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Meike Kühnlein, Boris Thies, Thomas Nauß, and Jörg Bendix

1. Introduction Precipitation affects all aspects of human life. However, despite its great importance, the correct spatiotemporal detection and quantification of this key factor of the global water cycle is still associated with large uncertainties. This is mainly due to the high spatial and temporal variability of precipitation distribution. In this context, optical sensors aboard geostationary weather satellites provide information about rainfall distribution in a high spatial and temporal

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J. J. Shi, W-K. Tao, T. Matsui, R. Cifelli, A. Hou, S. Lang, A. Tokay, N-Y. Wang, C. Peters-Lidard, G. Skofronick-Jackson, S. Rutledge, and W. Petersen

estimation algorithms ( Petersen et al. 2007 ). In this study, the Weather Research and Forecasting model (WRF) with the Goddard microphysics scheme was utilized. WRF has also been coupled with multisensor, multifrequency satellite simulators in the Goddard Satellite Data Simulation Unit (SDSU) for model evaluation and GPM algorithm support. The goal is to combine radar, satellite, and in situ measurements in addition to model data to improve precipitation measurement. The Goddard cloud microphysics

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Rémy Roca, Philippe Chambon, Isabelle Jobard, Pierre-Emmanuel Kirstetter, Marielle Gosset, and Jean Claude Bergès

late June and characterized by a northward jump of the ITCZ ( Sultan and Janicot 2003 ) showing a strong modification of the rain regimes and synoptic-scale variability ( Gu and Adler 2004 ). The day-to-day variability of rainfall alternates between active and inactive phases at the intraseasonal scale with modes at 10–25 days and around 40–50 days, respectively ( Sultan et al. 2003 ). At shorter synoptic time scales, variability of the rainfall is also observed and linked to tropical wave dynamics

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