{"id":83270,"date":"2026-10-28T15:32:22","date_gmt":"2026-10-28T14:32:22","guid":{"rendered":"https:\/\/nilu.gnist.dev\/publikasjoner\/estimating-stratospheric-polar-vortex-strength-using-ambient-ocean-generated-infrasound-and-stochastics-based-machine-learning\/"},"modified":"2026-10-28T15:32:22","modified_gmt":"2026-10-28T14:32:22","slug":"estimating-stratospheric-polar-vortex-strength-using-ambient-ocean-generated-infrasound-and-stochastics-based-machine-learning","status":"publish","type":"nva_publication","link":"https:\/\/nilu.gnist.dev\/en\/publications\/estimating-stratospheric-polar-vortex-strength-using-ambient-ocean-generated-infrasound-and-stochastics-based-machine-learning\/","title":{"rendered":"Estimating stratospheric polar vortex strength using ambient ocean-generated infrasound and stochastics-based machine learning"},"content":{"rendered":"<p class=\"wp-block-paragraph\">There are sparse opportunities for direct measurement of upper stratospheric winds, yet improving their representation in subseasonal-to-seasonal prediction models can have significant benefits. There is solid evidence from previous research that global atmospheric infrasound waves are sensitive to stratospheric dynamics. However, there is a lack of results providing a direct mapping between infrasound recordings and polar-cap upper stratospheric winds. The global International Monitoring System (IMS), which monitors compliance with the Comprehensive Nuclear-Test-Ban Treaty, includes ground-based stations that can be used to characterize the infrasound soundscape continuously. In this study, multi-station IMS infrasound data were utilized along with a machine-learning supported stochastic model, Delay-SDE-net, to demonstrate how a near-real-time estimate of the polar-cap averaged zonal wind at 1-hPa pressure level can be found from infrasound data. The infrasound was filtered to a temporal low-frequency regime dominated by microbaroms, which are ambient-noise infrasonic waves continuously radiated into the atmosphere from nonlinear interaction between counter-propagating ocean surface waves. Delay-SDE-net was trained on 5 years (2014\u20132018) of infrasound data from three stations and the ERA5 reanalysis 1-hPa polar-cap averaged zonal wind. Using infrasound in 2019\u20132020 for validation, we demonstrate a prediction of the polar-cap averaged zonal wind, with an error standard deviation of around 12\u2009m\u00b7s compared with ERA5. These findings highlight the potential of using infrasound data for near-real-time measurements of upper stratospheric dynamics. A long-term goal is to improve high-top atmospheric model accuracy, which can have significant implications for weather and climate prediction.<\/p>\n","protected":false},"template":"","meta":{"_acf_changed":false,"_searchwp_excluded":"","_id":"","_status":"PUBLISHED","_sync_date":"2026-10-27 22:00:08","footnotes":""},"nva_tax_category":[927],"class_list":["post-83270","nva_publication","type-nva_publication","status-publish","hentry","nva_tax_category-scientific-journal-publication"],"acf":[],"_links":{"self":[{"href":"https:\/\/nilu.gnist.dev\/en\/wp-json\/wp\/v2\/nva_publication\/83270","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/nilu.gnist.dev\/en\/wp-json\/wp\/v2\/nva_publication"}],"about":[{"href":"https:\/\/nilu.gnist.dev\/en\/wp-json\/wp\/v2\/types\/nva_publication"}],"version-history":[{"count":0,"href":"https:\/\/nilu.gnist.dev\/en\/wp-json\/wp\/v2\/nva_publication\/83270\/revisions"}],"wp:attachment":[{"href":"https:\/\/nilu.gnist.dev\/en\/wp-json\/wp\/v2\/media?parent=83270"}],"wp:term":[{"taxonomy":"nva_tax_category","embeddable":true,"href":"https:\/\/nilu.gnist.dev\/en\/wp-json\/wp\/v2\/nva_tax_category?post=83270"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}