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Hurricane damage assessment for residential construction considering the non-stationarity in hurricane intensity and frequency

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Abstract

Natural hazards such as hurricanes may cause extensive economic losses and social disruption for civil structures and infrastructures in coastal areas, implying the importance of understanding the construction performance subjected to hurricanes and assessing the hurricane damages properly. The intensity and frequency of hurricanes have been reported to change with time due to the potential impact of climate change. In this paper, a probability-based model of hurricane damage assessment for coastal constructions is proposed taking into account the non-stationarity in hurricane intensity and frequency. The non-homogeneous Poisson process is employed to model the non-stationarity in hurricane occurrence while the non-stationarity in hurricane intensity is reflected by the time-variant statistical parameters (e.g., mean value and/or standard deviation), with which the mean value and variation of the cumulative hurricane damage are evaluated explicitly. The Miami-Dade County, Florida, USA, is chosen to illustrate the hurricane damage assessment method proposed in this paper. The role of non-stationarity in hurricane intensity and occurrence rate due to climate change in hurricane damage is investigated using some representative changing patterns of hurricane parameters.

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References

  • Australian Greenhouse Office (AGO). 2007. An assessment of the need to adopt buildings for the unavoidable consequences of climate change. Final report. Canberra, Australia: Commonwealth of Australia, Australian Greenhouse Office

    Google Scholar 

  • Bjarnadottir S, Li Yue, Stewart M G. 2011. A probabilistic-based framework for impact and adaptation assessment of climate change on hurricane damage risks and costs. Structural Safety, 33(3): 173–185

    Article  Google Scholar 

  • Blake E S, Gibney E J. 2011. The deadliest, costliest, and most intense United States tropical cyclones from 1851 to 2010 (and other frequently requested hurricane facts), NOAA technical memorandum NWS NHC-6. Miami, Florida: National Hurricane Center (NHC)

    Google Scholar 

  • Climate Change Science Program (CCSP). 2008. Weather and climate extremes in a changing climate. Regions of focus: North America, Hawaii, Caribbean, and U.S. Pacific Islands. A report by the U.S. climate change science program and the subcommittee on global change research. Washington D C, USA: Department of Commerce, NOAA’s National Climatic Data Center

    Google Scholar 

  • Devore J L. 2000. Probability and Statistics for Engineering and the Sciences. 5th ed. Pacific Grove, CA: Duxbury Press

    Google Scholar 

  • Ellingwood B R, Lee J Y. 2015. Life cycle performance goals for civil infrastructure: intergenerational risk-informed decisions. Structure and Infrastructure Engineering: Maintenance, Management, Life-Cycle Design and Performance, doi: 10.1080/15732479.2015.1064966

    Google Scholar 

  • Elsner J B, Bossak B H. 2001. Bayesian analysis of U.S. hurricane climate. Journal of Climate, 14(23): 4341–4350

    Article  Google Scholar 

  • Emanuel K. 2005. Increasing destructiveness of tropical cyclones over the past 30 years. Nature, 436(7051): 686–688

    Article  Google Scholar 

  • Fitzpatrick P J. 2006. Hurricanes: A Reference Handbook. 2nd ed. Santa Barbara California, USA: ABC-CLIO Ltd

    Google Scholar 

  • Hallegatte S. 2007. The use of synthetic hurricane tracks in risk analysis and climate change damage assessment. Journal of Applied Meteorology and Climatology, 46(11): 1956–1966

    Article  Google Scholar 

  • Holland G J, Webster P J. 2007. Heightened tropical cyclone activity in the North Atlantic: natural variability or climate trend?. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 365(1860): 2695–2716

    Article  Google Scholar 

  • Huang Zhigang, Rosowsky D V, Sparks P R. 2001. Long-term hurricane risk assessment and expected damage to residential structures. Reliability Engineering & System Safety, 74(3): 239–249

    Article  Google Scholar 

  • Jain V K, Davidson R, Rosowsky D. 2005. Modeling changes in hurricane risk over time. Natural Hazards Review, 6(2): 88–96

    Article  Google Scholar 

  • Katz R W. 2002. Stochastic modeling of hurricane damage. Journal of Applied Meteorology, 41(7): 754–762

