Geographical coverage 0˚W-360˚E 50˚N-82˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005 Product Specification
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VI NOMENCLATURE OF FILES
VI1 Nomenclature of files downloaded through the MyOcean Web PortalDirectgetfile Service
VI11 Nomenclature of the product line
The description of the syntax for the SL TAC SLA products line is given by
SEALEVEL_ltREGIONgt_SLA_L3_ltDELAYgt_OBSERVATIONS_008_ltZONEgt_ltLETTERgtwhere
REGION GLO global geographic coverage product
BS Black Sea products
MED Mediterranean products
ARC Arctic products (for NRT products)
EUROPE Europe products (for NRT products)
DELAY NRT near real time products
RAN delayed time or reanalysis products
ZONE 001 number on 3 digits
002
003
004
LETTER a letter on 1 digit
b
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VI12 Nomenclature of the datasets
The nomenclature used is
dataset-duacs-ltdelaygt-ltzonegt-ltmissiongt-lttype of slagt-l3where the fileds in ltgt are described below
delay nrt near-real time productsran delayed time products
zone global global geographic coverage productmedsea Mediterranean productsblacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1 (only for ran)e2 ERS-2 (only for ran)tp TOPEXPoseidon (only for ran)tpn TOPEXPoseidon on its new orbit (only for
ran)g2 GFO (only for ran)j1 Jason-1 (only for ran)j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisat (only for ran)enn Envisat on its new orbitc2 Cryosat-2 (only for nrt)
type of sla sla filtered slasla_unfiltered non filtered sla (only for ran products)
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VI13 Nomenclature of the NetCdf files
The nomenclature used is
ltdelaygt_ltzonegt_ltmissiongt_sla_ltvariablegt_ltdatebegingt_ltdateendgt_ltdateprodgtnc where the fileds in ltgt are de-scribed below
delay nrt near-real time productsdt delayed time products
zone global global geographic coverage productmed Mediterranean products (for dt)mfstep Mediterranean products (for nrt)blacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1e2 ERS-2tp TOPEXPoseidontpn TOPEXPoseidon on its new orbitg2 GFOj1 Jason-1j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisatenn Envisat on its new orbitc2 Cryosat-2
variable vfec filtered and sub-sampled slavxxc non filtered and non sub-sampled sla (only
for dt)datebegin YYYYMMDD() beginning date of the datasetdateend YYYYMMDD() end date of the datasetdateprod YYYYMMDD production date of the dataset
() For dt data as the dates in the file names are rounded the user wanting data for date T has to read the filescontaining dates T+1 and T-1 in their name and check inside the files if there are some data for date T
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VII DATA FORMAT
This chapter presents the data storage format used for MyOcean products
VII1 NetCdf
The products are stored using the NetCDF format NetCDF (network Common Data Form) is an interface for array-oriented data access and a library that provides an implementation of the interface The netCDF library also definesa machine-independent format for representing scientific data Together the interface library and format support thecreation access and sharing of scientific data The netCDF software was developed at the Unidata Program Center inBoulder Colorado The netCDF libraries define a machine-independent format for representing scientific data Pleasesee Unidata NetCDF pages for more information and to retreive NetCDF software package onhttpwwwunidataucaredupackagesnetcdfindexhtml
NetCDF data is
bull Self-Describing A netCDF file includes information about the data it contains
bull Architecture-independent A netCDF file is represented in a form that can be accessed by computers with dif-ferent ways of storing integers characters and floating-point numbers
bull Direct-access A small subset of a large dataset may be accessed efficiently without first reading through allthe preceding data
bull Appendable Data can be appended to a netCDF dataset along one dimension without copying the dataset orredefining its structure The structure of a netCDF dataset can be changed though this sometimes causes thedataset to be copied
bull Sharable One writer and multiple readers may simultaneously access the same netCDF file
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VII2 Structure and semantic of NetCDF along-track files
The NetCDF Sea Level TAC files are based on the attribute data tags defined by the Cooperative OceanAtmosphereResearch Data Service (COARDS) and Climate and Forecast (CF) metadata conventions The CF convention gener-alises and extends the COARDS convention but relaxes the COARDS constraints on dimension and order and specifiesmethods for reducing the size of datasetsA wide range of software are available to write or read NetCDFCF files API are made available by UNIDATA(httpwwwunidataucaredusoftwarenetcdf)
bull CC++Fortran
bull Java
bull MATLAB Objective-C Perl Python R Ruby TclTk
In addition to these conventions the files are using a common structure and semantic
bull 1 dimension is defined
ndash time it is used to check NetCDF variables depending on time
bull 8 variables are defined
ndash short SLA contains the Sea Level Anomaly values for each time given
ndash int longitude contains the longitude for each measurement
ndash short track contains the track number for each measurement
ndash double time contains the time in days since 1950-01-01 000000 UTC for each measurement
ndash short mean_profile_point_index index of the corrsponding point in the track of the mean profile
ndash byte flag flag=0 the processed data comes from OGDR if flag=1 the processed data comes from theIGDR
ndash int latitude contains the latitude for each measurement
ndash short cycle contains the cycle number for each measurement
bull global attributes
ndash the global attributes gives information about the creation of the file
Example of a NetCDF sla file
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netcdf nrt_global_j1_sla_vfec_20101230_20101230_20101230 dimensions
time = 10385 variables
short SLA(time) SLAcoordinates = longitude latitude SLAlong_name = Sea Level Anomaly SLA_FillValue = 32767s SLAadd_offset = 0 SLAscale_factor = 0001 SLAunits = m SLAstandard_name = sea_surface_height_above_sea_level
int longitude(time) longitudelong_name = Longitude of measurement longitude_FillValue = 2147483647 longitudeadd_offset = 0 longitudestandard_name = longitude longitudescale_factor = 1e-06 longitudeunits = degrees_east
short track(time) tracklong_name = Track in cycle the measurement belongs to track_FillValue = 32767s trackunits = 1 trackcoordinates = longitude latitude
double time(time) timelong_name = Time of measurement time_FillValue = 184467440737096e+19 timeaxis = T timestandard_name = time timeunits = days since 1950-01-01 000000 UTC
int latitude(time) latitudelong_name = Latitude of measurement latitude_FillValue = 2147483647 latitudeadd_offset = 0 latitudestandard_name = latitude latitudescale_factor = 1e-06 latitudeunits = degrees_north
short flag(time) flagcoordinates = longitude latitude flag_FillValue = 3267s flaglong_name = data origin flagflag_values = 1s 0s flagflag_meanings = igdr_like non_igdr_like flagcomment = The origin of the data is determined by the types of geophysical datarecords (GDR) used in computation of the SLA 1 for the Interim GDR (IGDR) and0 for Operational GDR (OGDR)
short cycle(time) cyclelong_name = Cycle the measurement belongs to cycle_FillValue = 32767s cycleunits = 1 cyclecoordinates = longitude latitude
global attributeshistory = 22-Feb-2011 155243 CET File created by the SSLATODUACS system version 1001 comment = Produce from ENVISAT Extension Phase satellite altimetry data institution = CLSCNES
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references = httpwwwavisooceanobscomfileadmindocumentsdatatoolshdbk_duacspdf source = satellite altimetry title = along track Sea Level Anomaly Conventions = CF-14
dataSLA =
7 7 11 10 -2 -22 -39 -41 -30 -13 -3 -5 -16 -26 -32 -35-35 -35 -37 -35 -31 -29 -31 -35 -32 -21 -10 -10 -19 -20 -1-69 -57 -49 -45 -39 -30 -28 -31 -27 -13 -2 -5 -15 -3 1112 3 -7 -10 -14 -15 -22 -31 -37 -32 -17 -10
longitude =74743328 74868400 74993968 75120040 75246616 7537372875501368 75629568 75758320 75887656 76017568 76148080 7627920876388952 76477056 76565456 76654144 76743128 76832400 76921984329429568 329535424 329641792 329748672 329856096 329964032330072512 330181536 330291072 330401184
track =92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 9292 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92113 113 113 113 113 113 113 113 113 113 113 113 113 113113 113 113 113 113 113 113 113 113
time =222780000565705 222780001314719 222780002063733222780002812747 222780003561761 222780004310775 222780005059788222780005808802 222780006557816 22278000730683 222780008055844222780008804858 222780009553872 22278001017805 222780010677393222788257112198 222788257486705 222788257861212 222788258235719222788258610226 222788258984733 222788259359239 222788259733746222788260108253 22278826048276
mean_profile_point_index =1872 1878 1884 1890 1896 1902 1908 19141920 1926 1932 1938 1944 1949 1953 1957 1961 1965 1969 19732306 2309 2312 2315 2318 2321 2327 2330 2333 2336 2339 23422345 2348 2351 2354 2357 2360 2363 2366
flag =0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
latitude =-16225506 -16539731 -16853833 -17167810 -17481660 -17795380-18108966 -18422418 -18735729 -19048899 -19361924 -19674801-19987527 -20248015 -20456329 -20664569 -20872739 -2108083739481297 39628277 39775133 39921866 40068472 40214953 4036130840507533 40653629 40799592 40945423 41091120 41236684 41382111
cycle =331 331 331 331 331 331 331 331 331 331 331 331 331
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331 331 331 331 331 331 331 331 331 331 331 331 331 331331 331 331 331 331 331 331 331 331 331 331 331
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VIII HOW TO DOWNLOAD A PRODUCT
VIII1 Download a product through the MyOcean Web Portal DirectgetfileService
You first need to register Please find below the registration stepshttpwwwmyoceaneuweb34-products-and-services-faqphp1Once registered the MyOcean FAQ httpwwwmyoceaneuweb34-products-and-services-faqwill guide you on How to download a product through the MyOcean Web Portal Directgetfile Service
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IX NEWS AND UPDATES
IX1 [Duacs] Operational news
To be kept informed on events occurring on the satellites and on the eventual interruption of the services of the DUACSprocessing system see the [Duacs] operational news on the Aviso websitehttpwwwavisooceanobscomendataoperational-newsindexhtml
IX2 Updates
To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtmlSince 2010 a complete reprocessing of all altimetry data (cumulated total of about 55 years of data) is available Themain changes introduced in the Duacs DT v300 reprocessed data set in SSALTODUACS reprocessed DT data setare listed herehttpwwwavisooceanobscomfileadmindocumentsdataduacsduacs_DT_2010_reprocessing_impactpdf
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III25 Multi-mission cross-calibration
The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistentand accurate information It removes any residual orbit error (OE Le Traon and Ogor 1998[32]) or longwavelength error (LWE Le Traon et al 1998[31]) as well as large scale biases and discrepancies betweenvarious data flows
This process is based on two very different algorithms a global multi-mission crossover minimization fororbit error reduction (OER) and Optimal Interpolation (OI) for LWE
Multi-satellite crossover determination is performed on a daily basis All altimeter fields (measurementcorrections and other fields such as bathymetry MSS) are interpolated at crossover locations and datesCrossovers are then appended to the existing crossover database as more altimeter data become availableThis crossover data set is the input of the Orbit Error Reduction (OER) method Using the precision of thereference mission orbit a very accurate orbit error can be estimated This processing step does not concernOGDR dataLWE is mostly due to residual tidal or inverse barometer errors and high frequency ocean signals The OIused for LWE reduction uses precise parameters derived from
bull accurate statistical description of sea level variability
bull localized correlation scales
bull mission-specific noise and precise assumptions on the long wavelength errors to be removed (from arecent analysis of one year of data from each mission)
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III26 Product generation
The product generation process is composed of four steps computation of raw SLA cross-validationfilteringampsub-sampling and generation of by-products
III261 Computation of raw SLA
Since the geoid is not well known yet the SSH cannot be used directly the SSH anomalies are used insteadThey are computed from the difference of the instantaneous SSH - a temporal reference This temporalreference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeattrack analysis cannot be used The errors affecting the SLAs MPs and MSS have different magnitudes andwavelengths The computation of the SLAs and their errors associated are detailed in Dibarboure et al 2010[9]
Use of a Mean ProfileIn the repeat track analysis (when the satellites flies over a repetitive orbit) measurements are re-sampledalong a theoretical ground track (or mean track) associated to each mission Then a Mean Profile (MP) issubtracted from the re-sampled data to obtain SLA The MP is a time average of similarly re-sampled dataover a long period
bull The Mean Profile used for Jason-2 is computed with 10 years of TP (cycles 11 to 353) and 6 years ofJason-1 (cycles 11 to 250)
bull The Mean Profile used from Jason-1 cycle 262 to 374 (where satellites are on interleaved ground-tracks) is computed with 3 years of TP (cycles 369 to 479)
bull No Mean Profile can be used for Envisat on its new orbit (enn) Jason-1 on its geodetic orbit (j1g) norfor Cryosat-2 mission (c2) because there is no repetitive track The MSS must be used instead (seebelow)
Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible
bull Indeed as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide precise cross-track projection andor interpolation schemes are required to avoid errors
bull The mesoscale variability error (which is lt35 cm for MP between 3 to 5 years and lt1cm for WLof 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a prioriknowledge from Sea Level maps derived from previous iterations or from other missions
bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
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bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for Envisat since november 2010 and for Cryosat-2 mission (c2)because the satellite is not in a repetitive orbit phase The alternative is to use the MSS instead The griddedMSS is derived from along track MPs and data from geodetic phases Thus any error on the MP is alsocontained in the MSS There are essentially 4 types of additional errors on gridded MSS which are hard toquantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
Note that for the Arctic regional products the DTU10 MSS [1] is taken into account instead of the CLS01MSS Indeed the accuracy of DTU10 compared to CLS01 is further demonstrated by the significant sealevel anomaly variance reduction found over the whole Arctic Ocean as shown in Prandi et al [42]
III262 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III263 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
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III27 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III271 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
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III272 Performance indicators
To appreciate the quality situation of the DUACS system new performance indicators are computed dailyThey aim at evaluate the status of the main processing steps of the system the input data availability theinput data coverage the input data quality and the output product quality These indicators are computed foreach and every currently working satellite and combined to obtain the overall status
Figure 8 Example with the key performance indicator on 20090627
See the description the latest and previous indicators on Aviso websitehttpwwwavisooceanobscomindexphpid=1516
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III3 Delayed Time processing steps
III31 Input data models and corrections applied
Delayed Time MyOcean products are generated
bull from Aviso GDR products for TP Jason-1 Jason-2 and Envisat (GDR-A cycles 1 to 22 GDR-Bcycles 23 to 85 GDR-C from cycle 86)
bull from NOAA GDR for GFO and from CERSAT (IFREMER) OPR for ERS-1 and ERS-2 (phases C(1st 35-day repeat orbit period) phase E and F (geodetic phases) phase G for ERS-1 (last 35-dayrepeat orbit period tandem phase with ERS-2 phase A for ERS-2 (1st 35-day repeat orbit periodtandem phase with ERS-1))
All GDR products are computed with a Precise Orbit Ephemeris (POE) and are delivered within 2 to 3months depending on the mission For several missions an updated orbit is used
bull For ERS-1amp-2 the orbit used is DGME-04 provided by Delft Institute (httpwwwdeostudelftnl)until June 2003
bull For TopexPoseidon the orbit used is GSFC (std0809) for the whole mission
bull For Envisat CNES POE of GDR-C standard is used for the whole mission
bull For the whole GFO mission the orbit used is GSFC (std0809) and when not available NASA POE isused
Altimetric product Source Availability Type of orbit
TopexPoseidon GDR NASACNES - GSFC POE
Jason-1 GDR (GDR-C) CNESNASA ~40 days CNES POE
Jason-2 GDR (GDR-C) CNESNASA ~60 days CNES POE
GFO GDR NOAA - GSFCNASA POE
ERS-1amp2 IFREMERESA - DGME-04
Envisat (GDR-A GDR-B andGDR-C from cycle 86)
ESA ~2 months CNES POE
Table 5 SSALTODUACS Delayed Time Input data overview
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
j2j1
j1n
tptp
ne1
e2en
enn
g2O
cean
tide
GO
T4v
7(S
1an
dS2
are
incl
uded
)Po
letid
e[W
ahr
1985
[53]
]So
lidea
rth
tide
Ela
stic
resp
onse
totid
alpo
tent
ial[
Car
twri
ghta
ndTa
yler
197
1[5]
][C
artw
righ
tand
Edd
en1
973[
6]]
Loa
ding
tide
GO
T4v
7(S
1pa
ram
eter
isin
clud
ed)
Sea
stat
ebi
asN
onpa
ram
etri
cSS
B[G
aspa
reta
l20
02[2
0]]
Non
para
met
ric
SSB
[NT
ran
and
al2
010[
51]]
BM
3[G
aspa
ran
dO
gor
1994
[17]
]
Non
para
met
ric
SSB
[Mer
tzet
al
2005
[38]
]
Non
para
met
ric
SSB
[Gas
pare
tal
2002
]w
ithG
DR
-Bst
anda
rds
forc
ycle
s9
to85
and
with
GD
R-C
stan
dard
sfr
omcy
cle
86
Non
para
met
ric
SSB
[NT
ran
etal
20
10[5
1]]
Orb
iter
ror
Glo
bal m
ulti-
mis
sion
cros
sove
rmin
imiz
atio
n(L
eTr
aon
and
Ogo
r19
98[3
2])
Lon
gw
ave-
leng
her
rors
Opt
imal
Inte
rpol
atio
n(L
eTr
aon
etal
19
98[3
1])
Inte
rcal
ibra
tion
Ref
eren
cefr
omcy
cle
11R
efer
ence
from
cycl
e1
to35
4C
orre
ctio
nof
regi
onal
bias
J2J
1de
duce
dfr
omin
terc
alib
ratio
nph
ase
(cyc
le11
J2)
Cor
rect
ion
ofgl
obal
biai
sJ1
TP
deacutedu
ced
from
inte
rcal
ibra
tion
phas
e(c
ycle
s11
J1)
Mea
npr
o-fil
e(s
eeII
I36
1)
Com
pute
dw
ithcy
cles
11-3
53T
Pda
taan
dw
ithcy
cles
11-2
50J1
data
ref
eren
ced
[199
319
99]
TP
J1 c
ompu
ted
with
cycl
es11
-353
TP
data
and
with
cycl
es11
-250
J1da
tar
efer
ence
d[1
993
1999
]T
PNJ
1Nc
ompu
ted
with
cycl
es36
9-47
9T
PNda
tar
efer
ence
d[1
993
1999
]
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
ref
eren
ced
[199
319
99]
EN
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
re
fere
nced
[199
319
99]
EN
Nu
seof
MSS
_CN
ES_
CL
S11
[39]
Com
pute
dw
ithcy
cles
37-1
87G
2da
ta
refe
renc
ed[1
993
1999
]
Peri
odof
use
from
cycl
e9
from
cycl
e9
cycl
es1
to48
1cy
cles
15to
43In
clud
ing
E-F
geod
etic
phas
es
cycl
es1
to83
from
cycl
e9
cycl
es37
to22
2
Tabl
e7
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(2
2)
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III32 Acquisition
The acqusition process in Delayed time is much simpler than in Near Real time it consists in a synchronisa-tion process of all the auxiliary data required to homogenize propely the altimeter data sets The acquisitionstep uses the GDRs or the OPRs provided by the agencies
III33 Homogenization
The Homogenization process consists in applying the most recent corrections models and references rec-ommended for altimeter products Each mission is processed separately as its needs depend on the baseinput data The list of corrections and models currently applied is provided in tables 6 and 7 for DT data
III34 Input data quality control
The Input Data Quality Control is a critical process applied to guarantee that DUACS uses only the mostaccurate altimeter data Thanks to the high quality of current missions this process rejects a small percent-age of altimeter measurements but these erroneous data could be the cause of a significant quality lossThe quality control relies on standard raw data editing with quality flags or parameter thresholds but alsoon complex data editing algorithms based on the detection of erroneous artefacts mono and multi-missioncrossover validation and macroscopic statistics to edit out large data flows that do not meet the systemrsquosrequirements
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III35 Multi-mission cross-calibration
The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistentand accurate information It removes any residual orbit error (OE Le Traon and Ogor 1998[32]) or longwavelength error (LWE Le Traon et al 1998[31]) as well as large scale biases and discrepancies betweenvarious data flows
This process is based on two very different algorithms a global multi-mission crossover minimization fororbit error reduction (OER) and Optimal Interpolation (OI) for LWE
Multi-satellite crossover determination is performed on a daily basis All altimeter fields (measurementcorrections and other fields such as bathymetry MSS) are interpolated at crossover locations and datesCrossovers are then appended to the existing crossover database as more altimeter data become availableThis crossover data set is the input of the Orbit Error Reduction (OER) method Using the precision of thereference mission orbit a very accurate orbit error can be estimated LWE is mostly due to residual tidalor inverse barometer errors and high frequency ocean signals The OI used for LWE reduction uses preciseparameters derived from
bull accurate statistical description of sea level variability
bull localized correlation scales
bull mission-specific noise and precise assumptions on the long wavelength errors to be removed (from arecent analysis of one year of data from each mission)
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III36 Product generation
The product generation process is composed of four steps computation of raw SLA cross-validationfilteringampsub-sampling and generation of by-products
III361 Computation of raw SLA
Since the geoid is not well known yet the SSH cannot be used directly the SSH anomalies are used insteadThey are computed from the difference of the instantaneous SSH - a temporal reference This temporalreference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeattrack analysis cannot be used The errors affecting the SLAs MPs and MSS have different magnitudes andwavelengths The computation of the SLAs and their errors associated are detailed in Dibarboure et al 2010[9]
Use of a Mean ProfileIn the repeat track analysis (when the satellites flies over a repetitive orbit) measurements are re-sampledalong a theoretical ground track (or mean track) associated to each mission Then a Mean Profile (MP) issubtracted from the re-sampled data to obtain SLA The MP is a time average of similarly re-sampled dataover a long period
bull The Mean Profile used for TP (cycles 1 to 364) Jason-1 (cycles 1 to 259) and Jason-2 is computedwith 10 years of TP (cycles 11 to 353) and 6 years of Jason-1 (cycles 11 to 250)
bull The Mean Profile used for TP (cycles 368 to 481) and from Jason-1 cycle 262 to 374 (where satellitesare on interleaved ground-tracks) is computed with 3 years of TP (cycles 369 to 479)
bull The Mean Profile used for ERS-1 in its 35 days repetitive orbit mission ERS-2 and Envisat (only forthe first orbit before November 2010) is computed with 8 years of ERS-2 (cycles 1 to 85) and 6 yearsof Envisat (cycles 10 to 72)
bull No Mean Profile can be used for Envisat on its new orbit (enn) Jason-1 on its geodetic orbit (j1g)because there is no repetitive track The MSS must be used instead (see below)
bull The Mean Profile used for GFO is computed with 7 years of GFO cycles 37 to 187
Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible
bull Indeed as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide precise cross-track projection andor interpolation schemes are required to avoid errors
bull The mesoscale variability error (which is lt35 cm for MP between 3 to 5 years and lt1cm for WLof 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a prioriknowledge from Sea Level maps derived from previous iterations or from other missions
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bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for ERS-1 for its 168 days geodetic mission (phases E-F from April1994 to March 1995) or for Envisat since november 2010 because the satellite is not in a repetitive orbitphase The alternative is to use the MSS instead The gridded MSS is derived from along track MPs anddata from geodetic phases Thus any error on the MP is also contained in the MSS There are essentially 4types of additional errors on gridded MSS which are hard to quantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
III362 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III363 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
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III37 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III371 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
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IV MYOCEAN PRODUCTS
IV1 Near Real Time Products
The purpose of the NRT DUACS component is the acquisition of altimeter data from various altimeter mis-sions in near-real time (ie within a few days at most) the validation and correction of these altimeter datasets (ie edition and selection update of corrections and homogenization orbit error reduction) in order toproduce each day along-track productsProducts are as follows
Along-track products global and regional (Mediterranean and Black Seas Arctic Ocean and Europeareas)
bull Sea Level Anomaly (NRT-SLA) for each mission with NRT-SLA ephemeris
IV11 Delay of the products
The availability of the products in near real time is three to twelve hours after the measurement for along-track products Those products are delivered every day
IV12 Temporal availibility
The following table presents the available products by mission and by data periodNear real time products
NRT Jason-2 Jason-1 and Jason-1geodetic
Envisat new Cryosat-2
Temporal Time availability ymlowast
ongoingymlowast-20120303 for
repeat track and20120507-ongoing for
geodetic track
ymlowast
2012040820120101
ongoing
NRT-SLA X X X X
lowastym the temporal coverage for NRT products is fluctuating and depends on updates of Delayed Time prod-ucts When DT products are updated (3 to 4 times per year) the oldest NRT products are replaced by thebetter quality DT products so that the 2 series are overlapping on few weeks or few months
IV2 Delayed Time Products
The Delayed Time component of SSALTODUACS system is responsible for the production of processedJason-1 Jason-2 TP Envisat GFO ERS12 and even Geosat data in order to provide a homogeneousinter-calibrated and highly accurate long time series of SLA DT products are more precise than NRT products Two reasons explain this quality difference The firstone is the better intrinsic quality of the POE orbit used in the GDR processing The second reason is that
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in the DT DUACS processing the products can be computed optimally with a centred computation timewindow for OER LWE On the contrary in NRT case future data are not available so the computationtime window is not centred and therefore not optimalAs for NRT products improved altimeter corrections and processing algorithms are used ocean tide modelto correct altimeter data improved methods for orbit error reduction and mapping
Along-Track products global and regional (Mediterranean and Black Seas)
bull Sea Level Anomaly (DT-SLA) for each mission
IV21 Delay of the products
Weekly products are delivered The availability of the products in delayed time is at the best two monthsafter the date of the measurement The product generation needs all the GDR data of all the missions to takeinto account the best corrections as possible The time delay can be longer in the case of a missing mission
IV22 Temporal availibility
The following table presents the available products by mission and by data periodDelayed time SSALTODUACS products
Upd Jason-2 Jason-1new6
Jason-1 GFO Envisatnew6
Envisat ERS-16
ERS-2Topexnew6
Topex
TemporalTimeavailabil-ity
200810ymlowast
200902ymlowast
200204200810
200001200809
201010ymlowast
200210201010
199210200304
200209200510
199209200204
DT-SLA X X X X X X X X X
lowast ym those dates are updated regularly (3 to 4 times per year) and are avalaible when you download thedata at httpwwwmyoceaneuweb24-cataloguephp6 Jason-1 new orbit starting 200809 Envisat new orbit starting 201010 TP new orbit starting 200209 ERS-1The geodetic phases (E-F) are included There are no ERS-1 data between December 23 1993 and April 10 1994(ERS-1 phase D - 2nd ice phase) Note that during that time products are based only on TopexPoseidon data
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V DESCRIPTION OF THE PRODUCT SPECIFICATION
V1 General information
Product Specification SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001
Geographical coverage global
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 20-50km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001 Product Specification
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Product Specification SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002
Geographical coverage 55˚W-35˚E 30˚N-46˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002 Product Specification
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Product Specification SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003
Geographical coverage 27˚E-42˚E 40˚N-47˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003 Product Specification
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Product Specification SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004
Geographical coverage 25˚W-42˚E 21˚N-66˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004 Product Specification
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Product Specification SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005
Geographical coverage 0˚W-360˚E 50˚N-82˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005 Product Specification
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VI NOMENCLATURE OF FILES
VI1 Nomenclature of files downloaded through the MyOcean Web PortalDirectgetfile Service
VI11 Nomenclature of the product line
The description of the syntax for the SL TAC SLA products line is given by
SEALEVEL_ltREGIONgt_SLA_L3_ltDELAYgt_OBSERVATIONS_008_ltZONEgt_ltLETTERgtwhere
REGION GLO global geographic coverage product
BS Black Sea products
MED Mediterranean products
ARC Arctic products (for NRT products)
EUROPE Europe products (for NRT products)
DELAY NRT near real time products
RAN delayed time or reanalysis products
ZONE 001 number on 3 digits
002
003
004
LETTER a letter on 1 digit
b
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VI12 Nomenclature of the datasets
The nomenclature used is
dataset-duacs-ltdelaygt-ltzonegt-ltmissiongt-lttype of slagt-l3where the fileds in ltgt are described below
delay nrt near-real time productsran delayed time products
zone global global geographic coverage productmedsea Mediterranean productsblacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1 (only for ran)e2 ERS-2 (only for ran)tp TOPEXPoseidon (only for ran)tpn TOPEXPoseidon on its new orbit (only for
ran)g2 GFO (only for ran)j1 Jason-1 (only for ran)j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisat (only for ran)enn Envisat on its new orbitc2 Cryosat-2 (only for nrt)
type of sla sla filtered slasla_unfiltered non filtered sla (only for ran products)
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VI13 Nomenclature of the NetCdf files
The nomenclature used is
ltdelaygt_ltzonegt_ltmissiongt_sla_ltvariablegt_ltdatebegingt_ltdateendgt_ltdateprodgtnc where the fileds in ltgt are de-scribed below
delay nrt near-real time productsdt delayed time products
zone global global geographic coverage productmed Mediterranean products (for dt)mfstep Mediterranean products (for nrt)blacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1e2 ERS-2tp TOPEXPoseidontpn TOPEXPoseidon on its new orbitg2 GFOj1 Jason-1j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisatenn Envisat on its new orbitc2 Cryosat-2
variable vfec filtered and sub-sampled slavxxc non filtered and non sub-sampled sla (only
for dt)datebegin YYYYMMDD() beginning date of the datasetdateend YYYYMMDD() end date of the datasetdateprod YYYYMMDD production date of the dataset
() For dt data as the dates in the file names are rounded the user wanting data for date T has to read the filescontaining dates T+1 and T-1 in their name and check inside the files if there are some data for date T
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VII DATA FORMAT
This chapter presents the data storage format used for MyOcean products
VII1 NetCdf
The products are stored using the NetCDF format NetCDF (network Common Data Form) is an interface for array-oriented data access and a library that provides an implementation of the interface The netCDF library also definesa machine-independent format for representing scientific data Together the interface library and format support thecreation access and sharing of scientific data The netCDF software was developed at the Unidata Program Center inBoulder Colorado The netCDF libraries define a machine-independent format for representing scientific data Pleasesee Unidata NetCDF pages for more information and to retreive NetCDF software package onhttpwwwunidataucaredupackagesnetcdfindexhtml
NetCDF data is
bull Self-Describing A netCDF file includes information about the data it contains
bull Architecture-independent A netCDF file is represented in a form that can be accessed by computers with dif-ferent ways of storing integers characters and floating-point numbers
bull Direct-access A small subset of a large dataset may be accessed efficiently without first reading through allthe preceding data
bull Appendable Data can be appended to a netCDF dataset along one dimension without copying the dataset orredefining its structure The structure of a netCDF dataset can be changed though this sometimes causes thedataset to be copied
bull Sharable One writer and multiple readers may simultaneously access the same netCDF file
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VII2 Structure and semantic of NetCDF along-track files
The NetCDF Sea Level TAC files are based on the attribute data tags defined by the Cooperative OceanAtmosphereResearch Data Service (COARDS) and Climate and Forecast (CF) metadata conventions The CF convention gener-alises and extends the COARDS convention but relaxes the COARDS constraints on dimension and order and specifiesmethods for reducing the size of datasetsA wide range of software are available to write or read NetCDFCF files API are made available by UNIDATA(httpwwwunidataucaredusoftwarenetcdf)
bull CC++Fortran
bull Java
bull MATLAB Objective-C Perl Python R Ruby TclTk
In addition to these conventions the files are using a common structure and semantic
bull 1 dimension is defined
ndash time it is used to check NetCDF variables depending on time
bull 8 variables are defined
ndash short SLA contains the Sea Level Anomaly values for each time given
ndash int longitude contains the longitude for each measurement
ndash short track contains the track number for each measurement
ndash double time contains the time in days since 1950-01-01 000000 UTC for each measurement
ndash short mean_profile_point_index index of the corrsponding point in the track of the mean profile
ndash byte flag flag=0 the processed data comes from OGDR if flag=1 the processed data comes from theIGDR
ndash int latitude contains the latitude for each measurement
ndash short cycle contains the cycle number for each measurement
bull global attributes
ndash the global attributes gives information about the creation of the file
Example of a NetCDF sla file
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netcdf nrt_global_j1_sla_vfec_20101230_20101230_20101230 dimensions
time = 10385 variables
short SLA(time) SLAcoordinates = longitude latitude SLAlong_name = Sea Level Anomaly SLA_FillValue = 32767s SLAadd_offset = 0 SLAscale_factor = 0001 SLAunits = m SLAstandard_name = sea_surface_height_above_sea_level
int longitude(time) longitudelong_name = Longitude of measurement longitude_FillValue = 2147483647 longitudeadd_offset = 0 longitudestandard_name = longitude longitudescale_factor = 1e-06 longitudeunits = degrees_east
short track(time) tracklong_name = Track in cycle the measurement belongs to track_FillValue = 32767s trackunits = 1 trackcoordinates = longitude latitude
double time(time) timelong_name = Time of measurement time_FillValue = 184467440737096e+19 timeaxis = T timestandard_name = time timeunits = days since 1950-01-01 000000 UTC
int latitude(time) latitudelong_name = Latitude of measurement latitude_FillValue = 2147483647 latitudeadd_offset = 0 latitudestandard_name = latitude latitudescale_factor = 1e-06 latitudeunits = degrees_north
short flag(time) flagcoordinates = longitude latitude flag_FillValue = 3267s flaglong_name = data origin flagflag_values = 1s 0s flagflag_meanings = igdr_like non_igdr_like flagcomment = The origin of the data is determined by the types of geophysical datarecords (GDR) used in computation of the SLA 1 for the Interim GDR (IGDR) and0 for Operational GDR (OGDR)
short cycle(time) cyclelong_name = Cycle the measurement belongs to cycle_FillValue = 32767s cycleunits = 1 cyclecoordinates = longitude latitude
global attributeshistory = 22-Feb-2011 155243 CET File created by the SSLATODUACS system version 1001 comment = Produce from ENVISAT Extension Phase satellite altimetry data institution = CLSCNES
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references = httpwwwavisooceanobscomfileadmindocumentsdatatoolshdbk_duacspdf source = satellite altimetry title = along track Sea Level Anomaly Conventions = CF-14
dataSLA =
7 7 11 10 -2 -22 -39 -41 -30 -13 -3 -5 -16 -26 -32 -35-35 -35 -37 -35 -31 -29 -31 -35 -32 -21 -10 -10 -19 -20 -1-69 -57 -49 -45 -39 -30 -28 -31 -27 -13 -2 -5 -15 -3 1112 3 -7 -10 -14 -15 -22 -31 -37 -32 -17 -10
longitude =74743328 74868400 74993968 75120040 75246616 7537372875501368 75629568 75758320 75887656 76017568 76148080 7627920876388952 76477056 76565456 76654144 76743128 76832400 76921984329429568 329535424 329641792 329748672 329856096 329964032330072512 330181536 330291072 330401184
track =92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 9292 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92113 113 113 113 113 113 113 113 113 113 113 113 113 113113 113 113 113 113 113 113 113 113
time =222780000565705 222780001314719 222780002063733222780002812747 222780003561761 222780004310775 222780005059788222780005808802 222780006557816 22278000730683 222780008055844222780008804858 222780009553872 22278001017805 222780010677393222788257112198 222788257486705 222788257861212 222788258235719222788258610226 222788258984733 222788259359239 222788259733746222788260108253 22278826048276
mean_profile_point_index =1872 1878 1884 1890 1896 1902 1908 19141920 1926 1932 1938 1944 1949 1953 1957 1961 1965 1969 19732306 2309 2312 2315 2318 2321 2327 2330 2333 2336 2339 23422345 2348 2351 2354 2357 2360 2363 2366
flag =0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
latitude =-16225506 -16539731 -16853833 -17167810 -17481660 -17795380-18108966 -18422418 -18735729 -19048899 -19361924 -19674801-19987527 -20248015 -20456329 -20664569 -20872739 -2108083739481297 39628277 39775133 39921866 40068472 40214953 4036130840507533 40653629 40799592 40945423 41091120 41236684 41382111
cycle =331 331 331 331 331 331 331 331 331 331 331 331 331
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331 331 331 331 331 331 331 331 331 331 331 331 331 331331 331 331 331 331 331 331 331 331 331 331 331
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
VIII HOW TO DOWNLOAD A PRODUCT
VIII1 Download a product through the MyOcean Web Portal DirectgetfileService
You first need to register Please find below the registration stepshttpwwwmyoceaneuweb34-products-and-services-faqphp1Once registered the MyOcean FAQ httpwwwmyoceaneuweb34-products-and-services-faqwill guide you on How to download a product through the MyOcean Web Portal Directgetfile Service
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
IX NEWS AND UPDATES
IX1 [Duacs] Operational news
To be kept informed on events occurring on the satellites and on the eventual interruption of the services of the DUACSprocessing system see the [Duacs] operational news on the Aviso websitehttpwwwavisooceanobscomendataoperational-newsindexhtml
IX2 Updates
To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtmlSince 2010 a complete reprocessing of all altimetry data (cumulated total of about 55 years of data) is available Themain changes introduced in the Duacs DT v300 reprocessed data set in SSALTODUACS reprocessed DT data setare listed herehttpwwwavisooceanobscomfileadmindocumentsdataduacsduacs_DT_2010_reprocessing_impactpdf
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III26 Product generation
The product generation process is composed of four steps computation of raw SLA cross-validationfilteringampsub-sampling and generation of by-products
III261 Computation of raw SLA
Since the geoid is not well known yet the SSH cannot be used directly the SSH anomalies are used insteadThey are computed from the difference of the instantaneous SSH - a temporal reference This temporalreference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeattrack analysis cannot be used The errors affecting the SLAs MPs and MSS have different magnitudes andwavelengths The computation of the SLAs and their errors associated are detailed in Dibarboure et al 2010[9]
Use of a Mean ProfileIn the repeat track analysis (when the satellites flies over a repetitive orbit) measurements are re-sampledalong a theoretical ground track (or mean track) associated to each mission Then a Mean Profile (MP) issubtracted from the re-sampled data to obtain SLA The MP is a time average of similarly re-sampled dataover a long period
bull The Mean Profile used for Jason-2 is computed with 10 years of TP (cycles 11 to 353) and 6 years ofJason-1 (cycles 11 to 250)
bull The Mean Profile used from Jason-1 cycle 262 to 374 (where satellites are on interleaved ground-tracks) is computed with 3 years of TP (cycles 369 to 479)
bull No Mean Profile can be used for Envisat on its new orbit (enn) Jason-1 on its geodetic orbit (j1g) norfor Cryosat-2 mission (c2) because there is no repetitive track The MSS must be used instead (seebelow)
Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible
bull Indeed as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide precise cross-track projection andor interpolation schemes are required to avoid errors
bull The mesoscale variability error (which is lt35 cm for MP between 3 to 5 years and lt1cm for WLof 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a prioriknowledge from Sea Level maps derived from previous iterations or from other missions
bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
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PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for Envisat since november 2010 and for Cryosat-2 mission (c2)because the satellite is not in a repetitive orbit phase The alternative is to use the MSS instead The griddedMSS is derived from along track MPs and data from geodetic phases Thus any error on the MP is alsocontained in the MSS There are essentially 4 types of additional errors on gridded MSS which are hard toquantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
Note that for the Arctic regional products the DTU10 MSS [1] is taken into account instead of the CLS01MSS Indeed the accuracy of DTU10 compared to CLS01 is further demonstrated by the significant sealevel anomaly variance reduction found over the whole Arctic Ocean as shown in Prandi et al [42]
III262 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III263 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III27 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III271 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III272 Performance indicators
To appreciate the quality situation of the DUACS system new performance indicators are computed dailyThey aim at evaluate the status of the main processing steps of the system the input data availability theinput data coverage the input data quality and the output product quality These indicators are computed foreach and every currently working satellite and combined to obtain the overall status
Figure 8 Example with the key performance indicator on 20090627
See the description the latest and previous indicators on Aviso websitehttpwwwavisooceanobscomindexphpid=1516
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III3 Delayed Time processing steps
III31 Input data models and corrections applied
Delayed Time MyOcean products are generated
bull from Aviso GDR products for TP Jason-1 Jason-2 and Envisat (GDR-A cycles 1 to 22 GDR-Bcycles 23 to 85 GDR-C from cycle 86)
bull from NOAA GDR for GFO and from CERSAT (IFREMER) OPR for ERS-1 and ERS-2 (phases C(1st 35-day repeat orbit period) phase E and F (geodetic phases) phase G for ERS-1 (last 35-dayrepeat orbit period tandem phase with ERS-2 phase A for ERS-2 (1st 35-day repeat orbit periodtandem phase with ERS-1))
All GDR products are computed with a Precise Orbit Ephemeris (POE) and are delivered within 2 to 3months depending on the mission For several missions an updated orbit is used
bull For ERS-1amp-2 the orbit used is DGME-04 provided by Delft Institute (httpwwwdeostudelftnl)until June 2003
bull For TopexPoseidon the orbit used is GSFC (std0809) for the whole mission
bull For Envisat CNES POE of GDR-C standard is used for the whole mission
bull For the whole GFO mission the orbit used is GSFC (std0809) and when not available NASA POE isused
Altimetric product Source Availability Type of orbit
TopexPoseidon GDR NASACNES - GSFC POE
Jason-1 GDR (GDR-C) CNESNASA ~40 days CNES POE
Jason-2 GDR (GDR-C) CNESNASA ~60 days CNES POE
GFO GDR NOAA - GSFCNASA POE
ERS-1amp2 IFREMERESA - DGME-04
Envisat (GDR-A GDR-B andGDR-C from cycle 86)
ESA ~2 months CNES POE
Table 5 SSALTODUACS Delayed Time Input data overview
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
DU
AC
S20
11D
Tpr
oduc
t(gtV
30
0)j2
j1j1
ntp
tpn
e1e2
ene
nng2
Prod
uct
stan
dard
ref
GD
R-C
OPR
GD
R-A
(Cyc
les
1to
22)
GD
R-B
(cyc
les
23-8
5)
GD
R(N
OA
A)
Orb
itC
nes
POE
GSF
C(I
TR
F20
05G
RA
CE
last
stan
dard
s)
DG
ME
-04
(Sch
arro
oan
dV
isse
r19
98[4
8]C
NE
SPO
E(G
DR
-1st
anda
rds
forc
ycle
s9
to22
GD
R-C
stan
dard
sfr
omcy
cle
23)
GSF
C(I
TR
F20
05
GR
AC
Ela
stst
anda
rds
Iono
pher
icD
ual f
requ
ency
altim
eter
rang
em
easu
rem
ents
Dua
l fre
quen
cyal
timet
erra
nge
mea
sure
men
ts(T
opex
)D
OR
IS(P
OSE
IDO
N)
Ben
t mod
elB
ent m
odel
(cyc
les
1-36
)G
IMm
odem
from
cycl
e37
((Ii
jima
etal
19
98[2
4])
Dua
l-fr
eque
ncy
altim
eter
rang
em
easu
rem
ent(
cycl
e9-
64)a
ndG
IMm
odel
gtcyc
le65
(Iiji
ma
etal
19
99[2
4])c
orre
cted
from
8m
mbi
as
From
GIM
mod
el(I
ijim
aet
al1
998
[24]
)
Dry
trop
o-sp
here
Mod
elco
mpu
ted
from
EC
MW
FG
auss
ian
grid
s(n
ewS1
and
S2at
mos
pher
ictid
esar
eap
plie
d)
Mod
elco
mpu
ted
from
EC
MW
Fre
ctan
gula
rgri
ds(n
ewS1
and
S2at
mos
pher
ictid
esar
ein
clud
ed)
Wet
trop
o-sp
here
JMR
AM
Rra
diom
eter
furt
hert
han
50km
from
the
coas
tsF
rom
EC
MW
Fm
odel
ford
ista
nces
betw
een
10an
d50
km
TM
Rra
diom
eter
(Sch
aroo
etal
20
04[4
9])
MW
RC
orre
ctio
nof
the
drif
ton
the
236
GH
zbr
ight
ness
tem
pera
ture
(Sch
arro
oet
al
2004
[49]
)Neu
ral
Net
wor
kal
gori
thm
(Tra
nan
dO
blig
is
2003
[50]
MW
Rra
diom
eter
furt
hert
han
50km
from
the
coas
tsan
dco
rrec
ted
from
side
lobe
s(f
rom
cycl
e41
)E
CM
WF
mod
elfo
rdis
tanc
esbe
twee
n10
and
50km
GFO
radi
omet
er
DA
CM
OG
2DH
igh
Res
olut
ion
forc
edw
ithE
CM
WF
pres
sure
and
win
gfie
lds
(S1
and
S2w
ere
excl
uded
)+in
vers
eba
rom
eter
com
pute
dfr
omre
ctan
gula
rgri
ds
Tabl
e6
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(1
2)
Page 33
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
j2j1
j1n
tptp
ne1
e2en
enn
g2O
cean
tide
GO
T4v
7(S
1an
dS2
are
incl
uded
)Po
letid
e[W
ahr
1985
[53]
]So
lidea
rth
tide
Ela
stic
resp
onse
totid
alpo
tent
ial[
Car
twri
ghta
ndTa
yler
197
1[5]
][C
artw
righ
tand
Edd
en1
973[
6]]
Loa
ding
tide
GO
T4v
7(S
1pa
ram
eter
isin
clud
ed)
Sea
stat
ebi
asN
onpa
ram
etri
cSS
B[G
aspa
reta
l20
02[2
0]]
Non
para
met
ric
SSB
[NT
ran
and
al2
010[
51]]
BM
3[G
aspa
ran
dO
gor
1994
[17]
]
Non
para
met
ric
SSB
[Mer
tzet
al
2005
[38]
]
Non
para
met
ric
SSB
[Gas
pare
tal
2002
]w
ithG
DR
-Bst
anda
rds
forc
ycle
s9
to85
and
with
GD
R-C
stan
dard
sfr
omcy
cle
86
Non
para
met
ric
SSB
[NT
ran
etal
20
10[5
1]]
Orb
iter
ror
Glo
bal m
ulti-
mis
sion
cros
sove
rmin
imiz
atio
n(L
eTr
aon
and
Ogo
r19
98[3
2])
Lon
gw
ave-
leng
her
rors
Opt
imal
Inte
rpol
atio
n(L
eTr
aon
etal
19
98[3
1])
Inte
rcal
ibra
tion
Ref
eren
cefr
omcy
cle
11R
efer
ence
from
cycl
e1
to35
4C
orre
ctio
nof
regi
onal
bias
J2J
1de
duce
dfr
omin
terc
alib
ratio
nph
ase
(cyc
le11
J2)
Cor
rect
ion
ofgl
obal
biai
sJ1
TP
deacutedu
ced
from
inte
rcal
ibra
tion
phas
e(c
ycle
s11
J1)
Mea
npr
o-fil
e(s
eeII
I36
1)
Com
pute
dw
ithcy
cles
11-3
53T
Pda
taan
dw
ithcy
cles
11-2
50J1
data
ref
eren
ced
[199
319
99]
TP
J1 c
ompu
ted
with
cycl
es11
-353
TP
data
and
with
cycl
es11
-250
J1da
tar
efer
ence
d[1
993
1999
]T
PNJ
1Nc
ompu
ted
with
cycl
es36
9-47
9T
PNda
tar
efer
ence
d[1
993
1999
]
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
ref
eren
ced
[199
319
99]
EN
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
re
fere
nced
[199
319
99]
EN
Nu
seof
MSS
_CN
ES_
CL
S11
[39]
Com
pute
dw
ithcy
cles
37-1
87G
2da
ta
refe
renc
ed[1
993
1999
]
Peri
odof
use
from
cycl
e9
from
cycl
e9
cycl
es1
to48
1cy
cles
15to
43In
clud
ing
E-F
geod
etic
phas
es
cycl
es1
to83
from
cycl
e9
cycl
es37
to22
2
Tabl
e7
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(2
2)
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III32 Acquisition
The acqusition process in Delayed time is much simpler than in Near Real time it consists in a synchronisa-tion process of all the auxiliary data required to homogenize propely the altimeter data sets The acquisitionstep uses the GDRs or the OPRs provided by the agencies
III33 Homogenization
The Homogenization process consists in applying the most recent corrections models and references rec-ommended for altimeter products Each mission is processed separately as its needs depend on the baseinput data The list of corrections and models currently applied is provided in tables 6 and 7 for DT data
III34 Input data quality control
The Input Data Quality Control is a critical process applied to guarantee that DUACS uses only the mostaccurate altimeter data Thanks to the high quality of current missions this process rejects a small percent-age of altimeter measurements but these erroneous data could be the cause of a significant quality lossThe quality control relies on standard raw data editing with quality flags or parameter thresholds but alsoon complex data editing algorithms based on the detection of erroneous artefacts mono and multi-missioncrossover validation and macroscopic statistics to edit out large data flows that do not meet the systemrsquosrequirements
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III35 Multi-mission cross-calibration
The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistentand accurate information It removes any residual orbit error (OE Le Traon and Ogor 1998[32]) or longwavelength error (LWE Le Traon et al 1998[31]) as well as large scale biases and discrepancies betweenvarious data flows
This process is based on two very different algorithms a global multi-mission crossover minimization fororbit error reduction (OER) and Optimal Interpolation (OI) for LWE
Multi-satellite crossover determination is performed on a daily basis All altimeter fields (measurementcorrections and other fields such as bathymetry MSS) are interpolated at crossover locations and datesCrossovers are then appended to the existing crossover database as more altimeter data become availableThis crossover data set is the input of the Orbit Error Reduction (OER) method Using the precision of thereference mission orbit a very accurate orbit error can be estimated LWE is mostly due to residual tidalor inverse barometer errors and high frequency ocean signals The OI used for LWE reduction uses preciseparameters derived from
bull accurate statistical description of sea level variability
bull localized correlation scales
bull mission-specific noise and precise assumptions on the long wavelength errors to be removed (from arecent analysis of one year of data from each mission)
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III36 Product generation
The product generation process is composed of four steps computation of raw SLA cross-validationfilteringampsub-sampling and generation of by-products
III361 Computation of raw SLA
Since the geoid is not well known yet the SSH cannot be used directly the SSH anomalies are used insteadThey are computed from the difference of the instantaneous SSH - a temporal reference This temporalreference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeattrack analysis cannot be used The errors affecting the SLAs MPs and MSS have different magnitudes andwavelengths The computation of the SLAs and their errors associated are detailed in Dibarboure et al 2010[9]
Use of a Mean ProfileIn the repeat track analysis (when the satellites flies over a repetitive orbit) measurements are re-sampledalong a theoretical ground track (or mean track) associated to each mission Then a Mean Profile (MP) issubtracted from the re-sampled data to obtain SLA The MP is a time average of similarly re-sampled dataover a long period
bull The Mean Profile used for TP (cycles 1 to 364) Jason-1 (cycles 1 to 259) and Jason-2 is computedwith 10 years of TP (cycles 11 to 353) and 6 years of Jason-1 (cycles 11 to 250)
bull The Mean Profile used for TP (cycles 368 to 481) and from Jason-1 cycle 262 to 374 (where satellitesare on interleaved ground-tracks) is computed with 3 years of TP (cycles 369 to 479)
bull The Mean Profile used for ERS-1 in its 35 days repetitive orbit mission ERS-2 and Envisat (only forthe first orbit before November 2010) is computed with 8 years of ERS-2 (cycles 1 to 85) and 6 yearsof Envisat (cycles 10 to 72)
bull No Mean Profile can be used for Envisat on its new orbit (enn) Jason-1 on its geodetic orbit (j1g)because there is no repetitive track The MSS must be used instead (see below)
bull The Mean Profile used for GFO is computed with 7 years of GFO cycles 37 to 187
Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible
bull Indeed as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide precise cross-track projection andor interpolation schemes are required to avoid errors
bull The mesoscale variability error (which is lt35 cm for MP between 3 to 5 years and lt1cm for WLof 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a prioriknowledge from Sea Level maps derived from previous iterations or from other missions
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bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for ERS-1 for its 168 days geodetic mission (phases E-F from April1994 to March 1995) or for Envisat since november 2010 because the satellite is not in a repetitive orbitphase The alternative is to use the MSS instead The gridded MSS is derived from along track MPs anddata from geodetic phases Thus any error on the MP is also contained in the MSS There are essentially 4types of additional errors on gridded MSS which are hard to quantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
III362 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III363 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
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III37 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III371 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
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IV MYOCEAN PRODUCTS
IV1 Near Real Time Products
The purpose of the NRT DUACS component is the acquisition of altimeter data from various altimeter mis-sions in near-real time (ie within a few days at most) the validation and correction of these altimeter datasets (ie edition and selection update of corrections and homogenization orbit error reduction) in order toproduce each day along-track productsProducts are as follows
Along-track products global and regional (Mediterranean and Black Seas Arctic Ocean and Europeareas)
bull Sea Level Anomaly (NRT-SLA) for each mission with NRT-SLA ephemeris
IV11 Delay of the products
The availability of the products in near real time is three to twelve hours after the measurement for along-track products Those products are delivered every day
IV12 Temporal availibility
The following table presents the available products by mission and by data periodNear real time products
NRT Jason-2 Jason-1 and Jason-1geodetic
Envisat new Cryosat-2
Temporal Time availability ymlowast
ongoingymlowast-20120303 for
repeat track and20120507-ongoing for
geodetic track
ymlowast
2012040820120101
ongoing
NRT-SLA X X X X
lowastym the temporal coverage for NRT products is fluctuating and depends on updates of Delayed Time prod-ucts When DT products are updated (3 to 4 times per year) the oldest NRT products are replaced by thebetter quality DT products so that the 2 series are overlapping on few weeks or few months
IV2 Delayed Time Products
The Delayed Time component of SSALTODUACS system is responsible for the production of processedJason-1 Jason-2 TP Envisat GFO ERS12 and even Geosat data in order to provide a homogeneousinter-calibrated and highly accurate long time series of SLA DT products are more precise than NRT products Two reasons explain this quality difference The firstone is the better intrinsic quality of the POE orbit used in the GDR processing The second reason is that
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in the DT DUACS processing the products can be computed optimally with a centred computation timewindow for OER LWE On the contrary in NRT case future data are not available so the computationtime window is not centred and therefore not optimalAs for NRT products improved altimeter corrections and processing algorithms are used ocean tide modelto correct altimeter data improved methods for orbit error reduction and mapping
Along-Track products global and regional (Mediterranean and Black Seas)
bull Sea Level Anomaly (DT-SLA) for each mission
IV21 Delay of the products
Weekly products are delivered The availability of the products in delayed time is at the best two monthsafter the date of the measurement The product generation needs all the GDR data of all the missions to takeinto account the best corrections as possible The time delay can be longer in the case of a missing mission
IV22 Temporal availibility
The following table presents the available products by mission and by data periodDelayed time SSALTODUACS products
Upd Jason-2 Jason-1new6
Jason-1 GFO Envisatnew6
Envisat ERS-16
ERS-2Topexnew6
Topex
TemporalTimeavailabil-ity
200810ymlowast
200902ymlowast
200204200810
200001200809
201010ymlowast
200210201010
