Abstract This study evaluates the precipitation retrieval performance of 13 Passive Microwave (PMW) radiometers used as input to the Japan Aerospace and Exploration Agency (JAXA) Global Satellite Mapping of Precipitation (GSMaP) dataset, relative to the Global Precipitation Measurements (GPM) Ku-band Precipitation Radar (KuPR) observations. These PMW sensors include the GPM Microwave Imager (GMI), Advanced Microwave Scanning Radiometer 2 (AMSR2), four Special Sensor Microwave Imager/Sounders (SSMISs), two Advanced Technology Microwave Sounders (ATMSs) onboard the Suomi National Polar-orbiting Partnership (SNPP) and the NOAA-20 satellites, and five Microwave Humidity Sounders (MHSs) onboard NOAA-18, NOAA-19, MetOp-A, MetOp-B, and MetOp-C satellites. We identified several key factors affecting the performance of these 13 sensors, including channel availability, retrieval algorithm, spatial resolution, and snowfall retrieval scheme. Over ocean, AMSR2 and GMI show the best performance, mainly due to their finer spatial resolution and the usage of ~10 GHz. Interestingly, GMI and three SSMISs (onboard F16, F17, and F19) exhibit several identical precipitation values. Further analyses indicate that these artificial values appear under snowfall conditions, suggesting an issue with the snowfall algorithm. Over land, the precipitation intensity retrieved from GMI, AMSR2 and SSMISs show high concentrations near specific values, which also contribute to their poorer performance. Over both ocean and land, MHSs perform better than ATMSs, most likely due to the finer spatial resolution. These results will provide guidance and insights for future PMW algorithm developments, and also utilization of the merged satellite precipitation products.
Ryu et al. (Wed,) studied this question.