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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.

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

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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