Journal article

Review of the global models used within phase 1 of the Chemistry-Climate Model Initiative (CCMI)

Olaf Morgenstern, Michaela I Hegglin, Eugene Rozanov, Fiona M O'Connor, N Luke Abraham, Hideharu Akiyoshi, Alexander T Archibald, Slimane Bekki, Neal Butchart, Martyn P Chipperfield, Makoto Deushi, Sandip S Dhomse, Rolando R Garcia, Steven C Hardiman, Larry W Horowitz, Patrick Joeckel, Beatrice Josse, Douglas Kinnison, Meiyun Lin, Eva Mancini Show all

Geoscientific Model Development | COPERNICUS GESELLSCHAFT MBH | Published : 2017

Abstract

We present an overview of state-of-the-art chemistry–climate and chemistry transport models that are used within phase 1 of the Chemistry–Climate Model Initiative (CCMI-1). The CCMI aims to conduct a detailed evaluation of participating models using process-oriented diagnostics derived from observations in order to gain confidence in the models' projections of the stratospheric ozone layer, tropospheric composition, air quality, where applicable global climate change, and the interactions between them. Interpretation of these diagnostics requires detailed knowledge of the radiative, chemical, dynamical, and physical processes incorporated in the models. Also an understanding of the degree to..

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University of Melbourne Researchers

Grants

Awarded by Royal Society Marsden Fund


Awarded by Swiss National Science Foundation


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


Awarded by UK DECC/Defra Met Office Hadley Centre Climate Programme


Awarded by European Project


Awarded by Horizon European Union's Framework Programme for Research and Innovation CRESCENDO project


Awarded by Australian Government's Australian Antarctic science grant program


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


Awarded by Commonwealth Department of the Environment


Awarded by National computational infrastructure INCMAS project


Awarded by Natural Environment Research Council


Funding Acknowledgements

We thank the Centre for Environmental Data Analysis (CEDA) for hosting the CCMI data archive. This work has been supported by NIWA as part of its government-funded, core research. Olaf Morgenstern acknowledges support from the Royal Society Marsden Fund, grant 12-NIW-006, and under the Deep South National Science Challenge.. 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). 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) of the Ministry of the Environment, Japan, and computations were performed on NEC-SX9/A(ECO) computers at the CGER, NIES. Wuhu Feng (NCAS) provided support for the TOMCAT simulations. Neal Butchart, Steven C. Hardiman, and Fiona M. O'Connor and the development of HadGEM3-ES were supported by the Joint UK DECC/Defra Met Office Hadley Centre Climate Programme (GA01101). Neal Butchart and Steven C. Hardiman also acknowledge additional support from the European Project 603557-STRATOCLIM under the FP7-ENV.2013.6.1-2 programme. Fiona M. O'Connor acknowledges additional support from the Horizon 2020 European Union's Framework Programme for Research and Innovation CRESCENDO project under grant agreement no. 641816. Slimane Bekki acknowledges support from the European Project 603557-STRATOCLIM under the FP7-ENV. 2013.6.1-2 programme and from the Centre National d'Etudes Spatiales (CNES, France) within the SOLSPEC project. Kane Stone and Robyn Schofield acknowledge funding from the Australian Government's Australian Antarctic science grant program (FoRCES 4012), the Australian Research Council's Centre of Excellence for Climate System Science (CE110001028), the Commonwealth Department of the Environment (grant 2011/16853), and computational support from National computational infrastructure INCMAS project q90. The CNRM-CM chemistry-climate people acknowledge the support from Meteo-France, CNRS, and CERFACS, and in particular the work of the entire team in charge of the CNRM/CERFACS climate model.