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Original Research Papers

Atlantic basin, U.S. and Caribbean landfall activity rates over the 2006–2010 period: an insurance industry perspective

Authors:

Manuel Lonfat ,

RMS Ltd., 30 Monument Street, London EC3R 8NB, GB
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Auguste Boissonnade,

RMS Inc., 7015 Gateway Blvd, Newark, CA, US
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Robert Muir-Wood

RMS Ltd., 30 Monument Street, London EC3R 8NB, GB
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Abstract

Atlantic hurricane activity has been particularly high since 1995, with nine seasons recording more hurricanes than the long-term average. The recognition that current activity is not the same as the long-term historical average means that, for the purpose of catastrophe risk assessment, we need to be explicit as to the time period over which expected activity is evaluated.We have chosen to explore activities over a 5-yr forward looking time window, which bounds the range of business applications for which catastrophe loss models are employed. This time horizon is also shorter than the pattern of past multidecadal periods of high and low activity.

The methodology used to assess activity rates for the next 5 yr contains a blend of statistical analyses and an expert elicitation. A panel of experts was convened to discuss expected levels of activity for the next 5 yr across the Atlantic, along the U.S. and Caribbean coasts. The results indicate hurricane activities along the U.S. coast are expected to be between 20 and 35% higher than the long-term average, depending on storm intensity. The implementation of these findings has included work to determine how increases are distributed by track type and by region, and the impacts on expected losses.

How to Cite: Lonfat, M., Boissonnade, A. and Muir-Wood, R., 2007. Atlantic basin, U.S. and Caribbean landfall activity rates over the 2006–2010 period: an insurance industry perspective. Tellus A: Dynamic Meteorology and Oceanography, 59(4), pp.499–510. DOI: http://doi.org/10.1111/j.1600-0870.2007.00242.x
  Published on 01 Jan 2007
 Accepted on 26 Feb 2007            Submitted on 31 Aug 2006

References

  1. Anthes , R. A. , Corell , R. W. , Holland , G. , Hurrell , J. W. , McCracken , M. C. and co-authors. 2006. Hurricanes and global warming potential linkages and consequences. Bull. Amer Meteor Soc . 87 , 623 - 628 .  

  2. Ayyub , B. 2000 . Elicitation of Expert Opinions for Uncertainty and Risks . CRC Press , New York , pp. 328 .  

  3. Blake , E. S. and Gray , W. M. 2004 . Prediction of August Atlantic basin hurricane activity . Wea. Forecast . 19 , 1044 – 1060 .  

  4. Budnitz , R. J. , Apostolakis , G. , Boore , D. M. , Cluft , C. L. , Coppersmith , K. J. and co-authors. 1997 . Recommendations for probabilistic seismic hazard analysis: guidance on uncertainty and use of experts. NUREG/CR-6372, Volume 1, Washington, DC: U.S. Nuclear Regulatory Commission. TIC: 235076  

  5. Budnitz , R. J. , Apostolakis , G., G. , Boore , D. M. , Cluff , L. S. , Coppersmith , K. J. and co-authors. 1998 . Use of technical expert panels: applications to probabilistic seismic hazard analysis. Risk Analysis 18 ( 4 ), 463 - 469 .  

  6. Chan , J. C. L. 2006 . Comment on “Changes in tropical cyclone number, duration, and intensity in a warming environment” . Science 311 , 1713b .  

  7. Chenoweth , M. and Landsea , C. 2004 . The San Diego Hurricane of 2 October 1858 . Bull. Amer Meteor. Soc . 85 , 1689 – 1697 .  

  8. Clemen , R. T. and Winkler , R. L. 1999 . Combining probability distributions from experts in risk analysis . Risk Analysis 19 , 187 – 203 .  

  9. Cook , R. M. 1991 . Experts in Uncertainty: Opinion and Subjective Probability in Science . Oxford University Press , Oxford , pp. 321 .  

  10. Coppersmith , K. J. , Nieman , J. K. , Perman , T. R. , Youngs , R. , Perry , E and co-authors . 2005. Update to the Probabilistic Volcanic Hazard Analysis, Yucca Mountain, Nevada. American Geophysical Union, Fall Meeting 2005, abstract #V31E-07  

  11. Curry , J. A. , Webster , P. J. and Holland , G. J. 2006 . Mixing politics and science in testing the hypothesis that greenhouse warming is causing a global increase in hurricane intensity . Bull. Amer Meteor Soc . 87 , 1025 – 1037 .  

