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Because the number of prognostic variables is limited, many parameters of model output are diagnostic variables. GCMs employ parameterizations that have usually been derived empirically to represent processes that are not directly accounted for in the model but must be represented in the model, such as waves above the Nyquist frequency.
A minimal GCM (also SGCM, for simple general circulation model) consists of a dynamical core[?], for example the primitive equations[?], energy input into the model in the from of radiative cooling, and energy dissipation in the form of scale-dependent friction, so that atmospheric waves[?] with the highest wavenumbers are the ones most strongly attenuated.
A recent trend in GCMs is to extend them to become Earth system models[?], that would include such things as submodels for economic growth and its effect on carbon dioxide emissions.
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