Modeling the Temporal Correlation in Hurricane Frequency for Damage Assessment of Residential Structures Subjected to Climate Change
Publication: Journal of Structural Engineering
Volume 143, Issue 5
Abstract
Severe hurricanes in coastal areas have caused enormous human and economic losses. Furthermore, the intensity and frequency of future hurricanes may increase due to the potential impact of climate change. Due to common underlying climatological causes, interrelations may exist between successive hurricane events. This paper proposes a novel approach for modeling the temporal correlation in hurricane frequency and develops an analytical method that reflects this correlation to estimate the statistical properties of cumulative hurricane damage. The method provides a closed-form solution to the mean and variance of hurricane damage, and can be used to assess the impacts of temporal correlation and nonstationarity in hurricane events quantitatively. The applicability of the method is demonstrated through a case study of Miami-Dade County, Florida, in which it is found that the nonstationarity in hurricane events increases the mean value of hurricane damage over a future period of 100 years, while the temporal correlation increases its variance.
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Acknowledgments
The research described in this paper was supported by National Natural Science Foundation of China under Grant number 51578315, and the International Program Development Fund from the University of Sydney. The support from TNList, Tsinghua University is also acknowledged. The author would like to acknowledge the thoughtful suggestions of three anonymous reviewers which substantially improved the present paper.
References
AGO (Australian Greenhouse Office). (2007). “An assessment of the need to adopt buildings for the unavoidable consequences of climate change.” Canberra, Australia.
Artiles, A. (2006). “Florida public hurricane loss projection model: Calibration and validation of vulnerability matrices with 2004 hurricane season claim data.” Ph.D. thesis, Dept. of Civil Engineering, Florida Institute of Technology, Melbourne, FL.
ASCE. (2012). “Minimum design loads for buildings and other structures.” Reston, VA.
Bjarnadottir, S., Li, Y., and Stewart, M. G. (2011). “A probabilistic-based framework for impact and adaptation assessment of climate change on hurricane damage risks and costs.” Struct. Saf., 33(3), 173–185.
Ellingwood, B. R., and Lee, J. Y. (2015). “Life cycle performance goals for civil infrastructure: Intergenerational risk-informed decisions.” Struct. Infrastruct. Eng., 12(7), 822–829.
Emanuel, K. A. (2005a). “Increasing destructiveness of tropical cyclones over the past 30 years.” Nature, 436(7051), 686–688.
Emanuel, K. A. (2005b). Divine wind: The history and science of hurricanes, Oxford University Press, New York.
Emery, X., and Cornejo, J. (2010). “Truncated Gaussian simulation of discrete-valued, ordinal coregionalized variables.” Comput. Geosci., 36(10), 1325–1338.
Florida Department of Financial Services. (2006). “Task force on long-term solutions for Florida’s hurricane insurance market.” ⟨http://www.myfloridacfo.com/HurricaneInsuranceTaskForce⟩ (Sep. 17, 2015).
Holland, G. J., and Webster, P. J. (2007). “Heightened tropical cyclone activity in the North Atlantic: Natural variability or climate trend?” R. Soc. London Philos. Trans., 365(1860), 2695–2716.
Huang, Z., Rosowsky, D. V., and Sparks, P. R. (2001). “Long-term hurricane risk assessment and expected damage to residential structures.” Reliab. Eng. Syst. Saf., 74(3), 239–249.
Ibrahim, N. A., and Suliadi, S. (2011). “Generating correlated discrete ordinal data using R and SAS IML.” Comput. Methods Prog. Biomed., 104, e122–e132.
IPCC (Intergovernmental Panel on Climate Change). (2014). “Climate Change 2014: Synthesis Rep. Contribution of Working Groups I, II and III to the Fifth Assessment Rep. of the Intergovernmental Panel on Climate Change,” Geneva.
Katz, R. W. (2002). “Stochastic modeling of hurricane damage.” J. Appl. Meteorol., 41(7), 754–762.
Khanduri, A. C., and Morrow, G. C. (2003). “Vulnerability of buildings to windstorms and insurance loss estimation.” J. Wind Eng. Ind. Aerodyn., 91(4), 455–467.
Knutson, T. R., et al. (2010). “Tropical cyclones and climate change.” Nat. Geosci., 3(3), 157–163.
