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    Using MM5 to Hindcast the Ocean Surface Forcing Fields over the Gulf of Maine and Georges Bank Region

    Source: Journal of Atmospheric and Oceanic Technology:;2005:;volume( 022 ):;issue: 002::page 131
    Author:
    Chen, Changsheng
    ,
    Beardsley, R. C.
    ,
    Hu, Song
    ,
    Xu, Qichun
    ,
    Lin, Huichan
    DOI: 10.1175/JTECH-1682.1
    Publisher: American Meteorological Society
    Abstract: The fifth-generation Pennsylvania State University?NCAR Mesoscale Model (MM5) is applied to the Gulf of Maine/Georges Bank (GoM/GB) region. This model is configured with two numerical domains with horizontal resolutions of 30 and 10 km, respectively, and driven by the NCAR-Eta weather model through a nested grid approach. Comparison of model-computed winds, wind stress, and heat flux with in situ data collected on moored meteorological buoys in the western GoM and over GB in 1995 shows that during the passage of atmospheric fronts over this region, MM5 provides a reasonable prediction of wind speed but not wind direction, and provides a relatively accurate estimation of longwave radiation but overestimates sensible and latent fluxes. The nudging data assimilation approach with inclusion of in situ wind data significantly improves the accuracy of the predicted wind speed and direction. Incorporation of the Fairall et al. air?sea flux algorithms with inclusion of Advanced Very High Resolution Radiometer (AVHRR)-derived SST improves the accuracy of the predicted latent and sensible heat fluxes in the GoM/GB region for both stable and unstable weather conditions.
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      Using MM5 to Hindcast the Ocean Surface Forcing Fields over the Gulf of Maine and Georges Bank Region

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4227361
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    • Journal of Atmospheric and Oceanic Technology

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    contributor authorChen, Changsheng
    contributor authorBeardsley, R. C.
    contributor authorHu, Song
    contributor authorXu, Qichun
    contributor authorLin, Huichan
    date accessioned2017-06-09T17:22:39Z
    date available2017-06-09T17:22:39Z
    date copyright2005/02/01
    date issued2005
    identifier issn0739-0572
    identifier otherams-84066.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4227361
    description abstractThe fifth-generation Pennsylvania State University?NCAR Mesoscale Model (MM5) is applied to the Gulf of Maine/Georges Bank (GoM/GB) region. This model is configured with two numerical domains with horizontal resolutions of 30 and 10 km, respectively, and driven by the NCAR-Eta weather model through a nested grid approach. Comparison of model-computed winds, wind stress, and heat flux with in situ data collected on moored meteorological buoys in the western GoM and over GB in 1995 shows that during the passage of atmospheric fronts over this region, MM5 provides a reasonable prediction of wind speed but not wind direction, and provides a relatively accurate estimation of longwave radiation but overestimates sensible and latent fluxes. The nudging data assimilation approach with inclusion of in situ wind data significantly improves the accuracy of the predicted wind speed and direction. Incorporation of the Fairall et al. air?sea flux algorithms with inclusion of Advanced Very High Resolution Radiometer (AVHRR)-derived SST improves the accuracy of the predicted latent and sensible heat fluxes in the GoM/GB region for both stable and unstable weather conditions.
    publisherAmerican Meteorological Society
    titleUsing MM5 to Hindcast the Ocean Surface Forcing Fields over the Gulf of Maine and Georges Bank Region
    typeJournal Paper
    journal volume22
    journal issue2
    journal titleJournal of Atmospheric and Oceanic Technology
    identifier doi10.1175/JTECH-1682.1
    journal fristpage131
    journal lastpage145
    treeJournal of Atmospheric and Oceanic Technology:;2005:;volume( 022 ):;issue: 002
    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