High-Resolution Hail Observations: Implications for NWS Warning Operations

Scott F. Blair NOAA/NWS Weather Forecast Office, Kansas City, Missouri

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Jennifer M. Laflin NOAA/NWS Weather Forecast Office, Kansas City, Missouri

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Dennis E. Cavanaugh NOAA/NWS Weather Forecast Office, Little Rock, Arkansas

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Kristopher J. Sanders NOAA/NWS Weather Forecast Office, Topeka, Kansas

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Scott R. Currens Tradewind Energy, Lenexa, Kansas

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Justin I. Pullin NOAA/NWS Weather Forecast Office, Tallahassee, Florida

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Dylan T. Cooper NOAA/NWS Weather Forecast Office, Charleston, West Virginia

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Derek R. Deroche NOAA/NWS Central Region Headquarters, Kansas City, Missouri

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Jared W. Leighton NOAA/NWS Weather Forecast Office, Kansas City, Missouri

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Robert V. Fritchie CoreLogic, Norman, Oklahoma

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Mike J. Mezeul II Mike Mezeul II Photography, Frisco, Texas

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Barrett T. Goudeau Department of Atmospheric Science, University of Alabama in Huntsville, Huntsville, Alabama

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Stephen J. Kreller Department of Geography and Anthropology, Louisiana State University, Baton Rouge, Louisiana

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John J. Bosco Department of Atmospheric Sciences, University of Louisiana at Monroe, Monroe, Louisiana

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Charley M. Kelly NOAA/NWS Weather Forecast Office, St. Louis, Missouri

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Holly M. Mallinson Department of Atmospheric Sciences, University of Illinois at Urbana–Champaign, Urbana, Illinois

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Abstract

A field research campaign, the Hail Spatial and Temporal Observing Network Effort (HailSTONE), was designed to obtain physical high-resolution hail measurements at the ground associated with convective storms to help address several operational challenges that remain unsatisfied through public storm reports. Field phases occurred over a 5-yr period, yielding hail measurements from 73 severe thunderstorms [hail diameter ≥ 1.00 in. (2.54 cm)]. These data provide unprecedented insight into the hailfall character of each storm and afford a baseline to explore the representativeness of the climatological hail database and hail forecasts in NWS warning products. Based upon the full analysis of HailSTONE observations, hail sizes recorded in Storm Data as well as hail size forecasts in NWS warnings frequently underestimated the maximum diameter hailfall occurring at the surface. NWS hail forecasts were generally conservative in size and at least partially calibrated to incoming hail reports. Storm mode played a notable role in determining the potential range of maximum hail size during the life span of each storm. Supercells overwhelmingly produced the largest hail diameters, with smaller maximum hail sizes observed as convection became progressively less organized. Warning forecasters may employ a storm-mode hail size forecast philosophy, in conjunction with other radar-based hail detection techniques, to better anticipate and forecast hail sizes during convective warning episodes.

© 2017 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Scott F. Blair, scott.blair@noaa.gov

Abstract

A field research campaign, the Hail Spatial and Temporal Observing Network Effort (HailSTONE), was designed to obtain physical high-resolution hail measurements at the ground associated with convective storms to help address several operational challenges that remain unsatisfied through public storm reports. Field phases occurred over a 5-yr period, yielding hail measurements from 73 severe thunderstorms [hail diameter ≥ 1.00 in. (2.54 cm)]. These data provide unprecedented insight into the hailfall character of each storm and afford a baseline to explore the representativeness of the climatological hail database and hail forecasts in NWS warning products. Based upon the full analysis of HailSTONE observations, hail sizes recorded in Storm Data as well as hail size forecasts in NWS warnings frequently underestimated the maximum diameter hailfall occurring at the surface. NWS hail forecasts were generally conservative in size and at least partially calibrated to incoming hail reports. Storm mode played a notable role in determining the potential range of maximum hail size during the life span of each storm. Supercells overwhelmingly produced the largest hail diameters, with smaller maximum hail sizes observed as convection became progressively less organized. Warning forecasters may employ a storm-mode hail size forecast philosophy, in conjunction with other radar-based hail detection techniques, to better anticipate and forecast hail sizes during convective warning episodes.

© 2017 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Scott F. Blair, scott.blair@noaa.gov
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