Advances in Atmospheric Sciences

, Volume 33, Issue 3, pp 352–364 | Cite as

Weak ENSO asymmetry due to weak nonlinear air–sea interaction in CMIP5 climate models

  • Yan Sun
  • Fan WangEmail author
  • De-Zheng Sun


State-of-the-art climate models have long-standing intrinsic biases that limit their simulation and projection capabilities. Significantly weak ENSO asymmetry and weakly nonlinear air–sea interaction over the tropical Pacific was found in CMIP5 (Coupled Model Intercomparison Project, Phase 5) climate models compared with observation. The results suggest that a weak nonlinear air–sea interaction may play a role in the weak ENSO asymmetry. Moreover, a weak nonlinearity in air–sea interaction in the models may be associated with the biases in the mean climate—the cold biases in the equatorial central Pacific. The excessive cold tongue bias pushes the deep convection far west to the western Pacific warm pool region and suppresses its development in the central equatorial Pacific. The deep convection has difficulties in further moving to the eastern equatorial Pacific, especially during extreme El Ni˜no events, which confines the westerly wind anomaly to the western Pacific. This weakens the eastern Pacific El Ni˜no events, especially the extreme El Ni˜no events, and thus leads to the weakened ENSO asymmetry in climate models. An accurate mean state structure (especially a realistic cold tongue and deep convection) is critical to reproducing ENSO events in climate models. Our evaluation also revealed that ENSO statistics in CMIP5 climate models are slightly improved compared with those of CMIP3. The weak ENSO asymmetry in CMIP5 is closer to the observation. It is more evident in CMIP5 that strong ENSO activities are usually accompanied by strong ENSO asymmetry, and the diversity of ENSO amplitude is reduced.

Key words

ENSO asymmetry nonlinearity air–sea interaction cold tongue CMIP5 deep convection 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Supplementary material

376_2015_5018_MOESM1_ESM.pdf (1.9 mb)
Supplementary material, approximately 1934 KB.


