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Uncertainty in predictions of the climate response to rising levels of greenhouse gases

Abstract

The range of possibilities for future climate evolution1,2,3 needs to be taken into account when planning climate change mitigation and adaptation strategies. This requires ensembles of multi-decadal simulations to assess both chaotic climate variability and model response uncertainty4,5,6,7,8,9. Statistical estimates of model response uncertainty, based on observations of recent climate change10,11,12,13, admit climate sensitivities—defined as the equilibrium response of global mean temperature to doubling levels of atmospheric carbon dioxide—substantially greater than 5 K. But such strong responses are not used in ranges for future climate change14 because they have not been seen in general circulation models. Here we present results from the ‘climateprediction.net’ experiment, the first multi-thousand-member grand ensemble of simulations using a general circulation model and thereby explicitly resolving regional details15,16,17,18,19,20,21. We find model versions as realistic as other state-of-the-art climate models but with climate sensitivities ranging from less than 2 K to more than 11 K. Models with such extreme sensitivities are critical for the study of the full range of possible responses of the climate system to rising greenhouse gas levels, and for assessing the risks associated with specific targets for stabilizing these levels.

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Figure 1: Frequency distributions of Tg (colours indicate density of trajectories per 0.1 K interval) through the three phases of the simulation.
Figure 2: The response to parameter perturbations.
Figure 3: The temperature (left panels) and precipitation (right panels) anomaly fields in response to doubling the CO2 concentrations.

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Acknowledgements

We thank all participants in the ‘climateprediction.net’ experiment and the many individuals who have given their time to make the project a reality and a success. This work was supported by the Natural Environment Research Council's COAPEC, e-Science and fellowship programmes, the UK Department of Trade and Industry, the UK Department of the Environment, Food and Rural Affairs, and the US National Oceanic and Atmospheric Administration. We also thank Tessella Support Services plc, Research Systems Inc., Numerical Algorithms Group Ltd, Risk Management Solutions Inc. and the CMIP II modelling groups.

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Correspondence to D. A. Stainforth.

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Supplementary information

Supplementary Discussion

Discussion of the PC based model and how the control climates of different model versions compare with observations. Also, discussion of the mechanism which can lead to unphysical cooling in a model with a mixed layer ocean. Finally, some comments on the sensitivity of results to the choice of perturbations. (DOC 30 kb)

Supplementary Figure Legends

Legends for the supplementary figures. (DOC 24 kb)

Supplementary Figure 1

Comparison of annual mean temperature and precipitation fields with observations for: i) the super computer version of HadSM3, ii) the unperturbed climateprediction.net model version, iii) a low sensitivity model version, and iv) a high sensitivity model version. (PDF 444 kb)

Supplementary Figure 2

The difference in annual mean surface temperature between control and calibration phases for a stable and an unstable simulation; the latter exhibiting the cooling problem described in the supplementary discussion. (PDF 110 kb)

Supplementary Figure 3

Temperature and temperature anomaly fields from a simulation exhibiting the cooling problem in the double CO2 phase. (PDF 132 kb)

Supplementary Figure 4

Further exploration of the sensitivity of the simulated climate sensitivity distribution to the choice of parameter perturbations. (PDF 14 kb)

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Stainforth, D., Aina, T., Christensen, C. et al. Uncertainty in predictions of the climate response to rising levels of greenhouse gases. Nature 433, 403–406 (2005). https://doi.org/10.1038/nature03301

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