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PRODUCT USER MANUAL
For Global Ocean Reanalysis Products
GLOBAL-REANALYSIS-PHY-001-025
Issue: 3.2
Contributors: Gilles Garric , Laurent Parent,
CMEMS version scope : Version 3.0
Approval Date :
PUM for Global Ocean Physical Reanalysis Products
GLOBAL_REANALYSIS_PHY_001_025,
Ref: CMEMS-GLO-PUM-001-025
Date : Jan 2017
Issue : 3.2
© EU Copernicus Marine Service – Public Page 2/ 25
CHANGE RECORD
Issue Date § Description of Change Author Validated By
0.0 23 may 2011
- Creation of the document with GLORYS Mercator Océan contribution
Nicolas Ferry
0.1 27 May 2011
all Merging with CMCC + ESSC contributions + various editing
E Dombrowsky, Simona Masina, Andrea Storto, Keith Haines, Maria Valdivieso
2.0 20 October 2011
all New template Nicolas Ferry, Laurent Parent, Bernard Barnier, Jean-Marc Molines, Simona Masina, Andrea Storto, Keith Haines, Maria Valdivieso
2.1 27 February 2012
all Update for V2.1: CMCC and U-Reading changes
Andrea Storto, Maria Valdivieso, Nicolas Ferry
2.2 14 January 2013
all Change product name and add Authenticated FTP download mechanism
Laurence Crosnier
2.3 14 February 2013
Remove DGF access from Met office DU
Alistair Sellar E. Dombrowsky
2.4 27 September 2013
all Update for V2.4: Production Unit changes
Nicolas Ferry, Laurent Parent, Bernard Barnier, Jean-Marc Molines, Simona Masina, Andrea Storto, Keith Haines, Maria Valdivieso
2.5 12
April
2014
Update for V2.5: add ECMWF products ORAP5.0
Hao Zuo, Magdalena Balmaseda Y. Drillet
L. Crosnier
PUM for Global Ocean Physical Reanalysis Products
GLOBAL_REANALYSIS_PHY_001_025,
Ref: CMEMS-GLO-PUM-001-025
Date : Jan 2017
Issue : 3.2
© EU Copernicus Marine Service – Public Page 3/ 25
2.6 17 Dec 2014
all Various updates Hao Zuo, Andrea Storto, Laurent Parent
L. Crosnier
2.7 May 1 2015
all Change format to fit CMEMS graphical rules
L. Crosnier
2.8 July 25 2015
Page 32
Update description of ORAP5.0
Hao Zuo L. Crosnier
2.9 January 2016
all Update for year 2014
Suppress references to products 001_004 and 001_010, no longer in V2
Suppress old references to MyOcean
Marie Drévillon Y Drillet
3.1 September 2016
Replace products 001_009 by 001_025.
Gilles Garric Y. Drillet
3.2 January 2017
all Remove products 001_011 and 001_017
Yann Drillet Y. Drillet
PUM for Global Ocean Physical Reanalysis Products
GLOBAL_REANALYSIS_PHY_001_025,
Ref: CMEMS-GLO-PUM-001-025
Date : Jan 2017
Issue : 3.2
© EU Copernicus Marine Service – Public Page 4/ 25
Table of contents
I INTRODUCTION ......................................................................................................................................... 6
I.1 Summary ...................................................................................................................................................... 6
I.2 History of changes ....................................................................................................................................... 7
II HOW TO DOWNLOAD A PRODUCT ......................................................................................................... 8
II.1 Download a product through the CMEMS Web Portal Subsetter Service ........................................... 8
II.2 Download a product through the CMEMS Web Portal FTP Service .................................................... 8
II.3 Download a product through the CMEMS Web Portal Direct Get File Service .................................. 8
III DESCRIPTION OF THE PRODUCT SPECIFICATION ...................................................................... 9
III.1 General Information ................................................................................................................................ 9
III.2 Details of datasets ................................................................................................................................... 10
III.3 Production Subsystem Description ....................................................................................................... 11
III.3.1 GLOBAL_REANALYSIS_PHY_001_025 ................................................................................ 11
III.3.2 Summary ..................................................................................................................................... 15
IV NOMENCLATURE OF FILES .................................................................................................................. 16
IV.1 Nomenclature of files when downloaded through the CMEMS Web Portal Subsetter Service ...... 16
IV.2 Nomenclature of files when downloaded through the CMEMS Web Portal Directgetfile or
Authenticated FTP Service ............................................................................................................................ 16
IV.3 Grid ......................................................................................................................................................... 17
IV.4 Domain coverage .................................................................................................................................... 17
IV.5 Vertical Levels ........................................................................................................................................ 17
IV.6 Other information: mean centre of Products, land mask value, missing value ................................ 18
V FILE FORMAT ........................................................................................................................................... 19
V.1 Netcdf ........................................................................................................................................................ 19
V.2 Structure and semantic of NetCDF maps files ....................................................................................... 19
V.3 Reading software ..................................................................................................................................... 25
GLOSSARY AND ABBREVIATIONS
CMEMS Copernicus Monitoring Environment Marine Service
MFC Monitoring and Forecasting Centre
Med Mediterranean
NetCDF Network Common Data Form
CF Climate Forecast (convention for NetCDF)
SSS Sea surface salinity.
