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Operational estimation of accumulated precipitation using satellite observation by Eumetsat H-SAF. Attilio Di Diodato National Centre for Aeronautical Meteorology and Climatology (CNMCA) Italy. - PowerPoint PPT Presentation
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Operational estimation of Operational estimation of accumulated precipitation accumulated precipitation
using satellite observation by using satellite observation by Eumetsat H-SAFEumetsat H-SAF
Attilio Di Diodato Attilio Di Diodato National Centre for Aeronautical National Centre for Aeronautical
Meteorology and Climatology Meteorology and Climatology (CNMCA)(CNMCA)
ItalyItaly
A lot of activities have been running at Centro Nazionale di Meteorologia e Climatologia Aeronautica (C.N.M.C.A.), the Air Force National Weather Centre, to reach the EUMETSAT H-SAF final target: development of algorithms, validation of results, implementation of operative procedure to supply the service and to monitor the service performances. The H-SAF precipitation products generating system is designed with high efficiency, redundancy in machine and data link, easy to control by H24 human operator system.
Italian Air Force - Meteorological Service has made many efforts to rapidly improve satellite receiving system, computing power, licensed software, engineering know-how, consuming nearly nothing of H-SAF
budget.
List of H-SAF precipitation products and indication of the Units responsible of algorithm development.List of H-SAF precipitation products and indication of the Units responsible of algorithm development.
CodeCode AcronymAcronym Product nameProduct name Responsible for Responsible for developmentdevelopment
H-01H-01 PR-OBS-1PR-OBS-1 Precipitation rate at ground by MW conical scannersPrecipitation rate at ground by MW conical scanners I.S.A.C.-C.N.R. ITALYI.S.A.C.-C.N.R. ITALY
H-02H-02 PR-OBS-2PR-OBS-2 Precipitation rate at ground by MW cross-track scannersPrecipitation rate at ground by MW cross-track scanners I.S.A.C.-C.N.R. ITALYI.S.A.C.-C.N.R. ITALY
H-03H-03 PR-OBS-3PR-OBS-3 Precipitation rate at ground by GEO/IR supported by Precipitation rate at ground by GEO/IR supported by LEO/MWLEO/MW I.S.A.C.-C.N.R. ITALYI.S.A.C.-C.N.R. ITALY
H-04H-04 PR-OBS-4PR-OBS-4 Precipitation rate at ground by LEO/MW supported by Precipitation rate at ground by LEO/MW supported by GEO/IRGEO/IR I.S.A.C.-C.N.R. ITALYI.S.A.C.-C.N.R. ITALY
H-05H-05 PR-OBS-5PR-OBS-5 Accumulated precipitation at ground by MW+IR and MW Accumulated precipitation at ground by MW+IR and MW onlyonly C.N.M.C.A. ITALYC.N.M.C.A. ITALY
H-06H-06 PR-ASS-1PR-ASS-1 Accumulated precipitation at ground computed by a NWPAccumulated precipitation at ground computed by a NWP C.N.M.C.A. ITALYC.N.M.C.A. ITALY
HSAF domain
PR-ASS-1 (COSMO-ME domain)
Next implementation of cluster HP with 128 compute nodes each forth-processor Intel Xeon will allow to cover the whole HSAF area with NWP COSMO ME.
computing capabilities more than 13,5 TFlops.
Super-Computing
Basic considerations on Basic considerations on time sampling error structure time sampling error structure
A preliminary study on precipitation time series recorded A preliminary study on precipitation time series recorded by a network of 76 automatic stations (perfect sampling by a network of 76 automatic stations (perfect sampling
time step: 15 minutes) showed the following results:time step: 15 minutes) showed the following results:
Sampling periods
24-h cumulated 3-h cumulated
Bias STD Bias STD
3 h -1.53% 142% -0.84% 167%
1 h -3.70% 66% -5.1% 74%
30 min 0.54% 37% -2.98% 43%
Basic considerations (2)Basic considerations (2)This time structure of precipitation field implies that
instantaneous sampling like that obtained by satellite remote sensing requires accomplishing short
time scanning.
H03 PR-OBS-3 Precipitation rate at ground by GEO/IR supported by LEO/MW
Integration of instantaneous Integration of instantaneous precipitationprecipitation
Aim: to obtain a value of accumulated precipitation Aim: to obtain a value of accumulated precipitation ((RS_acc ) ) starting from satellite estimation of starting from satellite estimation of instantaneous precipitation.instantaneous precipitation.
RS_acc=∫T RS (t) dt
The evaluation of the accumulated precipitation The evaluation of the accumulated precipitation achieved by the integration of any interpolation achieved by the integration of any interpolation function (linear, cubic, spline, etc..) is very function (linear, cubic, spline, etc..) is very similar.similar.
Integration of instantaneous Integration of instantaneous precipitationprecipitation
Assumption: rain rate does not change Assumption: rain rate does not change during the 15 minutes intervals.during the 15 minutes intervals.
The accumulated precipitation for each The accumulated precipitation for each time step is obtained with the rain rate time step is obtained with the rain rate value multiplied by the same time step. value multiplied by the same time step.
