{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,28]],"date-time":"2026-07-28T23:42:11Z","timestamp":1785282131429,"version":"3.55.0"},"reference-count":53,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2018,6,14]],"date-time":"2018-06-14T00:00:00Z","timestamp":1528934400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The performance of the latest released Integrated Multi-satellitE Retrievals for GPM mission (IMERG) version 5 (IMERG v5) and the TRMM Multisatellite Precipitation Analysis 3B42 version 7 (3B42 v7) are evaluated and compared at multiple temporal scales over a semi-humid to humid climate transition area (Huaihe River basin) from 2015 to 2017. The impacts of rainfall rate, latitude and elevation on precipitation detection skills are also investigated. Results indicate that both satellite estimates showed a high Pearson correlation coefficient (r, above 0.89) with gauge observations, and an overestimation of precipitation at monthly and annual scales. Mean daily precipitation of IMERG v5 and 3B42 v7 display a consistent spatial pattern, and both characterize the observed precipitation distribution well, but 3B42 v7 tends to markedly overestimate precipitation over water bodies. Both satellite precipitation products overestimate rainfalls with intensity ranging from 0.5 to 25 mm\/day, but tend to underestimate light (0\u20130.5 mm\/day) and heavy (&gt;25 mm\/day) rainfalls, especially for torrential rains (above 100 mm\/day). Regarding each gauge station, the IMERG v5 has larger mean r (0.36 for GPM, 0.33 for TRMM) and lower mean relative root mean square error (RRMSE, 1.73 for GPM, 1.88 for TRMM) than those of 3B42 v7. The higher probability of detection (POD), critical success index (CSI) and lower false alarm ratio (FAR) of IMERG v5 than those of 3B42 v7 at different rainfall rates indicates that IMERG v5 in general performs better in detecting the observed precipitations. This study provides a better understanding of the spatiotemporal distribution of accuracy of IMERG v5 and 3B42 v7 precipitation and the influencing factors, which is of great significance to hydrological applications.<\/jats:p>","DOI":"10.3390\/rs10060944","type":"journal-article","created":{"date-parts":[[2018,6,14]],"date-time":"2018-06-14T11:06:06Z","timestamp":1528974366000},"page":"944","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":99,"title":["Multiscale Comparative Evaluation of the GPM IMERG v5 and TRMM 3B42 v7 Precipitation Products from 2015 to 2017 over a Climate Transition Area of China"],"prefix":"10.3390","volume":"10","author":[{"given":"Cheng","family":"Chen","sequence":"first","affiliation":[{"name":"Center for Eco-Environmental Research, Nanjing Hydraulic Research Institute, Nanjing 210029, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qiuwen","family":"Chen","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Nanjing 210029, China"},{"name":"Center for Eco-Environmental Research, Nanjing Hydraulic Research Institute, Nanjing 210029, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4411-8196","authenticated-orcid":false,"given":"Zheng","family":"Duan","sequence":"additional","affiliation":[{"name":"Chair of Hydrology and River Basin Management, Technical University of Munich, Arcisstrasse 21, 80333 Munich, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jianyun","family":"Zhang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Nanjing 210029, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kangle","family":"Mo","sequence":"additional","affiliation":[{"name":"Center for Eco-Environmental Research, Nanjing Hydraulic Research Institute, Nanjing 210029, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhe","family":"Li","sequence":"additional","affiliation":[{"name":"Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guoqiang","family":"Tang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Hydroscience and Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2018,6,14]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"328","DOI":"10.1016\/j.jhydrol.2010.04.027","article-title":"High-resolution space\u2013time rainfall analysis using integrated ann inference systems","volume":"387","author":"Langella","year":"2010","journal-title":"J. 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