Large spread in interannual Variance of atmospheric CO2 concentration across CMIP6 Earth System Models

Large spread in interannual Variance of atmospheric CO2 concentration across CMIP6 Earth System Models | 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 Large spread in interannual Variance of atmospheric CO2 concentration across CMIP6 Earth System Models Veronica Martin-Gomez, Yohan Ruprich-Robert, Etienne Tourigny, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3009767/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 09 Dec, 2023 Read the published version in npj Climate and Atmospheric Science → Version 1 posted 8 You are reading this latest preprint version Abstract Numerical Earth System Models (ESMs) are our best tool to predict the evolution of atmospheric CO2 concentration and its effect on Global temperature. However, large uncertainties exist among ESMs in the year-to-year variations of atmospheric CO2 concentration. This prevents us from precisely understanding its past evolution and from accurately estimating its future evolution. Here we analyze various ESMs simulations from the 6th Coupled Model Intercomparison Projects (CMIP6) to understand the origins of the inter-model uncertainty in the interannual variability of the atmospheric CO2 concentration. We show that most of this uncertainty is coming from the simulation of the land CO2 flux internal variability. Although models agree that those variations are driven by El Niño Southern Oscillation (ENSO), similar ENSO-related surface temperature and precipitation teleconnections across models drive different land CO2 fluxes, pointing to the land vegetation models as the dominant source of the inter-model uncertainty. Earth and environmental sciences/Biogeochemistry Earth and environmental sciences/Climate sciences internal variability CO2 CMIP6 inter-model uncertainties verification Paris Agreement Implementation Full Text Additional Declarations (Not answered) Supplementary Files SupplementaryMaterialMartinGomeznpj.pdf Cite Share Download PDF Status: Published Journal Publication published 09 Dec, 2023 Read the published version in npj Climate and Atmospheric Science → Version 1 posted Editorial decision: revise 11 Aug, 2023 Review # 1 received at journal 03 Aug, 2023 Reviewer # 1 agreed at journal 11 Jul, 2023 Reviewers invited by journal 07 Jun, 2023 Editor assigned by journal 06 Jun, 2023 Submission checks completed at journal 05 Jun, 2023 First submitted to journal 02 Jun, 2023 Unknown event 02 Jun, 2023 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-3009767","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":207593833,"identity":"7b401972-2640-4ed2-9129-fbc1f92b9616","order_by":0,"name":"Veronica 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