Aggregation of Experts Judgments for Climate Tipping Points

Aggregation of Experts Judgments for Climate Tipping Points | 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 Aggregation of Experts Judgments for Climate Tipping Points Marcello Basili, Federico Crudu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3579951/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 This paper introduces a method for the evaluation of the occurrence of tipping points based on the combination of probability intervals from experts judgments elicited in face-to-face interviews. The computation of such conditional probabilities is based on the aggregation of imprecise probability judgments through the Steiner point. The probability of a tipping point can be updated by the standard Bayes rule to generate tipping point scenarios. Our results suggest that tipping events may happen with relatively large probabilities, in contrast with the view that tipping points are low-probability-high-impact events. This suggests that mitigation and containment policies cannot be further postponed. JEL Classification: Q54; D81; C10 Bayesian updating aggregation of opinions global warming judgmental forecasting Steiner point tipping points 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-3579951","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":251692946,"identity":"18249d36-8be9-4ba3-99a2-1fd5f8e67e54","order_by":0,"name":"Marcello Basili","email":"","orcid":"","institution":"Università degli Studi di Siena","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Marcello","middleName":"","lastName":"Basili","suffix":""},{"id":251692947,"identity":"67530979-0480-4e58-9664-142134b8eead","order_by":1,"name":"Federico Crudu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6ElEQVRIiWNgGAWjYBAC9gYGAwYQAgMeBhsGBmYGhgNwESyA5wCqljSYFtx6eFAM5GE4DGPi0cLevPFxRYGdHAP72WcSb9vOJ25nZ394gKHgD24tPMeKDc8YJBsz8KSbSc5tu524s5nHAK/D7CVyzCQbDA4kNkiwsUnzArVsOMxDwC/yb8x/Imk5B9TC/gC/FgkeM0YkLQeAWhjwO4yHJ60Y6LBkYzaeNGbLOeeSjYEOMziQYGCMWwv74Y0fG/7YyfGzH2O88abMTnbD+eOPP3z4I4dTCxywofASCGsYBaNgFIyCUYAHAAAslUtzojZHxQAAAABJRU5ErkJggg==","orcid":"","institution":"Università degli Studi di Siena","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Federico","middleName":"","lastName":"Crudu","suffix":""}],"badges":[],"createdAt":"2023-11-08 15:29:41","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3579951/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3579951/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":47793319,"identity":"ccc0235e-1d81-48f8-ab27-7261199ca463","added_by":"auto","created_at":"2023-12-07 14:37:48","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1221468,"visible":true,"origin":"","legend":"","description":"","filename":"EMAsubmission.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3579951/v1_covered_f273e3bf-2d5e-4f32-979c-0a77691997fd.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Aggregation of Experts Judgments for Climate Tipping Points","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Bayesian updating, aggregation of opinions, global warming, judgmental forecasting, Steiner point, tipping points","lastPublishedDoi":"10.21203/rs.3.rs-3579951/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3579951/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis paper introduces a method for the evaluation of the occurrence of tipping points based on the combination of probability intervals from experts judgments elicited in face-to-face interviews. 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