Evaluation and Error Decomposition of IMERG Product Based on Multiple Satellite Sensors

The Integrated Multisatellite Retrievals for GPM (IMERG) is designed to derive precipitation by merging data from all the passive microwave (PMW) and infrared (IR) sensors. While input source errors originating PMW IR sensors are important, their structure, characteristics, algorithm improvement remain unclear. Our study utilized a four-component error decomposition (4CED) method systematic random evaluate detectability of IMERG dataset identify based on multi-sensors. 30 min stations in Tunxi Watershed were used 2018 2020. includes five types instruments. results show that sample ratio (Morph, + Morph, only) much higher than (AMSR2, SSMIS, GMI, MHS, ATMS), with 72.8% sources 27.2% sources. high false sensor leads poor performance alarm (FAR, 0.5854), critical success index (CSI, 0.3014), Brier score (BS, 0.1126). As 4CED, Morph have large magnitude total bias (TB), hit overestimate (HOB), underestimate (HUB), (FB), miss (MB), which related prediction ability size. In addition, prominent component AMSR2, IR, indicating some inherent (retrieval algorithm) needs be removed. These findings can support improving retrieval reducing dataset.