SSC Sea surface currents
SSH Sea surface height
RMS Root mean square
SDN SeaDataNet (climatology)
CHL Chlorophyll
SLA Sea Level Anomalies
PC Production Center
PU Production Unit
Meridional Velocity West to East component of the horizontal velocity vector
Zonal Velocity South to North component of the horizontal velocity vector
ftp Protocol to download files
OpenDAP Open-Source Project for a Network Data Access Protocol. Protocol to download subset of data from a n-dimensional gridded dataset (ie: 4 dimensions: lon-lat,depth,time)
Subsetter CMEMS service tool to download a NetCDF file of a selected geographical box using values of longitude an latitude, and time range
Directgetfile CMEMS service tool (FTP like) to download a NetCDF file
PUM for Global Ocean Physical Reanalysis Products
GLOBAL_REANALYSIS_PHY_001_025
GLOBAL_REANALYSIS_PHYS_001_011 and 017
Ref: CMEMS-GLO-PUM-001-025-011-017
Date :September 2016
Issue : 2.9
© EU Copernicus Marine Service – Public Page 6/ 25
I INTRODUCTION
I.1 Summary
This document describes the global ocean reanalysis produced by the CMEMS Global Monitoring and Forecasting Centre, the data services that are available to access them and how to use the files and services.
GLOBAL-REANALYSIS-PHY-001-025 is the Global Ocean Physical Reanalysis products.
The goal of the CMEMS global ocean reanalysis is to provide an eddy permitting (1/4°) global ocean simulation, covering the recent period during which altimeter data are available (period starting with the launch of TOPEX POSEIDON and ERS-1 satellites early in the nineties), constrained by assimilation of observations and describing the space-time evolution of:
3D thermodynamic variables (T, S)
3D dynamic variables (U, V)
sea surface height
sea-ice features (concentration, thickness and horizontal velocity).
The reanalysis are built to be as close as possible to the observations (i.e. realistic) and in agreement with the model physics.
025 covers the period 1993 to 2015. The numerical products available for users are 3D daily mean averages and 2D daily mean fields.
The table below synthesizes the data set of the global ocean physical reanalysis product:
Product Name Product origin
Production Unit
Data set Kind of data set
GLOBAL-REANALYSIS-PHY-001-025
GLORYS2V4 GLO-MERCATOR-TOULOUSE-FR
dataset-global-reanalysis-phy-001-025-ran-fr-glorys2v4-monthly-t
dataset-global-reanalysis-phy-001-025-ran-fr-glorys2v4-monthly-s
dataset-global-reanalysis-phy-001-025-ran-fr-glorys2v4-monthly-u-v
dataset-global-reanalysis-phy-001-025-ran-fr-glorys2v4-monthly-ssh
reanalysis
dataset-global-reanalysis-phy-001-025-ran-fr-glorys2v4-monthly-ice
dataset-global-reanalysis-phy-001-025-ran-fr-glorys2v4-coordinates
dataset-global-reanalysis-phy-001-025-ran-fr-glorys2v4-daily-t
dataset-global-reanalysis-phy-001-025-ran-fr-glorys2v4-daily-s
dataset-global-reanalysis-phy-001-025-ran-fr-glorys2v4-daily-u-v
dataset-global-reanalysis-phy-001-025-ran-fr-glorys2v4-daily-ssh
dataset-global-reanalysis-phy-001-025-ran-fr-glorys2v4-daily-ice
I.2 History of changes
On January 2017, the following changes occurred:
GLOBAL_REANALYSIS_PHYS_001_011 and GLOBAL_REANALYSIS_PHYS_001_017 have suppressed, a new Global Reanalysis Ensemble Product (GREP) (GLOBAL_REANALYSIS_PHYS_001_026) based on several global physical reanalysis is now available in CMEMS
On April 8 2015, the following changes occurred:
GLOBAL_REANALYSIS_PHYS_001_009: Year 2013 is added; Mixed Layer Depth parameter is added; Daily mean surface fields (SST, SSH, 0m and 15m depth currents, sea ice variables) are added.
GLOBAL_REANALYSIS_PHYS_001_011: Year 2013 is added;
GLOBAL_REANALYSIS_PHYS_001_017: Year 2013 is added; 5-Daily mean surface velocity fields are added.
On January 2016, the following changes occurred:
GLOBAL_REANALYSIS_PHYS_001_009: Year 2014 is added;
On September 2016, the following changes occurred:
GLOBAL_REANALYSIS_PHY_001_025 replaces the GLOBAL REANALYSIS PHYS_001_009: the period covered is 1993-2015.
II HOW TO DOWNLOAD A PRODUCT
II.1 Download a product through the CMEMS Web Portal Subsetter Service
You first need to register. Please find below the registration steps:
http://marine.copernicus.eu/web/34-products-and-services-faq.php#1
Once registered, the CMEMS FAQ http://marine.copernicus.eu/web/34-products-and-services-
faq.php will guide you on How to download a product through the CMEMS Web Portal Subsetter Service.
Products 025 is available through Subsetter service.
II.2 Download a product through the CMEMS Web Portal FTP Service
You first need to register. Please find below the registration steps:
http://marine.copernicus.eu/web/34-products-and-services-faq.php#1
Once registered, the CMEMS FAQ http://marine.copernicus.eu/web/34-products-and-
services-faq.php will guide you on How to download a product through the CMEMS Web
Portal Authenticated FTP Service.
Products 025 is available through, CMEMS FTP Service.
