{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,2]],"date-time":"2026-04-02T13:02:55Z","timestamp":1775134975359,"version":"3.50.1"},"reference-count":70,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2021,9,10]],"date-time":"2021-09-10T00:00:00Z","timestamp":1631232000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["GEO\/ATM 1854511 and EAR 1850661"],"award-info":[{"award-number":["GEO\/ATM 1854511 and EAR 1850661"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>This article examines the reliability of satellite and reanalysis estimates of rainfall in the Congo Basin and over Lake Victoria and its catchment. Nine satellite products and five reanalysis products are considered. They are assessed by way of inter-comparison and by comparison with observational data sets. The three locations considered include a region with little observational gauge data (the Congo), a region with extensive gauge data (Lake Victoria catchment), and an inland water body. Several important results emerge: for one, the diversity of estimates is generally very large, except for the Lake Victoria catchment. Reanalysis products show little relationship with observed rainfall or with the satellite estimates, and thus should not be used to assess rainfall in these regions. Most of the products either overestimate or underestimate rainfall over the lake. The diversity of estimates makes it difficult to assess the factors governing the interannual variability of rainfall in these regions. This is shown by way of correlation with sea-surface temperatures, particularly with the Ni\u00f1o 3.4 temperatures and with the Dipole Mode Index over the Indian Ocean. Some guidance is given as to the best products to utilize. Overall, any user must establish that the is product reliable in the region studied.<\/jats:p>","DOI":"10.3390\/rs13183609","type":"journal-article","created":{"date-parts":[[2021,9,12]],"date-time":"2021-09-12T21:48:01Z","timestamp":1631483281000},"page":"3609","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":29,"title":["Assessing the Reliability of Satellite and Reanalysis Estimates of Rainfall in Equatorial Africa"],"prefix":"10.3390","volume":"13","author":[{"given":"Sharon E.","family":"Nicholson","sequence":"first","affiliation":[{"name":"Department of Earth, Ocean and Atmospheric Sciences, Florida State University, Tallahassee, FL 32306, USA"}]},{"given":"Douglas A.","family":"Klotter","sequence":"additional","affiliation":[{"name":"Department of Earth, Ocean and Atmospheric Sciences, Florida State University, Tallahassee, FL 32306, USA"}]}],"member":"1968","published-online":{"date-parts":[[2021,9,10]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1002\/2017RG000574","article-title":"A review of global precipitation data sets: Data sources, estimation, and inter-comparisons","volume":"56","author":"Sun","year":"2018","journal-title":"Rev. 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