Articles | Volume 16, issue 12
https://doi.org/10.5194/nhess-16-2823-2016
https://doi.org/10.5194/nhess-16-2823-2016
Research article
 | 
21 Dec 2016
Research article |  | 21 Dec 2016

Spatial–temporal clustering of tornadoes

Bruce D. Malamud, Donald L. Turcotte, and Harold E. Brooks

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Cited articles

Adlerman, E. J., Droegemeier, K. K., and Davies-Jones, R.: A numerical simulation of cyclic mesocyclogenesis, J. Atmos. Sci., 56, 2045–2069, https://doi.org/10.1175/1520-0469(1999)056<2045:ANSOCM>2.0.CO;2, 1999.
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Bluestein, H. B. and Weisman, M. L.: The interaction of numerically simulated supercells initiated along lines, Mon. Weather Rev., 128, 3128–3149, https://doi.org/10.1175/1520-0493(2000)128<3128:TIONSS>2.0.CO;2, 2000.
Brooks, H. E.: On the relationship of tornado path length and width to intensity, Weather Forecast., 19, 310–319, https://doi.org/10.1175/1520-0434(2004)019<0310:OTROTP>2.0.CO;2, 2004.
Burgess, D. W., Wood, V. T., and Brown, R. A.: Mesocyclone evolution statistics. 12th Conf. on Severe Local Storms, San Antonio, TX, Amer. Meteor. Soc., 422–424, 1982.
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Short summary
We introduce a novel method for the spatial–temporal cluster analysis of severe tornado touchdowns that are part of tornado outbreaks. Tornado outbreaks, groups of tornadoes occurring close to each other in time and space, constitute a severe hazard that has few quantitative measures. Our new approach, which we illustrate using three USA severe tornado outbreaks and models, differentiates between types of tornado outbreaks and, within outbreaks, identifies clusters in both time and space.
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