Journal article

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

Olaf Morgenstern, Kane A Stone, Robyn Schofield, Hideharu Akiyoshi, Yousuke Yamashita, Douglas E Kinnison, Rolando R Garcia, Kengo Sudo, David A Plummer, John Scinocca, Luke D Oman, Michael E Manyin, Guang Zeng, Eugene Rozanov, Andrea Stenke, Laura E Revell, Giovanni Pitari, Eva Mancini, Glauco Di Genova, Daniele Visioni Show all

Atmospheric Chemistry and Physics | Copernicus Publications | Published : 2018

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 thes..

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University of Melbourne Researchers

Grants

Awarded by New Zealand Royal Society Marsden Fund


Awarded by Australian Research Council's Centre of Excellence for Climate System Science


Awarded by Australian Government's National Computational Merit Allocation Scheme


Awarded by Australian Antarctic science grant program


Awarded by Swiss National Science Foundation


Awarded by Environment Research and Technology Development Fund of the Ministry of the Environment, Japan


Funding Acknowledgements

We thank the Centre for Environmental Data Analysis (CEDA) for hosting the CCMI-1 data archive. We acknowledge the modelling groups for making their simulations available for this analysis, and the joint WCRP SPARC/IGAC Chemistry-Climate Model Initiative (CCMI) for organizing and coordinating this model data analysis activity. We acknowledge the UK Met Office for use of the MetUM. This research was supported by the NZ Government's Strategic Science Investment Fund (SSIF) through the NIWA programme CACV. Olaf Morgen-stern acknowledges funding by the New Zealand Royal Society Marsden Fund (grant 12-NIW-006) and by the Deep South National Science Challenge (http://www.deepsouthchallenge.co.nz). The authors wish to acknowledge the contribution of NeSI high-performance computing facilities to the results of this research. New Zealand's national facilities are provided by the New Zealand eScience Infrastructure (NeSI) and funded jointly by NeSI's collaborator institutions and through the Ministry of Business, Innovation & Employment's Research Infrastructure programme (https://www.nesi.org.nz). ACCESS-CCM runs were supported by Australian Research Council's Centre of Excellence for Climate System Science (CE110001028), the Australian Government's National Computational Merit Allocation Scheme (q90) and Australian Antarctic science grant program (FoRCES 4012). WACCM is a component of NCAR's Community Earth System Model (CESM), which is supported by the National Science Foundation (NSF). Computing resources (ark:/85065/d7wd3xhc) were provided by the Climate Simulation Laboratory at NCAR's Computational and Information Systems Laboratory, sponsored by the National Science Foundation and other agencies. The SOCOL team acknowledges support from the Swiss National Science Foundation under grant agreement CRSII2_147659 (FUPSOL II). CCSRNIES's research was supported by the Environment Research and Technology Development Fund (2-1303 and 2-1709) of the Ministry of the Environment, Japan, and computations were performed on NEC-SX9/A(ECO) and NEC SX-ACE computers at the CGER, NIES.