II.3 Download a product through the CMEMS Web Portal Direct Get File Service
You first need to register. Please find below the registration steps:
http://marine.copernicus.eu/web/34-products-and-services-faq.php#1
Once registered, the CMEMS FAQ http://marine.copernicus.eu/web/34-products-and-
services-faq.php will guide you on How to download a product through the CMEMS Web
Portal Direct Get File Service.
Products 025 is available through Direct Get File service.
III DESCRIPTION OF THE PRODUCT SPECIFICATION
III.1 General Information
The main features of the global reanalysis product are summarized in the table below:
Products GLOBAL-REANALYSIS-PHY-001-025
Geographical coverage -180°E 180°E ; 77°S 90°N
Variables Temperature
Salinity
Sea Surface Height
Horizontal velocity (meridional and zonal component)
Sea Ice concentration
Sea Ice thickness
Sea ice velocity (meridional and zonal component)
Reanalysis GLOBAL-REANALYSIS-PHY-001-025 (GLORYS2V4),
Available time series From January 1993 to December 2015 for 001_025
Temporal resolution 3D monthly and daily average fields and daily 2D diagnostics of mixed layer depth for 001_025 (GLORYS2V4).
Target delivery time n.a.
Delivery mechanism Subsetter, DirectGetFile and Authenticated FTP for 001_025 (GLORYS2V4)
Horizontal resolution ORCA 0.25° grid
Number of vertical levels 001_025 (GLORYS2V4): 75 levels
Assimilated observations 001_025 (GLORYS2V4): altimetric sea level anomaly, temperature and salinity in situ profiles, sea-surface temperature observations, sea ice concentration
Format Netcdf CF1.0
Table 1: GLOBAL-REANALYSIS-PHYS-001-025 product
Detailed information on the systems and products are on CMEMS web site: marine.copernicus.eu .
III.2 Details of datasets
DATASETS VARIABLES AND UNIT
or GEOGRAPHICAL COVERAGE
NAME OF VARIABLES IN THE NETCDF FILE
or DOMAIN AREA
GLOBAL_REANALYSIS_PHY_001_025 (GLORYS2V4)
global-reanalysis-phy-001-025-ran-fr-glorys2-gridt
Temperature [K] votemper
global-reanalysis-phy-001-025-ran-fr-glorys2-grid2D
Sea Surface Height [m] sossheig
global-reanalysis-phy-001-025-ran-fr-glorys2-grids
Salinity [PSU] vosaline
global-reanalysis-phy-001-025-ran-fr-glorys2-gridu
Zonal velocity [m/s] vozocrtx
global-reanalysis-phy-001-025-ran-fr-glorys2-gridv
Meridional velocity [m/s] Vomecrty
global-reanalysis-phy-001-025-ran-fr-glorys2-icemod
Sea ice concentration [0;1], sea ice thickness [m], sea ice zonal velocity [m/s], sea ice meridional velocity [m/s]
Ileadfrac Iicethic Iicevelu Iicevelv
global-reanalysis-phy-001-025-ran-fr-glorys2-daily
Sea Surface Temperature [K] Sea Surface Salinity [psu] Sea Surface Height [m] Zonal Velocity (0m) [m/s] Meridional Velocity (0m) [m/s] Zonal Velocity (15m) [m/s] Meridional Velocity (15m) [m/s] Mixed Layer Depth (rho) [m] Mixed Layer Depth (T) [m] Mixed Layer Depth (turbocline) [m] Sea Ice Concentration [0;1] Sea Ice Thickness [m] Sea Ice Temperature [K] Sea Ice Zonal Velocity [m/s] Sea Ice Meridional Velocity [m/s]
votemper vosaline sossheig vozocrtx0m vomecrty0m vozocrtx15m vomecrty15m somxl010 somxlt02 somxlavt ileadfra iicethic iicetemp iicevelu iicevelv
Table 2: List of the datasets (column 1), of the variable for each dataset (column 2) and their names in the NetCDF files (column 3) for GLOBAL-REANALYSIS-PHY-001-025 product
III.3 Production Subsystem Description
III.3.1 GLOBAL_REANALYSIS_PHY_001_025
a. GLORYS2V4 reanalysis relies on three main components:
1. the ocean model (including the surface atmospheric boundary condition)
2. the data assimilation method
3. the assimilated observations
b. We review here these three components.
Ocean model:
- OGCM configuration:
The reanalysis system is based on the version 3.1 of NEMO (Nucelus for European Models of the Ocean) ocean model (Madec, 2008); the configuration uses the tripolar ORCA grid type (1442x1021 grid points) (Madec and Imbard, 1996) at ¼° horizontal resolution. (The three poles being located in Antarctica, Northern Asia and Northern Canada). The ¼ ° resolution of the ORCA grid type (ORCA025 hereafter) corresponds to 27 km at the equator, 22 km at Cape Hatteras (Gulf Stream area) and 12 km at high latitudes (Arctic Ocean & regional seas around Antarctica).
The vertical grid has 75 z-levels, with a resolution of 1 meter near the surface, 200 meters in the deepest ocean (> 3000m depth) and 24 levels with the upper 100m. .
The bathymetry used in the system is a combination of interpolated ETOPO1 (Amante and Eakins, 2009) and GEBCO8 (Becker et al., 2009) databases. ETOPO datasets are used in regions deeper than 300 m and GEBCO8 is used in regions shallower than 200 m with a linear interpolation in the 200 m – 300 m layer. The minimum depth in the model is set to 12 meters, except in the Bahamas region (~ 3 meters). Three islands have been added in the Torres Strait to diminish the transport and the Palk Strait (between India and Sri Lanka) has been opened with a 3m depth.