Total accumulated precipitation in 3, 6, Total accumulated precipitation in 3, 6, 12 and 24 hours is a sum up of each 12 and 24 hours is a sum up of each contribution.contribution.
Quality ControlQuality Control
Search of outliers every 15 minutes and Search of outliers every 15 minutes and on the differents accumulation periods, on the differents accumulation periods,
using climatological data (different using climatological data (different thresholds by season and geographic thresholds by season and geographic position) got from “Climate Atlas of position) got from “Climate Atlas of
Europe” led by Meteo France inside the Europe” led by Meteo France inside the project ECSN (European Climate Support project ECSN (European Climate Support
Network) of EUMETNET.Network) of EUMETNET.
PR-OBS 5 Version 1PR-OBS 5 Version 1The algorithm runs on the operational chain at CNMCA;The algorithm runs on the operational chain at CNMCA;
The products are available about fifteen minutes after the synoptic hours;The products are available about fifteen minutes after the synoptic hours;
If an input file is missing the algorithm cuts the value of the previous file. If an input file is missing the algorithm cuts the value of the previous file.
PR-OBS 5 Version 1PR-OBS 5 Version 1
The final result contains not negligible The final result contains not negligible random and bias error due to the random and bias error due to the indirect nature of the relationship indirect nature of the relationship between the observation and the between the observation and the
precipitation, the inadequate precipitation, the inadequate sampling and algorithm sampling and algorithm
imperfections. imperfections.
PR-OBS 5 Version 1PR-OBS 5 Version 1
Use of N-SAF cloud mask
Case study 23 July 2008Case study 23 July 2008
Case study 23 July 2008Case study 23 July 2008
Case study Case study 23 July 200823 July 2008
Version2: Use of rain gauge Version2: Use of rain gauge datadata
Ground measurements Ground measurements points (only synoptic points (only synoptic
stations on GTS network) stations on GTS network) are used for the are used for the
intercalibration between intercalibration between satellite estimations and satellite estimations and
real measurements due to real measurements due to timeliness and cal/val aims.timeliness and cal/val aims.
Use of rain gauge dataUse of rain gauge dataWe have to consider that rain gauge measurements are not
perfect, but they are affected by some bias error, due to:- Trace precipitation- Wetting loss- Evaporation loss- Wind-induced error
Pc=K(Pg + ΔPw + ΔPe) + ΔPt
For operational aims only wind-induced error has taken in account
Pc=K * Pg
where K = 1/ CR with CR= catch ratio
Use of rain gauge dataUse of rain gauge dataCR= exp(-0.041* vg)
Where vg = wind speed (m/s) at gauge height.
Logarithmic wind reduction equation (Garrat 1992) is used to convert the measured wind speed at certain height to the wind speed at gauge height.
vg = vH * log(h/ Z0)/log(H/ Z0)
where:• h = Height of the gauge orifice (m)• H = Height of the wind speed measurement (m) (usually 10 m for the
stations comply with WMO standards)• Z0 = Roughness length (m) (usually taken as 0.03m)• vH = Wind speed measured at height H
• At all rain gauge points the difference between ground measurements and satellite estimated precipitation is calculated.
• The values of satellite estimations on the rain gauge points are obtained by interpolation techiques
Increments computationIncrements computation
Version 2: spatial interpolation Version 2: spatial interpolation Use of Kriging method to interpolate the incrementsUse of Kriging method to interpolate the incrementsDistribution of differences over the gridded HSAF area is
prepared by using standard kriging method.
In each satellite grid point the final
product is the sum of satellite precipitation estimation and the
increment.
Version 2: final result Version 2: final result
Version 2: case studyVersion 2: case studyfinal result final result
ProblemsProblemsThis method reduces the bias error introduced
basically from IR observations by geostationary satellite, but we have other problems:
• Ground data are not available over sea areas;Ground data are not available over sea areas;• Observation network density is poor over some Observation network density is poor over some
regions;regions;• Precipitation information inside synop messages Precipitation information inside synop messages
are presents only every 6 hours;are presents only every 6 hours;• We don’t take in account the orography;We don’t take in account the orography;
Future developmentsFuture developmentsTo use the QPF by numerical model COSMO - ME as To use the QPF by numerical model COSMO - ME as
background field (OI).background field (OI). Model resolution: 7 KmModel resolution: 7 Km2 Runs per day (00 and 12 UTC)2 Runs per day (00 and 12 UTC)Output every 3 hours.Output every 3 hours.
Future developmentsFuture developments To improve the output of H03 algorithm To improve the output of H03 algorithm
(istantaneous precipitation), for example (istantaneous precipitation), for example through a clouds discrimination.through a clouds discrimination.
NEFODINA: a product to discriminate NEFODINA: a product to discriminate convective cloudsconvective clouds
An application for automatic detection of convective phenomena (NEFODINA) running operationally at Italian Met Service, which make use of three SEVIRI Channels (6, 7 and 10 )
Algorithms have been upgraded and improved with the contribution of the former Eumetsat fellowship (2003-2005, Dr. Puca) .
Early detection of convective clusters and active Nuclei identification.
Nowcasting of active nuclei evolving phase.
Running operationally over Mediterranean area.Running operationally over Mediterranean area.
Under testing over full diskUnder testing over full disk