The Empirical Dependence of Tornadogenesis on Elevation Roughness: Historical Record Analysis Using Bayes’s Law in Arkansas

Abstract

Recent research suggests that surface elevation variability may influence tornado activity, though separating this effect from reporting biases is difficult to do in observations. Here we employ Bayes’s law to calculate the empirical joint dependence of tornado probability on population density and elevation roughness in the vicinity of Arkansas for the period 1955–2015. This approach is based purely on data, exploits elevation and population information explicitly in the vicinity of each tornado, and enables an explicit test of the dependence of results on elevation roughness length scale. A simple log-link linear regression fit to this empirical distribution yields an 11% decrease in tornado probability per 10-m increase in elevation roughness at fixed population density for large elevation roughness length scales (15–20 km). This effect increases by at least a factor of 2 moving toward smaller length scales down to 1 km. The elevation effect exhibits no time trend, while the population bias effect decreases systematically in time, consistent with the improvement of reporting practices. Results are robust across time periods and the exclusion of EF1 tornadoes and are consistent with recent county-level and gridded analyses. This work highlights the need for a deeper physical understanding of how elevation heterogeneity affects tornadogenesis and also provides the foundation for a general Bayesian tornado probability model that integrates both meteorological and nonmeteorological parameters.

Differences in tornado activities and key tornadic environments between China and the United States

“…As observed in GD, terrain may have an important impact on the differences in tornado activities between the United States and China. Previous statistical analyses over the Great Plains and Arkansas have shown that terrain roughness has a negative effect on the tornado probability at a fixed population density (Jagger et al ., 2015; Elsner et al ., 2016; Hua and Chavas, 2019). China has fairly mountainous regions in the south, from Guangdong to Zhejiang Provinces.…”

Statistical and Empirical Relationships between Tornado Intensity and Both Topography and Land Cover Using Rapid-Scan Radar Observations and a GIS

“…Rev.). Furthermore, topography and the frictional properties of the land cover have been proven to affect the vortex's intensity and physical structure (Lewellen 2012(Lewellen , 2014, and they may influence its genesis (Kellner and Niyogi 2014;Schenkman et al 2014;Roberts et al 2016;Lyza and Knupp 2018;Hua and Chavas 2019). Recent numerical simulations have provided additional support of these relationships (e.g., Coffer and Parker 2017;Dahl et al 2017;Fiedler 2017).…”

“…Despite the foundation provided by early laboratory simulations and recent numerical simulations, to date, there have been no peer-reviewed observational studies quantitatively investigating how the intensity of a tornado may be affected by topography or surface friction. Although some work has been devoted to examining the relationships between tornado behavior (genesis/decay, structure, path, and intensity) and surface topography, many of these studies have been idealized in some manner, and those that are observational [except Lyza and Knupp (2018) and Hua and Chavas (2019)] only analyzed a small number of cases or a singular event. Multiple observational studies have investigated ties between tornadogenesis and surface roughness 1 (e.g., Lamb 1957;Hardy 1971;Fujita 1973;Snider 1977;Elsom and Meaden 1982;Kellner and Niyogi 2014) but most of these studies suffer from spatiotemporal deficiencies, and, furthermore, their results have also been conflicting.…”

Idealized Simulations of a Supercell Interacting with an Urban Area

“…In addition to gradients in atmospheric properties, supercells have also been found to be influenced by variability in land surface characteristics, particularly terrain [14][15][16][17]. Some studies have also noted that tornado development in supercells may be impacted by elevation changes [18][19][20][21][22] while others have explored the link between tornado formation and variations in surface roughness [22][23][24]. Numerical simulations have also shown that the development of near-ground rotation is sensitive to surface friction magnitude [25][26][27].…”