3rd Role Play: Sceptical scientists

The third role play confronted all participants with the question of the usefulness of climate models specifically for climate mitigation and adaptation policies. It was fun to observe all groups sticking to their prescribed role rather consequently, which led to a sometimes heated but never superficial debate.

During the lecture of the week before it was argued that ‘all models are wrong, but some are useful’ as Box (1976) put it. This was the stance taken by the pro-modelling scientists, who argued that simplifications are a necessary and crucial part of a model. Their main arguments went along three lines. Firstly, climate models are based on established physical laws, which I personally however regard as nothing particularly noteworthy but rather a minimum requirement. Secondly, model intercomparison would show that models from different research centres yield relatively similar results so that there must be a true core to their findings. Finally, the capabilities of models to simulate both current climate and past climate change would act as proof that models are indeed a good representation of the climate system. While this is true, we have to distinguish carefully between explanatory and predictive purpose, meaning that one cannot necessarily extrapolate models into the future based on past fit.

Talking about adequacy of purpose as explained by Parker (2009), it is clear that for our discussion the purpose was to inform policymakers. In our opinion for the role of scientists sceptical to modelling, the problem regarding this purpose lies much more in the socio-economic than in the natural sciences sphere. I want to stress that none of us questioned the unanimous link between CO2 emissions and global temperature increase, but are somewhat critical to projections about future economic growth as well as technology and efficiency improvement. Unfortunately, Integrated Assessment Models (IAMs) on which the IPCC reports are strongly based, rest on a set of assumptions which frequently have not much empirical data to draw upon. Simple parameters like discount and growth rates as well as unknown damage functions have a tremendous influence on policy recommendations but are hard to pin down as they are largely normative in the end. Within the debate we therefore argued that climate policy does not need to be based on uncertain model outcomes but rather that past observations of climate change impacts are enough to justify immediate action. However and contrary to this position stated in the discussion, I do believe that using IAMs is more valuable than simply trusting on our ‘gut feeling’ as it was termed by the Green party, who argued very much in favour of using climate models for policymaking.

The point where I had the feeling that our critique came to nothing was the lack of better alternatives. It is always easy to criticise a model for being inaccurate in the details and providing a false impression of scientific certainty, while coming up with a more practical alternative is a much harder task. This type of learning process within the discussion was not greatly altered by support from the ‘ÖDP’ party, who supported our modelling-critical position simply by arguing for more localised climate policies that rather address regional environmental pollutions, while seeing global emission reductions only as a convenient side effect. I had the impression that this lacks the global perspective required for all problems in the overall climate change nexus.

To conclude, using climate and integrated assessment models for policy purposes might be far from perfect but it does at least provide us with a point of reference – even if uncertain socio-economic developments are included. We only have to be cautious for the illusory perception of knowledge that models may trigger. For this purpose it is crucial to always clearly state a model’s limitations and underlying assumptions with regard to uncertain future developments.