Global climate models (GCMs) use mathematical equations to describe the behavior of factors of the Earth system that impact climate. These factors include dynamics of the atmosphere, oceans, land surface, living things, and ice, plus energy from the Sun. Sophisticated climate models are increasingly able to include details such as clouds, rainfall, evaporation, and sea ice. Thousands of climate researchers use global climate models to better understand the long-term effects of global changes such as increasing greenhouses gases or decreasing Arctic sea ice. The models are used to simulate conditions over hundreds of years, so that we can predict how our planet's climate will likely change.
"Resolution" is an important concept in many types of modeling, including climate modeling. Spatial resolution specifies how large (in degrees of latitude and longitude or in km or miles) the grid cells in a model are.
Although we know that traits like temperature vary continuously over the surface of the Earth, calculating such properties for the entire globe is beyond the reach of even the fastest supercomputers. Instead, a climate model places "virtual weather stations" at intervals around the modeled Earth and reports the calculated properties at each station. Models use grids of "cells" to establish the locations of the "virtual weather stations." A typical climate model might have grid cells with a size of about 100 km (62 miles) on a side. The "virtual weather stations" are located at the corners of the grid cells.
Models can be generated with higher or lower resolutions. The grid cells could be reduced in size to 50 km. This would mean that more cells cover Earth's surface, increasing spatial resolution. Or the grid cells could be enlarged to 200 km. This would mean fewer grid cells and decreased spatial resolution. More, smaller cells increases the amount of computing time because there are more "virtual weather stations" at which atmospheric variables must be calculated. Higher resolution models provide much more detailed information, but take lots more computing time. As a general rule, increasing the resolution of a model by a factor of two means about ten times as much computing power will be needed (or that the model will take ten times as long to run on the same computer).
Model grids for atmospheric (including climate) models are three dimensional, extending upward through our atmosphere. Early climate models typically had about 10 layers vertically; more recent ones often have about 30 layers. Because the atmosphere is so thin compared to the vast size of our planet, vertical layers are much closer together as compared to the horizontal dimensions of grid cells. Vertical layers might be spaced at 11 km intervals as compared to the 100 km intervals for horizontal spacing.