Advertisement

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

  • Yunxia Guo
  • Yijun HouEmail author
  • Peng QiEmail author
Article
  • 5 Downloads

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 (CMA-STI), 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.

Keyword

typhoon hazard analysis Monte-Carlo simulation wind field model extreme wind speed 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Notes

Acknowledgment

Data from the CMA-STI Best Track Dataset for Tropical Cyclones over the Western North Pacific online dataset are gratefully acknowledged. Thanks are extended to the reviewers.

References

  1. American Society of Civil Engineers. 2005. ASCE/SEI 7-05 minimum design loads for buildings and other structures. ASCE, US.Google Scholar
  2. Batts M E, Simiu E, Russell L R. 1980. Hurricane wind speeds in the United States. Journal of the Structural Division, 106(10): 2 001–2 016.Google Scholar
  3. Chen K M. 1981. The typhoon pressure field and wind field models. Acta Oceanologica Sinica, 3(1): 44–56. (in Chinese with English abstract)CrossRefGoogle Scholar
  4. Chen K M. 1992. A new method calculating typhoon wind field. Marine Forecasts, 9(3): 60–65. (in Chinese with English abstract)Google Scholar
  5. Cui W, Caracoglia L. 2015. Simulation and analysis of intervention costs due to wind-induced damage on tall buildings. Engineering Structures, 87: 183–197.CrossRefGoogle Scholar
  6. Cui W, Caracoglia L. 2016. Exploring hurricane wind speed along US Atlantic coast in warming climate and effects on predictions of structural damage and intervention costs. Engineering Structures, 122: 209–225.CrossRefGoogle Scholar
  7. Fang G S, Zhao L, Cao S Y, Ge Y J, Pang W C. 2018a. A novel analytical model for wind field simulation under typhoon boundary layer considering multi-field correlation and height-dependency. Journal of Wind Engineering and Industrial Aerodynamics, 175: 77–89.CrossRefGoogle Scholar
  8. Fang G S, Zhao L, Song L L, Liang X D, Zhu L D, Cao S Y, Ge Y J. 2018b. Reconstruction of radial parametric pressure field near ground surface of landing typhoons in Northwest Pacific Ocean. Journal of Wind Engineering and Industrial Aerodynamics, 183: 223–234.CrossRefGoogle Scholar
  9. Georgiou P N, Davenport A G, Vickery B J. 1983. Design wind speeds in regions dominated by tropical cyclones. Journal of Wind Engineering and Industrial Aerodynamics, 13(1–3): 139–152.CrossRefGoogle Scholar
  10. Georgiou PN. 1986. Design Wind Speeds in Tropical Cyclone-Prone Regions. University of Western Ontario, London, Canada.Google Scholar
  11. Harper B A, Holland G J. 1999. An updated parametric model of the tropical cyclone. In: Proceedings of the 23rd Conference on Hurricanes and Tropical Meteorology. AMS, Dallas, Texas.Google Scholar
  12. Holland G J. 1980. An analytic model of the wind and pressure profiles in hurricanes. Monthly Weather Review, 108(8): 1 212–1 218.CrossRefGoogle Scholar
  13. Hong H P, Li S H, Duan Z D. 2016. Typhoon wind hazard estimation and mapping for coastal region in mainland China. Natural Hazards Review, 17(2): 04016001.CrossRefGoogle Scholar
  14. Hubbert G D, Holland G J, Leslie L M, Manton M J. 1991. A real-time system for forecasting tropical cyclone storm surges. Weather and Forecasting, 6(1): 86–97.CrossRefGoogle Scholar
  15. Jakobsen F, Madsen H. 2004. Comparison and further development of parametric tropical cyclone models for storm surge modelling. Journal of Wind Engineering and Industrial Aerodynamics, 92(5): 375–391.CrossRefGoogle Scholar