199210200304
200209200510
199209200204
DT-SLA X X X X X X X X X
lowast ym those dates are updated regularly (3 to 4 times per year) and are avalaible when you download thedata at httpwwwmyoceaneuweb24-cataloguephp6 Jason-1 new orbit starting 200809 Envisat new orbit starting 201010 TP new orbit starting 200209 ERS-1The geodetic phases (E-F) are included There are no ERS-1 data between December 23 1993 and April 10 1994(ERS-1 phase D - 2nd ice phase) Note that during that time products are based only on TopexPoseidon data
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V DESCRIPTION OF THE PRODUCT SPECIFICATION
V1 General information
Product Specification SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001
Geographical coverage global
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 20-50km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001 Product Specification
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Product Specification SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002
Geographical coverage 55˚W-35˚E 30˚N-46˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002 Product Specification
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Product Specification SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003
Geographical coverage 27˚E-42˚E 40˚N-47˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003 Product Specification
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Product Specification SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004
Geographical coverage 25˚W-42˚E 21˚N-66˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004 Product Specification
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Product Specification SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005
Geographical coverage 0˚W-360˚E 50˚N-82˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005 Product Specification
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VI NOMENCLATURE OF FILES
VI1 Nomenclature of files downloaded through the MyOcean Web PortalDirectgetfile Service
VI11 Nomenclature of the product line
The description of the syntax for the SL TAC SLA products line is given by
SEALEVEL_ltREGIONgt_SLA_L3_ltDELAYgt_OBSERVATIONS_008_ltZONEgt_ltLETTERgtwhere
REGION GLO global geographic coverage product
BS Black Sea products
MED Mediterranean products
ARC Arctic products (for NRT products)
EUROPE Europe products (for NRT products)
DELAY NRT near real time products
RAN delayed time or reanalysis products
ZONE 001 number on 3 digits
002
003
004
LETTER a letter on 1 digit
b
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VI12 Nomenclature of the datasets
The nomenclature used is
dataset-duacs-ltdelaygt-ltzonegt-ltmissiongt-lttype of slagt-l3where the fileds in ltgt are described below
delay nrt near-real time productsran delayed time products
zone global global geographic coverage productmedsea Mediterranean productsblacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1 (only for ran)e2 ERS-2 (only for ran)tp TOPEXPoseidon (only for ran)tpn TOPEXPoseidon on its new orbit (only for
ran)g2 GFO (only for ran)j1 Jason-1 (only for ran)j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisat (only for ran)enn Envisat on its new orbitc2 Cryosat-2 (only for nrt)
type of sla sla filtered slasla_unfiltered non filtered sla (only for ran products)
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VI13 Nomenclature of the NetCdf files
The nomenclature used is
ltdelaygt_ltzonegt_ltmissiongt_sla_ltvariablegt_ltdatebegingt_ltdateendgt_ltdateprodgtnc where the fileds in ltgt are de-scribed below
delay nrt near-real time productsdt delayed time products
zone global global geographic coverage productmed Mediterranean products (for dt)mfstep Mediterranean products (for nrt)blacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1e2 ERS-2tp TOPEXPoseidontpn TOPEXPoseidon on its new orbitg2 GFOj1 Jason-1j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisatenn Envisat on its new orbitc2 Cryosat-2
variable vfec filtered and sub-sampled slavxxc non filtered and non sub-sampled sla (only
for dt)datebegin YYYYMMDD() beginning date of the datasetdateend YYYYMMDD() end date of the datasetdateprod YYYYMMDD production date of the dataset
() For dt data as the dates in the file names are rounded the user wanting data for date T has to read the filescontaining dates T+1 and T-1 in their name and check inside the files if there are some data for date T
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VII DATA FORMAT
This chapter presents the data storage format used for MyOcean products
VII1 NetCdf
The products are stored using the NetCDF format NetCDF (network Common Data Form) is an interface for array-oriented data access and a library that provides an implementation of the interface The netCDF library also definesa machine-independent format for representing scientific data Together the interface library and format support thecreation access and sharing of scientific data The netCDF software was developed at the Unidata Program Center inBoulder Colorado The netCDF libraries define a machine-independent format for representing scientific data Pleasesee Unidata NetCDF pages for more information and to retreive NetCDF software package onhttpwwwunidataucaredupackagesnetcdfindexhtml
NetCDF data is
bull Self-Describing A netCDF file includes information about the data it contains
bull Architecture-independent A netCDF file is represented in a form that can be accessed by computers with dif-ferent ways of storing integers characters and floating-point numbers
bull Direct-access A small subset of a large dataset may be accessed efficiently without first reading through allthe preceding data
bull Appendable Data can be appended to a netCDF dataset along one dimension without copying the dataset orredefining its structure The structure of a netCDF dataset can be changed though this sometimes causes thedataset to be copied
bull Sharable One writer and multiple readers may simultaneously access the same netCDF file
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VII2 Structure and semantic of NetCDF along-track files
The NetCDF Sea Level TAC files are based on the attribute data tags defined by the Cooperative OceanAtmosphereResearch Data Service (COARDS) and Climate and Forecast (CF) metadata conventions The CF convention gener-alises and extends the COARDS convention but relaxes the COARDS constraints on dimension and order and specifiesmethods for reducing the size of datasetsA wide range of software are available to write or read NetCDFCF files API are made available by UNIDATA(httpwwwunidataucaredusoftwarenetcdf)
bull CC++Fortran
bull Java
bull MATLAB Objective-C Perl Python R Ruby TclTk
In addition to these conventions the files are using a common structure and semantic
bull 1 dimension is defined
ndash time it is used to check NetCDF variables depending on time
bull 8 variables are defined
ndash short SLA contains the Sea Level Anomaly values for each time given
ndash int longitude contains the longitude for each measurement
ndash short track contains the track number for each measurement
ndash double time contains the time in days since 1950-01-01 000000 UTC for each measurement
ndash short mean_profile_point_index index of the corrsponding point in the track of the mean profile
ndash byte flag flag=0 the processed data comes from OGDR if flag=1 the processed data comes from theIGDR
ndash int latitude contains the latitude for each measurement
ndash short cycle contains the cycle number for each measurement
bull global attributes
ndash the global attributes gives information about the creation of the file
Example of a NetCDF sla file
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netcdf nrt_global_j1_sla_vfec_20101230_20101230_20101230 dimensions
time = 10385 variables
short SLA(time) SLAcoordinates = longitude latitude SLAlong_name = Sea Level Anomaly SLA_FillValue = 32767s SLAadd_offset = 0 SLAscale_factor = 0001 SLAunits = m SLAstandard_name = sea_surface_height_above_sea_level
int longitude(time) longitudelong_name = Longitude of measurement longitude_FillValue = 2147483647 longitudeadd_offset = 0 longitudestandard_name = longitude longitudescale_factor = 1e-06 longitudeunits = degrees_east
short track(time) tracklong_name = Track in cycle the measurement belongs to track_FillValue = 32767s trackunits = 1 trackcoordinates = longitude latitude
double time(time) timelong_name = Time of measurement time_FillValue = 184467440737096e+19 timeaxis = T timestandard_name = time timeunits = days since 1950-01-01 000000 UTC
int latitude(time) latitudelong_name = Latitude of measurement latitude_FillValue = 2147483647 latitudeadd_offset = 0 latitudestandard_name = latitude latitudescale_factor = 1e-06 latitudeunits = degrees_north
short flag(time) flagcoordinates = longitude latitude flag_FillValue = 3267s flaglong_name = data origin flagflag_values = 1s 0s flagflag_meanings = igdr_like non_igdr_like flagcomment = The origin of the data is determined by the types of geophysical datarecords (GDR) used in computation of the SLA 1 for the Interim GDR (IGDR) and0 for Operational GDR (OGDR)
short cycle(time) cyclelong_name = Cycle the measurement belongs to cycle_FillValue = 32767s cycleunits = 1 cyclecoordinates = longitude latitude
global attributeshistory = 22-Feb-2011 155243 CET File created by the SSLATODUACS system version 1001 comment = Produce from ENVISAT Extension Phase satellite altimetry data institution = CLSCNES
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references = httpwwwavisooceanobscomfileadmindocumentsdatatoolshdbk_duacspdf source = satellite altimetry title = along track Sea Level Anomaly Conventions = CF-14
dataSLA =
7 7 11 10 -2 -22 -39 -41 -30 -13 -3 -5 -16 -26 -32 -35-35 -35 -37 -35 -31 -29 -31 -35 -32 -21 -10 -10 -19 -20 -1-69 -57 -49 -45 -39 -30 -28 -31 -27 -13 -2 -5 -15 -3 1112 3 -7 -10 -14 -15 -22 -31 -37 -32 -17 -10
longitude =74743328 74868400 74993968 75120040 75246616 7537372875501368 75629568 75758320 75887656 76017568 76148080 7627920876388952 76477056 76565456 76654144 76743128 76832400 76921984329429568 329535424 329641792 329748672 329856096 329964032330072512 330181536 330291072 330401184
track =92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 9292 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92113 113 113 113 113 113 113 113 113 113 113 113 113 113113 113 113 113 113 113 113 113 113
time =222780000565705 222780001314719 222780002063733222780002812747 222780003561761 222780004310775 222780005059788222780005808802 222780006557816 22278000730683 222780008055844222780008804858 222780009553872 22278001017805 222780010677393222788257112198 222788257486705 222788257861212 222788258235719222788258610226 222788258984733 222788259359239 222788259733746222788260108253 22278826048276
mean_profile_point_index =1872 1878 1884 1890 1896 1902 1908 19141920 1926 1932 1938 1944 1949 1953 1957 1961 1965 1969 19732306 2309 2312 2315 2318 2321 2327 2330 2333 2336 2339 23422345 2348 2351 2354 2357 2360 2363 2366
flag =0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
latitude =-16225506 -16539731 -16853833 -17167810 -17481660 -17795380-18108966 -18422418 -18735729 -19048899 -19361924 -19674801-19987527 -20248015 -20456329 -20664569 -20872739 -2108083739481297 39628277 39775133 39921866 40068472 40214953 4036130840507533 40653629 40799592 40945423 41091120 41236684 41382111
cycle =331 331 331 331 331 331 331 331 331 331 331 331 331
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331 331 331 331 331 331 331 331 331 331 331 331 331 331331 331 331 331 331 331 331 331 331 331 331 331
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VIII HOW TO DOWNLOAD A PRODUCT
VIII1 Download a product through the MyOcean Web Portal DirectgetfileService
You first need to register Please find below the registration stepshttpwwwmyoceaneuweb34-products-and-services-faqphp1Once registered the MyOcean FAQ httpwwwmyoceaneuweb34-products-and-services-faqwill guide you on How to download a product through the MyOcean Web Portal Directgetfile Service
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IX NEWS AND UPDATES
IX1 [Duacs] Operational news
To be kept informed on events occurring on the satellites and on the eventual interruption of the services of the DUACSprocessing system see the [Duacs] operational news on the Aviso websitehttpwwwavisooceanobscomendataoperational-newsindexhtml
IX2 Updates
To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtmlSince 2010 a complete reprocessing of all altimetry data (cumulated total of about 55 years of data) is available Themain changes introduced in the Duacs DT v300 reprocessed data set in SSALTODUACS reprocessed DT data setare listed herehttpwwwavisooceanobscomfileadmindocumentsdataduacsduacs_DT_2010_reprocessing_impactpdf
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bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for Envisat since november 2010 and for Cryosat-2 mission (c2)because the satellite is not in a repetitive orbit phase The alternative is to use the MSS instead The griddedMSS is derived from along track MPs and data from geodetic phases Thus any error on the MP is alsocontained in the MSS There are essentially 4 types of additional errors on gridded MSS which are hard toquantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
Note that for the Arctic regional products the DTU10 MSS [1] is taken into account instead of the CLS01MSS Indeed the accuracy of DTU10 compared to CLS01 is further demonstrated by the significant sealevel anomaly variance reduction found over the whole Arctic Ocean as shown in Prandi et al [42]
III262 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III263 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
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III27 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III271 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
Page 30
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III272 Performance indicators
To appreciate the quality situation of the DUACS system new performance indicators are computed dailyThey aim at evaluate the status of the main processing steps of the system the input data availability theinput data coverage the input data quality and the output product quality These indicators are computed foreach and every currently working satellite and combined to obtain the overall status
Figure 8 Example with the key performance indicator on 20090627
See the description the latest and previous indicators on Aviso websitehttpwwwavisooceanobscomindexphpid=1516
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III3 Delayed Time processing steps
III31 Input data models and corrections applied
Delayed Time MyOcean products are generated
bull from Aviso GDR products for TP Jason-1 Jason-2 and Envisat (GDR-A cycles 1 to 22 GDR-Bcycles 23 to 85 GDR-C from cycle 86)
bull from NOAA GDR for GFO and from CERSAT (IFREMER) OPR for ERS-1 and ERS-2 (phases C(1st 35-day repeat orbit period) phase E and F (geodetic phases) phase G for ERS-1 (last 35-dayrepeat orbit period tandem phase with ERS-2 phase A for ERS-2 (1st 35-day repeat orbit periodtandem phase with ERS-1))
All GDR products are computed with a Precise Orbit Ephemeris (POE) and are delivered within 2 to 3months depending on the mission For several missions an updated orbit is used
bull For ERS-1amp-2 the orbit used is DGME-04 provided by Delft Institute (httpwwwdeostudelftnl)until June 2003
bull For TopexPoseidon the orbit used is GSFC (std0809) for the whole mission
bull For Envisat CNES POE of GDR-C standard is used for the whole mission
bull For the whole GFO mission the orbit used is GSFC (std0809) and when not available NASA POE isused
Altimetric product Source Availability Type of orbit
TopexPoseidon GDR NASACNES - GSFC POE
Jason-1 GDR (GDR-C) CNESNASA ~40 days CNES POE
Jason-2 GDR (GDR-C) CNESNASA ~60 days CNES POE
GFO GDR NOAA - GSFCNASA POE
ERS-1amp2 IFREMERESA - DGME-04
Envisat (GDR-A GDR-B andGDR-C from cycle 86)
ESA ~2 months CNES POE
Table 5 SSALTODUACS Delayed Time Input data overview
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
DU
AC
S20
11D
Tpr
oduc
t(gtV
30
0)j2
j1j1
ntp
tpn
e1e2
ene
nng2
Prod
uct
stan
dard
ref
GD
R-C
OPR
GD
R-A
(Cyc
les
1to
22)
GD
R-B
(cyc
les
23-8
5)
GD
R(N
OA
A)
Orb
itC
nes
POE
GSF
C(I
TR
F20
05G
RA
CE
last
stan
dard
s)
DG
ME
-04
(Sch
arro
oan
dV
isse
r19
98[4
8]C
NE
SPO
E(G
DR
-1st
anda
rds
forc
ycle
s9
to22
GD
R-C
stan
dard
sfr
omcy
cle
23)
GSF
C(I
TR
F20
05
GR
AC
Ela
stst
anda
rds
Iono
pher
icD
ual f
requ
ency
altim
eter
rang
em
easu
rem
ents
Dua
l fre
quen
cyal
timet
erra
nge
mea
sure
men
ts(T
opex
)D
OR
IS(P
OSE
IDO
N)
Ben
t mod
elB
ent m
odel
(cyc
les
1-36
)G
IMm
odem
from
cycl
e37
((Ii
jima
etal
19
98[2
4])
Dua
l-fr
eque
ncy
altim
eter
rang
em
easu
rem
ent(
cycl
e9-
64)a
ndG
IMm
odel
gtcyc
le65
(Iiji
ma
etal
19
99[2
4])c
orre
cted
from
8m
mbi
as
From
GIM
mod
el(I
ijim
aet
al1
998
[24]
)
Dry
trop
o-sp
here
Mod
elco
mpu
ted
from
EC
MW
FG
auss
ian
grid
s(n
ewS1
and
S2at
mos
pher
ictid
esar
eap
plie
d)
Mod
elco
mpu
ted
from
EC
MW
Fre
ctan
gula
rgri
ds(n
ewS1
and
S2at
mos
pher
ictid
esar
ein
clud
ed)
Wet
trop
o-sp
here
JMR
AM
Rra
diom
eter
furt
hert
han
50km
from
the
coas
tsF
rom
EC
MW
Fm
odel
ford
ista
nces
betw
een
10an
d50
km
TM
Rra
diom
eter
(Sch
aroo
etal
20
04[4
9])
MW
RC
orre
ctio
nof
the
drif
ton
the
236
GH
zbr
ight
ness
tem
pera
ture
(Sch
arro
oet
al
2004
[49]
)Neu
ral
Net
wor
kal
gori
thm
(Tra
nan
dO
blig
is
2003
[50]
MW
Rra
diom
eter
furt
hert
han
50km
from
the
coas
tsan
dco
rrec
ted
from
side
lobe
s(f
rom
cycl
e41
)E
CM
WF
mod
elfo
rdis
tanc
esbe
twee
n10
and
50km
GFO
radi
omet
er
DA
CM
OG
2DH
igh
Res
olut
ion
forc
edw
ithE
CM
WF
pres
sure
and
win
gfie
lds
(S1
and
S2w
ere
excl
uded
)+in
vers
eba
rom
eter
com
pute
dfr
omre
ctan
gula
rgri
ds
Tabl
e6
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(1
2)
Page 33
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
j2j1
j1n
tptp
ne1
e2en
enn
g2O
cean
tide
GO
T4v
7(S
1an
dS2
are
incl
uded
)Po
letid
e[W
ahr
1985
[53]
]So
lidea
rth
tide
Ela
stic
resp
onse
totid
alpo
tent
ial[
Car
twri
ghta
ndTa
yler
197
1[5]
][C
artw
righ
tand
Edd
en1
973[
6]]
Loa
ding
tide
GO
T4v
7(S
1pa
ram
eter
isin
clud
ed)
Sea
stat
ebi
asN
onpa
ram
etri
cSS
B[G
aspa
reta
l20
02[2
0]]
Non
para
met
ric
SSB
[NT
ran
and
al2
010[
51]]
BM
3[G
aspa
ran
dO
gor
1994
[17]
]
Non
para
met
ric
SSB
[Mer
tzet
al
2005
[38]
]
Non
para
met
ric
SSB
[Gas
pare
tal
2002
]w
ithG
DR
-Bst
anda
rds
forc
ycle
s9
to85
and
with
GD
R-C
stan
dard
sfr
omcy
cle
86
Non
para
met
ric
SSB
[NT
ran
etal
20
10[5
1]]
Orb
iter
ror
Glo
bal m
ulti-
mis
sion
cros
sove
rmin
imiz
atio
n(L
eTr
aon
and
Ogo
r19
98[3
2])
Lon
gw
ave-
leng
her
rors
Opt
imal
Inte
rpol
atio
n(L
eTr
aon
etal
19
98[3
1])
Inte
rcal
ibra
tion
Ref
eren
cefr
omcy
cle
11R
efer
ence
from
cycl
e1
to35
4C
orre
ctio
nof
regi
onal
bias
J2J
1de
duce
dfr
omin
terc
alib
ratio
nph
ase
(cyc
le11
J2)
Cor
rect
ion
ofgl
obal
biai
sJ1
TP
deacutedu
ced
from
inte
rcal
ibra
tion
phas
e(c
ycle
s11
J1)
Mea
npr
o-fil
e(s
eeII
I36
1)
Com
pute
dw
ithcy
cles
11-3
53T
Pda
taan
dw
ithcy
cles
11-2
50J1
data
ref
eren
ced
[199
319
99]
TP
J1 c
ompu
ted
with
cycl
es11
-353
TP
data
and
with
cycl
es11
-250
J1da
tar
efer
ence
d[1
993
1999
]T
PNJ
1Nc
ompu
ted
with
cycl
es36
9-47
9T
PNda
tar
efer
ence
d[1
993
1999
]
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
ref
eren
ced
[199
319
99]
EN
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
re
fere
nced
[199
319
99]
EN
Nu
seof
MSS
_CN
ES_
CL
S11
[39]
Com
pute
dw
ithcy
cles
37-1
87G
2da
ta
refe
renc
ed[1
993
1999
]
Peri
odof
use
from
cycl
e9
from
cycl
e9
cycl
es1
to48
1cy
cles
15to
43In
clud
ing
E-F
geod
etic
phas
es
cycl
es1
to83
from
cycl
e9
cycl
es37
to22
2
Tabl
e7
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(2
2)
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III32 Acquisition
The acqusition process in Delayed time is much simpler than in Near Real time it consists in a synchronisa-tion process of all the auxiliary data required to homogenize propely the altimeter data sets The acquisitionstep uses the GDRs or the OPRs provided by the agencies
III33 Homogenization
The Homogenization process consists in applying the most recent corrections models and references rec-ommended for altimeter products Each mission is processed separately as its needs depend on the baseinput data The list of corrections and models currently applied is provided in tables 6 and 7 for DT data
III34 Input data quality control
The Input Data Quality Control is a critical process applied to guarantee that DUACS uses only the mostaccurate altimeter data Thanks to the high quality of current missions this process rejects a small percent-age of altimeter measurements but these erroneous data could be the cause of a significant quality lossThe quality control relies on standard raw data editing with quality flags or parameter thresholds but alsoon complex data editing algorithms based on the detection of erroneous artefacts mono and multi-missioncrossover validation and macroscopic statistics to edit out large data flows that do not meet the systemrsquosrequirements
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III35 Multi-mission cross-calibration
The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistentand accurate information It removes any residual orbit error (OE Le Traon and Ogor 1998[32]) or longwavelength error (LWE Le Traon et al 1998[31]) as well as large scale biases and discrepancies betweenvarious data flows
This process is based on two very different algorithms a global multi-mission crossover minimization fororbit error reduction (OER) and Optimal Interpolation (OI) for LWE
Multi-satellite crossover determination is performed on a daily basis All altimeter fields (measurementcorrections and other fields such as bathymetry MSS) are interpolated at crossover locations and datesCrossovers are then appended to the existing crossover database as more altimeter data become availableThis crossover data set is the input of the Orbit Error Reduction (OER) method Using the precision of thereference mission orbit a very accurate orbit error can be estimated LWE is mostly due to residual tidalor inverse barometer errors and high frequency ocean signals The OI used for LWE reduction uses preciseparameters derived from
bull accurate statistical description of sea level variability
bull localized correlation scales
bull mission-specific noise and precise assumptions on the long wavelength errors to be removed (from arecent analysis of one year of data from each mission)
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III36 Product generation
The product generation process is composed of four steps computation of raw SLA cross-validationfilteringampsub-sampling and generation of by-products
III361 Computation of raw SLA
Since the geoid is not well known yet the SSH cannot be used directly the SSH anomalies are used insteadThey are computed from the difference of the instantaneous SSH - a temporal reference This temporalreference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeattrack analysis cannot be used The errors affecting the SLAs MPs and MSS have different magnitudes andwavelengths The computation of the SLAs and their errors associated are detailed in Dibarboure et al 2010[9]
Use of a Mean ProfileIn the repeat track analysis (when the satellites flies over a repetitive orbit) measurements are re-sampledalong a theoretical ground track (or mean track) associated to each mission Then a Mean Profile (MP) issubtracted from the re-sampled data to obtain SLA The MP is a time average of similarly re-sampled dataover a long period
bull The Mean Profile used for TP (cycles 1 to 364) Jason-1 (cycles 1 to 259) and Jason-2 is computedwith 10 years of TP (cycles 11 to 353) and 6 years of Jason-1 (cycles 11 to 250)
bull The Mean Profile used for TP (cycles 368 to 481) and from Jason-1 cycle 262 to 374 (where satellitesare on interleaved ground-tracks) is computed with 3 years of TP (cycles 369 to 479)
bull The Mean Profile used for ERS-1 in its 35 days repetitive orbit mission ERS-2 and Envisat (only forthe first orbit before November 2010) is computed with 8 years of ERS-2 (cycles 1 to 85) and 6 yearsof Envisat (cycles 10 to 72)
bull No Mean Profile can be used for Envisat on its new orbit (enn) Jason-1 on its geodetic orbit (j1g)because there is no repetitive track The MSS must be used instead (see below)
bull The Mean Profile used for GFO is computed with 7 years of GFO cycles 37 to 187
Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible
bull Indeed as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide precise cross-track projection andor interpolation schemes are required to avoid errors
bull The mesoscale variability error (which is lt35 cm for MP between 3 to 5 years and lt1cm for WLof 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a prioriknowledge from Sea Level maps derived from previous iterations or from other missions
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bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for ERS-1 for its 168 days geodetic mission (phases E-F from April1994 to March 1995) or for Envisat since november 2010 because the satellite is not in a repetitive orbitphase The alternative is to use the MSS instead The gridded MSS is derived from along track MPs anddata from geodetic phases Thus any error on the MP is also contained in the MSS There are essentially 4types of additional errors on gridded MSS which are hard to quantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
III362 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III363 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
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III37 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III371 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
Page 39
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
IV MYOCEAN PRODUCTS
IV1 Near Real Time Products
The purpose of the NRT DUACS component is the acquisition of altimeter data from various altimeter mis-sions in near-real time (ie within a few days at most) the validation and correction of these altimeter datasets (ie edition and selection update of corrections and homogenization orbit error reduction) in order toproduce each day along-track productsProducts are as follows
Along-track products global and regional (Mediterranean and Black Seas Arctic Ocean and Europeareas)
bull Sea Level Anomaly (NRT-SLA) for each mission with NRT-SLA ephemeris
IV11 Delay of the products
The availability of the products in near real time is three to twelve hours after the measurement for along-track products Those products are delivered every day
IV12 Temporal availibility
The following table presents the available products by mission and by data periodNear real time products
NRT Jason-2 Jason-1 and Jason-1geodetic
Envisat new Cryosat-2
Temporal Time availability ymlowast
ongoingymlowast-20120303 for
repeat track and20120507-ongoing for
geodetic track
ymlowast
2012040820120101
ongoing
NRT-SLA X X X X
lowastym the temporal coverage for NRT products is fluctuating and depends on updates of Delayed Time prod-ucts When DT products are updated (3 to 4 times per year) the oldest NRT products are replaced by thebetter quality DT products so that the 2 series are overlapping on few weeks or few months
IV2 Delayed Time Products
The Delayed Time component of SSALTODUACS system is responsible for the production of processedJason-1 Jason-2 TP Envisat GFO ERS12 and even Geosat data in order to provide a homogeneousinter-calibrated and highly accurate long time series of SLA DT products are more precise than NRT products Two reasons explain this quality difference The firstone is the better intrinsic quality of the POE orbit used in the GDR processing The second reason is that
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in the DT DUACS processing the products can be computed optimally with a centred computation timewindow for OER LWE On the contrary in NRT case future data are not available so the computationtime window is not centred and therefore not optimalAs for NRT products improved altimeter corrections and processing algorithms are used ocean tide modelto correct altimeter data improved methods for orbit error reduction and mapping
Along-Track products global and regional (Mediterranean and Black Seas)
bull Sea Level Anomaly (DT-SLA) for each mission
IV21 Delay of the products
Weekly products are delivered The availability of the products in delayed time is at the best two monthsafter the date of the measurement The product generation needs all the GDR data of all the missions to takeinto account the best corrections as possible The time delay can be longer in the case of a missing mission
IV22 Temporal availibility
The following table presents the available products by mission and by data periodDelayed time SSALTODUACS products
Upd Jason-2 Jason-1new6
Jason-1 GFO Envisatnew6
Envisat ERS-16
ERS-2Topexnew6
Topex
TemporalTimeavailabil-ity
200810ymlowast
200902ymlowast
200204200810
200001200809
201010ymlowast
200210201010
199210200304
200209200510
199209200204
DT-SLA X X X X X X X X X
lowast ym those dates are updated regularly (3 to 4 times per year) and are avalaible when you download thedata at httpwwwmyoceaneuweb24-cataloguephp6 Jason-1 new orbit starting 200809 Envisat new orbit starting 201010 TP new orbit starting 200209 ERS-1The geodetic phases (E-F) are included There are no ERS-1 data between December 23 1993 and April 10 1994(ERS-1 phase D - 2nd ice phase) Note that during that time products are based only on TopexPoseidon data
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V DESCRIPTION OF THE PRODUCT SPECIFICATION
V1 General information
Product Specification SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001
Geographical coverage global
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 20-50km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001 Product Specification
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
Product Specification SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002
Geographical coverage 55˚W-35˚E 30˚N-46˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002 Product Specification
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Product Specification SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003
Geographical coverage 27˚E-42˚E 40˚N-47˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003 Product Specification
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
Product Specification SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004
Geographical coverage 25˚W-42˚E 21˚N-66˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004 Product Specification
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Product Specification SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005
Geographical coverage 0˚W-360˚E 50˚N-82˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005 Product Specification
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VI NOMENCLATURE OF FILES
VI1 Nomenclature of files downloaded through the MyOcean Web PortalDirectgetfile Service
VI11 Nomenclature of the product line
The description of the syntax for the SL TAC SLA products line is given by
SEALEVEL_ltREGIONgt_SLA_L3_ltDELAYgt_OBSERVATIONS_008_ltZONEgt_ltLETTERgtwhere
REGION GLO global geographic coverage product
BS Black Sea products
MED Mediterranean products
ARC Arctic products (for NRT products)
EUROPE Europe products (for NRT products)
DELAY NRT near real time products
RAN delayed time or reanalysis products
ZONE 001 number on 3 digits
002
003
004
LETTER a letter on 1 digit
b
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VI12 Nomenclature of the datasets
The nomenclature used is
dataset-duacs-ltdelaygt-ltzonegt-ltmissiongt-lttype of slagt-l3where the fileds in ltgt are described below
delay nrt near-real time productsran delayed time products
zone global global geographic coverage productmedsea Mediterranean productsblacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1 (only for ran)e2 ERS-2 (only for ran)tp TOPEXPoseidon (only for ran)tpn TOPEXPoseidon on its new orbit (only for
ran)g2 GFO (only for ran)j1 Jason-1 (only for ran)j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisat (only for ran)enn Envisat on its new orbitc2 Cryosat-2 (only for nrt)
type of sla sla filtered slasla_unfiltered non filtered sla (only for ran products)
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VI13 Nomenclature of the NetCdf files
The nomenclature used is
ltdelaygt_ltzonegt_ltmissiongt_sla_ltvariablegt_ltdatebegingt_ltdateendgt_ltdateprodgtnc where the fileds in ltgt are de-scribed below
delay nrt near-real time productsdt delayed time products
zone global global geographic coverage productmed Mediterranean products (for dt)mfstep Mediterranean products (for nrt)blacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1e2 ERS-2tp TOPEXPoseidontpn TOPEXPoseidon on its new orbitg2 GFOj1 Jason-1j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisatenn Envisat on its new orbitc2 Cryosat-2
variable vfec filtered and sub-sampled slavxxc non filtered and non sub-sampled sla (only
for dt)datebegin YYYYMMDD() beginning date of the datasetdateend YYYYMMDD() end date of the datasetdateprod YYYYMMDD production date of the dataset
() For dt data as the dates in the file names are rounded the user wanting data for date T has to read the filescontaining dates T+1 and T-1 in their name and check inside the files if there are some data for date T
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VII DATA FORMAT
This chapter presents the data storage format used for MyOcean products
VII1 NetCdf
The products are stored using the NetCDF format NetCDF (network Common Data Form) is an interface for array-oriented data access and a library that provides an implementation of the interface The netCDF library also definesa machine-independent format for representing scientific data Together the interface library and format support thecreation access and sharing of scientific data The netCDF software was developed at the Unidata Program Center inBoulder Colorado The netCDF libraries define a machine-independent format for representing scientific data Pleasesee Unidata NetCDF pages for more information and to retreive NetCDF software package onhttpwwwunidataucaredupackagesnetcdfindexhtml
NetCDF data is
bull Self-Describing A netCDF file includes information about the data it contains
bull Architecture-independent A netCDF file is represented in a form that can be accessed by computers with dif-ferent ways of storing integers characters and floating-point numbers
bull Direct-access A small subset of a large dataset may be accessed efficiently without first reading through allthe preceding data
bull Appendable Data can be appended to a netCDF dataset along one dimension without copying the dataset orredefining its structure The structure of a netCDF dataset can be changed though this sometimes causes thedataset to be copied
bull Sharable One writer and multiple readers may simultaneously access the same netCDF file
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VII2 Structure and semantic of NetCDF along-track files
The NetCDF Sea Level TAC files are based on the attribute data tags defined by the Cooperative OceanAtmosphereResearch Data Service (COARDS) and Climate and Forecast (CF) metadata conventions The CF convention gener-alises and extends the COARDS convention but relaxes the COARDS constraints on dimension and order and specifiesmethods for reducing the size of datasetsA wide range of software are available to write or read NetCDFCF files API are made available by UNIDATA(httpwwwunidataucaredusoftwarenetcdf)
bull CC++Fortran
bull Java
bull MATLAB Objective-C Perl Python R Ruby TclTk
In addition to these conventions the files are using a common structure and semantic
bull 1 dimension is defined
ndash time it is used to check NetCDF variables depending on time
bull 8 variables are defined
ndash short SLA contains the Sea Level Anomaly values for each time given
ndash int longitude contains the longitude for each measurement
ndash short track contains the track number for each measurement
ndash double time contains the time in days since 1950-01-01 000000 UTC for each measurement
ndash short mean_profile_point_index index of the corrsponding point in the track of the mean profile
ndash byte flag flag=0 the processed data comes from OGDR if flag=1 the processed data comes from theIGDR
ndash int latitude contains the latitude for each measurement
ndash short cycle contains the cycle number for each measurement
bull global attributes
ndash the global attributes gives information about the creation of the file
Example of a NetCDF sla file
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netcdf nrt_global_j1_sla_vfec_20101230_20101230_20101230 dimensions
time = 10385 variables
short SLA(time) SLAcoordinates = longitude latitude SLAlong_name = Sea Level Anomaly SLA_FillValue = 32767s SLAadd_offset = 0 SLAscale_factor = 0001 SLAunits = m SLAstandard_name = sea_surface_height_above_sea_level
int longitude(time) longitudelong_name = Longitude of measurement longitude_FillValue = 2147483647 longitudeadd_offset = 0 longitudestandard_name = longitude longitudescale_factor = 1e-06 longitudeunits = degrees_east
short track(time) tracklong_name = Track in cycle the measurement belongs to track_FillValue = 32767s trackunits = 1 trackcoordinates = longitude latitude
double time(time) timelong_name = Time of measurement time_FillValue = 184467440737096e+19 timeaxis = T timestandard_name = time timeunits = days since 1950-01-01 000000 UTC
int latitude(time) latitudelong_name = Latitude of measurement latitude_FillValue = 2147483647 latitudeadd_offset = 0 latitudestandard_name = latitude latitudescale_factor = 1e-06 latitudeunits = degrees_north
short flag(time) flagcoordinates = longitude latitude flag_FillValue = 3267s flaglong_name = data origin flagflag_values = 1s 0s flagflag_meanings = igdr_like non_igdr_like flagcomment = The origin of the data is determined by the types of geophysical datarecords (GDR) used in computation of the SLA 1 for the Interim GDR (IGDR) and0 for Operational GDR (OGDR)
short cycle(time) cyclelong_name = Cycle the measurement belongs to cycle_FillValue = 32767s cycleunits = 1 cyclecoordinates = longitude latitude
global attributeshistory = 22-Feb-2011 155243 CET File created by the SSLATODUACS system version 1001 comment = Produce from ENVISAT Extension Phase satellite altimetry data institution = CLSCNES
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references = httpwwwavisooceanobscomfileadmindocumentsdatatoolshdbk_duacspdf source = satellite altimetry title = along track Sea Level Anomaly Conventions = CF-14
dataSLA =
7 7 11 10 -2 -22 -39 -41 -30 -13 -3 -5 -16 -26 -32 -35-35 -35 -37 -35 -31 -29 -31 -35 -32 -21 -10 -10 -19 -20 -1-69 -57 -49 -45 -39 -30 -28 -31 -27 -13 -2 -5 -15 -3 1112 3 -7 -10 -14 -15 -22 -31 -37 -32 -17 -10
longitude =74743328 74868400 74993968 75120040 75246616 7537372875501368 75629568 75758320 75887656 76017568 76148080 7627920876388952 76477056 76565456 76654144 76743128 76832400 76921984329429568 329535424 329641792 329748672 329856096 329964032330072512 330181536 330291072 330401184
track =92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 9292 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92113 113 113 113 113 113 113 113 113 113 113 113 113 113113 113 113 113 113 113 113 113 113
time =222780000565705 222780001314719 222780002063733222780002812747 222780003561761 222780004310775 222780005059788222780005808802 222780006557816 22278000730683 222780008055844222780008804858 222780009553872 22278001017805 222780010677393222788257112198 222788257486705 222788257861212 222788258235719222788258610226 222788258984733 222788259359239 222788259733746222788260108253 22278826048276
mean_profile_point_index =1872 1878 1884 1890 1896 1902 1908 19141920 1926 1932 1938 1944 1949 1953 1957 1961 1965 1969 19732306 2309 2312 2315 2318 2321 2327 2330 2333 2336 2339 23422345 2348 2351 2354 2357 2360 2363 2366
flag =0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
latitude =-16225506 -16539731 -16853833 -17167810 -17481660 -17795380-18108966 -18422418 -18735729 -19048899 -19361924 -19674801-19987527 -20248015 -20456329 -20664569 -20872739 -2108083739481297 39628277 39775133 39921866 40068472 40214953 4036130840507533 40653629 40799592 40945423 41091120 41236684 41382111
cycle =331 331 331 331 331 331 331 331 331 331 331 331 331
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331 331 331 331 331 331 331 331 331 331 331 331 331 331331 331 331 331 331 331 331 331 331 331 331 331
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VIII HOW TO DOWNLOAD A PRODUCT
VIII1 Download a product through the MyOcean Web Portal DirectgetfileService
You first need to register Please find below the registration stepshttpwwwmyoceaneuweb34-products-and-services-faqphp1Once registered the MyOcean FAQ httpwwwmyoceaneuweb34-products-and-services-faqwill guide you on How to download a product through the MyOcean Web Portal Directgetfile Service
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IX NEWS AND UPDATES
IX1 [Duacs] Operational news
To be kept informed on events occurring on the satellites and on the eventual interruption of the services of the DUACSprocessing system see the [Duacs] operational news on the Aviso websitehttpwwwavisooceanobscomendataoperational-newsindexhtml
IX2 Updates
To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtmlSince 2010 a complete reprocessing of all altimetry data (cumulated total of about 55 years of data) is available Themain changes introduced in the Duacs DT v300 reprocessed data set in SSALTODUACS reprocessed DT data setare listed herehttpwwwavisooceanobscomfileadmindocumentsdataduacsduacs_DT_2010_reprocessing_impactpdf
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III27 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III271 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
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III272 Performance indicators
To appreciate the quality situation of the DUACS system new performance indicators are computed dailyThey aim at evaluate the status of the main processing steps of the system the input data availability theinput data coverage the input data quality and the output product quality These indicators are computed foreach and every currently working satellite and combined to obtain the overall status
Figure 8 Example with the key performance indicator on 20090627
See the description the latest and previous indicators on Aviso websitehttpwwwavisooceanobscomindexphpid=1516
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III3 Delayed Time processing steps
III31 Input data models and corrections applied
Delayed Time MyOcean products are generated
bull from Aviso GDR products for TP Jason-1 Jason-2 and Envisat (GDR-A cycles 1 to 22 GDR-Bcycles 23 to 85 GDR-C from cycle 86)
bull from NOAA GDR for GFO and from CERSAT (IFREMER) OPR for ERS-1 and ERS-2 (phases C(1st 35-day repeat orbit period) phase E and F (geodetic phases) phase G for ERS-1 (last 35-dayrepeat orbit period tandem phase with ERS-2 phase A for ERS-2 (1st 35-day repeat orbit periodtandem phase with ERS-1))
All GDR products are computed with a Precise Orbit Ephemeris (POE) and are delivered within 2 to 3months depending on the mission For several missions an updated orbit is used
bull For ERS-1amp-2 the orbit used is DGME-04 provided by Delft Institute (httpwwwdeostudelftnl)until June 2003
bull For TopexPoseidon the orbit used is GSFC (std0809) for the whole mission
bull For Envisat CNES POE of GDR-C standard is used for the whole mission
bull For the whole GFO mission the orbit used is GSFC (std0809) and when not available NASA POE isused
Altimetric product Source Availability Type of orbit
TopexPoseidon GDR NASACNES - GSFC POE
Jason-1 GDR (GDR-C) CNESNASA ~40 days CNES POE
Jason-2 GDR (GDR-C) CNESNASA ~60 days CNES POE
GFO GDR NOAA - GSFCNASA POE
ERS-1amp2 IFREMERESA - DGME-04
Envisat (GDR-A GDR-B andGDR-C from cycle 86)
ESA ~2 months CNES POE
Table 5 SSALTODUACS Delayed Time Input data overview
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DU
AC
S20
11D
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Prod
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stan
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ref
GD
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GD
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les
1to
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GD
R-B
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Dry
trop
o-sp
here
Mod
elco
mpu
ted
from
EC
MW
FG
auss
ian
grid
s(n
ewS1
and
S2at
mos
pher
ictid
esar
eap
plie
d)
Mod
elco
mpu
ted
from
EC
MW
Fre
ctan
gula
rgri
ds(n
ewS1
and
S2at
mos
pher
ictid
esar
ein
clud
ed)
Wet
trop
o-sp
here
JMR
AM
Rra
diom
eter
furt
hert
han
50km
from
the
coas
tsF
rom
EC
MW
Fm
odel
ford
ista
nces
betw
een
10an
d50
km
TM
Rra
diom
eter
(Sch
aroo
etal
20
04[4
9])
MW
RC
orre
ctio
nof
the
drif
ton
the
236
GH
zbr
ight
ness
tem
pera
ture
(Sch
arro
oet
al
2004
[49]
)Neu
ral
Net
wor
kal
gori
thm
(Tra
nan
dO
blig
is
2003
[50]
MW
Rra
diom
eter
furt
hert
han
50km
from
the
coas
tsan
dco
rrec
ted
from
side
lobe
s(f
rom
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e41
)E
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WF
mod
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and
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OG
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ion
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edw
ithE
CM
WF
pres
sure
and
win
gfie
lds
(S1
and
S2w
ere
excl
uded
)+in
vers
eba
rom
eter
com
pute
dfr
omre
ctan
gula
rgri
ds
Tabl
e6
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(1
2)
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
j2j1
j1n
tptp
ne1
e2en
enn
g2O
cean
tide
GO
T4v
7(S
1an
dS2
are
incl
uded
)Po
letid
e[W
ahr
1985
[53]
]So
lidea
rth
tide
Ela
stic
resp
onse
totid
alpo
tent
ial[
Car
twri
ghta
ndTa
yler
197
1[5]
][C
artw
righ
tand
Edd
en1
973[
6]]
Loa
ding
tide
GO
T4v
7(S
1pa
ram
eter
isin
clud
ed)
Sea
stat
ebi
asN
onpa
ram
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cSS
B[G
aspa
reta
l20
02[2
0]]
Non
para
met
ric
SSB
[NT
ran
and
al2
010[
51]]
BM
3[G
aspa
ran
dO
gor
1994
[17]
]
Non
para
met
ric
SSB
[Mer
tzet
al
2005
[38]
]
Non
para
met
ric
SSB
[Gas
pare
tal
2002
]w
ithG
DR
-Bst
anda
rds
forc
ycle
s9
to85
and
with
GD
R-C
stan
dard
sfr
omcy
cle
86
Non
para
met
ric
SSB
[NT
ran
etal
20
10[5
1]]
Orb
iter
ror
Glo
bal m
ulti-
mis
sion
cros
sove
rmin
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n(L
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and
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2])
Lon
gw
ave-
leng
her
rors
Opt
imal
Inte
rpol
atio
n(L
eTr
aon
etal
19
98[3
1])
Inte
rcal
ibra
tion
Ref
eren
cefr
omcy
cle
11R
efer
ence
from
cycl
e1
to35
4C
orre
ctio
nof
regi
onal
bias
J2J
1de
duce
dfr
omin
terc
alib
ratio
nph
ase
(cyc
le11
J2)
Cor
rect
ion
ofgl
obal
biai
sJ1
TP
deacutedu
ced
from
inte
rcal
ibra
tion
phas
e(c
ycle
s11
J1)
Mea
npr
o-fil
e(s
eeII
I36
1)
Com
pute
dw
ithcy
cles
11-3
53T
Pda
taan
dw
ithcy
cles
11-2
50J1
data
ref
eren
ced
[199
319
99]
TP
J1 c
ompu
ted
with
cycl
es11
-353
TP
data
and
with
cycl
es11
-250
J1da
tar
efer
ence
d[1
993
1999
]T
PNJ
1Nc
ompu
ted
with
cycl
es36
9-47
9T
PNda
tar
efer
ence
d[1
993
1999
]
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
ref
eren
ced
[199
319
99]
EN
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
re
fere
nced
[199
319
99]
EN
Nu
seof
MSS
_CN
ES_
CL
S11
[39]
Com
pute
dw
ithcy
cles
37-1
87G
2da
ta
refe
renc
ed[1
993
1999
]
Peri
odof
use
from
cycl
e9
from
cycl
e9
cycl
es1
to48
1cy
cles
15to
43In
clud
ing
E-F
geod
etic
phas
es
cycl
es1
to83
from
cycl
e9
cycl
es37
to22
2
Tabl
e7
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(2
2)
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III32 Acquisition
The acqusition process in Delayed time is much simpler than in Near Real time it consists in a synchronisa-tion process of all the auxiliary data required to homogenize propely the altimeter data sets The acquisitionstep uses the GDRs or the OPRs provided by the agencies
III33 Homogenization
The Homogenization process consists in applying the most recent corrections models and references rec-ommended for altimeter products Each mission is processed separately as its needs depend on the baseinput data The list of corrections and models currently applied is provided in tables 6 and 7 for DT data
III34 Input data quality control
The Input Data Quality Control is a critical process applied to guarantee that DUACS uses only the mostaccurate altimeter data Thanks to the high quality of current missions this process rejects a small percent-age of altimeter measurements but these erroneous data could be the cause of a significant quality lossThe quality control relies on standard raw data editing with quality flags or parameter thresholds but alsoon complex data editing algorithms based on the detection of erroneous artefacts mono and multi-missioncrossover validation and macroscopic statistics to edit out large data flows that do not meet the systemrsquosrequirements
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III35 Multi-mission cross-calibration
The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistentand accurate information It removes any residual orbit error (OE Le Traon and Ogor 1998[32]) or longwavelength error (LWE Le Traon et al 1998[31]) as well as large scale biases and discrepancies betweenvarious data flows
This process is based on two very different algorithms a global multi-mission crossover minimization fororbit error reduction (OER) and Optimal Interpolation (OI) for LWE
Multi-satellite crossover determination is performed on a daily basis All altimeter fields (measurementcorrections and other fields such as bathymetry MSS) are interpolated at crossover locations and datesCrossovers are then appended to the existing crossover database as more altimeter data become availableThis crossover data set is the input of the Orbit Error Reduction (OER) method Using the precision of thereference mission orbit a very accurate orbit error can be estimated LWE is mostly due to residual tidalor inverse barometer errors and high frequency ocean signals The OI used for LWE reduction uses preciseparameters derived from
bull accurate statistical description of sea level variability
bull localized correlation scales
bull mission-specific noise and precise assumptions on the long wavelength errors to be removed (from arecent analysis of one year of data from each mission)
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III36 Product generation
The product generation process is composed of four steps computation of raw SLA cross-validationfilteringampsub-sampling and generation of by-products
III361 Computation of raw SLA
Since the geoid is not well known yet the SSH cannot be used directly the SSH anomalies are used insteadThey are computed from the difference of the instantaneous SSH - a temporal reference This temporalreference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeattrack analysis cannot be used The errors affecting the SLAs MPs and MSS have different magnitudes andwavelengths The computation of the SLAs and their errors associated are detailed in Dibarboure et al 2010[9]
Use of a Mean ProfileIn the repeat track analysis (when the satellites flies over a repetitive orbit) measurements are re-sampledalong a theoretical ground track (or mean track) associated to each mission Then a Mean Profile (MP) issubtracted from the re-sampled data to obtain SLA The MP is a time average of similarly re-sampled dataover a long period
bull The Mean Profile used for TP (cycles 1 to 364) Jason-1 (cycles 1 to 259) and Jason-2 is computedwith 10 years of TP (cycles 11 to 353) and 6 years of Jason-1 (cycles 11 to 250)
bull The Mean Profile used for TP (cycles 368 to 481) and from Jason-1 cycle 262 to 374 (where satellitesare on interleaved ground-tracks) is computed with 3 years of TP (cycles 369 to 479)
bull The Mean Profile used for ERS-1 in its 35 days repetitive orbit mission ERS-2 and Envisat (only forthe first orbit before November 2010) is computed with 8 years of ERS-2 (cycles 1 to 85) and 6 yearsof Envisat (cycles 10 to 72)
bull No Mean Profile can be used for Envisat on its new orbit (enn) Jason-1 on its geodetic orbit (j1g)because there is no repetitive track The MSS must be used instead (see below)
bull The Mean Profile used for GFO is computed with 7 years of GFO cycles 37 to 187
Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible
bull Indeed as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide precise cross-track projection andor interpolation schemes are required to avoid errors
bull The mesoscale variability error (which is lt35 cm for MP between 3 to 5 years and lt1cm for WLof 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a prioriknowledge from Sea Level maps derived from previous iterations or from other missions
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bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for ERS-1 for its 168 days geodetic mission (phases E-F from April1994 to March 1995) or for Envisat since november 2010 because the satellite is not in a repetitive orbitphase The alternative is to use the MSS instead The gridded MSS is derived from along track MPs anddata from geodetic phases Thus any error on the MP is also contained in the MSS There are essentially 4types of additional errors on gridded MSS which are hard to quantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
III362 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III363 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
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III37 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III371 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
IV MYOCEAN PRODUCTS
IV1 Near Real Time Products
The purpose of the NRT DUACS component is the acquisition of altimeter data from various altimeter mis-sions in near-real time (ie within a few days at most) the validation and correction of these altimeter datasets (ie edition and selection update of corrections and homogenization orbit error reduction) in order toproduce each day along-track productsProducts are as follows
Along-track products global and regional (Mediterranean and Black Seas Arctic Ocean and Europeareas)
bull Sea Level Anomaly (NRT-SLA) for each mission with NRT-SLA ephemeris
IV11 Delay of the products
The availability of the products in near real time is three to twelve hours after the measurement for along-track products Those products are delivered every day
IV12 Temporal availibility
The following table presents the available products by mission and by data periodNear real time products
NRT Jason-2 Jason-1 and Jason-1geodetic
Envisat new Cryosat-2
Temporal Time availability ymlowast
ongoingymlowast-20120303 for
repeat track and20120507-ongoing for
geodetic track
ymlowast
2012040820120101
ongoing
NRT-SLA X X X X
lowastym the temporal coverage for NRT products is fluctuating and depends on updates of Delayed Time prod-ucts When DT products are updated (3 to 4 times per year) the oldest NRT products are replaced by thebetter quality DT products so that the 2 series are overlapping on few weeks or few months
IV2 Delayed Time Products
The Delayed Time component of SSALTODUACS system is responsible for the production of processedJason-1 Jason-2 TP Envisat GFO ERS12 and even Geosat data in order to provide a homogeneousinter-calibrated and highly accurate long time series of SLA DT products are more precise than NRT products Two reasons explain this quality difference The firstone is the better intrinsic quality of the POE orbit used in the GDR processing The second reason is that
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in the DT DUACS processing the products can be computed optimally with a centred computation timewindow for OER LWE On the contrary in NRT case future data are not available so the computationtime window is not centred and therefore not optimalAs for NRT products improved altimeter corrections and processing algorithms are used ocean tide modelto correct altimeter data improved methods for orbit error reduction and mapping
Along-Track products global and regional (Mediterranean and Black Seas)
bull Sea Level Anomaly (DT-SLA) for each mission
IV21 Delay of the products
Weekly products are delivered The availability of the products in delayed time is at the best two monthsafter the date of the measurement The product generation needs all the GDR data of all the missions to takeinto account the best corrections as possible The time delay can be longer in the case of a missing mission
IV22 Temporal availibility
The following table presents the available products by mission and by data periodDelayed time SSALTODUACS products
Upd Jason-2 Jason-1new6
Jason-1 GFO Envisatnew6
Envisat ERS-16
ERS-2Topexnew6
Topex
TemporalTimeavailabil-ity
200810ymlowast
200902ymlowast
200204200810
200001200809
201010ymlowast
200210201010
199210200304
200209200510
199209200204
DT-SLA X X X X X X X X X
lowast ym those dates are updated regularly (3 to 4 times per year) and are avalaible when you download thedata at httpwwwmyoceaneuweb24-cataloguephp6 Jason-1 new orbit starting 200809 Envisat new orbit starting 201010 TP new orbit starting 200209 ERS-1The geodetic phases (E-F) are included There are no ERS-1 data between December 23 1993 and April 10 1994(ERS-1 phase D - 2nd ice phase) Note that during that time products are based only on TopexPoseidon data
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V DESCRIPTION OF THE PRODUCT SPECIFICATION
V1 General information
Product Specification SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001
Geographical coverage global
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 20-50km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001 Product Specification
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Product Specification SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002
Geographical coverage 55˚W-35˚E 30˚N-46˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002 Product Specification
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Product Specification SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003
Geographical coverage 27˚E-42˚E 40˚N-47˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003 Product Specification
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Product Specification SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004
Geographical coverage 25˚W-42˚E 21˚N-66˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004 Product Specification
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Product Specification SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005
Geographical coverage 0˚W-360˚E 50˚N-82˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005 Product Specification
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VI NOMENCLATURE OF FILES
VI1 Nomenclature of files downloaded through the MyOcean Web PortalDirectgetfile Service
VI11 Nomenclature of the product line
The description of the syntax for the SL TAC SLA products line is given by
SEALEVEL_ltREGIONgt_SLA_L3_ltDELAYgt_OBSERVATIONS_008_ltZONEgt_ltLETTERgtwhere
REGION GLO global geographic coverage product
BS Black Sea products
MED Mediterranean products
ARC Arctic products (for NRT products)
EUROPE Europe products (for NRT products)
DELAY NRT near real time products
RAN delayed time or reanalysis products
ZONE 001 number on 3 digits
002
003
004
LETTER a letter on 1 digit
b
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VI12 Nomenclature of the datasets
The nomenclature used is
dataset-duacs-ltdelaygt-ltzonegt-ltmissiongt-lttype of slagt-l3where the fileds in ltgt are described below
delay nrt near-real time productsran delayed time products
zone global global geographic coverage productmedsea Mediterranean productsblacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1 (only for ran)e2 ERS-2 (only for ran)tp TOPEXPoseidon (only for ran)tpn TOPEXPoseidon on its new orbit (only for
