Grey swan tropical cyclones

Abstract

We define ‘grey swan’ tropical cyclones as high-impact storms that would not be predicted based on history but may be foreseeable using physical knowledge together with historical data. Here we apply a climatological–hydrodynamic method to estimate grey swan tropical cyclone storm surge threat for three highly vulnerable coastal regions. We identify a potentially large risk in the Persian Gulf, where tropical cyclones have never been recorded, and larger-than-expected threats in Cairns, Australia, and Tampa, Florida. Grey swan tropical cyclones striking Tampa, Cairns and Dubai can generate storm surges of about 6 m, 5.7 m and 4 m, respectively, with estimated annual exceedance probabilities of about 1/10,000. With climate change, these probabilities can increase significantly over the twenty-first century (to 1/3,100–1/1,100 in the middle and 1/2,500–1/700 towards the end of the century for Tampa). Worse grey swan tropical cyclones, inducing surges exceeding 11 m in Tampa and 7 m in Dubai, are also revealed with non-negligible probabilities, especially towards the end of the century.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Figure 1: The 1921 Tampa hurricane compared with two grey swan TCs.
Figure 2: Estimated storm surge level as a function of return period for Tampa for the NCEP/NCAR reanalysis climate of 1980–2005, based on 7,800 synthetic events.
Figure 3: Estimated storm surge level as a function of return period for Tampa in the climate of 1980–2005 (based on 2,100 events), 2006–2036 (3,100 events), 2037–2067 (3,100 events), and 2068–2098 (3,100 events) projected using each of the six climate models for the IPCC AR5 RCP8.5 emission scenario.
Figure 4: Storm surge risk analysis for Cairns, Australia, based on 2,400 synthetic events in the NCEP/NCAR reanalysis climate of 1980–2010.
Figure 5: Storm surge risk analysis for Dubai, based on 3,100 synthetic events in the MERRA reanalysis climate of 1980–2010.

References

  1. 1

    Taleb, N. N. The Black Swan: The Impact of the Highly Improbable Fragility (Random House LLC, 2010).

    Google Scholar 

  2. 2

    Aven, T. On the meaning of a black swan in a risk context. Saf. Sci. 57, 44–51 (2013).

    Article  Google Scholar 

  3. 3

    Nafday, A. M. Strategies for managing the consequences of black swan events. Leadership Manage. Eng. 9, 191–197 (2009).

    Article  Google Scholar 

  4. 4

    Stein, J. L. & Stein, S. Gray swans: Comparison of natural and financial hazard assessment and mitigation. Nat. Hazards 72, 1279–1297 (2014).

    Article  Google Scholar 

  5. 5

    Paté Cornell, E. On “Black Swans” and “Perfect Storms”: Risk analysis and management when statistics are not enough. Risk Anal. 32, 1823–1833 (2012).

    Article  Google Scholar 

  6. 6

    Needham, H., Keim, B. D. & Sathiaraj, D. A review of tropical cyclone-generated storm surges: Global data sources, observations and impacts. Rev. Geophys. 53, 545–591 (2015).

    Article  Google Scholar 

  7. 7

    Fritz, H. M. et al. Hurricane Katrina storm surge distribution and field observations on the Mississippi Barrier Islands. Estuar. Coast. Shelf Sci. 74, 12–20 (2007).

    Article  Google Scholar 

  8. 8

    Travis, J. Scientists’ fears come true as hurricane floods New Orleans. Science 309, 1656–1659 (2005).

    CAS  Article  Google Scholar 

  9. 9

    Fritz, H. M., Blount, C. D., Thwin, S., Thu, M. K. & Chan, N. Cyclone Nargis storm surge in Myanmar. Nature Geosci. 2, 448–449 (2009).

    CAS  Article  Google Scholar 

  10. 10

    Scileppi, E. & Donnelly, J. P. Sedimentary evidence of hurricane strikes in western Long Island, New York. Geochem. Geophys. Geosyst. 8, Q06011 (2007).

