Examining strong winds from a time-varying perspective
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Engineers commonly use numerical and laboratory models to represent the wind and evaluate its impacts on structures. There are some key assumptions incorporated into these models including neutral stability and stationarity. The implication of these assumptions is that the turbulence characteristics of the wind are the same given a common surface roughness. The Synoptic Wind And Thunderstorm Hurricane (SWATH) field experiment was conducted to collect high temporal and spatial resolution data from various strong wind events to evaluate the adequacy of these fundamental assumptions. The four events discussed in this study included a thunderstorm out ow, a pre-frontal environment, a strong surface low, and a hurricane. The data from these events were analyzed utilizing the Hilbert-Huang Transform in a time-dependent framework. Traditional turbulence statistics and commonly used empirical models were evaluated and modified. The results suggested that despite having similar surface roughness, the events were unique, and that the empirical models generally did not agree with the observed cases. The Hilbert-Huang Transform provided a way to develop a time-varying mean, but also exhibited difficulty handling intermittency within the time history.