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    Toward 1-km ensemble forecasts over large domains

    Source: Monthly Weather Review:;2017:;volume( 145 ):;issue: 008::page 2943
    Author:
    Schwartz, Craig S.
    ,
    Romine, Glen S.
    ,
    Fossell, Kathryn R.
    ,
    Sobash, Ryan A.
    ,
    Weisman, Morris L.
    DOI: 10.1175/MWR-D-16-0410.1
    Publisher: American Meteorological Society
    Abstract: recipitation forecasts from convection-allowing ensembles with 3- and 1-km horizontal grid spacing were evaluated between 15 May and 15 June 2013 over central and eastern portions of the United States. Probabilistic forecasts produced from 10- and 30-member 3-km ensembles were consistently better than forecasts from individual 1-km ensemble members. However, 10-member, 1-km probabilistic forecasts usually produced the best forecasts, especially over the first 12 hours and at rainfall rates ≥ 5.0 mm/hr at later times. Further object-based investigation revealed that better 1-km forecasts at heavier rainfall rates were associated with more accurate placement of mesoscale convective systems compared to 3-km forecasts. The collective results indicate promise for 1-km ensembles once computational resources can support their operational implementation.
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      Toward 1-km ensemble forecasts over large domains

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    • Monthly Weather Review

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    contributor authorSchwartz, Craig S.
    contributor authorRomine, Glen S.
    contributor authorFossell, Kathryn R.
    contributor authorSobash, Ryan A.
    contributor authorWeisman, Morris L.
    date accessioned2017-06-09T17:34:41Z
    date available2017-06-09T17:34:41Z
    date issued2017
    identifier issn0027-0644
    identifier otherams-87452.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4231123
    description abstractrecipitation forecasts from convection-allowing ensembles with 3- and 1-km horizontal grid spacing were evaluated between 15 May and 15 June 2013 over central and eastern portions of the United States. Probabilistic forecasts produced from 10- and 30-member 3-km ensembles were consistently better than forecasts from individual 1-km ensemble members. However, 10-member, 1-km probabilistic forecasts usually produced the best forecasts, especially over the first 12 hours and at rainfall rates ≥ 5.0 mm/hr at later times. Further object-based investigation revealed that better 1-km forecasts at heavier rainfall rates were associated with more accurate placement of mesoscale convective systems compared to 3-km forecasts. The collective results indicate promise for 1-km ensembles once computational resources can support their operational implementation.
    publisherAmerican Meteorological Society
    titleToward 1-km ensemble forecasts over large domains
    typeJournal Paper
    journal volume145
    journal issue008
    journal titleMonthly Weather Review
    identifier doi10.1175/MWR-D-16-0410.1
    journal fristpage2943
    journal lastpage2969
    treeMonthly Weather Review:;2017:;volume( 145 ):;issue: 008
    contenttypeFulltext
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