Validation of Satellite Rainfall Estimates against Rain Gauge Data for Enhanced Drought Monitoring and Early Warning Systems in Botswana

Validation of Satellite Rainfall Estimates against Rain Gauge Data for Enhanced Drought Monitoring and Early Warning Systems in Botswana | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Validation of Satellite Rainfall Estimates against Rain Gauge Data for Enhanced Drought Monitoring and Early Warning Systems in Botswana Rejoice Molosiwa, Kgakgamatso Mphale, Nicholas Mbangiwa This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6196056/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Satellite rainfall estimation products (SREs) play a crucial role in overcoming the absence and scarcity of rain gauge data to monitor rainfall-related risks and provide early warnings. However, SREs can be subject to several sources of errors and need to be validated before use. This work provides the validation of three ( 3 ) SREs: Climate Hazards Group Infrared Precipitation with Stations (CHIRPS v2.0), Tropical Applications of Meteorology using Satellite and Ground-based Observation (TAMSAT) v3.0, and TerraClimate with respect to their performance in detecting rainfall patterns in Botswana at monthly scales from 1984 to 2016. Rain gauge data from the Botswana Department of Meteorological Services (BDMS) was used as reference data. Botswana is highly vulnerable to droughts; thus, understanding rainfall products strengths and weaknesses is important. A comparative analysis was conducted using pairwise comparison statistics and categorical statistics. CHIRPS and TAMSAT strongly correlate with low rainfall, while TerraClimate overestimates it. All three products underestimate high rainfall amounts. CHIRPS has the best efficiency in estimating rainfall, as evidenced by its high Kling-Gupta efficiency (KGE) score of 0.94. All products show their best results during the wet season, while CHIRPS typically surpasses the other two in the dry season, evidenced by a False Alarm Ratio (FAR) of 0.12, indicating effective detection under low rainfall conditions. All products demonstrate the best performance in Northern Botswana, where rainfall is dominated by the incursion of tropical depression. The study determined that the CHIRPS dataset can serve as an effective alternative to rain-gauge rainfall data in semiarid Botswana. Botswana Drought Rainfall Satellite rainfall estimates gauge observations pairwise comparison categorical validation Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6196056","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":433070802,"identity":"4aaeef7b-818d-45cb-900c-e5be90f253e7","order_by":0,"name":"Rejoice Molosiwa","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAx0lEQVRIiWNgGAWjYFAC5gYGBgMgzd7ABuYbENbCCNXCc4AkLSAgkUCkFt32xsaHPwoOy5vPfGP2gKHGjsFcIgG/FrMzB5uNeQwOG865nWNuwHAsmcFyBiEtNxLbpBkMbjPOkM4xk2BgOwBkE6FF8ofBbfsZkmeAWv4RqUWCx+B24gwJHjMJxjZitED88j95Bk9auUFiXzKP5fwHBLQcbz748MefNNsZ7Ie3PfjwzU7OnOcAfi2oAOgkHlLUj4JRMApGwSjAAQArBEI7zq3XbAAAAABJRU5ErkJggg==","orcid":"","institution":"University of Botswana","correspondingAuthor":true,"prefix":"","firstName":"Rejoice","middleName":"","lastName":"Molosiwa","suffix":""},{"id":433070803,"identity":"dbbe9b69-0c4e-4dd8-b0cf-7a5fb50bf3bc","order_by":1,"name":"Kgakgamatso Mphale","email":"","orcid":"","institution":"University of Botswana","correspondingAuthor":false,"prefix":"","firstName":"Kgakgamatso","middleName":"","lastName":"Mphale","suffix":""},{"id":433070804,"identity":"6b39e5f5-0bbe-45b7-b58e-33ca2bc3fb9a","order_by":2,"name":"Nicholas Mbangiwa","email":"","orcid":"","institution":"University of Botswana","correspondingAuthor":false,"prefix":"","firstName":"Nicholas","middleName":"","lastName":"Mbangiwa","suffix":""}],"badges":[],"createdAt":"2025-03-10 13:38:26","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6196056/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6196056/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":84962377,"identity":"6d95de02-9f1a-47c0-b7f5-779c3d298fc2","added_by":"auto","created_at":"2025-06-19 09:17:08","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1077951,"visible":true,"origin":"","legend":"","description":"","filename":"RejoiceMolosiwaUniversityofBotswanaSREValidation18March2025V3.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6196056/v1_covered_a5ab9c72-3b3c-4eb6-842c-c8a01d40eb54.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Validation of Satellite Rainfall Estimates against Rain Gauge Data for Enhanced Drought Monitoring and Early Warning Systems in Botswana","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Botswana, Drought, Rainfall, Satellite rainfall estimates, gauge observations, pairwise comparison, categorical validation","lastPublishedDoi":"10.21203/rs.3.rs-6196056/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6196056/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eSatellite rainfall estimation products (SREs) play a crucial role in overcoming the absence and scarcity of rain gauge data to monitor rainfall-related risks and provide early warnings. However, SREs can be subject to several sources of errors and need to be validated before use. This work provides the validation of three (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) SREs: Climate Hazards Group Infrared Precipitation with Stations (CHIRPS v2.0), Tropical Applications of Meteorology using Satellite and Ground-based Observation (TAMSAT) v3.0, and TerraClimate with respect to their performance in detecting rainfall patterns in Botswana at monthly scales from 1984 to 2016. Rain gauge data from the Botswana Department of Meteorological Services (BDMS) was used as reference data. Botswana is highly vulnerable to droughts; thus, understanding rainfall products strengths and weaknesses is important. A comparative analysis was conducted using pairwise comparison statistics and categorical statistics. CHIRPS and TAMSAT strongly correlate with low rainfall, while TerraClimate overestimates it. 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