    Article  Google Scholar 

  11. 11

    Brandon, C. M., Woodruff, J. D., Donnelly, J. P. & Sullivan, R. M. How unique was Hurricane Sandy? Sedimentary reconstructions of extreme flooding from New York harbor. Sci. Rep. 4, 7366 (2014).

    CAS  Article  Google Scholar 

  12. 12

    Lin, N., Emanuel, K. A., Smith, J. A. & Vanmarcke, E. Risk assessment of hurricane storm surge for New York City. J. Geophys. Res. 115, D18121 (2010).

    Article  Google Scholar 

  13. 13

    Lin, N., Emanuel, K., Oppenheimer, M. & Vanmarcke, E. Physically based assessment of hurricane surge threat under climate change. Nature Clim. Change 2, 1–6 (2012).

    Article  Google Scholar 

  14. 14

    Mas, E. et al. Field survey report and satellite image interpretation of the 2013 Super Typhoon Haiyan in the Philippines. Nat. Hazards Earth Syst. Sci. 15, 817–825 (2015).

    Article  Google Scholar 

  15. 15

    Bankoff, G. Cultures of Disaster: Society and Natural Hazard in the Philippines 232 (Routledge Curzon, 2003).

    Google Scholar 

  16. 16

    Vickery, P., Skerlj, P. & Twisdale, L. Simulation of hurricane risk in the U.S. using empirical track model. J. Struct. Eng. 126, 1222–1237 (2000).

    Article  Google Scholar 

  17. 17

    Toro, G. R., Resio, D. T., Divoky, D., Niedoroda, A. W. & Reed, C. Efficient joint-probability methods for hurricane surge frequency analysis. Ocean Eng. 37, 125–134 (2010).

    Article  Google Scholar 

  18. 18

    Hall, T. M. & Sobel, A. H. On the impact angle of Hurricane Sandy’s New Jersey landfall. Geophys. Res. Lett. 40, 2312–2315 (2013).

    Article  Google Scholar 

  19. 19

    Emanuel, K., Ravela, S., Vivant, E. & Risi, C. A Statistical deterministic approach to hurricane risk assessment. Bull. Am. Meteorol. Soc. 87, 299–314 (2006).

    Article  Google Scholar 

  20. 20

    Emanuel, K., Sundararajan, R. & Williams, J. Hurricanes and global warming: Results from downscaling IPCC AR4 simulations. Bull. Am. Meteorol. Soc. 89, 347–367 (2008).

    Article  Google Scholar 

  21. 21

    Emanuel, K. The dependence of hurricane intensity on climate. Nature 326, 483–485 (1987).

    Article  Google Scholar 

  22. 22

    Elsner, J. B., Kossin, J. P. & Jagger, T. H. The increasing intensity of the strongest tropical cyclones. Nature 455, 92–95 (2008).

    CAS  Article  Google Scholar 

  23. 23

    Knutson, T. R. et al. Tropical cyclones and climate change. Nature Geosci. 3, 157–163 (2010).

    CAS  Article  Google Scholar 

  24. 24

    Emanuel, K. A. Downscaling CMIP5 climate models shows increased tropical cyclone activity over the 21st century. Proc. Natl Acad. Sci. USA 110, 12219–12224 (2013).

    CAS  Article  Google Scholar 

  25. 25

    Westerink, J. J. et al. A basin- to channel-scale unstructured grid hurricane storm surge model applied to southern Louisiana. Mon. Weath. Rev. 136, 833–864 (2008).

    Article  Google Scholar 

  26. 26

    Lin, N., Lane, P., Emanuel, K. A., Sullivan, R. M. & Donnelly, J. P. Heightened hurricane surge risk in northwest Florida revealed from climatological–hydrodynamic modeling and paleorecord reconstruction. J. Geophys. Res. Atmos. 119, 8606–8623 (2014).