ran)g2 GFO (only for ran)j1 Jason-1 (only for ran)j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisat (only for ran)enn Envisat on its new orbitc2 Cryosat-2 (only for nrt)
type of sla sla filtered slasla_unfiltered non filtered sla (only for ran products)
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VI13 Nomenclature of the NetCdf files
The nomenclature used is
ltdelaygt_ltzonegt_ltmissiongt_sla_ltvariablegt_ltdatebegingt_ltdateendgt_ltdateprodgtnc where the fileds in ltgt are de-scribed below
delay nrt near-real time productsdt delayed time products
zone global global geographic coverage productmed Mediterranean products (for dt)mfstep Mediterranean products (for nrt)blacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1e2 ERS-2tp TOPEXPoseidontpn TOPEXPoseidon on its new orbitg2 GFOj1 Jason-1j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisatenn Envisat on its new orbitc2 Cryosat-2
variable vfec filtered and sub-sampled slavxxc non filtered and non sub-sampled sla (only
for dt)datebegin YYYYMMDD() beginning date of the datasetdateend YYYYMMDD() end date of the datasetdateprod YYYYMMDD production date of the dataset
() For dt data as the dates in the file names are rounded the user wanting data for date T has to read the filescontaining dates T+1 and T-1 in their name and check inside the files if there are some data for date T
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VII DATA FORMAT
This chapter presents the data storage format used for MyOcean products
VII1 NetCdf
The products are stored using the NetCDF format NetCDF (network Common Data Form) is an interface for array-oriented data access and a library that provides an implementation of the interface The netCDF library also definesa machine-independent format for representing scientific data Together the interface library and format support thecreation access and sharing of scientific data The netCDF software was developed at the Unidata Program Center inBoulder Colorado The netCDF libraries define a machine-independent format for representing scientific data Pleasesee Unidata NetCDF pages for more information and to retreive NetCDF software package onhttpwwwunidataucaredupackagesnetcdfindexhtml
NetCDF data is
bull Self-Describing A netCDF file includes information about the data it contains
bull Architecture-independent A netCDF file is represented in a form that can be accessed by computers with dif-ferent ways of storing integers characters and floating-point numbers
bull Direct-access A small subset of a large dataset may be accessed efficiently without first reading through allthe preceding data
bull Appendable Data can be appended to a netCDF dataset along one dimension without copying the dataset orredefining its structure The structure of a netCDF dataset can be changed though this sometimes causes thedataset to be copied
bull Sharable One writer and multiple readers may simultaneously access the same netCDF file
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VII2 Structure and semantic of NetCDF along-track files
The NetCDF Sea Level TAC files are based on the attribute data tags defined by the Cooperative OceanAtmosphereResearch Data Service (COARDS) and Climate and Forecast (CF) metadata conventions The CF convention gener-alises and extends the COARDS convention but relaxes the COARDS constraints on dimension and order and specifiesmethods for reducing the size of datasetsA wide range of software are available to write or read NetCDFCF files API are made available by UNIDATA(httpwwwunidataucaredusoftwarenetcdf)
bull CC++Fortran
bull Java
bull MATLAB Objective-C Perl Python R Ruby TclTk
In addition to these conventions the files are using a common structure and semantic
bull 1 dimension is defined
ndash time it is used to check NetCDF variables depending on time
bull 8 variables are defined
ndash short SLA contains the Sea Level Anomaly values for each time given
ndash int longitude contains the longitude for each measurement
ndash short track contains the track number for each measurement
ndash double time contains the time in days since 1950-01-01 000000 UTC for each measurement
ndash short mean_profile_point_index index of the corrsponding point in the track of the mean profile
ndash byte flag flag=0 the processed data comes from OGDR if flag=1 the processed data comes from theIGDR
ndash int latitude contains the latitude for each measurement
ndash short cycle contains the cycle number for each measurement
bull global attributes
ndash the global attributes gives information about the creation of the file
Example of a NetCDF sla file
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netcdf nrt_global_j1_sla_vfec_20101230_20101230_20101230 dimensions
time = 10385 variables
short SLA(time) SLAcoordinates = longitude latitude SLAlong_name = Sea Level Anomaly SLA_FillValue = 32767s SLAadd_offset = 0 SLAscale_factor = 0001 SLAunits = m SLAstandard_name = sea_surface_height_above_sea_level
int longitude(time) longitudelong_name = Longitude of measurement longitude_FillValue = 2147483647 longitudeadd_offset = 0 longitudestandard_name = longitude longitudescale_factor = 1e-06 longitudeunits = degrees_east
short track(time) tracklong_name = Track in cycle the measurement belongs to track_FillValue = 32767s trackunits = 1 trackcoordinates = longitude latitude
double time(time) timelong_name = Time of measurement time_FillValue = 184467440737096e+19 timeaxis = T timestandard_name = time timeunits = days since 1950-01-01 000000 UTC
int latitude(time) latitudelong_name = Latitude of measurement latitude_FillValue = 2147483647 latitudeadd_offset = 0 latitudestandard_name = latitude latitudescale_factor = 1e-06 latitudeunits = degrees_north
short flag(time) flagcoordinates = longitude latitude flag_FillValue = 3267s flaglong_name = data origin flagflag_values = 1s 0s flagflag_meanings = igdr_like non_igdr_like flagcomment = The origin of the data is determined by the types of geophysical datarecords (GDR) used in computation of the SLA 1 for the Interim GDR (IGDR) and0 for Operational GDR (OGDR)
short cycle(time) cyclelong_name = Cycle the measurement belongs to cycle_FillValue = 32767s cycleunits = 1 cyclecoordinates = longitude latitude
global attributeshistory = 22-Feb-2011 155243 CET File created by the SSLATODUACS system version 1001 comment = Produce from ENVISAT Extension Phase satellite altimetry data institution = CLSCNES
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references = httpwwwavisooceanobscomfileadmindocumentsdatatoolshdbk_duacspdf source = satellite altimetry title = along track Sea Level Anomaly Conventions = CF-14
dataSLA =
7 7 11 10 -2 -22 -39 -41 -30 -13 -3 -5 -16 -26 -32 -35-35 -35 -37 -35 -31 -29 -31 -35 -32 -21 -10 -10 -19 -20 -1-69 -57 -49 -45 -39 -30 -28 -31 -27 -13 -2 -5 -15 -3 1112 3 -7 -10 -14 -15 -22 -31 -37 -32 -17 -10
longitude =74743328 74868400 74993968 75120040 75246616 7537372875501368 75629568 75758320 75887656 76017568 76148080 7627920876388952 76477056 76565456 76654144 76743128 76832400 76921984329429568 329535424 329641792 329748672 329856096 329964032330072512 330181536 330291072 330401184
track =92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 9292 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92113 113 113 113 113 113 113 113 113 113 113 113 113 113113 113 113 113 113 113 113 113 113
time =222780000565705 222780001314719 222780002063733222780002812747 222780003561761 222780004310775 222780005059788222780005808802 222780006557816 22278000730683 222780008055844222780008804858 222780009553872 22278001017805 222780010677393222788257112198 222788257486705 222788257861212 222788258235719222788258610226 222788258984733 222788259359239 222788259733746222788260108253 22278826048276
mean_profile_point_index =1872 1878 1884 1890 1896 1902 1908 19141920 1926 1932 1938 1944 1949 1953 1957 1961 1965 1969 19732306 2309 2312 2315 2318 2321 2327 2330 2333 2336 2339 23422345 2348 2351 2354 2357 2360 2363 2366
flag =0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
latitude =-16225506 -16539731 -16853833 -17167810 -17481660 -17795380-18108966 -18422418 -18735729 -19048899 -19361924 -19674801-19987527 -20248015 -20456329 -20664569 -20872739 -2108083739481297 39628277 39775133 39921866 40068472 40214953 4036130840507533 40653629 40799592 40945423 41091120 41236684 41382111
cycle =331 331 331 331 331 331 331 331 331 331 331 331 331
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331 331 331 331 331 331 331 331 331 331 331 331 331 331331 331 331 331 331 331 331 331 331 331 331 331
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VIII HOW TO DOWNLOAD A PRODUCT
VIII1 Download a product through the MyOcean Web Portal DirectgetfileService
You first need to register Please find below the registration stepshttpwwwmyoceaneuweb34-products-and-services-faqphp1Once registered the MyOcean FAQ httpwwwmyoceaneuweb34-products-and-services-faqwill guide you on How to download a product through the MyOcean Web Portal Directgetfile Service
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IX NEWS AND UPDATES
IX1 [Duacs] Operational news
To be kept informed on events occurring on the satellites and on the eventual interruption of the services of the DUACSprocessing system see the [Duacs] operational news on the Aviso websitehttpwwwavisooceanobscomendataoperational-newsindexhtml
IX2 Updates
To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtmlSince 2010 a complete reprocessing of all altimetry data (cumulated total of about 55 years of data) is available Themain changes introduced in the Duacs DT v300 reprocessed data set in SSALTODUACS reprocessed DT data setare listed herehttpwwwavisooceanobscomfileadmindocumentsdataduacsduacs_DT_2010_reprocessing_impactpdf
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III272 Performance indicators
To appreciate the quality situation of the DUACS system new performance indicators are computed dailyThey aim at evaluate the status of the main processing steps of the system the input data availability theinput data coverage the input data quality and the output product quality These indicators are computed foreach and every currently working satellite and combined to obtain the overall status
Figure 8 Example with the key performance indicator on 20090627
See the description the latest and previous indicators on Aviso websitehttpwwwavisooceanobscomindexphpid=1516
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III3 Delayed Time processing steps
III31 Input data models and corrections applied
Delayed Time MyOcean products are generated
bull from Aviso GDR products for TP Jason-1 Jason-2 and Envisat (GDR-A cycles 1 to 22 GDR-Bcycles 23 to 85 GDR-C from cycle 86)
bull from NOAA GDR for GFO and from CERSAT (IFREMER) OPR for ERS-1 and ERS-2 (phases C(1st 35-day repeat orbit period) phase E and F (geodetic phases) phase G for ERS-1 (last 35-dayrepeat orbit period tandem phase with ERS-2 phase A for ERS-2 (1st 35-day repeat orbit periodtandem phase with ERS-1))
All GDR products are computed with a Precise Orbit Ephemeris (POE) and are delivered within 2 to 3months depending on the mission For several missions an updated orbit is used
bull For ERS-1amp-2 the orbit used is DGME-04 provided by Delft Institute (httpwwwdeostudelftnl)until June 2003
bull For TopexPoseidon the orbit used is GSFC (std0809) for the whole mission
bull For Envisat CNES POE of GDR-C standard is used for the whole mission
bull For the whole GFO mission the orbit used is GSFC (std0809) and when not available NASA POE isused
Altimetric product Source Availability Type of orbit
TopexPoseidon GDR NASACNES - GSFC POE
Jason-1 GDR (GDR-C) CNESNASA ~40 days CNES POE
Jason-2 GDR (GDR-C) CNESNASA ~60 days CNES POE
GFO GDR NOAA - GSFCNASA POE
ERS-1amp2 IFREMERESA - DGME-04
Envisat (GDR-A GDR-B andGDR-C from cycle 86)
ESA ~2 months CNES POE
Table 5 SSALTODUACS Delayed Time Input data overview
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DU
AC
S20
11D
Tpr
oduc
t(gtV
30
0)j2
j1j1
ntp
tpn
e1e2
ene
nng2
Prod
uct
stan
dard
ref
GD
R-C
OPR
GD
R-A
(Cyc
les
1to
22)
GD
R-B
(cyc
les
23-8
5)
GD
R(N
OA
A)
Orb
itC
nes
POE
GSF
C(I
TR
F20
05G
RA
CE
last
stan
dard
s)
DG
ME
-04
(Sch
arro
oan
dV
isse
r19
98[4
8]C
NE
SPO
E(G
DR
-1st
anda
rds
forc
ycle
s9
to22
GD
R-C
stan
dard
sfr
omcy
cle
23)
GSF
C(I
TR
F20
05
GR
AC
Ela
stst
anda
rds
Iono
pher
icD
ual f
requ
ency
altim
eter
rang
em
easu
rem
ents
Dua
l fre
quen
cyal
timet
erra
nge
mea
sure
men
ts(T
opex
)D
OR
IS(P
OSE
IDO
N)
Ben
t mod
elB
ent m
odel
(cyc
les
1-36
)G
IMm
odem
from
cycl
e37
((Ii
jima
etal
19
98[2
4])
Dua
l-fr
eque
ncy
altim
eter
rang
em
easu
rem
ent(
cycl
e9-
64)a
ndG
IMm
odel
gtcyc
le65
(Iiji
ma
etal
19
99[2
4])c
orre
cted
from
8m
mbi
as
From
GIM
mod
el(I
ijim
aet
al1
998
[24]
)
Dry
trop
o-sp
here
Mod
elco
mpu
ted
from
EC
MW
FG
auss
ian
grid
s(n
ewS1
and
S2at
mos
pher
ictid
esar
eap
plie
d)
Mod
elco
mpu
ted
from
EC
MW
Fre
ctan
gula
rgri
ds(n
ewS1
and
S2at
mos
pher
ictid
esar
ein
clud
ed)
Wet
trop
o-sp
here
JMR
AM
Rra
diom
eter
furt
hert
han
50km
from
the
coas
tsF
rom
EC
MW
Fm
odel
ford
ista
nces
betw
een
10an
d50
km
TM
Rra
diom
eter
(Sch
aroo
etal
20
04[4
9])
MW
RC
orre
ctio
nof
the
drif
ton
the
236
GH
zbr
ight
ness
tem
pera
ture
(Sch
arro
oet
al
2004
[49]
)Neu
ral
Net
wor
kal
gori
thm
(Tra
nan
dO
blig
is
2003
[50]
MW
Rra
diom
eter
furt
hert
han
50km
from
the
coas
tsan
dco
rrec
ted
from
side
lobe
s(f
rom
cycl
e41
)E
CM
WF
mod
elfo
rdis
tanc
esbe
twee
n10
and
50km
GFO
radi
omet
er
DA
CM
OG
2DH
igh
Res
olut
ion
forc
edw
ithE
CM
WF
pres
sure
and
win
gfie
lds
(S1
and
S2w
ere
excl
uded
)+in
vers
eba
rom
eter
com
pute
dfr
omre
ctan
gula
rgri
ds
Tabl
e6
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(1
2)
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j2j1
j1n
tptp
ne1
e2en
enn
g2O
cean
tide
GO
T4v
7(S
1an
dS2
are
incl
uded
)Po
letid
e[W
ahr
1985
[53]
]So
lidea
rth
tide
Ela
stic
resp
onse
totid
alpo
tent
ial[
Car
twri
ghta
ndTa
yler
197
1[5]
][C
artw
righ
tand
Edd
en1
973[
6]]
Loa
ding
tide
GO
T4v
7(S
1pa
ram
eter
isin
clud
ed)
Sea
stat
ebi
asN
onpa
ram
etri
cSS
B[G
aspa
reta
l20
02[2
0]]
Non
para
met
ric
SSB
[NT
ran
and
al2
010[
51]]
BM
3[G
aspa
ran
dO
gor
1994
[17]
]
Non
para
met
ric
SSB
[Mer
tzet
al
2005
[38]
]
Non
para
met
ric
SSB
[Gas
pare
tal
2002
]w
ithG
DR
-Bst
anda
rds
forc
ycle
s9
to85
and
with
GD
R-C
stan
dard
sfr
omcy
cle
86
Non
para
met
ric
SSB
[NT
ran
etal
20
10[5
1]]
Orb
iter
ror
Glo
bal m
ulti-
mis
sion
cros
sove
rmin
imiz
atio
n(L
eTr
aon
and
Ogo
r19
98[3
2])
Lon
gw
ave-
leng
her
rors
Opt
imal
Inte
rpol
atio
n(L
eTr
aon
etal
19
98[3
1])
Inte
rcal
ibra
tion
Ref
eren
cefr
omcy
cle
11R
efer
ence
from
cycl
e1
to35
4C
orre
ctio
nof
regi
onal
bias
J2J
1de
duce
dfr
omin
terc
alib
ratio
nph
ase
(cyc
le11
J2)
Cor
rect
ion
ofgl
obal
biai
sJ1
TP
deacutedu
ced
from
inte
rcal
ibra
tion
phas
e(c
ycle
s11
J1)
Mea
npr
o-fil
e(s
eeII
I36
1)
Com
pute
dw
ithcy
cles
11-3
53T
Pda
taan
dw
ithcy
cles
11-2
50J1
data
ref
eren
ced
[199
319
99]
TP
J1 c
ompu
ted
with
cycl
es11
-353
TP
data
and
with
cycl
es11
-250
J1da
tar
efer
ence
d[1
993
1999
]T
PNJ
1Nc
ompu
ted
with
cycl
es36
9-47
9T
PNda
tar
efer
ence
d[1
993
1999
]
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
ref
eren
ced
[199
319
99]
EN
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
re
fere
nced
[199
319
99]
EN
Nu
seof
MSS
_CN
ES_
CL
S11
[39]
Com
pute
dw
ithcy
cles
37-1
87G
2da
ta
refe
renc
ed[1
993
1999
]
Peri
odof
use
from
cycl
e9
from
cycl
e9
cycl
es1
to48
1cy
cles
15to
43In
clud
ing
E-F
geod
etic
phas
es
cycl
es1
to83
from
cycl
e9
cycl
es37
to22
2
Tabl
e7
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(2
2)
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III32 Acquisition
The acqusition process in Delayed time is much simpler than in Near Real time it consists in a synchronisa-tion process of all the auxiliary data required to homogenize propely the altimeter data sets The acquisitionstep uses the GDRs or the OPRs provided by the agencies
III33 Homogenization
The Homogenization process consists in applying the most recent corrections models and references rec-ommended for altimeter products Each mission is processed separately as its needs depend on the baseinput data The list of corrections and models currently applied is provided in tables 6 and 7 for DT data
III34 Input data quality control
The Input Data Quality Control is a critical process applied to guarantee that DUACS uses only the mostaccurate altimeter data Thanks to the high quality of current missions this process rejects a small percent-age of altimeter measurements but these erroneous data could be the cause of a significant quality lossThe quality control relies on standard raw data editing with quality flags or parameter thresholds but alsoon complex data editing algorithms based on the detection of erroneous artefacts mono and multi-missioncrossover validation and macroscopic statistics to edit out large data flows that do not meet the systemrsquosrequirements
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III35 Multi-mission cross-calibration
The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistentand accurate information It removes any residual orbit error (OE Le Traon and Ogor 1998[32]) or longwavelength error (LWE Le Traon et al 1998[31]) as well as large scale biases and discrepancies betweenvarious data flows
This process is based on two very different algorithms a global multi-mission crossover minimization fororbit error reduction (OER) and Optimal Interpolation (OI) for LWE
Multi-satellite crossover determination is performed on a daily basis All altimeter fields (measurementcorrections and other fields such as bathymetry MSS) are interpolated at crossover locations and datesCrossovers are then appended to the existing crossover database as more altimeter data become availableThis crossover data set is the input of the Orbit Error Reduction (OER) method Using the precision of thereference mission orbit a very accurate orbit error can be estimated LWE is mostly due to residual tidalor inverse barometer errors and high frequency ocean signals The OI used for LWE reduction uses preciseparameters derived from
bull accurate statistical description of sea level variability
bull localized correlation scales
bull mission-specific noise and precise assumptions on the long wavelength errors to be removed (from arecent analysis of one year of data from each mission)
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III36 Product generation
The product generation process is composed of four steps computation of raw SLA cross-validationfilteringampsub-sampling and generation of by-products
III361 Computation of raw SLA
Since the geoid is not well known yet the SSH cannot be used directly the SSH anomalies are used insteadThey are computed from the difference of the instantaneous SSH - a temporal reference This temporalreference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeattrack analysis cannot be used The errors affecting the SLAs MPs and MSS have different magnitudes andwavelengths The computation of the SLAs and their errors associated are detailed in Dibarboure et al 2010[9]
Use of a Mean ProfileIn the repeat track analysis (when the satellites flies over a repetitive orbit) measurements are re-sampledalong a theoretical ground track (or mean track) associated to each mission Then a Mean Profile (MP) issubtracted from the re-sampled data to obtain SLA The MP is a time average of similarly re-sampled dataover a long period
bull The Mean Profile used for TP (cycles 1 to 364) Jason-1 (cycles 1 to 259) and Jason-2 is computedwith 10 years of TP (cycles 11 to 353) and 6 years of Jason-1 (cycles 11 to 250)
bull The Mean Profile used for TP (cycles 368 to 481) and from Jason-1 cycle 262 to 374 (where satellitesare on interleaved ground-tracks) is computed with 3 years of TP (cycles 369 to 479)
bull The Mean Profile used for ERS-1 in its 35 days repetitive orbit mission ERS-2 and Envisat (only forthe first orbit before November 2010) is computed with 8 years of ERS-2 (cycles 1 to 85) and 6 yearsof Envisat (cycles 10 to 72)
bull No Mean Profile can be used for Envisat on its new orbit (enn) Jason-1 on its geodetic orbit (j1g)because there is no repetitive track The MSS must be used instead (see below)
bull The Mean Profile used for GFO is computed with 7 years of GFO cycles 37 to 187
Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible
bull Indeed as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide precise cross-track projection andor interpolation schemes are required to avoid errors
bull The mesoscale variability error (which is lt35 cm for MP between 3 to 5 years and lt1cm for WLof 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a prioriknowledge from Sea Level maps derived from previous iterations or from other missions
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bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for ERS-1 for its 168 days geodetic mission (phases E-F from April1994 to March 1995) or for Envisat since november 2010 because the satellite is not in a repetitive orbitphase The alternative is to use the MSS instead The gridded MSS is derived from along track MPs anddata from geodetic phases Thus any error on the MP is also contained in the MSS There are essentially 4types of additional errors on gridded MSS which are hard to quantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
III362 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III363 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
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III37 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III371 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
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IV MYOCEAN PRODUCTS
IV1 Near Real Time Products
The purpose of the NRT DUACS component is the acquisition of altimeter data from various altimeter mis-sions in near-real time (ie within a few days at most) the validation and correction of these altimeter datasets (ie edition and selection update of corrections and homogenization orbit error reduction) in order toproduce each day along-track productsProducts are as follows
Along-track products global and regional (Mediterranean and Black Seas Arctic Ocean and Europeareas)
bull Sea Level Anomaly (NRT-SLA) for each mission with NRT-SLA ephemeris
IV11 Delay of the products
The availability of the products in near real time is three to twelve hours after the measurement for along-track products Those products are delivered every day
IV12 Temporal availibility
The following table presents the available products by mission and by data periodNear real time products
NRT Jason-2 Jason-1 and Jason-1geodetic
Envisat new Cryosat-2
Temporal Time availability ymlowast
ongoingymlowast-20120303 for
repeat track and20120507-ongoing for
geodetic track
ymlowast
2012040820120101
ongoing
NRT-SLA X X X X
lowastym the temporal coverage for NRT products is fluctuating and depends on updates of Delayed Time prod-ucts When DT products are updated (3 to 4 times per year) the oldest NRT products are replaced by thebetter quality DT products so that the 2 series are overlapping on few weeks or few months
IV2 Delayed Time Products
The Delayed Time component of SSALTODUACS system is responsible for the production of processedJason-1 Jason-2 TP Envisat GFO ERS12 and even Geosat data in order to provide a homogeneousinter-calibrated and highly accurate long time series of SLA DT products are more precise than NRT products Two reasons explain this quality difference The firstone is the better intrinsic quality of the POE orbit used in the GDR processing The second reason is that
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in the DT DUACS processing the products can be computed optimally with a centred computation timewindow for OER LWE On the contrary in NRT case future data are not available so the computationtime window is not centred and therefore not optimalAs for NRT products improved altimeter corrections and processing algorithms are used ocean tide modelto correct altimeter data improved methods for orbit error reduction and mapping
Along-Track products global and regional (Mediterranean and Black Seas)
bull Sea Level Anomaly (DT-SLA) for each mission
IV21 Delay of the products
Weekly products are delivered The availability of the products in delayed time is at the best two monthsafter the date of the measurement The product generation needs all the GDR data of all the missions to takeinto account the best corrections as possible The time delay can be longer in the case of a missing mission
IV22 Temporal availibility
The following table presents the available products by mission and by data periodDelayed time SSALTODUACS products
Upd Jason-2 Jason-1new6
Jason-1 GFO Envisatnew6
Envisat ERS-16
ERS-2Topexnew6
Topex
TemporalTimeavailabil-ity
200810ymlowast
200902ymlowast
200204200810
200001200809
201010ymlowast
200210201010
199210200304
200209200510
199209200204
DT-SLA X X X X X X X X X
lowast ym those dates are updated regularly (3 to 4 times per year) and are avalaible when you download thedata at httpwwwmyoceaneuweb24-cataloguephp6 Jason-1 new orbit starting 200809 Envisat new orbit starting 201010 TP new orbit starting 200209 ERS-1The geodetic phases (E-F) are included There are no ERS-1 data between December 23 1993 and April 10 1994(ERS-1 phase D - 2nd ice phase) Note that during that time products are based only on TopexPoseidon data
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V DESCRIPTION OF THE PRODUCT SPECIFICATION
V1 General information
Product Specification SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001
Geographical coverage global
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 20-50km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001 Product Specification
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Product Specification SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002
Geographical coverage 55˚W-35˚E 30˚N-46˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002 Product Specification
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Product Specification SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003
Geographical coverage 27˚E-42˚E 40˚N-47˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003 Product Specification
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Product Specification SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004
Geographical coverage 25˚W-42˚E 21˚N-66˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004 Product Specification
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Product Specification SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005
Geographical coverage 0˚W-360˚E 50˚N-82˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005 Product Specification
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VI NOMENCLATURE OF FILES
VI1 Nomenclature of files downloaded through the MyOcean Web PortalDirectgetfile Service
VI11 Nomenclature of the product line
The description of the syntax for the SL TAC SLA products line is given by
SEALEVEL_ltREGIONgt_SLA_L3_ltDELAYgt_OBSERVATIONS_008_ltZONEgt_ltLETTERgtwhere
REGION GLO global geographic coverage product
BS Black Sea products
MED Mediterranean products
ARC Arctic products (for NRT products)
EUROPE Europe products (for NRT products)
DELAY NRT near real time products
RAN delayed time or reanalysis products
ZONE 001 number on 3 digits
002
003
004
LETTER a letter on 1 digit
b
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VI12 Nomenclature of the datasets
The nomenclature used is
dataset-duacs-ltdelaygt-ltzonegt-ltmissiongt-lttype of slagt-l3where the fileds in ltgt are described below
delay nrt near-real time productsran delayed time products
zone global global geographic coverage productmedsea Mediterranean productsblacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1 (only for ran)e2 ERS-2 (only for ran)tp TOPEXPoseidon (only for ran)tpn TOPEXPoseidon on its new orbit (only for
ran)g2 GFO (only for ran)j1 Jason-1 (only for ran)j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisat (only for ran)enn Envisat on its new orbitc2 Cryosat-2 (only for nrt)
type of sla sla filtered slasla_unfiltered non filtered sla (only for ran products)
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VI13 Nomenclature of the NetCdf files
The nomenclature used is
ltdelaygt_ltzonegt_ltmissiongt_sla_ltvariablegt_ltdatebegingt_ltdateendgt_ltdateprodgtnc where the fileds in ltgt are de-scribed below
delay nrt near-real time productsdt delayed time products
zone global global geographic coverage productmed Mediterranean products (for dt)mfstep Mediterranean products (for nrt)blacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1e2 ERS-2tp TOPEXPoseidontpn TOPEXPoseidon on its new orbitg2 GFOj1 Jason-1j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisatenn Envisat on its new orbitc2 Cryosat-2
variable vfec filtered and sub-sampled slavxxc non filtered and non sub-sampled sla (only
for dt)datebegin YYYYMMDD() beginning date of the datasetdateend YYYYMMDD() end date of the datasetdateprod YYYYMMDD production date of the dataset
() For dt data as the dates in the file names are rounded the user wanting data for date T has to read the filescontaining dates T+1 and T-1 in their name and check inside the files if there are some data for date T
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VII DATA FORMAT
This chapter presents the data storage format used for MyOcean products
VII1 NetCdf
The products are stored using the NetCDF format NetCDF (network Common Data Form) is an interface for array-oriented data access and a library that provides an implementation of the interface The netCDF library also definesa machine-independent format for representing scientific data Together the interface library and format support thecreation access and sharing of scientific data The netCDF software was developed at the Unidata Program Center inBoulder Colorado The netCDF libraries define a machine-independent format for representing scientific data Pleasesee Unidata NetCDF pages for more information and to retreive NetCDF software package onhttpwwwunidataucaredupackagesnetcdfindexhtml
NetCDF data is
bull Self-Describing A netCDF file includes information about the data it contains
bull Architecture-independent A netCDF file is represented in a form that can be accessed by computers with dif-ferent ways of storing integers characters and floating-point numbers
bull Direct-access A small subset of a large dataset may be accessed efficiently without first reading through allthe preceding data
bull Appendable Data can be appended to a netCDF dataset along one dimension without copying the dataset orredefining its structure The structure of a netCDF dataset can be changed though this sometimes causes thedataset to be copied
bull Sharable One writer and multiple readers may simultaneously access the same netCDF file
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VII2 Structure and semantic of NetCDF along-track files
The NetCDF Sea Level TAC files are based on the attribute data tags defined by the Cooperative OceanAtmosphereResearch Data Service (COARDS) and Climate and Forecast (CF) metadata conventions The CF convention gener-alises and extends the COARDS convention but relaxes the COARDS constraints on dimension and order and specifiesmethods for reducing the size of datasetsA wide range of software are available to write or read NetCDFCF files API are made available by UNIDATA(httpwwwunidataucaredusoftwarenetcdf)
bull CC++Fortran
bull Java
bull MATLAB Objective-C Perl Python R Ruby TclTk
In addition to these conventions the files are using a common structure and semantic
bull 1 dimension is defined
ndash time it is used to check NetCDF variables depending on time
bull 8 variables are defined
ndash short SLA contains the Sea Level Anomaly values for each time given
ndash int longitude contains the longitude for each measurement
ndash short track contains the track number for each measurement
ndash double time contains the time in days since 1950-01-01 000000 UTC for each measurement
ndash short mean_profile_point_index index of the corrsponding point in the track of the mean profile
ndash byte flag flag=0 the processed data comes from OGDR if flag=1 the processed data comes from theIGDR
ndash int latitude contains the latitude for each measurement
ndash short cycle contains the cycle number for each measurement
bull global attributes
ndash the global attributes gives information about the creation of the file
Example of a NetCDF sla file
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netcdf nrt_global_j1_sla_vfec_20101230_20101230_20101230 dimensions
time = 10385 variables
short SLA(time) SLAcoordinates = longitude latitude SLAlong_name = Sea Level Anomaly SLA_FillValue = 32767s SLAadd_offset = 0 SLAscale_factor = 0001 SLAunits = m SLAstandard_name = sea_surface_height_above_sea_level
int longitude(time) longitudelong_name = Longitude of measurement longitude_FillValue = 2147483647 longitudeadd_offset = 0 longitudestandard_name = longitude longitudescale_factor = 1e-06 longitudeunits = degrees_east
short track(time) tracklong_name = Track in cycle the measurement belongs to track_FillValue = 32767s trackunits = 1 trackcoordinates = longitude latitude
double time(time) timelong_name = Time of measurement time_FillValue = 184467440737096e+19 timeaxis = T timestandard_name = time timeunits = days since 1950-01-01 000000 UTC
int latitude(time) latitudelong_name = Latitude of measurement latitude_FillValue = 2147483647 latitudeadd_offset = 0 latitudestandard_name = latitude latitudescale_factor = 1e-06 latitudeunits = degrees_north
short flag(time) flagcoordinates = longitude latitude flag_FillValue = 3267s flaglong_name = data origin flagflag_values = 1s 0s flagflag_meanings = igdr_like non_igdr_like flagcomment = The origin of the data is determined by the types of geophysical datarecords (GDR) used in computation of the SLA 1 for the Interim GDR (IGDR) and0 for Operational GDR (OGDR)
short cycle(time) cyclelong_name = Cycle the measurement belongs to cycle_FillValue = 32767s cycleunits = 1 cyclecoordinates = longitude latitude
global attributeshistory = 22-Feb-2011 155243 CET File created by the SSLATODUACS system version 1001 comment = Produce from ENVISAT Extension Phase satellite altimetry data institution = CLSCNES
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references = httpwwwavisooceanobscomfileadmindocumentsdatatoolshdbk_duacspdf source = satellite altimetry title = along track Sea Level Anomaly Conventions = CF-14
dataSLA =
7 7 11 10 -2 -22 -39 -41 -30 -13 -3 -5 -16 -26 -32 -35-35 -35 -37 -35 -31 -29 -31 -35 -32 -21 -10 -10 -19 -20 -1-69 -57 -49 -45 -39 -30 -28 -31 -27 -13 -2 -5 -15 -3 1112 3 -7 -10 -14 -15 -22 -31 -37 -32 -17 -10
longitude =74743328 74868400 74993968 75120040 75246616 7537372875501368 75629568 75758320 75887656 76017568 76148080 7627920876388952 76477056 76565456 76654144 76743128 76832400 76921984329429568 329535424 329641792 329748672 329856096 329964032330072512 330181536 330291072 330401184
track =92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 9292 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92113 113 113 113 113 113 113 113 113 113 113 113 113 113113 113 113 113 113 113 113 113 113
time =222780000565705 222780001314719 222780002063733222780002812747 222780003561761 222780004310775 222780005059788222780005808802 222780006557816 22278000730683 222780008055844222780008804858 222780009553872 22278001017805 222780010677393222788257112198 222788257486705 222788257861212 222788258235719222788258610226 222788258984733 222788259359239 222788259733746222788260108253 22278826048276
mean_profile_point_index =1872 1878 1884 1890 1896 1902 1908 19141920 1926 1932 1938 1944 1949 1953 1957 1961 1965 1969 19732306 2309 2312 2315 2318 2321 2327 2330 2333 2336 2339 23422345 2348 2351 2354 2357 2360 2363 2366
flag =0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
latitude =-16225506 -16539731 -16853833 -17167810 -17481660 -17795380-18108966 -18422418 -18735729 -19048899 -19361924 -19674801-19987527 -20248015 -20456329 -20664569 -20872739 -2108083739481297 39628277 39775133 39921866 40068472 40214953 4036130840507533 40653629 40799592 40945423 41091120 41236684 41382111
cycle =331 331 331 331 331 331 331 331 331 331 331 331 331
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331 331 331 331 331 331 331 331 331 331 331 331 331 331331 331 331 331 331 331 331 331 331 331 331 331
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VIII HOW TO DOWNLOAD A PRODUCT
VIII1 Download a product through the MyOcean Web Portal DirectgetfileService
You first need to register Please find below the registration stepshttpwwwmyoceaneuweb34-products-and-services-faqphp1Once registered the MyOcean FAQ httpwwwmyoceaneuweb34-products-and-services-faqwill guide you on How to download a product through the MyOcean Web Portal Directgetfile Service
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IX NEWS AND UPDATES
IX1 [Duacs] Operational news
To be kept informed on events occurring on the satellites and on the eventual interruption of the services of the DUACSprocessing system see the [Duacs] operational news on the Aviso websitehttpwwwavisooceanobscomendataoperational-newsindexhtml
IX2 Updates
To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtmlSince 2010 a complete reprocessing of all altimetry data (cumulated total of about 55 years of data) is available Themain changes introduced in the Duacs DT v300 reprocessed data set in SSALTODUACS reprocessed DT data setare listed herehttpwwwavisooceanobscomfileadmindocumentsdataduacsduacs_DT_2010_reprocessing_impactpdf
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III3 Delayed Time processing steps
III31 Input data models and corrections applied
Delayed Time MyOcean products are generated
bull from Aviso GDR products for TP Jason-1 Jason-2 and Envisat (GDR-A cycles 1 to 22 GDR-Bcycles 23 to 85 GDR-C from cycle 86)
bull from NOAA GDR for GFO and from CERSAT (IFREMER) OPR for ERS-1 and ERS-2 (phases C(1st 35-day repeat orbit period) phase E and F (geodetic phases) phase G for ERS-1 (last 35-dayrepeat orbit period tandem phase with ERS-2 phase A for ERS-2 (1st 35-day repeat orbit periodtandem phase with ERS-1))
All GDR products are computed with a Precise Orbit Ephemeris (POE) and are delivered within 2 to 3months depending on the mission For several missions an updated orbit is used
bull For ERS-1amp-2 the orbit used is DGME-04 provided by Delft Institute (httpwwwdeostudelftnl)until June 2003
bull For TopexPoseidon the orbit used is GSFC (std0809) for the whole mission
bull For Envisat CNES POE of GDR-C standard is used for the whole mission
bull For the whole GFO mission the orbit used is GSFC (std0809) and when not available NASA POE isused
Altimetric product Source Availability Type of orbit
TopexPoseidon GDR NASACNES - GSFC POE
Jason-1 GDR (GDR-C) CNESNASA ~40 days CNES POE
Jason-2 GDR (GDR-C) CNESNASA ~60 days CNES POE
GFO GDR NOAA - GSFCNASA POE
ERS-1amp2 IFREMERESA - DGME-04
Envisat (GDR-A GDR-B andGDR-C from cycle 86)
ESA ~2 months CNES POE
Table 5 SSALTODUACS Delayed Time Input data overview
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DU
AC
S20
11D
Tpr
oduc
t(gtV
30
0)j2
j1j1
ntp
tpn
e1e2
ene
nng2
Prod
uct
stan
dard
ref
GD
R-C
OPR
GD
R-A
(Cyc
les
1to
22)
GD
R-B
(cyc
les
23-8
5)
GD
R(N
OA
A)
Orb
itC
nes
POE
GSF
C(I
TR
F20
05G
RA
CE
last
stan
dard
s)
DG
ME
-04
(Sch
arro
oan
dV
isse
r19
98[4
8]C
NE
SPO
E(G
DR
-1st
anda
rds
forc
ycle
s9
to22
GD
R-C
stan
dard
sfr
omcy
cle
23)
GSF
C(I
TR
F20
05
GR
AC
Ela
stst
anda
rds
Iono
pher
icD
ual f
requ
ency
altim
eter
rang
em
easu
rem
ents
Dua
l fre
quen
cyal
timet
erra
nge
mea
sure
men
ts(T
opex
)D
OR
IS(P
OSE
IDO
N)
Ben
t mod
elB
ent m
odel
(cyc
les
1-36
)G
IMm
odem
from
cycl
e37
((Ii
jima
etal
19
98[2
4])
Dua
l-fr
eque
ncy
altim
eter
rang
em
easu
rem
ent(
cycl
e9-
64)a
ndG
IMm
odel
gtcyc
le65
(Iiji
ma
etal
19
99[2
4])c
orre
cted
from
8m
mbi
as
From
GIM
mod
el(I
ijim
aet
al1
998
[24]
)
Dry
trop
o-sp
here
Mod
elco
mpu
ted
from
EC
MW
FG
auss
ian
grid
s(n
ewS1
and
S2at
mos
pher
ictid
esar
eap
plie
d)
Mod
elco
mpu
ted
from
EC
MW
Fre
ctan
gula
rgri
ds(n
ewS1
and
S2at
mos
pher
ictid
esar
ein
clud
ed)
Wet
trop
o-sp
here
JMR
AM
Rra
diom
eter
furt
hert
han
50km
from
the
coas
tsF
rom
EC
MW
Fm
odel
ford
ista
nces
betw
een
10an
d50
km
TM
Rra
diom
eter
(Sch
aroo
etal
20
04[4
9])
MW
RC
orre
ctio
nof
the
drif
ton
the
236
GH
zbr
ight
ness
tem
pera
ture
(Sch
arro
oet
al
2004
[49]
)Neu
ral
Net
wor
kal
gori
thm
(Tra
nan
dO
blig
is
2003
[50]
MW
Rra
diom
eter
furt
hert
han
50km
from
the
coas
tsan
dco
rrec
ted
from
side
lobe
s(f
rom
cycl
e41
)E
CM
WF
mod
elfo
rdis
tanc
esbe
twee
n10
and
50km
GFO
radi
omet
er
DA
CM
OG
2DH
igh
Res
olut
ion
forc
edw
ithE
CM
WF
pres
sure
and
win
gfie
lds
(S1
and
S2w
ere
excl
uded
)+in
vers
eba
rom
eter
com
pute
dfr
omre
ctan
gula
rgri
ds
Tabl
e6
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(1
2)
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j2j1
j1n
tptp
ne1
e2en
enn
g2O
cean
tide
GO
T4v
7(S
1an
dS2
are
incl
uded
)Po
letid
e[W
ahr
1985
[53]
]So
lidea
rth
tide
Ela
stic
resp
onse
totid
alpo
tent
ial[
Car
twri
ghta
ndTa
yler
197
1[5]
][C
artw
righ
tand
Edd
en1
973[
6]]
Loa
ding
tide
GO
T4v
7(S
1pa
ram
eter
isin
clud
ed)
Sea
stat
ebi
asN
onpa
ram
etri
cSS
B[G
aspa
reta
l20
02[2
0]]
Non
para
met
ric
SSB
[NT
ran
and
al2
010[
51]]
BM
3[G
aspa
ran
dO
gor
1994
[17]
]
Non
para
met
ric
SSB
[Mer
tzet
al
2005
[38]
]
Non
para
met
ric
SSB
[Gas
pare
tal
2002
]w
ithG
DR
-Bst
anda
rds
forc
ycle
s9
to85
and
with
GD
R-C
stan
dard
sfr
omcy
cle
86
Non
para
met
ric
SSB
[NT
ran
etal
20
10[5
1]]
Orb
iter
ror
Glo
bal m
ulti-
mis
sion
cros
sove
rmin
imiz
atio
n(L
eTr
aon
and
Ogo
r19
98[3
2])
Lon
gw
ave-
leng
her
rors
Opt
imal
Inte
rpol
atio
n(L
eTr
aon
etal
19
98[3
1])
Inte
rcal
ibra
tion
Ref
eren
cefr
omcy
cle
11R
efer
ence
from
cycl
e1
to35
4C
orre
ctio
nof
regi
onal
bias
J2J
1de
duce
dfr
omin
terc
alib
ratio
nph
ase
(cyc
le11
J2)
Cor
rect
ion
ofgl
obal
biai
sJ1
TP
deacutedu
ced
from
inte
rcal
ibra
tion
phas
e(c
ycle
s11
J1)
Mea
npr
o-fil
e(s
eeII
I36
1)
Com
pute
dw
ithcy
cles
11-3
53T
Pda
taan
dw
ithcy
cles
11-2
50J1
data
ref
eren
ced
[199
319
99]
TP
J1 c
ompu
ted
with
cycl
es11
-353
TP
data
and
with
cycl
es11
-250
J1da
tar
efer
ence
d[1
993
1999
]T
PNJ
1Nc
ompu
ted
with
cycl
es36
9-47
9T
PNda
tar
efer
ence
d[1
993
1999
]
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
ref
eren
ced
[199
319
99]
EN
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
re
fere
nced
[199
319
99]
EN
Nu
seof
MSS
_CN
ES_
CL
S11
[39]
Com
pute
dw
ithcy
cles
37-1
87G
2da
ta
refe
renc
ed[1
993
1999
]
Peri
odof
use
from
cycl
e9
from
cycl
e9
cycl
es1
to48
1cy
cles
15to
43In
clud
ing
E-F
geod
etic
phas
es
cycl
es1
to83
from
cycl
e9
cycl
es37
to22
2
Tabl
e7
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(2
2)
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III32 Acquisition
The acqusition process in Delayed time is much simpler than in Near Real time it consists in a synchronisa-tion process of all the auxiliary data required to homogenize propely the altimeter data sets The acquisitionstep uses the GDRs or the OPRs provided by the agencies
III33 Homogenization
The Homogenization process consists in applying the most recent corrections models and references rec-ommended for altimeter products Each mission is processed separately as its needs depend on the baseinput data The list of corrections and models currently applied is provided in tables 6 and 7 for DT data
III34 Input data quality control
The Input Data Quality Control is a critical process applied to guarantee that DUACS uses only the mostaccurate altimeter data Thanks to the high quality of current missions this process rejects a small percent-age of altimeter measurements but these erroneous data could be the cause of a significant quality lossThe quality control relies on standard raw data editing with quality flags or parameter thresholds but alsoon complex data editing algorithms based on the detection of erroneous artefacts mono and multi-missioncrossover validation and macroscopic statistics to edit out large data flows that do not meet the systemrsquosrequirements
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III35 Multi-mission cross-calibration
The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistentand accurate information It removes any residual orbit error (OE Le Traon and Ogor 1998[32]) or longwavelength error (LWE Le Traon et al 1998[31]) as well as large scale biases and discrepancies betweenvarious data flows
This process is based on two very different algorithms a global multi-mission crossover minimization fororbit error reduction (OER) and Optimal Interpolation (OI) for LWE
Multi-satellite crossover determination is performed on a daily basis All altimeter fields (measurementcorrections and other fields such as bathymetry MSS) are interpolated at crossover locations and datesCrossovers are then appended to the existing crossover database as more altimeter data become availableThis crossover data set is the input of the Orbit Error Reduction (OER) method Using the precision of thereference mission orbit a very accurate orbit error can be estimated LWE is mostly due to residual tidalor inverse barometer errors and high frequency ocean signals The OI used for LWE reduction uses preciseparameters derived from
bull accurate statistical description of sea level variability
bull localized correlation scales
bull mission-specific noise and precise assumptions on the long wavelength errors to be removed (from arecent analysis of one year of data from each mission)
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III36 Product generation
The product generation process is composed of four steps computation of raw SLA cross-validationfilteringampsub-sampling and generation of by-products
III361 Computation of raw SLA
Since the geoid is not well known yet the SSH cannot be used directly the SSH anomalies are used insteadThey are computed from the difference of the instantaneous SSH - a temporal reference This temporalreference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeattrack analysis cannot be used The errors affecting the SLAs MPs and MSS have different magnitudes andwavelengths The computation of the SLAs and their errors associated are detailed in Dibarboure et al 2010[9]
Use of a Mean ProfileIn the repeat track analysis (when the satellites flies over a repetitive orbit) measurements are re-sampledalong a theoretical ground track (or mean track) associated to each mission Then a Mean Profile (MP) issubtracted from the re-sampled data to obtain SLA The MP is a time average of similarly re-sampled dataover a long period
bull The Mean Profile used for TP (cycles 1 to 364) Jason-1 (cycles 1 to 259) and Jason-2 is computedwith 10 years of TP (cycles 11 to 353) and 6 years of Jason-1 (cycles 11 to 250)
bull The Mean Profile used for TP (cycles 368 to 481) and from Jason-1 cycle 262 to 374 (where satellitesare on interleaved ground-tracks) is computed with 3 years of TP (cycles 369 to 479)
bull The Mean Profile used for ERS-1 in its 35 days repetitive orbit mission ERS-2 and Envisat (only forthe first orbit before November 2010) is computed with 8 years of ERS-2 (cycles 1 to 85) and 6 yearsof Envisat (cycles 10 to 72)
bull No Mean Profile can be used for Envisat on its new orbit (enn) Jason-1 on its geodetic orbit (j1g)because there is no repetitive track The MSS must be used instead (see below)
bull The Mean Profile used for GFO is computed with 7 years of GFO cycles 37 to 187
Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible
bull Indeed as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide precise cross-track projection andor interpolation schemes are required to avoid errors
bull The mesoscale variability error (which is lt35 cm for MP between 3 to 5 years and lt1cm for WLof 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a prioriknowledge from Sea Level maps derived from previous iterations or from other missions
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bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for ERS-1 for its 168 days geodetic mission (phases E-F from April1994 to March 1995) or for Envisat since november 2010 because the satellite is not in a repetitive orbitphase The alternative is to use the MSS instead The gridded MSS is derived from along track MPs anddata from geodetic phases Thus any error on the MP is also contained in the MSS There are essentially 4types of additional errors on gridded MSS which are hard to quantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
III362 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III363 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
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III37 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III371 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
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IV MYOCEAN PRODUCTS
IV1 Near Real Time Products
The purpose of the NRT DUACS component is the acquisition of altimeter data from various altimeter mis-sions in near-real time (ie within a few days at most) the validation and correction of these altimeter datasets (ie edition and selection update of corrections and homogenization orbit error reduction) in order toproduce each day along-track productsProducts are as follows
Along-track products global and regional (Mediterranean and Black Seas Arctic Ocean and Europeareas)
bull Sea Level Anomaly (NRT-SLA) for each mission with NRT-SLA ephemeris
IV11 Delay of the products
The availability of the products in near real time is three to twelve hours after the measurement for along-track products Those products are delivered every day
IV12 Temporal availibility
The following table presents the available products by mission and by data periodNear real time products
NRT Jason-2 Jason-1 and Jason-1geodetic
Envisat new Cryosat-2
Temporal Time availability ymlowast
ongoingymlowast-20120303 for
repeat track and20120507-ongoing for
geodetic track
ymlowast
2012040820120101
ongoing
NRT-SLA X X X X
lowastym the temporal coverage for NRT products is fluctuating and depends on updates of Delayed Time prod-ucts When DT products are updated (3 to 4 times per year) the oldest NRT products are replaced by thebetter quality DT products so that the 2 series are overlapping on few weeks or few months
IV2 Delayed Time Products
The Delayed Time component of SSALTODUACS system is responsible for the production of processedJason-1 Jason-2 TP Envisat GFO ERS12 and even Geosat data in order to provide a homogeneousinter-calibrated and highly accurate long time series of SLA DT products are more precise than NRT products Two reasons explain this quality difference The firstone is the better intrinsic quality of the POE orbit used in the GDR processing The second reason is that
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in the DT DUACS processing the products can be computed optimally with a centred computation timewindow for OER LWE On the contrary in NRT case future data are not available so the computationtime window is not centred and therefore not optimalAs for NRT products improved altimeter corrections and processing algorithms are used ocean tide modelto correct altimeter data improved methods for orbit error reduction and mapping
Along-Track products global and regional (Mediterranean and Black Seas)
bull Sea Level Anomaly (DT-SLA) for each mission
IV21 Delay of the products
Weekly products are delivered The availability of the products in delayed time is at the best two monthsafter the date of the measurement The product generation needs all the GDR data of all the missions to takeinto account the best corrections as possible The time delay can be longer in the case of a missing mission
IV22 Temporal availibility
The following table presents the available products by mission and by data periodDelayed time SSALTODUACS products
Upd Jason-2 Jason-1new6
Jason-1 GFO Envisatnew6
Envisat ERS-16
ERS-2Topexnew6
Topex
TemporalTimeavailabil-ity
200810ymlowast
200902ymlowast
200204200810
200001200809
201010ymlowast
200210201010
199210200304
200209200510
199209200204
DT-SLA X X X X X X X X X
lowast ym those dates are updated regularly (3 to 4 times per year) and are avalaible when you download thedata at httpwwwmyoceaneuweb24-cataloguephp6 Jason-1 new orbit starting 200809 Envisat new orbit starting 201010 TP new orbit starting 200209 ERS-1The geodetic phases (E-F) are included There are no ERS-1 data between December 23 1993 and April 10 1994(ERS-1 phase D - 2nd ice phase) Note that during that time products are based only on TopexPoseidon data
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V DESCRIPTION OF THE PRODUCT SPECIFICATION
V1 General information
Product Specification SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001
Geographical coverage global
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 20-50km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001 Product Specification
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Product Specification SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002
Geographical coverage 55˚W-35˚E 30˚N-46˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002 Product Specification
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Product Specification SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003
Geographical coverage 27˚E-42˚E 40˚N-47˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003 Product Specification
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Product Specification SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004
Geographical coverage 25˚W-42˚E 21˚N-66˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004 Product Specification
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Product Specification SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005
Geographical coverage 0˚W-360˚E 50˚N-82˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005 Product Specification
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VI NOMENCLATURE OF FILES
VI1 Nomenclature of files downloaded through the MyOcean Web PortalDirectgetfile Service
VI11 Nomenclature of the product line
The description of the syntax for the SL TAC SLA products line is given by
SEALEVEL_ltREGIONgt_SLA_L3_ltDELAYgt_OBSERVATIONS_008_ltZONEgt_ltLETTERgtwhere
REGION GLO global geographic coverage product
BS Black Sea products
MED Mediterranean products
ARC Arctic products (for NRT products)
EUROPE Europe products (for NRT products)
DELAY NRT near real time products
RAN delayed time or reanalysis products
ZONE 001 number on 3 digits
002
003
004
LETTER a letter on 1 digit
b
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VI12 Nomenclature of the datasets
The nomenclature used is
dataset-duacs-ltdelaygt-ltzonegt-ltmissiongt-lttype of slagt-l3where the fileds in ltgt are described below
delay nrt near-real time productsran delayed time products
zone global global geographic coverage productmedsea Mediterranean productsblacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1 (only for ran)e2 ERS-2 (only for ran)tp TOPEXPoseidon (only for ran)tpn TOPEXPoseidon on its new orbit (only for
ran)g2 GFO (only for ran)j1 Jason-1 (only for ran)j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisat (only for ran)enn Envisat on its new orbitc2 Cryosat-2 (only for nrt)
type of sla sla filtered slasla_unfiltered non filtered sla (only for ran products)
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VI13 Nomenclature of the NetCdf files
The nomenclature used is
ltdelaygt_ltzonegt_ltmissiongt_sla_ltvariablegt_ltdatebegingt_ltdateendgt_ltdateprodgtnc where the fileds in ltgt are de-scribed below
delay nrt near-real time productsdt delayed time products
zone global global geographic coverage productmed Mediterranean products (for dt)mfstep Mediterranean products (for nrt)blacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1e2 ERS-2tp TOPEXPoseidontpn TOPEXPoseidon on its new orbitg2 GFOj1 Jason-1j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisatenn Envisat on its new orbitc2 Cryosat-2
variable vfec filtered and sub-sampled slavxxc non filtered and non sub-sampled sla (only
for dt)datebegin YYYYMMDD() beginning date of the datasetdateend YYYYMMDD() end date of the datasetdateprod YYYYMMDD production date of the dataset
() For dt data as the dates in the file names are rounded the user wanting data for date T has to read the filescontaining dates T+1 and T-1 in their name and check inside the files if there are some data for date T
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VII DATA FORMAT
This chapter presents the data storage format used for MyOcean products
VII1 NetCdf
The products are stored using the NetCDF format NetCDF (network Common Data Form) is an interface for array-oriented data access and a library that provides an implementation of the interface The netCDF library also definesa machine-independent format for representing scientific data Together the interface library and format support thecreation access and sharing of scientific data The netCDF software was developed at the Unidata Program Center inBoulder Colorado The netCDF libraries define a machine-independent format for representing scientific data Pleasesee Unidata NetCDF pages for more information and to retreive NetCDF software package onhttpwwwunidataucaredupackagesnetcdfindexhtml
NetCDF data is
bull Self-Describing A netCDF file includes information about the data it contains
bull Architecture-independent A netCDF file is represented in a form that can be accessed by computers with dif-ferent ways of storing integers characters and floating-point numbers
bull Direct-access A small subset of a large dataset may be accessed efficiently without first reading through allthe preceding data
bull Appendable Data can be appended to a netCDF dataset along one dimension without copying the dataset orredefining its structure The structure of a netCDF dataset can be changed though this sometimes causes thedataset to be copied
bull Sharable One writer and multiple readers may simultaneously access the same netCDF file
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VII2 Structure and semantic of NetCDF along-track files
The NetCDF Sea Level TAC files are based on the attribute data tags defined by the Cooperative OceanAtmosphereResearch Data Service (COARDS) and Climate and Forecast (CF) metadata conventions The CF convention gener-alises and extends the COARDS convention but relaxes the COARDS constraints on dimension and order and specifiesmethods for reducing the size of datasetsA wide range of software are available to write or read NetCDFCF files API are made available by UNIDATA(httpwwwunidataucaredusoftwarenetcdf)
bull CC++Fortran
bull Java
bull MATLAB Objective-C Perl Python R Ruby TclTk
In addition to these conventions the files are using a common structure and semantic
bull 1 dimension is defined
ndash time it is used to check NetCDF variables depending on time
bull 8 variables are defined
ndash short SLA contains the Sea Level Anomaly values for each time given
ndash int longitude contains the longitude for each measurement
ndash short track contains the track number for each measurement
ndash double time contains the time in days since 1950-01-01 000000 UTC for each measurement
ndash short mean_profile_point_index index of the corrsponding point in the track of the mean profile
ndash byte flag flag=0 the processed data comes from OGDR if flag=1 the processed data comes from theIGDR
ndash int latitude contains the latitude for each measurement
ndash short cycle contains the cycle number for each measurement
bull global attributes
ndash the global attributes gives information about the creation of the file
Example of a NetCDF sla file
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netcdf nrt_global_j1_sla_vfec_20101230_20101230_20101230 dimensions
time = 10385 variables
