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    Stochastic Transport in Upper Ocean Dynamics II

    STUOD 2022 Workshop, London, UK, September 26–29

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    Contributor(s)
    Chapron, Bertrand (editor)
    Crisan, Dan (editor)
    Holm, Darryl (editor)
    Mémin, Etienne (editor)
    Radomska, Anna (editor)
    Language
    English
    Show full item record
    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. All topics of these proceedings are essential to the scientific foundations of oceanography which has a vital role in climate science. Studies convened in this volume focus on a range of fundamental areas, including: 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. These fundamental subjects in modern science and technology are urgently required in order to meet the challenges of climate change faced today by human society. This proceedings volume represents a lasting legacy of crucial scientific expertise to help meet this ongoing challenge, for the benefit of academics and professionals in pure and applied mathematics, computational science, data analysis, data assimilation and oceanography.
    URI
    https://library.oapen.org/handle/20.500.12657/76747
    Keywords
    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
    DOI
    10.1007/978-3-031-40094-0
    ISBN
    9783031400940, 9783031400933, 9783031400940
    Publisher
    Springer Nature
    Publisher website
    https://www.springernature.com/gp/products/books
    Publication date and place
    Cham, 2024
    Grantor
    • Horizon 2020 Framework Programme - [...]
    Imprint
    Springer Nature Switzerland
    Series
    Mathematics of Planet Earth, 11
    Pages
    338
    Rights
    http://creativecommons.org/licenses/by/4.0/
    • Imported or submitted locally

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    License

    • If not noted otherwise all contents are available under Attribution 4.0 International (CC BY 4.0)

    Credits

    • logo EU
    • This project received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 683680, 810640, 871069 and 964352.

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