Floating-parcel clustering induced by the multi-scale dynamics on the Subpolar Front of the Sea of Japan

Floating-parcel clustering induced by the multi-scale dynamics on the Subpolar Front of the Sea of Japan | 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 Floating-parcel clustering induced by the multi-scale dynamics on the Subpolar Front of the Sea of Japan Konstantin Koshel, Dmitrii Stepanov, Pavel Berloff This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9561696/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract This study investigated clustering of floating tracer in an eddy-resolving solution of comprehensive general circulation model (GCM). The tracer was represented by Lagrangian particles carrying both density and area characteristics, which evolve and characterize clustering. By decomposing the dynamically constrained flow velocity into the commonly used geostrophic and ageostrophic components, so that the latter contains partially resolved submesoscale motions, we uncovered specific roles played by these components in the clustering process, for the first time. The ageostrophic flow is responsible for the clustering, due to the velocity divergence, whereas the geostrophic flow component tends to weaken the clustering via chaotic stirring.These results are broadly consistent with the earlier kinematic, idealized studies, but here, for the first time, we not only considered comprehensive GCM solution but also carried out the corresponding in-depth analyses.Finally, to illuminate important links with the kinematic studies and existing theories, we strengthened our results by considering the clustering in a stochastic velocity field tuned to represent ageostrophic flow component eddy-resolving numerical simulations Lagrangian framework clustering stochastic model Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 09 May, 2026 Reviewers agreed at journal 09 May, 2026 Reviewers agreed at journal 07 May, 2026 Reviewers invited by journal 07 May, 2026 Editor assigned by journal 30 Apr, 2026 Submission checks completed at journal 30 Apr, 2026 First submitted to journal 29 Apr, 2026 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-9561696","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":632649691,"identity":"b6f10d30-af17-48e2-9966-33b55d27ca2d","order_by":0,"name":"Konstantin Koshel","email":"","orcid":"","institution":"V.I. 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