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foundation. Their observation that EMICs should not be viewed as “poor cousins” of more elaborate models[1] similarly seems to support the view that we should resist the impulse to try to decide which models are “more real” than others. Any model which succeeds in capturing a real pattern in the time-evolution of the world (and which is of consequent predictive use) should be given equal standing.

The sense of “complexity” here also has more than a little in common with the notion we’ve been working with so far. McGuffie & Henderson-Sellers chose to illustrate the climate model hierarchy as a pyramid for good reason; while they say that the “vertical axis [is] not intended to be qualitative,[2]” the pyramidal shape is intended to illustrate the eventual convergence of the four different modeling considerations they give in a single comprehensive model. A complex model in this sense, then, is one which incorporates patterns describing dynamics, radiative processes, surface processes, and chemical processes. The parallels to dynamical complexity should be relatively clear here: a system that is highly dynamically complex will admit of a variety of different modeling perspectives (in virtue of exhibiting a plethora of different patterns). For some predictive purposes, the system can be treated as a simpler system, facilitating the identification of (real) patterns that might be obfuscated when the system is considered as a whole. I have repeatedly argued that this practice of simplification is a methodological approach that should not be underappreciated (and which is not overridden by the addition of complexity theory to mainstream science). EMIC are fantastic case-study in this fact, a diverse mixture of idealizations and simplifications of various stripes that have been developed to explore particular climate subsystems, but whose outputs frequently are of use in


  1. We shall discuss these more elaborate models in detail in the next chapter.
  2. Ibid., p. 51

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