GENERAL CIRCULATION MODELS of the atmosphere are computer-driven mathematical models that aim to represent the numerous actions within the atmosphere of the entire world and its interactions with the surface of the Earth. Initially intended to improve understanding of the movements of the atmosphere, with a view to predicting weather phenomena and preparing for adverse weather, circulation models have since provided further understanding of the impact of atmospheric warming and its implications for all forms of life on the Earth.
The atmosphere is an extraordinarily complex system—or set of systems—and modeling its actions is far beyond the ability of any single human brain. Indeed, its complexity is such that it even defeats the intuitive nature of the brain because second, third, and higher-order effects are, if not unimaginable, then at least incalculable. However, appreciating that level of sophistication and complexity was not possible until the expanded observations of the atmosphere that resulted from World War II.
These new observations opened the eyes of scientists to global interactions. Previously, only partial models, based on geographical regions, had been attempted. They also helped to demonstrate that processes such as cloud formation and other forms of meteorological physics were much more complex than had previously been imagined. Indeed, understanding the turbulent behavior of gases and liquids remains one of the most complex problems in modern mundane physics. For example, the influence of tropical and trade wind systems had not been fully integrated into worldwide models, while the circulation of the oceans has still not been comprehensively audited at all depths.
Attempts to create a model by experimental means, through, for example, heating gases around a spherical object, were crude approximations at best because of the lack of subtlety in defining the specific characteristics of the earth compared to a simple, homogeneous sphere. More success has been reached by identifying a series of simpler, lower-level equations and the ways in which they interact with each other from the bottom up have been more successful than approaches from the top down.
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