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High-Resolution Hail Observations: Implications for NWS Warning Operations
- Source :
- Weather and Forecasting. 32:1101-1119
- Publication Year :
- 2017
- Publisher :
- American Meteorological Society, 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.
- Subjects :
- Atmospheric Science
010504 meteorology & atmospheric sciences
Nowcasting
Meteorology
0208 environmental biotechnology
High resolution
Storm
02 engineering and technology
01 natural sciences
020801 environmental engineering
Hail spike
Maximum diameter
Convective storm detection
Thunderstorm
Environmental science
Storm Data
0105 earth and related environmental sciences
Subjects
Details
- ISSN :
- 15200434 and 08828156
- Volume :
- 32
- Database :
- OpenAIRE
- Journal :
- Weather and Forecasting
- Accession number :
- edsair.doi...........07e7664c814eafb2d2d393060207d7b3
- Full Text :
- https://doi.org/10.1175/waf-d-16-0203.1