[Objective] The aim of this paper was to analyze the risks in the typhoon hazard factors in Hainan Island. [Method] Taking the theory and method of natural disasters evaluation as starting point and supporting point, ...[Objective] The aim of this paper was to analyze the risks in the typhoon hazard factors in Hainan Island. [Method] Taking the theory and method of natural disasters evaluation as starting point and supporting point, and selecting Hainan province as the research target, where the typhoon disaster occurred relatively serious, based on the typhoon data during 1958-2008, with happening frequency of typhoon hazard-formative factors, maximum rainfall, potentially devastating effects of typhoon winds as evaluation indexes, the typhoon disaster risk evaluation index system and evaluation model were established. And by dint of GIS technique, Hainan island typhoon disaster risk zoning of hazard-formative factors and grading were prepared. [Result] Typhoon occurred frequently in Hainan and there were no certain rules of its annual changes. The monthly changes mainly happed during July to October. The highly dangerous area of typhoon mainly distributed in east coast area. The annual daily precipitation decreased from central mountainous area to the surroundings; typhoon hided in the destructive highly risked area in east, south and west area; low disastrous area occurred in the middle area; the risks of disastrous factors weakened from east area to west area. The distribution area of each level was that low dangerous area>mild dangerous area>highly dangerous area>secondary low dangerous area>highly dangerous area. [Conclusion] The study supplied scientific reference for the government in the united organization and direction of disaster relief work.展开更多
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 ...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 Yah 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.展开更多
基金Supported by Hainan Natural Fund Program (809058)Key Operation Suggestion Program of China Meteorological Bureau " Typhoon Disaster Risk Evaluation and Division"
文摘[Objective] The aim of this paper was to analyze the risks in the typhoon hazard factors in Hainan Island. [Method] Taking the theory and method of natural disasters evaluation as starting point and supporting point, and selecting Hainan province as the research target, where the typhoon disaster occurred relatively serious, based on the typhoon data during 1958-2008, with happening frequency of typhoon hazard-formative factors, maximum rainfall, potentially devastating effects of typhoon winds as evaluation indexes, the typhoon disaster risk evaluation index system and evaluation model were established. And by dint of GIS technique, Hainan island typhoon disaster risk zoning of hazard-formative factors and grading were prepared. [Result] Typhoon occurred frequently in Hainan and there were no certain rules of its annual changes. The monthly changes mainly happed during July to October. The highly dangerous area of typhoon mainly distributed in east coast area. The annual daily precipitation decreased from central mountainous area to the surroundings; typhoon hided in the destructive highly risked area in east, south and west area; low disastrous area occurred in the middle area; the risks of disastrous factors weakened from east area to west area. The distribution area of each level was that low dangerous area>mild dangerous area>highly dangerous area>secondary low dangerous area>highly dangerous area. [Conclusion] The study supplied scientific reference for the government in the united organization and direction of disaster relief work.
基金Supported by the National Key Research and Development Program of China(Nos.2016YFC1402004,2016YFC1402000,2018YFC1407003)the National Natural Science Foundation of China(Nos.U1706216,U1606402,41421005)
文摘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 Yah 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.
