Perspective

Missing iris effect as a possible cause of muted hydrological change and high climate sensitivity in models

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Abstract

Equilibrium climate sensitivity to a doubling of CO2 falls between 2.0 and 4.6 K in current climate models, and they suggest a weak increase in global mean precipitation. Inferences from the observational record, however, place climate sensitivity near the lower end of this range and indicate that models underestimate some of the changes in the hydrological cycle. These discrepancies raise the possibility that important feedbacks are missing from the models. A controversial hypothesis suggests that the dry and clear regions of the tropical atmosphere expand in a warming climate and thereby allow more infrared radiation to escape to space. This so-called iris effect could constitute a negative feedback that is not included in climate models. We find that inclusion of such an effect in a climate model moves the simulated responses of both temperature and the hydrological cycle to rising atmospheric greenhouse gas concentrations closer to observations. Alternative suggestions for shortcomings of models — such as aerosol cooling, volcanic eruptions or insufficient ocean heat uptake — may explain a slow observed transient warming relative to models, but not the observed enhancement of the hydrological cycle. We propose that, if precipitating convective clouds are more likely to cluster into larger clouds as temperatures rise, this process could constitute a plausible physical mechanism for an iris effect.

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Change history

  • Corrected online 25 February 2016

    In the version of the Perspective originally published, there were errors in the Supplementary Information. After correcting these, the reported correlations between actual climate change feedback and tropical regression in the sentence beginning 'In the analysis of the CMIP5 ensemble presented here...' are +0.38 and +0.32 for the AMIP and historical experiments, respectively. In addition, the subsequent statement now reads: 'Of the eleven models that match CERES net regression in either experiment, four have ECS above 3 K and seven below. When run with a prescribed evolution of sea surface temperatures (AMIP) only the two versions of the Beijing Climate Center (BCC) model match observations in the slope of the regression between net, longwave and shortwave radiation with temperature. If run in coupled mode (historical) only one version of the Goddard Institute for Space Studies (GISS-E2-H) model matches CERES data.' The authors acknowledge David Coppin for pointing out these errors. These errors have been corrected in the online versions of the Perspective.

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Acknowledgements

Contributions from S. Bony, P. Forster, Quiang Fu, A. Gettelman, J. Gregory, I. Held, S. Klein, R. Lindzen, R. Pierrehumbert, S. Po-Chedley, D. Popke, F. Rauser, S. Sherwood and M. Zelinka were valuable in advancing this study. CERES data were obtained from the NASA Langley Research Center, HadCRUT4 data are provided by the Met Office Hadley Centre and the Climatic Research Unit at the University of East Anglia, and CMIP5 data from the coupled modelling groups (Supplementary Table 3) coordinated by the World Climate Research Programme's Working Group on Coupled Modelling. This work was supported by the Max-Planck-Gesellschaft (MPG) and by funding through the EUCLIPSE project from the European Union, Seventh Framework Programme (FP7/2007-2013) under grant agreement no. 244067. Computational resources were made available by Deutsches Klimarechenzentrum (DKRZ) through support from Bundesministerium für Bildung und Forschung (BMBF).

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  1. Max Planck Institute for Meteorology, Bundesstrasse 53, 20146 Hamburg, Germany

    • Thorsten Mauritsen
    •  & Bjorn Stevens

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Correspondence to Thorsten Mauritsen.

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