“Partial cells” parameterization (Adcroft et al., 1997) is chosen to represent the topographic floor as staircases but making the depth of the bottom cell variable and adjustable to the real depth of the ocean floor (Barnier et al., 2006).
The horizontal pressure gradient is represented by a free surface formulation in which high frequency gravity waves are filtered out (Roullet and Madec, 2000).
The advection of the tracers (temperature and salinity) is computed with a total variance diminishing (TVD) advection scheme (Lévy et al., 2001; Cravatte et al., 2007). A Laplacian lateral isopycnal diffusion on tracers is used (300m2.s-1at the Equator and decreasing poleward proportionally to the grid size ).
The momentum advection term is computed with the energy and enstrophy conserving scheme proposed by Arakawa and Lamb (1981).
An horizontal bi-harmonic viscosity for the lateral dissipation of momentum (−1×1011 m4 s−1 at the Equator and decreasing poleward as the cube of the grid size) is used. In this system, a Laplacian operator (2000 m2.s-1) is applied in the Ob and Ienissei estuaries to avoid local numerical instabilities.
The vertical mixing is parameterized according to a turbulent closure model (order 1.5) adapted by Blanke and Delecluse (1993).
The lateral friction condition is a partial-slip condition with a regionalisation of a no-slip condition (over the Mediterranean Sea).
Instead of being constant, the depth of light extinction is separated in Red-Green-Blue bands depending on the chlorophyll data distribution from mean monthly SeaWIFS climatology.
Barotropic mixing due to tidal currents in the semi-enclosed Indonesian throughflow region has been parameterized following Koch-Larrouy et al. (2008).
The reanalysis system uses the thermodynamic-dynamic sea-ice model LIM2 (Fichefet and Maqueda, 1997) with the Elastic-Viscous-Plastic rheology (Hunke and Dukowicz, 1997). The thermodynamics are based on the 2+1 (ice+snow) layers formulation.
- Surface forcing fields / corrections:
The reanalysis system is driven at the surface by the ERA-Interim reanalysis products (Dee et al., 2011), interpolated onto the ORCA025 grid using the Akima interpolation algorithm. Momentum and heat turbulent surface fluxes are computed from the Large and Yeager (2004) bulk formulae using the following set of atmospheric variables at 3H sampling: surface air temperature and surface humidity at 2 m height, mean sea level pressure and wind at 10 m height. Daily downward longwave and shortwave radiative fluxes and rainfall (solid + liquid) fluxes are also used in the surface heat and freshwater budgets. An analytical formulation (Bernie et al., 2005) is applied to the daily shortwave flux in order to reproduce an ideal diurnal cycle.
Due to large known biases in precipitations and radiative fluxes at the surface, a satellite-based large-scale corrections (Garric et al., 2011) is applied to the ERA-Interim fluxes. These corrections are applied (1) to the low-passed filtered ERA-Interim fluxes (80% amplitude attenuation at the synoptic scales) and (2) to the seasonal climatology. No corrections are applied at high latitudes (poleward 65°N and 60°S). Large-scale corrections of precipitations, resp. radiatives fluxes, at the surface are performed with the Passive Microwave Water Cycle (PMWC) (Hilburn, 2009), resp GEWEX SRB 3.1 (http: //eosweb.larc.nasa.gov/PRODOCS/srb/table srb.html), satellite data sets.
Also, specific corrections are applied at high latitudes to counteract kwown warm biases in ERA-Interim surface conditions. In the Arctic Ocean northward 80°N: surface air temperature is cooled by 2°C and 85% of air humidity is retained. Southward 60°S in the Southern Ocean: 80% of downward ERAinterim SW is retained and 110% of downward ERAinterim LW is applied.
The evaporation minus precipitation quantities (EmP hereafter) is set equal to zero at each model time-step. In addition, a global mean EmP seasonal cycle is imposed to the one observed by the GRACE geodetic mission. Despite the previous correction and updates, the freshwater budget (EmP) is far from being balanced. We add a trend of 1.4 mm/year to the runoffs in order to represent somehow the recent estimation of the global mass (glaciers, land water storage, Greenland & Antarctica) (Chambers et al., 2016)
The monthly seasonal climatology river runoff is now inferred from Dai et al. (2009).It is a reliable estimate for the world’s 925 largest rivers of continental freshwater discharge. This database uses new data, mostly from recent years, streamflow simulated by Community Land Model version 3 to fill the gaps, in all lands areas except Antarctica and Greenland. In addition, the runoff fluxes coming from Greenland and Antarctica ice sheets and glaciers melting is built with Altiberg icebergs database project (Tournadre et al., 2012). This complements the estimation of Silva et al. (2006) for Antarctica already present in the previous system. The total river runoff represents 1.3 Sv.
No global restoring strategy has been implemented in this system to sea surface salinity or the sea surface temperature. But a temperature and salinity 3D-restoring towards EN4 products (Good et al., 2013) is applied below 2000m and poleward 60°S with a representative time scale of 20 years. Also, a temperature and salinity restoring toward EN4 products has been added at Gibraltar and Bab-el-Mandeb straits.
- Initial Conditions:
The simulation started at rest the 4th December 1991, with prescribed temperature and salinity. Initial conditions for temperature and salinity based from EN4 (Good et al., 2013) are used. A method using a robust regression model applied to the EN4 monthly objective analysis, allowed to re-built the December 1991 water masses conditions.
