Severe Storms / Tornadic Storms

Future Changes in Tropical Cyclone Tornadoes

Tornadoes are a co-occurring extreme that can be produced by landfalling tropical cyclones (TCs). These tornadoes can exacerbate the loss of life and property damage caused by the TC from which they were spawned. It is uncertain how the severe weather environments of landfalling TCs may change in a future climate and how this could impact tornado activity from TCs. In this study, we investigated four TCs that made landfall in the U.S. and produced large tornado outbreaks. We performed four-member ensembles of convective-allowing (4-km resolution) regional climate model simulations representing each TC in the historical climate and a mid-twenty-first century future climate. To identify potentially tornadic storms, or TC-tornado (TCT) surrogates, we used thresholds for three-hourly maximum updraft helicity and maximum radar reflectivity, as tornadoes are not resolved in the model. We found that the ensemble-mean number of TCT-surrogates increased substantially (56–299%) in the future, supported by increases in most-unstable convective available potential energy, surface-to-700-hPa bulk wind shear, and 0–1-km storm-relative helicity in the tornado-producing region of the TCs. On the other hand, future changes in most-unstable convective inhibition had minimal influence on future TCT-surrogates. This provides robust evidence that tornado activity from TCs may increase in the future. Furthermore, TCT-surrogate frequency between 00Z and 09Z increased for three of the four cases, suggesting enhanced tornado activity at night, when people are asleep and more likely to miss warnings. All of these factors indicate that TC-tornadoes may become more frequent and a greater hazard in the future, compounding impacts from future increases in TC winds and precipitation.

• Forbis, D. C., Patricola, C. M., Bercos-Hickey, E. & Gallus, W. A., Jr. (2024). Mid-Century Climate Change Impacts on Tornado-Producing Tropical Cyclones. Weather and Climate Extremes, 44, 100684.

_{This research was supported by the U.S. Department of Energy Office of Science (BER RGMA program) under Early Career Research Program Award Number DE-SC0021109.  High-performance computing resources provided by the Texas Advanced Computing Center (TACC) at The University of Texas at Austin.}

Anthropogenic Influences on Tornadic Storms

The impact of climate change on severe storms and tornadoes remains uncertain, largely owing to inconsistencies in observational data and limitations of climate models. We performed ensembles of convection-permitting climate model simulations to examine how three tornadic storms would change if similar events were to occur in pre-industrial and future climates. The choice of events includes winter, nocturnal, and spring tornadic storms to provide insight into how the timing and seasonality of storms may affect their response to climate change. Updraft helicity (UH), convective available potential energy (CAPE), storm-relative helicity (SRH), and convective inhibition (CIN) were used to determine the favorability for the three tornadic storm events in the different climate states. We found that from the pre-industrial period to the present, the potential for tornadic storms decreased for the winter event and increased for the nocturnal and spring events. With future climate change, the potential for tornadic storms increased for the winter and nocturnal events in association with increased CAPE, and decreased for the spring event despite greater CAPE.

• Bercos-Hickey, E., Patricola, C. M., & Gallus, W. A., Jr. (2021). Anthropogenic Influences on Tornadic Storms. Journal of Climate, 34(22), 8989–9006.

_{This research was supported by the Department of Defense.  High-performance computing resources provided by the National Energy Research Scientific Computing Center (NERSC).}

Future Changes in Early-Season Severe Thunderstorms

Hazardous convective weather (HCW; i.e. tornadoes, large hail, and severe wind) is a damaging phenomenon of extreme weather. However, future spatiotemporal changes in HCW are unknown, in part associated with the high computational cost of convection-permitting (4 km) global climate model simulations. We used the Weather Research and Forecasting (WRF) model to conduct convection-permitting simulations to project future changes in early-season (January - April) HCW over the central-to-eastern U.S. Simulations were performed for a historical period (1991-2000) and a future period (2091-2100) forced by Representative Concentration Pathway 8.5. HCW occurrence, defined as updraft vertical velocity (UVV) exceeding 18 m/s in a favorable environment, is projected to increase by 173% in the future based on convection-permitting simulations. The future increases in HCW were supported by increases in UVV, HCW environmental favorability primarily driven by CAPE, and the conditional probability of HCW occurrence. Finally, a random forest model trained on convection-permitting data and run using coarser input data reproduces a future increase in HCW occurrence, but overpredicts the percent increase by 4.25 times. If further advances in machine learning methods can be used to predict storm-scale variables from coarser resolution data, computational costs could be reduced by performing coarse resolution global model simulations and applying machine learning to infer information at finer spatial scales. 

• Erickson, N. E., & Patricola, C. M. (2025). Future Changes in Early-Season Severe Thunderstorms: A Comparison of Machine Learning and Convection-Permitting Dynamical Downscaling. Artificial Intelligence for the Earth Systems, in revision.

_{This research was supported by Iowa State University, College of Liberal Arts and Sciences, and by the U.S. Department of Energy Office of Science (BER RGMA program).  High-performance computing resources provided by the National Energy Research Scientific Computing Center (NERSC).}

_{updated 6/11/2025}