Stochastic Transport in Upper Ocean Dynamics II. STUOD 2022 Workshop, London, UK, September 26–29
Type | Book / Conference proceedings | ||||||||
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Date | 2024 | ||||||||
Language | English | ||||||||
Author(s) | Chapron Bertrand1, Crisan Dan2, Holm Darryl2, Mémin Etienne3, Radomska Anna (eds)2 | ||||||||
Affiliation(s) | 1 : Ifremer, Institut Français de Recherche pour l’Exploitation de la Mer, Plouzané,France 2 : Imperial College London, London,UK 3 : Inria, Institut National de Recherche en Sciences et Technologies du Numérique, Rennes, France |
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DOI | 10.1007/978-3-031-40094-0 | ||||||||
Publisher | Springer Nature Switzerland | ||||||||
Note | Mathematics of Planet Earth : 11. ISSN 2524-4264, E-ISSN 2524-4272. ISBN978-3-031-40093-3, Softcover ISBN 978-3-031-40096-4, eBook ISBN 978-3-031-40094-0 | ||||||||
Keyword(s) | Open Access, mathematics of planet earth, math open access proceedings, STUOD, ocean modelling, ocean observations, stochastic partial differential equations, dynamical systems, data analysis, data assimilation, deep learning | ||||||||
Abstract | This open access proceedings volume brings selected, peer-reviewed contributions presented at the Third Stochastic Transport in Upper Ocean Dynamics (STUOD) 2022 Workshop, held virtually and in person at the Imperial College London, UK, September 26–29, 2022. The STUOD project is supported by an ERC Synergy Grant, and led by Imperial College London, the National Institute for Research in Computer Science and Automatic Control (INRIA) and the French Research Institute for Exploitation of the Sea (IFREMER). The project aims to deliver new capabilities for assessing variability and uncertainty in upper ocean dynamics. It will provide decision makers a means of quantifying the effects of local patterns of sea level rise, heat uptake, carbon storage and change of oxygen content and pH in the ocean. Its multimodal monitoring will enhance the scientific understanding of marine debris transport, tracking of oil spills and accumulation of plastic in the sea. Observations at a high resolution of upper ocean properties such as temperature, salinity, topography, wind, waves and velocity; Large scale numerical simulations; Data-based stochastic equations for upper ocean dynamics that quantify simulation error; Stochastic data assimilation to reduce uncertainty.
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