Projected increase in El Niño-driven tropical cyclone frequency in the Pacific


The El Niño/Southern Oscillation (ENSO) drives substantial variability in tropical cyclone (TC) activity around the world1,2,3. However, it remains uncertain how the projected future changes in ENSO under greenhouse warming4,5,6,7,8 will affect TC activity, apart from an expectation that the overall frequency of TCs is likely to decrease for most ocean basins9,10,11. Here we show robust changes in ENSO-driven variability in TC occurrence by the late twenty-first century. In particular, we show that TCs become more frequent (20–40%) during future-climate El Niño events compared with present-climate El Niño events—and less frequent during future-climate La Niña events—around a group of small island nations (for example, Fiji, Vanuatu, Marshall Islands and Hawaii) in the Pacific. We examine TCs across 20 models from the Coupled Model Intercomparison Project phase 5 database12, forced under historical and greenhouse warming conditions. The 12 most realistic models identified show a strong consensus on El Niño-driven changes in future-climate large-scale environmental conditions that modulate development of TCs over the off-equatorial western Pacific and the central North Pacific regions. These results have important implications for climate change and adaptation pathways for the vulnerable Pacific island nations.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

Figure 1: Multimodel-mean composites of anisotropic Gaussian TC density estimates for El Niño and La Niña, and their differences (that is, El Niño–La Niña), at every 2.5° × 2.5° grid box over the period 1970–2000.
Figure 2: Projected future changes in TC density.
Figure 3: December–February Southern Hemisphere and July–September Northern Hemisphere mean large-scale variables for present-climate El Niño events, and the direction of projected changes between present-climate and future-climate El Niño events.
Figure 4: Schematic illustration of a mechanism for increased TC formation in the ‘horseshoe-shaped’ region in the western Pacific during future-climate El Niño events compared with the present-climate El Niño events.


  1. 1

    Camargo, S. J., Sobel, A. H., Barnston, A. G. & Philip, J. K. in Global Perspectives on Tropical Cyclones: From Science to Mitigation (eds Chan, J. C. L. & Kepert, J. D.) 325–360 (World Scientific, 2010).

    Google Scholar 

  2. 2

    Chand, S. S. & Walsh, K. J. E. Tropical cyclone activity in the Fiji region: spatial patterns and relationship to large-scale circulation. J. Clim. 22, 3877–3893 (2009).

    Article  Google Scholar 

  3. 3

    Ramsay, H. A., Leslie, L. M., Lamb, P. J., Richman, M. B. & Leplastrier, M. Interannual variability of tropical cyclones in the Australian region: role of large-scale environment. J. Clim. 21, 1083–1103 (2008).

    Article  Google Scholar 

  4. 4

    Cai, W. et al. Increasing frequency of extreme El Niño events due to greenhouse warming. Nat. Clim. Change 4, 111–116 (2014).

    CAS  Article  Google Scholar 

  5. 5

    Collins, M. et al. The impact of global warming on the tropical Pacific Ocean and El Niño. Nat. Geosci. 3, 391–397 (2010).

    CAS  Article  Google Scholar 

  6. 6

    Power, S., Delage, F., Chung, C., Kociuba, G. & Keay, K. Robust twenty-first-century projections of El Niño and related precipitation variability. Nature 502, 541–545 (2013).

    CAS  Article  Google Scholar 

  7. 7

    Yeh, S.-W. et al. El Niño in a changing climate. Nature 461, 511–514 (2009).

    CAS  Article  Google Scholar 

  8. 8

    Kim, S. T. & Yu, J.-Y. Two types of ENSO in CMIP5 models. J. Geophys. Res. 39, L11704 (2012).

    Google Scholar 

  9. 9

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

    CAS  Article  Google Scholar 

  10. 10

    Murakami, H., Hsu, P.-C., Arakawa, O. & Li, T. Influence of model biases on projected future changes in tropical cyclone frequency of occurrence. J. Clim. 27, 2159–2181 (2014).

    Article  Google Scholar 

  11. 11

    Tory, K. J., Chand, S. S., McBride, J. L., Ye, H. & Dare, R. A. Projected changes in late twenty-first-century tropical cyclone frequency in 13 coupled climate models from Phase 5 of the Coupled Model Intercomparison Project. J. Clim. 26, 9946–9959 (2013).

    Article  Google Scholar 

  12. 12

    Taylor, K. E., Stouffer, R. J. & Meehl, G. A. An overview of CMIP5 and the experimental design. Bull. Am. Meteorol. Soc. 93, 485–498 (2012).

    Article  Google Scholar 

  13. 13

    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 

  14. 14

    Camargo, S. J. Global and regional aspects of tropical cyclone activity in the CMIP5 models. J. Clim. 26, 9880–9902 (2013).

    Article  Google Scholar 

  15. 15

    Wang, C., Zhang, L., Lee, S.-K., Wu, L. & Mechoso, C. R. A global perspective on CMIP5 climate model biases. Nat. Clim. Change 4, 201–205 (2014).

