IDEAS home Printed from https://ideas.repec.org/a/wly/riskan/v27y2007i6p1497-1517.html

Hurricane Destructive Power Predictions Based on Historical Storm and Sea Surface Temperature Data

Author

Listed:
  • Kenneth T. Bogen
  • Edwin D. Jones
  • Larry E. Fischer

Abstract

Forecasting destructive hurricane potential is complicated by substantial, unexplained intraannual variation in storm‐specific power dissipation index (PDI, or integrated third power of wind speed), and interannual variation in annual accumulated PDI (APDI). A growing controversy concerns the recent hypothesis that the clearly positive trend in North Atlantic Ocean (NAO) sea surface temperature (SST) since 1970 explains increased hurricane intensities over this period, and so implies ominous PDI and APDI growth as global warming continues. To test this “SST hypothesis” and examine its quantitative implications, a combination of statistical and probabilistic methods were applied to National Hurricane Center HURDAT best‐track data on NAO hurricanes during 1880–2002, and corresponding National Oceanographic and Atmospheric Administration Extended Reconstruction SST estimates. Notably, hurricane behavior was compared to corresponding hurricane‐specific (i.e., spatiotemporally linked) SST; previous similar comparisons considered only SST averaged over large NAO regions. Contrary to the SST hypothesis, SST was found to vary in a monthly pattern inconsistent with that of corresponding PDI, and to be at best weakly associated with PDI or APDI despite strong correlation with corresponding mean latitude (R2= 0.55) or with combined mean location and a ∼90‐year periodic trend (R2= 0.70). Over the last century, the lower 75% of APDIs appear randomly sampled from a nearly uniform distribution, and the upper 25% of APDIs from a nearly lognormal distribution. From the latter distribution, a baseline (SST‐independent) stochastic model was derived predicting that over the next half century, APDI will not likely exceed its maximum value over the last half century by more than a factor of 1.5. This factor increased to 2 using a baseline model modified to assume SST‐dependence conditioned on an upper bound of the increasing NAO SST trend observed since 1970. An additional model was developed that predicts PDI statistics conditional on APDI. These PDI and APDI models can be used to estimate upper bounds on indices of hurricane power likely to be realized over the next century, under divergent assumptions regarding SST influence.

Suggested Citation

  • Kenneth T. Bogen & Edwin D. Jones & Larry E. Fischer, 2007. "Hurricane Destructive Power Predictions Based on Historical Storm and Sea Surface Temperature Data," Risk Analysis, John Wiley & Sons, vol. 27(6), pages 1497-1517, December.
  • Handle: RePEc:wly:riskan:v:27:y:2007:i:6:p:1497-1517
    DOI: 10.1111/j.1539-6924.2007.00984.x
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/j.1539-6924.2007.00984.x
    Download Restriction: no

