But what is the question
Politicians say we should invest in helping vulnerable people adapt to climate change. But how should we spend the money?
According to two UK researchers we can best help people in the developing world by funding climate modelers in the rich world:
The British Prime Minister Gordon Brown recently proposed establishing a fund of $100 billion, contributed by the wealthiest nations, to help the most vulnerable countries adapt to climate change. . . Wisely planning how the funds generated by the Prime Minister's recent proposal should be invested therefore needs good scientific guidance. In our view, this can be best achieved by climate models providing highly accurate localised predictions. As a result of the significant scientific effort to date, aided by public concern, models simulating climate change have gained considerable skill. . . There will be many scientific and technical challenges along the way, but the hope is that simulations of the global environment will be able to maximise the number of people around the world who can adapt to, and be protected from the worst impacts of, global warming.
Here is a different perspective:
Excerpted from: Dessai, S., Hulme, M., Lempert, R., and R. Pielke, Jr., 2009. Climate prediction: a limit to adaptation?, Chapter 5 in, Adapting to Climate Change: Thresholds, Values, Governance, W. N. Adger, I. Lorenzoni and K.L. O'Brien (eds.), Cambridge University Press, Cambridge, pp. 64-78.
Given the deep uncertainties involved in climate prediction (and even more so in the prediction of climate impacts) and given that climate is usually only one factor in decisions aimed at climate adaptation, we conclude that the ‘predict and provide’ approach to science in support of climate change adaptation is significantly flawed. Other areas of public policy have come up with similar conclusions (for example, earthquake risk, national security, public health). We therefore argue that the epistemological limits to climate prediction should not be interpreted as a limit to adaptation, despite the widespread belief that it is. By avoiding an approach that places climate prediction (and consequent risk assessment) at its heart, successful adaptation strategies can be developed in the face of this deep uncertainty. We suggest that decision-makers systematically examine the performance of their adaptation strategies/policies/activities over a wide range of plausible futures driven by uncertainty about the future state of climate and many other economic, political and cultural factors. They should choose a strategy that they find sufficiently robust across these alternative futures. Such an approach can identify successful adaptation strategies without accurate and precise predictions of future climate.
These findings have significant implications for science policies as well. At a time when government expects decisions to be based on the best possible science (evidence-based policy-making), we have shown that the science of climate prediction is unlikely to fulfil the expectations of decision-makers . Overprecise climate predictions can potentially lead to bad decisions if misinterpreted or used incorrectly. From a science policy perspective it is worth reflecting on where science funding agencies should focus their efforts if one of the goals is to maximize the societal benefit of science in society. The recent World Modelling Summit for Climate Prediction called for a substantial increase in computing power (an increase by a factor of 1000) in order to provide better information at the local level. We believe, however, that society will benefit much more from a greater understanding of the vulnerability of climate-influenced decisions to large irreducible uncertainties than in seeking to increase the accuracy and precision of the next generation of climate models .