Using Extreme Value Theory to Assess the Mortality Risk of Tornado Outbreaks
Vilane Gonçalves Sales , Eric Strobl
International Journal of Disaster Risk Science ›› 2023, Vol. 14 ›› Issue (1) : 14 -25.
Using Extreme Value Theory to Assess the Mortality Risk of Tornado Outbreaks
The majority of tornado fatalities occur during severe thunderstorm occurrences that produce a large number of tornadoes, termed tornado outbreaks. This study used extreme value theory to estimate the impact of tornado outbreaks on fatalities while accounting for climate and demographic factors. The findings indicate that the number of fatalities increases with the increase of tornado outbreaks. Additionally, this study undertook a counterfactual analysis to determine what would have been the probability of a tornado outbreak under various climatic and demographic scenarios. The results of the counterfactual study indicate that the likelihood of increased mortality increases as the population forecast grows. Intensified El Niño events, on the other hand, reduce the likelihood of further fatalities. La Niña events are expected to increase probability of fatalities.
Climate change / Demography / Extreme value theory / Fatalities / Tornado outbreaks
| [1] |
|
| [2] |
|
| [3] |
|
| [4] |
Arias, P., N. Bellouin, E. Coppola, R. Jones, G. Krinner, J. Marotzke, V. Naik, M.D. Palmer, et al. 2021. Technical summary. In Climate change 2021: The physical science basis. Contribution of Working Group I to the sixth assessment report of the Intergovernmental Panel on Climate Change, ed. V. Masson-Delmotte, P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, et al., 33−144. Cambridge, UK: Cambridge University Press. |
| [5] |
|
| [6] |
|
| [7] |
|
| [8] |
|
| [9] |
|
| [10] |
|
| [11] |
|
| [12] |
|
| [13] |
|
| [14] |
|
| [15] |
|
| [16] |
|
| [17] |
|
| [18] |
Finkenstadt, B., and H. Rootzén (eds.). 2003. In Extreme values in finance, telecommunications, and the environment. Boca Raton: CRC Press. |
| [19] |
|
| [20] |
|
| [21] |
|
| [22] |
Gilleland, E., and R.W. Katz. 2016. extRemes 2.0: An extreme value analysis package in R. Journal of Statistical Software 72(8): 1–39. |
| [23] |
|
| [24] |
|
| [25] |
Lipika, B. 2018. Multivariate extreme value theory with an application to climate data in the Western Cape Province. Master’s thesis. Department of Statistical Sciences, University of Cape Town, South Africa. |
| [26] |
McPhaden, M.J., A. Santoso, and W. Cai (eds.). 2020. In El Niño Southern Oscillation in a changing climate. Hoboken, NJ: John Wiley & Sons. |
| [27] |
|
| [28] |
NOAA (National Oceanic and Atmospheric Administration). 2020. Storm Prediction Center – NOAA/National Weather Service. https://www.spc.noaa.gov/. Accessed 20 Jul 2021. |
| [29] |
|
| [30] |
|
| [31] |
|
| [32] |
|
| [33] |
|
| [34] |
|
| [35] |
|
| [36] |
|
| [37] |
|
| [38] |
|
| [39] |
Tippett, M.K., and J.E. Cohen. 2016. Tornado outbreak variability follows Taylor’s power law of fluctuation scaling and increases dramatically with severity. Nature Communications 7(1): Article 10668. |
| [40] |
Tippett, M.K., and C. Lepore. 2021. ENSO‐based predictability of a regional severe thunderstorm index. Geophysical Research Letters 48(18): Article e2021GL094907. |
| [41] |
|
| [42] |
Towler, E., D. Llewellyn, A. Prein, and E. Gilleland. 2020. Extreme-value analysis for the characterization of extremes in water resources: A generalized workflow and case study on New Mexico monsoon precipitation. Weather and Climate Extremes 29: Article 100260. |
| [43] |
U.S. Census Bureau. 2020. Decennial census of population and housing. http://data.census.gov. Accessed 12 Dec 2020. |
| [44] |
|
| [45] |
|
/
| 〈 |
|
〉 |