Initial conditions for sea ice (ice concentration) were inferred from the NSDIC Bootstrap products for December 1991. The ice thickness has been issued from analytical relationships found between a mean (2002-2009) GLORYS1V1 January sea ice concentration and its ice thickness counterpart.
Time step and ramp up phase: the time step is set to 720 sec the first and second week of the run; then, the time step is set to 1440s all along the experiment. No data are assimilated during the first two weeks.
Data Assimilation method
The data assimilation method relies on a reduced order Kalman filter based on the SEEK formulation introduced by Pham et al. (1998). Here we present a short description of what we call Système d’Assimilation Mercator version 2 (SAM2).
An important feature of GLORYS2V4 reanalysis system (implemented also in the real-time global forecasting systems) is the analysis is performed at the middle of the 7-day assimilation cycle, and not at the end of the assimilation cycle.
The SEEK formulation requires knowledge of the forecast error covariance of the control vector. In GLORYS2V4, this vector is composed of the 2D barotropic height, the 3D temperature, salinity, zonal and meridional velocity fields and finally sea ice concentration. The forecast error covariance is based on the statistics of a collection of 3D ocean state anomalies (typically a few hundred) and is seasonally variable (i.e. fixed basis, seasonally variable). This approach is similar to the Ensemble optimal interpolation (EnOI) developed by Oke et al., (2008) which is an approximation to the EnKF that uses a stationary ensemble to define background error covariances. In our case, the anomalies are high pass filtered ocean states (Hanning filter, length cut-off frequency = 1/30 days-1) available over the 1993-2009 time period every 3 days. These ocean states come from a reference simulation but without data assimilation.
A 3D-VAR bias correction method has been implemented to correct large-scale temperature and salinity biases when enough observations are present.
These increments are applied with an Incremental Analysis Update (Bloom et al., 1996, Benkiran and Greiner, 2008). The IAU is a low-pass filter giving a smooth model integration.
We set to zero the global mean increment of the steric sea surface height.
Assimilated observations:
The assimilated data consist of satellite SST and SLA data, in situ temperature and salinity profiles, and sea ice concentration. The model innovation (observation minus model equivalent, y-Hx) is computed at appropriate time (FGAT, First Guess at Appropriate Time).
As stated in the model description section, the start time for GLORYS2V4 reanalysis is the 4th December 1992 at 00H UTC. The ocean model is integrated during the first two weeks without data assimilation. Then, all available observations are assimilated.
SLA: provided by CMEMS SLA TAC (CLS: Collecte Localisation Satellites):
SEALEVEL-GLO-SLA-L3-REP-OBSERVATIONS-008-001-b product
Here is a short summary of the DT altimetric data sets availability:
Jason-2 Jason-1
new (1)
Jason-1 GFO Envisat Envisat
new (2)
ERS-1(3)
ERS-2
Temporal
Time
availability:
beginning / end
2008/10
2009/02
2012/03
2002/04
2008/10
2000/01
2008/09
2002/10
2010/10
2010/10
2012/04
1992/10
2002/10
Topex new
(4)
Topex Cryosat2 AltiKa H2-YA2
Temporal
Time
availability:
beginning / end
2002/09
2005/10
1992/09
2002/04
2011/01 2013/03 2014/04
2016/01
Table: Time period during which altimetric data sets available
(1) Jason-1 new orbit: starting 2009/02
(2) Envisat new orbit: starting 2010/10
(3) There are no ERS-1 data between December 23, 1993 and April 10, 1994 (ERS-1 phase D – 2nd ice phase)
(4) T/P new orbit: starting 2002/09
The assimilation of SLA observations requires the knowledge of a mean sea surface height. This surface reference is an adjusted version of Mean Dynamic Topography (MDT hereafter) dataset. . We use the MDT based on the “CNES-CLS13” MDT with adjustment using high resolution analysis and with the Post Glacial Rebound. This product, referenced on the 20-year altimeter period, takes also into account the last version of GOCE geoid and is replacing the MDT named “CNES-CLS09” derived from observations (Rio et al., 2011) used in the previous system.
SST: The daily Reynolds 1/4° AVHRR-only daily SST version 2 product (see http://www.ncdc.noaa.gov/oa/climate/research/sst/oi-daily.php) is assimilated once at the date of the analysis (i.e. the day 4 at 24H00 of the assimilation cycle).
In Situ profiles (T, S): The CORA 4.1 in situ database provides by the CMEMS IS TAC (Szekely et al., 2015) is assimilated (http://www.coriolis.eu.org/Science/Data-and-Products). For 2014-2015 years, the delayed mode database was not available; the real-time database produced by Coriolis data center was used instead.
Sea Ice concentration: The IFREMER/CERSAT products (Ezraty et al., 2007) are assimilated once at the date of the analysis (i.e. the day 4 at 24H00 of the assimilation cycle).
Observation error:
Observation error includes both the instrumental error (Rme) and the model representativeness error (Rre). These errors are supposed to be uncorrelated and are modelled by diagonal matrices (i.e. the observation errors are mutually uncorrelated).
SST: An empirical error is used. It is function of the representativeness error Rre of in-situ measurements and equal to RSST = max (0,5°C, Rin_situ(T)).
