Hybrid Prediction of Weekly Tornado Activity Out to Week 3: Utilizing Weather Regimes

Abstract

Tornadoes are one of the high-impact weather phenomena that can induce life loss and property damage. Here, we investigate the relationship between large-scale weather regimes and tornado occurrence in boreal spring. Results show that weather regimes strongly modulate the probability of tornado occurrence in the United States due to changes in shear and convective available potential energy and that persisting weather regimes (lasting ≥3 days) contribute to greater than 70% of outbreak days (days with ≥10 tornadoes). A hybrid model based on the weather regime frequency predicted by a numerical model is developed to predict above/below normal weekly tornado activity and has skill better than climatology out to Week 3. The hybrid model can be applied to real-time forecasting and aide in mitigation of severe weather events.Plain Language Summary Severe storms that are capable of producing tornadoes, strong winds, and hail may lead to a high number of fatalities and property damage. The relationship between tornadoes and the large-scale, recurrent weather patterns over the United States is investigated. It is shown that specific weather patterns may alter tornado activity and that persisting weather patterns contribute to greater than 70% of tornado outbreak days. Finally, a hybrid model is created to predict tornado activity, and the skill of the model is better than using a long-term average out to Week 3, which is an improvement of the current forecasting state.

Major Changes in Extreme Dust Events Dynamics Over the Arabian Peninsula During 2003–2017 Driven by Atmospheric Conditions

“…(ii) Severe widespread prolonged dust events are triggered and maintained by persistent synoptic circulations (e.g., Beegum et al., 2018; Dumka et al., 2019; Hamidi et al., 2017, 2014; Houssos et al., 2015; Knippertz & Fink, 2006; Knippertz & Stuut, 2014; Shao et al., 2010; Solomos et al., 2017). A synoptic circulation should sustain at least 3 days to reach its persistent nature (e.g., Guemas et al., 2010, 2009; Kyselý & Domonkos, 2006; Miller et al., 2020). All the identified dust events in our study are widespread in nature and affect most of the Arabian Peninsula and its surrounding regions.…”

Skillful Subseasonal Prediction of United States Extreme Warm Days and Standardized Precipitation Index in Boreal Summer

“…It is important to reiterate that the predictors influence the occurrence of extreme heat events with a few weeks lag, and a statistical model like the one developed in this study can be used in conjunction with operational models at the shorter lead times as the operational forecast skill is much larger at week 1 and week 2. Recently, the authors demonstrated the importance and value of simple statistical and empirical models in predicting winter Eurasian atmospheric blocking (Miller and Wang 2019) and springtime U.S. severe weather (D. E. Miller et al 2020). As with the previous studies, the MLR model here may serve as a benchmark for operational models at weeks 3 and 4 over the eastern United States while aiding in irrigation scheduling, crop planning, reservoir operation, and providing mitigation of impacts from extreme heat events.…”

“…This study aims to predict the number of EWDs per week and 14-day standardized precipitation index (SPI) with a focus on weeks 3 and 4. Here, EWDs are defined as a day with a detrended daily average temperature greater than the 90th percentile of all July and August days from 1980 to 2017 at each grid point (Miller and Wang 2019). The field is smoothed by averaging a 58 3 58 box centered at each grid point.…”

Using the daily change in the Southern Oscillation Index to develop analogues and the relationship to severe weather outbreaks

“…A similar result was found recently by Gensini and Marinaro (2016) who used global atmospheric angular momentum time series and the change with time or Miller et al . (2020) who used a statistical‐dynamic model of weather regimes to demonstrate skill in anticipating tornado outbreak days 1–3 weeks prior to the event. These investigations examined only tornado days while this work included other severe convective weather phenomena such as hail and wind events.…”

“…Also, Miller et al . (2020) use a hybrid statistical–dynamic technique to project tornado outbreak frequency out to week three with skill better than climatology. Their paper examined the association of severe weather with persistent weather regimes during May, which is the peak month for the occurrence of tornadoes.…”