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Degree of simulated suppression of Atlantic tropical cyclones modulated by flavour of El Niño

Nature Geoscience volume 9, pages 155–160 (2016)Cite this article

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Abstract

El Niño/Southern Oscillation, the dominant mode of interannual climate variability, strongly influences tropical cyclone activity. During canonical El Niño, the warm phase, Atlantic tropical cyclones are suppressed. However, the past decades have witnessed different El Niño characteristics, ranging from warming over the east Pacific cold tongue in canonical events to warming near the warm pool, known as warm pool El Niño or central Pacific El Niño. Global climate models project possible future increases in intensity of warm pool El Niño. Here we use a climate model at a resolution sufficient to explicitly simulate tropical cyclones to investigate how these flavours of El Niño may affect such cyclones. We show that Atlantic tropical cyclones are suppressed regardless of El Niño type. For the warmest 10% of each El Niño flavour, warm pool El Niño is substantially less effective at suppressing Atlantic tropical cyclones than cold tongue El Niño. However, for the same absolute warming intensity, the opposite is true. This is because less warming is required near the warm pool to satisfy the sea surface temperature threshold for deep convection, which leads to tropical cyclone suppression through vertical wind shear enhancements. We conclude that an understanding of future changes in not only location, but also intensity and frequency, of El Niño is important for forecasts and projections of Atlantic tropical cyclone activity.

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Figure 1: SST forcing during flavours of El Niño.
Figure 2: Simulated effects of flavours of El Niño on tropical cyclone track density.
Figure 3: Distributions of seasonal tropical cyclone activity simulated under climatological and El Niño SST forcings.
Figure 4: Simulated deep convection and prescribed SST and SST anomalies during climatology and flavours of El Niño.
Figure 5: Simulated Walker circulation response to flavours of El Niño.

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References

  1. Bove, M. C., O’Brien, J. J., Elsner, J. B., Landsea, C. W. & Niu, X. Effect of El Niño on U.S. landfalling hurricanes, revisited. Bull. Am. Meteorol. Soc. 79, 2477–2482 (1998).

    Article  Google Scholar 

  2. Pielke, R. A. Jr & Landsea, C. W. La Niña, El Niño, and Atlantic hurricane damages in the United States. Bull. Am. Meteorol. Soc. 80, 2027–2033 (1999).

    Article  Google Scholar 

  3. Smith, S. R., Brolley, J., O’Brien, J. J. & Tartaglione, C. A. ENSO’s impact on regional U.S. hurricane activity. J. Clim. 20, 1404–1414 (2007).

    Article  Google Scholar 

  4. Arkin, P. A. The relationship between interannual variability in the 200 mb tropical wind field and the Southern Oscillation. Mon. Weath. Rev. 110, 1393–1404 (1982).

    Article  Google Scholar 

  5. Gray, W. M. Atlantic seasonal hurricane frequency. Part I: El Niño and 30 mb quasi-biennial oscillation influences. Mon. Weath. Rev. 112, 1649–1668 (1984).

    Article  Google Scholar 

  6. Goldenberg, S. B. & Shapiro, L. J. Physical mechanisms for the association of El Niño and West African rainfall with Atlantic major hurricane activity. J. Clim. 9, 1169–1187 (1996).

    Article  Google Scholar 

  7. Gray, W. M. Global view of the origin of tropical disturbances and storms. Mon. Weath. Rev. 96, 669–700 (1968).

    Article  Google Scholar 

  8. Frank, W. M. & Ritchie, E. A. Effects of vertical wind shear on the intensity and structure of numerically simulated hurricanes. Mon. Weath. Rev. 129, 2249–2269 (2001).

    Article  Google Scholar 

  9. Gallina, G. M. & Velden, C. S. Environmental vertical wind shear and tropical cyclone intensity change utilizing enhanced satellite derived wind information. In 25th Conference on Hurricanes and Tropical Meteorology 172–173 (Am. Meteorol. Soc., 2002).

  10. Wong, M. L. M. & Chan, J. C. L. Tropical cyclone intensity in vertical wind shear. J. Atmos. Sci. 61, 1859–1876 (2004).

    Article  Google Scholar 

  11. Tang, B. H. & Neelin, J. D. ENSO influence on Atlantic hurricanes via tropospheric warming. Geophys. Res. Lett. 31, L24204 (2004).

    Article  Google Scholar 

  12. Ashok, K., Behera, S. K., Rao, S. A., Weng, H. & Yamagata, T. El Niño Modoki and its possible teleconnection. J. Geophys. Res. 112, C11007 (2007).