SLA: The SLA observation error Rme (in variance) is specified according to the knowledge of instrumental features. We use a 2 cm error for JASON (with new orbit or not) and TOPEX-POSEIDON (with new orbit or not) and a 3.5 cm error for ERS-2, GFO and ENVISAT. In October 2010, the Envisat altimeter was brought to a lower orbit, which has led to a slight degradation of data quality (Ollivier and Faugere, 2010). In consequence, a 5.5 cm error is attributed to this altimeter (Envisat new). We use a 4 cm error for Cryosat-2, 2 cm error for Altika and 4 cm error for HY-2A.
Mean Dynamic Topography: A representativeness error for the MDT has been added to the SLA observation error. This error is 5 cm on average. Largest values (~10 cm) are located on shelves,
along the coast (model representativeness + observation error due to tides) and in the regions of sharp fronts (Gulf Stream, Kuroshio,...).
In situ profiles: The observation error of temperature and salinity profiles includes both the instrument error and the representativeness error by assuming that the model representativeness is a function of the geographical location and depth. For temperature, this error is dominated by the inaccuracy of the thermocline position given by the model and the data (profilers depth uncertainty can reach 5 m or 2 % of the depth). It ranges from about ~1°C at the surface to 0.1°C below 500m. The higher surface values correspond to mixed layer processes or thermocline motions that are not resolved by the model (filaments, internal gravity waves …). Contrary to the temperature, the salinity observation error can be very large in coastal areas due to run-off uncertainty. The halocline gradient is also weaker than the thermocline gradient, leading to a more homogeneous error on the vertical.
Sea Ice concentration: An empirical error is used. The error is 0.01 when the concentration is equal to 0, then a linear decreasing trend is applied from 0.25 (concentration equal to 0.01) to 0.05 (concentration equal to 1).
For all the bibliographic references cited in text, refer to the Quid document.
III.3.2 Summary
System name
domain resolution
Model version
Data Assimilation Assimilated
Observations
001_025
GLORYS2V4
Global, ¼°, 75 vertical levels
ORCA025 LIM2 EVP NEMO 3.0, 3-hourly atmospheric forcing from ERA-Interim, including SW+LW+PRECIP corrections Date of start: 4
th
December 1991. Model spin-up: 2 weeks
SAM2 (SEEK Kernel) + FGAT + IAU and bias correction
Reynolds 0.25° AVHRR-only-SST, DT SLA from all altimetric satellites, in situ T, S profiles from CORIOLIS CORAv4.1 data base, CERSAT Sea Ice Concentration
Table summarizing the reanalyse features.
IV NOMENCLATURE OF FILES
The nomenclature of the downloaded files differs on the basis of the chosen download mechanism Subsetter, Directgetfile or Authenticated FTP service.
IV.1 Nomenclature of files when downloaded through the CMEMS Web Portal Subsetter Service
GLOBAL_ANALYSIS_PHY_001_025 file nomenclature when downloaded through the Subsetter functionality (TDS) is based on product dataset name (see Table2, column1) and a numerical reference related to each product request date on the server.
The scheme is:
datasetname-nnnnnnnnnnnnn.nc
where :
.datasetname is a character string within one of the dataset from Table2.
. nnnnnnnnnnnnn: 13 digit integer linked to the request date.
.nc: standard NetCDF filename extension.
Example:
dataset-global-reanalysis-phy-001-025-ran-fr-glorys2v4-daily_1484236987711.nc
IV.2 Nomenclature of files when downloaded through the CMEMS Web Portal Directgetfile or Authenticated FTP Service
GLOBAL_REANALYSIS_PHY_001_025 product is available through the CMEMS Directgetfile.
GLOBAL_REANALYSIS_PHYS_001_025 product is also available through the Authenticated FTP downloading functionalities.
When downloading product via Directgetfile or Authenticated FTP you get data in ZIP archive format with a specific nomenclature. When ZIP archive is uncompressed, files are provided with the native nomenclature.
These two nomenclatures are described below with an example for GLOBAL_REANALYSIS_PHY_001_025 (GLORYS2V4):
File downloaded from directgetfile or Authenticated FTP:
The scheme is:
http---purl.org-mercator-ontology-product-database-datasetname_nnnnnnnnnnnnn.zip
Where:
datasetname is a character string within one of the dataset from Table2.
. nnnnnnnnnnnnn: 13 digit integer linked to the request date.
.zip: ZIP Archive filename extension.
File nomenclature after uncompressing ZIP archive :
The scheme is:
mercatorglorys2v4_gl4_mean_yyyymmd_RYYYYMMDD.nc
Where:
- yyyymmd: field daily mean central date, on YYYYMMDD format
- YYYYMMDD : creation date of the file
- .nc: standard NetCDF filename extension.
IV.3 Grid
GLOBAL-REANALYSIS-PHY-001-025: Native model outputs are interpolated on standard grids at ¼°.