    Article  Google Scholar 

  • Knutson T R, McBride J L, Chan J, et al. 2010. Tropical cyclones and climate change. Nature Geoscience, 3(3): 157–163

    Article  Google Scholar 

  • Landsea C W. 2007. Counting Atlantic tropical cyclones back to 1900. Eos, Transactions American Geophysical Union, 88(18): 197–202, doi: 10.1029/2007EO180001

    Article  Google Scholar 

  • Landsea C W, Harper B A, Hoarau K, et al. 2006. Can we detect trends in extreme tropical cyclones?. Science, 313(5786): 452–454

    Article  Google Scholar 

  • Li Yue, Ellingwood B R. 2006. Hurricane damage to residential construction in the US: Importance of uncertainty modeling in risk assessment. Engineering Structures, 28(7): 1009–1018

    Article  Google Scholar 

  • Li Yue, Stewart M G. 2011. Cyclone damage risks caused by enhanced greenhouse conditions and economic viability of strengthened residential construction. Natural Hazards Review, 12(1): 9–18

    Article  Google Scholar 

  • Li Quanwang, Wang Cao, Ellingwood B R. 2015. Time-dependent reliability of aging structures in the presence of non-stationary loads and degradation. Structural Safety, 52: 131–142

    Article  Google Scholar 

  • Lin Ning, Emanuel K, Oppenheimer M, et al. 2012. Physically based assessment of hurricane surge threat under climate change. Nature Climate Change, 2(6): 462–467

    Article  Google Scholar 

  • Liu Fangqian. 2012. Development and calibration of central pressure filling rate models for hurricane simulation [dissertation]. South Carolina, USA: Clemson University

    Google Scholar 

  • Mudd L, Wang Yue, Letchford C, et al. 2014. Assessing climate change impact on the U.S. east coast hurricane hazard: temperature, frequency, and track. Natural Hazards Review, 15(3): doi: 10.1061/(ASCE)NH.1527-6996.0000128

    Google Scholar 

  • Pinelli J P, Simiu E, Gurley K, et al. 2004. Hurricane damage prediction model for residential structures. Journal of Structural Engineering, 130(11): 1685–1691

    Article  Google Scholar 

  • Saunders M A, Lea A S. 2008. Large contribution of sea surface warming to recent increase in Atlantic hurricane activity. Nature, 451(7178): 557–560, doi: 10.1038/nature06422

    Article  Google Scholar 

  • Stewart M G, Rosowsky D V, Huang Zhigang. 2003. Hurricane risks and economic viability of strengthened construction. Natural Hazards Review, 4(1): 12–19

    Article  Google Scholar 

  • Unanwa C O, McDonald J R. 2000. Building wind damage prediction and mitigation using damage bands. Natural Hazards Review, 1(4): 197–203

    Article  Google Scholar 

  • Vickery P J, Masters F J, Powell M D, et al. 2009. Hurricane hazard modeling: the past, present, and future. Journal of Wind Engineering and Industrial Aerodynamics, 97(7–8): 392–405

    Article  Google Scholar 

  • Vickery P J, Skerlj P F, Twisdale L A. 2000. Simulation of hurricane risk in the U.S. using empirical track model. Journal of Structural Engineering, 126(10): 1222–1237

    Article  Google Scholar 

  • Vickery P J, Twisdale L A. 1995. Prediction of hurricane wind speeds in the United States. Journal of Structural Engineering, 121(11): 1691–1699

    Article  Google Scholar 

  • Weiss N A. 2014. Introductory Statistics. 9th ed. Harlow, Essex: Pearson

    Google Scholar 

  • Xu Fumin, Bui Thi T D, Perrie W. 2014. The observed analysis on the wave spectra of Hurricane Juan (2003). Acta Oceanologica Sinica, 33(11): 112–122

    Article  Google Scholar 

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Correspondence to Quanwang Li.

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Foundation item: The National Natural Science Foundation of China under contract No. 51578315; the Major Projects Fund of Chinese Ministry of Transport under contract No. 201332849A090.

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Wang, C., Li, Q., Pang, L. et al. Hurricane damage assessment for residential construction considering the non-stationarity in hurricane intensity and frequency. Acta Oceanol. Sin. 35, 110–118 (2016). https://doi.org/10.1007/s13131-016-0828-7

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  • DOI: https://doi.org/10.1007/s13131-016-0828-7

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