{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/quasi-objective-eddy-visualization-from","title":"Quasi-Objective Eddy Visualization from Sparse Drifter Data","arxiv_id":"2111.14117","date":"2021-11-28","proceeding":null,"authors":["Alex P. Encinas Bartos","Nikolas O. Aksamit","George Haller"],"abstract":"We employ a recently developed single-trajectory Lagrangian diagnostic tool, the trajectory rotation average $ (\\mathrm{\\overline{TRA}}) $, to visualize oceanic vortices (or eddies) from sparse drifter data. We apply the $ \\mathrm{\\overline{TRA}} $ to two drifter data sets that cover various oceanographic scales: the Grand Lagrangian Deployment (GLAD) and the Global Drifter Program (GDP). Based on the $ \\mathrm{\\overline{TRA}} $, we develop a general algorithm that extracts approximate eddy boundaries. We find that the $ \\mathrm{\\overline{TRA}} $ outperforms other available single-trajectory-based eddy detection methodologies on sparse drifter data and identifies eddies on scales that are unresolved by satellite-altimetry.","url_abs":"https://arxiv.org/abs/2111.14117v4","url_pdf":"https://arxiv.org/pdf/2111.14117v4.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"links_only","authors_date_abstract":"arXiv metadata, CC0 1.0 (https://info.arxiv.org/help/license), from the Kaggle arXiv metadata snapshot of 2026-09-12"},"code_links":[{"paper_slug":"quasi-objective-eddy-visualization-from","repo_url":"https://github.com/encinasbartos/quasiobjectiveeddyvisualizationfromsparsedrifterdata","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}