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    North Sea Wave Analysis Using Data Assimilation and Mesoscale Model Forcing Winds

    Source: Journal of Waterway, Port, Coastal, and Ocean Engineering:;2018:;Volume ( 144 ):;issue: 004
    Author:
    Caires S.;Marseille G. J.;Verlaan M.;Stoffelen A.
    DOI: 10.1061/(ASCE)WW.1943-5460.0000439
    Publisher: American Society of Civil Engineers
    Abstract: This article explores the use of the ensemble Kalman filter technique to improve the accuracy of North Sea wave field analyses. A nonhydrostatic convective-permitting mesoscale model was used to provide high-resolution forcing winds. These were adjusted by assimilating measurements of offshore wave heights directly into the wave model state. The ensemble Kalman filter data assimilation was shown to be very efficient, leading (compared to the results without data assimilation) to large reductions (up to 6%) in the root-mean-square error of the offshore wave heights and other model state variables, also (up to 4%) at locations other than those of the observations used.
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      North Sea Wave Analysis Using Data Assimilation and Mesoscale Model Forcing Winds

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4248183
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    • Journal of Waterway, Port, Coastal, and Ocean Engineering

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    contributor authorCaires S.;Marseille G. J.;Verlaan M.;Stoffelen A.
    date accessioned2019-02-26T07:36:08Z
    date available2019-02-26T07:36:08Z
    date issued2018
    identifier other%28ASCE%29WW.1943-5460.0000439.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4248183
    description abstractThis article explores the use of the ensemble Kalman filter technique to improve the accuracy of North Sea wave field analyses. A nonhydrostatic convective-permitting mesoscale model was used to provide high-resolution forcing winds. These were adjusted by assimilating measurements of offshore wave heights directly into the wave model state. The ensemble Kalman filter data assimilation was shown to be very efficient, leading (compared to the results without data assimilation) to large reductions (up to 6%) in the root-mean-square error of the offshore wave heights and other model state variables, also (up to 4%) at locations other than those of the observations used.
    publisherAmerican Society of Civil Engineers
    titleNorth Sea Wave Analysis Using Data Assimilation and Mesoscale Model Forcing Winds
    typeJournal Paper
    journal volume144
    journal issue4
    journal titleJournal of Waterway, Port, Coastal, and Ocean Engineering
    identifier doi10.1061/(ASCE)WW.1943-5460.0000439
    page4018005
    treeJournal of Waterway, Port, Coastal, and Ocean Engineering:;2018:;Volume ( 144 ):;issue: 004
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian