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Communication incl. Poster: BibTeX citation key:  Gerard
Gérard, E., Karbou, F., Rabier, F., Lafore, J.-P., Redelsperger, J.-L. & Bock, O. 2009. The use of satellite microwave observations over land to improve the hydrological cycle over the Tropics. Work presented at Third International AMMA Conference, July 20—24, at Ouagadougou, Burkina Faso.
Added by: roussot 2009-10-19 20:56:41
Categories: Atmospheric processes, Water cycle, Weather to Climatic modelling and forecasting
Creators: Bock, Gérard, Karbou, Lafore, Rabier, Redelsperger
Publisher: African Monsoon Multidisciplinary Analyses (Ouagadougou, Burkina Faso)
Collection: Third International AMMA Conference

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Popularity index:  50.26%
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Satellite microwave measurements have large atmospheric and surface information contents and are known to be very useful for Numerical Weather Prediction. However these observations are still not fully used over land because of non negligeable uncertainties about land emissivity and surface temperature. These data over land have a great potential of improving the model features, which is of particular interest for the AMMA community. New methods for land emissivity and surface temperature modelling anchored on satellite microwave observations have been proposed. One of these methods has been selected for this study. It consists in dynamically adjusting the emissivity for each atmospheric situation for a selection of surface channels and allocating this estimate to remaining surface and sounding channels. Such a method has been found very helpful to extend the use of observations measured by AMSUA, AMSUB/MHS and SSM/I instruments to land surfaces in the French global model.
We will first give a description of the land emissivity method. Then an overview of assimilation and forecast experiments using these satellite microwave observations in the global model during the AMMA 2006 summer period will be presented and results commented. A particular focus will be made on the hydrological cycle in the Tropics. The use of these data dramatically changes the model behaviour in terms of water vapour in the analysis as well as precipitation in the forecast. Amongst others, issues related to the observation quality control and the bias correction will be examined. Evaluation of the analysis total column water vapour with respect to AMMA GPS data will be presented.
Added by: roussot