Prototyping a Generic, Unified Land Surface Classification and Screening Methodology for GPM-Era Microwave Land Precipitation Retrieval Algorithms

Abstract

prototype generic, unified land surface classification and screening methodology for Global Precipitation Measurement (GPM)-era microwave land precipitation retrieval algorithms by using ancillary datasets is developed. As an alternative to the current radiometer-determined approach, the new methodology is shown to be promising in improving rain detection by providing better surface-cover-type information. The early prototype new surface screening scheme was applied to the current version of the Goddard profiling algorithm that is used for the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (GPROFV6). It has shown improvements in surface-cover-type classification and hence better precipitation retrieval comparisons with TRMM precipitation radar level-2 (L2) (2A25) data and the Global Precipitation Climatology Project (GPCP) version-2.1 (GPCPV2.1) datasets. The new ancillary data approach removes the current dependency of the screening step on relatively different satellite-specific channels and ensures the comparability and continuity of satellite-based precipitation products from different platforms. This is particularly important for advancing the current state of precipitation retrieval over land and for use in merged rainfall products.