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    Storm-Scale Data Assimilation and Ensemble Forecasts for the 27 April 2011 Severe Weather Outbreak in Alabama

    Source: Monthly Weather Review:;2015:;volume( 143 ):;issue: 008::page 3044
    Author:
    Yussouf, Nusrat
    ,
    Dowell, David C.
    ,
    Wicker, Louis J.
    ,
    Knopfmeier, Kent H.
    ,
    Wheatley, Dustan M.
    DOI: 10.1175/MWR-D-14-00268.1
    Publisher: American Meteorological Society
    Abstract: s part of NOAA?s Warn-on-Forecast (WoF) initiative, a multiscale ensemble-based assimilation and prediction system is developed using the WRF-ARW model and DART assimilation software. To evaluate the capabilities of the system, retrospective short-range probabilistic storm-scale (convection allowing) ensemble analyses and forecasts are produced for the 27 April 2011 Alabama severe weather outbreak. Results indicate that the storm-scale ensembles are able to analyze the observed storms with strong low-level rotation at approximately the correct locations and to retain the supercell structures during the 0?1-h forecasts with reasonable accuracy. The system predicts the low-level mesocyclones of significant isolated tornadic supercells that align well with the locations of radar-derived rotation. For cases with multiple interacting storms in close proximity, the system tends to produce more variability in mesocyclone forecasts from one initialization time to the next until the observations show the dominance of one of the cells. The short-range ensemble probabilistic forecasts obtained from this continuous 5-min storm-scale 6-h-long update system demonstrate the potential of a frequently updated, high-resolution NWP system that could be used to extend severe weather warning lead times. This study also demonstrates the challenges associated with developing a WoF-type system. The results motivate future work to reduce model errors associated with storm motion and spurious cells, and to design storm-scale ensembles that better represent typical 1-h forecast errors.
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      Storm-Scale Data Assimilation and Ensemble Forecasts for the 27 April 2011 Severe Weather Outbreak in Alabama

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    contributor authorYussouf, Nusrat
    contributor authorDowell, David C.
    contributor authorWicker, Louis J.
    contributor authorKnopfmeier, Kent H.
    contributor authorWheatley, Dustan M.
    date accessioned2017-06-09T17:32:32Z
    date available2017-06-09T17:32:32Z
    date copyright2015/08/01
    date issued2015
    identifier issn0027-0644
    identifier otherams-86973.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4230590
    description abstracts part of NOAA?s Warn-on-Forecast (WoF) initiative, a multiscale ensemble-based assimilation and prediction system is developed using the WRF-ARW model and DART assimilation software. To evaluate the capabilities of the system, retrospective short-range probabilistic storm-scale (convection allowing) ensemble analyses and forecasts are produced for the 27 April 2011 Alabama severe weather outbreak. Results indicate that the storm-scale ensembles are able to analyze the observed storms with strong low-level rotation at approximately the correct locations and to retain the supercell structures during the 0?1-h forecasts with reasonable accuracy. The system predicts the low-level mesocyclones of significant isolated tornadic supercells that align well with the locations of radar-derived rotation. For cases with multiple interacting storms in close proximity, the system tends to produce more variability in mesocyclone forecasts from one initialization time to the next until the observations show the dominance of one of the cells. The short-range ensemble probabilistic forecasts obtained from this continuous 5-min storm-scale 6-h-long update system demonstrate the potential of a frequently updated, high-resolution NWP system that could be used to extend severe weather warning lead times. This study also demonstrates the challenges associated with developing a WoF-type system. The results motivate future work to reduce model errors associated with storm motion and spurious cells, and to design storm-scale ensembles that better represent typical 1-h forecast errors.
    publisherAmerican Meteorological Society
    titleStorm-Scale Data Assimilation and Ensemble Forecasts for the 27 April 2011 Severe Weather Outbreak in Alabama
    typeJournal Paper
    journal volume143
    journal issue8
    journal titleMonthly Weather Review
    identifier doi10.1175/MWR-D-14-00268.1
    journal fristpage3044
    journal lastpage3066
    treeMonthly Weather Review:;2015:;volume( 143 ):;issue: 008
    contenttypeFulltext
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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