Assessment of CMIP6 Models' Performance for South America: Multilevel Perspective

Assessment of CMIP6 Models' Performance for South America: Multilevel Perspective | 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 Assessment of CMIP6 Models' Performance for South America: Multilevel Perspective Maria Leidinice da Silva, Michelle Simões Reboita, Naurinete Barreto, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8694678/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 10 You are reading this latest preprint version Abstract The selection of global climate models (GCMs) that represent the main features of the present climate is crucial for reducing uncertainties when assessing climate trends or driving regional climate models. Based on this premise, the main goal of this study is to assess the skill of 17 GCMs from the Coupled Model Intercomparison Project - Phase 6 (CMIP6) in representing basic features of the present climate (1979-2014). As the analyses are performed for different atmospheric variables and vertical levels, the study is considered multilevel. Different statistical metrics are used to compare the simulations with ERA5 reanalysis focusing on 5 subdomains of South America (SA): northern Amazon Basin (NAMZ), southern Amazon Basin (SAMZ), Northeast region of Brazil (NEB), South American Monsoon (SAM) and La Plata Basin (LPB). The statistics are summarized through a comprehensive rating index, which is described in detail in this study, in order to provide the models' ranking in terms of performance. Among the results, model performance varies across regions and variables. Models such as CNRM-CM6-1, GFDL-ESM4, MPI-ESM1-2-HR, and NorESM2-MM stand out for their superior performance across multiple variables and regions, whereas INM-CM4-8, KIOST, and NESM3 show limitations, particularly in simulating upper-level circulation and precipitation processes. Therefore, the main conclusion is that models should be chosen based on their performance in the region of interest. CMIP6 Models’ performance South America Atmospheric circulation Precipitation Air temperature Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 17 Apr, 2026 Reviews received at journal 16 Apr, 2026 Reviews received at journal 03 Mar, 2026 Reviewers agreed at journal 04 Feb, 2026 Reviewers agreed at journal 02 Feb, 2026 Reviewers agreed at journal 29 Jan, 2026 Reviewers invited by journal 29 Jan, 2026 Editor assigned by journal 25 Jan, 2026 Submission checks completed at journal 25 Jan, 2026 First submitted to journal 25 Jan, 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. 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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-8694678","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":582533538,"identity":"f3943620-1e04-4b2d-9681-7b177330bcc6","order_by":0,"name":"Maria Leidinice da Silva","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAvUlEQVRIiWNgGAWjYFCCBCA2sGDgZwbzJIjWIsEg2czA2ADUQoyeBIjhBgfAWoiwRrc9+QHjjwKJxM3HmZ8/LmCwqCOoxezMMwNmHgOJxG2H2QybZxDjMLMbCQbMQL8Ymx3mYWzmIU5L+gfGH0Atxs3Ea8kxYAA6TA7oPGK1nHlTAPKLnATQL7NnGEhINhDUcjx9A+OPPzY8/P2HH3wuqKjjJ2gLELD/gLGA4UCMBmTATKqGUTAKRsEoGBkAANqZL3lUHjVJAAAAAElFTkSuQmCC","orcid":"","institution":"Abdus Salam International Centre for Theoretical Physics","correspondingAuthor":true,"prefix":"","firstName":"Maria","middleName":"Leidinice da","lastName":"Silva","suffix":""},{"id":582533539,"identity":"5d62fb73-79e8-450c-8dbd-aba1ba0d60e0","order_by":1,"name":"Michelle Simões Reboita","email":"","orcid":"","institution":"Federal University of Itajubá","correspondingAuthor":false,"prefix":"","firstName":"Michelle","middleName":"Simões","lastName":"Reboita","suffix":""},{"id":582533540,"identity":"d95ab9d2-d912-4f6e-97a1-bb8e775cb692","order_by":2,"name":"Naurinete Barreto","email":"","orcid":"","institution":"National Institute for Space Research","correspondingAuthor":false,"prefix":"","firstName":"Naurinete","middleName":"","lastName":"Barreto","suffix":""},{"id":582533541,"identity":"54f1c031-afed-4a5c-a6b5-3319bb8fc65f","order_by":3,"name":"Lincoln Muniz Alves","email":"","orcid":"","institution":"National Institute for Space Research","correspondingAuthor":false,"prefix":"","firstName":"Lincoln","middleName":"Muniz","lastName":"Alves","suffix":""}],"badges":[],"createdAt":"2026-01-25 20:08:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8694678/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8694678/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":101753459,"identity":"caab83b2-e4c5-420b-a163-4db3af7c0a0e","added_by":"auto","created_at":"2026-02-03 10:40:06","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3295701,"visible":true,"origin":"","legend":"","description":"","filename":"DaSilvaetal2026TAAC.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8694678/v1_covered_1c684510-a298-41a1-b957-3d4ce298af44.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Assessment of CMIP6 Models' Performance for South America: Multilevel Perspective","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":"theoretical-and-applied-climatology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"taac","sideBox":"Learn more about [Theoretical and Applied Climatology](https://www.springer.com/journal/704)","snPcode":"704","submissionUrl":"https://submission.nature.com/new-submission/704/3","title":"Theoretical and Applied Climatology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"CMIP6, Models’ performance, South America, Atmospheric circulation, Precipitation, Air temperature","lastPublishedDoi":"10.21203/rs.3.rs-8694678/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8694678/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe selection of global climate models (GCMs) that represent the main features of the present climate is crucial for reducing uncertainties when assessing climate trends or driving regional climate models. 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