were found to fit the past data and hence deemed appropriate for extrapolation into the future. Such crude methods may be used for some of the processes, even in a full GCM, while research goes on to develop a better parameterization, based on an improved understanding of the detailed physics. The need for three-dimensional and time-dependent representations, especially when tackling the forecasting problem, is perhaps the largest single reason why advanced climate models are so complicated and expensive to design and run.
Simple models give some insight into the principal processes at work, and allow us to begin to account for recently observed small changes and of predicting major changes in the future. They also show, quite convincingly, that the basic physics implies non-trivial changes in mean surface temperature and/or global cloud cover in response to a doubling of the atmospheric CO2 concentration or other significant changes in greenhouse gas concentration. Finally, they illustrate the principles and main features of the feedback processes that make the final outcome of any global change scenario so uncertain.
What simple models cannot do is to give us a reliable quantitative prediction of the likely changes the Earth will experience in response to the expected ongoing increases in greenhouse forcing. For that we require much more sophisticated models, with dynamical schemes based on coupled ocean-atmosphere and a realistic treatment of radiative transfer.
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