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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.

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

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
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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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