Non-stationarity of extreme wind speeds in Hangzhou with time varying exposure

Mingfeng Huang, Qiang Li, Haiwei Xu, Wenjuan Lou, Ning Lin

Research output: Contribution to conferencePaperpeer-review


Extreme wind speed analysis has been carried out conventionally by assuming the extreme series data is stationary. However, time-varying trends of the extreme wind speed series could be detected at many surface meteorological stations in China. Two main reasons, exposure change and climate change, were provided to explain the temporal trends of annual maximum wind speed series data, recorded at Hangzhou (China) meteorological station. After making a correction on wind speed series for time varying exposure, it is necessary to perform non-stationary statistical modelling on the corrected extreme wind speed data series in addition to the classical extreme value analysis. The generalized extreme value (GEV) distribution with time-dependent location and scale parameters was selected as a non-stationary model to describe the corrected extreme wind speed series. The obtained non-stationary extreme value models were then used to estimate the non-stationary extreme wind speed quantiles with various mean recurrence intervals (MRIs), and compared to the corresponding stationary ones with various MRIs for the Hangzhou area in China. The results indicate that the nonstationary characteristics of extreme wind speed data should be carefully evaluated and reflected in the determination of design wind speeds.

Original languageEnglish (US)
StatePublished - 2017
Event9th Asia Pacific Conference on Wind Engineering, APCWE 2017 - Auckland, New Zealand
Duration: Dec 3 2017Dec 7 2017


Conference9th Asia Pacific Conference on Wind Engineering, APCWE 2017
Country/TerritoryNew Zealand

All Science Journal Classification (ASJC) codes

  • Energy Engineering and Power Technology
  • Renewable Energy, Sustainability and the Environment


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