A Consistent Treatment of Microwave Emissivity and Radar Backscatter for Retrieval of Precipitation over Water Surfaces

Abstract

he Global Precipitation Measurement (GPM) Microwave Imager (GMI) and dual-frequency precipitation radar (DPR) are designed to provide the most accurate instantaneous precipitation estimates currently available from space. The GPM Combined Radar?Radiometer Algorithm (CORRA) plays a key role in this process by retrieving precipitation profiles that are consistent with GMI and DPR measurements; therefore, it is desirable that the forward models in CORRA use the same geophysical input parameters. This study explores the feasibility of using internally consistent emissivity and surface backscatter cross-sectional models for water surfaces in CORRA. An empirical model for DPR Ku- and Ka-band as a function of 10-m wind speed and incidence angle is derived from GMI-only wind retrievals under clear-sky conditions. This allows for the measurements, which are also influenced by path-integrated attenuation (PIA) from precipitation, to be used as input to CORRA and for wind speed to be retrieved as output. Comparisons to buoy data give a wind rmse of 3.7 m s?1 for Ku+GMI retrievals and 3.2 m s?1 for Ku+Ka+GMI retrievals under precipitation (compared to 1.3 m s?1 for clear-sky GMI-only retrievals), and there is a reduction in bias from the global analysis (GANAL) background data (?10%) to the Ku+GMI (?3%) and Ku+Ka+GMI (?5%) retrievals. Ku+GMI retrievals of precipitation increase slightly in light (<1 mm h?1) and decrease in moderate to heavy precipitation (>1 mm h?1). The Ku+Ka+GMI retrievals, being additionally constrained by the Ka reflectivity, increase only slightly in moderate and heavy precipitation at low wind speeds (<5 m s?1) relative to retrievals using the surface reference estimate of PIA as input.