General Circulation Models in Environmental Science

General circulation models (GCM) are used to evaluate past, present, and future climatic phenomena. Climate consists of a region's prevailing weather. Variations in climate are primarily determined by the combined influences of the atmosphere, the continents, and the oceans. Such effects can both foster and hinder human activities. Consequently, considerable effort has been devoted to climate modeling.

In recent years, GCMs have been the primary tool used for climate simulation. These numerical representations describe climatic change in three-dimensions. The models involve numerous data inputs. In addition, they also require various approximations and prognostic equations. This information is typically analyzed by computer.

General circulation models have found various practical applications. Nonetheless, individual GCMs are only as accurate as the assumptions used to create them. Few current models are able to realistically simulate observed climates. Moreover, GCMs' coarse resolution precludes their use in small-scale weather prediction. Despite such limitations though, GCMs have proven useful in environmental science. In particular, the models have provided some valuable insights into possible negative consequences of increased atmospheric CO2 concentrations. By raising public concern over such pollution, GCMs may be able to minimize its eventual impact.

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ind stress and by air-sea fluxes of heat and fresh water. In addition, they can also include various other model parameters such as an eddy-mixing coefficient. Unfortunately, these inputs are not well-known. Hydrographic (e.g., temperature and salinity) data--as well as other oceanographic data--can actually only be used for model validation. This is typically performed through qualitative comparison of the data with a given model's results (Tziperman et al., 1992, p. 1434). Yet another problematic aspect of general circulation models involves feedback mechanisms. Such feedbacks typically occur between the atmosphere, the oceans, and the cryosphere. When GCMs are run with specified distributions of various forcings (i.e., sea surface temperature), accurate climatic projections depend on the accurate representation of feedbacks. In order to solve this dilemma, certain oceanic GCMs include such phenomena as sea ice and snow cover (Giorgi & Mearns, 1991, pp. 191-213). In addition, researchers have devised coupled atmospheric-ocean models (Garratt, 1993, pp. 419-433). Although coupled GCMs have been used for some time, current models typically employ realistic ocean GCMs (Grotch & MacCracken, 1991, pp. 286-302). These mode
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Approximate Pages = 18 (250 words per page)

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