Site adaptation of NASA-POWER reanalysis solar radiation products for tropical climates in Ghana using bias correction for clean energy application

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Abstract Solar radiation measurements are needed to simulate a diverse range of clean energy application systems for optimization. However worldwide, whereas radiometric measurement stations are scarce and mostly sparsely distributed, satellite and reanalysis products are available, though with resolution problems. Therefore in the absence of in-situ measurements, we developed a bias-corrected long-term solar radiation database for Ghana in West Africa, using reanalysis products retrieved from NASA’s Prediction of Worldwide Energy Resource (POWER) archives available at \(0.5^\circ \times 0.5^\circ\) spatial resolution by Cumulative Distribution Function (CDF) matching technique, with reference to a synthetic solar radiation database developed from sunshine duration measurements at 22 stations, in order to site-adapt the reanalysis products. From the results, the POWER products were improved by overall minimization in mean residual difference of -1.02–1.4 ± 0.07 kWhm− 2day− 1 to -0.85–1.2 ± 0.12 kWhm− 2day− 1 after bias correction, with a 9%, 27%, and 17% increase in smaller RD ranges of -0.5–0.5, -0.2–0.2, and − 0.1–0.1 kWhm− 2day− 1 respectively. Also, the Mean Bias Error (MBE) range minimized from − 0.51–0.6 ± 0.3 kWhm− 2day− 1 to -0.35–0.2 ± 0.1 kWhm− 2day− 1 with 17 stations showing residual differences in correlation coefficients greater than zero, indicative of higher correlation after bias correction. Overall, spatiotemporal characteristics are preserved, and the improvement is in acceptable margins for engineering application.
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Site adaptation of NASA-POWER reanalysis solar radiation products for tropical climates in Ghana using bias correction for clean energy application | 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 Site adaptation of NASA-POWER reanalysis solar radiation products for tropical climates in Ghana using bias correction for clean energy application Alfred Dawson Quansah, Patrick Boakye, David Ato Quansah, Lena Dzifa Mensah, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4571887/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 3 You are reading this latest preprint version Abstract Solar radiation measurements are needed to simulate a diverse range of clean energy application systems for optimization. However worldwide, whereas radiometric measurement stations are scarce and mostly sparsely distributed, satellite and reanalysis products are available, though with resolution problems. Therefore in the absence of in-situ measurements, we developed a bias-corrected long-term solar radiation database for Ghana in West Africa, using reanalysis products retrieved from NASA’s Prediction of Worldwide Energy Resource (POWER) archives available at \(0.5^\circ \times 0.5^\circ\) spatial resolution by Cumulative Distribution Function (CDF) matching technique, with reference to a synthetic solar radiation database developed from sunshine duration measurements at 22 stations, in order to site-adapt the reanalysis products. From the results, the POWER products were improved by overall minimization in mean residual difference of -1.02–1.4 ± 0.07 kWhm − 2 day − 1 to -0.85–1.2 ± 0.12 kWhm − 2 day − 1 after bias correction, with a 9%, 27%, and 17% increase in smaller RD ranges of -0.5–0.5, -0.2–0.2, and − 0.1–0.1 kWhm − 2 day − 1 respectively. Also, the Mean Bias Error (MBE) range minimized from − 0.51–0.6 ± 0.3 kWhm − 2 day − 1 to -0.35–0.2 ± 0.1 kWhm − 2 day − 1 with 17 stations showing residual differences in correlation coefficients greater than zero, indicative of higher correlation after bias correction. Overall, spatiotemporal characteristics are preserved, and the improvement is in acceptable margins for engineering application. NASA-POWER solar radiation bias correction energy meteorology sunshine Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editor assigned by journal 15 Jun, 2024 Submission checks completed at journal 15 Jun, 2024 First submitted to journal 12 Jun, 2024 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-4571887","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":317967886,"identity":"218c4950-8c49-4c23-9b5c-c4bc810625c4","order_by":0,"name":"Alfred Dawson Quansah","email":"","orcid":"","institution":"Ghana National Petroleum Corporation, Ghana","correspondingAuthor":false,"prefix":"","firstName":"Alfred","middleName":"Dawson","lastName":"Quansah","suffix":""},{"id":317967887,"identity":"2e22b31f-e107-4752-a203-a0c0b0c3826a","order_by":1,"name":"Patrick 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However worldwide, whereas radiometric measurement stations are scarce and mostly sparsely distributed, satellite and reanalysis products are available, though with resolution problems. Therefore in the absence of in-situ measurements, we developed a bias-corrected long-term solar radiation database for Ghana in West Africa, using reanalysis products retrieved from NASA\u0026rsquo;s Prediction of Worldwide Energy Resource (POWER) archives available at \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(0.5^\\circ \\times 0.5^\\circ\\)\u003c/span\u003e\u003c/span\u003e spatial resolution by Cumulative Distribution Function (CDF) matching technique, with reference to a synthetic solar radiation database developed from sunshine duration measurements at 22 stations, in order to site-adapt the reanalysis products. 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