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Abstract/Summary
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<jats:title>Abstract</jats:title><jats:p>Accurate and reliable estimation of rainfall is crucial for scientific research and various applications. However, the observed rainfall data is often limited. With the advancements in technology, many global gridded rainfall products are now available, but their accuracy levels vary across the world. In this study, we comprehensively analyzed the reliability and effectiveness of 23 publicly available global rainfall datasets against the observed rainfall for Patna, representing a typical urban monsoon climate in India. Thirteen continuous and ten categorical statistical metrics were applied at daily, weekly, monthly, and annual intervals over 16 years (2000–2015). The results indicate that the reliability of all derived rainfall datasets varied on different temporal scales and reference datasets used. Overall, in continuous metrics, MERRA2 and MSWEP consistently outperformed in all the temporal scales whereas in categorical metrics for analyzing the rainfall detection ability, AIMERG, followed by MERRA2 demonstrated superior performance among others. Furthermore, IMD GRID, GSMAP, PCCS, AIMERG, and IMERG performed well in estimating different rainfall intensities. MERRA2 and MSWEP, which have not been widely considered for evaluation in a monsoon climate were found to be outstanding performers consistently. Therefore, we suggest broadening the selection of global rainfall products in the evaluation to fully utilize the potentiality of all available options. Furthermore, our approach offers a reliable framework to comprehensively assess the performance of different gridded rainfall products and assist in the selection of the best rainfall product for a particular region and purpose.</jats:p>
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Hinweis
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DeepGreen-ID: 80af318ee6694ebab92d1cd0ddd1543f ; metadata provieded by: DeepGreen (https://www.oa-deepgreen.de/api/v1/), LIVIVO search scope life sciences (http://z3950.zbmed.de:6210/livivo), Crossref Unified Resource API (https://api.crossref.org/swagger-ui/index.html), to.science.api (https://frl.publisso.de/), ZDB JSON-API (beta) (https://zeitschriftendatenbank.de/api/), lobid - Dateninfrastruktur für Bibliotheken (https://lobid.org/resources/search)
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