    Article  Google Scholar 

  13. Kug, J.-S., Jin, F.-F. & An, S.-I. Two types of El Niño events: cold tongue El Niño and warm pool El Niño. J. Clim. 22, 1499–1515 (2009).

    Article  Google Scholar 

  14. Lee, T. & McPhaden, M. J. Increasing intensity of El Niño in the central-equatorial Pacific. Geophys. Res. Lett. 37, L14603 (2010).

    Google Scholar 

  15. Takahashi, K., Montecinos, A., Goubanova, K. & Dewitte, B. ENSO regimes: reinterpreting the canonical and Modoki El Niño. Geophys. Res. Lett. 38, L10704 (2011).

    Article  Google Scholar 

  16. Kim, H.-M., Webster, P. J. & Curry, J. A. Impact of shifting patterns of Pacific ocean warming on North Atlantic tropical cyclones. Science 325, 77–80 (2009).

    Article  Google Scholar 

  17. Lee, S.-K., Wang, C. & Enfield, D. B. On the impact of central Pacific warming events on Atlantic tropical storm activity. Geophys. Res. Lett. 37, L17702 (2010).

    Google Scholar 

  18. Larson, S., Lee, S.-K., Wang, C., Chung, E.-S. & Enfield, D. B. Impacts of non-canonical El Niño patterns on Atlantic hurricane activity. Geophys. Res. Lett. 39, L14706 (2012).

    Article  Google Scholar 

  19. 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 

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

    Article  Google Scholar 

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

    Google Scholar 

  22. Skamarock, W. C. et al. A Description of the Advanced Research WRF Version 3 NCAR/TN–475+STR (2008); http://dx.doi.org/10.5065/D68S4MVH.

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

    Article  Google Scholar 

  24. Wang, C. & Lee, S.-K. Co-variability of tropical cyclones in the North Atlantic and the eastern North Pacific. Geophys. Res. Lett. 36, L24702 (2009).

    Article  Google Scholar 

  25. Bell, G. D. et al. Climate Assessment for 1999. Bull. Am. Meteorol. Soc. 81, s1–s50 (2000).

    Article  Google Scholar 

  26. Williams, I. N., Pierrehumbert, R. T. & Huber, M. Global warming, convective threshold and false thermostats. Geophys. Res. Lett. 36, L21805 (2009).

    Article  Google Scholar 

  27. Gadgil, S., Joseph, P. V. & Joshi, N. V. Ocean–atmosphere coupling over monsoon regions. Nature 312, 141–143 (1984).

    Article  Google Scholar 

  28. Graham, N. E. & Barnett, T. P. Sea surface temperature, surface wind divergence, and convection over tropical oceans. Science 238, 657–659 (1987).

    Article  Google Scholar 

  29. Zhang, C. Large-scale variability of atmospheric deep convection in relation to sea surface temperature in the tropics. J. Clim. 6, 1898–1913 (1993).

    Article  Google Scholar 

  30. Waliser, D. E., Graham, N. E. & Gautier, C. Comparison of the highly reflective cloud and outgoing longwave radiation datasets for use in estimating tropical deep convection. J. Clim. 6, 331–353 (1993).

    Article  Google Scholar 

  31. Sabin, T. P., Babu, C. A. & Joseph, P. V. SST–convection relation over tropical oceans. Int. J. Climatol. 33, 1424–1435 (2013).

    Article  Google Scholar 

  32. Emanuel, K. A. & Nolan, D. Tropical cyclone activity and global climate. In 26th Conference on Hurricanes and Tropical Meteorology 240–241 (Am. Meteorol. Soc., 2004).

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

    Article  Google Scholar 

  34. Evans, J. L. & Waters, J. J. Simulated relationships between sea surface temperatures and tropical convection in climate models and their implications for tropical cyclone activity. J. Clim. 25, 7884–7895 (2012).

    Article  Google Scholar 

  35. Simpson, R. & Riehl, R. Mid-tropospheric ventilation as a constraint on hurricane development and maintenance. Preprints, Tech. Conf. on Hurricanes, Miami Beach, FL, Am. Meteorol. Soc. D4-1–D4-10 (1958).

  36. Tang, B. & Emanuel, K. Midlevel ventilation’s constraint on tropical cyclone intensity. J. Atmos. Sci. 67, 1817–1830 (2010).

    Article  Google Scholar 

  37. Patricola, C. M., Saravanan, R. & Chang, P. The impact of the El Niño–Southern Oscillation and Atlantic meridional mode on seasonal Atlantic tropical cyclone activity. J. Clim. 27, 5311–5328 (2014).

    Article  Google Scholar 

  38. Landsea, C. W., Pielke, R. A. Jr & Mestas-Nuñez, A. M. Atlantic basin hurricanes: indices of climate change. Climatic Change 42, 89–129 (1999).

