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High-Resolution Hail Observations: Implications for NWS Warning Operations.

Authors :
Blair, Scott F.
Laflin, Jennifer M.
Cavanaugh, Dennis E.
Sanders, Kristopher J.
Currens, Scott R.
Pullin, Justin I.
Cooper, Dylan T.
Deroche, Derek R.
Leighton, Jared W.
Fritchie, Robert V.
Mezeul II, Mike J.
Goudeau, Barrett T.
Kreller, Stephen J.
Bosco, John J.
Kelly, Charley M.
Mallinson, Holly M.
Source :
Weather & Forecasting; Jul2017, Vol. 32 Issue 3, p1101-1119, 19p
Publication Year :
2017

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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
08828156
Volume :
32
Issue :
3
Database :
Complementary Index
Journal :
Weather & Forecasting
Publication Type :
Academic Journal
Accession number :
131290368
Full Text :
https://doi.org/10.1175/WAF-D-16-0203.1