Projected Mean Temperatures over India under RCP Scenarios: A Comparison of Statistical and Dynamical Downscaling

Projected Mean Temperatures over India under RCP Scenarios: A Comparison of Statistical and Dynamical Downscaling | 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 Projected Mean Temperatures over India under RCP Scenarios: A Comparison of Statistical and Dynamical Downscaling Abdelkader Mezghani, Øivind Hodnebrog, Rasmus E. Benestad, Frode Stordal, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7092806/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 We evaluate and compare two downscaling methods for reproducing observed temperature statistics across weather stations in India: (i) a dynamical downscaling approach using the Weather Research and Forecasting (WRF) model, and (ii) an Empirical–Statistical Downscaling (ESD) method. Both methods are driven by the same global climate model, CESM1-CAM4, allowing a consistent evaluation. Owing to its computational efficiency, the ESD method is also applied to the full CMIP5 multi-model ensemble to explore a broader range of climate futures.Our analysis includes multi-scale evaluation at global, regional, and local levels, with a focus on seasonal and annual mean air temperature. Once validated, both methods are used to assess projected temperature changes at national and station scales. Despite a modest cold bias in WRF simulations (less than 0.5°C), both downscaling approaches project annual warming of approximately 1.5±0.5°C by 2041–2060 and 3.0±1.0°C by 2081–2100 under RCP8.5. Seasonal warming may reach up to 10°C in parts of India, indicating significant potential impacts on health, agriculture, and infrastructure. We find that increasing WRF resolution from 45km to 15km reduces cold biases, though projected temperature changes are more sensitive to the choice of downscaling method and input data than to model resolution. 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. 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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-7092806","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":493288521,"identity":"9bcf5068-f239-4a38-9d65-85099018f2f8","order_by":0,"name":"Abdelkader Mezghani","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA1klEQVRIiWNgGAWjYDACCQYDhgcHGBgbGBgYHxCvJQGihdmAAcghSQubBFFa+Gc3b3yQcMZOtl/6dFrVjYo/DObsDQQsuXOs2CDhRrLxzL7cbbdzzhgwWPYcIGDNjRwziYQPzIkbzvBuu53bZsBgcCMBvw75GznmPxI+1CfuB2opzv1HhBYDoC0MCTcOJ27g4d3GnNtAhBZDoF8kEs4cN55xhnezdM4xYx6DMwT8Ine7eeOHD8eqZft7eDd+zqmRkzM43oBfCwbgIVH9KBgFo2AUjAJsAACCC0v7+iQj5AAAAABJRU5ErkJggg==","orcid":"","institution":"Norwegian Meteorological Institute","correspondingAuthor":true,"prefix":"","firstName":"Abdelkader","middleName":"","lastName":"Mezghani","suffix":""},{"id":493288522,"identity":"05ee9dd8-0a8f-426e-b8d7-e25e11be3b40","order_by":1,"name":"Øivind Hodnebrog","email":"","orcid":"","institution":"Center for International Climate Research","correspondingAuthor":false,"prefix":"","firstName":"Øivind","middleName":"","lastName":"Hodnebrog","suffix":""},{"id":493288525,"identity":"1e549b65-56f9-4a1d-aa5e-b6926c5976a6","order_by":2,"name":"Rasmus E. 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