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Volume 18, issue 2 | Copyright

Special issue: Chemistry–Climate Modelling Initiative (CCMI) (ACP/AMT/ESSD/GMD...

Atmos. Chem. Phys., 18, 1091-1114, 2018
https://doi.org/10.5194/acp-18-1091-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 29 Jan 2018

Research article | 29 Jan 2018

Ozone sensitivity to varying greenhouse gases and ozone-depleting substances in CCMI-1 simulations

Olaf Morgenstern1, Kane A. Stone2,3,a, Robyn Schofield2,3, Hideharu Akiyoshi4, Yousuke Yamashita4,b, Douglas E. Kinnison5, Rolando R. Garcia5, Kengo Sudo6, David A. Plummer7, John Scinocca8, Luke D. Oman9, Michael E. Manyin9,10, Guang Zeng1, Eugene Rozanov11,12, Andrea Stenke12, Laura E. Revell12,13, Giovanni Pitari14, Eva Mancini14,15, Glauco Di Genova15, Daniele Visioni14,15, Sandip S. Dhomse16, and Martyn P. Chipperfield16 Olaf Morgenstern et al.
  • 1National Institute of Water and Atmospheric Research (NIWA), Wellington, New Zealand
  • 2School of Earth Sciences, University of Melbourne, Victoria, Australia
  • 3ARC Centre of Excellence in Climate System Science, University of New South Wales, Sydney, Australia
  • 4National Institute of Environmental Studies (NIES), Tsukuba, Japan
  • 5National Center for Atmospheric Research (NCAR), Boulder, Colorado, USA
  • 6Graduate School of Environmental Studies, Nagoya University, Nagoya, Japan
  • 7Environment and Climate Change Canada, Montréal, Canada
  • 8CCCMA, University of Victoria, Victoria, Canada
  • 9NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
  • 10Science Systems and Applications, Inc., Lanham, Maryland, USA
  • 11Physikalisch-Meteorologisches Observatorium Davos – World Radiation Center, Davos, Switzerland
  • 12Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
  • 13Bodeker Scientific, Christchurch, New Zealand
  • 14Dipartimento di Scienze Fisiche e Chimiche, Università dell'Aquila, L'Aquila, Italy
  • 15CETEMPS, Università dell'Aquila, L'Aquila, Italy
  • 16School of Earth and Environment, University of Leeds, Leeds, UK
  • anow at: Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts, USA
  • bnow at: Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Yokohama, Japan

Abstract. Ozone fields simulated for the first phase of the Chemistry-Climate Model Initiative (CCMI-1) will be used as forcing data in the 6th Coupled Model Intercomparison Project. Here we assess, using reference and sensitivity simulations produced for CCMI-1, the suitability of CCMI-1 model results for this process, investigating the degree of consistency amongst models regarding their responses to variations in individual forcings. We consider the influences of methane, nitrous oxide, a combination of chlorinated or brominated ozone-depleting substances, and a combination of carbon dioxide and other greenhouse gases. We find varying degrees of consistency in the models' responses in ozone to these individual forcings, including some considerable disagreement. In particular, the response of total-column ozone to these forcings is less consistent across the multi-model ensemble than profile comparisons. We analyse how stratospheric age of air, a commonly used diagnostic of stratospheric transport, responds to the forcings. For this diagnostic we find some salient differences in model behaviour, which may explain some of the findings for ozone. The findings imply that the ozone fields derived from CCMI-1 are subject to considerable uncertainties regarding the impacts of these anthropogenic forcings. We offer some thoughts on how to best approach the problem of generating a consensus ozone database from a multi-model ensemble such as CCMI-1.

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We assess how ozone as simulated by a group of chemistry–climate models responds to variations in man-made climate gases and ozone-depleting substances. We find some agreement, particularly in the middle and upper stratosphere, but also considerable disagreement elsewhere. Such disagreement affects the reliability of future ozone projections based on these models, and also constitutes a source of uncertainty in climate projections using prescribed ozone derived from these simulations.
We assess how ozone as simulated by a group of chemistry–climate models responds to variations...
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