Inter-comparison of plume model mass eruption rate predictions based on the 2010 Eyjafjallajökull eruption

Inter-comparison of plume model mass eruption rate predictions based on the 2010 Eyjafjallajökull eruption | 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 Inter-comparison of plume model mass eruption rate predictions based on the 2010 Eyjafjallajökull eruption Morgan Hetherington, Fabio Dioguardi, Tobias Dürig, Alan Cuthbertson, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7330551/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 During explosive eruptions, integral plume models are typically used to estimate real-time source parameters (e.g. mass eruption rate, plume height, and total grain size distribution) which are crucial for initiating tephra dispersal models and subsequently providing ash concentration forecasts for the aviation industry. However, uncertainties within integral models can significantly affect the accuracy of these estimates. Uncertainties may arise from the inclusion of additional parameters in more complex models, or from assumptions such as steady-state source conditions during inherently unsteady eruptions. This paper compares two integral plume models of differing complexity, FPLUME (by Folch et al., 2016) and REFIR (by Dürig et al., 2018; Dioguardi et al., 2020), to evaluate how well they replicate the mass eruption rate of the unsteady 2010 Eyjafjallajökull eruption in Iceland. In doing so, the aim is to evaluate whether the use of additional input parameters provides improved model accuracy when predicting mass eruption rates, and whether integral models can effectively capture unsteady source behaviour. Results highlight trade-offs between model complexity, parameter sensitivity, and the ability of integral frameworks to represent time-dependent processes in real time. Greater model complexity does not necessarily yield improved mass eruption rate predictions; instead, accurate parameterisation of the entrainment coefficient β is identified as the most crucial factor for improvement. Explosive eruptions unsteadiness mass eruption rate plume entrainment coefficients integral models Full Text Supplementary Files supplementarynomenclatureandlistofabbreviations.docx 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. 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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-7330551","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":516074815,"identity":"089f32d9-b2d1-4673-88ba-750389e5a449","order_by":0,"name":"Morgan 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eruption\u003c/p\u003e","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":"Explosive eruptions, unsteadiness, mass eruption rate, plume entrainment coefficients, integral models ","lastPublishedDoi":"10.21203/rs.3.rs-7330551/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7330551/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eDuring explosive eruptions, integral plume models are typically used to estimate real-time source parameters (e.g. mass eruption rate, plume height, and total grain size distribution) which are crucial for initiating tephra dispersal models and subsequently providing ash concentration forecasts for the aviation industry. However, uncertainties within integral models can significantly affect the accuracy of these estimates. Uncertainties may arise from the inclusion of additional parameters in more complex models, or from assumptions such as steady-state source conditions during inherently unsteady eruptions. This paper compares two integral plume models of differing complexity, FPLUME (by Folch et al., 2016) and REFIR (by D\u0026uuml;rig et al., 2018; Dioguardi et al., 2020), to evaluate how well they replicate the mass eruption rate of the unsteady 2010 Eyjafjallaj\u0026ouml;kull eruption in Iceland. In doing so, the aim is to evaluate whether the use of additional input parameters provides improved model accuracy when predicting mass eruption rates, and whether integral models can effectively capture unsteady source behaviour. Results highlight trade-offs between model complexity, parameter sensitivity, and the ability of integral frameworks to represent time-dependent processes in real time. Greater model complexity does not necessarily yield improved mass eruption rate predictions; instead, accurate parameterisation of the entrainment coefficient \u003cem\u003eβ\u003c/em\u003e is identified as the most crucial factor for improvement.\u003c/p\u003e","manuscriptTitle":"Inter-comparison of plume model mass eruption rate predictions based on the 2010 Eyjafjallajökull eruption","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-25 11:34:19","doi":"10.21203/rs.3.rs-7330551/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":"d547071f-9066-4298-ade2-bbaa03500781","owner":[],"postedDate":"September 25th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-12-01T17:58:28+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-25 11:34:19","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7330551","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7330551","identity":"rs-7330551","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}