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    Predictability of SST-Modulated Westerly Wind Bursts

    Source: Journal of Climate:;2009:;volume( 022 ):;issue: 014::page 3894
    Author:
    Gebbie, Geoffrey
    ,
    Tziperman, Eli
    DOI: 10.1175/2009JCLI2516.1
    Publisher: American Meteorological Society
    Abstract: Westerly wind bursts (WWBs), a significant player in ENSO dynamics, are modeled using an observationally motivated statistical approach that relates the characteristics of WWBs to the large-scale sea surface temperature. Although the WWB wind stress at a given location may be a nonlinear function of SST, the characteristics of WWBs are well described as a linear function of SST. Over 50% of the interannual variance in the WWB likelihood, zonal location, duration, and fetch is explained by changes in SST. The model captures what is seen in a 17-yr record of satellite-derived winds: the eastward migration and increased occurrence of wind bursts as the western Pacific warm pool extends. The WWB model shows significant skill in predicting the interannual variability of the characteristics of WWBs, while the prediction skill of the WWB seasonal cycle is limited by the record length of available data. The novel formulation of the WWB model can be implemented in a stochastic or deterministic mode, where the deterministic mode predicts the ensemble-mean WWB characteristics. Therefore, the WWB model is especially appropriate for ensemble prediction experiments with existing ENSO models that are not capable of simulating realistic WWBs on their own. Should only the slowly varying component of WWBs be important for ENSO prediction, this WWB model allows a shortcut to directly compute the slowly varying ensemble-mean wind field without performing many realizations.
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      Predictability of SST-Modulated Westerly Wind Bursts

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4210218
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    contributor authorGebbie, Geoffrey
    contributor authorTziperman, Eli
    date accessioned2017-06-09T16:28:50Z
    date available2017-06-09T16:28:50Z
    date copyright2009/07/01
    date issued2009
    identifier issn0894-8755
    identifier otherams-68638.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4210218
    description abstractWesterly wind bursts (WWBs), a significant player in ENSO dynamics, are modeled using an observationally motivated statistical approach that relates the characteristics of WWBs to the large-scale sea surface temperature. Although the WWB wind stress at a given location may be a nonlinear function of SST, the characteristics of WWBs are well described as a linear function of SST. Over 50% of the interannual variance in the WWB likelihood, zonal location, duration, and fetch is explained by changes in SST. The model captures what is seen in a 17-yr record of satellite-derived winds: the eastward migration and increased occurrence of wind bursts as the western Pacific warm pool extends. The WWB model shows significant skill in predicting the interannual variability of the characteristics of WWBs, while the prediction skill of the WWB seasonal cycle is limited by the record length of available data. The novel formulation of the WWB model can be implemented in a stochastic or deterministic mode, where the deterministic mode predicts the ensemble-mean WWB characteristics. Therefore, the WWB model is especially appropriate for ensemble prediction experiments with existing ENSO models that are not capable of simulating realistic WWBs on their own. Should only the slowly varying component of WWBs be important for ENSO prediction, this WWB model allows a shortcut to directly compute the slowly varying ensemble-mean wind field without performing many realizations.
    publisherAmerican Meteorological Society
    titlePredictability of SST-Modulated Westerly Wind Bursts
    typeJournal Paper
    journal volume22
    journal issue14
    journal titleJournal of Climate
    identifier doi10.1175/2009JCLI2516.1
    journal fristpage3894
    journal lastpage3909
    treeJournal of Climate:;2009:;volume( 022 ):;issue: 014
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
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