short SLA(time) SLAcoordinates = longitude latitude SLAlong_name = Sea Level Anomaly SLA_FillValue = 32767s SLAadd_offset = 0 SLAscale_factor = 0001 SLAunits = m SLAstandard_name = sea_surface_height_above_sea_level
int longitude(time) longitudelong_name = Longitude of measurement longitude_FillValue = 2147483647 longitudeadd_offset = 0 longitudestandard_name = longitude longitudescale_factor = 1e-06 longitudeunits = degrees_east
short track(time) tracklong_name = Track in cycle the measurement belongs to track_FillValue = 32767s trackunits = 1 trackcoordinates = longitude latitude
double time(time) timelong_name = Time of measurement time_FillValue = 184467440737096e+19 timeaxis = T timestandard_name = time timeunits = days since 1950-01-01 000000 UTC
int latitude(time) latitudelong_name = Latitude of measurement latitude_FillValue = 2147483647 latitudeadd_offset = 0 latitudestandard_name = latitude latitudescale_factor = 1e-06 latitudeunits = degrees_north
short flag(time) flagcoordinates = longitude latitude flag_FillValue = 3267s flaglong_name = data origin flagflag_values = 1s 0s flagflag_meanings = igdr_like non_igdr_like flagcomment = The origin of the data is determined by the types of geophysical datarecords (GDR) used in computation of the SLA 1 for the Interim GDR (IGDR) and0 for Operational GDR (OGDR)
short cycle(time) cyclelong_name = Cycle the measurement belongs to cycle_FillValue = 32767s cycleunits = 1 cyclecoordinates = longitude latitude
global attributeshistory = 22-Feb-2011 155243 CET File created by the SSLATODUACS system version 1001 comment = Produce from ENVISAT Extension Phase satellite altimetry data institution = CLSCNES
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references = httpwwwavisooceanobscomfileadmindocumentsdatatoolshdbk_duacspdf source = satellite altimetry title = along track Sea Level Anomaly Conventions = CF-14
dataSLA =
7 7 11 10 -2 -22 -39 -41 -30 -13 -3 -5 -16 -26 -32 -35-35 -35 -37 -35 -31 -29 -31 -35 -32 -21 -10 -10 -19 -20 -1-69 -57 -49 -45 -39 -30 -28 -31 -27 -13 -2 -5 -15 -3 1112 3 -7 -10 -14 -15 -22 -31 -37 -32 -17 -10
longitude =74743328 74868400 74993968 75120040 75246616 7537372875501368 75629568 75758320 75887656 76017568 76148080 7627920876388952 76477056 76565456 76654144 76743128 76832400 76921984329429568 329535424 329641792 329748672 329856096 329964032330072512 330181536 330291072 330401184
track =92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 9292 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92113 113 113 113 113 113 113 113 113 113 113 113 113 113113 113 113 113 113 113 113 113 113
time =222780000565705 222780001314719 222780002063733222780002812747 222780003561761 222780004310775 222780005059788222780005808802 222780006557816 22278000730683 222780008055844222780008804858 222780009553872 22278001017805 222780010677393222788257112198 222788257486705 222788257861212 222788258235719222788258610226 222788258984733 222788259359239 222788259733746222788260108253 22278826048276
mean_profile_point_index =1872 1878 1884 1890 1896 1902 1908 19141920 1926 1932 1938 1944 1949 1953 1957 1961 1965 1969 19732306 2309 2312 2315 2318 2321 2327 2330 2333 2336 2339 23422345 2348 2351 2354 2357 2360 2363 2366
flag =0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
latitude =-16225506 -16539731 -16853833 -17167810 -17481660 -17795380-18108966 -18422418 -18735729 -19048899 -19361924 -19674801-19987527 -20248015 -20456329 -20664569 -20872739 -2108083739481297 39628277 39775133 39921866 40068472 40214953 4036130840507533 40653629 40799592 40945423 41091120 41236684 41382111
cycle =331 331 331 331 331 331 331 331 331 331 331 331 331
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331 331 331 331 331 331 331 331 331 331 331 331 331 331331 331 331 331 331 331 331 331 331 331 331 331
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VIII HOW TO DOWNLOAD A PRODUCT
VIII1 Download a product through the MyOcean Web Portal DirectgetfileService
You first need to register Please find below the registration stepshttpwwwmyoceaneuweb34-products-and-services-faqphp1Once registered the MyOcean FAQ httpwwwmyoceaneuweb34-products-and-services-faqwill guide you on How to download a product through the MyOcean Web Portal Directgetfile Service
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IX NEWS AND UPDATES
IX1 [Duacs] Operational news
To be kept informed on events occurring on the satellites and on the eventual interruption of the services of the DUACSprocessing system see the [Duacs] operational news on the Aviso websitehttpwwwavisooceanobscomendataoperational-newsindexhtml
IX2 Updates
To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtmlSince 2010 a complete reprocessing of all altimetry data (cumulated total of about 55 years of data) is available Themain changes introduced in the Duacs DT v300 reprocessed data set in SSALTODUACS reprocessed DT data setare listed herehttpwwwavisooceanobscomfileadmindocumentsdataduacsduacs_DT_2010_reprocessing_impactpdf
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PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
DU
AC
S20
11D
Tpr
oduc
t(gtV
30
0)j2
j1j1
ntp
tpn
e1e2
ene
nng2
Prod
uct
stan
dard
ref
GD
R-C
OPR
GD
R-A
(Cyc
les
1to
22)
GD
R-B
(cyc
les
23-8
5)
GD
R(N
OA
A)
Orb
itC
nes
POE
GSF
C(I
TR
F20
05G
RA
CE
last
stan
dard
s)
DG
ME
-04
(Sch
arro
oan
dV
isse
r19
98[4
8]C
NE
SPO
E(G
DR
-1st
anda
rds
forc
ycle
s9
to22
GD
R-C
stan
dard
sfr
omcy
cle
23)
GSF
C(I
TR
F20
05
GR
AC
Ela
stst
anda
rds
Iono
pher
icD
ual f
requ
ency
altim
eter
rang
em
easu
rem
ents
Dua
l fre
quen
cyal
timet
erra
nge
mea
sure
men
ts(T
opex
)D
OR
IS(P
OSE
IDO
N)
Ben
t mod
elB
ent m
odel
(cyc
les
1-36
)G
IMm
odem
from
cycl
e37
((Ii
jima
etal
19
98[2
4])
Dua
l-fr
eque
ncy
altim
eter
rang
em
easu
rem
ent(
cycl
e9-
64)a
ndG
IMm
odel
gtcyc
le65
(Iiji
ma
etal
19
99[2
4])c
orre
cted
from
8m
mbi
as
From
GIM
mod
el(I
ijim
aet
al1
998
[24]
)
Dry
trop
o-sp
here
Mod
elco
mpu
ted
from
EC
MW
FG
auss
ian
grid
s(n
ewS1
and
S2at
mos
pher
ictid
esar
eap
plie
d)
Mod
elco
mpu
ted
from
EC
MW
Fre
ctan
gula
rgri
ds(n
ewS1
and
S2at
mos
pher
ictid
esar
ein
clud
ed)
Wet
trop
o-sp
here
JMR
AM
Rra
diom
eter
furt
hert
han
50km
from
the
coas
tsF
rom
EC
MW
Fm
odel
ford
ista
nces
betw
een
10an
d50
km
TM
Rra
diom
eter
(Sch
aroo
etal
20
04[4
9])
MW
RC
orre
ctio
nof
the
drif
ton
the
236
GH
zbr
ight
ness
tem
pera
ture
(Sch
arro
oet
al
2004
[49]
)Neu
ral
Net
wor
kal
gori
thm
(Tra
nan
dO
blig
is
2003
[50]
MW
Rra
diom
eter
furt
hert
han
50km
from
the
coas
tsan
dco
rrec
ted
from
side
lobe
s(f
rom
cycl
e41
)E
CM
WF
mod
elfo
rdis
tanc
esbe
twee
n10
and
50km
GFO
radi
omet
er
DA
CM
OG
2DH
igh
Res
olut
ion
forc
edw
ithE
CM
WF
pres
sure
and
win
gfie
lds
(S1
and
S2w
ere
excl
uded
)+in
vers
eba
rom
eter
com
pute
dfr
omre
ctan
gula
rgri
ds
Tabl
e6
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(1
2)
Page 33
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
j2j1
j1n
tptp
ne1
e2en
enn
g2O
cean
tide
GO
T4v
7(S
1an
dS2
are
incl
uded
)Po
letid
e[W
ahr
1985
[53]
]So
lidea
rth
tide
Ela
stic
resp
onse
totid
alpo
tent
ial[
Car
twri
ghta
ndTa
yler
197
1[5]
][C
artw
righ
tand
Edd
en1
973[
6]]
Loa
ding
tide
GO
T4v
7(S
1pa
ram
eter
isin
clud
ed)
Sea
stat
ebi
asN
onpa
ram
etri
cSS
B[G
aspa
reta
l20
02[2
0]]
Non
para
met
ric
SSB
[NT
ran
and
al2
010[
51]]
BM
3[G
aspa
ran
dO
gor
1994
[17]
]
Non
para
met
ric
SSB
[Mer
tzet
al
2005
[38]
]
Non
para
met
ric
SSB
[Gas
pare
tal
2002
]w
ithG
DR
-Bst
anda
rds
forc
ycle
s9
to85
and
with
GD
R-C
stan
dard
sfr
omcy
cle
86
Non
para
met
ric
SSB
[NT
ran
etal
20
10[5
1]]
Orb
iter
ror
Glo
bal m
ulti-
mis
sion
cros
sove
rmin
imiz
atio
n(L
eTr
aon
and
Ogo
r19
98[3
2])
Lon
gw
ave-
leng
her
rors
Opt
imal
Inte
rpol
atio
n(L
eTr
aon
etal
19
98[3
1])
Inte
rcal
ibra
tion
Ref
eren
cefr
omcy
cle
11R
efer
ence
from
cycl
e1
to35
4C
orre
ctio
nof
regi
onal
bias
J2J
1de
duce
dfr
omin
terc
alib
ratio
nph
ase
(cyc
le11
J2)
Cor
rect
ion
ofgl
obal
biai
sJ1
TP
deacutedu
ced
from
inte
rcal
ibra
tion
phas
e(c
ycle
s11
J1)
Mea
npr
o-fil
e(s
eeII
I36
1)
Com
pute
dw
ithcy
cles
11-3
53T
Pda
taan
dw
ithcy
cles
11-2
50J1
data
ref
eren
ced
[199
319
99]
TP
J1 c
ompu
ted
with
cycl
es11
-353
TP
data
and
with
cycl
es11
-250
J1da
tar
efer
ence
d[1
993
1999
]T
PNJ
1Nc
ompu
ted
with
cycl
es36
9-47
9T
PNda
tar
efer
ence
d[1
993
1999
]
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
ref
eren
ced
[199
319
99]
EN
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
re
fere
nced
[199
319
99]
EN
Nu
seof
MSS
_CN
ES_
CL
S11
[39]
Com
pute
dw
ithcy
cles
37-1
87G
2da
ta
refe
renc
ed[1
993
1999
]
Peri
odof
use
from
cycl
e9
from
cycl
e9
cycl
es1
to48
1cy
cles
15to
43In
clud
ing
E-F
geod
etic
phas
es
cycl
es1
to83
from
cycl
e9
cycl
es37
to22
2
Tabl
e7
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(2
2)
Page 34
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III32 Acquisition
The acqusition process in Delayed time is much simpler than in Near Real time it consists in a synchronisa-tion process of all the auxiliary data required to homogenize propely the altimeter data sets The acquisitionstep uses the GDRs or the OPRs provided by the agencies
III33 Homogenization
The Homogenization process consists in applying the most recent corrections models and references rec-ommended for altimeter products Each mission is processed separately as its needs depend on the baseinput data The list of corrections and models currently applied is provided in tables 6 and 7 for DT data
III34 Input data quality control
The Input Data Quality Control is a critical process applied to guarantee that DUACS uses only the mostaccurate altimeter data Thanks to the high quality of current missions this process rejects a small percent-age of altimeter measurements but these erroneous data could be the cause of a significant quality lossThe quality control relies on standard raw data editing with quality flags or parameter thresholds but alsoon complex data editing algorithms based on the detection of erroneous artefacts mono and multi-missioncrossover validation and macroscopic statistics to edit out large data flows that do not meet the systemrsquosrequirements
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PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III35 Multi-mission cross-calibration
The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistentand accurate information It removes any residual orbit error (OE Le Traon and Ogor 1998[32]) or longwavelength error (LWE Le Traon et al 1998[31]) as well as large scale biases and discrepancies betweenvarious data flows
This process is based on two very different algorithms a global multi-mission crossover minimization fororbit error reduction (OER) and Optimal Interpolation (OI) for LWE
Multi-satellite crossover determination is performed on a daily basis All altimeter fields (measurementcorrections and other fields such as bathymetry MSS) are interpolated at crossover locations and datesCrossovers are then appended to the existing crossover database as more altimeter data become availableThis crossover data set is the input of the Orbit Error Reduction (OER) method Using the precision of thereference mission orbit a very accurate orbit error can be estimated LWE is mostly due to residual tidalor inverse barometer errors and high frequency ocean signals The OI used for LWE reduction uses preciseparameters derived from
bull accurate statistical description of sea level variability
bull localized correlation scales
bull mission-specific noise and precise assumptions on the long wavelength errors to be removed (from arecent analysis of one year of data from each mission)
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PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III36 Product generation
The product generation process is composed of four steps computation of raw SLA cross-validationfilteringampsub-sampling and generation of by-products
III361 Computation of raw SLA
Since the geoid is not well known yet the SSH cannot be used directly the SSH anomalies are used insteadThey are computed from the difference of the instantaneous SSH - a temporal reference This temporalreference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeattrack analysis cannot be used The errors affecting the SLAs MPs and MSS have different magnitudes andwavelengths The computation of the SLAs and their errors associated are detailed in Dibarboure et al 2010[9]
Use of a Mean ProfileIn the repeat track analysis (when the satellites flies over a repetitive orbit) measurements are re-sampledalong a theoretical ground track (or mean track) associated to each mission Then a Mean Profile (MP) issubtracted from the re-sampled data to obtain SLA The MP is a time average of similarly re-sampled dataover a long period
bull The Mean Profile used for TP (cycles 1 to 364) Jason-1 (cycles 1 to 259) and Jason-2 is computedwith 10 years of TP (cycles 11 to 353) and 6 years of Jason-1 (cycles 11 to 250)
bull The Mean Profile used for TP (cycles 368 to 481) and from Jason-1 cycle 262 to 374 (where satellitesare on interleaved ground-tracks) is computed with 3 years of TP (cycles 369 to 479)
bull The Mean Profile used for ERS-1 in its 35 days repetitive orbit mission ERS-2 and Envisat (only forthe first orbit before November 2010) is computed with 8 years of ERS-2 (cycles 1 to 85) and 6 yearsof Envisat (cycles 10 to 72)
bull No Mean Profile can be used for Envisat on its new orbit (enn) Jason-1 on its geodetic orbit (j1g)because there is no repetitive track The MSS must be used instead (see below)
bull The Mean Profile used for GFO is computed with 7 years of GFO cycles 37 to 187
Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible
bull Indeed as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide precise cross-track projection andor interpolation schemes are required to avoid errors
bull The mesoscale variability error (which is lt35 cm for MP between 3 to 5 years and lt1cm for WLof 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a prioriknowledge from Sea Level maps derived from previous iterations or from other missions
Page 37
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for ERS-1 for its 168 days geodetic mission (phases E-F from April1994 to March 1995) or for Envisat since november 2010 because the satellite is not in a repetitive orbitphase The alternative is to use the MSS instead The gridded MSS is derived from along track MPs anddata from geodetic phases Thus any error on the MP is also contained in the MSS There are essentially 4types of additional errors on gridded MSS which are hard to quantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
III362 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III363 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
Page 38
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
III37 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III371 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
Page 39
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
IV MYOCEAN PRODUCTS
IV1 Near Real Time Products
The purpose of the NRT DUACS component is the acquisition of altimeter data from various altimeter mis-sions in near-real time (ie within a few days at most) the validation and correction of these altimeter datasets (ie edition and selection update of corrections and homogenization orbit error reduction) in order toproduce each day along-track productsProducts are as follows
Along-track products global and regional (Mediterranean and Black Seas Arctic Ocean and Europeareas)
bull Sea Level Anomaly (NRT-SLA) for each mission with NRT-SLA ephemeris
IV11 Delay of the products
The availability of the products in near real time is three to twelve hours after the measurement for along-track products Those products are delivered every day
IV12 Temporal availibility
The following table presents the available products by mission and by data periodNear real time products
NRT Jason-2 Jason-1 and Jason-1geodetic
Envisat new Cryosat-2
Temporal Time availability ymlowast
ongoingymlowast-20120303 for
repeat track and20120507-ongoing for
geodetic track
ymlowast
2012040820120101
ongoing
NRT-SLA X X X X
lowastym the temporal coverage for NRT products is fluctuating and depends on updates of Delayed Time prod-ucts When DT products are updated (3 to 4 times per year) the oldest NRT products are replaced by thebetter quality DT products so that the 2 series are overlapping on few weeks or few months
IV2 Delayed Time Products
The Delayed Time component of SSALTODUACS system is responsible for the production of processedJason-1 Jason-2 TP Envisat GFO ERS12 and even Geosat data in order to provide a homogeneousinter-calibrated and highly accurate long time series of SLA DT products are more precise than NRT products Two reasons explain this quality difference The firstone is the better intrinsic quality of the POE orbit used in the GDR processing The second reason is that
Page 40
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
in the DT DUACS processing the products can be computed optimally with a centred computation timewindow for OER LWE On the contrary in NRT case future data are not available so the computationtime window is not centred and therefore not optimalAs for NRT products improved altimeter corrections and processing algorithms are used ocean tide modelto correct altimeter data improved methods for orbit error reduction and mapping
Along-Track products global and regional (Mediterranean and Black Seas)
bull Sea Level Anomaly (DT-SLA) for each mission
IV21 Delay of the products
Weekly products are delivered The availability of the products in delayed time is at the best two monthsafter the date of the measurement The product generation needs all the GDR data of all the missions to takeinto account the best corrections as possible The time delay can be longer in the case of a missing mission
IV22 Temporal availibility
The following table presents the available products by mission and by data periodDelayed time SSALTODUACS products
Upd Jason-2 Jason-1new6
Jason-1 GFO Envisatnew6
Envisat ERS-16
ERS-2Topexnew6
Topex
TemporalTimeavailabil-ity
200810ymlowast
200902ymlowast
200204200810
200001200809
201010ymlowast
200210201010
199210200304
200209200510
199209200204
DT-SLA X X X X X X X X X
lowast ym those dates are updated regularly (3 to 4 times per year) and are avalaible when you download thedata at httpwwwmyoceaneuweb24-cataloguephp6 Jason-1 new orbit starting 200809 Envisat new orbit starting 201010 TP new orbit starting 200209 ERS-1The geodetic phases (E-F) are included There are no ERS-1 data between December 23 1993 and April 10 1994(ERS-1 phase D - 2nd ice phase) Note that during that time products are based only on TopexPoseidon data
Page 41
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
V DESCRIPTION OF THE PRODUCT SPECIFICATION
V1 General information
Product Specification SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001
Geographical coverage global
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 20-50km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001 Product Specification
Page 42
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
Product Specification SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002
Geographical coverage 55˚W-35˚E 30˚N-46˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002 Product Specification
Page 43
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
Product Specification SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003
Geographical coverage 27˚E-42˚E 40˚N-47˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003 Product Specification
Page 44
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
Product Specification SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004
Geographical coverage 25˚W-42˚E 21˚N-66˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004 Product Specification
Page 45
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
Product Specification SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005
Geographical coverage 0˚W-360˚E 50˚N-82˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005 Product Specification
Page 46
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
VI NOMENCLATURE OF FILES
VI1 Nomenclature of files downloaded through the MyOcean Web PortalDirectgetfile Service
VI11 Nomenclature of the product line
The description of the syntax for the SL TAC SLA products line is given by
SEALEVEL_ltREGIONgt_SLA_L3_ltDELAYgt_OBSERVATIONS_008_ltZONEgt_ltLETTERgtwhere
REGION GLO global geographic coverage product
BS Black Sea products
MED Mediterranean products
ARC Arctic products (for NRT products)
EUROPE Europe products (for NRT products)
DELAY NRT near real time products
RAN delayed time or reanalysis products
ZONE 001 number on 3 digits
002
003
004
LETTER a letter on 1 digit
b
Page 47
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
VI12 Nomenclature of the datasets
The nomenclature used is
dataset-duacs-ltdelaygt-ltzonegt-ltmissiongt-lttype of slagt-l3where the fileds in ltgt are described below
delay nrt near-real time productsran delayed time products
zone global global geographic coverage productmedsea Mediterranean productsblacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1 (only for ran)e2 ERS-2 (only for ran)tp TOPEXPoseidon (only for ran)tpn TOPEXPoseidon on its new orbit (only for
ran)g2 GFO (only for ran)j1 Jason-1 (only for ran)j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisat (only for ran)enn Envisat on its new orbitc2 Cryosat-2 (only for nrt)
type of sla sla filtered slasla_unfiltered non filtered sla (only for ran products)
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VI13 Nomenclature of the NetCdf files
The nomenclature used is
ltdelaygt_ltzonegt_ltmissiongt_sla_ltvariablegt_ltdatebegingt_ltdateendgt_ltdateprodgtnc where the fileds in ltgt are de-scribed below
delay nrt near-real time productsdt delayed time products
zone global global geographic coverage productmed Mediterranean products (for dt)mfstep Mediterranean products (for nrt)blacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1e2 ERS-2tp TOPEXPoseidontpn TOPEXPoseidon on its new orbitg2 GFOj1 Jason-1j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisatenn Envisat on its new orbitc2 Cryosat-2
variable vfec filtered and sub-sampled slavxxc non filtered and non sub-sampled sla (only
for dt)datebegin YYYYMMDD() beginning date of the datasetdateend YYYYMMDD() end date of the datasetdateprod YYYYMMDD production date of the dataset
() For dt data as the dates in the file names are rounded the user wanting data for date T has to read the filescontaining dates T+1 and T-1 in their name and check inside the files if there are some data for date T
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VII DATA FORMAT
This chapter presents the data storage format used for MyOcean products
VII1 NetCdf
The products are stored using the NetCDF format NetCDF (network Common Data Form) is an interface for array-oriented data access and a library that provides an implementation of the interface The netCDF library also definesa machine-independent format for representing scientific data Together the interface library and format support thecreation access and sharing of scientific data The netCDF software was developed at the Unidata Program Center inBoulder Colorado The netCDF libraries define a machine-independent format for representing scientific data Pleasesee Unidata NetCDF pages for more information and to retreive NetCDF software package onhttpwwwunidataucaredupackagesnetcdfindexhtml
NetCDF data is
bull Self-Describing A netCDF file includes information about the data it contains
bull Architecture-independent A netCDF file is represented in a form that can be accessed by computers with dif-ferent ways of storing integers characters and floating-point numbers
bull Direct-access A small subset of a large dataset may be accessed efficiently without first reading through allthe preceding data
bull Appendable Data can be appended to a netCDF dataset along one dimension without copying the dataset orredefining its structure The structure of a netCDF dataset can be changed though this sometimes causes thedataset to be copied
bull Sharable One writer and multiple readers may simultaneously access the same netCDF file
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VII2 Structure and semantic of NetCDF along-track files
The NetCDF Sea Level TAC files are based on the attribute data tags defined by the Cooperative OceanAtmosphereResearch Data Service (COARDS) and Climate and Forecast (CF) metadata conventions The CF convention gener-alises and extends the COARDS convention but relaxes the COARDS constraints on dimension and order and specifiesmethods for reducing the size of datasetsA wide range of software are available to write or read NetCDFCF files API are made available by UNIDATA(httpwwwunidataucaredusoftwarenetcdf)
bull CC++Fortran
bull Java
bull MATLAB Objective-C Perl Python R Ruby TclTk
In addition to these conventions the files are using a common structure and semantic
bull 1 dimension is defined
ndash time it is used to check NetCDF variables depending on time
bull 8 variables are defined
ndash short SLA contains the Sea Level Anomaly values for each time given
ndash int longitude contains the longitude for each measurement
ndash short track contains the track number for each measurement
ndash double time contains the time in days since 1950-01-01 000000 UTC for each measurement
ndash short mean_profile_point_index index of the corrsponding point in the track of the mean profile
ndash byte flag flag=0 the processed data comes from OGDR if flag=1 the processed data comes from theIGDR
ndash int latitude contains the latitude for each measurement
ndash short cycle contains the cycle number for each measurement
bull global attributes
ndash the global attributes gives information about the creation of the file
Example of a NetCDF sla file
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netcdf nrt_global_j1_sla_vfec_20101230_20101230_20101230 dimensions
time = 10385 variables
short SLA(time) SLAcoordinates = longitude latitude SLAlong_name = Sea Level Anomaly SLA_FillValue = 32767s SLAadd_offset = 0 SLAscale_factor = 0001 SLAunits = m SLAstandard_name = sea_surface_height_above_sea_level
int longitude(time) longitudelong_name = Longitude of measurement longitude_FillValue = 2147483647 longitudeadd_offset = 0 longitudestandard_name = longitude longitudescale_factor = 1e-06 longitudeunits = degrees_east
short track(time) tracklong_name = Track in cycle the measurement belongs to track_FillValue = 32767s trackunits = 1 trackcoordinates = longitude latitude
double time(time) timelong_name = Time of measurement time_FillValue = 184467440737096e+19 timeaxis = T timestandard_name = time timeunits = days since 1950-01-01 000000 UTC
int latitude(time) latitudelong_name = Latitude of measurement latitude_FillValue = 2147483647 latitudeadd_offset = 0 latitudestandard_name = latitude latitudescale_factor = 1e-06 latitudeunits = degrees_north
short flag(time) flagcoordinates = longitude latitude flag_FillValue = 3267s flaglong_name = data origin flagflag_values = 1s 0s flagflag_meanings = igdr_like non_igdr_like flagcomment = The origin of the data is determined by the types of geophysical datarecords (GDR) used in computation of the SLA 1 for the Interim GDR (IGDR) and0 for Operational GDR (OGDR)
short cycle(time) cyclelong_name = Cycle the measurement belongs to cycle_FillValue = 32767s cycleunits = 1 cyclecoordinates = longitude latitude
global attributeshistory = 22-Feb-2011 155243 CET File created by the SSLATODUACS system version 1001 comment = Produce from ENVISAT Extension Phase satellite altimetry data institution = CLSCNES
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references = httpwwwavisooceanobscomfileadmindocumentsdatatoolshdbk_duacspdf source = satellite altimetry title = along track Sea Level Anomaly Conventions = CF-14
dataSLA =
7 7 11 10 -2 -22 -39 -41 -30 -13 -3 -5 -16 -26 -32 -35-35 -35 -37 -35 -31 -29 -31 -35 -32 -21 -10 -10 -19 -20 -1-69 -57 -49 -45 -39 -30 -28 -31 -27 -13 -2 -5 -15 -3 1112 3 -7 -10 -14 -15 -22 -31 -37 -32 -17 -10
longitude =74743328 74868400 74993968 75120040 75246616 7537372875501368 75629568 75758320 75887656 76017568 76148080 7627920876388952 76477056 76565456 76654144 76743128 76832400 76921984329429568 329535424 329641792 329748672 329856096 329964032330072512 330181536 330291072 330401184
track =92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 9292 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92113 113 113 113 113 113 113 113 113 113 113 113 113 113113 113 113 113 113 113 113 113 113
time =222780000565705 222780001314719 222780002063733222780002812747 222780003561761 222780004310775 222780005059788222780005808802 222780006557816 22278000730683 222780008055844222780008804858 222780009553872 22278001017805 222780010677393222788257112198 222788257486705 222788257861212 222788258235719222788258610226 222788258984733 222788259359239 222788259733746222788260108253 22278826048276
mean_profile_point_index =1872 1878 1884 1890 1896 1902 1908 19141920 1926 1932 1938 1944 1949 1953 1957 1961 1965 1969 19732306 2309 2312 2315 2318 2321 2327 2330 2333 2336 2339 23422345 2348 2351 2354 2357 2360 2363 2366
flag =0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
latitude =-16225506 -16539731 -16853833 -17167810 -17481660 -17795380-18108966 -18422418 -18735729 -19048899 -19361924 -19674801-19987527 -20248015 -20456329 -20664569 -20872739 -2108083739481297 39628277 39775133 39921866 40068472 40214953 4036130840507533 40653629 40799592 40945423 41091120 41236684 41382111
cycle =331 331 331 331 331 331 331 331 331 331 331 331 331
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331 331 331 331 331 331 331 331 331 331 331 331 331 331331 331 331 331 331 331 331 331 331 331 331 331
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VIII HOW TO DOWNLOAD A PRODUCT
VIII1 Download a product through the MyOcean Web Portal DirectgetfileService
You first need to register Please find below the registration stepshttpwwwmyoceaneuweb34-products-and-services-faqphp1Once registered the MyOcean FAQ httpwwwmyoceaneuweb34-products-and-services-faqwill guide you on How to download a product through the MyOcean Web Portal Directgetfile Service
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IX NEWS AND UPDATES
IX1 [Duacs] Operational news
To be kept informed on events occurring on the satellites and on the eventual interruption of the services of the DUACSprocessing system see the [Duacs] operational news on the Aviso websitehttpwwwavisooceanobscomendataoperational-newsindexhtml
IX2 Updates
To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtmlSince 2010 a complete reprocessing of all altimetry data (cumulated total of about 55 years of data) is available Themain changes introduced in the Duacs DT v300 reprocessed data set in SSALTODUACS reprocessed DT data setare listed herehttpwwwavisooceanobscomfileadmindocumentsdataduacsduacs_DT_2010_reprocessing_impactpdf
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j2j1
j1n
tptp
ne1
e2en
enn
g2O
cean
tide
GO
T4v
7(S
1an
dS2
are
incl
uded
)Po
letid
e[W
ahr
1985
[53]
]So
lidea
rth
tide
Ela
stic
resp
onse
totid
alpo
tent
ial[
Car
twri
ghta
ndTa
yler
197
1[5]
][C
artw
righ
tand
Edd
en1
973[
6]]
Loa
ding
tide
GO
T4v
7(S
1pa
ram
eter
isin
clud
ed)
Sea
stat
ebi
asN
onpa
ram
etri
cSS
B[G
aspa
reta
l20
02[2
0]]
Non
para
met
ric
SSB
[NT
ran
and
al2
010[
51]]
BM
3[G
aspa
ran
dO
gor
1994
[17]
]
Non
para
met
ric
SSB
[Mer
tzet
al
2005
[38]
]
Non
para
met
ric
SSB
[Gas
pare
tal
2002
]w
ithG
DR
-Bst
anda
rds
forc
ycle
s9
to85
and
with
GD
R-C
stan
dard
sfr
omcy
cle
86
Non
para
met
ric
SSB
[NT
ran
etal
20
10[5
1]]
Orb
iter
ror
Glo
bal m
ulti-
mis
sion
cros
sove
rmin
imiz
atio
n(L
eTr
aon
and
Ogo
r19
98[3
2])
Lon
gw
ave-
leng
her
rors
Opt
imal
Inte
rpol
atio
n(L
eTr
aon
etal
19
98[3
1])
Inte
rcal
ibra
tion
Ref
eren
cefr
omcy
cle
11R
efer
ence
from
cycl
e1
to35
4C
orre
ctio
nof
regi
onal
bias
J2J
1de
duce
dfr
omin
terc
alib
ratio
nph
ase
(cyc
le11
J2)
Cor
rect
ion
ofgl
obal
biai
sJ1
TP
deacutedu
ced
from
inte
rcal
ibra
tion
phas
e(c
ycle
s11
J1)
Mea
npr
o-fil
e(s
eeII
I36
1)
Com
pute
dw
ithcy
cles
11-3
53T
Pda
taan
dw
ithcy
cles
11-2
50J1
data
ref
eren
ced
[199
319
99]
TP
J1 c
ompu
ted
with
cycl
es11
-353
TP
data
and
with
cycl
es11
-250
J1da
tar
efer
ence
d[1
993
1999
]T
PNJ
1Nc
ompu
ted
with
cycl
es36
9-47
9T
PNda
tar
efer
ence
d[1
993
1999
]
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
ref
eren
ced
[199
319
99]
EN
Com
pute
dw
ithcy
cles
1-85
E2
data
and
with
cycl
es10
-72
EN
data
re
fere
nced
[199
319
99]
EN
Nu
seof
MSS
_CN
ES_
CL
S11
[39]
Com
pute
dw
ithcy
cles
37-1
87G
2da
ta
refe
renc
ed[1
993
1999
]
Peri
odof
use
from
cycl
e9
from
cycl
e9
cycl
es1
to48
1cy
cles
15to
43In
clud
ing
E-F
geod
etic
phas
es
cycl
es1
to83
from
cycl
e9
cycl
es37
to22
2
Tabl
e7
Cor
rect
ions
and
mod
els
appl
ied
inSS
ALT
OD
UA
CS
DT
prod
ucts
(gtv3
00
)(2
2)
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III32 Acquisition
The acqusition process in Delayed time is much simpler than in Near Real time it consists in a synchronisa-tion process of all the auxiliary data required to homogenize propely the altimeter data sets The acquisitionstep uses the GDRs or the OPRs provided by the agencies
III33 Homogenization
The Homogenization process consists in applying the most recent corrections models and references rec-ommended for altimeter products Each mission is processed separately as its needs depend on the baseinput data The list of corrections and models currently applied is provided in tables 6 and 7 for DT data
III34 Input data quality control
The Input Data Quality Control is a critical process applied to guarantee that DUACS uses only the mostaccurate altimeter data Thanks to the high quality of current missions this process rejects a small percent-age of altimeter measurements but these erroneous data could be the cause of a significant quality lossThe quality control relies on standard raw data editing with quality flags or parameter thresholds but alsoon complex data editing algorithms based on the detection of erroneous artefacts mono and multi-missioncrossover validation and macroscopic statistics to edit out large data flows that do not meet the systemrsquosrequirements
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III35 Multi-mission cross-calibration
The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistentand accurate information It removes any residual orbit error (OE Le Traon and Ogor 1998[32]) or longwavelength error (LWE Le Traon et al 1998[31]) as well as large scale biases and discrepancies betweenvarious data flows
This process is based on two very different algorithms a global multi-mission crossover minimization fororbit error reduction (OER) and Optimal Interpolation (OI) for LWE
Multi-satellite crossover determination is performed on a daily basis All altimeter fields (measurementcorrections and other fields such as bathymetry MSS) are interpolated at crossover locations and datesCrossovers are then appended to the existing crossover database as more altimeter data become availableThis crossover data set is the input of the Orbit Error Reduction (OER) method Using the precision of thereference mission orbit a very accurate orbit error can be estimated LWE is mostly due to residual tidalor inverse barometer errors and high frequency ocean signals The OI used for LWE reduction uses preciseparameters derived from
bull accurate statistical description of sea level variability
bull localized correlation scales
bull mission-specific noise and precise assumptions on the long wavelength errors to be removed (from arecent analysis of one year of data from each mission)
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III36 Product generation
The product generation process is composed of four steps computation of raw SLA cross-validationfilteringampsub-sampling and generation of by-products
III361 Computation of raw SLA
Since the geoid is not well known yet the SSH cannot be used directly the SSH anomalies are used insteadThey are computed from the difference of the instantaneous SSH - a temporal reference This temporalreference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeattrack analysis cannot be used The errors affecting the SLAs MPs and MSS have different magnitudes andwavelengths The computation of the SLAs and their errors associated are detailed in Dibarboure et al 2010[9]
Use of a Mean ProfileIn the repeat track analysis (when the satellites flies over a repetitive orbit) measurements are re-sampledalong a theoretical ground track (or mean track) associated to each mission Then a Mean Profile (MP) issubtracted from the re-sampled data to obtain SLA The MP is a time average of similarly re-sampled dataover a long period
bull The Mean Profile used for TP (cycles 1 to 364) Jason-1 (cycles 1 to 259) and Jason-2 is computedwith 10 years of TP (cycles 11 to 353) and 6 years of Jason-1 (cycles 11 to 250)
bull The Mean Profile used for TP (cycles 368 to 481) and from Jason-1 cycle 262 to 374 (where satellitesare on interleaved ground-tracks) is computed with 3 years of TP (cycles 369 to 479)
bull The Mean Profile used for ERS-1 in its 35 days repetitive orbit mission ERS-2 and Envisat (only forthe first orbit before November 2010) is computed with 8 years of ERS-2 (cycles 1 to 85) and 6 yearsof Envisat (cycles 10 to 72)
bull No Mean Profile can be used for Envisat on its new orbit (enn) Jason-1 on its geodetic orbit (j1g)because there is no repetitive track The MSS must be used instead (see below)
bull The Mean Profile used for GFO is computed with 7 years of GFO cycles 37 to 187
Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible
bull Indeed as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide precise cross-track projection andor interpolation schemes are required to avoid errors
bull The mesoscale variability error (which is lt35 cm for MP between 3 to 5 years and lt1cm for WLof 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a prioriknowledge from Sea Level maps derived from previous iterations or from other missions
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bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for ERS-1 for its 168 days geodetic mission (phases E-F from April1994 to March 1995) or for Envisat since november 2010 because the satellite is not in a repetitive orbitphase The alternative is to use the MSS instead The gridded MSS is derived from along track MPs anddata from geodetic phases Thus any error on the MP is also contained in the MSS There are essentially 4types of additional errors on gridded MSS which are hard to quantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
III362 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III363 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
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III37 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III371 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
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IV MYOCEAN PRODUCTS
IV1 Near Real Time Products
The purpose of the NRT DUACS component is the acquisition of altimeter data from various altimeter mis-sions in near-real time (ie within a few days at most) the validation and correction of these altimeter datasets (ie edition and selection update of corrections and homogenization orbit error reduction) in order toproduce each day along-track productsProducts are as follows
Along-track products global and regional (Mediterranean and Black Seas Arctic Ocean and Europeareas)
bull Sea Level Anomaly (NRT-SLA) for each mission with NRT-SLA ephemeris
IV11 Delay of the products
The availability of the products in near real time is three to twelve hours after the measurement for along-track products Those products are delivered every day
IV12 Temporal availibility
The following table presents the available products by mission and by data periodNear real time products
NRT Jason-2 Jason-1 and Jason-1geodetic
Envisat new Cryosat-2
Temporal Time availability ymlowast
ongoingymlowast-20120303 for
repeat track and20120507-ongoing for
geodetic track
ymlowast
2012040820120101
ongoing
NRT-SLA X X X X
lowastym the temporal coverage for NRT products is fluctuating and depends on updates of Delayed Time prod-ucts When DT products are updated (3 to 4 times per year) the oldest NRT products are replaced by thebetter quality DT products so that the 2 series are overlapping on few weeks or few months
IV2 Delayed Time Products
The Delayed Time component of SSALTODUACS system is responsible for the production of processedJason-1 Jason-2 TP Envisat GFO ERS12 and even Geosat data in order to provide a homogeneousinter-calibrated and highly accurate long time series of SLA DT products are more precise than NRT products Two reasons explain this quality difference The firstone is the better intrinsic quality of the POE orbit used in the GDR processing The second reason is that
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in the DT DUACS processing the products can be computed optimally with a centred computation timewindow for OER LWE On the contrary in NRT case future data are not available so the computationtime window is not centred and therefore not optimalAs for NRT products improved altimeter corrections and processing algorithms are used ocean tide modelto correct altimeter data improved methods for orbit error reduction and mapping
Along-Track products global and regional (Mediterranean and Black Seas)
bull Sea Level Anomaly (DT-SLA) for each mission
IV21 Delay of the products
Weekly products are delivered The availability of the products in delayed time is at the best two monthsafter the date of the measurement The product generation needs all the GDR data of all the missions to takeinto account the best corrections as possible The time delay can be longer in the case of a missing mission
IV22 Temporal availibility
The following table presents the available products by mission and by data periodDelayed time SSALTODUACS products
Upd Jason-2 Jason-1new6
Jason-1 GFO Envisatnew6
Envisat ERS-16
ERS-2Topexnew6
Topex
TemporalTimeavailabil-ity
200810ymlowast
200902ymlowast
200204200810
200001200809
201010ymlowast
200210201010
199210200304
200209200510
199209200204
DT-SLA X X X X X X X X X
lowast ym those dates are updated regularly (3 to 4 times per year) and are avalaible when you download thedata at httpwwwmyoceaneuweb24-cataloguephp6 Jason-1 new orbit starting 200809 Envisat new orbit starting 201010 TP new orbit starting 200209 ERS-1The geodetic phases (E-F) are included There are no ERS-1 data between December 23 1993 and April 10 1994(ERS-1 phase D - 2nd ice phase) Note that during that time products are based only on TopexPoseidon data
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V DESCRIPTION OF THE PRODUCT SPECIFICATION
V1 General information
Product Specification SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001
Geographical coverage global
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 20-50km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001 Product Specification
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Product Specification SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002
Geographical coverage 55˚W-35˚E 30˚N-46˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002 Product Specification
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Product Specification SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003
Geographical coverage 27˚E-42˚E 40˚N-47˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003 Product Specification
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Product Specification SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004
Geographical coverage 25˚W-42˚E 21˚N-66˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004 Product Specification
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Product Specification SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005
Geographical coverage 0˚W-360˚E 50˚N-82˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005 Product Specification
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VI NOMENCLATURE OF FILES
VI1 Nomenclature of files downloaded through the MyOcean Web PortalDirectgetfile Service
VI11 Nomenclature of the product line
The description of the syntax for the SL TAC SLA products line is given by
SEALEVEL_ltREGIONgt_SLA_L3_ltDELAYgt_OBSERVATIONS_008_ltZONEgt_ltLETTERgtwhere
REGION GLO global geographic coverage product
BS Black Sea products
MED Mediterranean products
ARC Arctic products (for NRT products)
EUROPE Europe products (for NRT products)
DELAY NRT near real time products
RAN delayed time or reanalysis products
ZONE 001 number on 3 digits
002
003
004
LETTER a letter on 1 digit
b
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VI12 Nomenclature of the datasets
The nomenclature used is
dataset-duacs-ltdelaygt-ltzonegt-ltmissiongt-lttype of slagt-l3where the fileds in ltgt are described below
delay nrt near-real time productsran delayed time products
zone global global geographic coverage productmedsea Mediterranean productsblacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1 (only for ran)e2 ERS-2 (only for ran)tp TOPEXPoseidon (only for ran)tpn TOPEXPoseidon on its new orbit (only for
ran)g2 GFO (only for ran)j1 Jason-1 (only for ran)j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisat (only for ran)enn Envisat on its new orbitc2 Cryosat-2 (only for nrt)
type of sla sla filtered slasla_unfiltered non filtered sla (only for ran products)
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VI13 Nomenclature of the NetCdf files
The nomenclature used is
ltdelaygt_ltzonegt_ltmissiongt_sla_ltvariablegt_ltdatebegingt_ltdateendgt_ltdateprodgtnc where the fileds in ltgt are de-scribed below
delay nrt near-real time productsdt delayed time products
zone global global geographic coverage productmed Mediterranean products (for dt)mfstep Mediterranean products (for nrt)blacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1e2 ERS-2tp TOPEXPoseidontpn TOPEXPoseidon on its new orbitg2 GFOj1 Jason-1j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisatenn Envisat on its new orbitc2 Cryosat-2
variable vfec filtered and sub-sampled slavxxc non filtered and non sub-sampled sla (only
for dt)datebegin YYYYMMDD() beginning date of the datasetdateend YYYYMMDD() end date of the datasetdateprod YYYYMMDD production date of the dataset
() For dt data as the dates in the file names are rounded the user wanting data for date T has to read the filescontaining dates T+1 and T-1 in their name and check inside the files if there are some data for date T
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VII DATA FORMAT
This chapter presents the data storage format used for MyOcean products
VII1 NetCdf
The products are stored using the NetCDF format NetCDF (network Common Data Form) is an interface for array-oriented data access and a library that provides an implementation of the interface The netCDF library also definesa machine-independent format for representing scientific data Together the interface library and format support thecreation access and sharing of scientific data The netCDF software was developed at the Unidata Program Center inBoulder Colorado The netCDF libraries define a machine-independent format for representing scientific data Pleasesee Unidata NetCDF pages for more information and to retreive NetCDF software package onhttpwwwunidataucaredupackagesnetcdfindexhtml
NetCDF data is
bull Self-Describing A netCDF file includes information about the data it contains
bull Architecture-independent A netCDF file is represented in a form that can be accessed by computers with dif-ferent ways of storing integers characters and floating-point numbers
bull Direct-access A small subset of a large dataset may be accessed efficiently without first reading through allthe preceding data
bull Appendable Data can be appended to a netCDF dataset along one dimension without copying the dataset orredefining its structure The structure of a netCDF dataset can be changed though this sometimes causes thedataset to be copied
bull Sharable One writer and multiple readers may simultaneously access the same netCDF file
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VII2 Structure and semantic of NetCDF along-track files
The NetCDF Sea Level TAC files are based on the attribute data tags defined by the Cooperative OceanAtmosphereResearch Data Service (COARDS) and Climate and Forecast (CF) metadata conventions The CF convention gener-alises and extends the COARDS convention but relaxes the COARDS constraints on dimension and order and specifiesmethods for reducing the size of datasetsA wide range of software are available to write or read NetCDFCF files API are made available by UNIDATA(httpwwwunidataucaredusoftwarenetcdf)
bull CC++Fortran
bull Java
bull MATLAB Objective-C Perl Python R Ruby TclTk
In addition to these conventions the files are using a common structure and semantic
bull 1 dimension is defined
ndash time it is used to check NetCDF variables depending on time
bull 8 variables are defined
ndash short SLA contains the Sea Level Anomaly values for each time given
ndash int longitude contains the longitude for each measurement
ndash short track contains the track number for each measurement
ndash double time contains the time in days since 1950-01-01 000000 UTC for each measurement
ndash short mean_profile_point_index index of the corrsponding point in the track of the mean profile
ndash byte flag flag=0 the processed data comes from OGDR if flag=1 the processed data comes from theIGDR
ndash int latitude contains the latitude for each measurement
ndash short cycle contains the cycle number for each measurement
bull global attributes
ndash the global attributes gives information about the creation of the file
Example of a NetCDF sla file
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netcdf nrt_global_j1_sla_vfec_20101230_20101230_20101230 dimensions
time = 10385 variables
short SLA(time) SLAcoordinates = longitude latitude SLAlong_name = Sea Level Anomaly SLA_FillValue = 32767s SLAadd_offset = 0 SLAscale_factor = 0001 SLAunits = m SLAstandard_name = sea_surface_height_above_sea_level
int longitude(time) longitudelong_name = Longitude of measurement longitude_FillValue = 2147483647 longitudeadd_offset = 0 longitudestandard_name = longitude longitudescale_factor = 1e-06 longitudeunits = degrees_east
short track(time) tracklong_name = Track in cycle the measurement belongs to track_FillValue = 32767s trackunits = 1 trackcoordinates = longitude latitude
double time(time) timelong_name = Time of measurement time_FillValue = 184467440737096e+19 timeaxis = T timestandard_name = time timeunits = days since 1950-01-01 000000 UTC
int latitude(time) latitudelong_name = Latitude of measurement latitude_FillValue = 2147483647 latitudeadd_offset = 0 latitudestandard_name = latitude latitudescale_factor = 1e-06 latitudeunits = degrees_north
short flag(time) flagcoordinates = longitude latitude flag_FillValue = 3267s flaglong_name = data origin flagflag_values = 1s 0s flagflag_meanings = igdr_like non_igdr_like flagcomment = The origin of the data is determined by the types of geophysical datarecords (GDR) used in computation of the SLA 1 for the Interim GDR (IGDR) and0 for Operational GDR (OGDR)
short cycle(time) cyclelong_name = Cycle the measurement belongs to cycle_FillValue = 32767s cycleunits = 1 cyclecoordinates = longitude latitude
global attributeshistory = 22-Feb-2011 155243 CET File created by the SSLATODUACS system version 1001 comment = Produce from ENVISAT Extension Phase satellite altimetry data institution = CLSCNES
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references = httpwwwavisooceanobscomfileadmindocumentsdatatoolshdbk_duacspdf source = satellite altimetry title = along track Sea Level Anomaly Conventions = CF-14
dataSLA =
7 7 11 10 -2 -22 -39 -41 -30 -13 -3 -5 -16 -26 -32 -35-35 -35 -37 -35 -31 -29 -31 -35 -32 -21 -10 -10 -19 -20 -1-69 -57 -49 -45 -39 -30 -28 -31 -27 -13 -2 -5 -15 -3 1112 3 -7 -10 -14 -15 -22 -31 -37 -32 -17 -10
longitude =74743328 74868400 74993968 75120040 75246616 7537372875501368 75629568 75758320 75887656 76017568 76148080 7627920876388952 76477056 76565456 76654144 76743128 76832400 76921984329429568 329535424 329641792 329748672 329856096 329964032330072512 330181536 330291072 330401184
track =92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 9292 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92113 113 113 113 113 113 113 113 113 113 113 113 113 113113 113 113 113 113 113 113 113 113
time =222780000565705 222780001314719 222780002063733222780002812747 222780003561761 222780004310775 222780005059788222780005808802 222780006557816 22278000730683 222780008055844222780008804858 222780009553872 22278001017805 222780010677393222788257112198 222788257486705 222788257861212 222788258235719222788258610226 222788258984733 222788259359239 222788259733746222788260108253 22278826048276
mean_profile_point_index =1872 1878 1884 1890 1896 1902 1908 19141920 1926 1932 1938 1944 1949 1953 1957 1961 1965 1969 19732306 2309 2312 2315 2318 2321 2327 2330 2333 2336 2339 23422345 2348 2351 2354 2357 2360 2363 2366
flag =0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
latitude =-16225506 -16539731 -16853833 -17167810 -17481660 -17795380-18108966 -18422418 -18735729 -19048899 -19361924 -19674801-19987527 -20248015 -20456329 -20664569 -20872739 -2108083739481297 39628277 39775133 39921866 40068472 40214953 4036130840507533 40653629 40799592 40945423 41091120 41236684 41382111
cycle =331 331 331 331 331 331 331 331 331 331 331 331 331
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331 331 331 331 331 331 331 331 331 331 331 331 331 331331 331 331 331 331 331 331 331 331 331 331 331
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VIII HOW TO DOWNLOAD A PRODUCT
VIII1 Download a product through the MyOcean Web Portal DirectgetfileService
You first need to register Please find below the registration stepshttpwwwmyoceaneuweb34-products-and-services-faqphp1Once registered the MyOcean FAQ httpwwwmyoceaneuweb34-products-and-services-faqwill guide you on How to download a product through the MyOcean Web Portal Directgetfile Service
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IX NEWS AND UPDATES
IX1 [Duacs] Operational news
To be kept informed on events occurring on the satellites and on the eventual interruption of the services of the DUACSprocessing system see the [Duacs] operational news on the Aviso websitehttpwwwavisooceanobscomendataoperational-newsindexhtml
IX2 Updates
To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtmlSince 2010 a complete reprocessing of all altimetry data (cumulated total of about 55 years of data) is available Themain changes introduced in the Duacs DT v300 reprocessed data set in SSALTODUACS reprocessed DT data setare listed herehttpwwwavisooceanobscomfileadmindocumentsdataduacsduacs_DT_2010_reprocessing_impactpdf
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III32 Acquisition
The acqusition process in Delayed time is much simpler than in Near Real time it consists in a synchronisa-tion process of all the auxiliary data required to homogenize propely the altimeter data sets The acquisitionstep uses the GDRs or the OPRs provided by the agencies
III33 Homogenization
The Homogenization process consists in applying the most recent corrections models and references rec-ommended for altimeter products Each mission is processed separately as its needs depend on the baseinput data The list of corrections and models currently applied is provided in tables 6 and 7 for DT data
III34 Input data quality control
The Input Data Quality Control is a critical process applied to guarantee that DUACS uses only the mostaccurate altimeter data Thanks to the high quality of current missions this process rejects a small percent-age of altimeter measurements but these erroneous data could be the cause of a significant quality lossThe quality control relies on standard raw data editing with quality flags or parameter thresholds but alsoon complex data editing algorithms based on the detection of erroneous artefacts mono and multi-missioncrossover validation and macroscopic statistics to edit out large data flows that do not meet the systemrsquosrequirements
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III35 Multi-mission cross-calibration
The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistentand accurate information It removes any residual orbit error (OE Le Traon and Ogor 1998[32]) or longwavelength error (LWE Le Traon et al 1998[31]) as well as large scale biases and discrepancies betweenvarious data flows
This process is based on two very different algorithms a global multi-mission crossover minimization fororbit error reduction (OER) and Optimal Interpolation (OI) for LWE
Multi-satellite crossover determination is performed on a daily basis All altimeter fields (measurementcorrections and other fields such as bathymetry MSS) are interpolated at crossover locations and datesCrossovers are then appended to the existing crossover database as more altimeter data become availableThis crossover data set is the input of the Orbit Error Reduction (OER) method Using the precision of thereference mission orbit a very accurate orbit error can be estimated LWE is mostly due to residual tidalor inverse barometer errors and high frequency ocean signals The OI used for LWE reduction uses preciseparameters derived from
bull accurate statistical description of sea level variability
bull localized correlation scales
bull mission-specific noise and precise assumptions on the long wavelength errors to be removed (from arecent analysis of one year of data from each mission)
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III36 Product generation
The product generation process is composed of four steps computation of raw SLA cross-validationfilteringampsub-sampling and generation of by-products
III361 Computation of raw SLA
Since the geoid is not well known yet the SSH cannot be used directly the SSH anomalies are used insteadThey are computed from the difference of the instantaneous SSH - a temporal reference This temporalreference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeattrack analysis cannot be used The errors affecting the SLAs MPs and MSS have different magnitudes andwavelengths The computation of the SLAs and their errors associated are detailed in Dibarboure et al 2010[9]
Use of a Mean ProfileIn the repeat track analysis (when the satellites flies over a repetitive orbit) measurements are re-sampledalong a theoretical ground track (or mean track) associated to each mission Then a Mean Profile (MP) issubtracted from the re-sampled data to obtain SLA The MP is a time average of similarly re-sampled dataover a long period
bull The Mean Profile used for TP (cycles 1 to 364) Jason-1 (cycles 1 to 259) and Jason-2 is computedwith 10 years of TP (cycles 11 to 353) and 6 years of Jason-1 (cycles 11 to 250)
bull The Mean Profile used for TP (cycles 368 to 481) and from Jason-1 cycle 262 to 374 (where satellitesare on interleaved ground-tracks) is computed with 3 years of TP (cycles 369 to 479)
bull The Mean Profile used for ERS-1 in its 35 days repetitive orbit mission ERS-2 and Envisat (only forthe first orbit before November 2010) is computed with 8 years of ERS-2 (cycles 1 to 85) and 6 yearsof Envisat (cycles 10 to 72)
bull No Mean Profile can be used for Envisat on its new orbit (enn) Jason-1 on its geodetic orbit (j1g)because there is no repetitive track The MSS must be used instead (see below)
bull The Mean Profile used for GFO is computed with 7 years of GFO cycles 37 to 187
Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible
bull Indeed as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide precise cross-track projection andor interpolation schemes are required to avoid errors
bull The mesoscale variability error (which is lt35 cm for MP between 3 to 5 years and lt1cm for WLof 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a prioriknowledge from Sea Level maps derived from previous iterations or from other missions
