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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.

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

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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