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    The National Severe Storms Laboratory Tornado Detection Algorithm

    Source: Weather and Forecasting:;1998:;volume( 013 ):;issue: 002::page 352
    Author:
    Mitchell, E. De Wayne
    ,
    Vasiloff, Steven V.
    ,
    Stumpf, Gregory J.
    ,
    Witt, Arthur
    ,
    Eilts, Michael D.
    ,
    Johnson, J. T.
    ,
    Thomas, Kevin W.
    DOI: 10.1175/1520-0434(1998)013<0352:TNSSLT>2.0.CO;2
    Publisher: American Meteorological Society
    Abstract: The National Severe Storms Laboratory (NSSL) has developed and tested a tornado detection algorithm (NSSL TDA) that has been designed to identify the locally intense vortices associated with tornadoes using the WSR-88D base velocity data. The NSSL TDA is an improvement over the current Weather Surveillance Radar-1988 Doppler (WSR-88D) Tornadic Vortex Signature Algorithm (88D TVS). The NSSL TDA has been designed to address the relatively low probability of detection (POD) of the 88D TVS algorithm without a high false alarm rate (FAR). Using an independent dataset consisting of 31 tornadoes, the NSSL TDA has a POD of 43%, FAR of 48%, critical success index (CSI) = 31%, and a Heidke skill score (HSS) of 46% compared to the 88D TVS, which has a POD of 3%, FAR of 0%, CSI of 3%, and HSS of 0%. In contrast to the 88D TVS, the NSSL TDA identifies tornadic vortices by 1) searching for strong shear between velocity gates that are azimuthally adjacent and constant in range, and 2) not requiring the presence of an algorithm-identified mesocyclone. This manuscript discusses the differences between the NSSL TDA and the 88D TVS and presents a performance comparison between the two algorithms. Strengths and weaknesses of the NSSL TDA and NSSL?s future work related to tornado identification using Doppler radar are also discussed.
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      The National Severe Storms Laboratory Tornado Detection Algorithm

    URI
    http://yetl.yabesh.ir/yetl1/handle/yetl/4166845
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    contributor authorMitchell, E. De Wayne
    contributor authorVasiloff, Steven V.
    contributor authorStumpf, Gregory J.
    contributor authorWitt, Arthur
    contributor authorEilts, Michael D.
    contributor authorJohnson, J. T.
    contributor authorThomas, Kevin W.
    date accessioned2017-06-09T14:55:00Z
    date available2017-06-09T14:55:00Z
    date copyright1998/06/01
    date issued1998
    identifier issn0882-8156
    identifier otherams-2960.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4166845
    description abstractThe National Severe Storms Laboratory (NSSL) has developed and tested a tornado detection algorithm (NSSL TDA) that has been designed to identify the locally intense vortices associated with tornadoes using the WSR-88D base velocity data. The NSSL TDA is an improvement over the current Weather Surveillance Radar-1988 Doppler (WSR-88D) Tornadic Vortex Signature Algorithm (88D TVS). The NSSL TDA has been designed to address the relatively low probability of detection (POD) of the 88D TVS algorithm without a high false alarm rate (FAR). Using an independent dataset consisting of 31 tornadoes, the NSSL TDA has a POD of 43%, FAR of 48%, critical success index (CSI) = 31%, and a Heidke skill score (HSS) of 46% compared to the 88D TVS, which has a POD of 3%, FAR of 0%, CSI of 3%, and HSS of 0%. In contrast to the 88D TVS, the NSSL TDA identifies tornadic vortices by 1) searching for strong shear between velocity gates that are azimuthally adjacent and constant in range, and 2) not requiring the presence of an algorithm-identified mesocyclone. This manuscript discusses the differences between the NSSL TDA and the 88D TVS and presents a performance comparison between the two algorithms. Strengths and weaknesses of the NSSL TDA and NSSL?s future work related to tornado identification using Doppler radar are also discussed.
    publisherAmerican Meteorological Society
    titleThe National Severe Storms Laboratory Tornado Detection Algorithm
    typeJournal Paper
    journal volume13
    journal issue2
    journal titleWeather and Forecasting
    identifier doi10.1175/1520-0434(1998)013<0352:TNSSLT>2.0.CO;2
    journal fristpage352
    journal lastpage366
    treeWeather and Forecasting:;1998:;volume( 013 ):;issue: 002
    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