    Article  Google Scholar 

  27. 27

    Aerts, J. C. J. H., Lin, N., Botzen, W., Emanuel, K. & de Moel, H. Low-probability flood risk modeling for New York City. Risk Anal. 33, 772–788 (2013).

    Article  Google Scholar 

  28. 28

    Aerts, J. C. J. H. et al. Evaluating Flood resilience strategies for coastal megacities. Science 344, 473–475 (2014).

    Article  Google Scholar 

  29. 29

    Weisberg, R. H. & Zheng, L. Hurricane storm surge simulations for Tampa Bay. Estuar. Coast. 29, 899–913 (2008).

    Article  Google Scholar 

  30. 30

    Kalnay, E. et al. The NCEP/NCAR 40-year reanalysis project. Bull. Am. Meteorol. Soc. 77, 437–471 (1996).

    Article  Google Scholar 

  31. 31

    Bossak, B. H. Early 19th Century US Hurricanes: A GIS Tool and Climate Analysis PhD dissertation, Florida State Univ. (2003)

  32. 32

    Morey, S. L., Baig, S., Bourassa, M. A., Dukhovskoy, D. S. & O’Brien, J. J. Remote forcing contribution to storm-induced sea level rise during Hurricane Dennis. Geophys. Res. Lett. 33, L19603 (2006).

    Article  Google Scholar 

  33. 33

    Chavas, D. R. & Emanuel, K. A. A QuikSCAT climatology of tropical cyclone size. Geophys. Res. Lett. 37, 18 (2010).

    Article  Google Scholar 

  34. 34

    Rotunno, R. & Emanuel, K. A. 1987: An air-sea interaction theory for tropical cyclones, Part II: Evolutionary study using axisymmetric nonhydrostatic numerical model. J. Atmos. Sci. 44, 542–561

  35. 35

    Chavas, D. R. & Emanuel, K. Equilibrium tropical cyclone size in an idealized state of axisymmetric radiative–convective equilibrium. J. Atmos. Sci. 71, 1663–1680 (2014).

    Article  Google Scholar 

  36. 36

    Emanuel, K. A. An air-sea interaction theory for tropical cyclones. Part I: Steady-state maintenance. J. Atmos. Sci. 43, 585–605 (1986).

    Article  Google Scholar 

  37. 37

    Nott, J., Green, C., Townsend, I. & Callaghan, J. The world record storm surge and the most intense southern hemisphere tropical cyclone: New evidence and modeling. Bull. Am. Meteorol. Soc. 95, 757–765 (2014).

    Article  Google Scholar 

  38. 38

    Hardy, T., Mason, L. & Astorquia, A. Surge Plus Tide Statistics for Selected Open Coast Locations Along the Queensland East Coast. Queensland Climate Change and Community Vulnerability to Tropical Cyclones. Ocean Hazards Assessment Stage 3 (Queensland Government Report, 2004)

  39. 39

    Haigh, I. D. et al. Estimating present day extreme water level exceedance probabilities around the coastline of Australia: Tropical cyclone-induced storm surges. Clim. Dynam. 42, 139–157 (2014).

    Article  Google Scholar 

  40. 40

    Nott, J. F. & Jagger, T. H. Deriving robust return periods for tropical cyclone inundations from sediments. Geophys. Res. Lett. 40, 370–373 (2012).

    Article  Google Scholar 

  41. 41

    Evan, A. T. & Camargo, S. J. A climatology of Arabian Sea cyclonic storms. J. Clim. 24, 140–158 (2011).

    Article  Google Scholar 

  42. 42

    Rienecker, M. M. et al. MERRA: NASA’s modern-era retrospective analysis for research and applications. J. Clim. 24, 3624–3648 (2011).

    Article  Google Scholar 

  43. 43

    Shirvani, A., Nazemosadat, S. M. J. & Kahya, E. Analyses of the Persian Gulf sea surface temperature: Prediction and detection of climate change signals. Arab. J. Geosci. 8, 2121–2130 (2015).