    Article  Google Scholar 

  39. Goldenberg, S. B., Landsea, C. W., Mestas-Nuñez, A. M. & Gray, W. M. The recent increase in Atlantic hurricane activity: causes and implications. Science 293, 474–479 (2001).

    Article  Google Scholar 

  40. Vitart, F. & Anderson, J. L. Sensitivity of Atlantic tropical storm frequency to ENSO and interdecadal variability of SSTs in an ensemble of AGCM integrations. J. Clim. 14, 533–545 (2001).

    Article  Google Scholar 

  41. Webster, P. J., Holland, G. J., Curry, J. A. & Chang, H.-R. Changes in tropical cyclone number, duration, and intensity in a warming environment. Science 309, 1844–1846 (2005).

    Article  Google Scholar 

  42. Bell, G. D. & Chelliah, M. Leading tropical modes associated with interannual and multidecadal fluctuations in North Atlantic hurricane activity. J. Clim. 19, 590–612 (2006).

    Article  Google Scholar 

  43. Kossin, J. P. & Vimont, D. J. A more general framework for understanding Atlantic hurricane variability and trends. Bull. Am. Meteorol. Soc. 88, 1767–1781 (2007).

    Article  Google Scholar 

  44. Klotzbach, P. J. The influence of El Niño–Southern Oscillation and the Atlantic Multidecadal Oscillation on Caribbean tropical cyclone activity. J. Clim. 24, 721–731 (2011).

    Article  Google Scholar 

  45. Kanamitsu, M. et al. NCEP-DOE AMIP-II Reanalysis (R-2). Bull. Am. Meteorol. Soc. 83, 1631–1643 (2002).

    Article  Google Scholar 

  46. Walsh, K. Objective detection of tropical cyclones in high-resolution analyses. Mon. Weath. Rev. 125, 1767–1779 (1997).

    Article  Google Scholar 

  47. Emanuel, K. A sensitivity of tropical cyclones to surface exchange coefficients and a revised steady-state model incorporating eye dynamics. J. Atmos. Sci. 52, 3969–3976 (1995).

    Article  Google Scholar 

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

    Article  Google Scholar 

  49. Camargo, S. J., Emanuel, K. A. & Sobel, A. H. Use of a genesis potential index to diagnose ENSO effects on tropical cyclone genesis. J. Clim. 20, 4819–4834 (2007).

    Article  Google Scholar 

  50. Landsea, C. W. & Franklin, J. L. Atlantic hurricane database uncertainty and presentation of a new database format. Mon. Weath. Rev. 141, 3576–3592 (2013).

    Article  Google Scholar 

  51. Schade, L. R. & Emanuel, K. A. The ocean’s effect on the intensity of tropical cyclones: results from a simple coupled atmosphere–ocean model. J. Atmos. Sci. 56, 642–651 (1999).

    Article  Google Scholar 

  52. Kalnay, E. et al. The NCEP/NCAR 40-year reanalysis project. Bull. Am. Meteorol. Soc. 77, 437–470 (1996).

    Article  Google Scholar 

  53. Adler, R. F. et al. The version 2 global precipitation climatology project (GPCP) monthly precipitation analysis (1979-present). J. Hydrometeorol. 4, 1147–1167 (2003).

    Article  Google Scholar 

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Acknowledgements

This research was supported by US National Science Foundation Grant AGS-1347808 and used the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by National Science Foundation Grant ACI-1053575. P.C. acknowledges the support from the National Program on Key Basic Research Project (973 Program) no. 2013CB956204 and no. 2014CB745000. High-performance computing resources were provided by the Texas Advanced Computing Center (TACC) at The University of Texas at Austin and by the Texas A&M Supercomputing Facility.

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Authors and Affiliations

  1. Department of Atmospheric Sciences, Texas A&M University, College Station, Texas 77843, USA

    Christina M. Patricola, Ping Chang & R. Saravanan

  2. Department of Oceanography, Texas A&M University, College Station, Texas 77843, USA

    Ping Chang

  3. Physical Oceanography Laboratory/Qingdao Collaborative Innovation Center of Marine Science and Technology, Ocean University of China, Qingdao 266100, China

    Ping Chang

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  1. Christina M. Patricola
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All authors contributed to designing the project, interpreting the results, and improving the paper. C.M.P. carried out the model simulations and analysis and wrote the paper.

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Correspondence to Christina M. Patricola.

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Patricola, C., Chang, P. & Saravanan, R. Degree of simulated suppression of Atlantic tropical cyclones modulated by flavour of El Niño. Nature Geosci 9, 155–160 (2016). https://doi.org/10.1038/ngeo2624

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