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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.

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

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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