Comprehensive global climate models1 are the only tools that account for the complex set of processes which will determine future climate change at both a global and regional level. Planners are typically faced with a wide range of predicted changes from different models of unknown relative quality2,3, owing to large but unquantified uncertainties in the modelling process4. Here we report a systematic attempt to determine the range of climate changes consistent with these uncertainties, based on a 53-member ensemble of model versions constructed by varying model parameters. We estimate a probability density function for the sensitivity of climate to a doubling of atmospheric carbon dioxide levels, and obtain a 5–95 per cent probability range of 2.4–5.4 °C. Our probability density function is constrained by objective estimates of the relative reliability of different model versions, the choice of model parameters that are varied and their uncertainty ranges, specified on the basis of expert advice. Our ensemble produces a range of regional changes much wider than indicated by traditional methods based on scaling the response patterns of an individual simulation5,6.
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We thank A. Thorpe and M. Allen for encouraging the development of this project. We also acknowledge many Hadley Centre colleagues for their advice on model parameters and their uncertainty ranges, and for comments on earlier versions of the manuscript. This work was supported by the UK Department of the Environment, Food and Rural Affairs. D.A.S. was funded by the NERC COAPEC thematic programme.
The authors declare that they have no competing financial interests.
Contains supporting detail of the GCM ensemble integrations including the parameters perturbations implemented. We also document in more detail the Climate Prediction Index, the methodology used to contruct pdfs of climate sensitivity and tests of the impact of biases in sea surface temperature. (DOC 248 kb)
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Murphy, J., Sexton, D., Barnett, D. et al. Quantification of modelling uncertainties in a large ensemble of climate change simulations. Nature 430, 768–772 (2004). https://doi.org/10.1038/nature02771
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