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    The Application of Uncertainty Quantification Techniques and Information Theory to Oil Spill and Ocean Forecasting.

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    Date
    2017
    Author
    Wang, Shitao
    Status
    Published
    
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    Abstract
    Quantifying uncertainties in ocean current forecasts is an important component of formulating a response to an oil spill, e.g. to compute the anticipated oil trajectories. Polynomial Chaos (PC) methods have recently been used to quantify uncertainties in the circulation forecast of the Gulf of Mexico caused by uncertain initial conditions and wind forcing data. The input uncertainties consisted of the amplitudes of perturbation modes whose space-time structure was obtained from Empirical Orthogonal Functions (EOF) decompositions. These e orts were the rst to rely on a PC approach to e ciently quantify uncertainties in an ocean model, and as such have raised a number of issues that we wish to address, namely the realism of the perturbations, the e ective choices in choosing the uncertain variables, the information trade-o s of the di erent uncertain input choices, and the ability to reduce these uncertainties if observational data is available. We explore whether these EOF-.....
    Resource URL
    https://scholarlyrepository.miami.edu/oa_dissertations/1931
    Publisher
    University of Miami (PhD Thesis)
    Coral Gables, Florida
    Document Language
    en
    Sustainable Development Goals (SDG)
    14.A
    Best Practice Type
    Manual (incl. handbook, guide, cookbook etc)
    Citation
    Wang, S. (2017) The Application of Uncertainty Quantification Techniques and Information Theory to Oil Spill and Ocean Forecasting. University of Miami, PhD Thesis, 118pp. (Open Access Dissertations 1931) DOI: http://dx.doi.org/10.25607/OBP-951
    URI
    http://hdl.handle.net/11329/1448
    http://dx.doi.org/10.25607/OBP-951
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