Uncertainties in the parameterizations used in climate models contribute to uncertainty in the climate predictions. To investigate the sensitivity of the model to these uncertainties, scientists carry out ensemble simulations in which they run multiple model simulations are run. For an ensemble experiment, the different model simulations vary only in the detail of the parameterizations used. For example, if a model parameterization makes use of a parameter, X, but the exact value of this parameter is yet to be fully determined, multiple model simulations are run, each with a slightly different value of X. In this way, scientists can explore the sensitivity of the model to this parameter, which helps them to assess the uncertainties involved. Ensemble simulations help scientists estimate the model error and highlight key uncertainties that have a large effect on the model results (areas that can then be targeted in future research).
The largest ensemble climate model experiment run to date is that of www.climateprediction.net, in which members of the public are encouraged to run different versions of a climate model on their home computers. Ensemble simulations can only be carried out with relatively fast-running climate models (those with lower resolution or a low degree of coupling between different components) as multiple simulations must be run.
SEE ALSO: Climate Models; Historical Development of Climate Models; Technology; Validation of Climate Models.
BIBLIOGRApHY. A. Henderson-Sellers and K. McGuffie, A Climate Modeling Primer (John Wiley & Sons, 2005); S. Solomon, et al., eds., Climate Change 2007: The Physical Science Basis, Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (Cambridge University Press, 2007); W.M. Washington and C.L. Parkinson, An Introduction to Three-Dimensional Climate Modeling (University Science Books, 2005).
IKirsty Pringle University of Leeds
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