The certainty of uncertainty

A paper on climate sensitivity today in Science will no doubt see a great deal of press in the next few weeks. In “Why is climate sensitivity so unpredictable?”, Gerard Roe and Marcia Baker explore the origin of the range of climate sensitivities typically cited in the literature. In particular they seek to explain the characteristic shape of the distribution of estimated climate sensitivities. This distribution includes a long tail towards values much higher than the standard 2-4.5 degrees C change in temperature (for a doubling of CO2) commonly referred to.

In essence, what Roe and Baker show is that this characteristic shape arises from the non-linear relationship between the strength of climate feedbacks (f) and the resulting temperature response (deltaT), which is proportional to 1/(1-f). They show that this places a strong constraint on our ability to determine a specific “true” value of climate sensitivity, S. These results could well be taken to suggest that climate sensitivity is so uncertain as to be effectively unknowable. This would be quite wrong.

The IPCC Summary For Policymakers shows the graph below for a business-as-usual carbon emissions scenario, comparing temperatures in the 1980s with temperatures in the 2020s (orange) and 2090s (red). The latter period is roughly when CO2 will have doubled under this scenario. The resulting global temperature changes cluster between 2 and 5 degrees C, but with a non-zero probability of a small negative temperature change and long tail suggesting somewhat higher probabilities of a very high temperature change (up to 8 degrees is shown).

We have very strong evidence for the middle range of climate sensitivities cited by the IPCC. But what Roe and Baker emphasize is that ruling out very high sensitivites is very difficult because even the relatively small feedbacks, if they are highly uncertain, can have a very large impact on our ability to determine S.

Paleoclimate data do provide a means to constrain the tail on the distribution and perhaps to show the likelihood of large values of S is lower than Roe and Baker’s calculations suggest. In particular, Annan and Hargreaves (2006) used a Bayesian statistical approach that combines information from both 20th century observations and from last glacial maximum data to produce an estimate of climate sensitivity that is much better constrained than by either set of observations alone (see our post on this, here). Their result is a mean value of deltaT close to 3ºC, and a high probability that the sensitivity is less than 4.5ºC, for a doubling of CO2 above pre-industrial levels. Thus, we emphasize that Roe and Baker’s result do not really tell us that, for example, 11°C of global warming in the next century entury is any likelier than we have suggested previously.

On the other hand, there is a counterpoint to such a comforting result. Roe and Baker note that the extreme warmth of the Eocene — something that has stymied climate modelers — could in principle be explained by not-very-dramatic changes in the strengths of the feedbacks, again because small changes in f can produce dramatic change in S. The boundary conditions for Eocene climate remain too poorly known to include in a formal calculation of climate sensitivity, but at the very least the extreme climate of this time suggests that we cannot readily cut the tail off the probability distribution of S.

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