From Wikipedia, the free encyclopedia

Parameterization in a climate model refers to the method of replacing processes that are too small-scale or complex to be physically represented in the model by a simplified process. This can be contrasted with other processes—e.g., large-scale flow of the atmosphere—that are explicitly resolved within the models.

Associated with these parameterizations are various parameters used in the simplified processes. Examples include the descent rate of raindrops, convective clouds, simplifications of the atmospheric radiative transfer on the basis of atmospheric radiative transfer codes, and cloud microphysics.

A typical climate model gridbox has sides of about 100-300 km. A typical cumulus cloud has a scale of less than a kilometer, and would require a grid even finer than this to be represented physically by the equations of fluid motion. Therefore the processes that such clouds represent are parameterized, by processes of various sophistication. In the earliest models, if a column of air in a model gridbox was unstable (ie, the bottom warmer than the top) then it would be overturned, and the air in that vertical column mixed. More sophisticated schemes add enhancements, recognizing that only some portions of the box might convect and that entrainment and other processes occur.

By contrast, the formation of large-scale (stratus-type) clouds is more physically based, they form when the relative humidity reaches some prescribed value. But again, sub grid scale processes need to be taken into account. Rather than assuming that clouds form at 100% relative humidity (in a real atmospheric air parcel, small supersaturations are required for cloud formation, i.e. relative humidities must be slightly greater than 100%, depending on the available CCN) the cloud fraction can be related to a "rh_crit" [1] (typically 95%), reflecting the sub grid scale variation that would occur in the real world.

The climateprediction.net project [2] attempted to estimate the sensitivity of the climate sensitivity of a version of HadCM3 (actually HadSM3) by varying various chosen parameters, such as vf1 (the ice fall speed through clouds), cw_land, cw_sea (this relates how much water there is in a cloud to when it starts raining), z0fsea (the roughness length of the sea surface), r_layers (related to the number and size of plant roots in the soil – and, consequently, to how water is taken up from the soil and into the atmosphere by plant transpiration). A fuller list is at [3].

This would include things like the freezing point of water, direct radiative effect of CO₂ and other items that are well constrained by lab experiments.

• Global climate model
• Climate Ensemble