Exploring CME–Sunspot Correlations Through Multi-Variable Statistical Analysis of CME Parameters

Exploring CME–Sunspot Correlations Through Multi-Variable Statistical Analysis of CME Parameters | 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 Exploring CME–Sunspot Correlations Through Multi-Variable Statistical Analysis of CME Parameters Juan Rafael Jiménez Sanabria, Daniel Felipe Pineda Cruz, Martín Mauricio Medina Lesmes This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7586808/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 Coronal mass ejections (CMEs) are among the most energetic solar phenomena, and their link to sunspot activity—the standard proxy of magnetic variability—is key for forecasting space weather. Previous studies reported correlations but relied mainly on coarse averages and heterogeneous populations. Here, we present a multivariate statistical analysis of CME occurrence rates and sunspot numbers (SSN) across Solar Cycles 23–25 (1996–2024). Our methodology incorporates systematic population stratification by angular width, dynamic velocity thresholds, and bootstrap confidence intervals to ensure statistical robustness. Two distinct regimes emerge. At the annual scale, the strongest correlations occur at velocities above the mean CME speed (scaling factors 1.17–1.34), with values up to r ≈ 0.97. At the monthly scale, however, the pattern reverses: slower CMEs exhibit the closest correspondence with SSN. Solar Cycle 24, in particular, displays exceptionally high correlations at very low velocity ranges. Extending this approach to Solar Cycle 25 (2020–2024), we find that even during its ascending and early-maximum phases, correlations remain strong (r > 0.9 at monthly resolution). These findings demonstrate that CME–sunspot coupling depends both on temporal resolution and on CME subpopulation. They further establish a physically grounded framework for translating sunspot based solar cycle predictions into targeted CME occurrence forecasts, thereby enhancing the predictive toolkit for space weather. Coronal Mass Ejections (CMEs) Sunspot Numbers (SSN) Solar Cycles 23–25 CME–sunspot correlations Space weather forecasting 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-7586808","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":514234297,"identity":"6c2bbfea-c68f-4667-b38e-2ed3c4258411","order_by":0,"name":"Juan Rafael Jiménez Sanabria","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABCElEQVRIiWNgGAWjYBACxgYQySMB4SX+s4GKsxGr5QNbGlQ1Hi2o+mewHSashXlG8rMHDDIW0fzSzYc/8/CcT9wu3/yA4UPZYQb+9gYcBqeZGwAdljtzzrEEYx6J24k729gMGGecO8wgceYADi0JZhIgLRtu5Bgk8xjcTtxwjIeBmbftMIOBRAIOLenfwFr238j/cJgn4RxEy1+8WnKgtkjkMDbOOHAAooURn5aeN2USCUAtM26kGTN8bEg23tmWZnCw51w6Dy6/GLanb5P42FOX2z8j+fGHxAY72e3Mhx8++FFmLYcrxAxBwok9SCIGQAwyngereiCQB5M/0LSMglEwCkbBKEAGAFK3XMMK1AhfAAAAAElFTkSuQmCC","orcid":"","institution":"Pedagogical and Technological University of Colombia","correspondingAuthor":true,"prefix":"","firstName":"Juan","middleName":"Rafael Jiménez","lastName":"Sanabria","suffix":""},{"id":514234298,"identity":"a2524b35-9791-4c8d-8877-d13ded1601d6","order_by":1,"name":"Daniel Felipe Pineda Cruz","email":"","orcid":"","institution":"Pedagogical and Technological University of Colombia","correspondingAuthor":false,"prefix":"","firstName":"Daniel","middleName":"Felipe Pineda","lastName":"Cruz","suffix":""},{"id":514234299,"identity":"b1750e93-6c0f-4b7c-a234-cb0a2f7df12c","order_by":2,"name":"Martín Mauricio Medina Lesmes","email":"","orcid":"","institution":"Pedagogical and Technological University of Colombia","correspondingAuthor":false,"prefix":"","firstName":"Martín","middleName":"Mauricio Medina","lastName":"Lesmes","suffix":""}],"badges":[],"createdAt":"2025-09-11 02:08:15","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7586808/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7586808/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":98622028,"identity":"c5a09b51-0fb3-4c0d-ac7d-9bcb1a345970","added_by":"auto","created_at":"2025-12-19 16:42:12","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":364229,"visible":true,"origin":"","legend":"","description":"","filename":"ExploringCMESunspotCorrelationsThroughMultiVariableStatisticalAnalysisofCMEParameters21.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7586808/v1_covered_a00ac209-b178-42d1-ac17-2e94bb1e99cc.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Exploring CME–Sunspot Correlations Through Multi-Variable Statistical Analysis of CME Parameters","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"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":"Coronal Mass Ejections (CMEs), Sunspot Numbers (SSN), Solar Cycles 23–25, CME–sunspot correlations, Space weather forecasting","lastPublishedDoi":"10.21203/rs.3.rs-7586808/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7586808/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eCoronal mass ejections (CMEs) are among the most energetic solar phenomena, and their link to sunspot activity—the standard proxy of magnetic variability—is key for forecasting space weather. Previous studies reported correlations but relied mainly on coarse averages and heterogeneous populations. Here, we present a multivariate statistical analysis of CME occurrence rates and sunspot numbers (SSN) across Solar Cycles 23–25 (1996–2024). Our methodology incorporates systematic population stratification by angular width, dynamic velocity thresholds, and bootstrap confidence intervals to ensure statistical robustness. Two distinct regimes emerge. At the annual scale, the strongest correlations occur at velocities above the mean CME speed (scaling factors 1.17–1.34), with values up to r ≈ 0.97. At the monthly scale, however, the pattern reverses: slower CMEs exhibit the closest correspondence with SSN. Solar Cycle 24, in particular, displays exceptionally high correlations at very low velocity ranges. Extending this approach to Solar Cycle 25 (2020–2024), we find that even during its ascending and early-maximum phases, correlations remain strong (r \u0026gt; 0.9 at monthly resolution). These findings demonstrate that CME–sunspot coupling depends both on temporal resolution and on CME subpopulation. 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