  16. Jiang Z H, Hua F, Qu P. 2008. A new scheme for adjusting the tropical cyclone parameters. Advances in Marine Science, 26(1): 1–7. (in Chinese with English abstract)Google Scholar
  17. Lee K H, Rosowsky D V. 2007. Synthetic hurricane wind speed records: development of a database for hazard analyses and risk studies. Natural Hazards Review, 8(2): 23–34.CrossRefGoogle Scholar
  18. Li Q S, Fang J Q, Jeary A P, Wong C K, Liu D K. 2000. Evaluation of wind effects on a supertall building based on full-scale measurements. Earthquake Engineering & Structural Dynamics, 29(12): 1 845–1 862.CrossRefGoogle Scholar
  19. Li Q S, Fang J Q, Jeary A P, Wong C K. 1998. Full scale measurements of wind effects on tall buildings. Journal of Wind Engineering and Industrial Aerodynamics, 74-76: 741–750.CrossRefGoogle Scholar
  20. Li Q S, Xiao Y Q, Wong C K, Jeary A P. 2004. Field measurements of typhoon effects on a super tall building. Engineering Structures, 26(2): 233–244.CrossRefGoogle Scholar
  21. Li Q, Duan Z D. 2005. Shapiro typhoon wind-field model and its numerical simulation. Journal of Natural Disasters, 14(1): 45–52. (in Chinese with English abstract)Google Scholar
  22. Li R L. 2007. Prediction of Typhoon Extreme Wind Speeds based on Improved Typhoon Key Parameters. Harbin Institute of Technolog, Harbin, China. (in Chinese with English abstract)Google Scholar
  23. Li S H, Hong H P. 2014. Observations on a hurricane wind hazard model used to map extreme hurricane wind speed. Journal of Structural Engineering, 141(10): 04014238.CrossRefGoogle Scholar
  24. Li S H, Hong H P. 2015. Use of historical best track data to estimate typhoon wind hazard at selected sites in China. Natural Hazards, 76(2): 1 395–1 414.CrossRefGoogle Scholar
  25. Li S H, Hong H P. 2016. Typhoon wind hazard estimation for China using an empirical track model. Natural Hazards, 82(2): 1 009–1 029.CrossRefGoogle Scholar
  26. Li T, Lei Y, Xu Z Q, Liu C. 2009. Initiative research on typhoon simulation by YanMeng wind field model. Journal of Xiamen University (Natural Science), 48(6): 840–843. (in Chinese with English abstract)Google Scholar
  27. Li X L, Pan Z D, She J. 1995. A method for adjustment of typhoon parameters. Journal of Oceanography of Huanghai & Bohai Seas, 13(2): 11–15. (in Chinese with English abstract)Google Scholar
  28. Lin W, Fang W H. 2013. Regional characteristics of Holland B parameter in typhoon wind field model for Northwest Pacific. Tropical Geography, 33(2): 124–132. (in Chinese with English abstract)Google Scholar
  29. Matsui M, Ishihara T, Hibi K. 2002. Directional characteristics of probability distribution of extreme wind speeds by typhoon simulation. Journal of Wind Engineering and Industrial Aerodynamics, 90(12–15): 1 541–1 553.CrossRefGoogle Scholar
  30. Meng Y, Matsui M, Hibi K. 1993. A theoretical analysis of the wind field in the typhoon boundary layer. Journal of Wind Engineering, 55: 7–8. (in Japanese)Google Scholar
  31. Meng Y, Matsui M, Hibi K. 1995. An analytical model for simulation of the wind field in a typhoon boundary layer. Journal of Wind Engineering and Industrial Aerodynamics, 56(2–3): 291–310.CrossRefGoogle Scholar
  32. Ministry of Housing and Urban-Rural Construction of the People’s Republic of China. 2012. GB 50009-2012 Load code for the design of building structures. Construction Industry Press of China, Beijing. (in Chinese)Google Scholar
  33. Mudd L, Wang Y, Letchford C, Rosowsky D. 2014. Assessing climate change impact on the U.S. east coast hurricane hazard: temperature, frequency, and track. Natural Hazards Review, 15(3): 04014001.CrossRefGoogle Scholar
