Climate Dynamics

, Volume 23, Issue 3–4, pp 327–339 | Cite as

A method for obtaining pre-twentieth century initial conditions for use in climate change studies

  • R. J. StoufferEmail author
  • A. J. Weaver
  • M. Eby


A method is proposed to initialise coupled atmosphere-ocean general circulation models (AOGCMs) developed to study climate change on multi-century time scales. The method assumes that current generation AOGCMs are developed and evaluated using present-day radiative forcing and near present day oceanic initial conditions. To find pre-twentieth century initial conditions, we propose that the radiative forcing be run backwards in time from the present to the desired starting date. The model should then be run for 3–5 centuries with the radiative forcing held constant at the desired date. In our tests, instantaneously switching to pre-twentieth century radiative forcing did not save computational time. When a sufficiently stable pre-twentieth century condition is achieved, the coupled system can be integrated forward to the present and into the future. This method is a first step toward the standardization of AOGCM initialization and suggests a framework for AOGCM initialization for the first time. It provides an internally consistent set of pre-twentieth century initial conditions, although they will vary from model to model. Furthermore, it is likely that this method will yield a fairly realistic present-day climate in transient climate change experiments of the twentieth century, if the model biases are not too large. The main disadvantage of the method is that it is fairly computationally expensive in that it requires an additional 4–6 centuries of model integration before starting historical twentieth century integrations. However, the relative cost of this technique diminishes as more simulations are conducted using the oceanic initial condition obtained using our method.


Radiative Condition Last Glacial Maximum Control Integration Flux Adjustment Cold Start Problem 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



We are indebted to our colleagues in the WCRP WGCM, and especially Larry Gates, and John Mitchell, for many stimulating discussions over many WCRP WGCM meetings, which ultimately lead to the writing of this manuscript. We are also indebted to K. Dixon, T. Delworth, J Meehl and J Gregory for their many thoughtful comments on this work. AJW is also grateful for funding support from the NSERC/CFCAS CLIVAR Program and for release time and funding provided by the Killam Foundation and the Canada Research Chair programs.


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Copyright information

© Springer-Verlag  2004

Authors and Affiliations

  1. 1.Geophysical Fluid Dynamics LaboratoryPrincetonUSA
  2. 2.School of Earth and Ocean Sciences University of VictoriaVictoriaCanada

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