Climate models are used for a variety of purposes from the study of dynamics of the weather and climate system to projections of future climate.
NOAA's Geophysical Fluid Dynamics Laboratory has created several ocean-atmosphere coupled models to predict how greenhouse gas emissions following different population, economic, and energy-use projections may affect the planet.
"Representative Concentration Pathways (RCPs) are not new, fully integrated scenarios (i.e., they are not a complete package of socioeconomic, emissions and climate projections). They are consistent sets of projections of only the components of radiative forcing that are meant to serve as input for climate modeling, pattern scaling and atmospheric chemistry modeling," according to the RCP Database.
Global climate models represent the planet as millions of grid boxes and then solve mathematical equations to calculate how energy is transferred between those boxes using the laws of thermodynamics. If done correctly, these models of how energy is cycled through all parts of the planet can be used to estimate dozens of environmental variables (winds, temperature, moisture, etc.). The models are tested by simulating historical conditions and then matching the results to our historical observational records. If the models can adequately recreate the past, they are then run forward in time to predict what may happen in the future.
Shown here are the predicted surface temperatures under the RCP 6.0 emissions scenario using GFDL's CM3 model. The CM3 is just one of many climate models that are analyzed to make predictions about our changing climate. The RCP 6.0 scenario uses a high greenhouse gas emission rate and is a stabilization scenario where total radiative forcing is stabilized after 2100 by employment of a range of technologies and strategies for reducing greenhouse gas emissions. 6.0 W/m2 refers to the radiative forcing reached by 2100.
In this imagery, if temperature is colored red, it is predicted to be higher than the 20th century average; if it is blue, then it is predicted to be lower than average.