Cite this paper:
GUO Yunxia, HOU Yijun, QI Peng. Analysis of typhoon wind hazard in Shenzhen City by Monte-Carlo Simulation[J]. Journal of Oceanology and Limnology, 2019, 37(6): 1994-2013

Analysis of typhoon wind hazard in Shenzhen City by Monte-Carlo Simulation

GUO Yunxia1,2,4, HOU Yijun1,3,4, QI Peng1,3,4
1 Key Laboratory of Ocean Circulation and Waves, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China;
2 University of Chinese Academy of Sciences, Beijing 100049, China;
3 Laboratory for Ocean and Climate Dynamics, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266237, China;
4 Center for Ocean Mega-Science, Chinese Academy of Sciences, Qingdao 266071, China
Abstract:
As one of the most serious natural disasters, many typhoons affect southeastern China every year. Taking Shenzhen, a coastal city in southeast China as an example, we employed a Monte-Carlo simulation to generate a large number of virtual typhoons for wind hazard analysis. By analyzing 67-year historical typhoons data from 1949 to 2015 using the Best Track Dataset for Tropical Cyclones over the Western North Pacific recorded by the Shanghai Typhoon Institute, China Meteorological Administration (CMASTI), typhoon characteristic parameters were extracted and optimal statistical distributions established for the parameters in relation to Shenzhen. We employed the Monte-Carlo method to sample each distribution to generate the characteristic parameters of virtual typhoons. In addition, the Yan Meng (YM) wind field model was introduced, and the sensitivity of the YM model to several parameters discussed. Using the YM wind field model, extreme wind speeds were extracted from the virtual typhoons. The extreme wind speeds for different return periods were predicted and compared with the current structural code to provide improved wind load information for wind-resistant structural design.
Key words:    typhoon hazard analysis|Monte-Carlo simulation|wind field model|extreme wind speed   
Received: 2018-09-07   Revised: 2019-02-28
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