Comparing Network "Gustiness" Over Various Geographic/Topographic Areas

Near surface wind gusts have a high impact on surface weather, especially in areas of complex and terrain. As wind gust is a result of turbulence which can be very difficult or impractical to model directly this study uses a collection of high density and quality networks to observe a relationship between surface sustained wind speed and gust. These networks span a wide variety of geographic and topographic areas and are dense enough to capture most aspects of the terrain they aim to represent. Using sustained wind speed and gust data from these stations a network “Gust Factor (GF)” is calculated for each and a linear regression performed to assess its ability to reproduce a gust for any given sustained wind speed. Gust factor for each network is also calculated by season, month, hour of the day, wind direction, individual station, and relative elevation within the network to assess how gust factor changes throughout the year, day, or to relative positioning. All calculated gust factors for each network are then compared to each other network to observe any dependency of gust factor on network features such as anemometer mounting height, sampling interval, averaging interval, and overall network homogeneity of measurements. In the future we plan to use these calculated network averages along with high resolution simulations of the network areas to test the hypothesis that departures of station gust factor from network average contain useful information about the station's exposure to surrounding terrain features and can be used to eliminate systematic and otherwise unfixable biases in gust forecasts.