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dc.contributor.authorJohn Y. N. Cho
dc.contributor.authorJames M. Kurdzo
dc.contributor.authorBetty J. Bennett
dc.contributor.authorMark E. Weber
dc.contributor.authorJoseph W. Dellicarpini
dc.contributor.authorAndrew Loconto
dc.contributor.authorHayden Frank
dc.date.accessioned2023-04-12T18:33:23Z
dc.date.available2023-04-12T18:33:23Z
dc.date.copyright2022/07/01
dc.date.issued2022
dc.identifier.otherWAF-D-21-0152.1.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4289872
dc.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.
dc.publisherAmerican Meteorological Society
dc.titleImpact of WSR-88D Intra-Volume Low-Level Scans on Severe Weather Warning Performance
dc.typeJournal Paper
dc.journal.volume37
dc.journal.issue7
dc.journal.titleWeather and Forecasting
dc.identifier.doi10.1175/WAF-D-21-0152.1
dc.journal.fristpage1169
dc.journal.lastpage1189
dc.page1169–1189
dc.treeWeather and Forecasting:;2022:;volume( 037 ):;issue: 007
dc.contenttypeFulltext


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