The ELDAS system implementation and output production at Météo-France Gianpaolo BALSAMO, François BOUYSSEL, Jöel NOILHAN ELDAS 2nd progress meetin – INM.

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Presentation transcript:

The ELDAS system implementation and output production at Météo-France Gianpaolo BALSAMO, François BOUYSSEL, Jöel NOILHAN ELDAS 2nd progress meetin – INM Madrid december 2003 ELDAS 2nd progress meeting – INM Madrid december 2003 T 2m t

Plan 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 /2003 comparison SWI and NDVI anomaly ELDAS EXPERIMENTSELDAS EXPERIMENTS May-June 2000 without precipitation forcings –ELDAS FORCINGS Use of precipitation forcing May-June 2000 with precipitation forcings

Variational surface analysis Mahfouf (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 vector y is the observation vector H is the observation operator Continuous analysis T 2m t WpWp t RH 2m 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 – x b ) T B -1 (x – x b ) + 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 model 20 to 200 km, 41 levels (1 hPa), 6h assimilation cycle for Surface Variables Atmospheric Blending (to avoid full re-analysis) The NWP model and the ELDAS resolution Cycle 25t1_op3 Operational version of May 2003 (stretching factor 3.5 )

+6hfcst New T2m, Rh2m, Ts, Tp, Ws New Wp The 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 analysis

The atmospheric coupling Restore Blending « + » +6hfcst Archive Atmospheric Analyse Atmospheric guess New Land Surface Analysis Atmospheric guess Archive Atmospheric Analyse New Land Surface Analysis

Plan 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 /2003 comparison SWI and NDVI anomaly ELDAS EXPERIMENTSELDAS EXPERIMENTS May-June 2000 without precipitation forcings –ELDAS FORCINGS Use of precipitation forcing May-June 2000 with precipitation forcings

Improved OI for Wp Operational Physiography Improved OI for Wp Ecoclimap Physiography Simplified 2D-VAR for Wp Operational Physiography Simplified 2D-VAR for Wp Ecoclimap Physiography The experimental frame

1 month score evolution ( T2m RH2m RMSE(P6-A))

Using Backscattering Coefficient of TRMM Precipitation Radar Seto et al (submitted to J. of Geo. Res.) Comparison of large scale soil moisture with satellite derived soil moisture (TRMM)

Plan 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 /2003 comparison SWI and NDVI anomaly ELDAS EXPERIMENTSELDAS EXPERIMENTS May-June 2000 without precipitation forcings –ELDAS FORCINGS Use of precipitation forcing May-June 2000 with precipitation forcings

Consistency 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) 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)

JuneJuly (CNES, 2003) Images SPOT/VEGETATION Variation of NDVI 2003 within respect to 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 )) Drought of summer 2003: Comparison of soil moisture and NDVI anomaly

Comparison of large scale soil moisture variation and NDVI anomalies over Africa Variation of SWI at 30 June 2003 compared to 30 June 2000 (ELDAS)

+6hfcst New 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 readjustment 00UTC 06UTC 12UTC 18UTC 00UTC 06UTC Calculation of the 24-h ARPEGE accumulated precipitation and innovation

Usage of ELDAS Precipitation forcings: I step W p a - W p f  WpP24-h  P 24-h Can we set a coefficient as

Observation Guess Obs-Guess Usage of ELDAS Precipitation forcings: II step

Usage of ELDAS Precipitation forcings: III step the two cycles without and with Precipitation readjustment are compared

Interpolation 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.

Conclusions  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 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 II Precipitation Obs. forcing To do Grib and Archive on 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) Perspectives Rad. Prec Obs. forcing Heating rates Assimilation B matrix Update Atmospheric Restore (or Blending) ? ?