  1. An, S.-I., Y.-G. Ham, J.-S. Kug, F.-F. Jin, and I.-S. Kang, 2005: El Ni˜no–La Ni˜na asymmetry in the Coupled Model Intercomparison Project simulations. J. Climate, 18, 2617–2627.CrossRefGoogle Scholar
  2. Adler, R. F., and Coauthors, 2003: The version-2 Global Precipitation Climatology Project (GPCP) monthly precipitation analysis (1979–present). Journal of Hydrometeorology, 4(6), 1147–1167.CrossRefGoogle Scholar
  3. An, S.-I., 2009: A review of interdecadal changes in the nonlinearity of the El Ni˜no-Southern Oscillation. Theor. Appl. Climatol., 97, 29–40.CrossRefGoogle Scholar
  4. An, S.-I., and F. F. Jin, 2004: Nonlinearity and asymmetry of ENSO. J. Climate, 17, 2399–2412.CrossRefGoogle Scholar
  5. An, S.-I., Y.-G. Ham, J.-S. Kug, F. F. Jin, and I.-S. Kang, 2009: El Ni˜no–La Ni˜na asymmetry in the coupled model intercomparison project simulations. J. Climate, 18, 2617–2627.CrossRefGoogle Scholar
  6. Bjerknes, J., 1969: Atmospheric teleconnections from the equatorial Pacific. Mon. Wea. Rev., 97, 163–172.CrossRefGoogle Scholar
  7. Burgers, G., and D. B. Stephenson, 1999: The “Normality” of El Ni˜no. Geophys. Res. Lett., 26, 1027–1030.CrossRefGoogle Scholar
  8. Cai, W. J., and Coauthors, 2014: Increasing frequency of extreme El Ni˜no events due to greenhouse warming. Nature Clim. Change, 4, 111–116.CrossRefGoogle Scholar
  9. Cane, M. A., 1983: Oceanographic events during El Ni˜no. Science, 222, 1189–1195.CrossRefGoogle Scholar
  10. Carton, J. A., and B. S. Giese, 2008: A reanalysis of ocean climate using Simple Ocean Data Assimilation (SODA). Mon. Wea. Rev., 136, 2999–3017, doi: 10.1175/2007MWR1978.1.CrossRefGoogle Scholar
  11. Graham, N. E., and T. P. Barnett, 1987: Sea surface temperature, surface wind divergence, and convection over tropical oceans. Science, 238, 657–659.CrossRefGoogle Scholar
  12. Guilyardi, E., 2006: El Ni˜no-mean state-seasonal cycle interactions in a multi-model ensemble. Climate Dyn., 26, 329–348.CrossRefGoogle Scholar
  13. Ham, Y. G., and J. S. Kug, 2012: How well do current climate models simulate two types of El Ni˜no? Climate Dyn., 39, 383–398.Google Scholar
  14. Ham, Y. G., and J. S. Kug, 2014: Improvement of ENSO simulation based on intermodel diversity? J. Climate., 28, 998–1015.CrossRefGoogle Scholar
  15. Harrison, D. E., and G. A. Vecchi, 1999: On the termination of El Ni˜no. Geophys. Res. Lett., 26, 1593–1596.CrossRefGoogle Scholar
  16. Jin, F. F., D. Neelin, and M. Ghil, 1994: El Ni˜no on the devil’s staircase: Annual subharmonic steps to chaos. Science, 264, 70–72.CrossRefGoogle Scholar
  17. Jin, F. F., S.-I. An, A. Timmermann, and J. X. Zhao, 2003: Strong El Ni˜no events and nonlinear dynamical heating. Geophys. Res. Lett., 30, 1120, doi: 10.1029/2002GL016356.CrossRefGoogle Scholar
  18. Kim, S. T., and J. Y. Yu, 2012: The two types of ENSO in CMIP5 models. Geophys. Res. Lett., 39, L11704, doi: 10.1029/2012 GL052006.Google Scholar
  19. Kim, S. T., W. J. Cai, F. F. Jin, J. Y. Yu. 2014: ENSO stability in coupled climate models and its association with mean state. Climate Dyn., 42, 3313–3321.CrossRefGoogle Scholar
  20. Kug, J.-S., I.-S. Kang, and S.-I. An, 2003: Symmetric and antisymmetric mass exchanges between the equatorial and offequatorial Pacific associated with ENSO. J. Geophys. Res., 108, 3284.CrossRefGoogle Scholar
  21. Kug, J.-S., F.-F. Jin, and S.-I. An, 2009: Two-types of El Ni˜no events: Cold tongue El Ni˜no and warm pool El Ni˜no. J. Climate, 22, 1499–1515.CrossRefGoogle Scholar
  22. Latif, M., and Coauthors, 2001: ENSIP: The El Ni˜no simulation intercomparison project. Climate Dyn., 18, 255–276.CrossRefGoogle Scholar
  23. Leloup, J., M. Lengaigne, and J.-P. Boulanger, 2008: Twentieth century ENSO characteristics in the IPCC database. Climate Dyn., 30, 277–291.CrossRefGoogle Scholar
  24. Li, G., and S. P. Xie, 2012: Origins of tropical-wide SST biases in CMIP multi-model ensembles. Geophys. Res. Lett., 39, L22703, doi: 10.1029/2012GL053777.Google Scholar
