Quantifying the Effect of a Parallax-Correcting Algorithm for Passive Microwave Satellite Precipitation Retrievals across the Conterminous United States

Abstract Satellite precipitation retrieval algorithms whose measurement instruments are tilted to the zenith line are subject to a spatial mismatch between the theoretical ground coordinates and the coordinate pair corresponding to the cloud layers sending spectral signals to the satellite. This is the case of the precipitation retrievals of the Global Precipitation Measurement (GPM) Microwave Imager (GMI) on board the core satellite of the GPM that uses the Goddard profiling algorithm (GPROF). Currently, no geometrical correction is applied to GMI retrievals of surface precipitation, creating a horizontal displacement (or parallax mismatching) between the reported surface and the corrected coordinates corresponding to the cloud structures intersecting the field of view. GPROF precipitation retrievals over the conterminous United States are analyzed using the ground-validated Multi-Radar Multi-Sensor (GV-MRMS) system data and the fifth generation European Centre for Medium-Range Weather Forecasts atmospheric reanalysis (ERA5) temperature profiles. Results applying this parallax correction scheme show improvements in the overall retrieval accuracy of GPROF, mainly during the summer months, for every precipitation type, when the freezing level (FL) is relatively high. The development of this new parallax correction algorithm for passive microwave radiometers will significantly improve the accuracy of remote sensing data by minimizing spatial distortions in atmospheric measurements, leading to more precise weather forecasting, climate monitoring, and environmental assessments. Significance Statement Our study addresses a critical issue in satellite precipitation retrieval algorithms regarding the spatial mismatch from tilted measurement instruments. By examining the precipitation retrievals of the Global Precipitation Measurement Microwave Imager (GMI) instrument, we highlight the consequential parallax mismatching between reported surface precipitation from observed cloud structures as well as the resulting error from this discrepancy. Through a novel geometrical correction scheme applied to GMI retrievals over the conterminous United States, we demonstrate significant enhancements in retrieval accuracy, particularly during summer months that are characterized by high-altitude freezing levels. These findings advance the reliability of satellite-based precipitation estimation, which is crucial for meteorological research and operational forecasting.