  34. National Institute of Building Science. 2009. HAZUS-MH MR4 hurricane model technical manual. Federal Emergency Management Agency.Google Scholar
  35. Neumann C J. 1987. The National Hurricane Center Risk Analysis Program (HURISK). NOAA Tech. Memo. NWS-NHC-38, U.S. Department of Commerce, National Oceanic and Atmospheric Administration, National Hurricane Center, Miami.Google Scholar
  36. Ou J P, Duan Z D, Chang L. 2002. Typhoon risk analysis for key coastal cities in southeast China. Journal of Natural Disasters, 11(4): 9–17. (in Chinese with English abstract)Google Scholar
  37. Powell M, Soukup G, Cocke S, Gulati S, Morisseau-Leroy N, Hamid S, Dorst N, Axe L. 2005. State of Florida hurricane loss projection model: atmospheric science component. Journal of Wind Engineering and Industrial Aerodynamics, 93(8): 651–674.CrossRefGoogle Scholar
  38. Rosowsky D V. Mudd L, Letchford C. 2016. Assessing climate change impact on the joint wind-rain hurricane hazard for the northeastern U.S. coastline. In: Gardoni P, Murphy C, Rowell A eds. Risk Analysis of Natural Hazards: Interdisciplinary Challenges and Integrated Solutions. Springer, Cham. p. 79–92.Google Scholar
  39. Russell L B. 1969. Probability Distributions for Texas Gulf Coast Hurricane Effects of Engineering Interest. Stanford University, Stanford.Google Scholar
  40. Russell L R. 1971. Probability distributions for hurricane effects. Journal of the Waterways, Harbors and Coastal Engineering Division, 97(1): 139–154.Google Scholar
  41. Shapiro L J. 1983. The Asymmetric boundary layer flow under a translating hurricane. Journal of the Atmospheric Sciences, 40(8): 1 984–1 998.CrossRefGoogle Scholar
  42. She J, Yuan Y L, Pan Z D. 1995. Numerical model of the typhoon wind field over the sea surface and its hindcast calibration. Acta Oceanologica Sinica, 17(3): 24–31. (in Chinese)Google Scholar
  43. Sheng L F, Wu Z M. 1993. A new fitting method for sea surface wind field of typhoon. Journal of Tropical Meteorology, 9(3): 265–271. (in Chinese with English abstract)Google Scholar
  44. Simiu E, Scanlan R H. 1996. Wind Effects on Structures: Fundamentals and Applications to Design. John Wiley & Sons, Inc., New York.Google Scholar
  45. Standards Association of Australia. 2002. AS/NZS 1170.2:2002 structural design actions part2: wind actions. Standards Association of Australia, New Zealand.Google Scholar
  46. Tao L Y, Yan J Y, Xu J L. 2001. Application of Monte-Carlo simulation method in wind engineering. Journal of Nanjing Institute of Meteorology, 24(3): 410–414. (in Chinese with English abstract)Google Scholar
  47. Thompson E F, Cardone V J. 1996. Practical modeling of hurricane surface wind fields. Journal of Waterway, Port, Coastal, and Ocean Engineering, 122(4): 195–205.CrossRefGoogle Scholar
  48. Typhoon Network of China. 2002. http://www.typhoon.org.cn/. Accessed on 2002-03-01. (in Chinese)
  49. Vickery P J, Skerlj P F, Steckley A C, Twisdale L A. 2000a. Hurricane wind field model for use in hurricane simulations. Journal of Structural Engineering, 126(10): 1 203–1 221.CrossRefGoogle Scholar
  50. Vickery P J, Skerlj P F, Twisdale L A. 2000b. Simulation of hurricane risk in the U.S. using empirical track model. Journal of Structural Engineering, 126(10): 1 222–1 237.CrossRefGoogle Scholar
  51. Vickery P J, Twisdale L A. 1995a. Prediction of hurricane wind speeds in the United States. Journal of Structural Engineering, 121(11): 1 691–1 699.CrossRefGoogle Scholar
  52. Vickery P J, Twisdale L A. 1995b. Wind-field and filling models for hurricane wind-speed predictions. Journal of Structural Engineering, 121(11): 1 700–1 709.CrossRefGoogle Scholar