  25. Li, G., and S. P. Xie, 2014: Tropical biases in CMIP5 multimodel ensemble: The excessive equatorial pacific cold tongue and double ITCZ problems. J. Climate, 27, 1765–1780, doi: 10.1175/JCLI-D-13-00337.1CrossRefGoogle Scholar
  26. McGregor, S., A. Timmermann, N. Schneider, M. Stuecker, and M. England, 2012: The Effect of the South Pacific convergence zone on the termination of El Ni˜no events and the meridional asymmetry of ENSO. J. Climate, 25, 5566–5586, doi: 10.1175/JCLI-D-11-00332.1.CrossRefGoogle Scholar
  27. McGregor, S., N. Ramesh, P. Spence, M. H. England, M. J. McPhaden, and A. Santoso, 2013: Meridional movement of wind anomalies during ENSO events and their role in event termination. Geophys. Res. Lett., 40, 749–754.CrossRefGoogle Scholar
  28. Mechoso, C. R., and Coauthors, 1995: The seasonal cycle over the tropical Pacific in coupled ocean-atmosphere general circulation models. Mon. Wea. Rev., 123, 2825–2838.CrossRefGoogle Scholar
  29. Philander, S. G. H., 1983: El Ni˜no Southern Oscillation phenomena. Nature, 302, 295–301.CrossRefGoogle Scholar
  30. Rayner, N. A., D. E. Parker, E. B. Horton, C. K. Folland, L. V. Alexander, D. P. Rowell, E. C. Kent, and A. Kaplan 2003: Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century, J. Geophys. Res., 108, 4407, doi: 10.1029/2002JD002670.CrossRefGoogle Scholar
  31. Rodgers, K. B., P. Friederichs, and M. Latif, 2004: Tropical Pacific decadal variability and its relation to decadal modulations of ENSO. J. Climate, 17, 3761–3774.CrossRefGoogle Scholar
  32. Sun, D. Z., and T. Zhang, 2006: A regulatory effect of ENSO on the time-mean thermal stratification of the equatorial upper ocean. Geophys. Res. Lett., 33, L07710, doi: 10.1029/2005 GL025296.CrossRefGoogle Scholar
  33. Sun, D.-Z., Y. Yu, and T. Zhang 2009: Tropical water vapor and cloud feedbacks in climate models: A further assessment using coupled simulations. J. Climate, 22(5), 1287–1304.CrossRefGoogle Scholar
  34. Sun, Y., D. Z. Sun, L. X. Wu, and F. Wang, 2013: Western Pacific warm pool and ENSO asymmetry in CMIP3 models. Adv. Atmos. Sci., 30, 940–953, doi: 10.1007/s00376-012-2161-1.CrossRefGoogle Scholar
  35. Wang, B., S.-I. An, 2002: A mechanism for decadal changes of ENSO behavior: Roles of background wind changes. Climate Dyn., 18, 475–486.CrossRefGoogle Scholar
  36. Wang, C. Z., L. P. Zhang, S. K. Lee, L. X.Wu, and C. R. Mechoso, 2014: A global perspective on CMIP5 climate model biases. Nature Clim. Change, 4, 201–205.CrossRefGoogle Scholar
  37. Zhang, W. J., and F. F. Jin, 2012: Improvements in the CMIP5 simulations of ENSO-SSTA meridional width. Geophys. Res. Lett., 39, L23704, doi: 10.1029/2012GL053588.Google Scholar
  38. Zhang, T., and D. Z. Sun, 2014: ENSO asymmetry in CMIP5 models. J. Climate, 27, 4070–4093.CrossRefGoogle Scholar
  39. Zhang, T., D. Z. Sun, R. Neale, and P. Rasch, 2009: An evaluation of ENSO asymmetry in the Community Climate System Models: A view from the subsurface. J. Climate, 22, 5933–5961, doi: 10.1175/2009JCLI2933.1.CrossRefGoogle Scholar

Copyright information

© Institute of Atmospheric Physics/Chinese Academy of Sciences, and Science Press and Springer-Verlag Berlin Heidelberg 2016

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, and provide a link to the Creative Commons license. You do not have permission under this license to share adapted material derived from this article or parts of it.

The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.

To view a copy of this license, visit (

Authors and Affiliations

  1. 1.Key Laboratory of Ocean Circulation and Waves, Institute of OceanologyChinese Academy of SciencesQingdaoChina
  2. 2.Laboratory for Ocean Dynamics and ClimateQingdao National Laboratory for Marine Science and TechnologyQingdaoChina
  3. 3.Cooperative Institute for Research in Environmental SciencesUniversity of Colorado, and NOAA/Earth System Research Laboratory/Physical Sciences DivisionBoulderUSA

Personalised recommendations