IV.4 Domain coverage
GLOBAL-REANALYSIS-PHY-001-025:
Domain Boundaries Projection Resolution Grid size
Image
Global 180°W-180°E
89°S-90°N Regular
1/4°
1440*681
Regular projection is plane chart
- Longitude and latitude step is constant
- Longitude step is equal to latitude step
- Longitude and latitude coordinates are 1D
array
IV.5 Vertical Levels
For GLOBAL-REANALYSIS-PHY-001-025 (GLORYS2V4),:
The vertical grid consists of 75 levels: the thickness of the surface layer is about 1 meter, is close to 10 m at 100 m depth and increases up to 200 meters at the bottom (near 6000m):
0.50, 1.55, 2.66, 3.85, 5.14, 6.54, 8.09, 9.82, 11.77, 13.99, 16.52, 19.42, 22.75, 26.55, 30.87, 35.74, 41.18, 47.21, 53.85, 61.11, 69.02, 77.61, 86.92, 97.04, 108.0, 120.00, 133.07, 147.40, 163.16, 180.54, 199.79, 221.14, 244.89, 271.35, 300.88, 333.86, 370.68, 411.79, 457.62, 508.63, 565.29, 628.02, 697.25, 773.36, 856.67, 947.44, 1045.85, 1151.99, 1265.86, 1387.37, 1516.36, 1652.56, 1795.67, 1945.29, 2101.02, 2262.42, 2429.02, 2600.38, 2776.03, 2955.57, 3138.56, 3324.64, 3513.44, 3704.65, 3897.98, 4093.15, 4289.95, 4488.15, 4687.58, 4888.07, 5089.47, 5291.68, 5494.57, 5698.06, 5902.05
IV.6 Other information: mean centre of Products, land mask value, missing value
GLOBAL-REANALYSIS-PHY-001-025 product is daily mean fields centered on the middle of the day.
V FILE FORMAT
V.1 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 defines a machine-independent format for representing scientific data. Together, the interface, library, and format support the creation, access, and sharing of scientific data. The NetCDF software was developed at the Unidata Program Center in Boulder, Colorado. The NetCDF libraries define a machine-independent format for representing scientific data.
Please see Unidata NetCDF pages for more information, and to retrieve NetCDF software package.
NetCDF data is:
* Self-Describing. A NetCDF file includes information about the data it contains.
* Architecture-independent. A NetCDF file is represented in a form that can be accessed by computers with different ways of storing integers, characters, and floating-point numbers.
* Direct-access. A small subset of a large dataset may be accessed efficiently, without first reading through all the preceding data.
* Appendable. Data can be appended to a NetCDF dataset along one dimension without copying the dataset or redefining its structure. The structure of a NetCDF dataset can be changed, though this sometimes causes the dataset to be copied.
* Sharable. One writer and multiple readers may simultaneously access the same NetCDF file.
V.2 Structure and semantic of NetCDF maps files
For GLOBAL_REANALYSIS_PHY_001_025 (GLORYS2V4):
netcdf mercatorglorys2v4_gl4_mean_yyyymmdd_RYYYYMMDD.nc
dimensions:
longitude = 1440 ;
latitude = 681 ;
depth = 75 ;
time = UNLIMITED ; // (1 currently)
variables:
float longitude(longitude) ;
longitude:valid_min = -180.f ;
longitude:valid_max = 179.75f ;
longitude:step = 0.25f ;
longitude:units = "degrees_east" ;
longitude:unit_long = "Degrees East" ;
longitude:long_name = "Longitude" ;
longitude:standard_name = "longitude" ;
longitude:axis = "X" ;
float latitude(latitude) ;
latitude:valid_min = -80.f ;
latitude:valid_max = 90.f ;
latitude:step = 0.25f ;
latitude:units = "degrees_north" ;
latitude:unit_long = "Degrees North" ;
latitude:long_name = "Latitude" ;
latitude:standard_name = "latitude" ;
latitude:axis = "Y" ;
float depth(depth) ;
depth:valid_min = 0.50576f ;
depth:valid_max = 5902.058f ;
depth:units = "m" ;
depth:positive = "down" ;
depth:unit_long = "Meters" ;
depth:long_name = "Depth" ;
depth:standard_name = "depth" ;
depth:axis = "Z" ;
float time(time) ;
time:long_name = "Time (hours since 1950-01-01)" ;
time:standard_name = "time" ;
time:calendar = "gregorian" ;
time:units = "hours since 1950-01-01 00:00:00" ;
time:axis = "T" ;
short mlp(time, latitude, longitude) ;
mlp:long_name = "Density ocean mixed layer thickness" ;
mlp:standard_name = "ocean_mixed_layer_thickness_defined_by_sigma_theta" ;
mlp:units = "m" ;
mlp:unit_long = "Meters" ;
mlp:add_offset = -0.152592554688454 ;
mlp:scale_factor = 0.152592554688454 ;
mlp:_FillValue = -32767s ;
mlp:valid_min = 1s ;
mlp:valid_max = 4875s ;
mlp:cell_methods = "area: mean" ;
short ssh(time, latitude, longitude) ;
ssh:long_name = "Sea surface height" ;
ssh:standard_name = "sea_surface_height_above_geoid" ;
ssh:units = "m" ;
ssh:unit_long = "Meters" ;
ssh:add_offset = 0. ;
ssh:scale_factor = 0.000305185094475746 ;
ssh:_FillValue = -32767s ;
ssh:valid_min = -6185s ;
ssh:valid_max = 5544s ;
ssh:cell_methods = "area: mean" ;
short bottomT(time, latitude, longitude) ;
bottomT:long_name = "Sea floor potential temperature" ;
