Evaluating Future Warming Scenarios in mainland India based on Bias-Corrected CMIP6 Multi-Model Ensembles

Evaluating Future Warming Scenarios in mainland India based on Bias-Corrected CMIP6 Multi-Model Ensembles | 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 Evaluating Future Warming Scenarios in mainland India based on Bias-Corrected CMIP6 Multi-Model Ensembles Avijit Paul, Monomoy Goswami This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9241553/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Understanding the spatio-temporal variability of temperature and its future evolution is critical for climate impact assessment and adaptation planning over India, a region characterized by complex physiography and pronounced climatic heterogeneity. This study presents a comprehensive assessment of future variations in monthly maximum, minimum, and mean temperatures over mainland India using outputs from Coupled Model Intercomparison Project Phase 6 (CMIP6) global climate models. To address climate model deficiencies, raw model outputs are bias-corrected and combined using an optimized multi-model ensemble framework. The resulting ensemble is applied to generate high-resolution temperature projections for the period 2025–2100 under four Shared Socioeconomic Pathway scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) to identify the most vulnerable regions for future warming. Spatio-temporal analyses reveal a consistent warming signal across the country, with the magnitude and spatial coverage of warming increasing markedly under higher-emission pathways. Regions characterized by complex topography, particularly the Himalayan and north-eastern areas, exhibit enhanced warming relative to the national average. Across all scenarios, monthly minimum temperature is projected to increase more rapidly than monthly maximum temperature, indicating intensified nocturnal warming and a progressive reduction in the monthly temperature range. These findings provide robust scientific evidence for anticipated temperature changes over India and offer valuable insights for climate risk assessment, policy formulation, and sustainable planning in climate-sensitive sectors. Future temperature projections of India Future Temperature trends of India CMIP6 Bias Correction Multi Model Ensemble Full Text Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 10 Apr, 2026 Reviewers invited by journal 01 Apr, 2026 Editor invited by journal 30 Mar, 2026 Editor assigned by journal 28 Mar, 2026 First submitted to journal 26 Mar, 2026 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-9241553","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":615757937,"identity":"4b1da045-bcd6-442b-8035-3572608e6937","order_by":0,"name":"Avijit Paul","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABDUlEQVRIiWNgGAWjYBADHsZmCEOGH0QmFBClhRnCkGwAaTEgyiKoFoMDIAqPFn7p9msfGGoOyzC38x9gLqg5zGN8fnXihwcGDPL8YgewapGcc6Z4BsOxw2CHMc8AMsxuvN0sAXSY4czZCVi1GNzISWZgYEuDaOFhA2k5uwGkJcHgNnYt9mAt/2Ba/gEdNuPs5h/4tBhIpB9mYGyzgWjhbTvMY8Dfuw2vLRI3cpgZEvvAWgwOz+xL55G4wbvNIsFAAqdf+GekP2b48E3C3rD/4MPHBd+s5fj7z26++aPCRp5fGrsWUEQwgKQMGxgYDkMsBquUwKEcBNgfgCl5Blhk8h/Ao3oUjIJRMApGIgAAKINVms6tTPkAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0001-9388-9571","institution":"Central Institute of Technology Kokrajhar Deemed to be University","correspondingAuthor":true,"prefix":"","firstName":"Avijit","middleName":"","lastName":"Paul","suffix":""},{"id":615757938,"identity":"a6dd35ad-25f6-48b6-8318-a70c2a66fa0e","order_by":1,"name":"Monomoy Goswami","email":"","orcid":"","institution":"Central Institute of Technology Kokrajhar Deemed to be University","correspondingAuthor":false,"prefix":"","firstName":"Monomoy","middleName":"","lastName":"Goswami","suffix":""}],"badges":[],"createdAt":"2026-03-27 07:36:56","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9241553/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9241553/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":106403438,"identity":"15bc6643-1f82-46cf-84ef-43cd819d49b0","added_by":"auto","created_at":"2026-04-08 09:14:17","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2007866,"visible":true,"origin":"","legend":"","description":"","filename":"Manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9241553/v1_covered_99aac926-a22e-4bb5-b60c-c09cae7e9753.pdf"}],"financialInterests":"","formattedTitle":"Evaluating Future Warming Scenarios in mainland India based on Bias-Corrected CMIP6 Multi-Model Ensembles","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"acta-geophysica","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"agph","sideBox":"Learn more about [Acta Geophysica](http://link.springer.com/journal/11600)","snPcode":"11600","submissionUrl":"https://www.editorialmanager.com/agph/default2.aspx","title":"Acta Geophysica","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Future temperature projections of India, Future Temperature trends of India, CMIP6, Bias Correction, Multi Model Ensemble","lastPublishedDoi":"10.21203/rs.3.rs-9241553/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9241553/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eUnderstanding the spatio-temporal variability of temperature and its future evolution is critical for climate impact assessment and adaptation planning over India, a region characterized by complex physiography and pronounced climatic heterogeneity. 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Across all scenarios, monthly minimum temperature is projected to increase more rapidly than monthly maximum temperature, indicating intensified nocturnal warming and a progressive reduction in the monthly temperature range. 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