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bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for ERS-1 for its 168 days geodetic mission (phases E-F from April1994 to March 1995) or for Envisat since november 2010 because the satellite is not in a repetitive orbitphase The alternative is to use the MSS instead The gridded MSS is derived from along track MPs anddata from geodetic phases Thus any error on the MP is also contained in the MSS There are essentially 4types of additional errors on gridded MSS which are hard to quantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
III362 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III363 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
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III37 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III371 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
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IV MYOCEAN PRODUCTS
IV1 Near Real Time Products
The purpose of the NRT DUACS component is the acquisition of altimeter data from various altimeter mis-sions in near-real time (ie within a few days at most) the validation and correction of these altimeter datasets (ie edition and selection update of corrections and homogenization orbit error reduction) in order toproduce each day along-track productsProducts are as follows
Along-track products global and regional (Mediterranean and Black Seas Arctic Ocean and Europeareas)
bull Sea Level Anomaly (NRT-SLA) for each mission with NRT-SLA ephemeris
IV11 Delay of the products
The availability of the products in near real time is three to twelve hours after the measurement for along-track products Those products are delivered every day
IV12 Temporal availibility
The following table presents the available products by mission and by data periodNear real time products
NRT Jason-2 Jason-1 and Jason-1geodetic
Envisat new Cryosat-2
Temporal Time availability ymlowast
ongoingymlowast-20120303 for
repeat track and20120507-ongoing for
geodetic track
ymlowast
2012040820120101
ongoing
NRT-SLA X X X X
lowastym the temporal coverage for NRT products is fluctuating and depends on updates of Delayed Time prod-ucts When DT products are updated (3 to 4 times per year) the oldest NRT products are replaced by thebetter quality DT products so that the 2 series are overlapping on few weeks or few months
IV2 Delayed Time Products
The Delayed Time component of SSALTODUACS system is responsible for the production of processedJason-1 Jason-2 TP Envisat GFO ERS12 and even Geosat data in order to provide a homogeneousinter-calibrated and highly accurate long time series of SLA DT products are more precise than NRT products Two reasons explain this quality difference The firstone is the better intrinsic quality of the POE orbit used in the GDR processing The second reason is that
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in the DT DUACS processing the products can be computed optimally with a centred computation timewindow for OER LWE On the contrary in NRT case future data are not available so the computationtime window is not centred and therefore not optimalAs for NRT products improved altimeter corrections and processing algorithms are used ocean tide modelto correct altimeter data improved methods for orbit error reduction and mapping
Along-Track products global and regional (Mediterranean and Black Seas)
bull Sea Level Anomaly (DT-SLA) for each mission
IV21 Delay of the products
Weekly products are delivered The availability of the products in delayed time is at the best two monthsafter the date of the measurement The product generation needs all the GDR data of all the missions to takeinto account the best corrections as possible The time delay can be longer in the case of a missing mission
IV22 Temporal availibility
The following table presents the available products by mission and by data periodDelayed time SSALTODUACS products
Upd Jason-2 Jason-1new6
Jason-1 GFO Envisatnew6
Envisat ERS-16
ERS-2Topexnew6
Topex
TemporalTimeavailabil-ity
200810ymlowast
200902ymlowast
200204200810
200001200809
201010ymlowast
200210201010
199210200304
200209200510
199209200204
DT-SLA X X X X X X X X X
lowast ym those dates are updated regularly (3 to 4 times per year) and are avalaible when you download thedata at httpwwwmyoceaneuweb24-cataloguephp6 Jason-1 new orbit starting 200809 Envisat new orbit starting 201010 TP new orbit starting 200209 ERS-1The geodetic phases (E-F) are included There are no ERS-1 data between December 23 1993 and April 10 1994(ERS-1 phase D - 2nd ice phase) Note that during that time products are based only on TopexPoseidon data
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V DESCRIPTION OF THE PRODUCT SPECIFICATION
V1 General information
Product Specification SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001
Geographical coverage global
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 20-50km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001 Product Specification
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Product Specification SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002
Geographical coverage 55˚W-35˚E 30˚N-46˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002 Product Specification
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Product Specification SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003
Geographical coverage 27˚E-42˚E 40˚N-47˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003 Product Specification
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Product Specification SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004
Geographical coverage 25˚W-42˚E 21˚N-66˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004 Product Specification
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Product Specification SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005
Geographical coverage 0˚W-360˚E 50˚N-82˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005 Product Specification
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VI NOMENCLATURE OF FILES
VI1 Nomenclature of files downloaded through the MyOcean Web PortalDirectgetfile Service
VI11 Nomenclature of the product line
The description of the syntax for the SL TAC SLA products line is given by
SEALEVEL_ltREGIONgt_SLA_L3_ltDELAYgt_OBSERVATIONS_008_ltZONEgt_ltLETTERgtwhere
REGION GLO global geographic coverage product
BS Black Sea products
MED Mediterranean products
ARC Arctic products (for NRT products)
EUROPE Europe products (for NRT products)
DELAY NRT near real time products
RAN delayed time or reanalysis products
ZONE 001 number on 3 digits
002
003
004
LETTER a letter on 1 digit
b
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VI12 Nomenclature of the datasets
The nomenclature used is
dataset-duacs-ltdelaygt-ltzonegt-ltmissiongt-lttype of slagt-l3where the fileds in ltgt are described below
delay nrt near-real time productsran delayed time products
zone global global geographic coverage productmedsea Mediterranean productsblacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1 (only for ran)e2 ERS-2 (only for ran)tp TOPEXPoseidon (only for ran)tpn TOPEXPoseidon on its new orbit (only for
ran)g2 GFO (only for ran)j1 Jason-1 (only for ran)j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisat (only for ran)enn Envisat on its new orbitc2 Cryosat-2 (only for nrt)
type of sla sla filtered slasla_unfiltered non filtered sla (only for ran products)
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VI13 Nomenclature of the NetCdf files
The nomenclature used is
ltdelaygt_ltzonegt_ltmissiongt_sla_ltvariablegt_ltdatebegingt_ltdateendgt_ltdateprodgtnc where the fileds in ltgt are de-scribed below
delay nrt near-real time productsdt delayed time products
zone global global geographic coverage productmed Mediterranean products (for dt)mfstep Mediterranean products (for nrt)blacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1e2 ERS-2tp TOPEXPoseidontpn TOPEXPoseidon on its new orbitg2 GFOj1 Jason-1j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisatenn Envisat on its new orbitc2 Cryosat-2
variable vfec filtered and sub-sampled slavxxc non filtered and non sub-sampled sla (only
for dt)datebegin YYYYMMDD() beginning date of the datasetdateend YYYYMMDD() end date of the datasetdateprod YYYYMMDD production date of the dataset
() For dt data as the dates in the file names are rounded the user wanting data for date T has to read the filescontaining dates T+1 and T-1 in their name and check inside the files if there are some data for date T
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VII DATA FORMAT
This chapter presents the data storage format used for MyOcean products
VII1 NetCdf
The products are stored using the NetCDF format NetCDF (network Common Data Form) is an interface for array-oriented data access and a library that provides an implementation of the interface The netCDF library also definesa machine-independent format for representing scientific data Together the interface library and format support thecreation access and sharing of scientific data The netCDF software was developed at the Unidata Program Center inBoulder Colorado The netCDF libraries define a machine-independent format for representing scientific data Pleasesee Unidata NetCDF pages for more information and to retreive NetCDF software package onhttpwwwunidataucaredupackagesnetcdfindexhtml
NetCDF data is
bull Self-Describing A netCDF file includes information about the data it contains
bull Architecture-independent A netCDF file is represented in a form that can be accessed by computers with dif-ferent ways of storing integers characters and floating-point numbers
bull Direct-access A small subset of a large dataset may be accessed efficiently without first reading through allthe preceding data
bull Appendable Data can be appended to a netCDF dataset along one dimension without copying the dataset orredefining its structure The structure of a netCDF dataset can be changed though this sometimes causes thedataset to be copied
bull Sharable One writer and multiple readers may simultaneously access the same netCDF file
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VII2 Structure and semantic of NetCDF along-track files
The NetCDF Sea Level TAC files are based on the attribute data tags defined by the Cooperative OceanAtmosphereResearch Data Service (COARDS) and Climate and Forecast (CF) metadata conventions The CF convention gener-alises and extends the COARDS convention but relaxes the COARDS constraints on dimension and order and specifiesmethods for reducing the size of datasetsA wide range of software are available to write or read NetCDFCF files API are made available by UNIDATA(httpwwwunidataucaredusoftwarenetcdf)
bull CC++Fortran
bull Java
bull MATLAB Objective-C Perl Python R Ruby TclTk
In addition to these conventions the files are using a common structure and semantic
bull 1 dimension is defined
ndash time it is used to check NetCDF variables depending on time
bull 8 variables are defined
ndash short SLA contains the Sea Level Anomaly values for each time given
ndash int longitude contains the longitude for each measurement
ndash short track contains the track number for each measurement
ndash double time contains the time in days since 1950-01-01 000000 UTC for each measurement
ndash short mean_profile_point_index index of the corrsponding point in the track of the mean profile
ndash byte flag flag=0 the processed data comes from OGDR if flag=1 the processed data comes from theIGDR
ndash int latitude contains the latitude for each measurement
ndash short cycle contains the cycle number for each measurement
bull global attributes
ndash the global attributes gives information about the creation of the file
Example of a NetCDF sla file
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netcdf nrt_global_j1_sla_vfec_20101230_20101230_20101230 dimensions
time = 10385 variables
short SLA(time) SLAcoordinates = longitude latitude SLAlong_name = Sea Level Anomaly SLA_FillValue = 32767s SLAadd_offset = 0 SLAscale_factor = 0001 SLAunits = m SLAstandard_name = sea_surface_height_above_sea_level
int longitude(time) longitudelong_name = Longitude of measurement longitude_FillValue = 2147483647 longitudeadd_offset = 0 longitudestandard_name = longitude longitudescale_factor = 1e-06 longitudeunits = degrees_east
short track(time) tracklong_name = Track in cycle the measurement belongs to track_FillValue = 32767s trackunits = 1 trackcoordinates = longitude latitude
double time(time) timelong_name = Time of measurement time_FillValue = 184467440737096e+19 timeaxis = T timestandard_name = time timeunits = days since 1950-01-01 000000 UTC
int latitude(time) latitudelong_name = Latitude of measurement latitude_FillValue = 2147483647 latitudeadd_offset = 0 latitudestandard_name = latitude latitudescale_factor = 1e-06 latitudeunits = degrees_north
short flag(time) flagcoordinates = longitude latitude flag_FillValue = 3267s flaglong_name = data origin flagflag_values = 1s 0s flagflag_meanings = igdr_like non_igdr_like flagcomment = The origin of the data is determined by the types of geophysical datarecords (GDR) used in computation of the SLA 1 for the Interim GDR (IGDR) and0 for Operational GDR (OGDR)
short cycle(time) cyclelong_name = Cycle the measurement belongs to cycle_FillValue = 32767s cycleunits = 1 cyclecoordinates = longitude latitude
global attributeshistory = 22-Feb-2011 155243 CET File created by the SSLATODUACS system version 1001 comment = Produce from ENVISAT Extension Phase satellite altimetry data institution = CLSCNES
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references = httpwwwavisooceanobscomfileadmindocumentsdatatoolshdbk_duacspdf source = satellite altimetry title = along track Sea Level Anomaly Conventions = CF-14
dataSLA =
7 7 11 10 -2 -22 -39 -41 -30 -13 -3 -5 -16 -26 -32 -35-35 -35 -37 -35 -31 -29 -31 -35 -32 -21 -10 -10 -19 -20 -1-69 -57 -49 -45 -39 -30 -28 -31 -27 -13 -2 -5 -15 -3 1112 3 -7 -10 -14 -15 -22 -31 -37 -32 -17 -10
longitude =74743328 74868400 74993968 75120040 75246616 7537372875501368 75629568 75758320 75887656 76017568 76148080 7627920876388952 76477056 76565456 76654144 76743128 76832400 76921984329429568 329535424 329641792 329748672 329856096 329964032330072512 330181536 330291072 330401184
track =92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 9292 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92113 113 113 113 113 113 113 113 113 113 113 113 113 113113 113 113 113 113 113 113 113 113
time =222780000565705 222780001314719 222780002063733222780002812747 222780003561761 222780004310775 222780005059788222780005808802 222780006557816 22278000730683 222780008055844222780008804858 222780009553872 22278001017805 222780010677393222788257112198 222788257486705 222788257861212 222788258235719222788258610226 222788258984733 222788259359239 222788259733746222788260108253 22278826048276
mean_profile_point_index =1872 1878 1884 1890 1896 1902 1908 19141920 1926 1932 1938 1944 1949 1953 1957 1961 1965 1969 19732306 2309 2312 2315 2318 2321 2327 2330 2333 2336 2339 23422345 2348 2351 2354 2357 2360 2363 2366
flag =0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
latitude =-16225506 -16539731 -16853833 -17167810 -17481660 -17795380-18108966 -18422418 -18735729 -19048899 -19361924 -19674801-19987527 -20248015 -20456329 -20664569 -20872739 -2108083739481297 39628277 39775133 39921866 40068472 40214953 4036130840507533 40653629 40799592 40945423 41091120 41236684 41382111
cycle =331 331 331 331 331 331 331 331 331 331 331 331 331
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331 331 331 331 331 331 331 331 331 331 331 331 331 331331 331 331 331 331 331 331 331 331 331 331 331
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VIII HOW TO DOWNLOAD A PRODUCT
VIII1 Download a product through the MyOcean Web Portal DirectgetfileService
You first need to register Please find below the registration stepshttpwwwmyoceaneuweb34-products-and-services-faqphp1Once registered the MyOcean FAQ httpwwwmyoceaneuweb34-products-and-services-faqwill guide you on How to download a product through the MyOcean Web Portal Directgetfile Service
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IX NEWS AND UPDATES
IX1 [Duacs] Operational news
To be kept informed on events occurring on the satellites and on the eventual interruption of the services of the DUACSprocessing system see the [Duacs] operational news on the Aviso websitehttpwwwavisooceanobscomendataoperational-newsindexhtml
IX2 Updates
To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtmlSince 2010 a complete reprocessing of all altimetry data (cumulated total of about 55 years of data) is available Themain changes introduced in the Duacs DT v300 reprocessed data set in SSALTODUACS reprocessed DT data setare listed herehttpwwwavisooceanobscomfileadmindocumentsdataduacsduacs_DT_2010_reprocessing_impactpdf
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III35 Multi-mission cross-calibration
The Multi-mission Cross-calibration process ensures that all flows from all satellites provide a consistentand accurate information It removes any residual orbit error (OE Le Traon and Ogor 1998[32]) or longwavelength error (LWE Le Traon et al 1998[31]) as well as large scale biases and discrepancies betweenvarious data flows
This process is based on two very different algorithms a global multi-mission crossover minimization fororbit error reduction (OER) and Optimal Interpolation (OI) for LWE
Multi-satellite crossover determination is performed on a daily basis All altimeter fields (measurementcorrections and other fields such as bathymetry MSS) are interpolated at crossover locations and datesCrossovers are then appended to the existing crossover database as more altimeter data become availableThis crossover data set is the input of the Orbit Error Reduction (OER) method Using the precision of thereference mission orbit a very accurate orbit error can be estimated LWE is mostly due to residual tidalor inverse barometer errors and high frequency ocean signals The OI used for LWE reduction uses preciseparameters derived from
bull accurate statistical description of sea level variability
bull localized correlation scales
bull mission-specific noise and precise assumptions on the long wavelength errors to be removed (from arecent analysis of one year of data from each mission)
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III36 Product generation
The product generation process is composed of four steps computation of raw SLA cross-validationfilteringampsub-sampling and generation of by-products
III361 Computation of raw SLA
Since the geoid is not well known yet the SSH cannot be used directly the SSH anomalies are used insteadThey are computed from the difference of the instantaneous SSH - a temporal reference This temporalreference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeattrack analysis cannot be used The errors affecting the SLAs MPs and MSS have different magnitudes andwavelengths The computation of the SLAs and their errors associated are detailed in Dibarboure et al 2010[9]
Use of a Mean ProfileIn the repeat track analysis (when the satellites flies over a repetitive orbit) measurements are re-sampledalong a theoretical ground track (or mean track) associated to each mission Then a Mean Profile (MP) issubtracted from the re-sampled data to obtain SLA The MP is a time average of similarly re-sampled dataover a long period
bull The Mean Profile used for TP (cycles 1 to 364) Jason-1 (cycles 1 to 259) and Jason-2 is computedwith 10 years of TP (cycles 11 to 353) and 6 years of Jason-1 (cycles 11 to 250)
bull The Mean Profile used for TP (cycles 368 to 481) and from Jason-1 cycle 262 to 374 (where satellitesare on interleaved ground-tracks) is computed with 3 years of TP (cycles 369 to 479)
bull The Mean Profile used for ERS-1 in its 35 days repetitive orbit mission ERS-2 and Envisat (only forthe first orbit before November 2010) is computed with 8 years of ERS-2 (cycles 1 to 85) and 6 yearsof Envisat (cycles 10 to 72)
bull No Mean Profile can be used for Envisat on its new orbit (enn) Jason-1 on its geodetic orbit (j1g)because there is no repetitive track The MSS must be used instead (see below)
bull The Mean Profile used for GFO is computed with 7 years of GFO cycles 37 to 187
Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible
bull Indeed as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide precise cross-track projection andor interpolation schemes are required to avoid errors
bull The mesoscale variability error (which is lt35 cm for MP between 3 to 5 years and lt1cm for WLof 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a prioriknowledge from Sea Level maps derived from previous iterations or from other missions
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bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for ERS-1 for its 168 days geodetic mission (phases E-F from April1994 to March 1995) or for Envisat since november 2010 because the satellite is not in a repetitive orbitphase The alternative is to use the MSS instead The gridded MSS is derived from along track MPs anddata from geodetic phases Thus any error on the MP is also contained in the MSS There are essentially 4types of additional errors on gridded MSS which are hard to quantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
III362 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III363 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
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III37 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III371 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
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IV MYOCEAN PRODUCTS
IV1 Near Real Time Products
The purpose of the NRT DUACS component is the acquisition of altimeter data from various altimeter mis-sions in near-real time (ie within a few days at most) the validation and correction of these altimeter datasets (ie edition and selection update of corrections and homogenization orbit error reduction) in order toproduce each day along-track productsProducts are as follows
Along-track products global and regional (Mediterranean and Black Seas Arctic Ocean and Europeareas)
bull Sea Level Anomaly (NRT-SLA) for each mission with NRT-SLA ephemeris
IV11 Delay of the products
The availability of the products in near real time is three to twelve hours after the measurement for along-track products Those products are delivered every day
IV12 Temporal availibility
The following table presents the available products by mission and by data periodNear real time products
NRT Jason-2 Jason-1 and Jason-1geodetic
Envisat new Cryosat-2
Temporal Time availability ymlowast
ongoingymlowast-20120303 for
repeat track and20120507-ongoing for
geodetic track
ymlowast
2012040820120101
ongoing
NRT-SLA X X X X
lowastym the temporal coverage for NRT products is fluctuating and depends on updates of Delayed Time prod-ucts When DT products are updated (3 to 4 times per year) the oldest NRT products are replaced by thebetter quality DT products so that the 2 series are overlapping on few weeks or few months
IV2 Delayed Time Products
The Delayed Time component of SSALTODUACS system is responsible for the production of processedJason-1 Jason-2 TP Envisat GFO ERS12 and even Geosat data in order to provide a homogeneousinter-calibrated and highly accurate long time series of SLA DT products are more precise than NRT products Two reasons explain this quality difference The firstone is the better intrinsic quality of the POE orbit used in the GDR processing The second reason is that
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in the DT DUACS processing the products can be computed optimally with a centred computation timewindow for OER LWE On the contrary in NRT case future data are not available so the computationtime window is not centred and therefore not optimalAs for NRT products improved altimeter corrections and processing algorithms are used ocean tide modelto correct altimeter data improved methods for orbit error reduction and mapping
Along-Track products global and regional (Mediterranean and Black Seas)
bull Sea Level Anomaly (DT-SLA) for each mission
IV21 Delay of the products
Weekly products are delivered The availability of the products in delayed time is at the best two monthsafter the date of the measurement The product generation needs all the GDR data of all the missions to takeinto account the best corrections as possible The time delay can be longer in the case of a missing mission
IV22 Temporal availibility
The following table presents the available products by mission and by data periodDelayed time SSALTODUACS products
Upd Jason-2 Jason-1new6
Jason-1 GFO Envisatnew6
Envisat ERS-16
ERS-2Topexnew6
Topex
TemporalTimeavailabil-ity
200810ymlowast
200902ymlowast
200204200810
200001200809
201010ymlowast
200210201010
199210200304
200209200510
199209200204
DT-SLA X X X X X X X X X
lowast ym those dates are updated regularly (3 to 4 times per year) and are avalaible when you download thedata at httpwwwmyoceaneuweb24-cataloguephp6 Jason-1 new orbit starting 200809 Envisat new orbit starting 201010 TP new orbit starting 200209 ERS-1The geodetic phases (E-F) are included There are no ERS-1 data between December 23 1993 and April 10 1994(ERS-1 phase D - 2nd ice phase) Note that during that time products are based only on TopexPoseidon data
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V DESCRIPTION OF THE PRODUCT SPECIFICATION
V1 General information
Product Specification SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001
Geographical coverage global
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 20-50km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001 Product Specification
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Product Specification SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002
Geographical coverage 55˚W-35˚E 30˚N-46˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002 Product Specification
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Product Specification SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003
Geographical coverage 27˚E-42˚E 40˚N-47˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003 Product Specification
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Product Specification SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004
Geographical coverage 25˚W-42˚E 21˚N-66˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004 Product Specification
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Product Specification SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005
Geographical coverage 0˚W-360˚E 50˚N-82˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005 Product Specification
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VI NOMENCLATURE OF FILES
VI1 Nomenclature of files downloaded through the MyOcean Web PortalDirectgetfile Service
VI11 Nomenclature of the product line
The description of the syntax for the SL TAC SLA products line is given by
SEALEVEL_ltREGIONgt_SLA_L3_ltDELAYgt_OBSERVATIONS_008_ltZONEgt_ltLETTERgtwhere
REGION GLO global geographic coverage product
BS Black Sea products
MED Mediterranean products
ARC Arctic products (for NRT products)
EUROPE Europe products (for NRT products)
DELAY NRT near real time products
RAN delayed time or reanalysis products
ZONE 001 number on 3 digits
002
003
004
LETTER a letter on 1 digit
b
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VI12 Nomenclature of the datasets
The nomenclature used is
dataset-duacs-ltdelaygt-ltzonegt-ltmissiongt-lttype of slagt-l3where the fileds in ltgt are described below
delay nrt near-real time productsran delayed time products
zone global global geographic coverage productmedsea Mediterranean productsblacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1 (only for ran)e2 ERS-2 (only for ran)tp TOPEXPoseidon (only for ran)tpn TOPEXPoseidon on its new orbit (only for
ran)g2 GFO (only for ran)j1 Jason-1 (only for ran)j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisat (only for ran)enn Envisat on its new orbitc2 Cryosat-2 (only for nrt)
type of sla sla filtered slasla_unfiltered non filtered sla (only for ran products)
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VI13 Nomenclature of the NetCdf files
The nomenclature used is
ltdelaygt_ltzonegt_ltmissiongt_sla_ltvariablegt_ltdatebegingt_ltdateendgt_ltdateprodgtnc where the fileds in ltgt are de-scribed below
delay nrt near-real time productsdt delayed time products
zone global global geographic coverage productmed Mediterranean products (for dt)mfstep Mediterranean products (for nrt)blacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1e2 ERS-2tp TOPEXPoseidontpn TOPEXPoseidon on its new orbitg2 GFOj1 Jason-1j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisatenn Envisat on its new orbitc2 Cryosat-2
variable vfec filtered and sub-sampled slavxxc non filtered and non sub-sampled sla (only
for dt)datebegin YYYYMMDD() beginning date of the datasetdateend YYYYMMDD() end date of the datasetdateprod YYYYMMDD production date of the dataset
() For dt data as the dates in the file names are rounded the user wanting data for date T has to read the filescontaining dates T+1 and T-1 in their name and check inside the files if there are some data for date T
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VII DATA FORMAT
This chapter presents the data storage format used for MyOcean products
VII1 NetCdf
The products are stored using the NetCDF format NetCDF (network Common Data Form) is an interface for array-oriented data access and a library that provides an implementation of the interface The netCDF library also definesa machine-independent format for representing scientific data Together the interface library and format support thecreation access and sharing of scientific data The netCDF software was developed at the Unidata Program Center inBoulder Colorado The netCDF libraries define a machine-independent format for representing scientific data Pleasesee Unidata NetCDF pages for more information and to retreive NetCDF software package onhttpwwwunidataucaredupackagesnetcdfindexhtml
NetCDF data is
bull Self-Describing A netCDF file includes information about the data it contains
bull Architecture-independent A netCDF file is represented in a form that can be accessed by computers with dif-ferent ways of storing integers characters and floating-point numbers
bull Direct-access A small subset of a large dataset may be accessed efficiently without first reading through allthe preceding data
bull Appendable Data can be appended to a netCDF dataset along one dimension without copying the dataset orredefining its structure The structure of a netCDF dataset can be changed though this sometimes causes thedataset to be copied
bull Sharable One writer and multiple readers may simultaneously access the same netCDF file
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VII2 Structure and semantic of NetCDF along-track files
The NetCDF Sea Level TAC files are based on the attribute data tags defined by the Cooperative OceanAtmosphereResearch Data Service (COARDS) and Climate and Forecast (CF) metadata conventions The CF convention gener-alises and extends the COARDS convention but relaxes the COARDS constraints on dimension and order and specifiesmethods for reducing the size of datasetsA wide range of software are available to write or read NetCDFCF files API are made available by UNIDATA(httpwwwunidataucaredusoftwarenetcdf)
bull CC++Fortran
bull Java
bull MATLAB Objective-C Perl Python R Ruby TclTk
In addition to these conventions the files are using a common structure and semantic
bull 1 dimension is defined
ndash time it is used to check NetCDF variables depending on time
bull 8 variables are defined
ndash short SLA contains the Sea Level Anomaly values for each time given
ndash int longitude contains the longitude for each measurement
ndash short track contains the track number for each measurement
ndash double time contains the time in days since 1950-01-01 000000 UTC for each measurement
ndash short mean_profile_point_index index of the corrsponding point in the track of the mean profile
ndash byte flag flag=0 the processed data comes from OGDR if flag=1 the processed data comes from theIGDR
ndash int latitude contains the latitude for each measurement
ndash short cycle contains the cycle number for each measurement
bull global attributes
ndash the global attributes gives information about the creation of the file
Example of a NetCDF sla file
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netcdf nrt_global_j1_sla_vfec_20101230_20101230_20101230 dimensions
time = 10385 variables
short SLA(time) SLAcoordinates = longitude latitude SLAlong_name = Sea Level Anomaly SLA_FillValue = 32767s SLAadd_offset = 0 SLAscale_factor = 0001 SLAunits = m SLAstandard_name = sea_surface_height_above_sea_level
int longitude(time) longitudelong_name = Longitude of measurement longitude_FillValue = 2147483647 longitudeadd_offset = 0 longitudestandard_name = longitude longitudescale_factor = 1e-06 longitudeunits = degrees_east
short track(time) tracklong_name = Track in cycle the measurement belongs to track_FillValue = 32767s trackunits = 1 trackcoordinates = longitude latitude
double time(time) timelong_name = Time of measurement time_FillValue = 184467440737096e+19 timeaxis = T timestandard_name = time timeunits = days since 1950-01-01 000000 UTC
int latitude(time) latitudelong_name = Latitude of measurement latitude_FillValue = 2147483647 latitudeadd_offset = 0 latitudestandard_name = latitude latitudescale_factor = 1e-06 latitudeunits = degrees_north
short flag(time) flagcoordinates = longitude latitude flag_FillValue = 3267s flaglong_name = data origin flagflag_values = 1s 0s flagflag_meanings = igdr_like non_igdr_like flagcomment = The origin of the data is determined by the types of geophysical datarecords (GDR) used in computation of the SLA 1 for the Interim GDR (IGDR) and0 for Operational GDR (OGDR)
short cycle(time) cyclelong_name = Cycle the measurement belongs to cycle_FillValue = 32767s cycleunits = 1 cyclecoordinates = longitude latitude
global attributeshistory = 22-Feb-2011 155243 CET File created by the SSLATODUACS system version 1001 comment = Produce from ENVISAT Extension Phase satellite altimetry data institution = CLSCNES
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references = httpwwwavisooceanobscomfileadmindocumentsdatatoolshdbk_duacspdf source = satellite altimetry title = along track Sea Level Anomaly Conventions = CF-14
dataSLA =
7 7 11 10 -2 -22 -39 -41 -30 -13 -3 -5 -16 -26 -32 -35-35 -35 -37 -35 -31 -29 -31 -35 -32 -21 -10 -10 -19 -20 -1-69 -57 -49 -45 -39 -30 -28 -31 -27 -13 -2 -5 -15 -3 1112 3 -7 -10 -14 -15 -22 -31 -37 -32 -17 -10
longitude =74743328 74868400 74993968 75120040 75246616 7537372875501368 75629568 75758320 75887656 76017568 76148080 7627920876388952 76477056 76565456 76654144 76743128 76832400 76921984329429568 329535424 329641792 329748672 329856096 329964032330072512 330181536 330291072 330401184
track =92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 9292 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92113 113 113 113 113 113 113 113 113 113 113 113 113 113113 113 113 113 113 113 113 113 113
time =222780000565705 222780001314719 222780002063733222780002812747 222780003561761 222780004310775 222780005059788222780005808802 222780006557816 22278000730683 222780008055844222780008804858 222780009553872 22278001017805 222780010677393222788257112198 222788257486705 222788257861212 222788258235719222788258610226 222788258984733 222788259359239 222788259733746222788260108253 22278826048276
mean_profile_point_index =1872 1878 1884 1890 1896 1902 1908 19141920 1926 1932 1938 1944 1949 1953 1957 1961 1965 1969 19732306 2309 2312 2315 2318 2321 2327 2330 2333 2336 2339 23422345 2348 2351 2354 2357 2360 2363 2366
flag =0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
latitude =-16225506 -16539731 -16853833 -17167810 -17481660 -17795380-18108966 -18422418 -18735729 -19048899 -19361924 -19674801-19987527 -20248015 -20456329 -20664569 -20872739 -2108083739481297 39628277 39775133 39921866 40068472 40214953 4036130840507533 40653629 40799592 40945423 41091120 41236684 41382111
cycle =331 331 331 331 331 331 331 331 331 331 331 331 331
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331 331 331 331 331 331 331 331 331 331 331 331 331 331331 331 331 331 331 331 331 331 331 331 331 331
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VIII HOW TO DOWNLOAD A PRODUCT
VIII1 Download a product through the MyOcean Web Portal DirectgetfileService
You first need to register Please find below the registration stepshttpwwwmyoceaneuweb34-products-and-services-faqphp1Once registered the MyOcean FAQ httpwwwmyoceaneuweb34-products-and-services-faqwill guide you on How to download a product through the MyOcean Web Portal Directgetfile Service
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IX NEWS AND UPDATES
IX1 [Duacs] Operational news
To be kept informed on events occurring on the satellites and on the eventual interruption of the services of the DUACSprocessing system see the [Duacs] operational news on the Aviso websitehttpwwwavisooceanobscomendataoperational-newsindexhtml
IX2 Updates
To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtmlSince 2010 a complete reprocessing of all altimetry data (cumulated total of about 55 years of data) is available Themain changes introduced in the Duacs DT v300 reprocessed data set in SSALTODUACS reprocessed DT data setare listed herehttpwwwavisooceanobscomfileadmindocumentsdataduacsduacs_DT_2010_reprocessing_impactpdf
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III36 Product generation
The product generation process is composed of four steps computation of raw SLA cross-validationfilteringampsub-sampling and generation of by-products
III361 Computation of raw SLA
Since the geoid is not well known yet the SSH cannot be used directly the SSH anomalies are used insteadThey are computed from the difference of the instantaneous SSH - a temporal reference This temporalreference can be a Mean Profile (MP) in the case of repeat track analysis or a gridded MSS when the repeattrack analysis cannot be used The errors affecting the SLAs MPs and MSS have different magnitudes andwavelengths The computation of the SLAs and their errors associated are detailed in Dibarboure et al 2010[9]
Use of a Mean ProfileIn the repeat track analysis (when the satellites flies over a repetitive orbit) measurements are re-sampledalong a theoretical ground track (or mean track) associated to each mission Then a Mean Profile (MP) issubtracted from the re-sampled data to obtain SLA The MP is a time average of similarly re-sampled dataover a long period
bull The Mean Profile used for TP (cycles 1 to 364) Jason-1 (cycles 1 to 259) and Jason-2 is computedwith 10 years of TP (cycles 11 to 353) and 6 years of Jason-1 (cycles 11 to 250)
bull The Mean Profile used for TP (cycles 368 to 481) and from Jason-1 cycle 262 to 374 (where satellitesare on interleaved ground-tracks) is computed with 3 years of TP (cycles 369 to 479)
bull The Mean Profile used for ERS-1 in its 35 days repetitive orbit mission ERS-2 and Envisat (only forthe first orbit before November 2010) is computed with 8 years of ERS-2 (cycles 1 to 85) and 6 yearsof Envisat (cycles 10 to 72)
bull No Mean Profile can be used for Envisat on its new orbit (enn) Jason-1 on its geodetic orbit (j1g)because there is no repetitive track The MSS must be used instead (see below)
bull The Mean Profile used for GFO is computed with 7 years of GFO cycles 37 to 187
Computation of a Mean ProfileThe computation of a Mean Profile is not a simple average of similarly co-located SSH data from the sameground track on the maximum period of time as possible
bull Indeed as the satellite ground track is not perfectly controlled and is often kept in a band of about1km wide precise cross-track projection andor interpolation schemes are required to avoid errors
bull The mesoscale variability error (which is lt35 cm for MP between 3 to 5 years and lt1cm for WLof 100-200km for MP between 7 and 15 years) is eliminated with an iterative process using a prioriknowledge from Sea Level maps derived from previous iterations or from other missions
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bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for ERS-1 for its 168 days geodetic mission (phases E-F from April1994 to March 1995) or for Envisat since november 2010 because the satellite is not in a repetitive orbitphase The alternative is to use the MSS instead The gridded MSS is derived from along track MPs anddata from geodetic phases Thus any error on the MP is also contained in the MSS There are essentially 4types of additional errors on gridded MSS which are hard to quantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
III362 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III363 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
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III37 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III371 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
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IV MYOCEAN PRODUCTS
IV1 Near Real Time Products
The purpose of the NRT DUACS component is the acquisition of altimeter data from various altimeter mis-sions in near-real time (ie within a few days at most) the validation and correction of these altimeter datasets (ie edition and selection update of corrections and homogenization orbit error reduction) in order toproduce each day along-track productsProducts are as follows
Along-track products global and regional (Mediterranean and Black Seas Arctic Ocean and Europeareas)
bull Sea Level Anomaly (NRT-SLA) for each mission with NRT-SLA ephemeris
IV11 Delay of the products
The availability of the products in near real time is three to twelve hours after the measurement for along-track products Those products are delivered every day
IV12 Temporal availibility
The following table presents the available products by mission and by data periodNear real time products
NRT Jason-2 Jason-1 and Jason-1geodetic
Envisat new Cryosat-2
Temporal Time availability ymlowast
ongoingymlowast-20120303 for
repeat track and20120507-ongoing for
geodetic track
ymlowast
2012040820120101
ongoing
NRT-SLA X X X X
lowastym the temporal coverage for NRT products is fluctuating and depends on updates of Delayed Time prod-ucts When DT products are updated (3 to 4 times per year) the oldest NRT products are replaced by thebetter quality DT products so that the 2 series are overlapping on few weeks or few months
IV2 Delayed Time Products
The Delayed Time component of SSALTODUACS system is responsible for the production of processedJason-1 Jason-2 TP Envisat GFO ERS12 and even Geosat data in order to provide a homogeneousinter-calibrated and highly accurate long time series of SLA DT products are more precise than NRT products Two reasons explain this quality difference The firstone is the better intrinsic quality of the POE orbit used in the GDR processing The second reason is that
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in the DT DUACS processing the products can be computed optimally with a centred computation timewindow for OER LWE On the contrary in NRT case future data are not available so the computationtime window is not centred and therefore not optimalAs for NRT products improved altimeter corrections and processing algorithms are used ocean tide modelto correct altimeter data improved methods for orbit error reduction and mapping
Along-Track products global and regional (Mediterranean and Black Seas)
bull Sea Level Anomaly (DT-SLA) for each mission
IV21 Delay of the products
Weekly products are delivered The availability of the products in delayed time is at the best two monthsafter the date of the measurement The product generation needs all the GDR data of all the missions to takeinto account the best corrections as possible The time delay can be longer in the case of a missing mission
IV22 Temporal availibility
The following table presents the available products by mission and by data periodDelayed time SSALTODUACS products
Upd Jason-2 Jason-1new6
Jason-1 GFO Envisatnew6
Envisat ERS-16
ERS-2Topexnew6
Topex
TemporalTimeavailabil-ity
200810ymlowast
200902ymlowast
200204200810
200001200809
201010ymlowast
200210201010
199210200304
200209200510
199209200204
DT-SLA X X X X X X X X X
lowast ym those dates are updated regularly (3 to 4 times per year) and are avalaible when you download thedata at httpwwwmyoceaneuweb24-cataloguephp6 Jason-1 new orbit starting 200809 Envisat new orbit starting 201010 TP new orbit starting 200209 ERS-1The geodetic phases (E-F) are included There are no ERS-1 data between December 23 1993 and April 10 1994(ERS-1 phase D - 2nd ice phase) Note that during that time products are based only on TopexPoseidon data
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V DESCRIPTION OF THE PRODUCT SPECIFICATION
V1 General information
Product Specification SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001
Geographical coverage global
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 20-50km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001 Product Specification
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Product Specification SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002
Geographical coverage 55˚W-35˚E 30˚N-46˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002 Product Specification
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Product Specification SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003
Geographical coverage 27˚E-42˚E 40˚N-47˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003 Product Specification
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Product Specification SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004
Geographical coverage 25˚W-42˚E 21˚N-66˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004 Product Specification
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Product Specification SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005
Geographical coverage 0˚W-360˚E 50˚N-82˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005 Product Specification
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VI NOMENCLATURE OF FILES
VI1 Nomenclature of files downloaded through the MyOcean Web PortalDirectgetfile Service
VI11 Nomenclature of the product line
The description of the syntax for the SL TAC SLA products line is given by
SEALEVEL_ltREGIONgt_SLA_L3_ltDELAYgt_OBSERVATIONS_008_ltZONEgt_ltLETTERgtwhere
REGION GLO global geographic coverage product
BS Black Sea products
MED Mediterranean products
ARC Arctic products (for NRT products)
EUROPE Europe products (for NRT products)
DELAY NRT near real time products
RAN delayed time or reanalysis products
ZONE 001 number on 3 digits
002
003
004
LETTER a letter on 1 digit
b
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VI12 Nomenclature of the datasets
The nomenclature used is
dataset-duacs-ltdelaygt-ltzonegt-ltmissiongt-lttype of slagt-l3where the fileds in ltgt are described below
delay nrt near-real time productsran delayed time products
zone global global geographic coverage productmedsea Mediterranean productsblacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1 (only for ran)e2 ERS-2 (only for ran)tp TOPEXPoseidon (only for ran)tpn TOPEXPoseidon on its new orbit (only for
ran)g2 GFO (only for ran)j1 Jason-1 (only for ran)j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisat (only for ran)enn Envisat on its new orbitc2 Cryosat-2 (only for nrt)
type of sla sla filtered slasla_unfiltered non filtered sla (only for ran products)
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VI13 Nomenclature of the NetCdf files
The nomenclature used is
ltdelaygt_ltzonegt_ltmissiongt_sla_ltvariablegt_ltdatebegingt_ltdateendgt_ltdateprodgtnc where the fileds in ltgt are de-scribed below
delay nrt near-real time productsdt delayed time products
zone global global geographic coverage productmed Mediterranean products (for dt)mfstep Mediterranean products (for nrt)blacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1e2 ERS-2tp TOPEXPoseidontpn TOPEXPoseidon on its new orbitg2 GFOj1 Jason-1j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisatenn Envisat on its new orbitc2 Cryosat-2
variable vfec filtered and sub-sampled slavxxc non filtered and non sub-sampled sla (only
for dt)datebegin YYYYMMDD() beginning date of the datasetdateend YYYYMMDD() end date of the datasetdateprod YYYYMMDD production date of the dataset
() For dt data as the dates in the file names are rounded the user wanting data for date T has to read the filescontaining dates T+1 and T-1 in their name and check inside the files if there are some data for date T
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VII DATA FORMAT
This chapter presents the data storage format used for MyOcean products
VII1 NetCdf
The products are stored using the NetCDF format NetCDF (network Common Data Form) is an interface for array-oriented data access and a library that provides an implementation of the interface The netCDF library also definesa machine-independent format for representing scientific data Together the interface library and format support thecreation access and sharing of scientific data The netCDF software was developed at the Unidata Program Center inBoulder Colorado The netCDF libraries define a machine-independent format for representing scientific data Pleasesee Unidata NetCDF pages for more information and to retreive NetCDF software package onhttpwwwunidataucaredupackagesnetcdfindexhtml
NetCDF data is
bull Self-Describing A netCDF file includes information about the data it contains
bull Architecture-independent A netCDF file is represented in a form that can be accessed by computers with dif-ferent ways of storing integers characters and floating-point numbers
bull Direct-access A small subset of a large dataset may be accessed efficiently without first reading through allthe preceding data
bull Appendable Data can be appended to a netCDF dataset along one dimension without copying the dataset orredefining its structure The structure of a netCDF dataset can be changed though this sometimes causes thedataset to be copied
bull Sharable One writer and multiple readers may simultaneously access the same netCDF file
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VII2 Structure and semantic of NetCDF along-track files
The NetCDF Sea Level TAC files are based on the attribute data tags defined by the Cooperative OceanAtmosphereResearch Data Service (COARDS) and Climate and Forecast (CF) metadata conventions The CF convention gener-alises and extends the COARDS convention but relaxes the COARDS constraints on dimension and order and specifiesmethods for reducing the size of datasetsA wide range of software are available to write or read NetCDFCF files API are made available by UNIDATA(httpwwwunidataucaredusoftwarenetcdf)
bull CC++Fortran
bull Java
bull MATLAB Objective-C Perl Python R Ruby TclTk
In addition to these conventions the files are using a common structure and semantic
bull 1 dimension is defined
ndash time it is used to check NetCDF variables depending on time
bull 8 variables are defined
ndash short SLA contains the Sea Level Anomaly values for each time given
ndash int longitude contains the longitude for each measurement
ndash short track contains the track number for each measurement
ndash double time contains the time in days since 1950-01-01 000000 UTC for each measurement
ndash short mean_profile_point_index index of the corrsponding point in the track of the mean profile
ndash byte flag flag=0 the processed data comes from OGDR if flag=1 the processed data comes from theIGDR
ndash int latitude contains the latitude for each measurement
ndash short cycle contains the cycle number for each measurement
bull global attributes
ndash the global attributes gives information about the creation of the file
Example of a NetCDF sla file
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netcdf nrt_global_j1_sla_vfec_20101230_20101230_20101230 dimensions
time = 10385 variables
short SLA(time) SLAcoordinates = longitude latitude SLAlong_name = Sea Level Anomaly SLA_FillValue = 32767s SLAadd_offset = 0 SLAscale_factor = 0001 SLAunits = m SLAstandard_name = sea_surface_height_above_sea_level
int longitude(time) longitudelong_name = Longitude of measurement longitude_FillValue = 2147483647 longitudeadd_offset = 0 longitudestandard_name = longitude longitudescale_factor = 1e-06 longitudeunits = degrees_east
short track(time) tracklong_name = Track in cycle the measurement belongs to track_FillValue = 32767s trackunits = 1 trackcoordinates = longitude latitude
double time(time) timelong_name = Time of measurement time_FillValue = 184467440737096e+19 timeaxis = T timestandard_name = time timeunits = days since 1950-01-01 000000 UTC
int latitude(time) latitudelong_name = Latitude of measurement latitude_FillValue = 2147483647 latitudeadd_offset = 0 latitudestandard_name = latitude latitudescale_factor = 1e-06 latitudeunits = degrees_north
short flag(time) flagcoordinates = longitude latitude flag_FillValue = 3267s flaglong_name = data origin flagflag_values = 1s 0s flagflag_meanings = igdr_like non_igdr_like flagcomment = The origin of the data is determined by the types of geophysical datarecords (GDR) used in computation of the SLA 1 for the Interim GDR (IGDR) and0 for Operational GDR (OGDR)
short cycle(time) cyclelong_name = Cycle the measurement belongs to cycle_FillValue = 32767s cycleunits = 1 cyclecoordinates = longitude latitude
global attributeshistory = 22-Feb-2011 155243 CET File created by the SSLATODUACS system version 1001 comment = Produce from ENVISAT Extension Phase satellite altimetry data institution = CLSCNES
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references = httpwwwavisooceanobscomfileadmindocumentsdatatoolshdbk_duacspdf source = satellite altimetry title = along track Sea Level Anomaly Conventions = CF-14
dataSLA =
7 7 11 10 -2 -22 -39 -41 -30 -13 -3 -5 -16 -26 -32 -35-35 -35 -37 -35 -31 -29 -31 -35 -32 -21 -10 -10 -19 -20 -1-69 -57 -49 -45 -39 -30 -28 -31 -27 -13 -2 -5 -15 -3 1112 3 -7 -10 -14 -15 -22 -31 -37 -32 -17 -10
longitude =74743328 74868400 74993968 75120040 75246616 7537372875501368 75629568 75758320 75887656 76017568 76148080 7627920876388952 76477056 76565456 76654144 76743128 76832400 76921984329429568 329535424 329641792 329748672 329856096 329964032330072512 330181536 330291072 330401184
track =92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 9292 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92113 113 113 113 113 113 113 113 113 113 113 113 113 113113 113 113 113 113 113 113 113 113
time =222780000565705 222780001314719 222780002063733222780002812747 222780003561761 222780004310775 222780005059788222780005808802 222780006557816 22278000730683 222780008055844222780008804858 222780009553872 22278001017805 222780010677393222788257112198 222788257486705 222788257861212 222788258235719222788258610226 222788258984733 222788259359239 222788259733746222788260108253 22278826048276
mean_profile_point_index =1872 1878 1884 1890 1896 1902 1908 19141920 1926 1932 1938 1944 1949 1953 1957 1961 1965 1969 19732306 2309 2312 2315 2318 2321 2327 2330 2333 2336 2339 23422345 2348 2351 2354 2357 2360 2363 2366
flag =0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
latitude =-16225506 -16539731 -16853833 -17167810 -17481660 -17795380-18108966 -18422418 -18735729 -19048899 -19361924 -19674801-19987527 -20248015 -20456329 -20664569 -20872739 -2108083739481297 39628277 39775133 39921866 40068472 40214953 4036130840507533 40653629 40799592 40945423 41091120 41236684 41382111
cycle =331 331 331 331 331 331 331 331 331 331 331 331 331
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331 331 331 331 331 331 331 331 331 331 331 331 331 331331 331 331 331 331 331 331 331 331 331 331 331
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VIII HOW TO DOWNLOAD A PRODUCT
VIII1 Download a product through the MyOcean Web Portal DirectgetfileService
You first need to register Please find below the registration stepshttpwwwmyoceaneuweb34-products-and-services-faqphp1Once registered the MyOcean FAQ httpwwwmyoceaneuweb34-products-and-services-faqwill guide you on How to download a product through the MyOcean Web Portal Directgetfile Service
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IX NEWS AND UPDATES
IX1 [Duacs] Operational news
To be kept informed on events occurring on the satellites and on the eventual interruption of the services of the DUACSprocessing system see the [Duacs] operational news on the Aviso websitehttpwwwavisooceanobscomendataoperational-newsindexhtml
IX2 Updates
To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtmlSince 2010 a complete reprocessing of all altimetry data (cumulated total of about 55 years of data) is available Themain changes introduced in the Duacs DT v300 reprocessed data set in SSALTODUACS reprocessed DT data setare listed herehttpwwwavisooceanobscomfileadmindocumentsdataduacsduacs_DT_2010_reprocessing_impactpdf
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bull Moreover the inter-annual variabilty error (lt5cm for WLgt5000km and lt5-8cm for WL of 200-500km) is accounted for by using the MSS computed over 1993-1999 (eg the GFO MP is computedon 2000-2006 but referenced onto 1993-1999 for the sake of coherency with other missions)
bull Finally for these Mean Profiles the latest standards and a maximum of data were used in order to in-crease as much as possible the quality of their estimation (see tables 6 and 7 Corrections and modelsapplied in SSALTODUACS Delayed-Time products) Note that a particular care was brought to theprocessing near coasts
Use of a MSSThe repeat track analysis is impossible for ERS-1 for its 168 days geodetic mission (phases E-F from April1994 to March 1995) or for Envisat since november 2010 because the satellite is not in a repetitive orbitphase The alternative is to use the MSS instead The gridded MSS is derived from along track MPs anddata from geodetic phases Thus any error on the MP is also contained in the MSS There are essentially 4types of additional errors on gridded MSS which are hard to quantify separately
bull To ensure a global MSS coherency between all data sets the gridding process averages all sensor-specific errors and especially geographically correlated ones
bull The gridding process has to perform some smoothing to make up for signals which cannot be resolvedaway from known track degrading along-track content
bull There are also errors related to the lack of spatial and temporal data (omission errors)
bull The error stemming from the geodetic data the variability not properly removed before the absorptionin the MSS and the impossibility to compute mean sea surface height content
III362 Cross validation
After the repeat track analysis the cross-validation technique is used as the ultimate screening process ofisolated and slightly erroneous measurements Small SLA flows are compared to previous and independentSLA data sets using a- 12 year climatology and a 3 sigma criteria for outlier removal
III363 Filtering and sub-sampling
Residual noise and small scale signals are then removed by filtering the data using a Lanczos filter As dataare filtered from small scales a sub-sampling is finally applied Along-track SLA are then producedNote that the filtering and sub-sampling is adapted to each region and product as a function of the char-acteristics of the area and of the assimilation needs
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III37 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III371 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
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IV MYOCEAN PRODUCTS
IV1 Near Real Time Products
