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Using Operational Radar To Identify Deep Hail Accumulations From Thunderstorms

Abstract

Thunderstorms that produce surface hail accumulations, sometimes as large as 60 cm in depth, have significantly affected the residents of the Front Range and High Plains of Colorado and Wyoming by creating hazardous road conditions and endangering lives and property. To date, surface hail accumulation is not part of a routine forecasting or monitoring system. Extensive coordinated hail accumulation reports and operational products designed to identify deep hail accumulating storms in real time are lacking. Kalina et al. used dual-polarization WSR-88D radar observations to calculate hail depth and hail accumulations but never validated the algorithm. This study shows how 20 quality-controlled hail depth reports from the hail depth database built by the Colorado Hail Accumulation from Thunderstorms (CHAT) project are being used to validate the Kalina et al. radar-based hail accumulation algorithm for operational application. The validated algorithm shows increased correlations between radar-derived and reported accumulations for hail depth reports not included in the validation. Furthermore, increases in computational efficiency have allowed the improved algorithm to be used operationally. With an improved hail accumulation algorithm, thunderstorms that produce hail accumulations are more frequently detected than previously reported.

Article / Publication Data
Active/Online
YES
Volume
34
Available Metadata
Accepted On
October 09, 2018
DOI ↗
Fiscal Year
NOAA IR URL ↗
Peer Reviewed
YES
Publication Name
Weather and Forecasting
Published On
February 01, 2019
Publisher Name
American Meteorological Society
Print Volume
34
Print Number
1
Page Range
133–150
Issue
1
Submitted On
April 05, 2018
URL ↗

Authors

Authors who have authored or contributed to this publication.

  • Robinson Wallace - lead None
    Other
  • Evan A. Kalina - third Gsl
    Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder
    NOAA/Global Systems Laboratory