Climate Dynamics

, Volume 40, Issue 11–12, pp 2825–2847 | Cite as

Analysis of the non-linearity in the pattern and time evolution of El Niño southern oscillation

  • Dietmar DommengetEmail author
  • Tobias Bayr
  • Claudia Frauen


In this study the observed non-linearity in the spatial pattern and time evolution of El Niño Southern Oscillation (ENSO) events is analyzed. It is shown that ENSO skewness is not only a characteristic of the amplitude of events (El Niños being stronger than La Niñas) but also of the spatial pattern and time evolution. It is demonstrated that these non-linearities can be related to the non-linear response of the zonal winds to sea surface temperature (SST) anomalies. It is shown in observations as well as in coupled model simulations that significant differences in the spatial pattern between positive (El Niño) versus negative (La Niña) and strong versus weak events exist, which is mostly describing the difference between central and east Pacific events. Central Pacific events tend to be weak El Niño or strong La Niña events. In turn east Pacific events tend to be strong El Niño or weak La Niña events. A rotation of the two leading empirical orthogonal function modes illustrates that for both El Niño and La Niña extreme events are more likely than expected from a normal distribution. The Bjerknes feedbacks and time evolution of strong ENSO events in observations as well as in coupled model simulations also show strong asymmetries, with strong El Niños being forced more strongly by zonal wind than by thermocline depth anomalies and are followed by La Niña events. In turn strong La Niña events are preceded by El Niño events and are more strongly forced by thermocline depth anomalies than by wind anomalies. Further, the zonal wind response to sea surface temperature anomalies during strong El Niño events is stronger and shifted to the east relative to strong La Niña events, supporting the eastward shifted El Niño pattern and the asymmetric time evolution. Based on the simplified hybrid coupled RECHOZ model of ENSO it can be shown that the non-linear zonal wind response to SST anomalies causes the asymmetric forcings of ENSO events. This also implies that strong El Niños are mostly wind driven and less predictable and strong La Niñas are mostly thermocline depth driven and better predictable, which is demonstrated by a set of 100 perfect model forecast ensembles.


El Nino Southern Oscillation El Nino Modoki ENSO teleconnections ENSO dynamics Seasonal to interannual predictions Tropical Pacific climate variability 



We like to thank Harry Hendon, Neville Nicholls and Yuko Okumura for fruitful discussions and comments. We also like to thank two anonymous referees for their comments. This study was supported by the ARC Centre of Excellence in Climate System Science (CE110001028), the ARC project “Beyond the linear dynamics of the El Nino Southern Oscillation” (DP120101442) and the Deutsche Forschung Gemeinschaft (DO1038/5-1).


