Article | Published:

Global trends in tropical cyclone risk

Nature Climate Change volume 2, pages 289294 (2012) | Download Citation

Abstract

The impact of tropical cyclones on humans depends on the number of people exposed and their vulnerability, as well as the frequency and intensity of storms. How will the cumulative effects of climate change, demography and vulnerability affect risk? Conventionally, reports assessing tropical cyclone risk trends are based on reported losses, but these figures are biased by improvements to information access. Here we present a new methodology based on thousands of physically observed events and related contextual parameters. We show that mortality risk depends on tropical cyclone intensity, exposure, levels of poverty and governance. Despite the projected reduction in the frequency of tropical cyclones, projected increases in both demographic pressure and tropical cyclone intensity over the next 20 years can be expected to greatly increase the number of people exposed per year and exacerbate disaster risk, despite potential progression in development and governance.

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Acknowledgements

U. Deichmann (World Bank) for providing the GDP distribution; A. Maskrey (United Nations International Strategy for Disaster Reduction) for finding the finances to supporting this study; R. Harding for English corrections.

Author information

Affiliations

  1. Global Change and Vulnerability Unit, DEWA/GRID-Geneva, United Nations Environment Programme, 11, ch. Anémones, 1219 Châtelaine, Geneva, Switzerland

    • P. Peduzzi
    • , B. Chatenoux
    • , H. Dao
    • , A. De Bono
    • , C. Herold
    •  & O. Nordbeck
  2. Institute of Geomatics and Risk Analysis (IGAR), Faculty of GeoSciences and Environment, Amphipôle, University of Lausanne, 1015 Lausanne, Switzerland

    • P. Peduzzi
  3. Institut F. A. Forel, Faculty of Sciences, University of Geneva, 10, Route de Suisse, 1290 Versoix, Switzerland

    • B. Chatenoux
    • , A. De Bono
    •  & C. Herold
  4. Department of Geography, University of Geneva, Faculty of Economic and Social Sciences, Uni Mail, 40, Bd du Pont-d’Arve, 1211 Geneva, Switzerland

    • H. Dao
  5. National Climatic Data Center/NOAA, 151, Patton Avenue, Asheville, North Carolina 28801-5001, USA

    • J. Kossin
  6. Institut Fourier, University of Grenoble, 100, rue des maths, BP 74, 38402 St Martin d’Hères, France

    • F. Mouton

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Contributions

P.P. developed the methodology, carried out the multiple-regression risk analysis, including trend and spatial risk distribution, and developed the MRI with H.D. B.C., C.H. and O.N. generated the spatial model for the TC buffers and extracted the human and economic exposure as well as contextual parameters. F.M. did the mathematical models for the TC buffers. H.D. produced the model of population distribution for 1970–2030 and produced the database on socio-economic parameters. A.D.B. georeferenced the losses and estimated the coastal population living in low-lying areas. J.K. and P.P. developed the method for extrapolating exposure and frequency for 2030 on the basis of a review of different climate change scenarios. P.P. is the lead author, with advice and critical review from J.K. and key contributions from all co-authors.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to P. Peduzzi.

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DOI

https://doi.org/10.1038/nclimate1410

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