the eldas system implementation and output production at météo-france gianpaolo balsamo, françois...
TRANSCRIPT
The ELDAS system implementation and output The ELDAS system implementation and output production at Météo-Franceproduction at Météo-France
Gianpaolo BALSAMO, François BOUYSSEL, Jöel NOILHANGianpaolo BALSAMO, François BOUYSSEL, Jöel NOILHAN
ELDAS ELDAS 2nd progress meetin2nd progress meeting – INM– INM MadridMadrid 10-11 december 200310-11 december 2003
T2m
t
Plan of the presentationPlan of the presentation
• ELDAS at Météo-FranceELDAS at Météo-France• The implementation of the system
– The NWP model (ARPEGE)– The coupling to atmosphere (Blending)– The data Assimilation technique (Simplified 2D-VAR)
• VALIDATION OF ECOCLIMAP & 2D-VARVALIDATION OF ECOCLIMAP & 2D-VAR• May-June 2003• Comparison of ALADIN and ARPEGE on June 2000• 2000/2003 comparison SWI and NDVI anomaly
• ELDAS EXPERIMENTSELDAS EXPERIMENTS• May-June 2000 without precipitation forcings
– ELDAS FORCINGSELDAS FORCINGS• Use of precipitation forcing• May-June 2000 with precipitation forcings
Variational surface analysisVariational surface analysisMahfouf (1991), Callies et al. (1998), Rhodin et al. (1999),Bouyssel et al. (2000), Hess (2001), Balsamo et al. (2003)
Formalism:
x is the control variables vectory is the observation vectorH is the observation operator
Continuous analysis
T2m
t
Wp
t
RH2m
t
6-h 12-h 18-h 0-h
The analysis is obtained by the minimization of the cost function J(x)
B is the background error covariance matrix
R is the observation error covariance matrix
= ½ (x – xb) T B-1 (x – xb) + ½(y – H(x))T R-1 (y – H(x))
J(x) = J b(x) + J o(x)
Advantages: Easier assim. asynop. obs.Extension on longer assim. Window (24-h)
ARPEGE: Global spectral stretched model20 to 200 km, 41 levels (1 hPa) , 6h assimilation cycle for Surface VariablesAtmospheric Blending (to avoid full re-analysis)
The NWP model and the ELDAS resolutionThe NWP model and the ELDAS resolution
Cycle 25t1_op3
Operational version of May 2003
(stretching factor 3.5 )
+6hfcst +6hfcst +6hfcst+6hfcstNew T2m, Rh2m, Ts, Tp, Ws
New Wp
The atmospheric couplingThe atmospheric coupling
• The atmospheric state is not re-analysed but a « Blending » technique is used to save atmospheric feedback of new land surface state
The land surface analysisThe land surface analysis
The atmospheric couplingThe atmospheric coupling
Restore Restore BlendingBlending
« + »« + »+6hfcst
Archive Atmospheric
Analyse
Atmospheric
guess
New Land Surface Analysis
New Land SurfaceAnalysis
Atmosphericguess
Archive Atmospheric
Analyse
New Land SurfaceAnalysis
Plan of the presentationPlan of the presentation
• ELDAS at Météo-FranceELDAS at Météo-France• The implementation of the system
– The NWP model (ARPEGE)– The coupling to atmosphere (Blending)– The data Assimilation technique (Simplified 2D-VAR)
• VALIDATION OF ECOCLIMAP & 2D-VARVALIDATION OF ECOCLIMAP & 2D-VAR• May-June 2003• Comparison of ALADIN and ARPEGE on June 2000• 2000/2003 comparison SWI and NDVI anomaly
• ELDAS EXPERIMENTSELDAS EXPERIMENTS• May-June 2000 without precipitation forcings
– ELDAS FORCINGSELDAS FORCINGS• Use of precipitation forcing• May-June 2000 with precipitation forcings
Improved Improved OI OI for Wpfor Wp
OpeOperational Physiographyrational Physiography
Improved Improved OIOI for Wp for Wp
EcoEcoclimap Physiographyclimap Physiography
Simplified Simplified 2D-VAR2D-VAR for Wp for Wp
OpeOperational Physiographyrational Physiography
Simplified Simplified 2D-VAR2D-VAR for Wp for Wp
EcoEcoclimap Physiographyclimap Physiography
The experimental frameThe experimental frame
1 month score evolution (1 month score evolution (T2m RH2m RMSE(P6-A))T2m RH2m RMSE(P6-A))
Using Backscattering Coefficient of TRMM Precipitation Radar
Seto et al. 2003 (submitted to J. of Geo. Res.)
