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    Multimodel Approach Based on Evidence Theory for Forecasting Tropical Cyclone Tracks

    Source: Monthly Weather Review:;2010:;volume( 138 ):;issue: 002::page 405
    Author:
    Poroseva, Svetlana V.
    ,
    Lay, Nathan
    ,
    Hussaini, M. Yousuff
    DOI: 10.1175/2009MWR2733.1
    Publisher: American Meteorological Society
    Abstract: In this paper a new multimodel approach for forecasting tropical cyclone tracks is presented. The approach is based on the Dempster?Shafer theory of evidence. At each forecast period, the multimodel forecast is given as an area where the tropical cyclone position is likely to occur. Each area includes a quantitative assessment of the credibility (degree of belief) of the prediction. The multimodel forecast is obtained by combining individual model forecasts into a single prediction by Dempster?s rule. Mathematical requirements associated with the Dempster?s rule are discussed. Particular attention is given to the requirement of independence of evidence sources, which, for tropical cyclone track forecasting, are the model and best-track data. The origin of this requirement is explored, and it is shown that for forecasting tropical cyclone tracks, this requirement is excessive. The influence of the number of models included in the multimodel approach on the forecasting ability is also studied. Data produced by the models of the Navy Operational Global Atmospheric Prediction System, the European Centre for Medium-Range Weather Forecasts, and the National Centers for Environmental Prediction are used to produce two-, three-, and four-model forecasts. The forecasting ability of the multimodel approach is evaluated using the best-track database of the tropical cyclones that occurred in the eastern and western North Pacific and South Indian Ocean basins in the year 2000.
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      Multimodel Approach Based on Evidence Theory for Forecasting Tropical Cyclone Tracks

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    https://yetl.yabesh.ir/yetl1/handle/yetl/4211134
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    • Monthly Weather Review

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    contributor authorPoroseva, Svetlana V.
    contributor authorLay, Nathan
    contributor authorHussaini, M. Yousuff
    date accessioned2017-06-09T16:31:44Z
    date available2017-06-09T16:31:44Z
    date copyright2010/02/01
    date issued2010
    identifier issn0027-0644
    identifier otherams-69462.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4211134
    description abstractIn this paper a new multimodel approach for forecasting tropical cyclone tracks is presented. The approach is based on the Dempster?Shafer theory of evidence. At each forecast period, the multimodel forecast is given as an area where the tropical cyclone position is likely to occur. Each area includes a quantitative assessment of the credibility (degree of belief) of the prediction. The multimodel forecast is obtained by combining individual model forecasts into a single prediction by Dempster?s rule. Mathematical requirements associated with the Dempster?s rule are discussed. Particular attention is given to the requirement of independence of evidence sources, which, for tropical cyclone track forecasting, are the model and best-track data. The origin of this requirement is explored, and it is shown that for forecasting tropical cyclone tracks, this requirement is excessive. The influence of the number of models included in the multimodel approach on the forecasting ability is also studied. Data produced by the models of the Navy Operational Global Atmospheric Prediction System, the European Centre for Medium-Range Weather Forecasts, and the National Centers for Environmental Prediction are used to produce two-, three-, and four-model forecasts. The forecasting ability of the multimodel approach is evaluated using the best-track database of the tropical cyclones that occurred in the eastern and western North Pacific and South Indian Ocean basins in the year 2000.
    publisherAmerican Meteorological Society
    titleMultimodel Approach Based on Evidence Theory for Forecasting Tropical Cyclone Tracks
    typeJournal Paper
    journal volume138
    journal issue2
    journal titleMonthly Weather Review
    identifier doi10.1175/2009MWR2733.1
    journal fristpage405
    journal lastpage420
    treeMonthly Weather Review:;2010:;volume( 138 ):;issue: 002
    contenttypeFulltext
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