Quantification of modelling uncertainties in a large ensemble of climate change simulations

James M. Murphy (), David M. H. Sexton, David N. Barnett, Gareth S. Jones, Mark J. Webb, Matthew Collins and David A. Stainforth
Additional contact information
James M. Murphy: Hadley Centre for Climate Prediction and Research, Met Office
David M. H. Sexton: Hadley Centre for Climate Prediction and Research, Met Office
David N. Barnett: Hadley Centre for Climate Prediction and Research, Met Office
Gareth S. Jones: Hadley Centre for Climate Prediction and Research, Met Office
Mark J. Webb: Hadley Centre for Climate Prediction and Research, Met Office
Matthew Collins: Hadley Centre for Climate Prediction and Research, Met Office
David A. Stainforth: University of Oxford

Nature, 2004, vol. 430, issue 7001, 768-772

Abstract: Abstract 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.

Date: 2004
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DOI: 10.1038/nature02771

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