High-Resolution Hail Observations: Implications for NWS Warning Operations

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.

An empirical model relating U.S. monthly hail occurrence to large‐scale meteorological environment

“…For example, only maximum hail size is reported, and that value may be quantized or distorted by association to reference objects (e.g., golf balls). Recent high‐resolution hail observations from field campaigns [e.g., Ortega et al ., ; Blair et al ., ] suggest that larger hail sizes are more common than would be expected from Storm Data hail reports. Another characteristic of the Storm Data hail reports are positive trends in the frequency of hail in excess of 2 in.…”

The algorithmic detection of pulse thunderstorms within a large, mostly non‐severe sample

“…If these storms were recorded as severe, rather than non‐severe, the random forest would be more adept at labelling pulse thunderstorms in these sections of data space, and overfitting would also probably relax. This possibility is reasonable in the light of recent studies using high‐resolution storm reports (Ortega et al, ; Blair et al, ). For instance, during the Hail Spatial and Temporal Observing Network Effort (HailSTONE) field project, Blair et al .…”

“…For instance, during the Hail Spatial and Temporal Observing Network Effort (HailSTONE) field project, Blair et al . () found that 32% of the severe‐hail‐producing storms sampled by field observers lacked a corresponding Storm Data report. Additionally, Storm Data hail diameters consistently under‐represented the maximum hail diameters sampled by the field team.…”

U.S. Hail Frequency and the Global Wind Oscillation

“…One parameter capable of identifying these storms is the supercell composite parameter (SCP; Thompson et al, 2003), which combines 0-6 km vertical wind shear (S06; m s −1 ), 0-3 km storm relative helicity (m 2 s −2 ), and surface-based convective available potential energy (J kg −1 ) into one convenient index that is skillful at statistically discriminating between supercell and nonsupercell environments. Supercells produce the vast majority of hailstones in excess of 5 cm in diameter (Blair et al, 2017), suggesting that such a proxy would be a useful metric for identifying favorable severe hail environments. This paper explores the influence of the GWO on hail frequency and intensity over the United States.…”

“…Previous research has indicated a relationship between the GWO and U.S. tornado frequency (Gensini & Marinaro, ; Moore, ). Since a majority of tornadoes are produced by supercell thunderstorms, it follows that variability in large hail frequency may also be explained by this metric, as large hail events are often an additional by‐product (Allen et al, ; Blair et al, ). Unlike tornadoes, few studies have considered the influence teleconnections on the frequency variability of damaging hailstones (Allen et al, ; Barrett & Henley, ; Lepore et al, ).…”