{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,10]],"date-time":"2026-06-10T10:52:51Z","timestamp":1781088771018,"version":"3.54.1"},"reference-count":81,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2015,5,5]],"date-time":"2015-05-05T00:00:00Z","timestamp":1430784000000},"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>TRMM Multi-satellite Precipitation Analysis (TMPA) satellite precipitation products have been utilized to quantify, forecast, or understand precipitation patterns, climate change, hydrologic models, and drought in numerous scientific investigations. The TMPA products recently went through a series of algorithm developments to enhance the accuracy and reliability of high-quality precipitation measurements, particularly in low rainfall environments and complex terrain. In this study, we evaluated four TMPA products (3B42: V6, V7temp, V7, RTV7) against 125 rain gauges in Northern Morocco to assess the accuracy of TMPA products in various regimes, examine the performance metrics of new algorithm developments, and assess the impact of the processing error in 2012. Results show that the research products outperform the real-time products in all environments within Morocco, and the newest algorithm development (3B42 V7) outperforms the previous version (V6), particularly in low rainfall and high-elevation environments. TMPA products continue to overestimate precipitation in arid environments and underestimate it in high-elevation areas. Lastly, the temporary processing error resulted in little bias except in arid environments. These results corroborate findings from previous studies, provide scientific data for the Middle East, highlight the difficulty of using TMPA products in varying conditions, and present preliminary research for future algorithm development for the GPM mission.<\/jats:p>","DOI":"10.3390\/rs70505697","type":"journal-article","created":{"date-parts":[[2015,5,5]],"date-time":"2015-05-05T10:43:16Z","timestamp":1430822596000},"page":"5697-5717","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":123,"title":["Assessment and Comparison of TMPA Satellite Precipitation Products in Varying Climatic and Topographic Regimes  in Morocco"],"prefix":"10.3390","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0494-8002","authenticated-orcid":false,"given":"Adam","family":"Milewski","sequence":"first","affiliation":[{"name":"Water Resources & Remote Sensing Group (WRRS), Department of Geology, University of Georgia, 210 Field Street, 306 Geography-Geology Building, Athens, GA 20602, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Racha","family":"Elkadiri","sequence":"additional","affiliation":[{"name":"Department of Geosciences, Western Michigan University, 1903 W. Michigan Avenue,  1187 Rood Hall, Kalamazoo, MI 49008, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michael","family":"Durham","sequence":"additional","affiliation":[{"name":"Water Resources & Remote Sensing Group (WRRS), Department of Geology, University of Georgia, 210 Field Street, 306 Geography-Geology Building, Athens, GA 20602, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2015,5,5]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1007\/s10040-006-0127-z","article-title":"How can remote sensing contribute in groundwater modeling?","volume":"15","author":"Brunner","year":"2007","journal-title":"Hydrogeol. 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