Evaluating the Effects of Disjunct Sampling and Averaging Time on Extreme Synoptic-Scale Wind Speeds

This study evaluates the effects of sampling interval and averaging period on the assessment of extreme synoptic-scale mean wind speeds for structural design, excluding hurricanes and mesoscale events, to focus on correction factors for the standard meteorological observations that are archived for more than 35,000 stations around the globe. A literature review reveals insights and flaws in past works that influenced the design of the two phases of the study. The first phase uses 2-minute mean wind speeds at 1 minute intervals over, typically, 20 years from 642 well-exposed stations distributed over the contiguous USA that are averaged to the World Meteorological Organization standard ten-minute and hourly means. Informed by the first stage results, which confirm good representation by the Weibull distribution with a von Karman autocorrelation, the second phase uses simulated 1000-year time series to investigate the parameters governing the effects, which are: sampling interval, averaging period, integral timescale of the autocorrelation, and the return period of the extremes. The effects of these four parameters, in any combination, consolidate into a single analytical equation with empirically calibrated coefficients, which is a good match to the empirical analysis of the first phase, when using the appropriate integral timescale.