Landsea, C. W. (2007). “Counting Atlantic tropical cyclones back to 1900.” Eos Trans. AGU, 88(18), 197–202.
Landsea, C. W., Harper, B. A., and Hoarau, K. (2006). “Can we detect trends in extreme tropical cyclones?” Science, 313(5786), 452–454.
Lee, J. Y., and Ellingwood, B. R. (2013). “Intergenerational risk-informed decision framework for civil infrastructure.” Proc., Int. Conf. on Structural Safety and Reliability, SIASSAR, New York.
Lee, J. Y., and Ellingwood, B. R. (2015). “Ethical discounting for civil infrastructure decisions extending over multiple generations.” Struct. Saf., 57, 43–52.
Li, Q., Wang, C., and Zhang, H. (2016). “A probabilistic framework for hurricane damage assessment considering non-stationarity and correlation in hurricane actions.” Struct. Saf., 59, 108–117.
Li, S. H., and Hong, H. P. (2015). “Observations on a hurricane wind hazard model used to map extreme hurricane wind speed.” J. Struct. Eng., .
Li, Y., and Ellingwood, B. R. (2006). “Hurricane damage to residential construction in the US: Importance of uncertainty modeling in risk assessment.” Eng. Struct., 28(7), 1009–1018.
Mudd, L., Wang, Y., Letchford, C., and Rosowsky, D. (2014a). “Assessing climate change impact on the US east coast hurricane hazard: Temperature, frequency, track.” Nat. Hazards Rev., .
Mudd, L., Wang, Y., Letchford, C., and Rosowsky, D. (2014b). “Hurricane wind hazard assessment for a rapidly warming climate scenario.” J. Wind Eng. Ind. Aerodyn., 133, 242–249.
NOAA (National Oceanic and Atmospheric Administration). (2016). “Historical hurricane tracks.” ⟨http://coast.noaa.gov/hurricanes/⟩.
Olsen, J. R. (2015). “Adapting infrastructure and civil engineering practice to a changing climate.” ASCE, Reston, VA.
Pielke, R. A., Jr., Gratz, J., Landsea, C. W., Collins, D., Saunders, M. A., and Musulin, R. (2008). “Normalized hurricane damage in the United States: 1900–2005.” Nat. Hazard Rev., 29–42.
Pinelli, J. P., Johnson, T., Pita, G. L., and Gurley, K. (2013). “Life-cycle assessment of personal residential roof decking and cover under hurricane threats.” Advances in hurricane engineering: Learning from our past, ASCE, Reston, VA, 483–495.
Rose, S. M. (2010). Introduction to probability models, 10th Ed., Elsevier, Oxford, U.K.
Saunders, M. A., and Lea, A. S. (2008). “Large contribution of sea surface warming to recent increase in Atlantic hurricane activity.” Nature, 451(7178), 557–560.
Sparks, P. R., Schiff, S. D., and Reinhold, T. A. (1994). “Wind damage to envelopes of houses and consequent insurance losses.” J. Wind Eng. Ind. Aerodyn., 53(1), 145–155.
Stewart, M. G., Rosowsky, D. V., and Huang, Z. (2003). “Hurricane risks and economic viability of strengthened construction.” Nat. Hazards Rev., 12–19.
Stewart, M. G., Wang, X., and Nguyen, M. N. (2011). “Climate change impact and risks of concrete infrastructure deterioration.” Eng. Struct., 33(4), 1326–1337.
Vickery, P. J., Masters, F. J., Powell, M. D., and Wadhera, D. (2009). “Hurricane hazard modeling: The past, present and future.” J. Wind Eng. Ind. Aerodyn., 97(7–8), 392–405.
Vickery, P. J., Skerlj, P. F., Steckley, A. C., and Twisdale, L. A. (2000). “Hurricane wind field model for use in hurricane simulations.” J. Struct. Eng., 1203–1221.
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Published In
Journal of Structural Engineering
Volume 143 • Issue 5 • May 2017
Copyright
©2016 American Society of Civil Engineers.
History
Received: Oct 28, 2015
Accepted: Sep 29, 2016
Published online: Nov 30, 2016
Discussion open until: Apr 30, 2017
Published in print: May 1, 2017
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