Comparison of large scale soil moisture with satellite Comparison of large scale soil moisture with satellite derived soil moisture (TRMM) derived soil moisture (TRMM)
Plan of the presentationPlan of the presentation
• ELDAS at Météo-FranceELDAS at Météo-France• The implementation of the system
– The NWP model (ARPEGE)– The coupling to atmosphere (Blending)– The data Assimilation technique (Simplified 2D-VAR)
• VALIDATION OF ECOCLIMAP & 2D-VARVALIDATION OF ECOCLIMAP & 2D-VAR• May-June 2003• Comparison of ALADIN and ARPEGE on June 2000• 2000/2003 comparison SWI and NDVI anomaly
• ELDAS EXPERIMENTSELDAS EXPERIMENTS• May-June 2000 without precipitation forcings
– ELDAS FORCINGSELDAS FORCINGS• Use of precipitation forcing• May-June 2000 with precipitation forcings
Consistency of results over June 2000: I) ALADINConsistency of results over June 2000: I) ALADIN
Habets et al. (2003)Balsamo et al. (2003)
The results obtained with a 2D-VAR assimilation cycle within ALADIN LAM model provided a more realistic soil moisture field compared to the hydrological coupled model, SAFRAN-ISBA-MODCOU (forced by Prec., Rad.)
Consistency of results over June 2000: II) ARPEGEConsistency of results over June 2000: II) ARPEGE
Habets et al. (2003)
The same comparison is produced for the ELDAS soil moisture obtained with the ARPEGE model. An improved
ELDAS cycle (no precipitation)
June July
(CNES, 2003) Images SPOT/VEGETATION
Variation of NDVI 2003 within respect to 2002
+positive Index 2003/2002 +negative
Variation of SWI at 30 June 2003 compared to 30 June 2000 (ELDAS)
On the 30 June 2003 (exp. 2D-Var + Ecoclimap (Masson et al. 2003))
Drought of summer 2003: Comparison of soil moisture Drought of summer 2003: Comparison of soil moisture and NDVI anomalyand NDVI anomaly
Comparison of large scale soil moisture variation and Comparison of large scale soil moisture variation and NDVI anomalies over AfricaNDVI anomalies over Africa
Variation of SWI at 30 June 2003 compared to 30 June 2000 (ELDAS)
+6hfcst +6hfcst +6hfcst+6hfcstNew T2m, Rh2m,
Ts, Tp, Ws
New Wp
• In order to fully benefit of the 2D-VAR analysis and the Precipitation
readjustment the two steps are applied sequentially
The 2D-VAR cycle and the Precipitation readjustmentThe 2D-VAR cycle and the Precipitation readjustment
00UTC 06UTC 12UTC 18UTC 00UTC 06UTC00UTC 06UTC 12UTC 18UTC 00UTC 06UTC
Calculation of the 24-h ARPEGE accumulated precipitation and innovation
Usage of ELDAS Precipitation forcings: I stepUsage of ELDAS Precipitation forcings: I step
Wpa - Wp
fWpP24-h P24-hCan we set a coefficient as
ObservationObservation GuessGuess
ObsObs--GuessGuess
Usage of ELDAS Precipitation forcings: II stepUsage of ELDAS Precipitation forcings: II step
Usage of ELDAS Precipitation forcings: III stepUsage of ELDAS Precipitation forcings: III step
the two cycles without and with Precipitation readjustment are compared
Interpolation to final ELDAS gridInterpolation to final ELDAS grid
the nearest point has been used for MF/INM interpolation and it is planned to be used also for the final production since it avoids post processing and save self consistency of surface fields.
ConclusionsConclusions
Validation of simplified 2D-Var and ECOCLIMAP database for the summer 2003 with the ARPEGE GCM model
Comparison with results previously obtained with ALADIN-France over Europe.
Production (advance phase) of ELDAS output without and with precipitation forcing
Local archive at 1-h rate and preparation of interpolation/grib procedure for MARS archive.
Phase IPhase I
2D-VAR soil moisture analysis
on a 24-h window
24-h forecast Arpege GCM
Atmospheric Restore
to the analysis
Surface Update of the new 2D-VAR land
surface variable
2D-VAR soil moisture analysis
on a 24-h window
24-h forecast Arpege GCM
Atmospheric Restore
(or Blending)
Surface Update of the new 2D-VAR land
surface variable
Phase IIPhase II
Precipitation Obs. forcing
To doTo do Grib and Archiveon MARS
2D-VAR land surface analysis
on a 24-h window
24-h forecast Arpege GCM
Surface Update of the new 2D-VAR land
surface variable(s)
PerspectivPerspectiveses
Rad. Prec Obs. forcing
Heating rates Assimilation
B matrix Update
Atmospheric Restore
(or Blending)
? ?
? ?