The alternative climate consensus – surprises are quite likely

Climate and climate models are coupled, nonlinear, chaotic systems. (1)  In the case of models it leads to non-unique solutions because of sensitive dependence and structural instability. The first is the dependence of the solution on imprecisely known climate parameters.  Plausible differences in values – shown as initial condition uncertainty in the schematic below – cause solutions to diverge exponentially with time.  The second relates to the depth and breadth of coupled processes in the model.  Changing coupling produces divergent solutions.  “Sensitive dependence and structural instability are humbling twin properties for chaotic dynamical systems, indicating limits about which kinds of questions are theoretically answerable.” (2)  There are multiple feasible solutions to any model that diverge with time – climate is not predictable using models.  Probabilities can, however, theoretically be assigned to the range of plausible solutions. (3)(4)  This has been known since Lorenz discovered chaos in the 1960’s. (5)


Source: Slingo and Palmer 2011

In climate it leads to abrupt shifts in state.  Locally as much as 10oC in as little as a decade and by a factor of two in hydrology. (6) Moy et al (2002) (7) present a record of sedimentation which is strongly influenced by ENSO variability. It is based on the presence of more or less red sediment in a South American lake core. More sedimentation is associated with El Niño. The proxy has continuous high resolution coverage over 11,000 years. It shows periods of high and low El Niño activity with a period of about 2,000 years. There was an abrupt shift some 5,000 years ago from La Niña dominance to El Niño dominance that is associated with the drying of the Sahel. There is a period around 3,500 years ago of high ENSO activity associated with the demise of the Minoan civilisation. Red intensity during the Minoan decline was above 200 – for comparison it was 99 during the largest 2oth century El Niño in 1997/98.

Anastasios Tsonis, of the Atmospheric Sciences Group at University of Wisconsin, Milwaukee, and colleagues used a mathematical network approach to analyse abrupt climate change on decadal timescales. Ocean and atmospheric indices – in this case the El Niño Southern Oscillation, the Pacific Decadal Oscillation, the North Atlantic Oscillation and the North Pacific Oscillation – can be thought of as chaotic oscillators that capture the major modes of climate variability. It is a way of analysing dynamic systems. It was found that they would synchronise at certain times and then shift into a new state at 20 to 30 year intervals in the 20th century.  Climate shifts around 1910, 1944/1945, 1976/1977 and 1998/2001. (8)(9)

It is no coincidence that shifts in ocean and atmospheric indices occur at the same time as changes in the trajectory of global surface temperature. Our ‘interest is to understand – first the natural variability of climate – and then take it from there. So we were very excited when we realized a lot of changes in the past century from warmer to cooler and then back to warmer were all natural,’ Tsonis said.

Michael Ghil, Distinguished Research Professor, Dept. of Atmospheric and Oceanic Sciences, UCLA, defined three climate hypotheses.  Equilibrium, periodic and chaotic.  These are purely illustrative.  The dominant scientific paradigm – the consensus if you like – is that climate is a coupled, non-linear, chaotic system.


Source:  Michael Ghil

Most people, however, implicitly assume a stable equilibrium and a gradual warming of the atmosphere.  In this paradigm – all climate change results from calculable forcing and inferable feedbacks.  More recently – there has been much more emphasis on periodic change.  A generally warmer state around which climate continues to wobble in predictable oscillations.  The reality is abrupt shifts in climate states that are unpredictable and more or less extreme – at 20 to 30 year intervals.

We have very little idea of how to predict the speed and extent of future climate shifts – or of the mechanics of triggers.   We can think of it as changes in the components of the climate system – cloud, ice, dust, biology, hydrology and atmospheric and ocean circulation.  Change in solar intensity – and theoretically anthropogenic changes in greenhouse gases, aerosols and land use change – pushes the system past a threshold at which stage changes in one element cause changes in another in a cascade of effects.  Ultimately the system stabilizes in a new balance of wind, cloud, currents, ice and biology.  Climate is a kaleidoscope – shake it up and a new pattern emerges.  Climate may well hold surprises – on either hot or colds ends of the spectrum – that are well outside the bounds of a steadily increasing global temperature. (10)

  1. IPCC, 2001: Climate Change 2001: The Scientific Basis. Contribution of Working Group I to the Third Assessment Report of the Intergovernmental Panel on Climate Change [Houghton, J.T., Y. Ding, D.J. Griggs, M. Noguer, P.J. van der Linden, X. Dai, K. Maskell, and C.A. Johnson (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 881pp.
  2. McWilliams, J. C. (2007). Irreducible imprecision in atmospheric and oceanic simulations.Proceedings of the National Academy of Sciences, 104(21), 8709-8713
  3. Slingo, J., & Palmer, T. (2011). Uncertainty in weather and climate prediction.Philosophical Transactions of the Royal Society of London A: Mathematical, Physical and Engineering Sciences,369(1956), 4751-4767.
  4. Palmer, T. N. (2012), Towards the probabilistic Earth-system simulator: a vision for the future of climate and weather prediction. Q.J.R. Meteorol. Soc., 138: 841–861. doi: 10.1002/qj.1923
  5. Lorenz E. N. (1969), The predictability of a flow which possesses many scales of motion, Tellus 21:19.
  6. National Research Council (U.S.), Committee on Abrupt Climate Change, 2002: Abrupt climate change: inevitable surprises, NAP, ISBN 0-309-07434-7. B
  7. Christopher M. Moy, Geoffrey O. Seltzer, Donald T. Rodbell, and David M. Anderson, (2002), Variability of El Niño/Southern Oscillation activity at millennial timescales during the Holocene epoch, Nature, 420, 162 – 165 (2002); doi:10.1038/nature01194
  8. Tsonis, A. A., Swanson, and S. Kravtsov (2007), A new dynamical mechanism for major climate shifts, Geophys. Res. Lett., 34, L13705, doi:10.1029/2007GL030288
  9. Swanson, K. L., and A. Tsonis (2009), Has the climate recently shifted? Geophys. Res. Lett., 36, L06711, doi:10.1029/2008GL037022.
  10. Kyle L. Swanson, George Sugihara, and Anastasios A. Tsonis (2009) Long-term natural variability and 20th century climate change, PNAS 2009 106 (38) 16120-16123; published ahead of print September 14, 2009,doi:10.1073/pnas.0908699106
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