  12. Dunion , J. P. , Landsea , C. W. , Houston , S. H. and Powell , M. D. 2003 . A reanalysis of the surface winds for Hurricane Donna of 1960. Mon. Wea. Re v . 131 , 1992 – 2011 .  

  13. Elsner , J. B. 2003 . Tracking hurricanes . Bull. Amer Meteor. Soc . 84 , 353 – 356 .  

  14. Elsner , J. B. 2006 . Evidence in support of the climate change-Atlantic hurricane hypothesis . Geo. Res. Lett . 33 , L16705 .  

  15. Elsner , J. B. , Niu , X. and Tsonis , A. A. 1998 . Multiyear prediction model of North Atlantic hurricane activity . Meteorol, Atmos. Phys . 68 , 43 – 51 .  

  16. Elsner , J. B. , Jagger , T. and Niu , X. 2000 . Changes in the rates of North Atlantic major hurricane activity during the 20th Century . Geo. Res. Lett . 27 , 1743 – 1746 .  

  17. Elsner , J. B. and Bossak , B. H. 2001 . Bayesian analysis of U.S. hurricane climate . J. Climate 14 , 4341 – 4350 .  

  18. Elsner , J. B. and Jagger , T. H. 2004 . A hierarchical Bayesian approach to seasonal hurricane modeling . J. Climate 17 , 2813 – 2827 .  

  19. Elsner , J. B. , Tsonis , A. A. and Jagger , T. H. 2006 . High frequency variability in hurricane power dissipation and its relationship to global temperature . Bull. Amer. Meteor Soc . 87 , 763 – 768 .  

  20. Emanuel , K. 2005a . Increasing destructiveness of tropical cyclones over the past 30 years . Nature 436 , 686 – 688 .  

  21. Emanuel , K. 2005b . Emanuel replies . Nature 438 , E13–E13 .  

  22. Goldenberg , S. B. , Landsea , C. W. , Mestas-Nufiez , A. M. and Gray , W. M. 2001 . The recent increase in Atlantic hurricane activity: causes and implications . Science 293 , 474 – 479 .  

  23. Grossi , P. , Kunreuther , H. and Patel , C. C. 2005 . Catastrophe Modeling: A New Approach to Managing Risk . Springer , New York , pp. 245 .  

  24. Hoyos , C. D. , Agudelo , P. A. , Webster , P. J. and Curry , J. A. 2006 . Deconvolution of the factors contributing to the increase in global hurricane intensity. Scienceacpress, doi: https://doi.org/10.1126/science.1123560 .  

  25. Jagger , T. H. , Niu , X. and Elsner , J. B. 2002 . A space-time model for seasonal hurricane prediction . Int. J. Climatology 22 , 451 – 465 .  

  26. Kamahori , H. , Yamazaki , N. , Mannoji , N. and Takahashi , K. 2006 . Variability in intense tropical cyclone days in the western North Pacific . SOLA 2 , 104 – 107 , doi: https://doi.org/10.2151/sola.2006-027 .  

  27. Klotzbach , P. J. 2006 . Trends in global tropical cyclone activity over the past twenty years (1986-2005) . Geophys. Rev. Lett . 33 , L10805 , 1 – 4 .  

  28. Klotzbach , P. J. and Gray , W. M. 2003 . Forecasting September Atlantic Basin tropical cyclone activity . Wea. Forecast . 18 , 1109 – 1128 .  

  29. Klotzbach , P. J. and Gray , W. M. 2004 . Updated 6-11-month prediction of Atlantic Basin seasonal hurricane activity . Wea. Forecast . 19 , 917 – 934 .  

  30. Landsea , C. W. 2005 . Meteorology: hurricanes and global warning. Nature 438 , El 1-E12 .  

  31. Landsea C. W. , Bell , G. D. , Gray , W. M. and Goldenberg , S. B. 1998 . The extremely active 1995 Atlantic hurricane season: environmental conditions and verification of seasonal forecasts. Mon. Wea. Re v . 126 , 1174 – 1193 .  

