%0 Journal Article %1 Stainforth2005Uncertainty %A Stainforth, D. A. %A Aina, T. %A Christensen, C. %A Collins, M. %A Faull, N. %A Frame, D. J. %A Kettleborough, J. A. %A Knight, S. %A Martin, A. %A Murphy, J. M. %A Piani, C. %A Sexton, D. %A Smith, L. A. %A Spicer, R. A. %A Thorpe, A. J. %A Allen, M. R. %D 2005 %I Nature Publishing Group %J Nature %K llr %N 7024 %P 403--406 %R 10.1038/nature03301 %T Uncertainty in predictions of the climate response to rising levels of greenhouse gases %U http://dx.doi.org/10.1038/nature03301 %V 433 %X 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.

@article{Stainforth2005Uncertainty, 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.}, added-at = {2019-08-14T18:35:35.000+0200}, author = {Stainforth, D. A. and Aina, T. and Christensen, C. and Collins, M. and Faull, N. and Frame, D. J. and Kettleborough, J. A. and Knight, S. and Martin, A. and Murphy, J. M. and Piani, C. and Sexton, D. and Smith, L. A. and Spicer, R. A. and Thorpe, A. J. and Allen, M. R.}, biburl = {https://www.bibsonomy.org/bibtex/2b46c848ba6c3cf92fbf33f63af06c327/karinawilliams}, citeulike-article-id = {84173}, citeulike-linkout-0 = {http://dx.doi.org/10.1038/nature03301}, citeulike-linkout-1 = {http://dx.doi.org/10.1038/nature03301}, comment = {(private-note)Cited by mcSweeney et al as "an approach pioneered in the UK by the Hadley centre (murphy el al 2004) and climateprediction.net (Stainforth et al 2005) has been the use of ensembles which systematically explore the use of ensembles whih systematically explore the implication of known uncertainties in model parameters."}, day = 27, doi = {10.1038/nature03301}, interhash = {e38508571f95bd575310c413cf92d62d}, intrahash = {b46c848ba6c3cf92fbf33f63af06c327}, issn = {0028-0836}, journal = {Nature}, keywords = {llr}, month = jan, number = 7024, pages = {403--406}, posted-at = {2012-01-08 13:24:31}, priority = {2}, publisher = {Nature Publishing Group}, timestamp = {2019-08-14T18:35:35.000+0200}, title = {Uncertainty in predictions of the climate response to rising levels of greenhouse gases}, url = {http://dx.doi.org/10.1038/nature03301}, volume = 433, year = 2005 }