Global Climate Models

Climate models are numerical representations of various parts of the Earth’s climate system. There are two ways of looking at this. In some ways, scientists are trying to reduce the complex behaviour of the climate down to a set of mathematical equations, in the hope that they can then begin to understand the processes that are going on. This is true especially of fairly simple models.

For state-of-the-art General Circulation Models/Global Climate Models (GCMs) such as the one used in the experiment, it is more a case of trying to represent everything, even if things then get so complicated that we can’t always understand what’s going on. The equations can then be tweaked so that the model does as well as possible at producing past and current climates (compared to archived observations). If the model accurately reproduces past and current climates it can then be used to try to predict what the climate could do in the future.

GCMs try to simulate as much as possible about the climate system: the incoming and outgoing radiation, the way the air moves, the way clouds form and precipitation falls, the way the ice sheets grow or shrink, etc. They are frequently (as in the model we use) coupled to a representation of the ocean. They may take into account how the vegetation on the Earth’s surface changes. Critically, they try to calculate how all these different parts of the climate system interact, and how the feedback processes work.

Climate models divide the surface of the Earth into a horizontal grid, the atmosphere into vertical levels, and time into discrete timesteps.

Processes that are smaller than the size of one of these cubes, such as cloud formation, are difficult to model and so need to be parameterized.