Quantifying the Effect of a Parallax Correcting Algorithm for Passive Microwave Satellite Precipitation Retrievals across the Continental United States
Andres F. Monsalve, Hernan A. Moreno, Eric Goldenstern, Christian Kummerow
公開日: 2025/9/23
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 GPM Passive Microwave Imagery (GMI) on board the core satellite of the Global Precipitation Mission (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 Continental United States are analyzed using the ground-validated Multi-Resolution Multi-Sensor (GV-MRMS) system data and the European Centre for Medium-Range Weather Forecasts Reanalysis version 5 (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.