Climate Dynamics

, Volume 35, Issue 7–8, pp 1257–1287 | Cite as

Emulating AOGCM results using simple climate models

  • Dirk OliviéEmail author
  • Nicola Stuber


Three simple climate models (SCMs) are calibrated using simulations from atmosphere ocean general circulation models (AOGCMs). In addition to using two conventional SCMs, results from a third simpler model developed specifically for this study are obtained. An easy to implement and comprehensive iterative procedure is applied that optimises the SCM emulation of global-mean surface temperature and total ocean heat content, and, if available in the SCM, of surface temperature over land, over the ocean and in both hemispheres, and of the global-mean ocean temperature profile. The method gives best-fit estimates as well as uncertainty intervals for the different SCM parameters. For the calibration, AOGCM simulations with two different types of forcing scenarios are used: pulse forcing simulations performed with 2 AOGCMs and gradually changing forcing simulations from 15 AOGCMs obtained within the framework of the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. The method is found to work well. For all possible combinations of SCMs and AOGCMs the emulation of AOGCM results could be improved. The obtained SCM parameters depend both on the AOGCM data and the type of forcing scenario. SCMs with a poor representation of the atmosphere thermal inertia are better able to emulate AOGCM results from gradually changing forcing than from pulse forcing simulations. Correct simultaneous emulation of both atmospheric temperatures and the ocean temperature profile by the SCMs strongly depends on the representation of the temperature gradient between the atmosphere and the mixed layer. Introducing climate sensitivities that are dependent on the forcing mechanism in the SCMs allows the emulation of AOGCM responses to carbon dioxide and solar insolation forcings equally well. Also, some SCM parameters are found to be very insensitive to the fitting, and the reduction of their uncertainty through the fitting procedure is only marginal, while other parameters change considerably. The very simple SCM is found to reproduce the AOGCM results as well as the other two comparably more sophisticated SCMs.


Simple climate models Energy balance models Pulse response Inverse modelling 



We thank Jan Fuglestvedt and Ragnhild Bieltvedt Skeie for the use of their SCM and many helpful discussions, and David Salas-Mélia for his help with the CNRM-CM3 simulations. We also thank Keith Shine for advice, fruitful discussions and valuable comments on draft versions of this paper. We acknowledge the modelling groups, the Programme for Climate Model Diagnosis and Intercomparison (PCMDI) and the WCRP’s Working Group on Coupled Modelling (WGCM) for their roles in making available the WCRP CMIP3 multi-model dataset. Support of this dataset is provided by the Office of Science, US Department of Energy. This work was supported by the European Union FP6 Integrated Project QUANTIFY ( under contract no. 003893 (GOCE).


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Copyright information

© Springer-Verlag 2010

Authors and Affiliations

  1. 1.Centre National de Recherches MétéorologiquesToulouseFrance
  2. 2.Department of MeteorologyUniversity of ReadingReadingUK

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