IDEAS home Printed from https://ideas.repec.org/a/spr/nathaz/v104y2020i2d10.1007_s11069-020-04219-x.html
   My bibliography  Save this article

Hurricane trend detection

Author

Listed:
  • Craig Loehle
  • Erica Staehling

    (Weather Tiger, LLC)

Abstract

Because a change in the frequency (number/year) of hurricanes could be a result of climate change, we analyzed the historical record of Atlantic basin and US landfalling hurricanes, as well as US continental accumulated cyclone energy to evaluate issues related to trend detection. Hurricane and major hurricane landfall counts exhibited no significant overall trend over 167 years of available data, nor did accumulated cyclone energy over the continental USA over 119 years of available data, although shorter-term trends were evident in all three datasets. Given the χ2 distribution evinced by hurricane and major hurricane counts, we generated synthetic series to test the effect of segment length, demonstrating that shorter series were increasingly likely to exhibit spurious trends. Compared to synthetic data with the same mean, the historical all-storm data were more likely to exhibit short-term trends, providing some evidence for long-term persistence at timescales below 10 years. Because this might be due to known climate modes, we examined the relationship between the Atlantic multidecadal oscillation (AMO) and hurricane frequency in light of these short-term excursions. We found that while ratios of hurricane counts with AMO phase matched expectations, statistical tests were less clear due to noise. Over a period of 167 years, we found that an upward trend of roughly 0.7/century is sufficient to be detectable with 80% confidence over the range from 1 to 21 storms/year. Storm energy data 1900–2018 over land were also analyzed. The trend was again zero. The pattern of spurious trends for short segments was again found. Results for AMO periods were similar to count data. Atlantic basin all storms and major storms (1950–2018) did not exhibit any trend over the whole period or after 1990. Major storms 1950–1989 exhibited a significant downward trend. All-storm basin scale storms exhibited short-term trends matching those expected from a Poisson process. A new test for Poisson series was developed based on the 95% distribution of slopes for simulated data across a range of series lengths. Because short data series are inherently likely to yield spurious trends, care is needed when interpreting hurricane trend data.

Suggested Citation

  • Craig Loehle & Erica Staehling, 2020. "Hurricane trend detection," 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. 104(2), pages 1345-1357, November.
    • Handle: RePEc:spr:nathaz:v:104:y:2020:i:2:d:10.1007_s11069-020-04219-x
    DOI: 10.1007/s11069-020-04219-x
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11069-020-04219-x
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11069-020-04219-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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    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. James P. Kossin, 2017. "Hurricane intensification along United States coast suppressed during active hurricane periods," Nature, Nature, vol. 541(7637), pages 390-393, January.
    3. Il-Ju Moon & Sung-Hun Kim & Johnny C. L. Chan, 2019. "Climate change and tropical cyclone trend," Nature, Nature, vol. 570(7759), pages 3-5, June.
    4. Mark A. Saunders & Adam S. Lea, 2008. "Large contribution of sea surface warming to recent increase in Atlantic hurricane activity," Nature, Nature, vol. 451(7178), pages 557-560, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Gabriel A. Vecchi & Christopher Landsea & Wei Zhang & Gabriele Villarini & Thomas Knutson, 2021. "Changes in Atlantic major hurricane frequency since the late-19th century," Nature Communications, Nature, vol. 12(1), pages 1-9, December.
    2. Coilín ÓhAiseadha & Gerré Quinn & Ronan Connolly & Michael Connolly & Willie Soon, 2020. "Energy and Climate Policy—An Evaluation of Global Climate Change Expenditure 2011–2018," Energies, MDPI, vol. 13(18), pages 1-49, September.

    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. 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.
    2. 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.
    3. Christina M. Giovas, 2021. "Sustainable Indigenous Fishing in the Pre-Contact Caribbean: Evidence and Critical Considerations from Carriacou, Grenada," Sustainability, MDPI, vol. 13(16), pages 1-15, August.
    4. Andrea Staid & Seth Guikema & Roshanak Nateghi & Steven Quiring & Michael Gao, 2014. "Simulation of tropical cyclone impacts to the U.S. power system under climate change scenarios," Climatic Change, Springer, vol. 127(3), pages 535-546, December.
    5. Xiaotong Sui & Mingzhao Hu & Haoyun Wang & Lingdi Zhao, 2023. "Improved elasticity estimation model for typhoon storm surge losses in 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. 116(2), pages 2363-2381, March.
    6. Nekeisha Spencer & Eric Strobl, 2022. "Poverty and hurricane risk exposure in Jamaica," The Geneva Risk and Insurance Review, Palgrave Macmillan;International Association for the Study of Insurance Economics (The Geneva Association), vol. 47(1), pages 141-157, March.
    7. 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.
    8. 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.
    9. Yanos Zylberberg, 2010. "Natural natural disasters and economic disruption," PSE Working Papers halshs-00564946, HAL.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. Kai Yin & Sudong Xu & Quan Zhao & Nini Zhang & Mengqi Li, 2021. "Effects of sea surface warming and sea-level rise on tropical cyclone and inundation modeling at Shanghai coast," 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. 109(1), pages 755-784, October.
    17. 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.
    18. Ranger, Nicola & Niehörster, Falk, 2011. "Deep uncertainty in long-term hurricane risk: scenario generation and implications for future climate experiments," LSE Research Online Documents on Economics 37587, London School of Economics and Political Science, LSE Library.
    19. 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.
    20. 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.

    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:spr:nathaz:v:104:y:2020:i:2:d:10.1007_s11069-020-04219-x. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.