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Feyera A. Hirpa, Mekonnen Gebremichael, and Thomas Hopson

1. Introduction The availability of high-resolution satellite precipitation products has made them very attractive for hydrological applications in regions that have less-dense and less-consistent ground-based measurements. Some of these products are available in (near) real time, making them suitable for flood-forecasting applications. The concept behind these high-resolution satellite precipitation algorithms is to combine information from the more accurate (but infrequent) microwave (MW

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Tufa Dinku, Pietro Ceccato, Keith Cressman, and Stephen J. Connor

:// ). These maps are based on the National Oceanic and Atmospheric Administration (NOAA)/Climate Prediction Center (CPC) morphing technique (CMORPH; Joyce et al. 2004 ) rainfall estimates. There are many satellite rainfall products available over the region of interest. However, the accuracy of satellite rainfall estimates has not been assessed over most of this region. Thus, validation of satellite rainfall products over this region would be an important contribution to FAO DLIS. It would also be an

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Axel Andersson, Christian Klepp, Karsten Fennig, Stephan Bakan, Hartmut Grassl, and Jörg Schulz

, blending and morphing techniques have been developed to combine different satellite and model data with the SSM/I time series. Generally these datasets fall into two categories providing either surface fluxes or precipitation estimates. Prominent surface flux products are the Goddard Satellite-Based Surface Turbulent Fluxes, version 2 (GSSTF2; Chou et al. 2003 ), the Japanese Ocean Flux Datasets with the Use of Remote Sensing Observations (J-OFURO 2; Kubota and Tomita 2007 ), the objectively analyzed

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