Chapter 3: Climate Science as ‘Post-normal’ Science
There is no more common error than to assume that, because prolonged and accurate mathematical calculations have been made, the application of the result to some fact of nature is absolutely certain. Alfred North Whitehead Climate change is an area of science where models inevitably play an important role. There is little scope, of course, for laboratory science, or experiments to be conducted with the earth’s climate – although that was the motivation of some early climate scientists who saw, during the Cold War, the possibility of altering climate and adversely aﬀecting agricultural production in the Soviet Union. Climate models are constructed using historical data and then tested against the same data, before being used to make predictions or projections about the future. Climate scientist Stephen Schneider (2001, p. 341) has suggested that the use of historical situations is ‘essential to test the tools used to make future estimates’, and he calls this a ‘systems version of “falsiﬁcation” ’, which is central to the conduct of science, but argues that there are ‘no precise analogues to the time-evolving what-if questions of global change disturbances’. So climate change science relies upon the operation of General Circulation Models (GCMs), which depend upon the availability of supercomputers to simulate the operation of the climate system. These are very expensive to develop and run, and as a consequence there are only a dozen or so full-scale models globally, and these are by no means independent of each other, borrowing code from each other...
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