• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.6
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• pp.667-673
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• 2019

Global warming may accelerate climate change and may increase disaster caused by strong winds. This research studied a method for a nonstationary frequency analysis considering the linear trend over time. The Bayesian method was used to estimate the posterior distribution of the parameters for the extreme value distribution of the annual maximum wind speed at Jeju Airport. The nonstationary frequency analysis was performed based on the Monte Carlo Markov Chain simulation and the Gibbs sampling. The estimated wind speeds by nonstationary frequency analysis was larger than those by stationary analysis. The conventional frequency analysis procedure assuming stationarity is likely to underestimate the future design wind speed in the region where statistically significant trend exists.