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    Application of Scale-Selective Data Assimilation to Regional Climate Modeling and Prediction

    Source: Monthly Weather Review:;2009:;volume( 138 ):;issue: 004::page 1307
    Author:
    Peng, Shiqiu
    ,
    Xie, Lian
    ,
    Liu, Bin
    ,
    Semazzi, Fredrick
    DOI: 10.1175/2009MWR2974.1
    Publisher: American Meteorological Society
    Abstract: A method referred to as scale-selective data assimilation (SSDA) is designed to inject the large-scale components of the atmospheric circulation from a global model into a regional model to improve regional climate simulations and predictions. The SSDA is implemented through the following procedure: 1) using a low-pass filter to extract the large-scale components of the atmospheric circulation from global analysis or model forecasts; 2) applying the filter to extract the regional-scale and the large-scale components of the atmospheric circulation from the regional model simulations or forecasts; 3) assimilating the large-scale circulation obtained from the global model into the corresponding component simulated by the regional model using the method of three-dimensional variational data assimilation (3DVAR) while maintaining the small-scale components from the regional model during the assimilation cycle; 4) combining the small-scale and the assimilated large-scale components as the adjusted forecasts by the regional climate model and allowing the two components to mutually adjust outside the data assimilation cycle. A case study of summer 2005 seasonal climate hindcasting for the regions of the Atlantic and the eastern United States indicates that the large-scale components from the Global Forecast System (GFS) analysis can be effectively assimilated into the regional model using the scale-selective data assimilation method devised in this study, resulting in an improvement in the overall results from the regional climate model.
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      Application of Scale-Selective Data Assimilation to Regional Climate Modeling and Prediction

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4211273
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    contributor authorPeng, Shiqiu
    contributor authorXie, Lian
    contributor authorLiu, Bin
    contributor authorSemazzi, Fredrick
    date accessioned2017-06-09T16:32:13Z
    date available2017-06-09T16:32:13Z
    date copyright2010/04/01
    date issued2009
    identifier issn0027-0644
    identifier otherams-69588.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4211273
    description abstractA method referred to as scale-selective data assimilation (SSDA) is designed to inject the large-scale components of the atmospheric circulation from a global model into a regional model to improve regional climate simulations and predictions. The SSDA is implemented through the following procedure: 1) using a low-pass filter to extract the large-scale components of the atmospheric circulation from global analysis or model forecasts; 2) applying the filter to extract the regional-scale and the large-scale components of the atmospheric circulation from the regional model simulations or forecasts; 3) assimilating the large-scale circulation obtained from the global model into the corresponding component simulated by the regional model using the method of three-dimensional variational data assimilation (3DVAR) while maintaining the small-scale components from the regional model during the assimilation cycle; 4) combining the small-scale and the assimilated large-scale components as the adjusted forecasts by the regional climate model and allowing the two components to mutually adjust outside the data assimilation cycle. A case study of summer 2005 seasonal climate hindcasting for the regions of the Atlantic and the eastern United States indicates that the large-scale components from the Global Forecast System (GFS) analysis can be effectively assimilated into the regional model using the scale-selective data assimilation method devised in this study, resulting in an improvement in the overall results from the regional climate model.
    publisherAmerican Meteorological Society
    titleApplication of Scale-Selective Data Assimilation to Regional Climate Modeling and Prediction
    typeJournal Paper
    journal volume138
    journal issue4
    journal titleMonthly Weather Review
    identifier doi10.1175/2009MWR2974.1
    journal fristpage1307
    journal lastpage1318
    treeMonthly Weather Review:;2009:;volume( 138 ):;issue: 004
    contenttypeFulltext
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