Are Some Cities Disproportionally Affected by Tornadoes
Bibliographic Data
| ID | 3775807 |
|---|---|
| Authors | Cooper P Corey (University of Tennessee at Knoxville, corresponding author), Jason C Senkbeil (University of Alabama), Kevin M Curtin (0000-0002-2850-7845, University of Alabama) |
| Year | 2025 |
| Volume | 115 |
| Issue | 1 |
| Pages | 19-38 |
| Publication date | 2025-01-02 |
| Peer Reviewed | Yes |
| Open Access | No |
| Type | ARTICLE |
| Venue | Annals of the American Association of Geographers (JOURNAL) |
| Journal identifiers | ISSN: 2469-4452 • E-ISSN: 2469-4460 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/24694452.2024.2412171 |
| OpenAlex | W4404070377 |
| Language | EN |
| References cited | 34 |
Despite the danger presented to communities, there is still a notable lack of knowledge on how the locations of tornadoes and tornado tracks, especially for violent tornadoes (VTs), vary on small spatial scales, such as in counties or cities. Certain cities like Moore, Oklahoma, have seen an abnormal number of VTs (three) compared to neighboring towns since the beginning of the historic record in 1950. The primary goal of this research was to determine if the atypical pattern of tornadoes seen in Moore and other selected cities can be replicated by random chance. This was done by generating Monte Carlo–style simulations of random tornado initial points and comparing the results with the actual number of tornadoes to determine the likelihood of the actual number of tornadoes occurring in these cities by random chance. Results show that it is difficult to replicate actual tornado patterns in the selected cities, indicating an unlikelihood of the cities’ historic tornado patterns occurring by random chance alone. The model was unable to replicate or overestimate the actual number of tornadoes greater than Enhanced Fujita 0 (>EF0) for Birmingham and Tuscaloosa, Alabama, or Wichita, Kansas. Additionally, the model could not replicate or overestimate Moore’s actual number of VTs at a rate exceeding 1 percent in any trial. The actual VT rates for Birmingham, Tuscaloosa, and Tanner, Alabama, were also notably difficult to replicate. One-sample t tests revealed that the average number of simulated total tornadoes > EF0 and VTs were significantly lower than what the cities have experienced. Furthermore, t tests show that the model was more capable of replicating the number of tornadoes from each category in cities adjacent to the primary cities, suggesting that the number of tornadoes hitting the latter is significantly greater than what would occur randomly. Possible meteorological and nonmeteorological explanations are discussed. Future research will require more cities to be analyzed to improve our understanding of small-scale tornado track variability and the degree of randomness involved. Potential findings from such study would be beneficial for emergency managers, urban planners, and the real estate and insurance industries
Economic geography · Geography · Meteorology · Regional science · Tornado · Flood Risk Assessment and Management · Meteorological Phenomena and Simulations · Tropical and Extratropical Cyclones Research
Tornado Fatalities in Context
Finescale Assessment of Mobile Home Tornado Vulnerability in the Central and Southeast United States
Observed and Projected Changes in United States Tornado Exposure
Spatiotemporal Analysis of Near-Miss Violent Tornadoes in the United States
Spatiotemporal Changes in Tornado Hazard Exposure
Exploring Spatial Patterns of Virginia Tornadoes Using Kernel Density and Space-Time Cube Analysis (1960–2019)
The Human Ecology of Tornadoes
Seasonal Frequency and Spatial Distribution of Tornadoes in the United States and Their Relationship to the El Niño/Southern Oscillation
| Citation velocity | historical |
|---|---|
| Highly cited | No |