15.5 An Overview of the ASCE/SEI/AMS Standard on Wind Speed Estimation Chapter on Treefall Pattern and Forest Damage Analysis

Thursday, 1 February 2024: 2:45 PM
342 (The Baltimore Convention Center)
Christopher M. Godfrey, PhD, University of North Carolina Asheville, Asheville, NC; and C. Karstens, C. J. Peterson, and F. T. Lombardo

The American Society of Civil Engineers (ASCE)/Structural Engineering Institute (SEI)/American Meteorological Society (AMS) Standard on Wind Speed Estimation draft chapter entitled "Treefall Pattern and Forest Damage Analysis" describes three techniques to estimate tornado wind speed. The Godfrey–Peterson, Lombardo, and Karstens methods each retrospectively analyze treefall patterns or forest damage caused by a tornado. The Lombardo and Karstens methods require the creation of a detailed database of digitized, georeferenced treefall vectors. These methods attempt to achieve a match between the observed treefall patterns and simulated treefall patterns produced by the wind field from an idealized axisymmetric vortex model. Wind speed estimates stem from the characteristics of the simulated wind field that produces the best match to either the observed treefall patterns or derived properties of those patterns. In contrast, the Godfrey–Peterson method uses the results of a coupled wind and tree resistance model to estimate the most probable wind speed associated with distinct levels of forest damage in small subplots along the entire tornado track. The Lombardo and Karstens methods apply most naturally to small patches or groves of trees, while the Godfrey–Peterson method works best for large, continuous expanses of forest, though each method can provide useful information in any setting that meets minimum requirements for that method. The choice to use a particular wind speed estimation method depends upon the specific circumstances of the damage assessment, including data availability, the spatial coverage of trees, characteristics of the terrain, and analysis tools available to the user.
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