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date accessioned2022-05-09T00:50:23Z
date available2022-05-09T00:50:23Z
date copyright16 Dec 2021
date issued2021
identifier otherWAF-D-21-0067.1.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4285621
description abstractPolarimetric radar data from the WSR-88D network are used to examine the evolution of various polarimetric precursor signatures to tornado dissipation within a sample of 36 supercell storms. These signatures include an increase in bulk hook echo median raindrop size, a decrease in midlevel differential radar reflectivity factor (Z DR) column area, a decrease in the magnitude of the Z DR arc, an increase in the area of low-level large hail, and a decrease in the orientation angle of the vector separating low-level Z DR and specific differential phase (K DP) maxima. Only supercells that produced “long-duration” tornadoes (with at least four consecutive volumes of WSR-88D data) are investigated, so that signatures can be sufficiently tracked in time, and novel algorithms are used to isolate each storm-scale process. During the time leading up to tornado dissipation, we find that hook echo median drop size (D 0) and median Z DR remain relatively constant, but hook echo median K DP and estimated number concentration (NT) increase. The Z DR arc maximum magnitude and Z DR–K DP separation orientation angles are observed to decrease in most dissipation cases. Neither the area of large hail nor the Z DR column area exhibit strong signals leading up to tornado dissipation. Finally, combinations of storm-scale behaviors and TVS behaviors occur most frequently just prior to tornado dissipation, but also are common 15–20 min prior to dissipation. The results from this study provide evidence that nowcasting tornado dissipation using dual-polarization radar may be possible when combined with TVS monitoring, subject to important caveats.
titleStorm-Scale Polarimetric Radar Signatures Associated with Tornado Dissipation in Supercells
typeJournal Paper
journal volume37
journal issue1
journal titleWeather and Forecasting
identifier doi10.1175/WAF-D-21-0067.1
page3–21
treeWeather and Forecasting:;2021:;volume( 037 ):;issue: 001
contenttypeFulltext


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