Climate and solar signals in property damage losses from hurricanes affecting the United States

Natural Hazards

Volumn 58, Issue 1, 2011, Pages 541-557

  Jagger, Thomas H ^a   Elsner, James B ^a   Burch, King ^b  

^a FLORIDA STATE UNIVERSITY   (United States)

^b NONE   (United States)

Author keywords

Environment; Hurricanes; Loss model; MCMC; Property damage; Risk compound Poisson

Indexed keywords

CLIMATE SIGNAL; EL NINO; HURRICANE; MARKOV CHAIN; MONTE CARLO ANALYSIS; NUMERICAL MODEL; RISK ASSESSMENT; STATISTICAL ANALYSIS; STORM DAMAGE; WATER TEMPERATURE;

ATLANTIC OCEAN; ATLANTIC OCEAN (NORTH); UNITED STATES;

EID: 79958841787     PISSN: 0921030X     EISSN: None     Source Type: Journal    
DOI: 10.1007/s11069-010-9685-4     Document Type: Article

References (31)

1. Changnon SA (2009) Characteristics of severe Atlantic hurricanes in the United States: 1949-2006. Nat Hazards 48(3): 329-337. doi: 10. 1007/s11069-008-9265-z.
2. Changnon SA, Changnon D (2009) Assessment of a method used to time adjust past storm losses. Nat Hazards 50(1): 5-12. doi: 10. 1007/s11069-008-9307-6.
3. Coles S (2001) An introduction to statistical modeling of extreme values. Springer, London.
4. Coles S, Pericchi L, Sisson S (2003) A fully probabilistic approach to extreme rainfall modeling. J Hydrol 273(1-4): 35-50.
5. Coles SG, Tawn JA (1996) A Bayesian analysis of extreme rainfall data. J Royal Stat Soc Ser C (Appl Stat) 45(4): 463-478, http://www. jstor. org/stable/2986068.
6. Elsner JB, Jagger TH (2004) A hierarchical Bayesian approach to seasonalhurricane modeling. J Clim 17(14): 2813-2827.
7. Elsner JB, Jagger TH (2006) Prediction models for annual US hurricane counts. J Clim 19(12): 2935-2952.
8. Elsner JB, Jagger TH (2008) United States and Caribbean tropical cyclone activity related to the solar cycle. Geophys Res Lett 35(18). doi: 10. 1029/2008GL034431.
9. Elsner JB, Bossak BH, Niu XF (2001) Secular changes to the ENSO-US hurricane relationship. Geophys Res Lett 28(21): 4123-4126.
10. Elsner JB, Niu XF, Jagger TH (2004) Detecting shifts in hurricane rates using a Markov chain Monte Carlo approach. J Clim 17(13): 2652-2666.
11. Elsner JB, Kossin JP, Jagger TH (2008) The increasing intensity of the strongest tropical cyclones. Nat Biotechnol 455(7209): 92-95. doi: 10. 1038/nature07234.
12. Elsner JB, Jagger TH, Hodges RE (2010) Daily tropical cyclone intensity response to solar ultraviolet radiation. Geophys Res Lett 37. doi: 10. 1029/2010GL043091.
13. Emanuel KA (1991) The theory of hurricanes. Annu Rev Fluid Mech 23: 179-196.
14. Gilks WR, Richardson S, Spiegelhalter DJ (1998) Markov chain Monte Carlo in practice. Chapman & Hall, Boca Raton, Fla., 98033429 edited by W. R. Gilks, S. Richardson, and D. J. Spiegelhalter. ill. ; 25 cm. Previously published: London : Chapman & Hall, 1996. Includes bibliographical references and index.
15. Hsieh P (2004) A data-analytic method for forecasting next record catastrophe loss. J Risk Insur 71(2): 309-322.
16. Jagger TH, Elsner JB (2006) Climatology models for extreme hurricane winds near the United States. J Clim 19(13): 3220-3236.
17. Jagger TH, Elsner JB, Niu XF (2001) A dynamic probability model of hurricane winds in coastal counties of the United States. J Appl Meteorol 40: 853-863.
18. Jagger TH, Elsner JB, Saunders MA (2008) Forecasting US insured hurricane losses. In: Murnane RJ, Diaz HF (eds) Climate extremes and society, chap 10. Cambridge University Press, Cambridge.
19. Jagger TH, Elsner JB, Burch KR (2010) Environmental signals in property damage losses from hurricanes. In: Elsner JB, Hodges RE, Malmstadt JC, Scheitlin KN (eds) Hurricanes and climate change, vol. 2, chap 6. Springer, New York.
20. Jones PD, Jonsson T, Wheeler D (1997) Extension to the North Atlantic oscillation using early instrumental pressure observations from Gibraltar and south-west Iceland. Int J Climatol 17(13): 1433-1450.
21. Katz RW (2002) Stochastic modeling of hurricane damage. J Appl Meteorol 41(7): 754-762.
22. Katz RW, Parlange MB, Naveau P (2002) Statistics of extremes in hydrology. Adv Water Resour 25(8-12): 1287-1304.
23. Leckebusch GC, Ulbrich U, Froehlich L, Pinto JG (2007) Property loss potentials for European midlatitude storms in a changing climate. Geophys Res Lett 34(5). doi: 10. 1029/2006GL027663.
24. Malmstadt JC, Scheitlin KN, Elsner JB (2009) Florida hurricanes and damage costs. Southeastern Geographer 49: 108-131.
25. Murnane RJ, Barton C, Collins E, Donnelly J, Elsner J, Emanuel K, Ginis I, Howard S, Landsea C, Liu K, Malmquist D, McKay M, Michaels A, Nelson N, O'Brien J, Scott D, Webb T III (2000) Model estimates hurricane wind speed probabilities. EOS Trans 81: 433-433. doi: 10. 1029/00EO00319.
26. Pielke RA, Gratz J, Landsea CW, Collins D, Saunders MA, Musulin R (2008) Normalized hurricane damage in the united states: 1900-2005. Nat Hazards Rev 9(1): 29-42 doi: 10. 1061/(ASCE1527-6988(2008)9: 1(29)) http://link. aip. org/link/?QNH/9/29/1.
27. Ropelewski CF, Jones PD (1987) An extension of the Tahiti-Darwin Southern oscillation index. Mon Weather Rev 115(9): 2161-2165.
28. Saunders MA, Lea AS (2005) Seasonal prediction of hurricane activity reaching the coast of the United States. Nat Biotechnol 434(7036): 1005-1008. doi: 10. 1038/nature03454.
29. Spiegelhalter DJ, Best NG, Gilks WR, Inskip H (1996) Hepatitis B: a case study in MCMC methods. In: Gilks WR, Richardson S, Spiegelhalter DJ (eds) Markov Chain Monte Carlo in practice, chap 2. Chapman & Hall/CRC, London, pp 21-43.
30. Spiegelhalter DJ, Best NG, Carlin BP, van der Linde A (2002) Bayesian measures of model complexity and fit. J Royal Stat Soc Ser B (Stat Methodol) 64(Part 4): 583-616.
31. Walshaw D (2000) Modelling extreme wind speeds in regions prone to hurricanes. J Royal Stat Soc Ser C (Appl Stat) 49(Part 1): 51-62.