Journal article

Large-scale tropospheric transport in the Chemistry-Climate Model Initiative (CCMI) simulations

Clara Orbe, Huang Yang, Darryn W Waugh, Guang Zeng, Olaf Morgenstern, Douglas E Kinnison, Jean-Francois Lamarque, Simone Tilmes, David A Plummer, John F Scinocca, Beatrice Josse, Virginie Marecal, Patrick Joeckel, Luke D Oman, Susan E Strahan, Makoto Deushi, Taichu Y Tanaka, Kohei Yoshida, Hideharu Akiyoshi, Yousuke Yamashita Show all

ATMOSPHERIC CHEMISTRY AND PHYSICS | COPERNICUS GESELLSCHAFT MBH | Published : 2018

Abstract

Understanding and modeling the large-scale transport of trace gases and aerosols is important for interpreting past (and projecting future) changes in atmospheric composition. Here we show that there are large differences in the global-scale atmospheric transport properties among the models participating in the IGAC SPARC Chemistry–Climate Model Initiative (CCMI). Specifically, we find up to 40% differences in the transport timescales connecting the Northern Hemisphere (NH) midlatitude surface to the Arctic and to Southern Hemisphere high latitudes, where the mean age ranges between 1.7 and 2.6 years. We show that these differences are related to large differences in vertical transport among..

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University of Melbourne Researchers

Grants

Awarded by Environment Research and Technology Development Fund of the Environmental Restoration and Conservation Agency, Japan


Awarded by New Zealand Royal Society Marsden Fund


Awarded by NSF


Awarded by NASA


Awarded by Swiss National Science Foundation


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


Funding Acknowledgements

We thank the Centre for Environmental Data Analysis (CEDA) for hosting the CCMI data archive. We acknowledge the modeling 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. In addition, Clara Orbe and Luke D. Oman want to acknowledge the high-performance computing resources provided by the NASA Center for Climate Simulation (NCCS) and support from the NASA Modeling, Analysis and Prediction (MAP) program. Hideharu Akiyoshi acknowledges the Environment Research and Technology Development Fund of the Environmental Restoration and Conservation Agency, Japan (2-1709) and NECSX9/A(ECO) computers at CGER, NIES. Olaf Morgenstern and Guang Zeng acknowledge the UK Met Office for use of the MetUM. Their research was supported by the NZ government's Strategic Science Investment Fund (SSIF) through the NIWA program CACV. Olaf Morgenstern 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). Olaf Morgenstern and Guang Zeng also wish to acknowledge the contribution of the 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 and Employment's Research Infrastructure program (https://www.nesi.org.nz). Darryn W. Waugh acknowledges support from NSF grant AGS-1403676 and NASA grant NNX14AP58G. The EMAC model simulations have been performed at the German Climate Computing Centre (DKRZ) through support from the Bundesministerium fur Bildung und Forschung (BMBF). DKRZ and its scientific steering committee are gratefully acknowledged for providing the HPC and data archiving resources for the consortial project ESCiMo (Earth System Chemistry integrated Modeling). Eugene Rozanov and Timofei Sukhodolov acknowledge support from the Swiss National Science Foundation under grant 200021169241 (VEC). Robyn Schofield and Kane A. Stone acknowledge support from the Australian Research Council's Centre of Excellence for Climate System Science (CE110001028), the Australian government's National Computational Merit Allocation Scheme (q90) and the Australian Antarctic science grant program (FoRCES 4012).