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
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