Influence of individual models and studies on quantitative mitigation findings in the IPCC Sixth Assessment Report

Influence of individual models and studies on quantitative mitigation findings in the IPCC Sixth Assessment Report | 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 Influence of individual models and studies on quantitative mitigation findings in the IPCC Sixth Assessment Report Ida Sognnaes, Glen Peters This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5698716/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 02 Oct, 2025 Read the published version in Nature Communications → Version 1 posted You are reading this latest preprint version Abstract Quantitative mitigation findings based on emissions scenarios submitted to the Intergovernmental Panel on Climate Change (IPCC) play an authoritative role in climate policy and decision making. We analyse the impact of the uneven representation of models and modelling studies in the IPCC Sixth Assessment Report (AR6) on statistical values that are used to present quantitative mitigation findings. We find that several key AR6 findings are influenced considerably by the model with the most scenarios, including emissions reductions by 2030 and the decline in fossil fuels consistent with 1.5°C, and we find that the year of net-zero greenhouse gas emissions is influenced considerably by both the model and the study with the most scenarios. We find that weighting by model- or study does not provide a straightforward solution and discuss three issues related to the use of database statistics to present emissions scenarios findings. Based on our findings and informed by the purpose of the IPCC and the kinds of insights that can be obtained from emissions scenarios, we suggest improvements to the current practices used in IPCC assessments. Earth and environmental sciences/Climate sciences/Climate change/Climate-change mitigation Earth and environmental sciences/Environmental social sciences/Climate-change mitigation Earth and environmental sciences/Environmental social sciences/Climate-change policy Earth and environmental sciences/Environmental social sciences/Socioeconomic scenarios Scientific community and society/Scientific community/Research management Full Text Additional Declarations There is NO Competing Interest. Supplementary Files SINCom20241223.pdf Supplementary Information to ‘Influence of individual models and studies on quantitative mitigation findings in the IPCC Sixth Assessment Report’ SupplementaryData1.xlsx Supplementary Dataset 1 SupplementaryData2.xlsx Supplementary Dataset 2 Cite Share Download PDF Status: Published Journal Publication published 02 Oct, 2025 Read the published version in Nature Communications → 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. 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-5698716","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":400637704,"identity":"20e19924-d8ea-4c9e-916f-756026078c96","order_by":0,"name":"Ida 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