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A large ozone-circulation feedback and its implications for global warming assessments

Nature Climate Change volume 5, pages 41–45 (2015)Cite this article

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Abstract

State-of-the-art climate models now include more climate processes simulated at higher spatial resolution than ever1. Nevertheless, some processes, such as atmospheric chemical feedbacks, are still computationally expensive and are often ignored in climate simulations1,2. Here we present evidence that the representation of stratospheric ozone in climate models can have a first-order impact on estimates of effective climate sensitivity. Using a comprehensive atmosphere–ocean chemistry–climate model, we find an increase in global mean surface warming of around 1 °C (~20%) after 75 years when ozone is prescribed at pre-industrial levels compared with when it is allowed to evolve self-consistently in response to an abrupt 4×CO2 forcing. The difference is primarily attributed to changes in long-wave radiative feedbacks associated with circulation-driven decreases in tropical lower stratospheric ozone and related stratospheric water vapour and cirrus cloud changes. This has important implications for global model intercomparison studies1,2 in which participating models often use simplified treatments of atmospheric composition changes that are consistent with neither the specified greenhouse gas forcing scenario nor the associated atmospheric circulation feedbacks3,4,5.

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Figure 1: Temporal evolution of the annual and global mean surface temperature anomalies.
Figure 2: Gregory regression plots.
Figure 3: Annual and zonal mean differences in ozone and temperature.
Figure 4: Cirrus cloud changes.

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Acknowledgements

We thank the European Research Council for funding through the ACCI project, project number 267760. The model development was part of the QUEST-ESM project supported by the UK Natural Environment Research Council (NERC) under contract numbers RH/H10/19 and R8/H12/124. We acknowledge use of the MONSooN system, a collaborative facility supplied under the Joint Weather and Climate Research Programme, which is a strategic partnership between the UK Met Office and NERC. A.C.M. acknowledges support from an AXA Postdoctoral Research Fellowship. For plotting, we used Matplotlib, a 2D graphics environment for the Python programming language developed by J. D. Hunter. We are grateful for advice of P. Telford during the model development stage of this project and thank the UKCA team at the UK Met Office for help and support.

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Author notes

  1. Peter Braesicke & Manoj M. Joshi

    Present address: Present addresses: Karlsruhe Institute of Technology, IMK-ASF, 76344 Eggenstein-Leopoldshafen, Germany (P.B.); Centre for Ocean and Atmospheric Sciences, University of East Anglia, Norwich NR4 7TJ, UK (M.M.J.).,

Authors and Affiliations

  1. Department of Chemistry, Centre for Atmospheric Science, University of Cambridge, Cambridge CB2 1EW, UK

    Peer J. Nowack, N. Luke Abraham, Amanda C. Maycock, Peter Braesicke & John A. Pyle

  2. National Centre for Atmospheric Science, UK

    N. Luke Abraham, Amanda C. Maycock, Peter Braesicke, Jonathan M. Gregory, Manoj M. Joshi, Annette Osprey & John A. Pyle

  3. Department of Meteorology, University of Reading, Reading RG6 6BB, UK

    Jonathan M. Gregory, Manoj M. Joshi & Annette Osprey

  4. Met Office Hadley Centre, Met Office, Exeter EX1 3PB, UK

    Jonathan M. Gregory

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Contributions

P.J.N. conducted the research on a day-to-day basis; the model was developed by N.L.A., J.M.G., M.M.J. and A.O.; N.L.A. and P.B. designed the initial experiment and its subsequent evolution; major analysis and interpretation of results was performed by P.J.N. and A.C.M.; P.J.N. led the paper writing, supported by A.C.M.; N.L.A., P.B. and J.A.P. all contributed to the discussion and interpretation of results and write-up; J.A.P. suggested the study.

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Correspondence to Peer J. Nowack.

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Nowack, P., Luke Abraham, N., Maycock, A. et al. A large ozone-circulation feedback and its implications for global warming assessments. Nature Clim Change 5, 41–45 (2015). https://doi.org/10.1038/nclimate2451

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