Evaluation of IMERG and GSMaP for Tropical Cyclone Applications

This study compares rainfall from NASA Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG V06) and JAXA Global Satellite Mapping of Precipitation (GSMaP V4) for tropical cyclone (TC) applications against satellite microwave-derived Goddard Profiling Algorithm (GPROF V05) precipitation data retrieved from 2000 to 2012. From a global data set of storms, all three products show consistent patterns in 1-dimensional azimuthal averages and in 2-dimensional rainfall distributions (where spatial correlation values are near 1.0). However, both IMERG and GSMaP overestimate precipitation amounts against GPROF, and IMERG overestimations are much higher than GSMaP within 125 km of the storm center. Based on this analysis, IMERG and GSMaP rainfall could be used to analyze TC precipitation patterns at high spatiotemporal resolutions. However, caution is required if high accuracy TC precipitation amplitude is required, particularly for IMERG. This study highlights opportunities to improve future versions of IMERG and GSMaP retrieval processing to reduce the discrepancies with GPROF. The National Aeronautics and Space Administration (NASA) Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG V06) and Japan Aerospace Exploration Agency (JAXA) Global Satellite Mapping of Precipitation (GSMaP V4) rainfall data sets were evaluated for tropical cyclone (TC) applications using the Goddard Profiling Algorithm (GPROF) precipitation data in 2000-2012. Results reveal consistent spatial distributions of TC rainfall between GPROF, IMERG, and GSMaP with correlation coefficients near 1 for seven storm intensity categories based on global storm analysis. Results also indicate both IMERG and GSMaP overestimate TC precipitation. Overall, this study demonstrates that both IMERG and GSMaP rainfall could be used for TC applications. However, a caution is recommended if high accuracy on TC precipitation amplitude is required. The high spatiotemporal resolution IMERG and GSMaP rain data sets are evaluated for tropical cyclone applications using GPROF precipitation Consistent characteristics of intensity and distribution on TC precipitation are found among IMERG, GSMaP, and GPROF data sets IMERG and GSMaP rain data sets could be used for TC applications with a caution if high accuracy precipitation amplitude is required