Earth and Atmospheric Sciences, Department of


Date of this Version



A THESIS Presented to the Faculty of The Graduate College at the University of Nebraska In Partial Fulfillment of Requirements For the Degree of Master of Science, Major: Earth and Atmospheric Sciences, Under the Supervision of Professor Clinton M. Rowe. Lincoln, Nebraska: December 2012

Copyright 2012 Jeramie M. Lippman


Nonconvective winds can be a dangerous and costly weather hazard. For example, over a ten year span from 2002 to 2011, there were over 200 fatalities and nearly 1,000 injuries, as well as over 6.4 billion dollars in monetary losses due to high, nonconvective winds. An important subset to nonconvective winds is the nonconvective wind gust. When winds are already relatively strong, a sudden wind gust can magnify already existing hazards. Three different methods were evaluated to determine if either of two physically based algorithms can outperform an empirical algorithm. The two physically based methods were the Wind Gust Estimate (WGE) method and the Air Force Weather Agency (AFWA) method. The empirical method was the Mean Gust Factor (MGF) method. Rapid Update Cycle (RUC) model analysis data were ingested into each algorithm and the resultant output was compared against the observed wind gust field. Each of the methods was evaluated from 10 March 2005 through 31 May 2005 over the CONUS, over eleven different geographical regions, and over portions of three neighboring states. Separate evaluations were also conducted for 2100 UTC and 0900 UTC over the CONUS to discern any diurnal variations in the capabilities of each method. The MGF method generally outperformed the other two methods in each of the test scenarios. Each of the physically based methods outperformed the other, depending on the test scenario, and each performed better during the daytime hours than at night. The MGF method, while performing reasonably well during the day, performed best at night. Sample size seemed to have an impact on method performance amongst the various regions.

Adviser: Clinton M. Rowe

Included in

Meteorology Commons