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Predicting the Course of Climate Change Over the Next Decade
Latif, M. and Keenlyside, N.S. 2011. A perspective on decadal climate variability and predictability. Deep-Sea Research II 58: 1880-1894.

"Climate variability," in the words of the authors, "can be either generated internally by interactions within or between the individual climate subcomponents (e.g., atmosphere, ocean and sea ice) or externally by e.g., volcanic eruptions, variations in the solar insolation at the top of the atmosphere, or changed atmospheric greenhouse gas concentrations in response to anthropogenic emissions." Some examples of these internal variations are "the North Atlantic Oscillation (NAO), the El Niño/Southern Oscillation (ENSO), the Pacific Decadal Variability (PDV), and the Atlantic Multidecadal Variability (AMV)," all of which "project on global or hemispheric surface air temperature (SAT), thereby masking anthropogenic climate change."

What was done
In a review of this extremely complex subject, Latif and Keenlyside -- who hold positions at Germany's Leibniz-Institute for Meerewissenschaften at the University of Kiel -- first describe various mechanisms that are responsible for internal variability, giving special attention to the variability of the Atlantic Meridional Overturning Circulation (AMOC), which they suggest is likely the origin of a considerable part of the decadal variability within the Atlantic Sector, after which they discuss the challenge of decadal SAT predictability and various factors limiting its realization.

What was learned
The two researchers list numerous problems that hamper decadal climate predictability, among which is the fact that "the models suffer from large biases." In the cases of annual mean sea surface temperature (SST) and SAT over land, for example, they state that "typical errors can amount up to 10°C in certain regions," as found by Randall et al. (2007) to be the case for many of the IPCC-AR4 models. And they add that several models also "fail to simulate a realistic El Niño/Southern Oscillation." In addition, they indicate that "several assumptions have generally to be made about the process under consideration that cannot be rigorously justified, and this is a major source of uncertainty."

Another problem they discus is the fact that "some components of the climate system are not well represented or not at all part of standard climate models," one example being the models' neglect of the stratosphere. This omission is quite serious, since Latif and Keenlyside say that "recent studies indicate that the mid-latitudinal response to both tropical and extra-tropical SST anomalies over the North Atlantic Sector may critically depend on stratospheric feedbacks," noting that Ineson and Scaife (2009) present evidence for "an active stratospheric role in the transition to cold conditions in northern Europe and mild conditions in southern Europe in late winter during El Niño years."

An additional common model shortcoming, even in stand-alone integrations with models forced by observed SSTs, is that model simulations of rainfall in the Sahel "fail to reproduce the correct magnitude of the decadal precipitation anomalies." Still another failure is the fact, as shown by Stroeve et al. (2007), that "virtually all climate models considerably underestimate the observed Arctic sea ice decline during the recent decades in the so-called 20th century integrations with prescribed (known natural and anthropogenic) observed forcing." And added to these problems is the fact that "atmospheric chemistry and aerosol processes are still not well incorporated into current climate models."

What it means
In summing up their findings, which include those noted above and a whole lot more, Latif and Keenlyside state that "a sufficient understanding of the mechanisms of decadal-to-multidecadal variability is lacking," that "state-of-the-art climate models suffer from large biases," that "they are incomplete and do not incorporate potentially important physics," that various mechanisms "differ strongly from model to model," that "the poor observational database does not allow a distinction between 'realistic' and 'unrealistic' simulations," and that many models "still fail to simulate a realistic El Niño/Southern Oscillation." Therefore, they conclude that "it cannot be assumed that current climate models are well suited to realize the full decadal predictability potential," which is a somewhat-obscure but kinder-and-gentler way of stating that current state-of-the-art climate models are simply not good enough to make reasonably accurate simulations of climate change over a period of time (either in the past or the future) that is measured in mere decades.

Ineson, S. and Scaife, A.A. 2009. The role of the stratosphere in the European climate response to El Niño. Nature Geoscience 2: 32-36.

Randall, D.A. and Wood, R.A. et al. 2007. Chapter 8: Climate Models and Their Evaluation. In: Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, United Kingdom.

Stroeve, J., Holland, M.M., Meier, W., Scambos, T. and Serreze, M. 2007. Arctic sea ice decline: faster than forecast. Geophysical Research Letters 34: 10.1029/2007GL029703.

Reviewed 26 October 2011