Understanding tornado trends is crucial for enhancing societal resilience. Previous research by Brooks et al. (2014) revealed a paradoxical trend: a decrease in annual tornado days coupled with an increase in outbreak days (days with numerous tornadoes). This study expands on that work by examining the temporal (seasonality) and geographical (regionality) aspects of these trends across the contiguous United States (CONUS) from 1960 to 2022. The calendar year is important because of varying levels of preparedness, and geographical location is significant due to differing population densities, socioeconomic factors, and housing conditions across tornado-prone areas. The research also addresses whether these trends have persisted in the past decade, considering the influence of anthropogenic climate change (ACC) and the possibility of multi-decadal cycles driven by internal climate variability.

The study builds upon previous work exploring tornado trends, including investigations into seasonal variations and regional shifts in activity. Brooks et al. (2014) established the initial dichotomy between decreasing tornado days and increasing outbreak days. Subsequent research by Moore (2017, 2019) and others (Childs et al., 2018; Trapp & Hoogewind, 2018; Gensini & Brooks, 2018; Moore, 2018) examined the spatial and temporal characteristics of tornadoes with varying levels of granularity. The authors reference studies that have explored the links between tornado activity and factors such as ENSO phases and North Atlantic SST variability, as well as the impacts of climate teleconnections and changes in observational practices. These prior studies provide a context for understanding the complexities of tornado climatology and the need for a more detailed investigation into regional and seasonal trends.

Utilizing the NOAA Storm Prediction Center (SPC) tornado report database from 1960 to 2022, the study followed a methodology similar to Brooks et al. (2014), defining a tornado day as any day with at least one (E)F-1+ tornado and a tornado outbreak day as any day with more than 30 (E)F-1+ tornadoes. Linear trends were calculated for both metrics. To address challenges with the 30-tornado threshold for outbreak days (yielding a small number of events), the analyses were repeated using thresholds of >10 and >20 tornadoes. The time series was further disaggregated by month and by warm (April-July) versus cool (November-February) seasons. Trends were calculated for individual states within tornado-prone regions (Southern Great Plains and Southeast). The study also examined the frequency of days with varying numbers of tornadoes (>10, >15, >20, >25) across three periods (1960-1979, 1980-1999, 2000-2022) for the Southern Great Plains and Southeast regions. Finally, interannual variability was assessed using annual differences in tornado reports and 15-year rolling standard deviations.

Over the 63-year period, the study found a statistically significant decrease in tornado days (1.03 days per year) and a statistically significant increase in tornado outbreak days (0.04 days per year). However, these linear trends showed reversals in the most recent decade. The analysis of monthly data revealed statistically significant negative trends in tornado days from March through September, with particularly dramatic decreases in June, July, and August, primarily in the Southern Great Plains. A three-week shift in the peak probability of a U.S. tornado day was observed (from June 14th to May 24th). Regional analysis showed significant warm-season decreases in tornado days across the Southern Great Plains, with the largest decrease in Texas. In contrast, the Southeast U.S. showed increases in both warm and cool-season tornado days, contributing significantly to the upward trend in outbreak days. This regional dichotomy suggests the 'fewer days, more tornadoes' tendency is driven largely by activity in the Southeast. The interannual variability analysis suggests larger volatility in warm seasons and a contribution from the Southeast to the overall increase in volatility in recent decades. The year 2011, an anomalously active year, significantly influenced the volatility trends.

The findings confirm and extend previous research showing a complex pattern of change in U.S. tornado activity. The observed decrease in tornado days, particularly during the warm season in the Southern Great Plains, coupled with an increase in outbreak days predominantly in the Southeast, highlights the regional and seasonal specificity of these trends. The shift in peak tornado probability underscores the implications for preparedness and mitigation efforts. The recent relaxation of these trends raises questions about the relative contributions of internal climate variability and anthropogenic climate change. While the observed changes may partly reflect internal variability or multidecadal cycles, the potential influence of ACC on large-scale circulation patterns, such as the jet stream, warrants further research. The increase in outbreak days, characterized by more intense and impactful tornadoes, emphasizes the need for improved forecasting and community preparedness, particularly in vulnerable communities in the Southeast.

This study provides a comprehensive analysis of U.S. tornado trends, highlighting regional and seasonal variations. The contrasting patterns between the Southern Great Plains and the Southeast underscore the complexity of tornado activity and the need for geographically and temporally nuanced preparedness strategies. Future research should focus on disentangling the relative roles of internal climate variability and anthropogenic forcing, and on improving the understanding and predictability of tornado outbreaks, especially in vulnerable regions. The limitations of the report-based dataset emphasize the value of incorporating meteorological proxy data to strengthen future analyses.

The study's reliance on a report-based dataset introduces limitations inherent to such data, including known biases and uncertainties in tornado detection and reporting. The relatively short historical record of comprehensive tornado data also limits the ability to fully characterize long-term trends and variability. Future work could incorporate meteorological proxies to help mitigate these limitations and provide a more robust understanding of tornado activity changes.