REQUIREMENTS FOR THE DEGREE OF

In order to achieve better understanding of the hydrological cycle and the distribution of global precipitation, various microwave satellite platforms have been launched in the past to allow significant advance in precipitation measurement from directly measuring microwave radiances and reflectivity from space. Nevertheless, ambiguities in precipitation estimation from the only use of sets of brightness temperature measurements could lead to significant error. These ambiguities can be reduced with the addition of complementary data sets that until this point have not been employed in retrieval algorithms. In this paper, the potential improvements to estimating precipitation that are possible by combining observed brightness temperature measurements with other available sources of information will be investigated. One way of passive microwave precipitation retrieval for the satellite-borne microwave radiometers is to be accomplished by the use of physical inversion-based algorithms, which uses Cloud Radiation Databases (CRDs). CRDs are composed of a large amount of vertical microphysical profiles, which are produced by various clou