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Analysis of Tornado-Induced Tree Fall Using Aerial Photography from the Joplin, Missouri, and Tuscaloosa–Birmingham, Alabama, Tornadoes of 2011
Ist Teil von
Journal of applied meteorology and climatology, 2013-05, Vol.52 (5), p.1049-1068
Ort / Verlag
Boston, MA: American Meteorological Society
Erscheinungsjahr
2013
Quelle
EZB Electronic Journals Library
Beschreibungen/Notizen
In this study, aerial imagery of tornado damage is used to digitize the falling direction of trees (i.e., tree fall) along the 22 May 2011 Joplin, Missouri, and 27 April 2011 Tuscaloosa–Birmingham, Alabama, tornado tracks. Normalized mean patterns of observed tree fall from each tornado’s peak-intensity period are subjectively compared with results from analytical vortex simulations of idealized tornado-induced tree fall to characterize mean properties of the near-surface flow as depicted by the model. A computationally efficient method of simulating tree fall is applied that uses a Gumbel distribution of critical tree-falling wind speeds on the basis of the enhanced Fujita scale. Results from these simulations suggest that both tornadoes had strong radial near-surface winds. A few distinct tree-fall patterns are identified at various locations along the Tuscaloosa–Birmingham tornado track. Concentrated bands of intense tree fall, collocated with and aligned parallel to the axis of underlying valley channels, extend well beyond the primary damage path. These damage patterns are hypothesized to be the result of flow acceleration caused by channeling within valleys. Another distinct pattern of tree fall, likely not linked to the underlying topography, may have been associated with a rear-flank downdraft (RFD) internal surge during the tornado’s intensification stage. Here, the wind field was strong enough to produce tornado-strength damage well beyond the visible funnel cloud. This made it difficult to distinguish between tornado- and RFD-related damage and thus illustrates an ambiguity in ascertaining tornado-damage-path width in some locations.