Data assimilation experiments for AMMA using radiosonde observations
Data assimilation experiments for AMMA, using radiosonde observations and satellite observations over land F. Rabier, C. Faccani, N. Fourrié, F. Karbou, J-P Lafore, P. Moll, M. Nuret, J-L Redelsperger Météo-France and CNRS, Toulouse, France A. Agusti-Panareda ECMWF, Reading F. Hdidou Direction de la Météorologie Nationale, Morocco O. Bock IGN, France
AMMA: The African Monsoon Multidisciplinary Analysis Better understand the mechanisms of the African monsoon and prevent dramatic situations (Redelsperger et al, 2006) Enhanced observations over West Africa in 2006 In particular, major effort to enhance the radiosonde network (Parker et al, 2008)
Impact of using the AMMA radiosonde dataset New radiosonde stations Enhanced time sampling AMMA database: additional data which were not received in real time + enhanced vertical resolution Bias correction for RH developed at ECMWF (Agusti-Panareda et al) Data impact studies With various datasets, With and without RH bias correction Number of soundings provided on GTS in 2006 and 2005 Period: 15 July- 15 September, 0 and 12 UTC
Validation of Total Column Water Vapour analyses: Comparison with GPS data at Tombouctou NO AMMA CNTR: data from GTS AMMABC AMMA: from the AMMA database AMMABC: AMMA + bias correction Pre. AMMA: with a 2005 network NOAMMA: No Radiosonde data GPS: Observations Very poor performance of NO AMMA Best performance of AMMABC
Impact on monthly mean precipitation over Africa AMMABC: AMMA + bias correction Pre. AMMA: with a 2005 network NOAMMA: No Radiosonde data CPC: Observations Very poor performance of NO AMMA Best performance of AMMABC Similar results obtained at ECMWF Monthly averaged RR better with bias correction Faccani et al, 2009
Impact on quantitative prediction of precipitation over Africa CNTR: data from GTS AMMA: from the AMMA database AMMABC: AMMA + bias correction Pre. AMMA: with a 2005 network Higher scores for AMMABC NOAMMA: No Radiosonde data Lowest scores for NO AMMA
Downstream impact Impact on geopotential at 500 h. Pa, averaged over 45 days 48 hr forecasts: AMMABC vs PREAMMA
8 Impact of assimilating low-level humidity observations over land on the African Monsoon during AMMA Improved emissivity parametrisation • Better simulation by the Radiative Transfer Model of the low-level peaking channels • Possibility to assimilate more channels • Experiments performed during AMMA in 2006 Control Density of assimilated AMSU-B Ch 5 during August 2006 Experiment
Assimilation of humidity observations over land Assimilation of AMSU-B Ch 2 (150 GHz) & Ch 5 (183± 7 GHz) over land, 45 days TCWV (EXP) - TCWV (CTL) Karbou et al, 2009
Summary of AMMA results Humidity bias correction (from ECMWF) over the AMMA region is beneficial Significant positive impact of additional AMMA RS data on the humidity analysis and on precipitation over Africa Positive downstream impact over Europe Using more satellite data over land also has a large positive impact in the Tropics More results to come in a AMMA special issue Weather and Forecasting
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