The purpose of the NRT DUACS component is the acquisition of altimeter data from various altimeter mis-sions in near-real time (ie within a few days at most) the validation and correction of these altimeter datasets (ie edition and selection update of corrections and homogenization orbit error reduction) in order toproduce each day along-track productsProducts are as follows
Along-track products global and regional (Mediterranean and Black Seas Arctic Ocean and Europeareas)
bull Sea Level Anomaly (NRT-SLA) for each mission with NRT-SLA ephemeris
IV11 Delay of the products
The availability of the products in near real time is three to twelve hours after the measurement for along-track products Those products are delivered every day
IV12 Temporal availibility
The following table presents the available products by mission and by data periodNear real time products
NRT Jason-2 Jason-1 and Jason-1geodetic
Envisat new Cryosat-2
Temporal Time availability ymlowast
ongoingymlowast-20120303 for
repeat track and20120507-ongoing for
geodetic track
ymlowast
2012040820120101
ongoing
NRT-SLA X X X X
lowastym the temporal coverage for NRT products is fluctuating and depends on updates of Delayed Time prod-ucts When DT products are updated (3 to 4 times per year) the oldest NRT products are replaced by thebetter quality DT products so that the 2 series are overlapping on few weeks or few months
IV2 Delayed Time Products
The Delayed Time component of SSALTODUACS system is responsible for the production of processedJason-1 Jason-2 TP Envisat GFO ERS12 and even Geosat data in order to provide a homogeneousinter-calibrated and highly accurate long time series of SLA DT products are more precise than NRT products Two reasons explain this quality difference The firstone is the better intrinsic quality of the POE orbit used in the GDR processing The second reason is that
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in the DT DUACS processing the products can be computed optimally with a centred computation timewindow for OER LWE On the contrary in NRT case future data are not available so the computationtime window is not centred and therefore not optimalAs for NRT products improved altimeter corrections and processing algorithms are used ocean tide modelto correct altimeter data improved methods for orbit error reduction and mapping
Along-Track products global and regional (Mediterranean and Black Seas)
bull Sea Level Anomaly (DT-SLA) for each mission
IV21 Delay of the products
Weekly products are delivered The availability of the products in delayed time is at the best two monthsafter the date of the measurement The product generation needs all the GDR data of all the missions to takeinto account the best corrections as possible The time delay can be longer in the case of a missing mission
IV22 Temporal availibility
The following table presents the available products by mission and by data periodDelayed time SSALTODUACS products
Upd Jason-2 Jason-1new6
Jason-1 GFO Envisatnew6
Envisat ERS-16
ERS-2Topexnew6
Topex
TemporalTimeavailabil-ity
200810ymlowast
200902ymlowast
200204200810
200001200809
201010ymlowast
200210201010
199210200304
200209200510
199209200204
DT-SLA X X X X X X X X X
lowast ym those dates are updated regularly (3 to 4 times per year) and are avalaible when you download thedata at httpwwwmyoceaneuweb24-cataloguephp6 Jason-1 new orbit starting 200809 Envisat new orbit starting 201010 TP new orbit starting 200209 ERS-1The geodetic phases (E-F) are included There are no ERS-1 data between December 23 1993 and April 10 1994(ERS-1 phase D - 2nd ice phase) Note that during that time products are based only on TopexPoseidon data
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V DESCRIPTION OF THE PRODUCT SPECIFICATION
V1 General information
Product Specification SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001
Geographical coverage global
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 20-50km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001 Product Specification
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Product Specification SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002
Geographical coverage 55˚W-35˚E 30˚N-46˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002 Product Specification
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Product Specification SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003
Geographical coverage 27˚E-42˚E 40˚N-47˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003 Product Specification
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Product Specification SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004
Geographical coverage 25˚W-42˚E 21˚N-66˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004 Product Specification
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Product Specification SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005
Geographical coverage 0˚W-360˚E 50˚N-82˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005 Product Specification
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VI NOMENCLATURE OF FILES
VI1 Nomenclature of files downloaded through the MyOcean Web PortalDirectgetfile Service
VI11 Nomenclature of the product line
The description of the syntax for the SL TAC SLA products line is given by
SEALEVEL_ltREGIONgt_SLA_L3_ltDELAYgt_OBSERVATIONS_008_ltZONEgt_ltLETTERgtwhere
REGION GLO global geographic coverage product
BS Black Sea products
MED Mediterranean products
ARC Arctic products (for NRT products)
EUROPE Europe products (for NRT products)
DELAY NRT near real time products
RAN delayed time or reanalysis products
ZONE 001 number on 3 digits
002
003
004
LETTER a letter on 1 digit
b
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VI12 Nomenclature of the datasets
The nomenclature used is
dataset-duacs-ltdelaygt-ltzonegt-ltmissiongt-lttype of slagt-l3where the fileds in ltgt are described below
delay nrt near-real time productsran delayed time products
zone global global geographic coverage productmedsea Mediterranean productsblacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1 (only for ran)e2 ERS-2 (only for ran)tp TOPEXPoseidon (only for ran)tpn TOPEXPoseidon on its new orbit (only for
ran)g2 GFO (only for ran)j1 Jason-1 (only for ran)j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisat (only for ran)enn Envisat on its new orbitc2 Cryosat-2 (only for nrt)
type of sla sla filtered slasla_unfiltered non filtered sla (only for ran products)
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VI13 Nomenclature of the NetCdf files
The nomenclature used is
ltdelaygt_ltzonegt_ltmissiongt_sla_ltvariablegt_ltdatebegingt_ltdateendgt_ltdateprodgtnc where the fileds in ltgt are de-scribed below
delay nrt near-real time productsdt delayed time products
zone global global geographic coverage productmed Mediterranean products (for dt)mfstep Mediterranean products (for nrt)blacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1e2 ERS-2tp TOPEXPoseidontpn TOPEXPoseidon on its new orbitg2 GFOj1 Jason-1j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisatenn Envisat on its new orbitc2 Cryosat-2
variable vfec filtered and sub-sampled slavxxc non filtered and non sub-sampled sla (only
for dt)datebegin YYYYMMDD() beginning date of the datasetdateend YYYYMMDD() end date of the datasetdateprod YYYYMMDD production date of the dataset
() For dt data as the dates in the file names are rounded the user wanting data for date T has to read the filescontaining dates T+1 and T-1 in their name and check inside the files if there are some data for date T
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VII DATA FORMAT
This chapter presents the data storage format used for MyOcean products
VII1 NetCdf
The products are stored using the NetCDF format NetCDF (network Common Data Form) is an interface for array-oriented data access and a library that provides an implementation of the interface The netCDF library also definesa machine-independent format for representing scientific data Together the interface library and format support thecreation access and sharing of scientific data The netCDF software was developed at the Unidata Program Center inBoulder Colorado The netCDF libraries define a machine-independent format for representing scientific data Pleasesee Unidata NetCDF pages for more information and to retreive NetCDF software package onhttpwwwunidataucaredupackagesnetcdfindexhtml
NetCDF data is
bull Self-Describing A netCDF file includes information about the data it contains
bull Architecture-independent A netCDF file is represented in a form that can be accessed by computers with dif-ferent ways of storing integers characters and floating-point numbers
bull Direct-access A small subset of a large dataset may be accessed efficiently without first reading through allthe preceding data
bull Appendable Data can be appended to a netCDF dataset along one dimension without copying the dataset orredefining its structure The structure of a netCDF dataset can be changed though this sometimes causes thedataset to be copied
bull Sharable One writer and multiple readers may simultaneously access the same netCDF file
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VII2 Structure and semantic of NetCDF along-track files
The NetCDF Sea Level TAC files are based on the attribute data tags defined by the Cooperative OceanAtmosphereResearch Data Service (COARDS) and Climate and Forecast (CF) metadata conventions The CF convention gener-alises and extends the COARDS convention but relaxes the COARDS constraints on dimension and order and specifiesmethods for reducing the size of datasetsA wide range of software are available to write or read NetCDFCF files API are made available by UNIDATA(httpwwwunidataucaredusoftwarenetcdf)
bull CC++Fortran
bull Java
bull MATLAB Objective-C Perl Python R Ruby TclTk
In addition to these conventions the files are using a common structure and semantic
bull 1 dimension is defined
ndash time it is used to check NetCDF variables depending on time
bull 8 variables are defined
ndash short SLA contains the Sea Level Anomaly values for each time given
ndash int longitude contains the longitude for each measurement
ndash short track contains the track number for each measurement
ndash double time contains the time in days since 1950-01-01 000000 UTC for each measurement
ndash short mean_profile_point_index index of the corrsponding point in the track of the mean profile
ndash byte flag flag=0 the processed data comes from OGDR if flag=1 the processed data comes from theIGDR
ndash int latitude contains the latitude for each measurement
ndash short cycle contains the cycle number for each measurement
bull global attributes
ndash the global attributes gives information about the creation of the file
Example of a NetCDF sla file
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netcdf nrt_global_j1_sla_vfec_20101230_20101230_20101230 dimensions
time = 10385 variables
short SLA(time) SLAcoordinates = longitude latitude SLAlong_name = Sea Level Anomaly SLA_FillValue = 32767s SLAadd_offset = 0 SLAscale_factor = 0001 SLAunits = m SLAstandard_name = sea_surface_height_above_sea_level
int longitude(time) longitudelong_name = Longitude of measurement longitude_FillValue = 2147483647 longitudeadd_offset = 0 longitudestandard_name = longitude longitudescale_factor = 1e-06 longitudeunits = degrees_east
short track(time) tracklong_name = Track in cycle the measurement belongs to track_FillValue = 32767s trackunits = 1 trackcoordinates = longitude latitude
double time(time) timelong_name = Time of measurement time_FillValue = 184467440737096e+19 timeaxis = T timestandard_name = time timeunits = days since 1950-01-01 000000 UTC
int latitude(time) latitudelong_name = Latitude of measurement latitude_FillValue = 2147483647 latitudeadd_offset = 0 latitudestandard_name = latitude latitudescale_factor = 1e-06 latitudeunits = degrees_north
short flag(time) flagcoordinates = longitude latitude flag_FillValue = 3267s flaglong_name = data origin flagflag_values = 1s 0s flagflag_meanings = igdr_like non_igdr_like flagcomment = The origin of the data is determined by the types of geophysical datarecords (GDR) used in computation of the SLA 1 for the Interim GDR (IGDR) and0 for Operational GDR (OGDR)
short cycle(time) cyclelong_name = Cycle the measurement belongs to cycle_FillValue = 32767s cycleunits = 1 cyclecoordinates = longitude latitude
global attributeshistory = 22-Feb-2011 155243 CET File created by the SSLATODUACS system version 1001 comment = Produce from ENVISAT Extension Phase satellite altimetry data institution = CLSCNES
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references = httpwwwavisooceanobscomfileadmindocumentsdatatoolshdbk_duacspdf source = satellite altimetry title = along track Sea Level Anomaly Conventions = CF-14
dataSLA =
7 7 11 10 -2 -22 -39 -41 -30 -13 -3 -5 -16 -26 -32 -35-35 -35 -37 -35 -31 -29 -31 -35 -32 -21 -10 -10 -19 -20 -1-69 -57 -49 -45 -39 -30 -28 -31 -27 -13 -2 -5 -15 -3 1112 3 -7 -10 -14 -15 -22 -31 -37 -32 -17 -10
longitude =74743328 74868400 74993968 75120040 75246616 7537372875501368 75629568 75758320 75887656 76017568 76148080 7627920876388952 76477056 76565456 76654144 76743128 76832400 76921984329429568 329535424 329641792 329748672 329856096 329964032330072512 330181536 330291072 330401184
track =92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 9292 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92113 113 113 113 113 113 113 113 113 113 113 113 113 113113 113 113 113 113 113 113 113 113
time =222780000565705 222780001314719 222780002063733222780002812747 222780003561761 222780004310775 222780005059788222780005808802 222780006557816 22278000730683 222780008055844222780008804858 222780009553872 22278001017805 222780010677393222788257112198 222788257486705 222788257861212 222788258235719222788258610226 222788258984733 222788259359239 222788259733746222788260108253 22278826048276
mean_profile_point_index =1872 1878 1884 1890 1896 1902 1908 19141920 1926 1932 1938 1944 1949 1953 1957 1961 1965 1969 19732306 2309 2312 2315 2318 2321 2327 2330 2333 2336 2339 23422345 2348 2351 2354 2357 2360 2363 2366
flag =0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
latitude =-16225506 -16539731 -16853833 -17167810 -17481660 -17795380-18108966 -18422418 -18735729 -19048899 -19361924 -19674801-19987527 -20248015 -20456329 -20664569 -20872739 -2108083739481297 39628277 39775133 39921866 40068472 40214953 4036130840507533 40653629 40799592 40945423 41091120 41236684 41382111
cycle =331 331 331 331 331 331 331 331 331 331 331 331 331
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331 331 331 331 331 331 331 331 331 331 331 331 331 331331 331 331 331 331 331 331 331 331 331 331 331
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VIII HOW TO DOWNLOAD A PRODUCT
VIII1 Download a product through the MyOcean Web Portal DirectgetfileService
You first need to register Please find below the registration stepshttpwwwmyoceaneuweb34-products-and-services-faqphp1Once registered the MyOcean FAQ httpwwwmyoceaneuweb34-products-and-services-faqwill guide you on How to download a product through the MyOcean Web Portal Directgetfile Service
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IX NEWS AND UPDATES
IX1 [Duacs] Operational news
To be kept informed on events occurring on the satellites and on the eventual interruption of the services of the DUACSprocessing system see the [Duacs] operational news on the Aviso websitehttpwwwavisooceanobscomendataoperational-newsindexhtml
IX2 Updates
To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtmlSince 2010 a complete reprocessing of all altimetry data (cumulated total of about 55 years of data) is available Themain changes introduced in the Duacs DT v300 reprocessed data set in SSALTODUACS reprocessed DT data setare listed herehttpwwwavisooceanobscomfileadmindocumentsdataduacsduacs_DT_2010_reprocessing_impactpdf
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III37 Quality control
The production of homogeneous products in a high quality data with a short delay is the key feature of theDUACS processing system But some events (failure on payload or on instruments delay maintenance onservers) can impact the quality of measurements or the data flows A strict quality control on each process-ing step is indispensable to appreciate the overall quality of the system and to provide the best user services
III371 Final quality Control
The Quality Control is the final process used by DUACS before product delivery In addition to dailyautomated controls and warnings to the operators each production delivers a large QC Report composed ofdetailed logs figures and statistics of each processing step Altimetry experts analyse these reports twice aweek
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IV MYOCEAN PRODUCTS
IV1 Near Real Time Products
The purpose of the NRT DUACS component is the acquisition of altimeter data from various altimeter mis-sions in near-real time (ie within a few days at most) the validation and correction of these altimeter datasets (ie edition and selection update of corrections and homogenization orbit error reduction) in order toproduce each day along-track productsProducts are as follows
Along-track products global and regional (Mediterranean and Black Seas Arctic Ocean and Europeareas)
bull Sea Level Anomaly (NRT-SLA) for each mission with NRT-SLA ephemeris
IV11 Delay of the products
The availability of the products in near real time is three to twelve hours after the measurement for along-track products Those products are delivered every day
IV12 Temporal availibility
The following table presents the available products by mission and by data periodNear real time products
NRT Jason-2 Jason-1 and Jason-1geodetic
Envisat new Cryosat-2
Temporal Time availability ymlowast
ongoingymlowast-20120303 for
repeat track and20120507-ongoing for
geodetic track
ymlowast
2012040820120101
ongoing
NRT-SLA X X X X
lowastym the temporal coverage for NRT products is fluctuating and depends on updates of Delayed Time prod-ucts When DT products are updated (3 to 4 times per year) the oldest NRT products are replaced by thebetter quality DT products so that the 2 series are overlapping on few weeks or few months
IV2 Delayed Time Products
The Delayed Time component of SSALTODUACS system is responsible for the production of processedJason-1 Jason-2 TP Envisat GFO ERS12 and even Geosat data in order to provide a homogeneousinter-calibrated and highly accurate long time series of SLA DT products are more precise than NRT products Two reasons explain this quality difference The firstone is the better intrinsic quality of the POE orbit used in the GDR processing The second reason is that
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in the DT DUACS processing the products can be computed optimally with a centred computation timewindow for OER LWE On the contrary in NRT case future data are not available so the computationtime window is not centred and therefore not optimalAs for NRT products improved altimeter corrections and processing algorithms are used ocean tide modelto correct altimeter data improved methods for orbit error reduction and mapping
Along-Track products global and regional (Mediterranean and Black Seas)
bull Sea Level Anomaly (DT-SLA) for each mission
IV21 Delay of the products
Weekly products are delivered The availability of the products in delayed time is at the best two monthsafter the date of the measurement The product generation needs all the GDR data of all the missions to takeinto account the best corrections as possible The time delay can be longer in the case of a missing mission
IV22 Temporal availibility
The following table presents the available products by mission and by data periodDelayed time SSALTODUACS products
Upd Jason-2 Jason-1new6
Jason-1 GFO Envisatnew6
Envisat ERS-16
ERS-2Topexnew6
Topex
TemporalTimeavailabil-ity
200810ymlowast
200902ymlowast
200204200810
200001200809
201010ymlowast
200210201010
199210200304
200209200510
199209200204
DT-SLA X X X X X X X X X
lowast ym those dates are updated regularly (3 to 4 times per year) and are avalaible when you download thedata at httpwwwmyoceaneuweb24-cataloguephp6 Jason-1 new orbit starting 200809 Envisat new orbit starting 201010 TP new orbit starting 200209 ERS-1The geodetic phases (E-F) are included There are no ERS-1 data between December 23 1993 and April 10 1994(ERS-1 phase D - 2nd ice phase) Note that during that time products are based only on TopexPoseidon data
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V DESCRIPTION OF THE PRODUCT SPECIFICATION
V1 General information
Product Specification SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001
Geographical coverage global
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 20-50km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001 Product Specification
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Product Specification SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002
Geographical coverage 55˚W-35˚E 30˚N-46˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002 Product Specification
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Product Specification SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003
Geographical coverage 27˚E-42˚E 40˚N-47˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003 Product Specification
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Product Specification SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004
Geographical coverage 25˚W-42˚E 21˚N-66˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004 Product Specification
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Product Specification SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005
Geographical coverage 0˚W-360˚E 50˚N-82˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005 Product Specification
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VI NOMENCLATURE OF FILES
VI1 Nomenclature of files downloaded through the MyOcean Web PortalDirectgetfile Service
VI11 Nomenclature of the product line
The description of the syntax for the SL TAC SLA products line is given by
SEALEVEL_ltREGIONgt_SLA_L3_ltDELAYgt_OBSERVATIONS_008_ltZONEgt_ltLETTERgtwhere
REGION GLO global geographic coverage product
BS Black Sea products
MED Mediterranean products
ARC Arctic products (for NRT products)
EUROPE Europe products (for NRT products)
DELAY NRT near real time products
RAN delayed time or reanalysis products
ZONE 001 number on 3 digits
002
003
004
LETTER a letter on 1 digit
b
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VI12 Nomenclature of the datasets
The nomenclature used is
dataset-duacs-ltdelaygt-ltzonegt-ltmissiongt-lttype of slagt-l3where the fileds in ltgt are described below
delay nrt near-real time productsran delayed time products
zone global global geographic coverage productmedsea Mediterranean productsblacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1 (only for ran)e2 ERS-2 (only for ran)tp TOPEXPoseidon (only for ran)tpn TOPEXPoseidon on its new orbit (only for
ran)g2 GFO (only for ran)j1 Jason-1 (only for ran)j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisat (only for ran)enn Envisat on its new orbitc2 Cryosat-2 (only for nrt)
type of sla sla filtered slasla_unfiltered non filtered sla (only for ran products)
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VI13 Nomenclature of the NetCdf files
The nomenclature used is
ltdelaygt_ltzonegt_ltmissiongt_sla_ltvariablegt_ltdatebegingt_ltdateendgt_ltdateprodgtnc where the fileds in ltgt are de-scribed below
delay nrt near-real time productsdt delayed time products
zone global global geographic coverage productmed Mediterranean products (for dt)mfstep Mediterranean products (for nrt)blacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1e2 ERS-2tp TOPEXPoseidontpn TOPEXPoseidon on its new orbitg2 GFOj1 Jason-1j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisatenn Envisat on its new orbitc2 Cryosat-2
variable vfec filtered and sub-sampled slavxxc non filtered and non sub-sampled sla (only
for dt)datebegin YYYYMMDD() beginning date of the datasetdateend YYYYMMDD() end date of the datasetdateprod YYYYMMDD production date of the dataset
() For dt data as the dates in the file names are rounded the user wanting data for date T has to read the filescontaining dates T+1 and T-1 in their name and check inside the files if there are some data for date T
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VII DATA FORMAT
This chapter presents the data storage format used for MyOcean products
VII1 NetCdf
The products are stored using the NetCDF format NetCDF (network Common Data Form) is an interface for array-oriented data access and a library that provides an implementation of the interface The netCDF library also definesa machine-independent format for representing scientific data Together the interface library and format support thecreation access and sharing of scientific data The netCDF software was developed at the Unidata Program Center inBoulder Colorado The netCDF libraries define a machine-independent format for representing scientific data Pleasesee Unidata NetCDF pages for more information and to retreive NetCDF software package onhttpwwwunidataucaredupackagesnetcdfindexhtml
NetCDF data is
bull Self-Describing A netCDF file includes information about the data it contains
bull Architecture-independent A netCDF file is represented in a form that can be accessed by computers with dif-ferent ways of storing integers characters and floating-point numbers
bull Direct-access A small subset of a large dataset may be accessed efficiently without first reading through allthe preceding data
bull Appendable Data can be appended to a netCDF dataset along one dimension without copying the dataset orredefining its structure The structure of a netCDF dataset can be changed though this sometimes causes thedataset to be copied
bull Sharable One writer and multiple readers may simultaneously access the same netCDF file
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VII2 Structure and semantic of NetCDF along-track files
The NetCDF Sea Level TAC files are based on the attribute data tags defined by the Cooperative OceanAtmosphereResearch Data Service (COARDS) and Climate and Forecast (CF) metadata conventions The CF convention gener-alises and extends the COARDS convention but relaxes the COARDS constraints on dimension and order and specifiesmethods for reducing the size of datasetsA wide range of software are available to write or read NetCDFCF files API are made available by UNIDATA(httpwwwunidataucaredusoftwarenetcdf)
bull CC++Fortran
bull Java
bull MATLAB Objective-C Perl Python R Ruby TclTk
In addition to these conventions the files are using a common structure and semantic
bull 1 dimension is defined
ndash time it is used to check NetCDF variables depending on time
bull 8 variables are defined
ndash short SLA contains the Sea Level Anomaly values for each time given
ndash int longitude contains the longitude for each measurement
ndash short track contains the track number for each measurement
ndash double time contains the time in days since 1950-01-01 000000 UTC for each measurement
ndash short mean_profile_point_index index of the corrsponding point in the track of the mean profile
ndash byte flag flag=0 the processed data comes from OGDR if flag=1 the processed data comes from theIGDR
ndash int latitude contains the latitude for each measurement
ndash short cycle contains the cycle number for each measurement
bull global attributes
ndash the global attributes gives information about the creation of the file
Example of a NetCDF sla file
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netcdf nrt_global_j1_sla_vfec_20101230_20101230_20101230 dimensions
time = 10385 variables
short SLA(time) SLAcoordinates = longitude latitude SLAlong_name = Sea Level Anomaly SLA_FillValue = 32767s SLAadd_offset = 0 SLAscale_factor = 0001 SLAunits = m SLAstandard_name = sea_surface_height_above_sea_level
int longitude(time) longitudelong_name = Longitude of measurement longitude_FillValue = 2147483647 longitudeadd_offset = 0 longitudestandard_name = longitude longitudescale_factor = 1e-06 longitudeunits = degrees_east
short track(time) tracklong_name = Track in cycle the measurement belongs to track_FillValue = 32767s trackunits = 1 trackcoordinates = longitude latitude
double time(time) timelong_name = Time of measurement time_FillValue = 184467440737096e+19 timeaxis = T timestandard_name = time timeunits = days since 1950-01-01 000000 UTC
int latitude(time) latitudelong_name = Latitude of measurement latitude_FillValue = 2147483647 latitudeadd_offset = 0 latitudestandard_name = latitude latitudescale_factor = 1e-06 latitudeunits = degrees_north
short flag(time) flagcoordinates = longitude latitude flag_FillValue = 3267s flaglong_name = data origin flagflag_values = 1s 0s flagflag_meanings = igdr_like non_igdr_like flagcomment = The origin of the data is determined by the types of geophysical datarecords (GDR) used in computation of the SLA 1 for the Interim GDR (IGDR) and0 for Operational GDR (OGDR)
short cycle(time) cyclelong_name = Cycle the measurement belongs to cycle_FillValue = 32767s cycleunits = 1 cyclecoordinates = longitude latitude
global attributeshistory = 22-Feb-2011 155243 CET File created by the SSLATODUACS system version 1001 comment = Produce from ENVISAT Extension Phase satellite altimetry data institution = CLSCNES
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references = httpwwwavisooceanobscomfileadmindocumentsdatatoolshdbk_duacspdf source = satellite altimetry title = along track Sea Level Anomaly Conventions = CF-14
dataSLA =
7 7 11 10 -2 -22 -39 -41 -30 -13 -3 -5 -16 -26 -32 -35-35 -35 -37 -35 -31 -29 -31 -35 -32 -21 -10 -10 -19 -20 -1-69 -57 -49 -45 -39 -30 -28 -31 -27 -13 -2 -5 -15 -3 1112 3 -7 -10 -14 -15 -22 -31 -37 -32 -17 -10
longitude =74743328 74868400 74993968 75120040 75246616 7537372875501368 75629568 75758320 75887656 76017568 76148080 7627920876388952 76477056 76565456 76654144 76743128 76832400 76921984329429568 329535424 329641792 329748672 329856096 329964032330072512 330181536 330291072 330401184
track =92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 9292 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92113 113 113 113 113 113 113 113 113 113 113 113 113 113113 113 113 113 113 113 113 113 113
time =222780000565705 222780001314719 222780002063733222780002812747 222780003561761 222780004310775 222780005059788222780005808802 222780006557816 22278000730683 222780008055844222780008804858 222780009553872 22278001017805 222780010677393222788257112198 222788257486705 222788257861212 222788258235719222788258610226 222788258984733 222788259359239 222788259733746222788260108253 22278826048276
mean_profile_point_index =1872 1878 1884 1890 1896 1902 1908 19141920 1926 1932 1938 1944 1949 1953 1957 1961 1965 1969 19732306 2309 2312 2315 2318 2321 2327 2330 2333 2336 2339 23422345 2348 2351 2354 2357 2360 2363 2366
flag =0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
latitude =-16225506 -16539731 -16853833 -17167810 -17481660 -17795380-18108966 -18422418 -18735729 -19048899 -19361924 -19674801-19987527 -20248015 -20456329 -20664569 -20872739 -2108083739481297 39628277 39775133 39921866 40068472 40214953 4036130840507533 40653629 40799592 40945423 41091120 41236684 41382111
cycle =331 331 331 331 331 331 331 331 331 331 331 331 331
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331 331 331 331 331 331 331 331 331 331 331 331 331 331331 331 331 331 331 331 331 331 331 331 331 331
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VIII HOW TO DOWNLOAD A PRODUCT
VIII1 Download a product through the MyOcean Web Portal DirectgetfileService
You first need to register Please find below the registration stepshttpwwwmyoceaneuweb34-products-and-services-faqphp1Once registered the MyOcean FAQ httpwwwmyoceaneuweb34-products-and-services-faqwill guide you on How to download a product through the MyOcean Web Portal Directgetfile Service
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IX NEWS AND UPDATES
IX1 [Duacs] Operational news
To be kept informed on events occurring on the satellites and on the eventual interruption of the services of the DUACSprocessing system see the [Duacs] operational news on the Aviso websitehttpwwwavisooceanobscomendataoperational-newsindexhtml
IX2 Updates
To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtmlSince 2010 a complete reprocessing of all altimetry data (cumulated total of about 55 years of data) is available Themain changes introduced in the Duacs DT v300 reprocessed data set in SSALTODUACS reprocessed DT data setare listed herehttpwwwavisooceanobscomfileadmindocumentsdataduacsduacs_DT_2010_reprocessing_impactpdf
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IV MYOCEAN PRODUCTS
IV1 Near Real Time Products
The purpose of the NRT DUACS component is the acquisition of altimeter data from various altimeter mis-sions in near-real time (ie within a few days at most) the validation and correction of these altimeter datasets (ie edition and selection update of corrections and homogenization orbit error reduction) in order toproduce each day along-track productsProducts are as follows
Along-track products global and regional (Mediterranean and Black Seas Arctic Ocean and Europeareas)
bull Sea Level Anomaly (NRT-SLA) for each mission with NRT-SLA ephemeris
IV11 Delay of the products
The availability of the products in near real time is three to twelve hours after the measurement for along-track products Those products are delivered every day
IV12 Temporal availibility
The following table presents the available products by mission and by data periodNear real time products
NRT Jason-2 Jason-1 and Jason-1geodetic
Envisat new Cryosat-2
Temporal Time availability ymlowast
ongoingymlowast-20120303 for
repeat track and20120507-ongoing for
geodetic track
ymlowast
2012040820120101
ongoing
NRT-SLA X X X X
lowastym the temporal coverage for NRT products is fluctuating and depends on updates of Delayed Time prod-ucts When DT products are updated (3 to 4 times per year) the oldest NRT products are replaced by thebetter quality DT products so that the 2 series are overlapping on few weeks or few months
IV2 Delayed Time Products
The Delayed Time component of SSALTODUACS system is responsible for the production of processedJason-1 Jason-2 TP Envisat GFO ERS12 and even Geosat data in order to provide a homogeneousinter-calibrated and highly accurate long time series of SLA DT products are more precise than NRT products Two reasons explain this quality difference The firstone is the better intrinsic quality of the POE orbit used in the GDR processing The second reason is that
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in the DT DUACS processing the products can be computed optimally with a centred computation timewindow for OER LWE On the contrary in NRT case future data are not available so the computationtime window is not centred and therefore not optimalAs for NRT products improved altimeter corrections and processing algorithms are used ocean tide modelto correct altimeter data improved methods for orbit error reduction and mapping
Along-Track products global and regional (Mediterranean and Black Seas)
bull Sea Level Anomaly (DT-SLA) for each mission
IV21 Delay of the products
Weekly products are delivered The availability of the products in delayed time is at the best two monthsafter the date of the measurement The product generation needs all the GDR data of all the missions to takeinto account the best corrections as possible The time delay can be longer in the case of a missing mission
IV22 Temporal availibility
The following table presents the available products by mission and by data periodDelayed time SSALTODUACS products
Upd Jason-2 Jason-1new6
Jason-1 GFO Envisatnew6
Envisat ERS-16
ERS-2Topexnew6
Topex
TemporalTimeavailabil-ity
200810ymlowast
200902ymlowast
200204200810
200001200809
201010ymlowast
200210201010
199210200304
200209200510
199209200204
DT-SLA X X X X X X X X X
lowast ym those dates are updated regularly (3 to 4 times per year) and are avalaible when you download thedata at httpwwwmyoceaneuweb24-cataloguephp6 Jason-1 new orbit starting 200809 Envisat new orbit starting 201010 TP new orbit starting 200209 ERS-1The geodetic phases (E-F) are included There are no ERS-1 data between December 23 1993 and April 10 1994(ERS-1 phase D - 2nd ice phase) Note that during that time products are based only on TopexPoseidon data
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V DESCRIPTION OF THE PRODUCT SPECIFICATION
V1 General information
Product Specification SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001
Geographical coverage global
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 20-50km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001 Product Specification
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Product Specification SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002
Geographical coverage 55˚W-35˚E 30˚N-46˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002 Product Specification
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Product Specification SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003
Geographical coverage 27˚E-42˚E 40˚N-47˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003 Product Specification
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Product Specification SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004
Geographical coverage 25˚W-42˚E 21˚N-66˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004 Product Specification
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Product Specification SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005
Geographical coverage 0˚W-360˚E 50˚N-82˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005 Product Specification
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VI NOMENCLATURE OF FILES
VI1 Nomenclature of files downloaded through the MyOcean Web PortalDirectgetfile Service
VI11 Nomenclature of the product line
The description of the syntax for the SL TAC SLA products line is given by
SEALEVEL_ltREGIONgt_SLA_L3_ltDELAYgt_OBSERVATIONS_008_ltZONEgt_ltLETTERgtwhere
REGION GLO global geographic coverage product
BS Black Sea products
MED Mediterranean products
ARC Arctic products (for NRT products)
EUROPE Europe products (for NRT products)
DELAY NRT near real time products
RAN delayed time or reanalysis products
ZONE 001 number on 3 digits
002
003
004
LETTER a letter on 1 digit
b
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VI12 Nomenclature of the datasets
The nomenclature used is
dataset-duacs-ltdelaygt-ltzonegt-ltmissiongt-lttype of slagt-l3where the fileds in ltgt are described below
delay nrt near-real time productsran delayed time products
zone global global geographic coverage productmedsea Mediterranean productsblacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1 (only for ran)e2 ERS-2 (only for ran)tp TOPEXPoseidon (only for ran)tpn TOPEXPoseidon on its new orbit (only for
ran)g2 GFO (only for ran)j1 Jason-1 (only for ran)j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisat (only for ran)enn Envisat on its new orbitc2 Cryosat-2 (only for nrt)
type of sla sla filtered slasla_unfiltered non filtered sla (only for ran products)
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VI13 Nomenclature of the NetCdf files
The nomenclature used is
ltdelaygt_ltzonegt_ltmissiongt_sla_ltvariablegt_ltdatebegingt_ltdateendgt_ltdateprodgtnc where the fileds in ltgt are de-scribed below
delay nrt near-real time productsdt delayed time products
zone global global geographic coverage productmed Mediterranean products (for dt)mfstep Mediterranean products (for nrt)blacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1e2 ERS-2tp TOPEXPoseidontpn TOPEXPoseidon on its new orbitg2 GFOj1 Jason-1j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisatenn Envisat on its new orbitc2 Cryosat-2
variable vfec filtered and sub-sampled slavxxc non filtered and non sub-sampled sla (only
for dt)datebegin YYYYMMDD() beginning date of the datasetdateend YYYYMMDD() end date of the datasetdateprod YYYYMMDD production date of the dataset
() For dt data as the dates in the file names are rounded the user wanting data for date T has to read the filescontaining dates T+1 and T-1 in their name and check inside the files if there are some data for date T
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VII DATA FORMAT
This chapter presents the data storage format used for MyOcean products
VII1 NetCdf
The products are stored using the NetCDF format NetCDF (network Common Data Form) is an interface for array-oriented data access and a library that provides an implementation of the interface The netCDF library also definesa machine-independent format for representing scientific data Together the interface library and format support thecreation access and sharing of scientific data The netCDF software was developed at the Unidata Program Center inBoulder Colorado The netCDF libraries define a machine-independent format for representing scientific data Pleasesee Unidata NetCDF pages for more information and to retreive NetCDF software package onhttpwwwunidataucaredupackagesnetcdfindexhtml
NetCDF data is
bull Self-Describing A netCDF file includes information about the data it contains
bull Architecture-independent A netCDF file is represented in a form that can be accessed by computers with dif-ferent ways of storing integers characters and floating-point numbers
bull Direct-access A small subset of a large dataset may be accessed efficiently without first reading through allthe preceding data
bull Appendable Data can be appended to a netCDF dataset along one dimension without copying the dataset orredefining its structure The structure of a netCDF dataset can be changed though this sometimes causes thedataset to be copied
bull Sharable One writer and multiple readers may simultaneously access the same netCDF file
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VII2 Structure and semantic of NetCDF along-track files
The NetCDF Sea Level TAC files are based on the attribute data tags defined by the Cooperative OceanAtmosphereResearch Data Service (COARDS) and Climate and Forecast (CF) metadata conventions The CF convention gener-alises and extends the COARDS convention but relaxes the COARDS constraints on dimension and order and specifiesmethods for reducing the size of datasetsA wide range of software are available to write or read NetCDFCF files API are made available by UNIDATA(httpwwwunidataucaredusoftwarenetcdf)
bull CC++Fortran
bull Java
bull MATLAB Objective-C Perl Python R Ruby TclTk
In addition to these conventions the files are using a common structure and semantic
bull 1 dimension is defined
ndash time it is used to check NetCDF variables depending on time
bull 8 variables are defined
ndash short SLA contains the Sea Level Anomaly values for each time given
ndash int longitude contains the longitude for each measurement
ndash short track contains the track number for each measurement
ndash double time contains the time in days since 1950-01-01 000000 UTC for each measurement
ndash short mean_profile_point_index index of the corrsponding point in the track of the mean profile
ndash byte flag flag=0 the processed data comes from OGDR if flag=1 the processed data comes from theIGDR
ndash int latitude contains the latitude for each measurement
ndash short cycle contains the cycle number for each measurement
bull global attributes
ndash the global attributes gives information about the creation of the file
Example of a NetCDF sla file
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netcdf nrt_global_j1_sla_vfec_20101230_20101230_20101230 dimensions
time = 10385 variables
short SLA(time) SLAcoordinates = longitude latitude SLAlong_name = Sea Level Anomaly SLA_FillValue = 32767s SLAadd_offset = 0 SLAscale_factor = 0001 SLAunits = m SLAstandard_name = sea_surface_height_above_sea_level
int longitude(time) longitudelong_name = Longitude of measurement longitude_FillValue = 2147483647 longitudeadd_offset = 0 longitudestandard_name = longitude longitudescale_factor = 1e-06 longitudeunits = degrees_east
short track(time) tracklong_name = Track in cycle the measurement belongs to track_FillValue = 32767s trackunits = 1 trackcoordinates = longitude latitude
double time(time) timelong_name = Time of measurement time_FillValue = 184467440737096e+19 timeaxis = T timestandard_name = time timeunits = days since 1950-01-01 000000 UTC
int latitude(time) latitudelong_name = Latitude of measurement latitude_FillValue = 2147483647 latitudeadd_offset = 0 latitudestandard_name = latitude latitudescale_factor = 1e-06 latitudeunits = degrees_north
short flag(time) flagcoordinates = longitude latitude flag_FillValue = 3267s flaglong_name = data origin flagflag_values = 1s 0s flagflag_meanings = igdr_like non_igdr_like flagcomment = The origin of the data is determined by the types of geophysical datarecords (GDR) used in computation of the SLA 1 for the Interim GDR (IGDR) and0 for Operational GDR (OGDR)
short cycle(time) cyclelong_name = Cycle the measurement belongs to cycle_FillValue = 32767s cycleunits = 1 cyclecoordinates = longitude latitude
global attributeshistory = 22-Feb-2011 155243 CET File created by the SSLATODUACS system version 1001 comment = Produce from ENVISAT Extension Phase satellite altimetry data institution = CLSCNES
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references = httpwwwavisooceanobscomfileadmindocumentsdatatoolshdbk_duacspdf source = satellite altimetry title = along track Sea Level Anomaly Conventions = CF-14
dataSLA =
7 7 11 10 -2 -22 -39 -41 -30 -13 -3 -5 -16 -26 -32 -35-35 -35 -37 -35 -31 -29 -31 -35 -32 -21 -10 -10 -19 -20 -1-69 -57 -49 -45 -39 -30 -28 -31 -27 -13 -2 -5 -15 -3 1112 3 -7 -10 -14 -15 -22 -31 -37 -32 -17 -10
longitude =74743328 74868400 74993968 75120040 75246616 7537372875501368 75629568 75758320 75887656 76017568 76148080 7627920876388952 76477056 76565456 76654144 76743128 76832400 76921984329429568 329535424 329641792 329748672 329856096 329964032330072512 330181536 330291072 330401184
track =92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 9292 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92113 113 113 113 113 113 113 113 113 113 113 113 113 113113 113 113 113 113 113 113 113 113
time =222780000565705 222780001314719 222780002063733222780002812747 222780003561761 222780004310775 222780005059788222780005808802 222780006557816 22278000730683 222780008055844222780008804858 222780009553872 22278001017805 222780010677393222788257112198 222788257486705 222788257861212 222788258235719222788258610226 222788258984733 222788259359239 222788259733746222788260108253 22278826048276
mean_profile_point_index =1872 1878 1884 1890 1896 1902 1908 19141920 1926 1932 1938 1944 1949 1953 1957 1961 1965 1969 19732306 2309 2312 2315 2318 2321 2327 2330 2333 2336 2339 23422345 2348 2351 2354 2357 2360 2363 2366
flag =0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
latitude =-16225506 -16539731 -16853833 -17167810 -17481660 -17795380-18108966 -18422418 -18735729 -19048899 -19361924 -19674801-19987527 -20248015 -20456329 -20664569 -20872739 -2108083739481297 39628277 39775133 39921866 40068472 40214953 4036130840507533 40653629 40799592 40945423 41091120 41236684 41382111
cycle =331 331 331 331 331 331 331 331 331 331 331 331 331
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331 331 331 331 331 331 331 331 331 331 331 331 331 331331 331 331 331 331 331 331 331 331 331 331 331
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VIII HOW TO DOWNLOAD A PRODUCT
VIII1 Download a product through the MyOcean Web Portal DirectgetfileService
You first need to register Please find below the registration stepshttpwwwmyoceaneuweb34-products-and-services-faqphp1Once registered the MyOcean FAQ httpwwwmyoceaneuweb34-products-and-services-faqwill guide you on How to download a product through the MyOcean Web Portal Directgetfile Service
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IX NEWS AND UPDATES
IX1 [Duacs] Operational news
To be kept informed on events occurring on the satellites and on the eventual interruption of the services of the DUACSprocessing system see the [Duacs] operational news on the Aviso websitehttpwwwavisooceanobscomendataoperational-newsindexhtml
IX2 Updates
To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtmlSince 2010 a complete reprocessing of all altimetry data (cumulated total of about 55 years of data) is available Themain changes introduced in the Duacs DT v300 reprocessed data set in SSALTODUACS reprocessed DT data setare listed herehttpwwwavisooceanobscomfileadmindocumentsdataduacsduacs_DT_2010_reprocessing_impactpdf
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in the DT DUACS processing the products can be computed optimally with a centred computation timewindow for OER LWE On the contrary in NRT case future data are not available so the computationtime window is not centred and therefore not optimalAs for NRT products improved altimeter corrections and processing algorithms are used ocean tide modelto correct altimeter data improved methods for orbit error reduction and mapping
Along-Track products global and regional (Mediterranean and Black Seas)
bull Sea Level Anomaly (DT-SLA) for each mission
IV21 Delay of the products
Weekly products are delivered The availability of the products in delayed time is at the best two monthsafter the date of the measurement The product generation needs all the GDR data of all the missions to takeinto account the best corrections as possible The time delay can be longer in the case of a missing mission
IV22 Temporal availibility
The following table presents the available products by mission and by data periodDelayed time SSALTODUACS products
Upd Jason-2 Jason-1new6
Jason-1 GFO Envisatnew6
Envisat ERS-16
ERS-2Topexnew6
Topex
TemporalTimeavailabil-ity
200810ymlowast
200902ymlowast
200204200810
200001200809
201010ymlowast
200210201010
199210200304
200209200510
199209200204
DT-SLA X X X X X X X X X
lowast ym those dates are updated regularly (3 to 4 times per year) and are avalaible when you download thedata at httpwwwmyoceaneuweb24-cataloguephp6 Jason-1 new orbit starting 200809 Envisat new orbit starting 201010 TP new orbit starting 200209 ERS-1The geodetic phases (E-F) are included There are no ERS-1 data between December 23 1993 and April 10 1994(ERS-1 phase D - 2nd ice phase) Note that during that time products are based only on TopexPoseidon data
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V DESCRIPTION OF THE PRODUCT SPECIFICATION
V1 General information
Product Specification SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001
Geographical coverage global
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 20-50km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001 Product Specification
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Product Specification SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002
Geographical coverage 55˚W-35˚E 30˚N-46˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002 Product Specification
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Product Specification SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003
Geographical coverage 27˚E-42˚E 40˚N-47˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003 Product Specification
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Product Specification SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004
Geographical coverage 25˚W-42˚E 21˚N-66˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004 Product Specification
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Product Specification SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005
Geographical coverage 0˚W-360˚E 50˚N-82˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005 Product Specification
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VI NOMENCLATURE OF FILES
VI1 Nomenclature of files downloaded through the MyOcean Web PortalDirectgetfile Service
VI11 Nomenclature of the product line
The description of the syntax for the SL TAC SLA products line is given by
SEALEVEL_ltREGIONgt_SLA_L3_ltDELAYgt_OBSERVATIONS_008_ltZONEgt_ltLETTERgtwhere
REGION GLO global geographic coverage product
BS Black Sea products
MED Mediterranean products
ARC Arctic products (for NRT products)
EUROPE Europe products (for NRT products)
DELAY NRT near real time products
RAN delayed time or reanalysis products
ZONE 001 number on 3 digits
002
003
004
LETTER a letter on 1 digit
b
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VI12 Nomenclature of the datasets
The nomenclature used is
dataset-duacs-ltdelaygt-ltzonegt-ltmissiongt-lttype of slagt-l3where the fileds in ltgt are described below
delay nrt near-real time productsran delayed time products
zone global global geographic coverage productmedsea Mediterranean productsblacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1 (only for ran)e2 ERS-2 (only for ran)tp TOPEXPoseidon (only for ran)tpn TOPEXPoseidon on its new orbit (only for
ran)g2 GFO (only for ran)j1 Jason-1 (only for ran)j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisat (only for ran)enn Envisat on its new orbitc2 Cryosat-2 (only for nrt)
type of sla sla filtered slasla_unfiltered non filtered sla (only for ran products)
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VI13 Nomenclature of the NetCdf files
The nomenclature used is
ltdelaygt_ltzonegt_ltmissiongt_sla_ltvariablegt_ltdatebegingt_ltdateendgt_ltdateprodgtnc where the fileds in ltgt are de-scribed below
delay nrt near-real time productsdt delayed time products
zone global global geographic coverage productmed Mediterranean products (for dt)mfstep Mediterranean products (for nrt)blacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1e2 ERS-2tp TOPEXPoseidontpn TOPEXPoseidon on its new orbitg2 GFOj1 Jason-1j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisatenn Envisat on its new orbitc2 Cryosat-2
variable vfec filtered and sub-sampled slavxxc non filtered and non sub-sampled sla (only
for dt)datebegin YYYYMMDD() beginning date of the datasetdateend YYYYMMDD() end date of the datasetdateprod YYYYMMDD production date of the dataset
() For dt data as the dates in the file names are rounded the user wanting data for date T has to read the filescontaining dates T+1 and T-1 in their name and check inside the files if there are some data for date T
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VII DATA FORMAT
This chapter presents the data storage format used for MyOcean products
VII1 NetCdf
The products are stored using the NetCDF format NetCDF (network Common Data Form) is an interface for array-oriented data access and a library that provides an implementation of the interface The netCDF library also definesa machine-independent format for representing scientific data Together the interface library and format support thecreation access and sharing of scientific data The netCDF software was developed at the Unidata Program Center inBoulder Colorado The netCDF libraries define a machine-independent format for representing scientific data Pleasesee Unidata NetCDF pages for more information and to retreive NetCDF software package onhttpwwwunidataucaredupackagesnetcdfindexhtml
NetCDF data is
bull Self-Describing A netCDF file includes information about the data it contains
bull Architecture-independent A netCDF file is represented in a form that can be accessed by computers with dif-ferent ways of storing integers characters and floating-point numbers
bull Direct-access A small subset of a large dataset may be accessed efficiently without first reading through allthe preceding data
bull Appendable Data can be appended to a netCDF dataset along one dimension without copying the dataset orredefining its structure The structure of a netCDF dataset can be changed though this sometimes causes thedataset to be copied
bull Sharable One writer and multiple readers may simultaneously access the same netCDF file
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VII2 Structure and semantic of NetCDF along-track files
The NetCDF Sea Level TAC files are based on the attribute data tags defined by the Cooperative OceanAtmosphereResearch Data Service (COARDS) and Climate and Forecast (CF) metadata conventions The CF convention gener-alises and extends the COARDS convention but relaxes the COARDS constraints on dimension and order and specifiesmethods for reducing the size of datasetsA wide range of software are available to write or read NetCDFCF files API are made available by UNIDATA(httpwwwunidataucaredusoftwarenetcdf)
bull CC++Fortran
bull Java
bull MATLAB Objective-C Perl Python R Ruby TclTk
In addition to these conventions the files are using a common structure and semantic
bull 1 dimension is defined
ndash time it is used to check NetCDF variables depending on time
bull 8 variables are defined
ndash short SLA contains the Sea Level Anomaly values for each time given
ndash int longitude contains the longitude for each measurement
ndash short track contains the track number for each measurement
ndash double time contains the time in days since 1950-01-01 000000 UTC for each measurement
ndash short mean_profile_point_index index of the corrsponding point in the track of the mean profile
ndash byte flag flag=0 the processed data comes from OGDR if flag=1 the processed data comes from theIGDR
ndash int latitude contains the latitude for each measurement
ndash short cycle contains the cycle number for each measurement
bull global attributes
ndash the global attributes gives information about the creation of the file
Example of a NetCDF sla file
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netcdf nrt_global_j1_sla_vfec_20101230_20101230_20101230 dimensions
time = 10385 variables
short SLA(time) SLAcoordinates = longitude latitude SLAlong_name = Sea Level Anomaly SLA_FillValue = 32767s SLAadd_offset = 0 SLAscale_factor = 0001 SLAunits = m SLAstandard_name = sea_surface_height_above_sea_level
int longitude(time) longitudelong_name = Longitude of measurement longitude_FillValue = 2147483647 longitudeadd_offset = 0 longitudestandard_name = longitude longitudescale_factor = 1e-06 longitudeunits = degrees_east
short track(time) tracklong_name = Track in cycle the measurement belongs to track_FillValue = 32767s trackunits = 1 trackcoordinates = longitude latitude
double time(time) timelong_name = Time of measurement time_FillValue = 184467440737096e+19 timeaxis = T timestandard_name = time timeunits = days since 1950-01-01 000000 UTC
int latitude(time) latitudelong_name = Latitude of measurement latitude_FillValue = 2147483647 latitudeadd_offset = 0 latitudestandard_name = latitude latitudescale_factor = 1e-06 latitudeunits = degrees_north
short flag(time) flagcoordinates = longitude latitude flag_FillValue = 3267s flaglong_name = data origin flagflag_values = 1s 0s flagflag_meanings = igdr_like non_igdr_like flagcomment = The origin of the data is determined by the types of geophysical datarecords (GDR) used in computation of the SLA 1 for the Interim GDR (IGDR) and0 for Operational GDR (OGDR)
short cycle(time) cyclelong_name = Cycle the measurement belongs to cycle_FillValue = 32767s cycleunits = 1 cyclecoordinates = longitude latitude
global attributeshistory = 22-Feb-2011 155243 CET File created by the SSLATODUACS system version 1001 comment = Produce from ENVISAT Extension Phase satellite altimetry data institution = CLSCNES
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references = httpwwwavisooceanobscomfileadmindocumentsdatatoolshdbk_duacspdf source = satellite altimetry title = along track Sea Level Anomaly Conventions = CF-14
dataSLA =
7 7 11 10 -2 -22 -39 -41 -30 -13 -3 -5 -16 -26 -32 -35-35 -35 -37 -35 -31 -29 -31 -35 -32 -21 -10 -10 -19 -20 -1-69 -57 -49 -45 -39 -30 -28 -31 -27 -13 -2 -5 -15 -3 1112 3 -7 -10 -14 -15 -22 -31 -37 -32 -17 -10
longitude =74743328 74868400 74993968 75120040 75246616 7537372875501368 75629568 75758320 75887656 76017568 76148080 7627920876388952 76477056 76565456 76654144 76743128 76832400 76921984329429568 329535424 329641792 329748672 329856096 329964032330072512 330181536 330291072 330401184
