Effects of uncertainty in cloud microphysics on passive microwave rainfall measurements

Physically-based retrieval algorithms for passive microwave radiometers have been used to monitor global rainfalls. The most important part of the algorithms may be accurate knowledge on the a-priori databases for the inversion of rainfalls. This study investigates the impacts of the uncertainties in a-priori databases associated with assumed cloud microphysics on rainfall measurements especially for extreme rain events. The Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and Precipitation Radar (PR) observations of Typhoon Sudal (2004) are used for the generation of rainfall databases and rainfall target scenes. Six different microphysics schemes are evaluated to better represent the rainfall structure of an intense tropical cyclone (TC).