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STUOD SIGNED

Stochastic Transport in Upper Ocean Dynamics

Total Cost €

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EC-Contrib. €

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Partnership

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 STUOD project word cloud

Explore the words cloud of the STUOD project. It provides you a very rough idea of what is the project "STUOD" about.

statistical    simulation    93    extract    quantify    velocity    salinity    storage    tackle    coordinate    numerical    topography    multimodal    differential    drifters    monitoring    scales    absorbed    trapped    combined    observations    complementary    quantifying    college    inria    accumulation    uncertain    greenhouse    matching    marine    floats    makers    interpret    unresolvable    simulations    decision    perform    dynamics    plastic    71    synergy    skill    transport    partial    tracking    science    network    ensemble    model    data    ph    comprise    expertise    oil    equations    sea    wind    human    world    debris    spills    continued    joint    oxygen    mathematical    goals    temperature    ifremer    warming    error    patterns    engaged    mathematics    stochastic    computer    covered    carbon    situ    ocean    emissions    heat    resolution    reduce    single    spde    upper    cooperation    gas    earth    effort    local    systemic    scientific    satellites    content    correlations    variability    assessing    calibre    assimilation    satellite    accounts    waves    reanalysis    imperial    computational   

Project "STUOD" data sheet

The following table provides information about the project.

Coordinator
IMPERIAL COLLEGE OF SCIENCE TECHNOLOGY AND MEDICINE 

Organization address
address: SOUTH KENSINGTON CAMPUS EXHIBITION ROAD
city: LONDON
postcode: SW7 2AZ
website: http://www.imperial.ac.uk/

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
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 Coordinator Country United Kingdom [UK]
 Total cost 9˙998˙875 €
 EC max contribution 9˙998˙875 € (100%)
 Programme 1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC))
 Code Call ERC-2019-SyG
 Funding Scheme ERC-SyG
 Starting year 2020
 Duration (year-month-day) from 2020-03-01   to  2026-02-28

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    IMPERIAL COLLEGE OF SCIENCE TECHNOLOGY AND MEDICINE UK (LONDON) coordinator 4˙956˙995.00
2    INSTITUT FRANCAIS DE RECHERCHE POUR L'EXPLOITATION DE LA MER FR (PLOUZANE) participant 2˙550˙325.00
3    INSTITUT NATIONAL DE RECHERCHE ENINFORMATIQUE ET AUTOMATIQUE FR (LE CHESNAY CEDEX) participant 2˙491˙555.00

Map

 Project objective

71% of Earth is covered by ocean. The ocean has absorbed 93% of the heat trapped by human’s greenhouse gas emissions. The ocean’s future responses to continued warming are uncertain. Our project will 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. Our approach accounts for transport on scales that are currently unresolvable in computer simulations, yet are observable by satellites, drifters and floats. Four scientific capabilities will be engaged: (i) observations at high resolution of upper ocean properties such as temperature, salinity, topography, wind, waves and velocity; (ii) large scale numerical simulations; (iii) data-based stochastic equations for upper ocean dynamics that quantify simulation error; and (iv) stochastic data assimilation to reduce uncertainty. These four scientific capabilities will tackle a network of joint tasks achieved through cooperation of three world-calibre institutions: IFREMER (ocean observations, reanalysis); INRIA (computational science); and Imperial College (mathematics, data assimilation). Our complementary skill sets comprise a single systemic effort: (1) Coordinate and interpret high-resolution satellite and in situ upper ocean observations (2) Extract correlations from data needed for the mathematical model (3) Perform an ensemble of computer simulations using our new stochastic partial differential equations (SPDE) which are derived by matching the observed statistical properties (4) Apply advanced data assimilation and computer simulations to reduce model uncertainty The key to achieving these goals will be synergy in our combined expertise.

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The information about "STUOD" are provided by the European Opendata Portal: CORDIS opendata.

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