{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,28]],"date-time":"2026-02-28T04:27:32Z","timestamp":1772252852777,"version":"3.50.1"},"reference-count":52,"publisher":"MDPI AG","issue":"14","license":[{"start":{"date-parts":[[2021,7,11]],"date-time":"2021-07-11T00:00:00Z","timestamp":1625961600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"NASA MEaSUREs","award":["NNH17ZDA001N-MEASURES"],"award-info":[{"award-number":["NNH17ZDA001N-MEASURES"]}]},{"name":"NASA Weather and Atmospheric Dynamics","award":["NNH19ZDA001N-ATDM"],"award-info":[{"award-number":["NNH19ZDA001N-ATDM"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Precipitation rate from various products of the integrated multisatellite retrievals for GPM (IMERG) and passive microwave (PMW) sensors are assessed with respect to near-surface wet-bulb temperature (Tw), precipitation intensity, and surface type (i.e., with and without snow and ice on the surface) over the contiguous United States (CONUS) and using ground radar product as reference precipitation. IMERG products include precipitation estimates from infrared (IR), combined PMW, and combination of PMW and IR. It was found that precipitation estimates from PMW products generally have higher skills than IR over snow- and ice-free surfaces. Over snow- and ice-covered surfaces: (1) most PMW products show higher correlation coefficients than IR, (2) at cold temperatures (e.g., Tw &lt; \u221210 \u00b0C), PMW products tend to underestimate and IR product shows large overestimations, and (3) PMW sensors show higher overall skill in detecting precipitation occurrence, but not necessarily at very cold Tw. The results suggest that the current approach of IMERG (i.e., replacing PMW with IR precipitation estimates over snow- and ice-surfaces) may need to be revised.<\/jats:p>","DOI":"10.3390\/rs13142726","type":"journal-article","created":{"date-parts":[[2021,7,11]],"date-time":"2021-07-11T22:16:48Z","timestamp":1626041808000},"page":"2726","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Investigating Various Products of IMERG for Precipitation Retrieval over Surfaces with and without Snow and Ice Cover"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5967-3013","authenticated-orcid":false,"given":"Alireza","family":"Arabzadeh","sequence":"first","affiliation":[{"name":"Department of Hydrology and Atmospheric Sciences, University of Arizona, Tucson, AZ 85721, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7594-8793","authenticated-orcid":false,"given":"Ali","family":"Behrangi","sequence":"additional","affiliation":[{"name":"Department of Hydrology and Atmospheric Sciences, University of Arizona, Tucson, AZ 85721, USA"},{"name":"Department of Geosciences, University of Arizona, Tucson, AZ 85721, USA"}]}],"member":"1968","published-online":{"date-parts":[[2021,7,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"125798","DOI":"10.1016\/j.jhydrol.2020.125798","article-title":"Impact of sampling of GPM orbital data on streamflow simulations","volume":"593","author":"Pradhan","year":"2021","journal-title":"J. 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