  32. Landsea , C. W. , Anderson , C. , Charles , N. , Clark , G. , Dunion , J. , Fernandez-Partagas , J. , Hungerford , P. , Neumann , C. and Zimmer , M. 2004a . The Atlantic hurricane database re-analysis project: Documentation for the 1851-1910 alterations and additions to the HURDAT database. In: Hurricanes and Typhoons: Past, Present and Future (eds R. J. Mumane and K.-B. Liu ). Columbia University Press , New York , 177 - 221 .  

  33. Landsea , C. W. , Franklin , J. L. , McAdie , C. J. , Beven , J. L. II , Gross , J. M. and co-authors. 2004 b. A reanalysis of hurricane Andrew’s intensity . Bull. Amer. Meteor Soc . 85 , 1699– 1712 .  

  34. Landsea , C. W. , Harper , B. A. , Hoaru , K. and Knaff , J. A. 2006 . Can we detect trends in extreme tropical cyclones? Science 313 , 452 – 454 .  

  35. Lloyd-Hughes , B. , Saunders , M. A. and Rockett , P. 2004 . A consolidated CLIPER model for improved August-September ENSO prediction skill . Wea. Forecast . 19 , 1089 – 1105 .  

  36. Mann , M. E. and Emanuel , K. A. 2006 . Atlantic hurricane trends linked to climate change . EOS 87 , 233 , 238,241 .  

  37. Owens , B. E and Landsea , C. W. 2003 . Assessing the skill of operational atlantic seasonal tropical cyclone forecasts . Wea. Forecast . 18 , 45 – 54 .  

  38. Pielke , R. A. and Landsea , C. W. 1999 . La Nina, El Nifio, and Atlantic hurricane damages in the United States . Bull. Amer Meteor. Soc . 80 , 2027 – 2033 .  

  39. Pielke , R. A. , Jr. , Landsea , C. W. , Mayfield , M. , Laver , J. and Pasch , R. 2005 . Hurricanes and global warming . Bull. Amer Meteor Soc . 86 , 1571 – 1575 .  

  40. Pielke , R. A. , Jr. , Landsea , C. W. , Mayfield , M. , Laver , J. , Pasch , R. 2006 . Reply to “Hurricanes and global warming potential linkages and consequences”. Bull. Amer. Meteor Soc . 87 , 628 - 631 .  

  41. Saunders , M. A. and Lea , A. S. 2005 . Seasonal prediction of hurricane activity reaching the coast of the United States . Nature 434 , 1005 – 1008 .  

  42. Sriver , R. and Huber , M. 2006 . Low frequency variability in globally integrated tropical cyclone power dissipation . Geophys. Res. Lett . 33 , L11705 .  

  43. Thomcroft , C. and Pytharoulis , I. 2001 . A dynamical approach to seasonal prediction of Atlantic tropical cyclone activity . Wea. Forecast . 16 , 725 – 735 .  

  44. Trenberth , K. 2005 . Uncertainty in Hurricanes and Global Warning . Nature 308 , 1753 – 1754 .  

  45. Trenberth , K. and Shea , D. J. 2006 . Atlantic hurricanes and natural variability in 2005 . Geophys. Rev. Lett . 33 , L12704 .  

  46. Velden , C. , Harper , B. , Wells , E , Beven , J. L. II , Zehr , R. and co-authors. 2006. The Dvorak tropical cyclone intensity estimation technique: a satellite-based method that has endured for over 30 years. Bull. Amer Meteor Soc . 87 , 1195 - 1210 .  

  47. Vitart , E and Stockdale , T. N. 2001 . Seasonal forecasting of tropical storms using coupled GCM integrations. Mon. Wea. Re v . 129 , 2521 – 2537 .  

  48. Webster , P. J. , Holland , G. J. , Curry , J. A. and Chang , H.-R. 2005 . Changes in tropical cyclone number, duration, and intensity in a warming environment . Science 309 , 1844 – 1846 .  

  49. WMO WMO200 . Statement on Tropical Cyclones and Climate Change, Available at http://www.wmo.ch/web/arep/arep-home.html.  

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