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    Growth of Forecast Errors from Covariances Modeled by 4DVAR and ETKF Methods 

    Source: Monthly Weather Review:;2010:;volume( 139 ):;issue: 005:;page 1505
    Author(s): Piccolo, Chiara
    Publisher: American Meteorological Society
    Abstract: umerical weather forecasting errors grow with time. Error growth results from the amplification of small perturbations due to atmospheric instability or from model deficiencies during model integration. In current NWP ...
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    Ensemble Data Assimilation Using a Unified Representation of Model Error 

    Source: Monthly Weather Review:;2015:;volume( 144 ):;issue: 001:;page 213
    Author(s): Piccolo, Chiara; Cullen, Mike
    Publisher: American Meteorological Society
    Abstract: natural way to set up an ensemble forecasting system is to use a model with additional stochastic forcing representing the model error and to derive the initial uncertainty by using an ensemble of analyses generated with ...
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    Use of the Information Content in Satellite Measurements for an Efficient Interface to Data Assimilation 

    Source: Monthly Weather Review:;2008:;volume( 136 ):;issue: 007:;page 2633
    Author(s): Migliorini, Stefano; Piccolo, Chiara; Rodgers, Clive D.
    Publisher: American Meteorological Society
    Abstract: Satellite observations are the most assimilated data type by operational meteorological centers. Spaceborne instruments can make measurements all over the globe and provide observations for assimilation even where the ...
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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
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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