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    Impact of WSR-88D Intra-Volume Low-Level Scans on Severe Weather Warning Performance

    Source: Weather and Forecasting:;2022:;volume( 037 ):;issue: 007::page 1169
    Author:
    John Y. N. Cho
    ,
    James M. Kurdzo
    ,
    Betty J. Bennett
    ,
    Mark E. Weber
    ,
    Joseph W. Dellicarpini
    ,
    Andrew Loconto
    ,
    Hayden Frank
    DOI: 10.1175/WAF-D-21-0152.1
    Publisher: American Meteorological Society
    Abstract: The statistical relationship between supplemental adaptive intra-volume low-level scan (SAILS) usage on the Weather Surveillance Radar-1988 Doppler and National Weather Service severe storm warning performance during 2014–20 is analyzed. Results show statistically significant improvement in severe thunderstorm (SVR), flash flood (FF), and tornado (TOR) warning performance associated with SAILS-on versus SAILS-off. Within the three possible SAILS modes of one (SAILSx1), two (SAILSx2), and three (SAILSx3) additional base scans per volume, for SVR, SAILSx2 and SAILSx3 are associated with better warning performance compared to SAILSx1; for FF and TOR, SAILSx3 is associated with better warning performance relative to SAILSx1 and SAILSx2. Two severe storm cases (one that spawned a tornado, one that did not) are presented where SAILS usage helped forecasters make the correct TOR warning decision, lending real-life credence to the statistical results. Furthermore, a statistical analysis of automated volume scan evaluation and termination effects, parsed by SAILS usage and mode, yield a statistically significant association between volume scan update rate and SVR warning lead time.
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      Impact of WSR-88D Intra-Volume Low-Level Scans on Severe Weather Warning Performance

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4289872
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    contributor authorJohn Y. N. Cho
    contributor authorJames M. Kurdzo
    contributor authorBetty J. Bennett
    contributor authorMark E. Weber
    contributor authorJoseph W. Dellicarpini
    contributor authorAndrew Loconto
    contributor authorHayden Frank
    date accessioned2023-04-12T18:33:23Z
    date available2023-04-12T18:33:23Z
    date copyright2022/07/01
    date issued2022
    identifier otherWAF-D-21-0152.1.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4289872
    description abstractThe statistical relationship between supplemental adaptive intra-volume low-level scan (SAILS) usage on the Weather Surveillance Radar-1988 Doppler and National Weather Service severe storm warning performance during 2014–20 is analyzed. Results show statistically significant improvement in severe thunderstorm (SVR), flash flood (FF), and tornado (TOR) warning performance associated with SAILS-on versus SAILS-off. Within the three possible SAILS modes of one (SAILSx1), two (SAILSx2), and three (SAILSx3) additional base scans per volume, for SVR, SAILSx2 and SAILSx3 are associated with better warning performance compared to SAILSx1; for FF and TOR, SAILSx3 is associated with better warning performance relative to SAILSx1 and SAILSx2. Two severe storm cases (one that spawned a tornado, one that did not) are presented where SAILS usage helped forecasters make the correct TOR warning decision, lending real-life credence to the statistical results. Furthermore, a statistical analysis of automated volume scan evaluation and termination effects, parsed by SAILS usage and mode, yield a statistically significant association between volume scan update rate and SVR warning lead time.
    publisherAmerican Meteorological Society
    titleImpact of WSR-88D Intra-Volume Low-Level Scans on Severe Weather Warning Performance
    typeJournal Paper
    journal volume37
    journal issue7
    journal titleWeather and Forecasting
    identifier doi10.1175/WAF-D-21-0152.1
    journal fristpage1169
    journal lastpage1189
    page1169–1189
    treeWeather and Forecasting:;2022:;volume( 037 ):;issue: 007
    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
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