  53. Vickery P J, Wadhera D, Twisdale L A, Lavelle F M. 2009. U.S. hurricane wind speed risk and uncertainty. Journal of Structural Engineering, 135(3): 301–320.CrossRefGoogle Scholar
  54. Vickery P J, Wadhera D. 2008. Statistical models of Holland pressure profile parameter and radius to maximum winds of hurricanes from flight-level pressure and H*Wind data. Journal of Applied Meteorology and Climatology, 47(10): 2 497–2 517.CrossRefGoogle Scholar
  55. Vickery P J. 2005. Simple empirical models for estimating the increase in the central pressure of tropical cyclones after landfall along the coastline of the United States. Journal of Applied Meteorology, 44(12): 1 807–1 826.CrossRefGoogle Scholar
  56. Wei W. 2009. Typhoon Wind Hazard Analysis of Shenzhen based on Wind-Field Model Numerical Simulation. Harbin Institute of Technology, Shenzhen. (in Chinese with English abstract)Google Scholar
  57. Xiao Y F, Duan Z D, Xiao Y Q, Ou J P, Chang L, Li Q S. 2011. Typhoon wind hazard analysis for southeast China coastal regions. Structural Safety, 33(4–5): 286–295.CrossRefGoogle Scholar
  58. Xiao Y F. 2011. Typhoon wind hazard analysis based on numerical simulation and fragility of light-gauge steel structure in southeast China coastal regions. Harbin Institute of Technology, Harbin, China. (in Chinese with English abstract)Google Scholar
  59. Xie R Q, Li X L, Wang Y H, Fang D X. 2015. Typhoon wind numerical simulation and hazard analysis for Guangdong Province. Journal of Anhui Jianzhu University, 23(4): 51–55. (in Chinese with English abstract)Google Scholar
  60. Xie R Q, Wu T, Wang Y H. 2014. Adaptability research on typhoon wind-field model. Journal of Hefei University (Natural Sciences), 24(2): 84–88. (in Chinese with English abstract)Google Scholar
  61. Xie R Q. 2008. Numerical simulation and typhoon wind hazard analysis based on CE wind-field model and Yan Meng wind-field mode. Harbin Institute of Technology, Harbin, China. (in Chinese with English abstract)Google Scholar
  62. Yasui H, Ohkuma T, Marukawa H, Katagiri J. 2002. Study on evaluation time in typhoon simulation based on Monte Carlo method. Journal of Wind Engineering and Industrial Aerodynamics, 90(12–15): 1 529–1 540.CrossRefGoogle Scholar
  63. Zhao L, Ge Y J, Song L L, Mao H Q. 2007. Monte-Carlo simulation analysis of typhoon extreme value wind characteristics in Guangzhou. Journal of Tongji University (Natural Science), 35(8): 1 034–1 038, 1 068. (in Chinese with English abstract)Google Scholar
  64. Zhao L, Ge Y J, Xiang H F. 2005. Application of typhoon stochastic simulation and its extreme value wind prediction. Journal of Tongji University (Natural Science), 33(7): 885–889. (in Chinese with English abstract)Google Scholar
  65. Zhao L, Lu A P, Zhu L D, Cao S Y, Ge Y J. 2013. Radial pressure profile of typhoon field near ground surface observed by distributed meteorologic stations. Journal of Wind Engineering and Industrial Aerodynamics, 122: 105–112.CrossRefGoogle Scholar

Copyright information

© Chinese Society for Oceanology and Limnology, Science Press and Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Key Laboratory of Ocean Circulation and Waves, Institute of OceanologyChinese Academy of SciencesQingdaoChina
  2. 2.University of Chinese Academy of SciencesBeijingChina
  3. 3.Laboratory for Ocean and Climate DynamicsQingdao National Laboratory for Marine Science and TechnologyQingdaoChina
  4. 4.Center for Ocean Mega-ScienceChinese Academy of SciencesQingdaoChina

Personalised recommendations