A General Linear Model to Describe Observed Global Warming as a Function of the Atmospheric Surface Concentrations of Greenhouse Gases and Greenhouse Constants

A General Linear Model to Describe Observed Global Warming as a Function of the Atmospheric Surface Concentrations of Greenhouse Gases and Greenhouse Constants | 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 A General Linear Model to Describe Observed Global Warming as a Function of the Atmospheric Surface Concentrations of Greenhouse Gases and Greenhouse Constants Rasmus Friberg This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4918162/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 is the first paper in a series of papers with the overall aim of analyzing and deriving theoretical models to indirectly measure and test the root cause of observed global warming (GW) and the greenhouse effect (GHE) at the earth’s surface due to the atmospheric concentration of greenhouse gases (GHGs) in general and the mass of anthropogenic CO 2 emissions (MACE) in particular. The objective of this specific paper is to present a new theoretical model, which is the framework theory and the starting point for explaining the relationship between observed global warming (GW) and the atmospheric concentrations of greenhouse gases (GHGs). It is derived from the theory of Lambert–Beer–Bouger’s law, Planck’s law and the heat balance over the atmospheric surface layer, where the GW is measured. The result is called the general linear model of GW (GLMGW). Consequently, the GLMGW indicates that there is a linear relationship between the observed GW (or GAST-global atmospheric surface temperature) and the GHG atmospheric surface concentrations. The characteristic constants of the GLMGW are the greenhouse constants for each GHG, which is a measure of how much the temperature rises per atmospheric concentration of a given greenhouse gas. The claims originating from the GLMGW were tested directly or indirectly in subsequent papers (Evidences I-V) based on the global data series of temperature and atmospheric GHG concentrations obtained from NOAA, ECMWF and GCP. Several new practical validated measurement models are available for calculating and forecasting GW as a function of the dominant GHGs. The different models can be used with high measurement certainty and forecasting capability to estimate several different quantities in the context of the GW; for example, the global atmospheric surface temperature anomaly (GASTA) can be used as a function of the atmospheric CO 2 concentration, and the remaining time and remaining MACE can be used to breach the 1.5K and 2.0K limits. Climate Analysis and Modeling Climatology Atmospheric Sciences global atmospheric surface temperature anomaly global warming greenhouse effect Keeling curve greenhouse gases CO2 radiative forcing climate sensitivity Full Text Additional Declarations The authors declare no competing interests. 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. 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-4918162","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":340614828,"identity":"171c1360-b7b1-42a7-9bc4-c213ee708155","order_by":0,"name":"Rasmus Friberg","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA1UlEQVRIie3PoQ7CMBCA4cNQc8nsLRCe4VBAsoRXmQJTAoogIYgJhucx9ggoZookYZlhhhkEEjFBG4IdxZHQP2la0S+9ArhcP9odGEBES33kvpVo7AxBtTeEbIkOz6HZLEgvSov1YgZT9MtT8pgReNEmrCVtJbsrxTCIW3KexXowUseklhBIUSwZeNiSozNqwjT5QLyyWBmCvhpllRWhsPsiJA653St0M4QYUTbzNhN+/os31oNVAaNIr9mtCjpetK0nb6kXsjmhzfV34vLNbZfL5fqjnqFsQHtr8LIFAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0009-0008-7436-708X","institution":"","correspondingAuthor":true,"prefix":"","firstName":"Rasmus","middleName":"","lastName":"Friberg","suffix":""}],"badges":[],"createdAt":"2024-08-15 08:48:06","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-4918162/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4918162/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":63324918,"identity":"aa068dca-640e-404f-81bb-91e2388014b7","added_by":"auto","created_at":"2024-08-27 02:41:26","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":670455,"visible":true,"origin":"","legend":"","description":"","filename":"GLMGW240820.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4918162/v1_covered_dd30a224-dbaf-4a24-9eb8-a049c4da2d1f.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eA General Linear Model to Describe Observed Global Warming as a Function of the Atmospheric Surface Concentrations of Greenhouse Gases and Greenhouse Constants\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Independent researcher","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":"global atmospheric surface temperature anomaly, global warming, greenhouse effect, Keeling curve, greenhouse gases, CO2, radiative forcing, climate sensitivity","lastPublishedDoi":"10.21203/rs.3.rs-4918162/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4918162/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis is the first paper in a series of papers with the overall aim of analyzing and deriving theoretical models to indirectly measure and test the root cause of observed global warming (GW) and the greenhouse effect (GHE) at the earth\u0026rsquo;s surface due to the atmospheric concentration of greenhouse gases (GHGs) in general and the mass of anthropogenic CO\u003csub\u003e2\u003c/sub\u003e emissions (MACE) in particular. 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The claims originating from the GLMGW were tested directly or indirectly in subsequent papers (Evidences I-V) based on the global data series of temperature and atmospheric GHG concentrations obtained from NOAA, ECMWF and GCP. Several new practical validated measurement models are available for calculating and forecasting GW as a function of the dominant GHGs. The different models can be used with high measurement certainty and forecasting capability to estimate several different quantities in the context of the GW; for example, the global atmospheric surface temperature anomaly (GASTA) can be used as a function of the atmospheric CO\u003csub\u003e2\u003c/sub\u003e concentration, and the remaining time and remaining MACE can be used to breach the 1.5K and 2.0K limits.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e","manuscriptTitle":"A General Linear Model to Describe Observed Global Warming as a Function of the Atmospheric Surface Concentrations of Greenhouse Gases and Greenhouse Constants","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-27 02:33:18","doi":"10.21203/rs.3.rs-4918162/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","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}}],"origin":"","ownerIdentity":"7dd79921-ba18-43a5-b568-7faac9e27d69","owner":[],"postedDate":"August 27th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":36407540,"name":"Climate Analysis and Modeling"},{"id":36407541,"name":"Climatology"},{"id":36407542,"name":"Atmospheric Sciences"}],"tags":[],"updatedAt":"2024-08-27T02:33:18+00:00","versionOfRecord":[],"versionCreatedAt":"2024-08-27 02:33:18","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4918162","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4918162","identity":"rs-4918162","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}