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more global analyses. We’ll explore the role that EMICs play in more comprehensive models in the next chapter (when we explore cutting-edge global circulation models and the tools climate scientists employ to create and work with them). For now, though, I would like to end this chapter with a few words about the limitation of the analytic method that undergirds both the creation of EMICs and much of science in general. We’ve seen a number of reasons why this analytic approach is worth preserving, but there are also good reasons to think that it cannot take us as far as we want to go.

4.2.2 Limits of the Analytic Method

It might help to begin by thinking about the traditional scientific paradigm as it has existed from the time of Newton and Galileo. The account that follows is simplified to the point of being apocryphal, but I think it captures the spirit of things well enough. For our purposes here, that’s enough: I’m interested not in giving a detailed historical account of the progress of science (many who are more well-suited to that task have already done a far better job than I ever could), but in pointing to some general themes and assumptions that first began to take root in the scientific revolution. It will be helpful to have these themes clearly in mind, as I think complexity theory is best understood as an approach to science that fills in the gaps left by the approach I’m about to describe. If you are a historian of science, I apologize for the simplifying liberties that I take with this complicated story (see Chapter Zero for more on why you’re probably not alone in being dissatisfied with what I have to say).

The greatest triumph of the scientific revolution was, arguably, the advent of the kind of experimental method that still underlies most science today: the fundamental insight that we

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