Page:Lawhead columbia 0054D 12326.pdf/222

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in most cases CGCMs aren’t even initialized with parameter values drawn from observation of the real climate’s state at the start of the model’s run. Rather, GCMs are allowed to “spin up” to a state that’s qualitatively identical to the state of the global climate at the beginning of the model’s predictive run. Why add this extra layer of complication to the modeling process, rather than just initializing the model with observed values? The spin up approach has a number of advantages; in addition to freeing climate modelers from the impossible task of empirically determining the values of all the parameters needed to run the model, the spin up also serves as a kind of rough test of the proposed dynamics of the model before it’s employed for prediction and ensures that parameter values are tailored for the grid-scale of the individual model.

A typical spin up procedure looks like this. The grid size is defined, and the equations of motion for the atmospheric, oceanic, terrestrial, and cryonic models are input. In essence, this defines a “dark Earth” with land, sky, and water but no exogenous climate forcings. The climate modelers then input relevant insolation parameters--they flip on the sun. This (unsurprisingly) causes a cascade of changes in the previously dark Earth. The model is allowed to run for (in general) a few hundred thousand years of “model time” until it settles down into a relatively stable equilibrium with temperatures, cloud cover, and air circulation patterns that resemble the real climate’s state at the start of the time period under investigation. The fact that the model does settle into such a state is at least a prima facie proof that it’s gotten things relatively right; if the model settled toward a state that looked very little like the state of interest (if it converged on a “snowball Earth” covered in glaciers, for instance), we would take it as evidence that something was very wrong indeed. Once the model has converged on this equilibrium state, modelers can feed in hypothetical parameters and observe the impact. They can change the

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