An analytical framework reduces cloud feedback uncertainty by linking percentage cloud change to surface ocean warming patterns

An analytical framework reduces cloud feedback uncertainty by linking percentage cloud change to surface ocean warming patterns | 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 Article An analytical framework reduces cloud feedback uncertainty by linking percentage cloud change to surface ocean warming patterns Jian Ma, Jing Feng, Hui Su, Matthew Collins, In-Sik Kang, Masahiro Watanabe, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7523727/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 02 Feb, 2026 Read the published version in npj Climate and Atmospheric Science → Version 1 posted 15 You are reading this latest preprint version Abstract Clouds significantly influence Earth’s radiative balance with complex ongoing response to surface warming. Key drivers of change are sea surface temperature (SST) pattern effect that reshapes cloud distributions, and beta feedback that scales low-level fraction change to climatological amounts. Cloud radiative feedback remains the largest source of uncertainty in future climate projections, but current constraints are insufficient. Here, we demonstrate that the percentage change in tropical cloud fraction, driven by spatial patterns of sea surface temperature (SST) increase, is linked to cloud height variations. We introduce a proportional warmer-get-higher paradigm and develop a pattern-based analytical framework, identifying three key factors governing cloud feedback: percentage cloud sensitivity to SST, climatological cloud cover, and SST warming patterns relative to the tropical mean. By leveraging recent observations to constrain these factors in two stages, we establish a process-oriented emergent constraint on projected cloud feedback in the 21st century. The first stage substitutes simulated cloud sensitivity and mean cloud cover to correct biases and reduce spread by half. Explaining 62% of remaining spread in an attribution procedure, SST pattern effect is further constrained by the second stage. This percentage framework yields total, low, middle, and high cloud feedback of 0.49 ± 0.27, 0.33 ± 0.21, 0.09 ± 0.09, and 0.07 ± 0.06 W m − 2 K − 1 (90% confidence), respectively. It reduces intermodel uncertainty by 59% for cloud feedback and 33% for surface warming, resulting in a climate sensitivity of 4.08 ± 0.97 K. Earth and environmental sciences/Climate sciences Earth and environmental sciences/Environmental sciences cloud feedback warming patterns emergent constraint climate change Full Text Additional Declarations No competing interests reported. Supplementary Files PCC.SM.pdf Cite Share Download PDF Status: Published Journal Publication published 02 Feb, 2026 Read the published version in npj Climate and Atmospheric Science → Version 1 posted Editorial decision: Revision requested 26 Oct, 2025 Reviews received at journal 26 Oct, 2025 Reviews received at journal 26 Oct, 2025 Reviews received at journal 21 Oct, 2025 Reviewers agreed at journal 20 Oct, 2025 Reviewers agreed at journal 20 Oct, 2025 Reviewers agreed at journal 20 Oct, 2025 Reviews received at journal 09 Oct, 2025 Reviewers agreed at journal 27 Sep, 2025 Reviewers agreed at journal 27 Sep, 2025 Reviewers agreed at journal 22 Sep, 2025 Reviewers invited by journal 22 Sep, 2025 Editor assigned by journal 12 Sep, 2025 Submission checks completed at journal 12 Sep, 2025 First submitted to journal 03 Sep, 2025 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-7523727","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":521645165,"identity":"cccca4a7-8315-466d-ac06-2b57e3eda3ee","order_by":0,"name":"Jian 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Key drivers of change are sea surface temperature (SST) pattern effect that reshapes cloud distributions, and beta feedback that scales low-level fraction change to climatological amounts. Cloud radiative feedback remains the largest source of uncertainty in future climate projections, but current constraints are insufficient. Here, we demonstrate that the percentage change in tropical cloud fraction, driven by spatial patterns of sea surface temperature (SST) increase, is linked to cloud height variations. We introduce a proportional warmer-get-higher paradigm and develop a pattern-based analytical framework, identifying three key factors governing cloud feedback: percentage cloud sensitivity to SST, climatological cloud cover, and SST warming patterns relative to the tropical mean. By leveraging recent observations to constrain these factors in two stages, we establish a process-oriented emergent constraint on projected cloud feedback in the 21st century. The first stage substitutes simulated cloud sensitivity and mean cloud cover to correct biases and reduce spread by half. Explaining 62% of remaining spread in an attribution procedure, SST pattern effect is further constrained by the second stage. This percentage framework yields total, low, middle, and high cloud feedback of 0.49\u0026thinsp;\u0026plusmn;\u0026thinsp;0.27, 0.33\u0026thinsp;\u0026plusmn;\u0026thinsp;0.21, 0.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09, and 0.07\u0026thinsp;\u0026plusmn;\u0026thinsp;0.06 W m\u003csup\u003e\u0026minus;\u0026thinsp;2\u003c/sup\u003e K\u003csup\u003e\u0026minus;\u0026thinsp;1\u003c/sup\u003e (90% confidence), respectively. It reduces intermodel uncertainty by 59% for cloud feedback and 33% for surface warming, resulting in a climate sensitivity of 4.08\u0026thinsp;\u0026plusmn;\u0026thinsp;0.97 K.\u003c/p\u003e","manuscriptTitle":"An analytical framework reduces cloud feedback uncertainty by linking percentage cloud change to surface ocean warming patterns","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-03 15:11:07","doi":"10.21203/rs.3.rs-7523727/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-10-27T02:18:02+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-27T01:21:59+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-27T00:49:54+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-21T10:58:36+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"52305569182357776626377925137126759850","date":"2025-10-20T16:22:28+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"179465057720491610472077729843030173704","date":"2025-10-20T07:53:28+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"20914578432824605685354599909885898081","date":"2025-10-20T07:08:08+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-09T10:08:22+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"142891006703786662887453394012291293096","date":"2025-09-27T18:16:44+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"332700948092975011368074978040931829642","date":"2025-09-27T13:40:55+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"337105181729230072445600707721509800241","date":"2025-09-22T17:23:11+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-09-22T11:14:07+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-12T11:56:41+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-09-12T10:01:50+00:00","index":"","fulltext":""},{"type":"submitted","content":"npj Climate and Atmospheric Science","date":"2025-09-03T06:54:21+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"npj-climate-and-atmospheric-science","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"npjclimatsci","sideBox":"Learn more about [npj Climate and Atmospheric Science](http://www.nature.com/npjclimatsci/)","snPcode":"41612","submissionUrl":"https://submission.springernature.com/new-submission/41612/3","title":"npj Climate and Atmospheric Science","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"NPJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6d06b35c-c325-40db-b968-61f5671d208e","owner":[],"postedDate":"October 3rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":55445803,"name":"Earth and environmental sciences/Climate sciences"},{"id":55445804,"name":"Earth and environmental sciences/Environmental sciences"}],"tags":[],"updatedAt":"2026-02-09T16:01:38+00:00","versionOfRecord":{"articleIdentity":"rs-7523727","link":"https://doi.org/10.1038/s41612-026-01339-2","journal":{"identity":"npj-climate-and-atmospheric-science","isVorOnly":false,"title":"npj Climate and Atmospheric Science"},"publishedOn":"2026-02-02 15:58:11","publishedOnDateReadable":"February 2nd, 2026"},"versionCreatedAt":"2025-10-03 15:11:07","video":"","vorDoi":"10.1038/s41612-026-01339-2","vorDoiUrl":"https://doi.org/10.1038/s41612-026-01339-2","workflowStages":[]},"version":"v1","identity":"rs-7523727","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7523727","identity":"rs-7523727","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}