track =92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 9292 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92113 113 113 113 113 113 113 113 113 113 113 113 113 113113 113 113 113 113 113 113 113 113
time =222780000565705 222780001314719 222780002063733222780002812747 222780003561761 222780004310775 222780005059788222780005808802 222780006557816 22278000730683 222780008055844222780008804858 222780009553872 22278001017805 222780010677393222788257112198 222788257486705 222788257861212 222788258235719222788258610226 222788258984733 222788259359239 222788259733746222788260108253 22278826048276
mean_profile_point_index =1872 1878 1884 1890 1896 1902 1908 19141920 1926 1932 1938 1944 1949 1953 1957 1961 1965 1969 19732306 2309 2312 2315 2318 2321 2327 2330 2333 2336 2339 23422345 2348 2351 2354 2357 2360 2363 2366
flag =0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
latitude =-16225506 -16539731 -16853833 -17167810 -17481660 -17795380-18108966 -18422418 -18735729 -19048899 -19361924 -19674801-19987527 -20248015 -20456329 -20664569 -20872739 -2108083739481297 39628277 39775133 39921866 40068472 40214953 4036130840507533 40653629 40799592 40945423 41091120 41236684 41382111
cycle =331 331 331 331 331 331 331 331 331 331 331 331 331
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331 331 331 331 331 331 331 331 331 331 331 331 331 331331 331 331 331 331 331 331 331 331 331 331 331
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VIII HOW TO DOWNLOAD A PRODUCT
VIII1 Download a product through the MyOcean Web Portal DirectgetfileService
You first need to register Please find below the registration stepshttpwwwmyoceaneuweb34-products-and-services-faqphp1Once registered the MyOcean FAQ httpwwwmyoceaneuweb34-products-and-services-faqwill guide you on How to download a product through the MyOcean Web Portal Directgetfile Service
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IX NEWS AND UPDATES
IX1 [Duacs] Operational news
To be kept informed on events occurring on the satellites and on the eventual interruption of the services of the DUACSprocessing system see the [Duacs] operational news on the Aviso websitehttpwwwavisooceanobscomendataoperational-newsindexhtml
IX2 Updates
To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtmlSince 2010 a complete reprocessing of all altimetry data (cumulated total of about 55 years of data) is available Themain changes introduced in the Duacs DT v300 reprocessed data set in SSALTODUACS reprocessed DT data setare listed herehttpwwwavisooceanobscomfileadmindocumentsdataduacsduacs_DT_2010_reprocessing_impactpdf
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V DESCRIPTION OF THE PRODUCT SPECIFICATION
V1 General information
Product Specification SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001
Geographical coverage global
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 20-50km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_GLO_SLA_L3_OBSERVATIONS_008_001 Product Specification
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Product Specification SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002
Geographical coverage 55˚W-35˚E 30˚N-46˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002 Product Specification
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Product Specification SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003
Geographical coverage 27˚E-42˚E 40˚N-47˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003 Product Specification
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Product Specification SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004
Geographical coverage 25˚W-42˚E 21˚N-66˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004 Product Specification
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Product Specification SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005
Geographical coverage 0˚W-360˚E 50˚N-82˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005 Product Specification
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VI NOMENCLATURE OF FILES
VI1 Nomenclature of files downloaded through the MyOcean Web PortalDirectgetfile Service
VI11 Nomenclature of the product line
The description of the syntax for the SL TAC SLA products line is given by
SEALEVEL_ltREGIONgt_SLA_L3_ltDELAYgt_OBSERVATIONS_008_ltZONEgt_ltLETTERgtwhere
REGION GLO global geographic coverage product
BS Black Sea products
MED Mediterranean products
ARC Arctic products (for NRT products)
EUROPE Europe products (for NRT products)
DELAY NRT near real time products
RAN delayed time or reanalysis products
ZONE 001 number on 3 digits
002
003
004
LETTER a letter on 1 digit
b
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VI12 Nomenclature of the datasets
The nomenclature used is
dataset-duacs-ltdelaygt-ltzonegt-ltmissiongt-lttype of slagt-l3where the fileds in ltgt are described below
delay nrt near-real time productsran delayed time products
zone global global geographic coverage productmedsea Mediterranean productsblacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1 (only for ran)e2 ERS-2 (only for ran)tp TOPEXPoseidon (only for ran)tpn TOPEXPoseidon on its new orbit (only for
ran)g2 GFO (only for ran)j1 Jason-1 (only for ran)j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisat (only for ran)enn Envisat on its new orbitc2 Cryosat-2 (only for nrt)
type of sla sla filtered slasla_unfiltered non filtered sla (only for ran products)
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VI13 Nomenclature of the NetCdf files
The nomenclature used is
ltdelaygt_ltzonegt_ltmissiongt_sla_ltvariablegt_ltdatebegingt_ltdateendgt_ltdateprodgtnc where the fileds in ltgt are de-scribed below
delay nrt near-real time productsdt delayed time products
zone global global geographic coverage productmed Mediterranean products (for dt)mfstep Mediterranean products (for nrt)blacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1e2 ERS-2tp TOPEXPoseidontpn TOPEXPoseidon on its new orbitg2 GFOj1 Jason-1j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisatenn Envisat on its new orbitc2 Cryosat-2
variable vfec filtered and sub-sampled slavxxc non filtered and non sub-sampled sla (only
for dt)datebegin YYYYMMDD() beginning date of the datasetdateend YYYYMMDD() end date of the datasetdateprod YYYYMMDD production date of the dataset
() For dt data as the dates in the file names are rounded the user wanting data for date T has to read the filescontaining dates T+1 and T-1 in their name and check inside the files if there are some data for date T
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VII DATA FORMAT
This chapter presents the data storage format used for MyOcean products
VII1 NetCdf
The products are stored using the NetCDF format NetCDF (network Common Data Form) is an interface for array-oriented data access and a library that provides an implementation of the interface The netCDF library also definesa machine-independent format for representing scientific data Together the interface library and format support thecreation access and sharing of scientific data The netCDF software was developed at the Unidata Program Center inBoulder Colorado The netCDF libraries define a machine-independent format for representing scientific data Pleasesee Unidata NetCDF pages for more information and to retreive NetCDF software package onhttpwwwunidataucaredupackagesnetcdfindexhtml
NetCDF data is
bull Self-Describing A netCDF file includes information about the data it contains
bull Architecture-independent A netCDF file is represented in a form that can be accessed by computers with dif-ferent ways of storing integers characters and floating-point numbers
bull Direct-access A small subset of a large dataset may be accessed efficiently without first reading through allthe preceding data
bull Appendable Data can be appended to a netCDF dataset along one dimension without copying the dataset orredefining its structure The structure of a netCDF dataset can be changed though this sometimes causes thedataset to be copied
bull Sharable One writer and multiple readers may simultaneously access the same netCDF file
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VII2 Structure and semantic of NetCDF along-track files
The NetCDF Sea Level TAC files are based on the attribute data tags defined by the Cooperative OceanAtmosphereResearch Data Service (COARDS) and Climate and Forecast (CF) metadata conventions The CF convention gener-alises and extends the COARDS convention but relaxes the COARDS constraints on dimension and order and specifiesmethods for reducing the size of datasetsA wide range of software are available to write or read NetCDFCF files API are made available by UNIDATA(httpwwwunidataucaredusoftwarenetcdf)
bull CC++Fortran
bull Java
bull MATLAB Objective-C Perl Python R Ruby TclTk
In addition to these conventions the files are using a common structure and semantic
bull 1 dimension is defined
ndash time it is used to check NetCDF variables depending on time
bull 8 variables are defined
ndash short SLA contains the Sea Level Anomaly values for each time given
ndash int longitude contains the longitude for each measurement
ndash short track contains the track number for each measurement
ndash double time contains the time in days since 1950-01-01 000000 UTC for each measurement
ndash short mean_profile_point_index index of the corrsponding point in the track of the mean profile
ndash byte flag flag=0 the processed data comes from OGDR if flag=1 the processed data comes from theIGDR
ndash int latitude contains the latitude for each measurement
ndash short cycle contains the cycle number for each measurement
bull global attributes
ndash the global attributes gives information about the creation of the file
Example of a NetCDF sla file
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netcdf nrt_global_j1_sla_vfec_20101230_20101230_20101230 dimensions
time = 10385 variables
short SLA(time) SLAcoordinates = longitude latitude SLAlong_name = Sea Level Anomaly SLA_FillValue = 32767s SLAadd_offset = 0 SLAscale_factor = 0001 SLAunits = m SLAstandard_name = sea_surface_height_above_sea_level
int longitude(time) longitudelong_name = Longitude of measurement longitude_FillValue = 2147483647 longitudeadd_offset = 0 longitudestandard_name = longitude longitudescale_factor = 1e-06 longitudeunits = degrees_east
short track(time) tracklong_name = Track in cycle the measurement belongs to track_FillValue = 32767s trackunits = 1 trackcoordinates = longitude latitude
double time(time) timelong_name = Time of measurement time_FillValue = 184467440737096e+19 timeaxis = T timestandard_name = time timeunits = days since 1950-01-01 000000 UTC
int latitude(time) latitudelong_name = Latitude of measurement latitude_FillValue = 2147483647 latitudeadd_offset = 0 latitudestandard_name = latitude latitudescale_factor = 1e-06 latitudeunits = degrees_north
short flag(time) flagcoordinates = longitude latitude flag_FillValue = 3267s flaglong_name = data origin flagflag_values = 1s 0s flagflag_meanings = igdr_like non_igdr_like flagcomment = The origin of the data is determined by the types of geophysical datarecords (GDR) used in computation of the SLA 1 for the Interim GDR (IGDR) and0 for Operational GDR (OGDR)
short cycle(time) cyclelong_name = Cycle the measurement belongs to cycle_FillValue = 32767s cycleunits = 1 cyclecoordinates = longitude latitude
global attributeshistory = 22-Feb-2011 155243 CET File created by the SSLATODUACS system version 1001 comment = Produce from ENVISAT Extension Phase satellite altimetry data institution = CLSCNES
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references = httpwwwavisooceanobscomfileadmindocumentsdatatoolshdbk_duacspdf source = satellite altimetry title = along track Sea Level Anomaly Conventions = CF-14
dataSLA =
7 7 11 10 -2 -22 -39 -41 -30 -13 -3 -5 -16 -26 -32 -35-35 -35 -37 -35 -31 -29 -31 -35 -32 -21 -10 -10 -19 -20 -1-69 -57 -49 -45 -39 -30 -28 -31 -27 -13 -2 -5 -15 -3 1112 3 -7 -10 -14 -15 -22 -31 -37 -32 -17 -10
longitude =74743328 74868400 74993968 75120040 75246616 7537372875501368 75629568 75758320 75887656 76017568 76148080 7627920876388952 76477056 76565456 76654144 76743128 76832400 76921984329429568 329535424 329641792 329748672 329856096 329964032330072512 330181536 330291072 330401184
track =92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 9292 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92113 113 113 113 113 113 113 113 113 113 113 113 113 113113 113 113 113 113 113 113 113 113
time =222780000565705 222780001314719 222780002063733222780002812747 222780003561761 222780004310775 222780005059788222780005808802 222780006557816 22278000730683 222780008055844222780008804858 222780009553872 22278001017805 222780010677393222788257112198 222788257486705 222788257861212 222788258235719222788258610226 222788258984733 222788259359239 222788259733746222788260108253 22278826048276
mean_profile_point_index =1872 1878 1884 1890 1896 1902 1908 19141920 1926 1932 1938 1944 1949 1953 1957 1961 1965 1969 19732306 2309 2312 2315 2318 2321 2327 2330 2333 2336 2339 23422345 2348 2351 2354 2357 2360 2363 2366
flag =0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
latitude =-16225506 -16539731 -16853833 -17167810 -17481660 -17795380-18108966 -18422418 -18735729 -19048899 -19361924 -19674801-19987527 -20248015 -20456329 -20664569 -20872739 -2108083739481297 39628277 39775133 39921866 40068472 40214953 4036130840507533 40653629 40799592 40945423 41091120 41236684 41382111
cycle =331 331 331 331 331 331 331 331 331 331 331 331 331
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331 331 331 331 331 331 331 331 331 331 331 331 331 331331 331 331 331 331 331 331 331 331 331 331 331
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VIII HOW TO DOWNLOAD A PRODUCT
VIII1 Download a product through the MyOcean Web Portal DirectgetfileService
You first need to register Please find below the registration stepshttpwwwmyoceaneuweb34-products-and-services-faqphp1Once registered the MyOcean FAQ httpwwwmyoceaneuweb34-products-and-services-faqwill guide you on How to download a product through the MyOcean Web Portal Directgetfile Service
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IX NEWS AND UPDATES
IX1 [Duacs] Operational news
To be kept informed on events occurring on the satellites and on the eventual interruption of the services of the DUACSprocessing system see the [Duacs] operational news on the Aviso websitehttpwwwavisooceanobscomendataoperational-newsindexhtml
IX2 Updates
To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtmlSince 2010 a complete reprocessing of all altimetry data (cumulated total of about 55 years of data) is available Themain changes introduced in the Duacs DT v300 reprocessed data set in SSALTODUACS reprocessed DT data setare listed herehttpwwwavisooceanobscomfileadmindocumentsdataduacsduacs_DT_2010_reprocessing_impactpdf
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Product Specification SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002
Geographical coverage 55˚W-35˚E 30˚N-46˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km for filtered 7km for unfiltered
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_MED_SLA_L3_OBSERVATIONS_008_002 Product Specification
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
Product Specification SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003
Geographical coverage 27˚E-42˚E 40˚N-47˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003 Product Specification
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
Product Specification SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004
Geographical coverage 25˚W-42˚E 21˚N-66˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004 Product Specification
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
Product Specification SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005
Geographical coverage 0˚W-360˚E 50˚N-82˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005 Product Specification
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VI NOMENCLATURE OF FILES
VI1 Nomenclature of files downloaded through the MyOcean Web PortalDirectgetfile Service
VI11 Nomenclature of the product line
The description of the syntax for the SL TAC SLA products line is given by
SEALEVEL_ltREGIONgt_SLA_L3_ltDELAYgt_OBSERVATIONS_008_ltZONEgt_ltLETTERgtwhere
REGION GLO global geographic coverage product
BS Black Sea products
MED Mediterranean products
ARC Arctic products (for NRT products)
EUROPE Europe products (for NRT products)
DELAY NRT near real time products
RAN delayed time or reanalysis products
ZONE 001 number on 3 digits
002
003
004
LETTER a letter on 1 digit
b
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VI12 Nomenclature of the datasets
The nomenclature used is
dataset-duacs-ltdelaygt-ltzonegt-ltmissiongt-lttype of slagt-l3where the fileds in ltgt are described below
delay nrt near-real time productsran delayed time products
zone global global geographic coverage productmedsea Mediterranean productsblacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1 (only for ran)e2 ERS-2 (only for ran)tp TOPEXPoseidon (only for ran)tpn TOPEXPoseidon on its new orbit (only for
ran)g2 GFO (only for ran)j1 Jason-1 (only for ran)j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisat (only for ran)enn Envisat on its new orbitc2 Cryosat-2 (only for nrt)
type of sla sla filtered slasla_unfiltered non filtered sla (only for ran products)
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VI13 Nomenclature of the NetCdf files
The nomenclature used is
ltdelaygt_ltzonegt_ltmissiongt_sla_ltvariablegt_ltdatebegingt_ltdateendgt_ltdateprodgtnc where the fileds in ltgt are de-scribed below
delay nrt near-real time productsdt delayed time products
zone global global geographic coverage productmed Mediterranean products (for dt)mfstep Mediterranean products (for nrt)blacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1e2 ERS-2tp TOPEXPoseidontpn TOPEXPoseidon on its new orbitg2 GFOj1 Jason-1j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisatenn Envisat on its new orbitc2 Cryosat-2
variable vfec filtered and sub-sampled slavxxc non filtered and non sub-sampled sla (only
for dt)datebegin YYYYMMDD() beginning date of the datasetdateend YYYYMMDD() end date of the datasetdateprod YYYYMMDD production date of the dataset
() For dt data as the dates in the file names are rounded the user wanting data for date T has to read the filescontaining dates T+1 and T-1 in their name and check inside the files if there are some data for date T
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VII DATA FORMAT
This chapter presents the data storage format used for MyOcean products
VII1 NetCdf
The products are stored using the NetCDF format NetCDF (network Common Data Form) is an interface for array-oriented data access and a library that provides an implementation of the interface The netCDF library also definesa machine-independent format for representing scientific data Together the interface library and format support thecreation access and sharing of scientific data The netCDF software was developed at the Unidata Program Center inBoulder Colorado The netCDF libraries define a machine-independent format for representing scientific data Pleasesee Unidata NetCDF pages for more information and to retreive NetCDF software package onhttpwwwunidataucaredupackagesnetcdfindexhtml
NetCDF data is
bull Self-Describing A netCDF file includes information about the data it contains
bull Architecture-independent A netCDF file is represented in a form that can be accessed by computers with dif-ferent ways of storing integers characters and floating-point numbers
bull Direct-access A small subset of a large dataset may be accessed efficiently without first reading through allthe preceding data
bull Appendable Data can be appended to a netCDF dataset along one dimension without copying the dataset orredefining its structure The structure of a netCDF dataset can be changed though this sometimes causes thedataset to be copied
bull Sharable One writer and multiple readers may simultaneously access the same netCDF file
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VII2 Structure and semantic of NetCDF along-track files
The NetCDF Sea Level TAC files are based on the attribute data tags defined by the Cooperative OceanAtmosphereResearch Data Service (COARDS) and Climate and Forecast (CF) metadata conventions The CF convention gener-alises and extends the COARDS convention but relaxes the COARDS constraints on dimension and order and specifiesmethods for reducing the size of datasetsA wide range of software are available to write or read NetCDFCF files API are made available by UNIDATA(httpwwwunidataucaredusoftwarenetcdf)
bull CC++Fortran
bull Java
bull MATLAB Objective-C Perl Python R Ruby TclTk
In addition to these conventions the files are using a common structure and semantic
bull 1 dimension is defined
ndash time it is used to check NetCDF variables depending on time
bull 8 variables are defined
ndash short SLA contains the Sea Level Anomaly values for each time given
ndash int longitude contains the longitude for each measurement
ndash short track contains the track number for each measurement
ndash double time contains the time in days since 1950-01-01 000000 UTC for each measurement
ndash short mean_profile_point_index index of the corrsponding point in the track of the mean profile
ndash byte flag flag=0 the processed data comes from OGDR if flag=1 the processed data comes from theIGDR
ndash int latitude contains the latitude for each measurement
ndash short cycle contains the cycle number for each measurement
bull global attributes
ndash the global attributes gives information about the creation of the file
Example of a NetCDF sla file
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netcdf nrt_global_j1_sla_vfec_20101230_20101230_20101230 dimensions
time = 10385 variables
short SLA(time) SLAcoordinates = longitude latitude SLAlong_name = Sea Level Anomaly SLA_FillValue = 32767s SLAadd_offset = 0 SLAscale_factor = 0001 SLAunits = m SLAstandard_name = sea_surface_height_above_sea_level
int longitude(time) longitudelong_name = Longitude of measurement longitude_FillValue = 2147483647 longitudeadd_offset = 0 longitudestandard_name = longitude longitudescale_factor = 1e-06 longitudeunits = degrees_east
short track(time) tracklong_name = Track in cycle the measurement belongs to track_FillValue = 32767s trackunits = 1 trackcoordinates = longitude latitude
double time(time) timelong_name = Time of measurement time_FillValue = 184467440737096e+19 timeaxis = T timestandard_name = time timeunits = days since 1950-01-01 000000 UTC
int latitude(time) latitudelong_name = Latitude of measurement latitude_FillValue = 2147483647 latitudeadd_offset = 0 latitudestandard_name = latitude latitudescale_factor = 1e-06 latitudeunits = degrees_north
short flag(time) flagcoordinates = longitude latitude flag_FillValue = 3267s flaglong_name = data origin flagflag_values = 1s 0s flagflag_meanings = igdr_like non_igdr_like flagcomment = The origin of the data is determined by the types of geophysical datarecords (GDR) used in computation of the SLA 1 for the Interim GDR (IGDR) and0 for Operational GDR (OGDR)
short cycle(time) cyclelong_name = Cycle the measurement belongs to cycle_FillValue = 32767s cycleunits = 1 cyclecoordinates = longitude latitude
global attributeshistory = 22-Feb-2011 155243 CET File created by the SSLATODUACS system version 1001 comment = Produce from ENVISAT Extension Phase satellite altimetry data institution = CLSCNES
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references = httpwwwavisooceanobscomfileadmindocumentsdatatoolshdbk_duacspdf source = satellite altimetry title = along track Sea Level Anomaly Conventions = CF-14
dataSLA =
7 7 11 10 -2 -22 -39 -41 -30 -13 -3 -5 -16 -26 -32 -35-35 -35 -37 -35 -31 -29 -31 -35 -32 -21 -10 -10 -19 -20 -1-69 -57 -49 -45 -39 -30 -28 -31 -27 -13 -2 -5 -15 -3 1112 3 -7 -10 -14 -15 -22 -31 -37 -32 -17 -10
longitude =74743328 74868400 74993968 75120040 75246616 7537372875501368 75629568 75758320 75887656 76017568 76148080 7627920876388952 76477056 76565456 76654144 76743128 76832400 76921984329429568 329535424 329641792 329748672 329856096 329964032330072512 330181536 330291072 330401184
track =92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 9292 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92113 113 113 113 113 113 113 113 113 113 113 113 113 113113 113 113 113 113 113 113 113 113
time =222780000565705 222780001314719 222780002063733222780002812747 222780003561761 222780004310775 222780005059788222780005808802 222780006557816 22278000730683 222780008055844222780008804858 222780009553872 22278001017805 222780010677393222788257112198 222788257486705 222788257861212 222788258235719222788258610226 222788258984733 222788259359239 222788259733746222788260108253 22278826048276
mean_profile_point_index =1872 1878 1884 1890 1896 1902 1908 19141920 1926 1932 1938 1944 1949 1953 1957 1961 1965 1969 19732306 2309 2312 2315 2318 2321 2327 2330 2333 2336 2339 23422345 2348 2351 2354 2357 2360 2363 2366
flag =0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
latitude =-16225506 -16539731 -16853833 -17167810 -17481660 -17795380-18108966 -18422418 -18735729 -19048899 -19361924 -19674801-19987527 -20248015 -20456329 -20664569 -20872739 -2108083739481297 39628277 39775133 39921866 40068472 40214953 4036130840507533 40653629 40799592 40945423 41091120 41236684 41382111
cycle =331 331 331 331 331 331 331 331 331 331 331 331 331
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331 331 331 331 331 331 331 331 331 331 331 331 331 331331 331 331 331 331 331 331 331 331 331 331 331
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VIII HOW TO DOWNLOAD A PRODUCT
VIII1 Download a product through the MyOcean Web Portal DirectgetfileService
You first need to register Please find below the registration stepshttpwwwmyoceaneuweb34-products-and-services-faqphp1Once registered the MyOcean FAQ httpwwwmyoceaneuweb34-products-and-services-faqwill guide you on How to download a product through the MyOcean Web Portal Directgetfile Service
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IX NEWS AND UPDATES
IX1 [Duacs] Operational news
To be kept informed on events occurring on the satellites and on the eventual interruption of the services of the DUACSprocessing system see the [Duacs] operational news on the Aviso websitehttpwwwavisooceanobscomendataoperational-newsindexhtml
IX2 Updates
To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtmlSince 2010 a complete reprocessing of all altimetry data (cumulated total of about 55 years of data) is available Themain changes introduced in the Duacs DT v300 reprocessed data set in SSALTODUACS reprocessed DT data setare listed herehttpwwwavisooceanobscomfileadmindocumentsdataduacsduacs_DT_2010_reprocessing_impactpdf
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
Product Specification SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003
Geographical coverage 27˚E-42˚E 40˚N-47˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT and weekly for RAN
Target delivery time 3-4 months for RAN and daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_BS_SLA_L3_OBSERVATIONS_008_003 Product Specification
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Product Specification SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004
Geographical coverage 25˚W-42˚E 21˚N-66˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004 Product Specification
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Product Specification SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005
Geographical coverage 0˚W-360˚E 50˚N-82˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005 Product Specification
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VI NOMENCLATURE OF FILES
VI1 Nomenclature of files downloaded through the MyOcean Web PortalDirectgetfile Service
VI11 Nomenclature of the product line
The description of the syntax for the SL TAC SLA products line is given by
SEALEVEL_ltREGIONgt_SLA_L3_ltDELAYgt_OBSERVATIONS_008_ltZONEgt_ltLETTERgtwhere
REGION GLO global geographic coverage product
BS Black Sea products
MED Mediterranean products
ARC Arctic products (for NRT products)
EUROPE Europe products (for NRT products)
DELAY NRT near real time products
RAN delayed time or reanalysis products
ZONE 001 number on 3 digits
002
003
004
LETTER a letter on 1 digit
b
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VI12 Nomenclature of the datasets
The nomenclature used is
dataset-duacs-ltdelaygt-ltzonegt-ltmissiongt-lttype of slagt-l3where the fileds in ltgt are described below
delay nrt near-real time productsran delayed time products
zone global global geographic coverage productmedsea Mediterranean productsblacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1 (only for ran)e2 ERS-2 (only for ran)tp TOPEXPoseidon (only for ran)tpn TOPEXPoseidon on its new orbit (only for
ran)g2 GFO (only for ran)j1 Jason-1 (only for ran)j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisat (only for ran)enn Envisat on its new orbitc2 Cryosat-2 (only for nrt)
type of sla sla filtered slasla_unfiltered non filtered sla (only for ran products)
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VI13 Nomenclature of the NetCdf files
The nomenclature used is
ltdelaygt_ltzonegt_ltmissiongt_sla_ltvariablegt_ltdatebegingt_ltdateendgt_ltdateprodgtnc where the fileds in ltgt are de-scribed below
delay nrt near-real time productsdt delayed time products
zone global global geographic coverage productmed Mediterranean products (for dt)mfstep Mediterranean products (for nrt)blacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1e2 ERS-2tp TOPEXPoseidontpn TOPEXPoseidon on its new orbitg2 GFOj1 Jason-1j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisatenn Envisat on its new orbitc2 Cryosat-2
variable vfec filtered and sub-sampled slavxxc non filtered and non sub-sampled sla (only
for dt)datebegin YYYYMMDD() beginning date of the datasetdateend YYYYMMDD() end date of the datasetdateprod YYYYMMDD production date of the dataset
() For dt data as the dates in the file names are rounded the user wanting data for date T has to read the filescontaining dates T+1 and T-1 in their name and check inside the files if there are some data for date T
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VII DATA FORMAT
This chapter presents the data storage format used for MyOcean products
VII1 NetCdf
The products are stored using the NetCDF format NetCDF (network Common Data Form) is an interface for array-oriented data access and a library that provides an implementation of the interface The netCDF library also definesa machine-independent format for representing scientific data Together the interface library and format support thecreation access and sharing of scientific data The netCDF software was developed at the Unidata Program Center inBoulder Colorado The netCDF libraries define a machine-independent format for representing scientific data Pleasesee Unidata NetCDF pages for more information and to retreive NetCDF software package onhttpwwwunidataucaredupackagesnetcdfindexhtml
NetCDF data is
bull Self-Describing A netCDF file includes information about the data it contains
bull Architecture-independent A netCDF file is represented in a form that can be accessed by computers with dif-ferent ways of storing integers characters and floating-point numbers
bull Direct-access A small subset of a large dataset may be accessed efficiently without first reading through allthe preceding data
bull Appendable Data can be appended to a netCDF dataset along one dimension without copying the dataset orredefining its structure The structure of a netCDF dataset can be changed though this sometimes causes thedataset to be copied
bull Sharable One writer and multiple readers may simultaneously access the same netCDF file
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VII2 Structure and semantic of NetCDF along-track files
The NetCDF Sea Level TAC files are based on the attribute data tags defined by the Cooperative OceanAtmosphereResearch Data Service (COARDS) and Climate and Forecast (CF) metadata conventions The CF convention gener-alises and extends the COARDS convention but relaxes the COARDS constraints on dimension and order and specifiesmethods for reducing the size of datasetsA wide range of software are available to write or read NetCDFCF files API are made available by UNIDATA(httpwwwunidataucaredusoftwarenetcdf)
bull CC++Fortran
bull Java
bull MATLAB Objective-C Perl Python R Ruby TclTk
In addition to these conventions the files are using a common structure and semantic
bull 1 dimension is defined
ndash time it is used to check NetCDF variables depending on time
bull 8 variables are defined
ndash short SLA contains the Sea Level Anomaly values for each time given
ndash int longitude contains the longitude for each measurement
ndash short track contains the track number for each measurement
ndash double time contains the time in days since 1950-01-01 000000 UTC for each measurement
ndash short mean_profile_point_index index of the corrsponding point in the track of the mean profile
ndash byte flag flag=0 the processed data comes from OGDR if flag=1 the processed data comes from theIGDR
ndash int latitude contains the latitude for each measurement
ndash short cycle contains the cycle number for each measurement
bull global attributes
ndash the global attributes gives information about the creation of the file
Example of a NetCDF sla file
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netcdf nrt_global_j1_sla_vfec_20101230_20101230_20101230 dimensions
time = 10385 variables
short SLA(time) SLAcoordinates = longitude latitude SLAlong_name = Sea Level Anomaly SLA_FillValue = 32767s SLAadd_offset = 0 SLAscale_factor = 0001 SLAunits = m SLAstandard_name = sea_surface_height_above_sea_level
int longitude(time) longitudelong_name = Longitude of measurement longitude_FillValue = 2147483647 longitudeadd_offset = 0 longitudestandard_name = longitude longitudescale_factor = 1e-06 longitudeunits = degrees_east
short track(time) tracklong_name = Track in cycle the measurement belongs to track_FillValue = 32767s trackunits = 1 trackcoordinates = longitude latitude
double time(time) timelong_name = Time of measurement time_FillValue = 184467440737096e+19 timeaxis = T timestandard_name = time timeunits = days since 1950-01-01 000000 UTC
int latitude(time) latitudelong_name = Latitude of measurement latitude_FillValue = 2147483647 latitudeadd_offset = 0 latitudestandard_name = latitude latitudescale_factor = 1e-06 latitudeunits = degrees_north
short flag(time) flagcoordinates = longitude latitude flag_FillValue = 3267s flaglong_name = data origin flagflag_values = 1s 0s flagflag_meanings = igdr_like non_igdr_like flagcomment = The origin of the data is determined by the types of geophysical datarecords (GDR) used in computation of the SLA 1 for the Interim GDR (IGDR) and0 for Operational GDR (OGDR)
short cycle(time) cyclelong_name = Cycle the measurement belongs to cycle_FillValue = 32767s cycleunits = 1 cyclecoordinates = longitude latitude
global attributeshistory = 22-Feb-2011 155243 CET File created by the SSLATODUACS system version 1001 comment = Produce from ENVISAT Extension Phase satellite altimetry data institution = CLSCNES
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references = httpwwwavisooceanobscomfileadmindocumentsdatatoolshdbk_duacspdf source = satellite altimetry title = along track Sea Level Anomaly Conventions = CF-14
dataSLA =
7 7 11 10 -2 -22 -39 -41 -30 -13 -3 -5 -16 -26 -32 -35-35 -35 -37 -35 -31 -29 -31 -35 -32 -21 -10 -10 -19 -20 -1-69 -57 -49 -45 -39 -30 -28 -31 -27 -13 -2 -5 -15 -3 1112 3 -7 -10 -14 -15 -22 -31 -37 -32 -17 -10
longitude =74743328 74868400 74993968 75120040 75246616 7537372875501368 75629568 75758320 75887656 76017568 76148080 7627920876388952 76477056 76565456 76654144 76743128 76832400 76921984329429568 329535424 329641792 329748672 329856096 329964032330072512 330181536 330291072 330401184
track =92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 9292 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92113 113 113 113 113 113 113 113 113 113 113 113 113 113113 113 113 113 113 113 113 113 113
time =222780000565705 222780001314719 222780002063733222780002812747 222780003561761 222780004310775 222780005059788222780005808802 222780006557816 22278000730683 222780008055844222780008804858 222780009553872 22278001017805 222780010677393222788257112198 222788257486705 222788257861212 222788258235719222788258610226 222788258984733 222788259359239 222788259733746222788260108253 22278826048276
mean_profile_point_index =1872 1878 1884 1890 1896 1902 1908 19141920 1926 1932 1938 1944 1949 1953 1957 1961 1965 1969 19732306 2309 2312 2315 2318 2321 2327 2330 2333 2336 2339 23422345 2348 2351 2354 2357 2360 2363 2366
flag =0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
latitude =-16225506 -16539731 -16853833 -17167810 -17481660 -17795380-18108966 -18422418 -18735729 -19048899 -19361924 -19674801-19987527 -20248015 -20456329 -20664569 -20872739 -2108083739481297 39628277 39775133 39921866 40068472 40214953 4036130840507533 40653629 40799592 40945423 41091120 41236684 41382111
cycle =331 331 331 331 331 331 331 331 331 331 331 331 331
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331 331 331 331 331 331 331 331 331 331 331 331 331 331331 331 331 331 331 331 331 331 331 331 331 331
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
VIII HOW TO DOWNLOAD A PRODUCT
VIII1 Download a product through the MyOcean Web Portal DirectgetfileService
You first need to register Please find below the registration stepshttpwwwmyoceaneuweb34-products-and-services-faqphp1Once registered the MyOcean FAQ httpwwwmyoceaneuweb34-products-and-services-faqwill guide you on How to download a product through the MyOcean Web Portal Directgetfile Service
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PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
IX NEWS AND UPDATES
IX1 [Duacs] Operational news
To be kept informed on events occurring on the satellites and on the eventual interruption of the services of the DUACSprocessing system see the [Duacs] operational news on the Aviso websitehttpwwwavisooceanobscomendataoperational-newsindexhtml
IX2 Updates
To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtmlSince 2010 a complete reprocessing of all altimetry data (cumulated total of about 55 years of data) is available Themain changes introduced in the Duacs DT v300 reprocessed data set in SSALTODUACS reprocessed DT data setare listed herehttpwwwavisooceanobscomfileadmindocumentsdataduacsduacs_DT_2010_reprocessing_impactpdf
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
Product Specification SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004
Geographical coverage 25˚W-42˚E 21˚N-66˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 7km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_EUR_SLA_L3_OBSERVATIONS_008_004 Product Specification
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
Product Specification SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005
Geographical coverage 0˚W-360˚E 50˚N-82˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005 Product Specification
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VI NOMENCLATURE OF FILES
VI1 Nomenclature of files downloaded through the MyOcean Web PortalDirectgetfile Service
VI11 Nomenclature of the product line
The description of the syntax for the SL TAC SLA products line is given by
SEALEVEL_ltREGIONgt_SLA_L3_ltDELAYgt_OBSERVATIONS_008_ltZONEgt_ltLETTERgtwhere
REGION GLO global geographic coverage product
BS Black Sea products
MED Mediterranean products
ARC Arctic products (for NRT products)
EUROPE Europe products (for NRT products)
DELAY NRT near real time products
RAN delayed time or reanalysis products
ZONE 001 number on 3 digits
002
003
004
LETTER a letter on 1 digit
b
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VI12 Nomenclature of the datasets
The nomenclature used is
dataset-duacs-ltdelaygt-ltzonegt-ltmissiongt-lttype of slagt-l3where the fileds in ltgt are described below
delay nrt near-real time productsran delayed time products
zone global global geographic coverage productmedsea Mediterranean productsblacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1 (only for ran)e2 ERS-2 (only for ran)tp TOPEXPoseidon (only for ran)tpn TOPEXPoseidon on its new orbit (only for
ran)g2 GFO (only for ran)j1 Jason-1 (only for ran)j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisat (only for ran)enn Envisat on its new orbitc2 Cryosat-2 (only for nrt)
type of sla sla filtered slasla_unfiltered non filtered sla (only for ran products)
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
VI13 Nomenclature of the NetCdf files
The nomenclature used is
ltdelaygt_ltzonegt_ltmissiongt_sla_ltvariablegt_ltdatebegingt_ltdateendgt_ltdateprodgtnc where the fileds in ltgt are de-scribed below
delay nrt near-real time productsdt delayed time products
zone global global geographic coverage productmed Mediterranean products (for dt)mfstep Mediterranean products (for nrt)blacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1e2 ERS-2tp TOPEXPoseidontpn TOPEXPoseidon on its new orbitg2 GFOj1 Jason-1j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisatenn Envisat on its new orbitc2 Cryosat-2
variable vfec filtered and sub-sampled slavxxc non filtered and non sub-sampled sla (only
for dt)datebegin YYYYMMDD() beginning date of the datasetdateend YYYYMMDD() end date of the datasetdateprod YYYYMMDD production date of the dataset
() For dt data as the dates in the file names are rounded the user wanting data for date T has to read the filescontaining dates T+1 and T-1 in their name and check inside the files if there are some data for date T
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
VII DATA FORMAT
This chapter presents the data storage format used for MyOcean products
VII1 NetCdf
The products are stored using the NetCDF format NetCDF (network Common Data Form) is an interface for array-oriented data access and a library that provides an implementation of the interface The netCDF library also definesa machine-independent format for representing scientific data Together the interface library and format support thecreation access and sharing of scientific data The netCDF software was developed at the Unidata Program Center inBoulder Colorado The netCDF libraries define a machine-independent format for representing scientific data Pleasesee Unidata NetCDF pages for more information and to retreive NetCDF software package onhttpwwwunidataucaredupackagesnetcdfindexhtml
NetCDF data is
bull Self-Describing A netCDF file includes information about the data it contains
bull Architecture-independent A netCDF file is represented in a form that can be accessed by computers with dif-ferent ways of storing integers characters and floating-point numbers
bull Direct-access A small subset of a large dataset may be accessed efficiently without first reading through allthe preceding data
bull Appendable Data can be appended to a netCDF dataset along one dimension without copying the dataset orredefining its structure The structure of a netCDF dataset can be changed though this sometimes causes thedataset to be copied
bull Sharable One writer and multiple readers may simultaneously access the same netCDF file
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VII2 Structure and semantic of NetCDF along-track files
The NetCDF Sea Level TAC files are based on the attribute data tags defined by the Cooperative OceanAtmosphereResearch Data Service (COARDS) and Climate and Forecast (CF) metadata conventions The CF convention gener-alises and extends the COARDS convention but relaxes the COARDS constraints on dimension and order and specifiesmethods for reducing the size of datasetsA wide range of software are available to write or read NetCDFCF files API are made available by UNIDATA(httpwwwunidataucaredusoftwarenetcdf)
bull CC++Fortran
bull Java
bull MATLAB Objective-C Perl Python R Ruby TclTk
In addition to these conventions the files are using a common structure and semantic
bull 1 dimension is defined
ndash time it is used to check NetCDF variables depending on time
bull 8 variables are defined
ndash short SLA contains the Sea Level Anomaly values for each time given
ndash int longitude contains the longitude for each measurement
ndash short track contains the track number for each measurement
ndash double time contains the time in days since 1950-01-01 000000 UTC for each measurement
ndash short mean_profile_point_index index of the corrsponding point in the track of the mean profile
ndash byte flag flag=0 the processed data comes from OGDR if flag=1 the processed data comes from theIGDR
ndash int latitude contains the latitude for each measurement
ndash short cycle contains the cycle number for each measurement
bull global attributes
ndash the global attributes gives information about the creation of the file
Example of a NetCDF sla file
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netcdf nrt_global_j1_sla_vfec_20101230_20101230_20101230 dimensions
time = 10385 variables
short SLA(time) SLAcoordinates = longitude latitude SLAlong_name = Sea Level Anomaly SLA_FillValue = 32767s SLAadd_offset = 0 SLAscale_factor = 0001 SLAunits = m SLAstandard_name = sea_surface_height_above_sea_level
int longitude(time) longitudelong_name = Longitude of measurement longitude_FillValue = 2147483647 longitudeadd_offset = 0 longitudestandard_name = longitude longitudescale_factor = 1e-06 longitudeunits = degrees_east
short track(time) tracklong_name = Track in cycle the measurement belongs to track_FillValue = 32767s trackunits = 1 trackcoordinates = longitude latitude
double time(time) timelong_name = Time of measurement time_FillValue = 184467440737096e+19 timeaxis = T timestandard_name = time timeunits = days since 1950-01-01 000000 UTC
int latitude(time) latitudelong_name = Latitude of measurement latitude_FillValue = 2147483647 latitudeadd_offset = 0 latitudestandard_name = latitude latitudescale_factor = 1e-06 latitudeunits = degrees_north
short flag(time) flagcoordinates = longitude latitude flag_FillValue = 3267s flaglong_name = data origin flagflag_values = 1s 0s flagflag_meanings = igdr_like non_igdr_like flagcomment = The origin of the data is determined by the types of geophysical datarecords (GDR) used in computation of the SLA 1 for the Interim GDR (IGDR) and0 for Operational GDR (OGDR)
short cycle(time) cyclelong_name = Cycle the measurement belongs to cycle_FillValue = 32767s cycleunits = 1 cyclecoordinates = longitude latitude
global attributeshistory = 22-Feb-2011 155243 CET File created by the SSLATODUACS system version 1001 comment = Produce from ENVISAT Extension Phase satellite altimetry data institution = CLSCNES
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references = httpwwwavisooceanobscomfileadmindocumentsdatatoolshdbk_duacspdf source = satellite altimetry title = along track Sea Level Anomaly Conventions = CF-14
dataSLA =
7 7 11 10 -2 -22 -39 -41 -30 -13 -3 -5 -16 -26 -32 -35-35 -35 -37 -35 -31 -29 -31 -35 -32 -21 -10 -10 -19 -20 -1-69 -57 -49 -45 -39 -30 -28 -31 -27 -13 -2 -5 -15 -3 1112 3 -7 -10 -14 -15 -22 -31 -37 -32 -17 -10
longitude =74743328 74868400 74993968 75120040 75246616 7537372875501368 75629568 75758320 75887656 76017568 76148080 7627920876388952 76477056 76565456 76654144 76743128 76832400 76921984329429568 329535424 329641792 329748672 329856096 329964032330072512 330181536 330291072 330401184
track =92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 9292 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92113 113 113 113 113 113 113 113 113 113 113 113 113 113113 113 113 113 113 113 113 113 113
time =222780000565705 222780001314719 222780002063733222780002812747 222780003561761 222780004310775 222780005059788222780005808802 222780006557816 22278000730683 222780008055844222780008804858 222780009553872 22278001017805 222780010677393222788257112198 222788257486705 222788257861212 222788258235719222788258610226 222788258984733 222788259359239 222788259733746222788260108253 22278826048276
mean_profile_point_index =1872 1878 1884 1890 1896 1902 1908 19141920 1926 1932 1938 1944 1949 1953 1957 1961 1965 1969 19732306 2309 2312 2315 2318 2321 2327 2330 2333 2336 2339 23422345 2348 2351 2354 2357 2360 2363 2366
flag =0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
latitude =-16225506 -16539731 -16853833 -17167810 -17481660 -17795380-18108966 -18422418 -18735729 -19048899 -19361924 -19674801-19987527 -20248015 -20456329 -20664569 -20872739 -2108083739481297 39628277 39775133 39921866 40068472 40214953 4036130840507533 40653629 40799592 40945423 41091120 41236684 41382111
cycle =331 331 331 331 331 331 331 331 331 331 331 331 331
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
331 331 331 331 331 331 331 331 331 331 331 331 331 331331 331 331 331 331 331 331 331 331 331 331 331
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
VIII HOW TO DOWNLOAD A PRODUCT
VIII1 Download a product through the MyOcean Web Portal DirectgetfileService
You first need to register Please find below the registration stepshttpwwwmyoceaneuweb34-products-and-services-faqphp1Once registered the MyOcean FAQ httpwwwmyoceaneuweb34-products-and-services-faqwill guide you on How to download a product through the MyOcean Web Portal Directgetfile Service
Page 55
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
IX NEWS AND UPDATES
IX1 [Duacs] Operational news
To be kept informed on events occurring on the satellites and on the eventual interruption of the services of the DUACSprocessing system see the [Duacs] operational news on the Aviso websitehttpwwwavisooceanobscomendataoperational-newsindexhtml
IX2 Updates
To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtmlSince 2010 a complete reprocessing of all altimetry data (cumulated total of about 55 years of data) is available Themain changes introduced in the Duacs DT v300 reprocessed data set in SSALTODUACS reprocessed DT data setare listed herehttpwwwavisooceanobscomfileadmindocumentsdataduacsduacs_DT_2010_reprocessing_impactpdf
Page 56
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
Product Specification SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005
Geographical coverage 0˚W-360˚E 50˚N-82˚N
Variables latitude
longitude
SLA
track
time
mean_profile_point_index
flag
cycle
Near Real time Yes
Reanalysis Yes
Available time series see sections IV22 for RAN and IV12 for NRT
Temporal resolution Daily for NRT
Target delivery time daily for NRT
Delivery mechanism MyOcean Information System
Horizontal resolution 14km
Number of vertical levels 1
Format Netcdf CF10
SEALEVEL_ARC_SLA_L3_OBSERVATIONS_008_005 Product Specification
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PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
VI NOMENCLATURE OF FILES
VI1 Nomenclature of files downloaded through the MyOcean Web PortalDirectgetfile Service
VI11 Nomenclature of the product line
The description of the syntax for the SL TAC SLA products line is given by
SEALEVEL_ltREGIONgt_SLA_L3_ltDELAYgt_OBSERVATIONS_008_ltZONEgt_ltLETTERgtwhere
REGION GLO global geographic coverage product
BS Black Sea products
MED Mediterranean products
ARC Arctic products (for NRT products)
EUROPE Europe products (for NRT products)
DELAY NRT near real time products
RAN delayed time or reanalysis products
ZONE 001 number on 3 digits
002
003
004
LETTER a letter on 1 digit
b
Page 47
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
VI12 Nomenclature of the datasets
The nomenclature used is
dataset-duacs-ltdelaygt-ltzonegt-ltmissiongt-lttype of slagt-l3where the fileds in ltgt are described below
delay nrt near-real time productsran delayed time products
zone global global geographic coverage productmedsea Mediterranean productsblacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1 (only for ran)e2 ERS-2 (only for ran)tp TOPEXPoseidon (only for ran)tpn TOPEXPoseidon on its new orbit (only for
ran)g2 GFO (only for ran)j1 Jason-1 (only for ran)j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisat (only for ran)enn Envisat on its new orbitc2 Cryosat-2 (only for nrt)
type of sla sla filtered slasla_unfiltered non filtered sla (only for ran products)
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VI13 Nomenclature of the NetCdf files
The nomenclature used is
ltdelaygt_ltzonegt_ltmissiongt_sla_ltvariablegt_ltdatebegingt_ltdateendgt_ltdateprodgtnc where the fileds in ltgt are de-scribed below
delay nrt near-real time productsdt delayed time products
zone global global geographic coverage productmed Mediterranean products (for dt)mfstep Mediterranean products (for nrt)blacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1e2 ERS-2tp TOPEXPoseidontpn TOPEXPoseidon on its new orbitg2 GFOj1 Jason-1j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisatenn Envisat on its new orbitc2 Cryosat-2
variable vfec filtered and sub-sampled slavxxc non filtered and non sub-sampled sla (only
for dt)datebegin YYYYMMDD() beginning date of the datasetdateend YYYYMMDD() end date of the datasetdateprod YYYYMMDD production date of the dataset
() For dt data as the dates in the file names are rounded the user wanting data for date T has to read the filescontaining dates T+1 and T-1 in their name and check inside the files if there are some data for date T
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VII DATA FORMAT
This chapter presents the data storage format used for MyOcean products
VII1 NetCdf
The products are stored using the NetCDF format NetCDF (network Common Data Form) is an interface for array-oriented data access and a library that provides an implementation of the interface The netCDF library also definesa machine-independent format for representing scientific data Together the interface library and format support thecreation access and sharing of scientific data The netCDF software was developed at the Unidata Program Center inBoulder Colorado The netCDF libraries define a machine-independent format for representing scientific data Pleasesee Unidata NetCDF pages for more information and to retreive NetCDF software package onhttpwwwunidataucaredupackagesnetcdfindexhtml
NetCDF data is
bull Self-Describing A netCDF file includes information about the data it contains
bull Architecture-independent A netCDF file is represented in a form that can be accessed by computers with dif-ferent ways of storing integers characters and floating-point numbers
bull Direct-access A small subset of a large dataset may be accessed efficiently without first reading through allthe preceding data
bull Appendable Data can be appended to a netCDF dataset along one dimension without copying the dataset orredefining its structure The structure of a netCDF dataset can be changed though this sometimes causes thedataset to be copied
bull Sharable One writer and multiple readers may simultaneously access the same netCDF file
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VII2 Structure and semantic of NetCDF along-track files
The NetCDF Sea Level TAC files are based on the attribute data tags defined by the Cooperative OceanAtmosphereResearch Data Service (COARDS) and Climate and Forecast (CF) metadata conventions The CF convention gener-alises and extends the COARDS convention but relaxes the COARDS constraints on dimension and order and specifiesmethods for reducing the size of datasetsA wide range of software are available to write or read NetCDFCF files API are made available by UNIDATA(httpwwwunidataucaredusoftwarenetcdf)
bull CC++Fortran
bull Java
bull MATLAB Objective-C Perl Python R Ruby TclTk
In addition to these conventions the files are using a common structure and semantic
bull 1 dimension is defined
ndash time it is used to check NetCDF variables depending on time
bull 8 variables are defined
ndash short SLA contains the Sea Level Anomaly values for each time given
ndash int longitude contains the longitude for each measurement
ndash short track contains the track number for each measurement
ndash double time contains the time in days since 1950-01-01 000000 UTC for each measurement
ndash short mean_profile_point_index index of the corrsponding point in the track of the mean profile
ndash byte flag flag=0 the processed data comes from OGDR if flag=1 the processed data comes from theIGDR
ndash int latitude contains the latitude for each measurement
ndash short cycle contains the cycle number for each measurement
bull global attributes
ndash the global attributes gives information about the creation of the file
Example of a NetCDF sla file
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netcdf nrt_global_j1_sla_vfec_20101230_20101230_20101230 dimensions
time = 10385 variables
short SLA(time) SLAcoordinates = longitude latitude SLAlong_name = Sea Level Anomaly SLA_FillValue = 32767s SLAadd_offset = 0 SLAscale_factor = 0001 SLAunits = m SLAstandard_name = sea_surface_height_above_sea_level
int longitude(time) longitudelong_name = Longitude of measurement longitude_FillValue = 2147483647 longitudeadd_offset = 0 longitudestandard_name = longitude longitudescale_factor = 1e-06 longitudeunits = degrees_east
short track(time) tracklong_name = Track in cycle the measurement belongs to track_FillValue = 32767s trackunits = 1 trackcoordinates = longitude latitude
double time(time) timelong_name = Time of measurement time_FillValue = 184467440737096e+19 timeaxis = T timestandard_name = time timeunits = days since 1950-01-01 000000 UTC
int latitude(time) latitudelong_name = Latitude of measurement latitude_FillValue = 2147483647 latitudeadd_offset = 0 latitudestandard_name = latitude latitudescale_factor = 1e-06 latitudeunits = degrees_north
short flag(time) flagcoordinates = longitude latitude flag_FillValue = 3267s flaglong_name = data origin flagflag_values = 1s 0s flagflag_meanings = igdr_like non_igdr_like flagcomment = The origin of the data is determined by the types of geophysical datarecords (GDR) used in computation of the SLA 1 for the Interim GDR (IGDR) and0 for Operational GDR (OGDR)
short cycle(time) cyclelong_name = Cycle the measurement belongs to cycle_FillValue = 32767s cycleunits = 1 cyclecoordinates = longitude latitude
global attributeshistory = 22-Feb-2011 155243 CET File created by the SSLATODUACS system version 1001 comment = Produce from ENVISAT Extension Phase satellite altimetry data institution = CLSCNES
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references = httpwwwavisooceanobscomfileadmindocumentsdatatoolshdbk_duacspdf source = satellite altimetry title = along track Sea Level Anomaly Conventions = CF-14
dataSLA =
7 7 11 10 -2 -22 -39 -41 -30 -13 -3 -5 -16 -26 -32 -35-35 -35 -37 -35 -31 -29 -31 -35 -32 -21 -10 -10 -19 -20 -1-69 -57 -49 -45 -39 -30 -28 -31 -27 -13 -2 -5 -15 -3 1112 3 -7 -10 -14 -15 -22 -31 -37 -32 -17 -10
longitude =74743328 74868400 74993968 75120040 75246616 7537372875501368 75629568 75758320 75887656 76017568 76148080 7627920876388952 76477056 76565456 76654144 76743128 76832400 76921984329429568 329535424 329641792 329748672 329856096 329964032330072512 330181536 330291072 330401184
track =92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 9292 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92113 113 113 113 113 113 113 113 113 113 113 113 113 113113 113 113 113 113 113 113 113 113
time =222780000565705 222780001314719 222780002063733222780002812747 222780003561761 222780004310775 222780005059788222780005808802 222780006557816 22278000730683 222780008055844222780008804858 222780009553872 22278001017805 222780010677393222788257112198 222788257486705 222788257861212 222788258235719222788258610226 222788258984733 222788259359239 222788259733746222788260108253 22278826048276
mean_profile_point_index =1872 1878 1884 1890 1896 1902 1908 19141920 1926 1932 1938 1944 1949 1953 1957 1961 1965 1969 19732306 2309 2312 2315 2318 2321 2327 2330 2333 2336 2339 23422345 2348 2351 2354 2357 2360 2363 2366
