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

Abstract

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