Date of Award

May 2016

Degree Type

Thesis

Degree Name

Master of Science

Department

Mathematics

First Advisor

Jon Kahl

Committee Members

Paul Roebber, Clark Evans

Keywords

Climatology, Forecasting, Gust, Gust Factors, Wind

Abstract

Wind gust forecasts are difficult given the small spatial and temporal scales at which they occur. As a result, a variety of statistical and numerical modeling approaches are used to forecast wind gusts, but a best practice has yet to be determined. One statistical approach, called a gust factor, is advantageous in its simplicity, and is often used operationally. Derived empirically from hourly and one-minute wind observations, we establish a climatology of gust factors for the 2000 to 2014 period at Milwaukee, WI. The gust factors are then stratified by wind speed, direction, time of day and year, and stability to gain insight into the potential sensitivities of the gust factor. Once the climatology of gust factors was established, the ability of the gust factor to forecast wind gusts was assessed deterministically for a variety of wind scenarios. The results suggest that gust factors derived from the standard hourly observational data tend to under-forecast the peak wind each hour. Some stratified gust factors show improvements relative to the non-stratified, mean gust factors. However, nearly all gust factor models show improvements relative to persistence and climatology forecasts.

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