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This paper describes several sensitivity studies carried out with the French global 4-D-Var system to check its ability to assimilate surface-sensitive observations over land from the Special Sensor Microwave Imager (SSM/I). As well as a sound knowledge of land-surface parameters, the assimilation of SSM/I observations requires effective rain-detection and bias-correction algorithms. Three sensitivity components are hence analyzed with a special emphasis on the land-surface emissivity at SSM/I frequencies estimated from satellite observations. Several rain algorithms were tested to reject cloudy/rainy observations over land, and the bias-correction scheme was adapted to improve its performance over land and sea surfaces. Once these problems have been outlined, a global 4-D-Var assimilation experiment which assimilates SSM/I observations over land surfaces was run and compared with a control experiment. The impact on forecast scores has been found to be globally positive. Nevertheless, the very high sensitivity of SSM/I to each of the three components presented in this study is characterized by opposite effects that, once clustered together, lead to some residual biases over land due to their combined effects.
Geoscience and Remote Sensing, IEEE Transactions on (Volume:49 , Issue: 4 )
Date of Publication: April 2011