Wind and Structures

Techno-Press (테크노프레스)
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Non-stationary statistical modeling of extreme wind speed series with exposure correction

  • Huang, Mingfeng (Institute of Structural Engineering, College of Civil Engineering & Architecture, Zhejiang University) ;
  • Li, Qiang (Institute of Structural Engineering, College of Civil Engineering & Architecture, Zhejiang University) ;
  • Xu, Haiwei (Institute of Structural Engineering, College of Civil Engineering & Architecture, Zhejiang University) ;
  • Lou, Wenjuan (Institute of Structural Engineering, College of Civil Engineering & Architecture, Zhejiang University) ;
  • Lin, Ning (Department of Civil and Environmental Engineering, Princeton University)
  • Received : 2017.10.18
  • Accepted : 2018.01.13
  • Published : 2018.03.25
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Abstract

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 daily maximum wind speed and 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 modeling 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) considering changing climate, and compared to the corresponding stationary ones with various MRIs for the Hangzhou area in China. The results indicate that the non-stationary property or dependence of extreme wind speed data should be carefully evaluated and reflected in the determination of design wind speeds.

Keywords

Acknowledgement

Supported by : National Natural Science Foundation of China

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