Editorial Type:
Article
Article Type:
Research Article

The Relationship between Elevation Roughness and Tornado Activity: A Spatial Statistical Model Fit to Data from the Central Great Plains

James B. Elsner Department of Geography, Florida State University, Tallahassee, Florida

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Tyler Fricker Department of Geography, Florida State University, Tallahassee, Florida

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Holly M. Widen Department of Geography, Florida State University, Tallahassee, Florida

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Carla M. Castillo Department of Geography, Florida State University, Tallahassee, Florida

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John Humphreys Department of Geography, Florida State University, Tallahassee, Florida

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Jihoon Jung Department of Geography, Florida State University, Tallahassee, Florida

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Shoumik Rahman Department of Geography, Florida State University, Tallahassee, Florida

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Amanda Richard Department of Geography, Florida State University, Tallahassee, Florida

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Thomas H. Jagger Department of Geography, Florida State University, Tallahassee, Florida

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Tachanat Bhatrasataponkul Department of Earth, Ocean, and Atmospheric Sciences, Florida State University, Tallahassee, Florida

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Christian Gredzens Department of Earth, Ocean, and Atmospheric Sciences, Florida State University, Tallahassee, Florida

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P. Grady Dixon Department of Geosciences, Fort Hays State University, Fort Hays, Kansas

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Print Publication:
01 Apr 2016
DOI:
https://doi.org/10.1175/JAMC-D-15-0225.1
Page(s):
849–859
Restricted access

Abstract

The statistical relationship between elevation roughness and tornado activity is quantified using a spatial model that controls for the effect of population on the availability of reports. Across a large portion of the central Great Plains the model shows that areas with uniform elevation tend to have more tornadoes on average than areas with variable elevation. The effect amounts to a 2.3% [(1.6%, 3.0%) = 95% credible interval] increase in the rate of a tornado occurrence per meter of decrease in elevation roughness, defined as the highest minus the lowest elevation locally. The effect remains unchanged if the model is fit to the data starting with the year 1995. The effect strengthens for the set of intense tornadoes and is stronger using an alternative definition of roughness. The elevation-roughness effect appears to be strongest over Kansas, but it is statistically significant over a broad domain that extends from Texas to South Dakota. The research is important for developing a local climatological description of tornado occurrence rates across the tornado-prone region of the Great Plains.

Corresponding author address: James B. Elsner, Dept. of Geography, Florida State University, 113 Collegiate Loop, Tallahassee, FL 32306. E-mail: jelsner@fsu.edu

Abstract

The statistical relationship between elevation roughness and tornado activity is quantified using a spatial model that controls for the effect of population on the availability of reports. Across a large portion of the central Great Plains the model shows that areas with uniform elevation tend to have more tornadoes on average than areas with variable elevation. The effect amounts to a 2.3% [(1.6%, 3.0%) = 95% credible interval] increase in the rate of a tornado occurrence per meter of decrease in elevation roughness, defined as the highest minus the lowest elevation locally. The effect remains unchanged if the model is fit to the data starting with the year 1995. The effect strengthens for the set of intense tornadoes and is stronger using an alternative definition of roughness. The elevation-roughness effect appears to be strongest over Kansas, but it is statistically significant over a broad domain that extends from Texas to South Dakota. The research is important for developing a local climatological description of tornado occurrence rates across the tornado-prone region of the Great Plains.

Corresponding author address: James B. Elsner, Dept. of Geography, Florida State University, 113 Collegiate Loop, Tallahassee, FL 32306. E-mail: jelsner@fsu.edu
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Cover Journal of Applied Meteorology and Climatology
Journal of Applied Meteorology and Climatology

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