    File URL: https://libkey.io/10.1111/j.1539-6924.2007.00984.x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Kerry Emanuel, 2005. "Increasing destructiveness of tropical cyclones over the past 30 years," Nature, Nature, vol. 436(7051), pages 686-688, August.
    2. Stuart Coles & Luis Pericchi, 2003. "Anticipating catastrophes through extreme value modelling," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 52(4), pages 405-416, October.
    3. Jeong, Jinook & Chung, Seoung, 2001. "Bootstrap tests for autocorrelation," Computational Statistics & Data Analysis, Elsevier, vol. 38(1), pages 49-69, November.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Stanley Changnon, 2009. "Characteristics of severe Atlantic hurricanes in the United States: 1949–2006," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 48(3), pages 329-337, March.
    2. Feng, Shufang & Peng, Ruiyan & Wang, Peihong & Peng, Benrong, 2025. "Mitigating typhoon damage with wetlands: estimating the typhoon protection value of intertidal and inland wetlands in China," Ecosystem Services, Elsevier, vol. 75(C).
    3. Lianjie Qin & Laiyin Zhu & Baoyin Liu & Zixuan Li & Yugang Tian & Gordon Mitchell & Shifei Shen & Wei Xu & Jianguo Chen, 2024. "Global expansion of tropical cyclone precipitation footprint," Nature Communications, Nature, vol. 15(1), pages 1-10, December.
    4. Teh, Su Yean & DeAngelis, Donald L. & Sternberg, Leonel da Silveira Lobo & Miralles-Wilhelm, Fernando R. & Smith, Thomas J. & Koh, Hock-Lye, 2008. "A simulation model for projecting changes in salinity concentrations and species dominance in the coastal margin habitats of the Everglades," Ecological Modelling, Elsevier, vol. 213(2), pages 245-256.
    5. Yanos Zylberberg, 2010. "Natural natural disasters and economic disruption," PSE Working Papers halshs-00564946, HAL.
    6. S. Seo, 2014. "Estimating Tropical Cyclone Damages Under Climate Change in the Southern Hemisphere Using Reported Damages," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 58(3), pages 473-490, July.
    7. Nicola Ranger & Falk Nieh�rster, 2011. "Deep uncertainty in long-term hurricane risk: scenario generation and implications for future climate experiments," GRI Working Papers 51, Grantham Research Institute on Climate Change and the Environment.
    8. Jun Wang & Zhenlou Chen & Shiyuan Xu & Beibei Hu, 2013. "Medium-scale natural disaster risk scenario analysis: a case study of Pingyang County, Wenzhou, China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 66(2), pages 1205-1220, March.
    9. Geoffrey Heal & Howard Kunreuther, 2010. "Environment and Energy: Catastrophic Liabilities from Nuclear Power Plants," NBER Chapters, in: Measuring and Managing Federal Financial Risk, pages 235-257, National Bureau of Economic Research, Inc.
    10. Laura A. Bakkensen & Robert O. Mendelsohn, 2016. "Risk and Adaptation: Evidence from Global Hurricane Damages and Fatalities," Journal of the Association of Environmental and Resource Economists, University of Chicago Press, vol. 3(3), pages 555-587.
    11. Davlasheridze, Meri & Fisher-Vanden, Karen & Allen Klaiber, H., 2017. "The effects of adaptation measures on hurricane induced property losses: Which FEMA investments have the highest returns?," Journal of Environmental Economics and Management, Elsevier, vol. 81(C), pages 93-114.
    12. Camila I. Donatti & Celia A. Harvey & David Hole & Steven N. Panfil & Hanna Schurman, 2020. "Indicators to measure the climate change adaptation outcomes of ecosystem-based adaptation," Climatic Change, Springer, vol. 158(3), pages 413-433, February.
    13. Hongxiang Yan & Hamid Moradkhani, 2016. "Toward more robust extreme flood prediction by Bayesian hierarchical and multimodeling," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 81(1), pages 203-225, March.
    14. Don Driscoll & Adam Felton & Philip Gibbons & Annika Felton & Nicola Munro & David Lindenmayer, 2012. "Priorities in policy and management when existing biodiversity stressors interact with climate-change," Climatic Change, Springer, vol. 111(3), pages 533-557, April.
    15. Dasgupta, Susmita & Laplante, Benoit & Murray, Siobhan & Wheeler, David, 2009. "Sea-level rise and storm surges : a comparative analysis of impacts in developing countries," Policy Research Working Paper Series 4901, The World Bank.
    16. R. S. Akhila & J. Kuttippurath & R. Rahul & A. Chakraborty, 2022. "Genesis and simultaneous occurrences of the super cyclone Kyarr and extremely severe cyclone Maha in the Arabian Sea in October 2019," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 113(2), pages 1133-1150, September.
    17. Raphaël Rousseau-Rizzi & Kerry Emanuel, 2022. "Natural and anthropogenic contributions to the hurricane drought of the 1970s–1980s," Nature Communications, Nature, vol. 13(1), pages 1-10, December.
    18. T. D. Pol & S. Gabbert & H.-P. Weikard & E. C. Ierland & E. M. T. Hendrix, 2017. "A Minimax Regret Analysis of Flood Risk Management Strategies Under Climate Change Uncertainty and Emerging Information," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 68(4), pages 1087-1109, December.
    19. Ruoping Chu & Kai Wang, 2025. "CFD in Urban Wind Resource Assessments: A Review," Energies, MDPI, vol. 18(10), pages 1-21, May.
    20. Austin Becker & Michele Acciaro & Regina Asariotis & Edgard Cabrera & Laurent Cretegny & Philippe Crist & Miguel Esteban & Andrew Mather & Steve Messner & Susumu Naruse & Adolf Ng & Stefan Rahmstorf &, 2013. "A note on climate change adaptation for seaports: a challenge for global ports, a challenge for global society," Climatic Change, Springer, vol. 120(4), pages 683-695, October.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wly:riskan:v:27:y:2007:i:6:p:1497-1517. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: https://doi.org/10.1111/(ISSN)1539-6924 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.