  1. An SI, Ham YG, Kug JS, Jin FF, Kang IS (2005) El Nino La Nina asymmetry in the coupled model intercomparison project simulations. J Clim 18:2617–2627CrossRefGoogle Scholar
  2. Ashok K, Behera SK, Rao SA, Weng HY, Yamagata T (2007) El Nino Modoki and its possible teleconnection. J Geophys Res Oceans 112Google Scholar
  3. Burgers G, Stephenson DB (1999) The “normality” of El Nino. Geophys Res Lett 26:1027–1030CrossRefGoogle Scholar
  4. Burgers G, Jin FF, van Oldenborgh GJ (2005) The simplest ENSO recharge oscillator. Geophys Res Lett 32Google Scholar
  5. Carton JA, Chepurin G, Cao XH (2000) A simple ocean data assimilation analysis of the global upper ocean 1950–95. Part II: results. J Phys Oceanogr 30:311–326CrossRefGoogle Scholar
  6. Choi J, An S-I, Yeh S-W (2012) Decadal amplitude modulation of two types of ENSO and its relationship with the mean state. Clim Dyn 38:2631–2644. doi: 10.1007/s00382-011-1186-y Google Scholar
  7. Dommenget D (2007) Evaluating EOF modes against a stochastic null hypothesis. Clim Dyn 28:517–531CrossRefGoogle Scholar
  8. Dommenget D, Latif M (2002) A cautionary note on the interpretation of EOFs. J Clim 15:216–225CrossRefGoogle Scholar
  9. Dommenget D, Semenov V, Latif M (2006) Impacts of the tropical Indian and Atlantic Oceans on ENSO. Geophys Res Lett 33Google Scholar
  10. Frauen C, Dommenget D (2010) El Nino and La Nina amplitude asymmetry caused by atmospheric feedbacks. Geophys Res Lett 37Google Scholar
  11. Frauen C, Dommenget D (2012) Influences of the tropical Indian and Atlantic Oceans on the predictability of ENSO. Geophys Res Lett 39Google Scholar
  12. Hoerling MP, Kumar A, Zhong M (1997) El Nino, La Nina, and the nonlinearity of their teleconnections. J Clim 10:1769–1786CrossRefGoogle Scholar
  13. Jansen MF, Dommenget D, Keenlyside N (2009) Tropical atmosphere-ocean interactions in a conceptual framework. J Clim 22:550–567CrossRefGoogle Scholar
  14. Kalnay E, Kanamitsu M, Kistler R, Collins W, Deaven D, Gandin L, Iredell M, Saha S, White G, Woollen J, Zhu Y, Chelliah M, Ebisuzaki W, Higgins W, Janowiak J, Mo KC, Ropelewski C, Wang J, Leetmaa A, Reynolds R, Jenne R, Joseph D (1996) The NCEP/NCAR 40-year reanalysis project. Bull Am Meteorol Soc 77:437–471CrossRefGoogle Scholar
  15. Kang IS, Kug JS (2002) El Nino and La Nina sea surface temperature anomalies: asymmetry characteristics associated with their wind stress anomalies. J Geophys Res Atmos 107Google Scholar
  16. Kao HY, Yu JY (2009) Contrasting eastern-pacific and central-pacific types of ENSO. J Clim 22:615–632CrossRefGoogle Scholar
  17. Keenlyside NS, Latif M (2007) Understanding equatorial Atlantic interannual variability. J Clim 20:131–142CrossRefGoogle Scholar
  18. Larkin NK, Harrison DE (2002) ENSO warm (El Nino) and cold (La Nina) event life cycles: ocean surface anomaly patterns, their symmetries, asymmetries, and implications. J Clim 15:1118–1140CrossRefGoogle Scholar
  19. Larkin NK, Harrison DE (2005) Global seasonal temperature and precipitation anomalies during El Nino autumn and winter. Geophys Res Lett 32Google Scholar
  20. Marsland SJ, Haak H, Jungclaus JH, Latif M, Roske F (2003) The Max-Planck-Institute global ocean/sea ice model with orthogonal curvilinear coordinates. Ocean Model 5:91–127CrossRefGoogle Scholar
  21. McPhaden MJ, Lee T, McClurg D (2011) El Nino and its relationship to changing background conditions in the tropical Pacific Ocean. Geophys Res Lett 38Google Scholar
  22. Meehl GA, Covey C, Delworth T, Latif M, McAvaney B, Mitchell JFB, Stouffer RJ, Taylor KE (2007) The WCRP CMIP3 multimodel dataset—a new era in climate change research. Bull Am Meteorol Soc 88:1383–+Google Scholar
  23. Monahan AH (2001) Nonlinear principal component analysis: tropical Indo-Pacific sea surface temperature and sea level pressure. J Clim 14:219–233CrossRefGoogle Scholar
  24. Ohba M, Ueda H (2009) Role of nonlinear atmospheric response to SST on the asymmetric transition process of ENSO. J Clim 22:177–192CrossRefGoogle Scholar
  25. Ohba M, Watanabe M (2012) Role of the Indo-Pacific interbasin coupling in predicting asymmetric ENSO transition and duration. J Clim 25Google Scholar
  26. Ohba M, Nohara D, Ueda H (2010) Simulation of asymmetric ENSO transition in WCRP CMIP3 multimodel experiments. J Clim 23:6051–6067CrossRefGoogle Scholar
  27. Okumura YM, Deser C (2010) Asymmetry in the duration of El Nino and La Nina. J Clim 23:5826–5843CrossRefGoogle Scholar
  28. Philip S, van Oldenborgh GJ (2009) Significant atmospheric nonlinearities in the ENSO cycle. J Clim 22:4014–4028CrossRefGoogle Scholar
  29. Rayner NA, Parker DE, Horton EB, Folland CK, Alexander LV, Rowell DP, Kent EC, Kaplan A (2003) Global analyses of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century. J Geophys Res Atmos 108Google Scholar
  30. Rodgers KB, Friederichs P, Latif M (2004) Tropical pacific decadal variability and its relation to decadal modulations of ENSO. J Clim 17:3761–3774CrossRefGoogle Scholar
  31. Schopf PS, Burgman RJ (2006) A simple mechanism for ENSO residuals and asymmetry. J Clim 19:3167–3179CrossRefGoogle Scholar
  32. Smith TM, Reynolds RW, Peterson TC, Lawrimore J (2008) Improvements to NOAA’s historical merged land-ocean surface temperature analysis (1880–2006). J Clim 21:2283–2296CrossRefGoogle Scholar
  33. Sun FP, Yu JY (2009) A 10–15-years modulation cycle of ENSO intensity. J Clim 22:1718–1735CrossRefGoogle Scholar
  34. Takahashi K, Montecinos A, Goubanova K, Dewitte B (2011) ENSO regimes: reinterpreting the canonical and Modoki El Nino. Geophys Res Lett 38Google Scholar
  35. van Oldenborgh GJ, Philip SY, Collins M (2005) El Nino in a changing climate: a multi-model study. Ocean Sci 1:81–95CrossRefGoogle Scholar
  36. Yeh SW, Kug JS, Dewitte B, Kwon MH, Kirtman BP, Jin FF (2009) El Nino in a changing climate. Nature 461:511–514CrossRefGoogle Scholar
  37. Yu JY, Kim ST (2011) Reversed spatial asymmetries between El Nino and La Nina and their linkage to decadal ENSO modulation in CMIP3 models. J Clim 24:5423–5434CrossRefGoogle Scholar
  38. Zhang XB, McPhaden MJ (2006) Wind stress variations and interannual sea surface temperature anomalies in the eastern equatorial Pacific. J Clim 19:226–241CrossRefGoogle Scholar
  39. Zhang XB, McPhaden MJ (2010) Surface layer heat balance in the eastern equatorial Pacific Ocean on interannual time scales: influence of local versus remote wind forcing. J Clim 23:4375–4394CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2012

Authors and Affiliations

  • Dietmar Dommenget
    • 1
    Email author
  • Tobias Bayr
    • 2
  • Claudia Frauen
    • 1
  1. 1.School of Mathematical SciencesMonash UniversityClaytonAustralia
  2. 2.Helmholtz Centre for Ocean Research Kiel (GEOMAR)KielGermany

Personalised recommendations