bottomT:standard_name = "sea_water_potential_temperature_at_sea_floor" ;
bottomT:units = "K" ;
bottomT:unit_long = "Kelvin" ;
bottomT:_FillValue = -32767s ;
bottomT:add_offset = 294.15 ;
bottomT:scale_factor = 0.000732444226741791 ;
bottomT:valid_min = -32766s ;
bottomT:valid_max = 20228s ;
bottomT:cell_methods = "area: mean" ;
short hice(time, latitude, longitude) ;
hice:long_name = "Sea ice thickness" ;
hice:standard_name = "sea_ice_thickness" ;
hice:units = "m" ;
hice:unit_long = "Meters" ;
hice:add_offset = -0.000762962736189365 ;
hice:scale_factor = 0.000762962736189365 ;
hice:_FillValue = -32767s ;
hice:valid_min = 1s ;
hice:valid_max = 7792s ;
hice:cell_methods = "area: mean where sea_ice" ;
short fice(time, latitude, longitude) ;
fice:long_name = "Ice concentration" ;
fice:standard_name = "sea_ice_area_fraction" ;
fice:units = "1" ;
fice:unit_long = "Fraction" ;
fice:add_offset = -3.81481368094683e-05 ;
fice:scale_factor = 3.81481368094683e-05 ;
fice:_FillValue = -32767s ;
fice:valid_min = 1s ;
fice:valid_max = 26495s ;
fice:cell_methods = "area: mean where sea_ice" ;
short uice(time, latitude, longitude) ;
uice:long_name = "Sea ice eastward velocity" ;
uice:standard_name = "eastward_sea_ice_velocity" ;
uice:units = "m s-1" ;
uice:unit_long = "Meters per second" ;
uice:add_offset = 0. ;
uice:scale_factor = 3.05185094475746e-05 ;
uice:_FillValue = -32767s ;
uice:valid_min = -18601s ;
uice:valid_max = 16685s ;
uice:cell_methods = "area: mean where sea_ice" ;
short vice(time, latitude, longitude) ;
vice:long_name = "Sea ice northward velocity" ;
vice:standard_name = "northward_sea_ice_velocity" ;
vice:units = "m s-1" ;
vice:unit_long = "Meters per second" ;
vice:add_offset = 0. ;
vice:scale_factor = 3.05185094475746e-05 ;
vice:_FillValue = -32767s ;
vice:valid_min = -15026s ;
vice:valid_max = 14630s ;
vice:cell_methods = "area: mean where sea_ice" ;
short temperature(time, depth, latitude, longitude) ;
temperature:long_name = "Temperature" ;
temperature:standard_name = "sea_water_potential_temperature" ;
temperature:units = "K" ;
temperature:unit_long = "Kelvin" ;
temperature:_FillValue = -32767s ;
temperature:add_offset = 294.15 ;
temperature:scale_factor = 0.000732444226741791 ;
temperature:valid_min = -32766s ;
temperature:valid_max = 20210s ;
temperature:cell_methods = "area: mean" ;
short salinity(time, depth, latitude, longitude) ;
salinity:long_name = "Salinity" ;
salinity:standard_name = "sea_water_salinity" ;
salinity:units = "1e-3" ;
salinity:unit_long = "Practical Salinity Unit" ;
salinity:_FillValue = -32767s ;
salinity:add_offset = -0.00152592547237873 ;
salinity:scale_factor = 0.00152592547237873 ;
salinity:valid_min = 2s ;
salinity:valid_max = 27262s ;
salinity:cell_methods = "area: mean" ;
short u(time, depth, latitude, longitude) ;
u:long_name = "Eastward velocity" ;
u:standard_name = "eastward_sea_water_velocity" ;
u:units = "m s-1" ;
u:unit_long = "Meters per second" ;
u:_FillValue = -32767s ;
u:add_offset = 0. ;
u:scale_factor = 0.000610370188951492 ;
u:valid_min = -3240s ;
u:valid_max = 3519s ;
u:cell_methods = "area: mean" ;
short v(time, depth, latitude, longitude) ;
v:long_name = "Northward velocity" ;
v:standard_name = "northward_sea_water_velocity" ;
v:units = "m s-1" ;
v:unit_long = "Meters per second" ;
v:_FillValue = -32767s ;
v:add_offset = 0. ;
v:scale_factor = 0.000610370188951492 ;
v:valid_min = -3145s ;
v:valid_max = 3353s ;
v:cell_methods = "area: mean" ;
// global attributes:
:title = "daily mean fields from Global Ocean Physics Analysis and Forecast updated Daily" ;
:easting = "longitude" ;
:northing = "latitude" ;
:history = "2016/09/08 12:52:39 MERCATOR OCEAN Netcdf creation" ;
:source = "MERCATOR GLORYS2V4" ;
:institution = "MERCATOR OCEAN" ;
:references = "http://www.mercator-ocean.fr" ;
:comment = "CMEMS product" ;
:Conventions = "CF-1.4" ;
:domain_name = "GL4" ;
:field_type = "mean" ;
:field_date = "2010-09-29 00:00:00" ;
:field_julian_date = 22186.f ;
:julian_day_unit = "days since 1950-01-01 00:00:00" ;
:forecast_range = "0-day_forecast" ;
:forecast_type = "nowcast" ;
:bulletin_date = "2010-10-06 00:00:00" ;
:bulletin_type = "operational" ;
:longitude_min = -180.f ;
:longitude_max = 179.75f ;
:latitude_min = -80.f ;
:latitude_max = 90.f ;
:z_min = 0.50576f ;
:z_max = 5902.058f ;
V.3 Reading software
NetCDF data can be browsed and used through a number of software, like:
ncBrowse: http://www.epic.noaa.gov/java/ncBrowse/, NetCDF Operator (NCO): http://nco.sourceforge.net/
IDL, Matlab, GMT, Ferret…
Useful information on UNIDATA: http://www.unidata.ucar.edu/software/netcdf/
Remember: Real_Value = (Display_Value X scale_factor) + add_offset
