U.S. Hail Frequency and the Global Wind Oscillation

Abstract

Changes in Earth relative atmospheric angular momentum can be described by an index known as the Global Wind Oscillation. This global index accounts for changes in Earth's atmospheric budget of relative angular momentum through interactions of tropical convection anomalies, extratropical dynamics, and engagement of surface torques (e.g., friction and mountain). It is shown herein that U.S. hail events are more (less) likely to occur in low (high) atmospheric angular momentum base states when excluding weak Global Wind Oscillation days, with the strongest relationships found in the boreal spring and fall. Severe, significant severe, and giant hail events are more likely to occur during Global Wind Oscillation phases 8, 1, 2, and 3 during the peak of U.S. severe weather season. Lower frequencies of hail events are generally found in Global Wind Oscillation phases 4–7 but vary based on Global Wind Oscillation amplitude and month. In addition, probabilistic anomalies of atmospheric ingredients supportive of hail producing supercell thunderstorms closely mimic locations of reported hail frequency, helping to corroborate report results.

Skillful Subseasonal Forecasts of Weekly Tornado and Hail Activity Using the Madden‐Julian Oscillation

“…While the principal question we set out to answer in this study revolved around the ability of the MJO to serve as a source of predictive skill, the simplicity of the two-class empirical model we developed lends opportunity to the addition of more predictors and additional classes that could lead to its improvement. Some potential predictors that operate on subseasonal and longer time scales include ENSO (Allen et al, 2015b;Childs et al, 2018;Cook et al, 2017;Lepore et al, 2017), the Global Wind Oscillation (Gensini & Allen, 2018;Gensini & Marinaro, 2016;Moore, 2017), Gulf of Mexico sea surface temperatures (Molina et al, 2016), antecedent drought conditions (Shepherd et al, 2009), the quasi-biennial oscillation (Baggett et al, 2017;Mundhenk et al, 2018;Son et al, 2017), the Arctic oscillation (Childs et al, 2018), and decadal-scale trends (Diffenbaugh et al, 2013;Tippett, 2014). ENSO has been shown to be a skillful predictor of severe weather activity at seasonal time scales (Allen et al, 2015b;Lepore et al, 2017).…”

“…For intermediate forecast lead times of 2–5 weeks (during the subseasonal portion of the so‐called subseasonal to seasonal time scale), skillful guidance for severe weather activity on weekly timescales is currently in its infancy (Allen et al, ; Barrett & Gensini, ; Barrett & Henley, ; Gensini & Allen, ; Gensini & Marinaro, ; Thompson & Roundy, ). While subseasonal forecasts of severe weather have the potential to increase public awareness and preparedness, they could also be beneficial to stakeholders such as emergency managers, catastrophe modelers, and insurance/reinsurance companies (Allen et al, ; Gunturi & Tippett, ; NOAA/NCEI, ; Simmons & Sutter, ; Smith & Matthews, ).…”

“…Fortunately, to fill the subseasonal forecast gap, prior work has identified sources of predictability that have the potential to improve forecasts of severe weather activity in the United States at subseasonal lead times. Two such promising sources of predictability are the Global Wind Oscillation (Gensini & Allen, 2018;Gensini & Marinaro, 2016;Moore, 2017) and the Madden-Julian Oscillation (MJO; Baggett et al, 2017;Barrett & Gensini, 2013;Barrett & Henley, 2015;Kiladis et al, 2014;Matthews, 2008;Mundhenk et al, 2018;Thompson & Roundy, 2013;Wheeler & Hendon, 2004). In this study, we focus on the MJO, which manifests itself in the form of anomalous tropical convection that propagates around the equator with a period of~30-60 days (Matthews, 2008).…”

Investigation of the temporal variability of thunderstorms in central and western Europe and the relation to large‐scale flow and teleconnection patterns

“…Despite these efforts, little attention has been paid to seasonal or to sub-seasonal climate variability of convective weather over Europe (Tippett et al, 2015). Teleconnections between remote climate signals and thunderstorm frequency have become an area of increasing focus in recent years (Barrett and Gensini, 2013;Lee et al, 2013;Thompson and Roundy, 2013;Allen et al, 2015b;Tippett et al, 2015;Dowdy, 2016;Gensini and Marinaro, 2016;Molina et al, 2016;Cook et al, 2017;Allen et al, 2018;Baggett et al, 2018;Gensini and Allen, 2018;Tippett, 2018;Trapp and Hoogewind, 2018). These modulations to frequency can lead to extreme differences in thunderstorm frequency from year to year, a pattern that is evident in European severe thunderstorm frequency (e.g.…”

An Analysis of Anomalous Winter and Spring Tornado Frequency by Phase of the El Niño/Southern Oscillation, the Global Wind Oscillation, and the Madden-Julian Oscillation

“…Another consideration is that the GWO data used in this study are based on globally integrated AAM. As noted by Gensini and Allen [41], this may confound the results.…”