An overview of results from the Coupled Model Intercomparison Project
The Coupled Model Intercomparison Project (CMIP) collects output from global coupled ocean–atmosphere general circulation models (coupled GCMs). Among other uses, such models are employed both to detect anthropogenic effects in the climate record of the past century and to project future climatic ch...
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Veröffentlicht in: | Global and planetary change 2003-06, Vol.37 (1), p.103-133 |
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Zusammenfassung: | The Coupled Model Intercomparison Project (CMIP) collects output from global coupled ocean–atmosphere general circulation models (coupled GCMs). Among other uses, such models are employed both to detect anthropogenic effects in the climate record of the past century and to project future climatic changes due to human production of greenhouse gases and aerosols. CMIP has archived output from both constant forcing (“control run”) and perturbed (1% per year increasing atmospheric carbon dioxide) simulations. This report summarizes results form 18 CMIP models. A third of the models refrain from employing ad hoc flux adjustments at the ocean–atmosphere interface. The new generation of non-flux-adjusted control runs are nearly as stable as—and agree with observations nearly as well as—the flux-adjusted models. Both flux-adjusted and non-flux-adjusted models simulate an overall level of natural internal climate variability that is within the bounds set by observations. These developments represent significant progress in the state of the art of climate modeling since the Second (1995) Scientific Assessment Report of the Intergovernmental Panel on Climate Change (IPCC; see Gates et al. [Gates, W.L., et al., 1996. Climate models—Evaluation. Climate Climate 1995: The Science of Climate Change, Houghton, J.T., et al. (Eds.), Cambridge Univ. Press, pp. 229–284]). In the increasing-CO
2 runs, differences between different models, while substantial, are not as great as one might expect from earlier assessments that relied on equilibrium climate sensitivity. |
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ISSN: | 0921-8181 1872-6364 |
DOI: | 10.1016/S0921-8181(02)00193-5 |