The Use of Collapsing Specific Differential Phase Columns to Predict Significant Severe Thunderstorm Wind Damage across the Northeastern United States

The Storm Prediction Center (SPC) considers severe thunderstorms that produce measured or estimated wind gusts of at least 33.4 ms-1 (65 kt), hail 5.08 cm (2 in) in diameter or greater, or an EF2 or greater tornado to be significant. Pinpointing which particular severe thunderstorms will produce significant severe weather events can be a difficult challenge for the warning decision forecaster. Out of the 1423 severe wind reports received by the NWS Albany between 1 January 2012 and 31 December 2017, only 46 (about 3%) were considered significant. However, these particular storms had a major impact on the lives of many people in the region and these storms received a large amount of media attention. Doppler radar radial velocity data may not always provide a clear picture of a storm’s severity due to inherent problems regarding the radar beam’s height and angle. As a result, forecasters need to rely on something other than just radial velocity during radar interrogation. This study examined the use of the dual-polarization product Specific Differential Phase (KDP) during radar interrogation to diagnose the potential of significant severe thunderstorm winds. When examined in vertical cross-sections, elevated strong cores of KDP were shown to lower towards the surface just prior to the reports of significant severe thunderstorm wind damage in 30 of 46 cases across the NWS Albany forecast area. This was statistically significant when compared with an examination of KDP cores from 51 ordinary (non-significant) severe storms during the same case days. The use of KDP columns can be a successful method to help forecasters predict when significant severe wind damage will occur, resulting in better lead times and more detailed information for impact-based severe thunderstorm warnings.

Publication Details

Published
2025-04-01
DOI
https://doi.org/10.25923/rmb7-7v44
Primary Topic
Botanical Research and Applications
Type
article
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article

The Use of Collapsing Specific Differential Phase Columns to Predict Significant Severe Thunderstorm Wind Damage across the Northeastern United States

Botanical Research and Applications
article

The Use of Collapsing Specific Differential Phase Columns to Predict Significant Severe Thunderstorm Wind Damage across the Northeastern United States

article en

Abstract

The Storm Prediction Center (SPC) considers severe thunderstorms that produce measured or estimated wind gusts of at least 33.4 ms-1 (65 kt), hail 5.08 cm (2 in) in diameter or greater, or an EF2 or greater tornado to be significant. Pinpointing which particular severe thunderstorms will produce significant severe weather events can be a difficult challenge for the warning decision forecaster. Out of the 1423 severe wind reports received by the NWS Albany between 1 January 2012 and 31 December 2017, only 46 (about 3%) were considered significant. However, these particular storms had a major impact on the lives of many people in the region and these storms received a large amount of media attention. Doppler radar radial velocity data may not always provide a clear picture of a storm’s severity due to inherent problems regarding the radar beam’s height and angle. As a result, forecasters need to rely on something other than just radial velocity during radar interrogation. This study examined the use of the dual-polarization product Specific Differential Phase (KDP) during radar interrogation to diagnose the potential of significant severe thunderstorm winds. When examined in vertical cross-sections, elevated strong cores of KDP were shown to lower towards the surface just prior to the reports of significant severe thunderstorm wind damage in 30 of 46 cases across the NWS Albany forecast area. This was statistically significant when compared with an examination of KDP cores from 51 ordinary (non-significant) severe storms during the same case days. The use of KDP columns can be a successful method to help forecasters predict when significant severe wind damage will occur, resulting in better lead times and more detailed information for impact-based severe thunderstorm warnings.

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Botanical Research and Applications
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