    Article  Google Scholar 

  44. 44

    Bister, M. & Emanuel, K. A. Low frequency variability of tropical cyclone potential intensity 1. Interannual to interdecadal variability. J. Geophys. Res. 107(D24), 4801 (2002).

    Article  Google Scholar 

  45. 45

    Evan, A. T., Kossin, J. P., Eddy’ Chung, C. & Ramanathan, V. Arabian Sea tropical cyclones intensified by emissions of black carbon and other aerosols. Nature 479, 94–97 (2011).

    CAS  Article  Google Scholar 

  46. 46

    Woodruff, J. D., Irish, J. L. & Camargo, S. J. Coastal flooding by tropical cyclones and sea-level rise. Nature 504, 44–52 (2013).

    CAS  Article  Google Scholar 

  47. 47

    Emanuel, K., Des Autels, C., Holloway, C. & Korty, R. Environmental control of tropical cyclone intensity. J. Atmos. Sci. 61, 843–858 (2004).

    Article  Google Scholar 

  48. 48

    Emanuel, K. & Rotunno, R. Self-stratification of tropical cyclone outflow. Part I: Implications for storm structure. J. Atmos. Sci. 68, 2236–2249 (2011).

    Article  Google Scholar 

  49. 49

    Lin, N. & Chavas, D. On hurricane parametric wind and applications in storm surge modeling. J. Geophys. Res. 117, D09120 (2012).

    Article  Google Scholar 

  50. 50

    Holland, G. J. An analytic model of the wind and pressure profiles in hurricanes. Mon. Weath. Rev. 108, 1212–1218 (1980).

    Article  Google Scholar 

  51. 51

    Luettich, R. A., Westerink, J. J. & Scheffner, N. W. ADCIRC: An Advanced Three-dimensional Circulation Model for Shelves, Coasts and Estuaries, Report 1: Theory and Methodology of ADCIRC-2DDI and ADCIRC-3DL DRP Technical Report DRP-92-6 (Department of the Army, US Army Corps of Engineers, Waterways Experiment Station, 1992)

  52. 52

    Dietrich, J. C. et al. Modeling hurricane waves and storm surge using integrally-coupled, scalable computations. Coast. Eng. 58, 45–65 (2011).

    Article  Google Scholar 

  53. 53

    Landsea, C. W. et al. A reanalysis of the 1921–1930 Atlantic hurricane database. J. Clim. 25, 865–885 (2012).

    Article  Google Scholar 

  54. 54

    Knapp, K. R., Kruk, M. C., Levinson, D. H., Diamond, H. J. & Neumann, C. J. The International Best Track Archive for Climate Stewardship (IBTrACS) unifying tropical cyclonedata. Bull. Am. Meteorol. Soc. 91, 363–376 (2010).

    Article  Google Scholar 

  55. 55

    Coles, S. An Introduction to Statistical Modeling of Extreme Values (Springer, 2001).

    Google Scholar 

Download references

Acknowledgements

We acknowledge the World Climate Research Program’s Working Group on Coupled Modeling, which is responsible for CMIP, and we thank the climate modelling groups for producing and making available their model output. We thank J. Westerink of the University of Notre Dame and C. Dietrich of North Carolina State University for their technical support on the ADCIRC model applied in this study for storm surge analysis. We also thank G. Holland of National Center for Atmospheric Science and J. Nott of James Cook University for their helpful comments. N.L. acknowledges support from Princeton University’s School of Engineering and Applied Science (Project X Fund) and Andlinger Center for Energy and the Environment (Innovation Fund). K.E. was supported by NSF Grant 1418508.

Author information

Affiliations

Authors

Contributions

K.E. performed numerical modelling of the storms. N.L. carried out storm surge simulations and statistical analysis. N.L. and K.E. co-wrote the paper.

Corresponding author

Correspondence to Ning Lin.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Lin, N., Emanuel, K. Grey swan tropical cyclones. Nature Clim Change 6, 106–111 (2016). https://doi.org/10.1038/nclimate2777

Download citation

Further reading

Search

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing