Climate simulations suggest that multi-decadal periods of high and low variability in the phenomenon known as the El Niño-Southern Oscillation in the tropical Pacific Ocean may be entirely unpredictable.

The episodic warming and cooling of the surface temperature of the tropical Pacific Ocean, known as the El Niño–Southern Oscillation (ENSO), causes year-to-year climate fluctuations, affecting weather, ecosystems and economies around the world. The occurrence of these episodes is not regular. For example, whereas the period covering the years 1970–2000 witnessed the strongest El Niño (warming) events on record, the years since 2000 have experienced fewer and weaker such events. Writing in the Journal of Climate, Wittenberg et al.1 make the case that these multi-decadal epochs of enhanced and subdued ENSO activity occur randomly and therefore may be unpredictable.

Changes in ENSO behaviour from decade to decade are commonly seen in historical observations and palaeoclimate proxy records2,3,4,5. These variations were first put into context by Wittenberg in an earlier study6, which examined a 2,000-year simulation based on a fairly realistic climate model, known as GFDL-CM2.1. This concluded that decadal- to centennial-scale changes in ENSO behaviour can be internally generated by the model in the absence of any external forcing, such as increases in greenhouse-gas concentration or variations in solar output.

Predicting whether the coming decades will bring an onslaught of strong ENSO events — or none at all — is crucial because of the impact of such events on weather patterns around the world. Individual episodes may be predicted up to two years in advance7, but on larger timescales our ability to forecast ENSO behaviour accurately may hinge on how ENSO responds to changes in the background climate system. This idea is supported by studies suggesting that the level of activity could be related to natural or man-made changes in the climate of the tropical Pacific8,9.

In their latest study, Wittenberg et al.1 used the same GFDL-CM2.1 model, this time to forecast epochs of high and low ENSO activity. For each epoch of activity in the model's control run, the authors performed 40 forecasts, each differing by a tiny perturbation of the size of the computer's rounding error to one of the model's numerical grid points. These 'perfect model' forecasts have the best chance of reproducing the extreme ENSO epochs seen in the control run, and permit assessment of the model's intrinsic ability to predict them.

The authors found that, beyond the first two to four years after initialization of the forecasts, the multi-decadal epochs of high and low ENSO activity are completely unpredictable. For each epoch, the model forecasts either active or quiet events with the same probability. That is, the perturbations can alter the forecasts in such a way that the model is capable of forecasting an inactive ENSO decade where it originally simulated a highly active one (Fig. 1a), or an active decade where it simulated a quiet one (Fig. 1b). Figure 1: Decadal forecasts of El Niño–Southern Oscillation activity. Using their GFDL-CM2.1 climate model, Wittenberg et al.1 performed simulations of the variability of the El Niño–Southern Oscillation (ENSO), here quantified using the Niño-3.4 sea surface temperature (SST) index. Two distinct epochs are shown, characterized by high (a) or low (b) ENSO variability in the model's control run (black curves). For each epoch, 3 sets of 40 simulations are initialized from model years 1721, 1731 and 1741, and from 1151, 1161 and 1171, respectively (faint grey curves). Model years do not coincide with historical years. The simulations differ in only one tiny perturbation applied to the model's initial conditions. For both epochs, at least one simulation out of 40 exhibits high (red curves) or low (blue curves) ENSO variability, indicating that the level of activity is unpredictable. (Graphic courtesy of Andrew Wittenberg.) Full size image

This is the 'butterfly effect' of chaos theory10 applied to ENSO events. Seemingly small perturbations to a system, such as the flapping of a butterfly's wings, may lead to large changes in that system. It is a sobering finding, because it suggests that the changes observed in ENSO behaviour during the twentieth century could very well be random fluctuations unrelated to natural or man-made changes in the climate of the tropical Pacific.

Further research is needed to determine whether the study's conclusions can be extrapolated from the model world to the real world. During the past decade, climate models have progressed substantially in their ability to simulate ENSO events. Many models can now emulate the long-term modulation first seen in the GFDL-CM2.1 simulations, possibly owing to the inclusion of improved wind patterns11. But it is not known whether even the best climate models simulate the correct mix of the myriad processes that influence ENSO. One cause of uncertainty might be that the decadal fluctuations in the background climate, which are thought to be the source of ENSO predictability12, are too weak in the models' simulations13. Conversely, models simulate activity that is much stronger than observed6,14, so this too-strong ENSO might be oblivious to the too-weak changes in background climate, resulting in decreased predictability. The realism of the simulations must be improved if model-based conclusions are to be applied to the real world.

Existing observational records are not yet long enough for us to investigate whether, and how, ENSO responds to long-term climate fluctuations that could be sources of predictability. Progress on this front depends on maintaining and expanding our observational capability in the ocean, which relies on arrays of autonomous profiling floats and tropical moorings. In the meantime, results such as those of Wittenberg et al. are reminders of the challenges associated with forecasting ENSO changes. Future attempts to attribute the causes of individual events and their decadal variations now face a much higher bar.

References 1 Wittenberg, A. T., Rosati, A., Delworth, T. L., Vecchi, G. A. & Zeng, F. J. Clim. http://dx.doi.org/10.1175/JCLI-D-13-00577.1 (2014). 2 McGregor, S., Timmermann, A., England, M. H., Timm, O. E. & Wittenberg, A. T. Clim. Past 9, 2269–2284 (2013). 3 Li, J. et al. Nature Clim. Change 1, 114–118 (2011). 4 Emile-Geay, J., Cobb, K. M., Mann, M. E. & Wittenberg, A. T. J. Clim. 26, 2329–2352 (2013). 5 Cobb, K. M. et al. Science 339, 67–70 (2013). 6 Wittenberg, A. T. Geophys. Res. Lett. 36, L12702 (2009). 7 Chen, D., Cane, M. A., Kaplan, A., Zebiak, S. E. & Huang, D. Nature 428, 733–736 (2004). 8 Wang, B. & An, S. Clim. Dyn. 18, 475–486 (2002). 9 DiNezio, P. N. et al. J. Clim. 25, 7399–7420 (2012). 10 Lorenz, E. N. presented at 139th Annu. Meet. AAAS, Boston, Mass. (1972); http://eaps4.mit.edu/research/Lorenz/Butterfly_1972.pdf. 11 Neale, R. B., Richter, J. H. & Jochum, M. J. Clim. 21, 5904–5924 (2008). 12 Kirtman, B. P. & Schopf, P. S. J. Clim. 11, 2804–2822 (1998). 13 Ault, T. R., Deser, C., Newman, M. & Emile-Geay, J. Geophys. Res. Lett. 40, 3450–3456 (2013). 14 Deser, C. et al. J. Clim. 25, 2622–2651 (2012). Download references

Author information Affiliations Pedro DiNezio is in the Department of Oceanography, School of Ocean and Earth Science and Technology, University of Hawaii, Honolulu, Hawaii 96822, USA. Pedro DiNezio Authors Pedro DiNezio View author publications You can also search for this author in PubMed Google Scholar Corresponding author Correspondence to Pedro DiNezio.

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About this article Cite this article DiNezio, P. A high bar for decadal forecasts of El Niño. Nature 507, 437–439 (2014). https://doi.org/10.1038/507437a Download citation Published: 26 March 2014

Issue Date: 27 March 2014

DOI : https://doi.org/10.1038/507437a