    Article  Google Scholar 

  16. 16

    Tory, K. J., Dare, R. A., Davidson, N. E., McBride, J. L. & Chand, S. S. The importance of low-deformation vorticity in tropical cyclone formation. Atmos. Chem. Phys. 13, 2115–2132 (2013).

    CAS  Article  Google Scholar 

  17. 17

    Horn, M. et al. Tracking scheme dependence of simulated tropical cyclone response to idealized climate simulations. J. Clim. 27, 9197–9213 (2014).

    Article  Google Scholar 

  18. 18

    Peters, G. P. et al. The challenge to keep global warming below 2 °C. Nat. Clim. Change 3, 4–6 (2013).

    Article  Google Scholar 

  19. 19

    Christensen, J. H. et al. in Climate Change 2013: The Physical Science Basis (eds Stocker, T. F. et al.) 1217–1308 (IPCC, Cambridge Univ. Press, 2013).

    Google Scholar 

  20. 20

    Vecchi, G. A. & Soden, B. J. Global warming and the weakening of the tropical circulation. J. Clim. 20, 4316–4340 (2007).

    Article  Google Scholar 

  21. 21

    Stevenson, S. et al. Will there be a significant change to El Niño in the twenty-first century? J. Clim. 25, 2129–2145 (2012).

    Article  Google Scholar 

  22. 22

    Trenberth, K. E. The definition of El Niño. Bull. Am. Meteorol. Soc. 78, 2771–2777 (1997).

    Article  Google Scholar 

  23. 23

    Wang, H. et al. How well do global climate models simulate the variability of Atlantic tropical cyclones associated with ENSO? J. Clim. 27, 5673–5692 (2014).

    Article  Google Scholar 

  24. 24

    Bell, R., Hodges, K., Vidale, P. L., Strachan, J. & Roberts, M. Simulation of the global ENSO–tropical cyclone teleconnection by a high-resolution coupled general circulation model. J. Clim. 27, 6404–6422 (2014).

    Article  Google Scholar 

  25. 25

    Kim, H.-S. et al. Tropical cyclone simulation and response to CO2 doubling in the GFDL CM2.5 high-resolution coupled climate model. J. Clim. 27, 8034–8054 (2014).

    Article  Google Scholar 

  26. 26

    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 cyclone data. Bull. Am. Meteorol. Soc. 91, 363–376 (2010).

    Article  Google Scholar 

  27. 27

    Shaman, J. & Maloney, E. D. Shortcomings in climate model simulations of the ENSO-Atlantic hurricane teleconnection. Clim. Dynam. 38, 1973–1988 (2012).

    Article  Google Scholar 

  28. 28

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

    Article  Google Scholar 

  29. 29

    Rayner, N. A. et al. Global analyses of SST, sea ice and night marine air temperature since the late nineteenth century. J. Geophys. Res. 108, 4407 (2003).

    Article  Google Scholar 

  30. 30

    Widlansky, M. J. et al. Changes in South Pacific rainfall bands in a warming climate. Nat. Clim. Change 3, 417–423 (2013).

    Article  Google Scholar 

  31. 31

    Cai, W. et al. ENSO and greenhouse warming. Nat. Clim. Change 5, 849–859 (2015).

    Article  Google Scholar 

  32. 32

    Johnson, N. C. & Xie, S.-P. Changes in the sea surface temperature threshold for tropical convection. Nat. Geosci. 3, 842–845 (2010).

    CAS  Article  Google Scholar 

  33. 33

    Tory, K. J., Chand, S. S., Dare, R. A. & McBride, J. L. An assessment of a model-independent tropical cyclone detection procedure in selected CMIP3 global climate models. J. Clim. 26, 5508–5522 (2013).

    Article  Google Scholar 

  34. 34

    Dunkerton, T. J., Montgomery, M. T. & Wang, Z. Tropical cyclogenesis in a tropical wave critical layer: easterly waves. Atmos. Chem. Phys. 9, 5587–5646 (2009).

    CAS  Article  Google Scholar 

  35. 35

    Emanuel, K. A. & Nolan, D. S. In 26th Conf. on Hurricanes and Tropical Meteorology (Am. Meteorol. Soc., 10A.2., 2004);

  36. 36

    Tippett, M. K., Camargo, S. J. & Sobel, A. H. A Poisson regression index for tropical cyclone genesis and the role of large-scale vorticity in genesis. J. Clim. 26, 2335–2357 (2011).

    Article  Google Scholar 

  37. 37

    Menkes, C. E. et al. Comparison of tropical cyclogenesis indices on seasonal to interannual timescales. Clim. Dynam. 38, 301–321 (2012).

    Article  Google Scholar 

  38. 38

    Bruyère, C. L., Holland, G. J. & Towler, E. Investigating the use of a genesis potential index for tropical cyclones in the North Atlantic basin. J. Clim. 25, 8611–8626 (2012).