flag =0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
latitude =-16225506 -16539731 -16853833 -17167810 -17481660 -17795380-18108966 -18422418 -18735729 -19048899 -19361924 -19674801-19987527 -20248015 -20456329 -20664569 -20872739 -2108083739481297 39628277 39775133 39921866 40068472 40214953 4036130840507533 40653629 40799592 40945423 41091120 41236684 41382111
cycle =331 331 331 331 331 331 331 331 331 331 331 331 331
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331 331 331 331 331 331 331 331 331 331 331 331 331 331331 331 331 331 331 331 331 331 331 331 331 331
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VIII HOW TO DOWNLOAD A PRODUCT
VIII1 Download a product through the MyOcean Web Portal DirectgetfileService
You first need to register Please find below the registration stepshttpwwwmyoceaneuweb34-products-and-services-faqphp1Once registered the MyOcean FAQ httpwwwmyoceaneuweb34-products-and-services-faqwill guide you on How to download a product through the MyOcean Web Portal Directgetfile Service
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IX NEWS AND UPDATES
IX1 [Duacs] Operational news
To be kept informed on events occurring on the satellites and on the eventual interruption of the services of the DUACSprocessing system see the [Duacs] operational news on the Aviso websitehttpwwwavisooceanobscomendataoperational-newsindexhtml
IX2 Updates
To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtmlSince 2010 a complete reprocessing of all altimetry data (cumulated total of about 55 years of data) is available Themain changes introduced in the Duacs DT v300 reprocessed data set in SSALTODUACS reprocessed DT data setare listed herehttpwwwavisooceanobscomfileadmindocumentsdataduacsduacs_DT_2010_reprocessing_impactpdf
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VI NOMENCLATURE OF FILES
VI1 Nomenclature of files downloaded through the MyOcean Web PortalDirectgetfile Service
VI11 Nomenclature of the product line
The description of the syntax for the SL TAC SLA products line is given by
SEALEVEL_ltREGIONgt_SLA_L3_ltDELAYgt_OBSERVATIONS_008_ltZONEgt_ltLETTERgtwhere
REGION GLO global geographic coverage product
BS Black Sea products
MED Mediterranean products
ARC Arctic products (for NRT products)
EUROPE Europe products (for NRT products)
DELAY NRT near real time products
RAN delayed time or reanalysis products
ZONE 001 number on 3 digits
002
003
004
LETTER a letter on 1 digit
b
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VI12 Nomenclature of the datasets
The nomenclature used is
dataset-duacs-ltdelaygt-ltzonegt-ltmissiongt-lttype of slagt-l3where the fileds in ltgt are described below
delay nrt near-real time productsran delayed time products
zone global global geographic coverage productmedsea Mediterranean productsblacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1 (only for ran)e2 ERS-2 (only for ran)tp TOPEXPoseidon (only for ran)tpn TOPEXPoseidon on its new orbit (only for
ran)g2 GFO (only for ran)j1 Jason-1 (only for ran)j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisat (only for ran)enn Envisat on its new orbitc2 Cryosat-2 (only for nrt)
type of sla sla filtered slasla_unfiltered non filtered sla (only for ran products)
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VI13 Nomenclature of the NetCdf files
The nomenclature used is
ltdelaygt_ltzonegt_ltmissiongt_sla_ltvariablegt_ltdatebegingt_ltdateendgt_ltdateprodgtnc where the fileds in ltgt are de-scribed below
delay nrt near-real time productsdt delayed time products
zone global global geographic coverage productmed Mediterranean products (for dt)mfstep Mediterranean products (for nrt)blacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1e2 ERS-2tp TOPEXPoseidontpn TOPEXPoseidon on its new orbitg2 GFOj1 Jason-1j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisatenn Envisat on its new orbitc2 Cryosat-2
variable vfec filtered and sub-sampled slavxxc non filtered and non sub-sampled sla (only
for dt)datebegin YYYYMMDD() beginning date of the datasetdateend YYYYMMDD() end date of the datasetdateprod YYYYMMDD production date of the dataset
() For dt data as the dates in the file names are rounded the user wanting data for date T has to read the filescontaining dates T+1 and T-1 in their name and check inside the files if there are some data for date T
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VII DATA FORMAT
This chapter presents the data storage format used for MyOcean products
VII1 NetCdf
The products are stored using the NetCDF format NetCDF (network Common Data Form) is an interface for array-oriented data access and a library that provides an implementation of the interface The netCDF library also definesa machine-independent format for representing scientific data Together the interface library and format support thecreation access and sharing of scientific data The netCDF software was developed at the Unidata Program Center inBoulder Colorado The netCDF libraries define a machine-independent format for representing scientific data Pleasesee Unidata NetCDF pages for more information and to retreive NetCDF software package onhttpwwwunidataucaredupackagesnetcdfindexhtml
NetCDF data is
bull Self-Describing A netCDF file includes information about the data it contains
bull Architecture-independent A netCDF file is represented in a form that can be accessed by computers with dif-ferent ways of storing integers characters and floating-point numbers
bull Direct-access A small subset of a large dataset may be accessed efficiently without first reading through allthe preceding data
bull Appendable Data can be appended to a netCDF dataset along one dimension without copying the dataset orredefining its structure The structure of a netCDF dataset can be changed though this sometimes causes thedataset to be copied
bull Sharable One writer and multiple readers may simultaneously access the same netCDF file
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VII2 Structure and semantic of NetCDF along-track files
The NetCDF Sea Level TAC files are based on the attribute data tags defined by the Cooperative OceanAtmosphereResearch Data Service (COARDS) and Climate and Forecast (CF) metadata conventions The CF convention gener-alises and extends the COARDS convention but relaxes the COARDS constraints on dimension and order and specifiesmethods for reducing the size of datasetsA wide range of software are available to write or read NetCDFCF files API are made available by UNIDATA(httpwwwunidataucaredusoftwarenetcdf)
bull CC++Fortran
bull Java
bull MATLAB Objective-C Perl Python R Ruby TclTk
In addition to these conventions the files are using a common structure and semantic
bull 1 dimension is defined
ndash time it is used to check NetCDF variables depending on time
bull 8 variables are defined
ndash short SLA contains the Sea Level Anomaly values for each time given
ndash int longitude contains the longitude for each measurement
ndash short track contains the track number for each measurement
ndash double time contains the time in days since 1950-01-01 000000 UTC for each measurement
ndash short mean_profile_point_index index of the corrsponding point in the track of the mean profile
ndash byte flag flag=0 the processed data comes from OGDR if flag=1 the processed data comes from theIGDR
ndash int latitude contains the latitude for each measurement
ndash short cycle contains the cycle number for each measurement
bull global attributes
ndash the global attributes gives information about the creation of the file
Example of a NetCDF sla file
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netcdf nrt_global_j1_sla_vfec_20101230_20101230_20101230 dimensions
time = 10385 variables
short SLA(time) SLAcoordinates = longitude latitude SLAlong_name = Sea Level Anomaly SLA_FillValue = 32767s SLAadd_offset = 0 SLAscale_factor = 0001 SLAunits = m SLAstandard_name = sea_surface_height_above_sea_level
int longitude(time) longitudelong_name = Longitude of measurement longitude_FillValue = 2147483647 longitudeadd_offset = 0 longitudestandard_name = longitude longitudescale_factor = 1e-06 longitudeunits = degrees_east
short track(time) tracklong_name = Track in cycle the measurement belongs to track_FillValue = 32767s trackunits = 1 trackcoordinates = longitude latitude
double time(time) timelong_name = Time of measurement time_FillValue = 184467440737096e+19 timeaxis = T timestandard_name = time timeunits = days since 1950-01-01 000000 UTC
int latitude(time) latitudelong_name = Latitude of measurement latitude_FillValue = 2147483647 latitudeadd_offset = 0 latitudestandard_name = latitude latitudescale_factor = 1e-06 latitudeunits = degrees_north
short flag(time) flagcoordinates = longitude latitude flag_FillValue = 3267s flaglong_name = data origin flagflag_values = 1s 0s flagflag_meanings = igdr_like non_igdr_like flagcomment = The origin of the data is determined by the types of geophysical datarecords (GDR) used in computation of the SLA 1 for the Interim GDR (IGDR) and0 for Operational GDR (OGDR)
short cycle(time) cyclelong_name = Cycle the measurement belongs to cycle_FillValue = 32767s cycleunits = 1 cyclecoordinates = longitude latitude
global attributeshistory = 22-Feb-2011 155243 CET File created by the SSLATODUACS system version 1001 comment = Produce from ENVISAT Extension Phase satellite altimetry data institution = CLSCNES
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references = httpwwwavisooceanobscomfileadmindocumentsdatatoolshdbk_duacspdf source = satellite altimetry title = along track Sea Level Anomaly Conventions = CF-14
dataSLA =
7 7 11 10 -2 -22 -39 -41 -30 -13 -3 -5 -16 -26 -32 -35-35 -35 -37 -35 -31 -29 -31 -35 -32 -21 -10 -10 -19 -20 -1-69 -57 -49 -45 -39 -30 -28 -31 -27 -13 -2 -5 -15 -3 1112 3 -7 -10 -14 -15 -22 -31 -37 -32 -17 -10
longitude =74743328 74868400 74993968 75120040 75246616 7537372875501368 75629568 75758320 75887656 76017568 76148080 7627920876388952 76477056 76565456 76654144 76743128 76832400 76921984329429568 329535424 329641792 329748672 329856096 329964032330072512 330181536 330291072 330401184
track =92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 9292 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92113 113 113 113 113 113 113 113 113 113 113 113 113 113113 113 113 113 113 113 113 113 113
time =222780000565705 222780001314719 222780002063733222780002812747 222780003561761 222780004310775 222780005059788222780005808802 222780006557816 22278000730683 222780008055844222780008804858 222780009553872 22278001017805 222780010677393222788257112198 222788257486705 222788257861212 222788258235719222788258610226 222788258984733 222788259359239 222788259733746222788260108253 22278826048276
mean_profile_point_index =1872 1878 1884 1890 1896 1902 1908 19141920 1926 1932 1938 1944 1949 1953 1957 1961 1965 1969 19732306 2309 2312 2315 2318 2321 2327 2330 2333 2336 2339 23422345 2348 2351 2354 2357 2360 2363 2366
flag =0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
latitude =-16225506 -16539731 -16853833 -17167810 -17481660 -17795380-18108966 -18422418 -18735729 -19048899 -19361924 -19674801-19987527 -20248015 -20456329 -20664569 -20872739 -2108083739481297 39628277 39775133 39921866 40068472 40214953 4036130840507533 40653629 40799592 40945423 41091120 41236684 41382111
cycle =331 331 331 331 331 331 331 331 331 331 331 331 331
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331 331 331 331 331 331 331 331 331 331 331 331 331 331331 331 331 331 331 331 331 331 331 331 331 331
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VIII HOW TO DOWNLOAD A PRODUCT
VIII1 Download a product through the MyOcean Web Portal DirectgetfileService
You first need to register Please find below the registration stepshttpwwwmyoceaneuweb34-products-and-services-faqphp1Once registered the MyOcean FAQ httpwwwmyoceaneuweb34-products-and-services-faqwill guide you on How to download a product through the MyOcean Web Portal Directgetfile Service
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IX NEWS AND UPDATES
IX1 [Duacs] Operational news
To be kept informed on events occurring on the satellites and on the eventual interruption of the services of the DUACSprocessing system see the [Duacs] operational news on the Aviso websitehttpwwwavisooceanobscomendataoperational-newsindexhtml
IX2 Updates
To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtmlSince 2010 a complete reprocessing of all altimetry data (cumulated total of about 55 years of data) is available Themain changes introduced in the Duacs DT v300 reprocessed data set in SSALTODUACS reprocessed DT data setare listed herehttpwwwavisooceanobscomfileadmindocumentsdataduacsduacs_DT_2010_reprocessing_impactpdf
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VI12 Nomenclature of the datasets
The nomenclature used is
dataset-duacs-ltdelaygt-ltzonegt-ltmissiongt-lttype of slagt-l3where the fileds in ltgt are described below
delay nrt near-real time productsran delayed time products
zone global global geographic coverage productmedsea Mediterranean productsblacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1 (only for ran)e2 ERS-2 (only for ran)tp TOPEXPoseidon (only for ran)tpn TOPEXPoseidon on its new orbit (only for
ran)g2 GFO (only for ran)j1 Jason-1 (only for ran)j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisat (only for ran)enn Envisat on its new orbitc2 Cryosat-2 (only for nrt)
type of sla sla filtered slasla_unfiltered non filtered sla (only for ran products)
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VI13 Nomenclature of the NetCdf files
The nomenclature used is
ltdelaygt_ltzonegt_ltmissiongt_sla_ltvariablegt_ltdatebegingt_ltdateendgt_ltdateprodgtnc where the fileds in ltgt are de-scribed below
delay nrt near-real time productsdt delayed time products
zone global global geographic coverage productmed Mediterranean products (for dt)mfstep Mediterranean products (for nrt)blacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1e2 ERS-2tp TOPEXPoseidontpn TOPEXPoseidon on its new orbitg2 GFOj1 Jason-1j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisatenn Envisat on its new orbitc2 Cryosat-2
variable vfec filtered and sub-sampled slavxxc non filtered and non sub-sampled sla (only
for dt)datebegin YYYYMMDD() beginning date of the datasetdateend YYYYMMDD() end date of the datasetdateprod YYYYMMDD production date of the dataset
() For dt data as the dates in the file names are rounded the user wanting data for date T has to read the filescontaining dates T+1 and T-1 in their name and check inside the files if there are some data for date T
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VII DATA FORMAT
This chapter presents the data storage format used for MyOcean products
VII1 NetCdf
The products are stored using the NetCDF format NetCDF (network Common Data Form) is an interface for array-oriented data access and a library that provides an implementation of the interface The netCDF library also definesa machine-independent format for representing scientific data Together the interface library and format support thecreation access and sharing of scientific data The netCDF software was developed at the Unidata Program Center inBoulder Colorado The netCDF libraries define a machine-independent format for representing scientific data Pleasesee Unidata NetCDF pages for more information and to retreive NetCDF software package onhttpwwwunidataucaredupackagesnetcdfindexhtml
NetCDF data is
bull Self-Describing A netCDF file includes information about the data it contains
bull Architecture-independent A netCDF file is represented in a form that can be accessed by computers with dif-ferent ways of storing integers characters and floating-point numbers
bull Direct-access A small subset of a large dataset may be accessed efficiently without first reading through allthe preceding data
bull Appendable Data can be appended to a netCDF dataset along one dimension without copying the dataset orredefining its structure The structure of a netCDF dataset can be changed though this sometimes causes thedataset to be copied
bull Sharable One writer and multiple readers may simultaneously access the same netCDF file
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VII2 Structure and semantic of NetCDF along-track files
The NetCDF Sea Level TAC files are based on the attribute data tags defined by the Cooperative OceanAtmosphereResearch Data Service (COARDS) and Climate and Forecast (CF) metadata conventions The CF convention gener-alises and extends the COARDS convention but relaxes the COARDS constraints on dimension and order and specifiesmethods for reducing the size of datasetsA wide range of software are available to write or read NetCDFCF files API are made available by UNIDATA(httpwwwunidataucaredusoftwarenetcdf)
bull CC++Fortran
bull Java
bull MATLAB Objective-C Perl Python R Ruby TclTk
In addition to these conventions the files are using a common structure and semantic
bull 1 dimension is defined
ndash time it is used to check NetCDF variables depending on time
bull 8 variables are defined
ndash short SLA contains the Sea Level Anomaly values for each time given
ndash int longitude contains the longitude for each measurement
ndash short track contains the track number for each measurement
ndash double time contains the time in days since 1950-01-01 000000 UTC for each measurement
ndash short mean_profile_point_index index of the corrsponding point in the track of the mean profile
ndash byte flag flag=0 the processed data comes from OGDR if flag=1 the processed data comes from theIGDR
ndash int latitude contains the latitude for each measurement
ndash short cycle contains the cycle number for each measurement
bull global attributes
ndash the global attributes gives information about the creation of the file
Example of a NetCDF sla file
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netcdf nrt_global_j1_sla_vfec_20101230_20101230_20101230 dimensions
time = 10385 variables
short SLA(time) SLAcoordinates = longitude latitude SLAlong_name = Sea Level Anomaly SLA_FillValue = 32767s SLAadd_offset = 0 SLAscale_factor = 0001 SLAunits = m SLAstandard_name = sea_surface_height_above_sea_level
int longitude(time) longitudelong_name = Longitude of measurement longitude_FillValue = 2147483647 longitudeadd_offset = 0 longitudestandard_name = longitude longitudescale_factor = 1e-06 longitudeunits = degrees_east
short track(time) tracklong_name = Track in cycle the measurement belongs to track_FillValue = 32767s trackunits = 1 trackcoordinates = longitude latitude
double time(time) timelong_name = Time of measurement time_FillValue = 184467440737096e+19 timeaxis = T timestandard_name = time timeunits = days since 1950-01-01 000000 UTC
int latitude(time) latitudelong_name = Latitude of measurement latitude_FillValue = 2147483647 latitudeadd_offset = 0 latitudestandard_name = latitude latitudescale_factor = 1e-06 latitudeunits = degrees_north
short flag(time) flagcoordinates = longitude latitude flag_FillValue = 3267s flaglong_name = data origin flagflag_values = 1s 0s flagflag_meanings = igdr_like non_igdr_like flagcomment = The origin of the data is determined by the types of geophysical datarecords (GDR) used in computation of the SLA 1 for the Interim GDR (IGDR) and0 for Operational GDR (OGDR)
short cycle(time) cyclelong_name = Cycle the measurement belongs to cycle_FillValue = 32767s cycleunits = 1 cyclecoordinates = longitude latitude
global attributeshistory = 22-Feb-2011 155243 CET File created by the SSLATODUACS system version 1001 comment = Produce from ENVISAT Extension Phase satellite altimetry data institution = CLSCNES
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references = httpwwwavisooceanobscomfileadmindocumentsdatatoolshdbk_duacspdf source = satellite altimetry title = along track Sea Level Anomaly Conventions = CF-14
dataSLA =
7 7 11 10 -2 -22 -39 -41 -30 -13 -3 -5 -16 -26 -32 -35-35 -35 -37 -35 -31 -29 -31 -35 -32 -21 -10 -10 -19 -20 -1-69 -57 -49 -45 -39 -30 -28 -31 -27 -13 -2 -5 -15 -3 1112 3 -7 -10 -14 -15 -22 -31 -37 -32 -17 -10
longitude =74743328 74868400 74993968 75120040 75246616 7537372875501368 75629568 75758320 75887656 76017568 76148080 7627920876388952 76477056 76565456 76654144 76743128 76832400 76921984329429568 329535424 329641792 329748672 329856096 329964032330072512 330181536 330291072 330401184
track =92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 9292 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92113 113 113 113 113 113 113 113 113 113 113 113 113 113113 113 113 113 113 113 113 113 113
time =222780000565705 222780001314719 222780002063733222780002812747 222780003561761 222780004310775 222780005059788222780005808802 222780006557816 22278000730683 222780008055844222780008804858 222780009553872 22278001017805 222780010677393222788257112198 222788257486705 222788257861212 222788258235719222788258610226 222788258984733 222788259359239 222788259733746222788260108253 22278826048276
mean_profile_point_index =1872 1878 1884 1890 1896 1902 1908 19141920 1926 1932 1938 1944 1949 1953 1957 1961 1965 1969 19732306 2309 2312 2315 2318 2321 2327 2330 2333 2336 2339 23422345 2348 2351 2354 2357 2360 2363 2366
flag =0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
latitude =-16225506 -16539731 -16853833 -17167810 -17481660 -17795380-18108966 -18422418 -18735729 -19048899 -19361924 -19674801-19987527 -20248015 -20456329 -20664569 -20872739 -2108083739481297 39628277 39775133 39921866 40068472 40214953 4036130840507533 40653629 40799592 40945423 41091120 41236684 41382111
cycle =331 331 331 331 331 331 331 331 331 331 331 331 331
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331 331 331 331 331 331 331 331 331 331 331 331 331 331331 331 331 331 331 331 331 331 331 331 331 331
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
VIII HOW TO DOWNLOAD A PRODUCT
VIII1 Download a product through the MyOcean Web Portal DirectgetfileService
You first need to register Please find below the registration stepshttpwwwmyoceaneuweb34-products-and-services-faqphp1Once registered the MyOcean FAQ httpwwwmyoceaneuweb34-products-and-services-faqwill guide you on How to download a product through the MyOcean Web Portal Directgetfile Service
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
IX NEWS AND UPDATES
IX1 [Duacs] Operational news
To be kept informed on events occurring on the satellites and on the eventual interruption of the services of the DUACSprocessing system see the [Duacs] operational news on the Aviso websitehttpwwwavisooceanobscomendataoperational-newsindexhtml
IX2 Updates
To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtmlSince 2010 a complete reprocessing of all altimetry data (cumulated total of about 55 years of data) is available Themain changes introduced in the Duacs DT v300 reprocessed data set in SSALTODUACS reprocessed DT data setare listed herehttpwwwavisooceanobscomfileadmindocumentsdataduacsduacs_DT_2010_reprocessing_impactpdf
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VI13 Nomenclature of the NetCdf files
The nomenclature used is
ltdelaygt_ltzonegt_ltmissiongt_sla_ltvariablegt_ltdatebegingt_ltdateendgt_ltdateprodgtnc where the fileds in ltgt are de-scribed below
delay nrt near-real time productsdt delayed time products
zone global global geographic coverage productmed Mediterranean products (for dt)mfstep Mediterranean products (for nrt)blacksea Black Sea productsarctic Arctic products (only for nrt)europe Europe products (only for nrt)
mission e1 ERS-1e2 ERS-2tp TOPEXPoseidontpn TOPEXPoseidon on its new orbitg2 GFOj1 Jason-1j1n Jason-1 on its new orbitj1g Jason-1 on its geodetic orbitj2 Jason-2en Envisatenn Envisat on its new orbitc2 Cryosat-2
variable vfec filtered and sub-sampled slavxxc non filtered and non sub-sampled sla (only
for dt)datebegin YYYYMMDD() beginning date of the datasetdateend YYYYMMDD() end date of the datasetdateprod YYYYMMDD production date of the dataset
() For dt data as the dates in the file names are rounded the user wanting data for date T has to read the filescontaining dates T+1 and T-1 in their name and check inside the files if there are some data for date T
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VII DATA FORMAT
This chapter presents the data storage format used for MyOcean products
VII1 NetCdf
The products are stored using the NetCDF format NetCDF (network Common Data Form) is an interface for array-oriented data access and a library that provides an implementation of the interface The netCDF library also definesa machine-independent format for representing scientific data Together the interface library and format support thecreation access and sharing of scientific data The netCDF software was developed at the Unidata Program Center inBoulder Colorado The netCDF libraries define a machine-independent format for representing scientific data Pleasesee Unidata NetCDF pages for more information and to retreive NetCDF software package onhttpwwwunidataucaredupackagesnetcdfindexhtml
NetCDF data is
bull Self-Describing A netCDF file includes information about the data it contains
bull Architecture-independent A netCDF file is represented in a form that can be accessed by computers with dif-ferent ways of storing integers characters and floating-point numbers
bull Direct-access A small subset of a large dataset may be accessed efficiently without first reading through allthe preceding data
bull Appendable Data can be appended to a netCDF dataset along one dimension without copying the dataset orredefining its structure The structure of a netCDF dataset can be changed though this sometimes causes thedataset to be copied
bull Sharable One writer and multiple readers may simultaneously access the same netCDF file
Page 50
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
VII2 Structure and semantic of NetCDF along-track files
The NetCDF Sea Level TAC files are based on the attribute data tags defined by the Cooperative OceanAtmosphereResearch Data Service (COARDS) and Climate and Forecast (CF) metadata conventions The CF convention gener-alises and extends the COARDS convention but relaxes the COARDS constraints on dimension and order and specifiesmethods for reducing the size of datasetsA wide range of software are available to write or read NetCDFCF files API are made available by UNIDATA(httpwwwunidataucaredusoftwarenetcdf)
bull CC++Fortran
bull Java
bull MATLAB Objective-C Perl Python R Ruby TclTk
In addition to these conventions the files are using a common structure and semantic
bull 1 dimension is defined
ndash time it is used to check NetCDF variables depending on time
bull 8 variables are defined
ndash short SLA contains the Sea Level Anomaly values for each time given
ndash int longitude contains the longitude for each measurement
ndash short track contains the track number for each measurement
ndash double time contains the time in days since 1950-01-01 000000 UTC for each measurement
ndash short mean_profile_point_index index of the corrsponding point in the track of the mean profile
ndash byte flag flag=0 the processed data comes from OGDR if flag=1 the processed data comes from theIGDR
ndash int latitude contains the latitude for each measurement
ndash short cycle contains the cycle number for each measurement
bull global attributes
ndash the global attributes gives information about the creation of the file
Example of a NetCDF sla file
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netcdf nrt_global_j1_sla_vfec_20101230_20101230_20101230 dimensions
time = 10385 variables
short SLA(time) SLAcoordinates = longitude latitude SLAlong_name = Sea Level Anomaly SLA_FillValue = 32767s SLAadd_offset = 0 SLAscale_factor = 0001 SLAunits = m SLAstandard_name = sea_surface_height_above_sea_level
int longitude(time) longitudelong_name = Longitude of measurement longitude_FillValue = 2147483647 longitudeadd_offset = 0 longitudestandard_name = longitude longitudescale_factor = 1e-06 longitudeunits = degrees_east
short track(time) tracklong_name = Track in cycle the measurement belongs to track_FillValue = 32767s trackunits = 1 trackcoordinates = longitude latitude
double time(time) timelong_name = Time of measurement time_FillValue = 184467440737096e+19 timeaxis = T timestandard_name = time timeunits = days since 1950-01-01 000000 UTC
int latitude(time) latitudelong_name = Latitude of measurement latitude_FillValue = 2147483647 latitudeadd_offset = 0 latitudestandard_name = latitude latitudescale_factor = 1e-06 latitudeunits = degrees_north
short flag(time) flagcoordinates = longitude latitude flag_FillValue = 3267s flaglong_name = data origin flagflag_values = 1s 0s flagflag_meanings = igdr_like non_igdr_like flagcomment = The origin of the data is determined by the types of geophysical datarecords (GDR) used in computation of the SLA 1 for the Interim GDR (IGDR) and0 for Operational GDR (OGDR)
short cycle(time) cyclelong_name = Cycle the measurement belongs to cycle_FillValue = 32767s cycleunits = 1 cyclecoordinates = longitude latitude
global attributeshistory = 22-Feb-2011 155243 CET File created by the SSLATODUACS system version 1001 comment = Produce from ENVISAT Extension Phase satellite altimetry data institution = CLSCNES
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references = httpwwwavisooceanobscomfileadmindocumentsdatatoolshdbk_duacspdf source = satellite altimetry title = along track Sea Level Anomaly Conventions = CF-14
dataSLA =
7 7 11 10 -2 -22 -39 -41 -30 -13 -3 -5 -16 -26 -32 -35-35 -35 -37 -35 -31 -29 -31 -35 -32 -21 -10 -10 -19 -20 -1-69 -57 -49 -45 -39 -30 -28 -31 -27 -13 -2 -5 -15 -3 1112 3 -7 -10 -14 -15 -22 -31 -37 -32 -17 -10
longitude =74743328 74868400 74993968 75120040 75246616 7537372875501368 75629568 75758320 75887656 76017568 76148080 7627920876388952 76477056 76565456 76654144 76743128 76832400 76921984329429568 329535424 329641792 329748672 329856096 329964032330072512 330181536 330291072 330401184
track =92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 9292 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92113 113 113 113 113 113 113 113 113 113 113 113 113 113113 113 113 113 113 113 113 113 113
time =222780000565705 222780001314719 222780002063733222780002812747 222780003561761 222780004310775 222780005059788222780005808802 222780006557816 22278000730683 222780008055844222780008804858 222780009553872 22278001017805 222780010677393222788257112198 222788257486705 222788257861212 222788258235719222788258610226 222788258984733 222788259359239 222788259733746222788260108253 22278826048276
mean_profile_point_index =1872 1878 1884 1890 1896 1902 1908 19141920 1926 1932 1938 1944 1949 1953 1957 1961 1965 1969 19732306 2309 2312 2315 2318 2321 2327 2330 2333 2336 2339 23422345 2348 2351 2354 2357 2360 2363 2366
flag =0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
latitude =-16225506 -16539731 -16853833 -17167810 -17481660 -17795380-18108966 -18422418 -18735729 -19048899 -19361924 -19674801-19987527 -20248015 -20456329 -20664569 -20872739 -2108083739481297 39628277 39775133 39921866 40068472 40214953 4036130840507533 40653629 40799592 40945423 41091120 41236684 41382111
cycle =331 331 331 331 331 331 331 331 331 331 331 331 331
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331 331 331 331 331 331 331 331 331 331 331 331 331 331331 331 331 331 331 331 331 331 331 331 331 331
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
VIII HOW TO DOWNLOAD A PRODUCT
VIII1 Download a product through the MyOcean Web Portal DirectgetfileService
You first need to register Please find below the registration stepshttpwwwmyoceaneuweb34-products-and-services-faqphp1Once registered the MyOcean FAQ httpwwwmyoceaneuweb34-products-and-services-faqwill guide you on How to download a product through the MyOcean Web Portal Directgetfile Service
Page 55
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
IX NEWS AND UPDATES
IX1 [Duacs] Operational news
To be kept informed on events occurring on the satellites and on the eventual interruption of the services of the DUACSprocessing system see the [Duacs] operational news on the Aviso websitehttpwwwavisooceanobscomendataoperational-newsindexhtml
IX2 Updates
To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtmlSince 2010 a complete reprocessing of all altimetry data (cumulated total of about 55 years of data) is available Themain changes introduced in the Duacs DT v300 reprocessed data set in SSALTODUACS reprocessed DT data setare listed herehttpwwwavisooceanobscomfileadmindocumentsdataduacsduacs_DT_2010_reprocessing_impactpdf
Page 56
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
VII DATA FORMAT
This chapter presents the data storage format used for MyOcean products
VII1 NetCdf
The products are stored using the NetCDF format NetCDF (network Common Data Form) is an interface for array-oriented data access and a library that provides an implementation of the interface The netCDF library also definesa machine-independent format for representing scientific data Together the interface library and format support thecreation access and sharing of scientific data The netCDF software was developed at the Unidata Program Center inBoulder Colorado The netCDF libraries define a machine-independent format for representing scientific data Pleasesee Unidata NetCDF pages for more information and to retreive NetCDF software package onhttpwwwunidataucaredupackagesnetcdfindexhtml
NetCDF data is
bull Self-Describing A netCDF file includes information about the data it contains
bull Architecture-independent A netCDF file is represented in a form that can be accessed by computers with dif-ferent ways of storing integers characters and floating-point numbers
bull Direct-access A small subset of a large dataset may be accessed efficiently without first reading through allthe preceding data
bull Appendable Data can be appended to a netCDF dataset along one dimension without copying the dataset orredefining its structure The structure of a netCDF dataset can be changed though this sometimes causes thedataset to be copied
bull Sharable One writer and multiple readers may simultaneously access the same netCDF file
Page 50
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
VII2 Structure and semantic of NetCDF along-track files
The NetCDF Sea Level TAC files are based on the attribute data tags defined by the Cooperative OceanAtmosphereResearch Data Service (COARDS) and Climate and Forecast (CF) metadata conventions The CF convention gener-alises and extends the COARDS convention but relaxes the COARDS constraints on dimension and order and specifiesmethods for reducing the size of datasetsA wide range of software are available to write or read NetCDFCF files API are made available by UNIDATA(httpwwwunidataucaredusoftwarenetcdf)
bull CC++Fortran
bull Java
bull MATLAB Objective-C Perl Python R Ruby TclTk
In addition to these conventions the files are using a common structure and semantic
bull 1 dimension is defined
ndash time it is used to check NetCDF variables depending on time
bull 8 variables are defined
ndash short SLA contains the Sea Level Anomaly values for each time given
ndash int longitude contains the longitude for each measurement
ndash short track contains the track number for each measurement
ndash double time contains the time in days since 1950-01-01 000000 UTC for each measurement
ndash short mean_profile_point_index index of the corrsponding point in the track of the mean profile
ndash byte flag flag=0 the processed data comes from OGDR if flag=1 the processed data comes from theIGDR
ndash int latitude contains the latitude for each measurement
ndash short cycle contains the cycle number for each measurement
bull global attributes
ndash the global attributes gives information about the creation of the file
Example of a NetCDF sla file
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netcdf nrt_global_j1_sla_vfec_20101230_20101230_20101230 dimensions
time = 10385 variables
short SLA(time) SLAcoordinates = longitude latitude SLAlong_name = Sea Level Anomaly SLA_FillValue = 32767s SLAadd_offset = 0 SLAscale_factor = 0001 SLAunits = m SLAstandard_name = sea_surface_height_above_sea_level
int longitude(time) longitudelong_name = Longitude of measurement longitude_FillValue = 2147483647 longitudeadd_offset = 0 longitudestandard_name = longitude longitudescale_factor = 1e-06 longitudeunits = degrees_east
short track(time) tracklong_name = Track in cycle the measurement belongs to track_FillValue = 32767s trackunits = 1 trackcoordinates = longitude latitude
double time(time) timelong_name = Time of measurement time_FillValue = 184467440737096e+19 timeaxis = T timestandard_name = time timeunits = days since 1950-01-01 000000 UTC
int latitude(time) latitudelong_name = Latitude of measurement latitude_FillValue = 2147483647 latitudeadd_offset = 0 latitudestandard_name = latitude latitudescale_factor = 1e-06 latitudeunits = degrees_north
short flag(time) flagcoordinates = longitude latitude flag_FillValue = 3267s flaglong_name = data origin flagflag_values = 1s 0s flagflag_meanings = igdr_like non_igdr_like flagcomment = The origin of the data is determined by the types of geophysical datarecords (GDR) used in computation of the SLA 1 for the Interim GDR (IGDR) and0 for Operational GDR (OGDR)
short cycle(time) cyclelong_name = Cycle the measurement belongs to cycle_FillValue = 32767s cycleunits = 1 cyclecoordinates = longitude latitude
global attributeshistory = 22-Feb-2011 155243 CET File created by the SSLATODUACS system version 1001 comment = Produce from ENVISAT Extension Phase satellite altimetry data institution = CLSCNES
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references = httpwwwavisooceanobscomfileadmindocumentsdatatoolshdbk_duacspdf source = satellite altimetry title = along track Sea Level Anomaly Conventions = CF-14
dataSLA =
7 7 11 10 -2 -22 -39 -41 -30 -13 -3 -5 -16 -26 -32 -35-35 -35 -37 -35 -31 -29 -31 -35 -32 -21 -10 -10 -19 -20 -1-69 -57 -49 -45 -39 -30 -28 -31 -27 -13 -2 -5 -15 -3 1112 3 -7 -10 -14 -15 -22 -31 -37 -32 -17 -10
longitude =74743328 74868400 74993968 75120040 75246616 7537372875501368 75629568 75758320 75887656 76017568 76148080 7627920876388952 76477056 76565456 76654144 76743128 76832400 76921984329429568 329535424 329641792 329748672 329856096 329964032330072512 330181536 330291072 330401184
track =92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 9292 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92113 113 113 113 113 113 113 113 113 113 113 113 113 113113 113 113 113 113 113 113 113 113
time =222780000565705 222780001314719 222780002063733222780002812747 222780003561761 222780004310775 222780005059788222780005808802 222780006557816 22278000730683 222780008055844222780008804858 222780009553872 22278001017805 222780010677393222788257112198 222788257486705 222788257861212 222788258235719222788258610226 222788258984733 222788259359239 222788259733746222788260108253 22278826048276
mean_profile_point_index =1872 1878 1884 1890 1896 1902 1908 19141920 1926 1932 1938 1944 1949 1953 1957 1961 1965 1969 19732306 2309 2312 2315 2318 2321 2327 2330 2333 2336 2339 23422345 2348 2351 2354 2357 2360 2363 2366
flag =0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
latitude =-16225506 -16539731 -16853833 -17167810 -17481660 -17795380-18108966 -18422418 -18735729 -19048899 -19361924 -19674801-19987527 -20248015 -20456329 -20664569 -20872739 -2108083739481297 39628277 39775133 39921866 40068472 40214953 4036130840507533 40653629 40799592 40945423 41091120 41236684 41382111
cycle =331 331 331 331 331 331 331 331 331 331 331 331 331
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331 331 331 331 331 331 331 331 331 331 331 331 331 331331 331 331 331 331 331 331 331 331 331 331 331
Page 54
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
VIII HOW TO DOWNLOAD A PRODUCT
VIII1 Download a product through the MyOcean Web Portal DirectgetfileService
You first need to register Please find below the registration stepshttpwwwmyoceaneuweb34-products-and-services-faqphp1Once registered the MyOcean FAQ httpwwwmyoceaneuweb34-products-and-services-faqwill guide you on How to download a product through the MyOcean Web Portal Directgetfile Service
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PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
IX NEWS AND UPDATES
IX1 [Duacs] Operational news
To be kept informed on events occurring on the satellites and on the eventual interruption of the services of the DUACSprocessing system see the [Duacs] operational news on the Aviso websitehttpwwwavisooceanobscomendataoperational-newsindexhtml
IX2 Updates
To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtmlSince 2010 a complete reprocessing of all altimetry data (cumulated total of about 55 years of data) is available Themain changes introduced in the Duacs DT v300 reprocessed data set in SSALTODUACS reprocessed DT data setare listed herehttpwwwavisooceanobscomfileadmindocumentsdataduacsduacs_DT_2010_reprocessing_impactpdf
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
VII2 Structure and semantic of NetCDF along-track files
The NetCDF Sea Level TAC files are based on the attribute data tags defined by the Cooperative OceanAtmosphereResearch Data Service (COARDS) and Climate and Forecast (CF) metadata conventions The CF convention gener-alises and extends the COARDS convention but relaxes the COARDS constraints on dimension and order and specifiesmethods for reducing the size of datasetsA wide range of software are available to write or read NetCDFCF files API are made available by UNIDATA(httpwwwunidataucaredusoftwarenetcdf)
bull CC++Fortran
bull Java
bull MATLAB Objective-C Perl Python R Ruby TclTk
In addition to these conventions the files are using a common structure and semantic
bull 1 dimension is defined
ndash time it is used to check NetCDF variables depending on time
bull 8 variables are defined
ndash short SLA contains the Sea Level Anomaly values for each time given
ndash int longitude contains the longitude for each measurement
ndash short track contains the track number for each measurement
ndash double time contains the time in days since 1950-01-01 000000 UTC for each measurement
ndash short mean_profile_point_index index of the corrsponding point in the track of the mean profile
ndash byte flag flag=0 the processed data comes from OGDR if flag=1 the processed data comes from theIGDR
ndash int latitude contains the latitude for each measurement
ndash short cycle contains the cycle number for each measurement
bull global attributes
ndash the global attributes gives information about the creation of the file
Example of a NetCDF sla file
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netcdf nrt_global_j1_sla_vfec_20101230_20101230_20101230 dimensions
time = 10385 variables
short SLA(time) SLAcoordinates = longitude latitude SLAlong_name = Sea Level Anomaly SLA_FillValue = 32767s SLAadd_offset = 0 SLAscale_factor = 0001 SLAunits = m SLAstandard_name = sea_surface_height_above_sea_level
int longitude(time) longitudelong_name = Longitude of measurement longitude_FillValue = 2147483647 longitudeadd_offset = 0 longitudestandard_name = longitude longitudescale_factor = 1e-06 longitudeunits = degrees_east
short track(time) tracklong_name = Track in cycle the measurement belongs to track_FillValue = 32767s trackunits = 1 trackcoordinates = longitude latitude
double time(time) timelong_name = Time of measurement time_FillValue = 184467440737096e+19 timeaxis = T timestandard_name = time timeunits = days since 1950-01-01 000000 UTC
int latitude(time) latitudelong_name = Latitude of measurement latitude_FillValue = 2147483647 latitudeadd_offset = 0 latitudestandard_name = latitude latitudescale_factor = 1e-06 latitudeunits = degrees_north
short flag(time) flagcoordinates = longitude latitude flag_FillValue = 3267s flaglong_name = data origin flagflag_values = 1s 0s flagflag_meanings = igdr_like non_igdr_like flagcomment = The origin of the data is determined by the types of geophysical datarecords (GDR) used in computation of the SLA 1 for the Interim GDR (IGDR) and0 for Operational GDR (OGDR)
short cycle(time) cyclelong_name = Cycle the measurement belongs to cycle_FillValue = 32767s cycleunits = 1 cyclecoordinates = longitude latitude
global attributeshistory = 22-Feb-2011 155243 CET File created by the SSLATODUACS system version 1001 comment = Produce from ENVISAT Extension Phase satellite altimetry data institution = CLSCNES
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
references = httpwwwavisooceanobscomfileadmindocumentsdatatoolshdbk_duacspdf source = satellite altimetry title = along track Sea Level Anomaly Conventions = CF-14
dataSLA =
7 7 11 10 -2 -22 -39 -41 -30 -13 -3 -5 -16 -26 -32 -35-35 -35 -37 -35 -31 -29 -31 -35 -32 -21 -10 -10 -19 -20 -1-69 -57 -49 -45 -39 -30 -28 -31 -27 -13 -2 -5 -15 -3 1112 3 -7 -10 -14 -15 -22 -31 -37 -32 -17 -10
longitude =74743328 74868400 74993968 75120040 75246616 7537372875501368 75629568 75758320 75887656 76017568 76148080 7627920876388952 76477056 76565456 76654144 76743128 76832400 76921984329429568 329535424 329641792 329748672 329856096 329964032330072512 330181536 330291072 330401184
track =92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 9292 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92113 113 113 113 113 113 113 113 113 113 113 113 113 113113 113 113 113 113 113 113 113 113
time =222780000565705 222780001314719 222780002063733222780002812747 222780003561761 222780004310775 222780005059788222780005808802 222780006557816 22278000730683 222780008055844222780008804858 222780009553872 22278001017805 222780010677393222788257112198 222788257486705 222788257861212 222788258235719222788258610226 222788258984733 222788259359239 222788259733746222788260108253 22278826048276
mean_profile_point_index =1872 1878 1884 1890 1896 1902 1908 19141920 1926 1932 1938 1944 1949 1953 1957 1961 1965 1969 19732306 2309 2312 2315 2318 2321 2327 2330 2333 2336 2339 23422345 2348 2351 2354 2357 2360 2363 2366
flag =0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
latitude =-16225506 -16539731 -16853833 -17167810 -17481660 -17795380-18108966 -18422418 -18735729 -19048899 -19361924 -19674801-19987527 -20248015 -20456329 -20664569 -20872739 -2108083739481297 39628277 39775133 39921866 40068472 40214953 4036130840507533 40653629 40799592 40945423 41091120 41236684 41382111
cycle =331 331 331 331 331 331 331 331 331 331 331 331 331
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
331 331 331 331 331 331 331 331 331 331 331 331 331 331331 331 331 331 331 331 331 331 331 331 331 331
Page 54
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
VIII HOW TO DOWNLOAD A PRODUCT
VIII1 Download a product through the MyOcean Web Portal DirectgetfileService
You first need to register Please find below the registration stepshttpwwwmyoceaneuweb34-products-and-services-faqphp1Once registered the MyOcean FAQ httpwwwmyoceaneuweb34-products-and-services-faqwill guide you on How to download a product through the MyOcean Web Portal Directgetfile Service
Page 55
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
IX NEWS AND UPDATES
IX1 [Duacs] Operational news
To be kept informed on events occurring on the satellites and on the eventual interruption of the services of the DUACSprocessing system see the [Duacs] operational news on the Aviso websitehttpwwwavisooceanobscomendataoperational-newsindexhtml
IX2 Updates
To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtmlSince 2010 a complete reprocessing of all altimetry data (cumulated total of about 55 years of data) is available Themain changes introduced in the Duacs DT v300 reprocessed data set in SSALTODUACS reprocessed DT data setare listed herehttpwwwavisooceanobscomfileadmindocumentsdataduacsduacs_DT_2010_reprocessing_impactpdf
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PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
netcdf nrt_global_j1_sla_vfec_20101230_20101230_20101230 dimensions
time = 10385 variables
short SLA(time) SLAcoordinates = longitude latitude SLAlong_name = Sea Level Anomaly SLA_FillValue = 32767s SLAadd_offset = 0 SLAscale_factor = 0001 SLAunits = m SLAstandard_name = sea_surface_height_above_sea_level
int longitude(time) longitudelong_name = Longitude of measurement longitude_FillValue = 2147483647 longitudeadd_offset = 0 longitudestandard_name = longitude longitudescale_factor = 1e-06 longitudeunits = degrees_east
short track(time) tracklong_name = Track in cycle the measurement belongs to track_FillValue = 32767s trackunits = 1 trackcoordinates = longitude latitude
double time(time) timelong_name = Time of measurement time_FillValue = 184467440737096e+19 timeaxis = T timestandard_name = time timeunits = days since 1950-01-01 000000 UTC
int latitude(time) latitudelong_name = Latitude of measurement latitude_FillValue = 2147483647 latitudeadd_offset = 0 latitudestandard_name = latitude latitudescale_factor = 1e-06 latitudeunits = degrees_north
short flag(time) flagcoordinates = longitude latitude flag_FillValue = 3267s flaglong_name = data origin flagflag_values = 1s 0s flagflag_meanings = igdr_like non_igdr_like flagcomment = The origin of the data is determined by the types of geophysical datarecords (GDR) used in computation of the SLA 1 for the Interim GDR (IGDR) and0 for Operational GDR (OGDR)
short cycle(time) cyclelong_name = Cycle the measurement belongs to cycle_FillValue = 32767s cycleunits = 1 cyclecoordinates = longitude latitude
global attributeshistory = 22-Feb-2011 155243 CET File created by the SSLATODUACS system version 1001 comment = Produce from ENVISAT Extension Phase satellite altimetry data institution = CLSCNES
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SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
references = httpwwwavisooceanobscomfileadmindocumentsdatatoolshdbk_duacspdf source = satellite altimetry title = along track Sea Level Anomaly Conventions = CF-14
dataSLA =
7 7 11 10 -2 -22 -39 -41 -30 -13 -3 -5 -16 -26 -32 -35-35 -35 -37 -35 -31 -29 -31 -35 -32 -21 -10 -10 -19 -20 -1-69 -57 -49 -45 -39 -30 -28 -31 -27 -13 -2 -5 -15 -3 1112 3 -7 -10 -14 -15 -22 -31 -37 -32 -17 -10
longitude =74743328 74868400 74993968 75120040 75246616 7537372875501368 75629568 75758320 75887656 76017568 76148080 7627920876388952 76477056 76565456 76654144 76743128 76832400 76921984329429568 329535424 329641792 329748672 329856096 329964032330072512 330181536 330291072 330401184
track =92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 9292 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92113 113 113 113 113 113 113 113 113 113 113 113 113 113113 113 113 113 113 113 113 113 113
time =222780000565705 222780001314719 222780002063733222780002812747 222780003561761 222780004310775 222780005059788222780005808802 222780006557816 22278000730683 222780008055844222780008804858 222780009553872 22278001017805 222780010677393222788257112198 222788257486705 222788257861212 222788258235719222788258610226 222788258984733 222788259359239 222788259733746222788260108253 22278826048276
mean_profile_point_index =1872 1878 1884 1890 1896 1902 1908 19141920 1926 1932 1938 1944 1949 1953 1957 1961 1965 1969 19732306 2309 2312 2315 2318 2321 2327 2330 2333 2336 2339 23422345 2348 2351 2354 2357 2360 2363 2366
flag =0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
latitude =-16225506 -16539731 -16853833 -17167810 -17481660 -17795380-18108966 -18422418 -18735729 -19048899 -19361924 -19674801-19987527 -20248015 -20456329 -20664569 -20872739 -2108083739481297 39628277 39775133 39921866 40068472 40214953 4036130840507533 40653629 40799592 40945423 41091120 41236684 41382111
cycle =331 331 331 331 331 331 331 331 331 331 331 331 331
Page 53
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
331 331 331 331 331 331 331 331 331 331 331 331 331 331331 331 331 331 331 331 331 331 331 331 331 331
Page 54
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
VIII HOW TO DOWNLOAD A PRODUCT
VIII1 Download a product through the MyOcean Web Portal DirectgetfileService
You first need to register Please find below the registration stepshttpwwwmyoceaneuweb34-products-and-services-faqphp1Once registered the MyOcean FAQ httpwwwmyoceaneuweb34-products-and-services-faqwill guide you on How to download a product through the MyOcean Web Portal Directgetfile Service
Page 55
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
IX NEWS AND UPDATES
IX1 [Duacs] Operational news
To be kept informed on events occurring on the satellites and on the eventual interruption of the services of the DUACSprocessing system see the [Duacs] operational news on the Aviso websitehttpwwwavisooceanobscomendataoperational-newsindexhtml
IX2 Updates
To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtmlSince 2010 a complete reprocessing of all altimetry data (cumulated total of about 55 years of data) is available Themain changes introduced in the Duacs DT v300 reprocessed data set in SSALTODUACS reprocessed DT data setare listed herehttpwwwavisooceanobscomfileadmindocumentsdataduacsduacs_DT_2010_reprocessing_impactpdf
Page 56
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
references = httpwwwavisooceanobscomfileadmindocumentsdatatoolshdbk_duacspdf source = satellite altimetry title = along track Sea Level Anomaly Conventions = CF-14
dataSLA =
7 7 11 10 -2 -22 -39 -41 -30 -13 -3 -5 -16 -26 -32 -35-35 -35 -37 -35 -31 -29 -31 -35 -32 -21 -10 -10 -19 -20 -1-69 -57 -49 -45 -39 -30 -28 -31 -27 -13 -2 -5 -15 -3 1112 3 -7 -10 -14 -15 -22 -31 -37 -32 -17 -10
longitude =74743328 74868400 74993968 75120040 75246616 7537372875501368 75629568 75758320 75887656 76017568 76148080 7627920876388952 76477056 76565456 76654144 76743128 76832400 76921984329429568 329535424 329641792 329748672 329856096 329964032330072512 330181536 330291072 330401184
track =92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 9292 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92 92113 113 113 113 113 113 113 113 113 113 113 113 113 113113 113 113 113 113 113 113 113 113
time =222780000565705 222780001314719 222780002063733222780002812747 222780003561761 222780004310775 222780005059788222780005808802 222780006557816 22278000730683 222780008055844222780008804858 222780009553872 22278001017805 222780010677393222788257112198 222788257486705 222788257861212 222788258235719222788258610226 222788258984733 222788259359239 222788259733746222788260108253 22278826048276
mean_profile_point_index =1872 1878 1884 1890 1896 1902 1908 19141920 1926 1932 1938 1944 1949 1953 1957 1961 1965 1969 19732306 2309 2312 2315 2318 2321 2327 2330 2333 2336 2339 23422345 2348 2351 2354 2357 2360 2363 2366
flag =0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
latitude =-16225506 -16539731 -16853833 -17167810 -17481660 -17795380-18108966 -18422418 -18735729 -19048899 -19361924 -19674801-19987527 -20248015 -20456329 -20664569 -20872739 -2108083739481297 39628277 39775133 39921866 40068472 40214953 4036130840507533 40653629 40799592 40945423 41091120 41236684 41382111
cycle =331 331 331 331 331 331 331 331 331 331 331 331 331
Page 53
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
331 331 331 331 331 331 331 331 331 331 331 331 331 331331 331 331 331 331 331 331 331 331 331 331 331
Page 54
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
VIII HOW TO DOWNLOAD A PRODUCT
VIII1 Download a product through the MyOcean Web Portal DirectgetfileService
You first need to register Please find below the registration stepshttpwwwmyoceaneuweb34-products-and-services-faqphp1Once registered the MyOcean FAQ httpwwwmyoceaneuweb34-products-and-services-faqwill guide you on How to download a product through the MyOcean Web Portal Directgetfile Service
Page 55
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
IX NEWS AND UPDATES
IX1 [Duacs] Operational news
To be kept informed on events occurring on the satellites and on the eventual interruption of the services of the DUACSprocessing system see the [Duacs] operational news on the Aviso websitehttpwwwavisooceanobscomendataoperational-newsindexhtml
IX2 Updates
To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtmlSince 2010 a complete reprocessing of all altimetry data (cumulated total of about 55 years of data) is available Themain changes introduced in the Duacs DT v300 reprocessed data set in SSALTODUACS reprocessed DT data setare listed herehttpwwwavisooceanobscomfileadmindocumentsdataduacsduacs_DT_2010_reprocessing_impactpdf
Page 56
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
331 331 331 331 331 331 331 331 331 331 331 331 331 331331 331 331 331 331 331 331 331 331 331 331 331
Page 54
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
VIII HOW TO DOWNLOAD A PRODUCT
VIII1 Download a product through the MyOcean Web Portal DirectgetfileService
You first need to register Please find below the registration stepshttpwwwmyoceaneuweb34-products-and-services-faqphp1Once registered the MyOcean FAQ httpwwwmyoceaneuweb34-products-and-services-faqwill guide you on How to download a product through the MyOcean Web Portal Directgetfile Service
Page 55
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
IX NEWS AND UPDATES
IX1 [Duacs] Operational news
To be kept informed on events occurring on the satellites and on the eventual interruption of the services of the DUACSprocessing system see the [Duacs] operational news on the Aviso websitehttpwwwavisooceanobscomendataoperational-newsindexhtml
IX2 Updates
To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtmlSince 2010 a complete reprocessing of all altimetry data (cumulated total of about 55 years of data) is available Themain changes introduced in the Duacs DT v300 reprocessed data set in SSALTODUACS reprocessed DT data setare listed herehttpwwwavisooceanobscomfileadmindocumentsdataduacsduacs_DT_2010_reprocessing_impactpdf
Page 56
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
VIII HOW TO DOWNLOAD A PRODUCT
VIII1 Download a product through the MyOcean Web Portal DirectgetfileService
You first need to register Please find below the registration stepshttpwwwmyoceaneuweb34-products-and-services-faqphp1Once registered the MyOcean FAQ httpwwwmyoceaneuweb34-products-and-services-faqwill guide you on How to download a product through the MyOcean Web Portal Directgetfile Service
Page 55
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
IX NEWS AND UPDATES
IX1 [Duacs] Operational news
To be kept informed on events occurring on the satellites and on the eventual interruption of the services of the DUACSprocessing system see the [Duacs] operational news on the Aviso websitehttpwwwavisooceanobscomendataoperational-newsindexhtml
IX2 Updates
To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtmlSince 2010 a complete reprocessing of all altimetry data (cumulated total of about 55 years of data) is available Themain changes introduced in the Duacs DT v300 reprocessed data set in SSALTODUACS reprocessed DT data setare listed herehttpwwwavisooceanobscomfileadmindocumentsdataduacsduacs_DT_2010_reprocessing_impactpdf
Page 56
PUM for Sea Level SLA Products Ref MYO-SL-PUM-008-001-005-v21
SEALEVEL__SLA_L3_OBSERVATIONS_008_00 Date 20120720Issue 31
IX NEWS AND UPDATES
IX1 [Duacs] Operational news
To be kept informed on events occurring on the satellites and on the eventual interruption of the services of the DUACSprocessing system see the [Duacs] operational news on the Aviso websitehttpwwwavisooceanobscomendataoperational-newsindexhtml
IX2 Updates
To have the information of the DUACS changes improvements and updates of the system please refer tohttpwwwavisooceanobscomendataproduct-informationduacspresentationupdatesindexhtmlSince 2010 a complete reprocessing of all altimetry data (cumulated total of about 55 years of data) is available Themain changes introduced in the Duacs DT v300 reprocessed data set in SSALTODUACS reprocessed DT data setare listed herehttpwwwavisooceanobscomfileadmindocumentsdataduacsduacs_DT_2010_reprocessing_impactpdf
Page 56
![No Slide Title · PDF file[Coleus sp. (Lamiaceae)], lantana [Lantana camara (Verbenaceae)], vinca [Vinca sp. (Apocynaceae)], and buckwheat [Fagopyrum esculentum ... No Slide Title](https://img.pdfslide.us/doc/110x75/5aaa44f47f8b9a81188dc30f/no-slide-title-coleus-sp-lamiaceae-lantana-lantana-camara-verbenaceae.jpg)
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