Satellite-based rainfall estimations are obtained from either microwave or infrared techniques but all these techniques have their own inherent limitations. Microwave radiances have a good physical connection with rainrate but the microwave observations from a single low-orbit satellite, (one or at most two images per day) are inadequate for the detection of rapidly changing precipitation distributions. Infrared images from geosynchronous-orbit satellites have high spatial and high temporal resolutions, but they do not have a direct physical connection with the instantaneous rainrate. However, infrared techniques provide reliable estimation of the rainfall amount accumulated during long time periods and averaged over large areas. To overcome the limitations of these techniques, different methods for estimating precipitation at various time and space scales, which combine low-orbit microwave and geostationary infrared satellite data, are developed. The Rain and Cloud Classification (RACC) method, based on an automatic classification procedure, is described; the method is applied to two case- studies corresponding to different climatic regions: tropical land in West Africa and sub-tropical Japan and surrounding oceanic regions, for which the infrared data from geostationary satellites (Météosat, GMS) and the microwave data from the SSM/I radiometer on board a U.S. DMSP polar satellite are used. The comparisons of monthly and daily rainfall estimates with surface rainfall validation data are presented. The results show that the combined microwave-infrared technique performed well.
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- Combination of Satellite Microwave and Infrared Measurements for Rainfall Estimation
- Springer Berlin Heidelberg