Adapting Passive Microwave-Based Precipitation Algorithms to Variable Microwave Land Surface Emissivity to Improve Precipitation Estimation from the GPM Constellation

Abstract A fully global satellite-based precipitation estimate that can transition across changing Earth surface and complex land/water conditions is an important capability for many hydrological applications, independent evaluation of the derived from weather climate models. This inherently challenging owing to complexity geophysical properties upon which instruments view. To date, these satellite observations originate primarily a variety wide-swath passive microwave (MW) imagers sounders. In contrast open ocean large water bodies, emissivity contribution MW measurements much more variable land surfaces, with varying sensitivities near-surface precipitation. The NASA/JAXA Global Precipitation Measurement (GPM) spacecraft (2014-current) equipped dual-frequency radar multichannel imaging radiometer specifically designed measurement, covering substantially area than its predecessor Tropical Rainfall Measuring Mission (TRMM). synergy between GPM’s has guided number new frameworks retrieval algorithms, whereby information carried by single narrow-swath exploited recover disparate constellation With over six years increased coverage provided GPM, insight been gained into nature ice/snow covered leading improvements in physical semi-physical based techniques adapt conditions. this manuscript, workings capabilities several approaches are highlighted.