    Article  Google Scholar 

  39. 39

    Camargo, S. J. et al. Testing the performance of tropical cyclone genesis indices in future climates using the HiRAM model. J. Clim. 27, 9171–9196 (2014).

    Article  Google Scholar 

  40. 40

    Song, Y. et al. Tropical cyclone genesis potential index over the western North Pacific simulated by CMIP5 models. Adv. Atmos. Sci. 32, 1539–1550.

  41. 41

    McBride, J. L. & Zehr, R. Observational analysis of tropical cyclone formation. Part II: Comparison of non-developing versus developing systems. J. Atmos. Sci. 38, 1132–1151 (1981).

    Article  Google Scholar 

  42. 42

    Davidson, N. E., Holland, G. J., McBride, J. L. & Keenan, T. D. On the formation of AMEX Tropical Cyclones Irma and Jason. Mon. Weath. Rev. 118, 1981–2000 (1990).

    Article  Google Scholar 

  43. 43

    Murphy, B. F., Ye, H. & Delage, F. Impacts of variations in the strength and structure of El Niño on Pacific rainfall in CMIP5 models. Clim. Dynam. 44, 3171–3186 (2015).

    Article  Google Scholar 

  44. 44

    Bellenger, H. et al. ENSO representation in climate models: from CMIP3 to CMIP5. Clim. Dynam. 42, 1999–2018 (2014).

    Article  Google Scholar 

  45. 45

    Taschetto, A. S. et al. Cold tongue and warm pool ENSO events in CMIP5: mean state and future projections. J. Clim. 27, 2861–2885 (2014).

    Article  Google Scholar 

  46. 46

    Grose, M. R. et al. Assessment of the CMIP5 global climate model simulations of the western tropical Pacific climate system and comparison to CMIP3. Int. J. Climatol. 34, 3382–3399 (2014).

    Article  Google Scholar 

  47. 47

    Wilks, D. S. Statistical Methods in the Atmospheric Sciences Ch. 5 (Academic, 2006).

    Google Scholar 

  48. 48

    Chand, S. et al. The different impact of positive-neutral and negative-neutral ENSO regimes on Australian tropical cyclones. J. Clim. 26, 8008–8016 (2013).

    Article  Google Scholar 

  49. 49

    Chand, S. et al. Impact of different ENSO regimes on southwest Pacific tropical cyclones. J. Clim. 26, 600–608 (2013).

    Article  Google Scholar 

  50. 50

    Flato, G. et al. in Climate Change 2013: The Physical Science Basis (eds Stocker, T. F. et al.) 741–866 (IPCC, Cambridge Univ. Press, 2013).

    Google Scholar 

  51. 51

    Taylor, K. E. Summarizing multiple aspects of model performance in a single diagram. J. Geophys. Res. 106, 7183–7192 (2001).

    Article  Google Scholar 

  52. 52

    Irving, D. B. Evaluating global climate models for the Pacific island region. Clim. Res. 49, 167–187 (2011).

    Article  Google Scholar 

  53. 53

    Chan, J. C. L. Tropical cyclone activity over the Western North Pacific associated with El Niño and La Niña events. J. Clim. 13, 2960–2972 (2000).

    Article  Google Scholar 

  54. 54

    Ramage, C. S. & Hori, A. M. Meteorological aspects of El Niño. Mon. Weath. Rev. 109, 1827–1835 (1981).

    Article  Google Scholar 

  55. 55

    Collins, M. et al. A comparison of perturbed physics and multi-model ensembles: Model errors, feedbacks and forcings. Clim. Dynam. 36, 1737–1766 (2011).

    Article  Google Scholar 

  56. 56

    Tebaldi, T. & Knutti, R. The use of multi-model ensemble in probabilistic climate projections. Phil. Trans. R. Soc. A 365, 2053–2075 (2007).

    Article  Google Scholar 

  57. 57

    Knutti, R., Masson, D. & Gettelman, A. Climate model genealogy: generation CMIP5 and how we got there. Geophys. Res. Lett. 40, 1194–1199 (2013).

    Article  Google Scholar 

Download references


This project is supported through funding from the Australian Government’s National Environmental Science Programme (NESP). We thank S. Power, A. Dowdy, M. Wheeler and E. Ebert from the Australian Bureau of Meteorology for their valuable feedback. S.S.C. also thanks P. Vamplew and colleagues at Federation University Australia for their comments on this work.

Author information




S.S.C. conceived and designed the study in discussion with K.J.T. and K.J.E.W., and wrote the initial draft of the paper. S.S.C., K.J.T. and H.Y. performed the analysis. All authors contributed to interpreting results, discussion of the associated dynamics, and improvement of this paper.

Corresponding author

Correspondence to Savin S. Chand.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Information

Supplementary Information (PDF 11694 kb)

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Chand, S., Tory, K., Ye, H. et al. Projected increase in El Niño-driven tropical cyclone frequency in the Pacific. Nature Clim Change 7, 123–127 (2017).

Download citation

Further reading