Journal article

Evaluating the Relationship between Interannual Variations in the Antarctic Ozone Hole and Southern Hemisphere Surface Climate in Chemistry-Climate Models

Zoe E Gillett, Julie M Arblaster, Andrea J Dittus, Makoto Deushi, Patrick Joeckel, Douglas E Kinnison, Olaf Morgenstern, David A Plummer, Laura E Revell, Eugene Rozanov, Robyn Schofield, Andrea Stenke, Kane A Stone, Simone Tilmes

Journal of Climate | AMER METEOROLOGICAL SOC | Published : 2019

Abstract

Studies have recently reported statistically significant relationships between observed year-to-year spring Antarctic ozone variability and the Southern Hemisphere annular mode and surface temperatures in spring–summer. This study investigates whether current chemistry–climate models (CCMs) can capture these relationships, in particular, the connection between November total column ozone (TCO) and Australian summer surface temperatures, where years with anomalously high TCO over the Antarctic polar cap tend to be followed by warmer summers. The interannual ozone–temperature teleconnection is examined over the historical period in the observations and simulations from the Whole Atmosphere Com..

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University of Melbourne Researchers

Grants

Awarded by Grains Research and Development Corporation


Awarded by Regional and Global Climate Modeling Program (RGCM) of the U.S. Department of Energy's Office of Biological and Environmental Research (BER)


Awarded by Australian Research Council (ARC) Centre of Excellence for Climate Extremes


Awarded by ARC Centre of Excellence for Climate System Science


Awarded by U.K. Natural Environment Research Council (NERC) Project SMURPHS


Awarded by Swiss National Science Foundation


Awarded by Australian Government's National Computational Merit Allocation Scheme


Awarded by Australian Antarctic science grant program


Funding Acknowledgements

Zoe Gillett was funded by the Grains Research and Development Corporation (UHS11005). Portions of this study were supported by the Regional and Global Climate Modeling Program (RGCM) of the U.S. Department of Energy's Office of Biological and Environmental Research (BER) Cooperative Agreement DE-FC02-97ER62402 and the National Science Foundation (NSF) as well as the Australian Research Council (ARC) Centre of Excellence for Climate Extremes (CE170100023). Andrea Dittus acknowledges support from the ARC Centre of Excellence for Climate System Science (CE110001028) and the U.K. Natural Environment Research Council (NERC) Project SMURPHS (NE/N006054/1). This research was undertaken with the assistance of resources and services from the National Computational Infrastructure, which is supported by the Australian Government. The National Center for Atmospheric Research (NCAR) Command Language (NCL) was used for data analysis and visualization. We acknowledge the modelling groups for making their simulations available for this analysis, the joint WCRP SPARC/IGAC Chemistry-Climate Model Initiative (CCMI) for organizing and coordinating the model data analysis activity, and the British Atmospheric Data Centre (BADC) for collecting and archiving the CCMI model output. We acknowledge high-performance computational support for the WACCM simulations from Yellowstone (ark:/85065/d7wd3xhc) provided by the Climate Simulation Laboratory at NCAR's Computational and Information Systems Laboratory, sponsored by NSF and other agencies. NCAR is funded by NSF. The EMAC 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 Modelling). Laura Revell acknowledges partial support from the Deep South National Science Challenge (Contract C01X1412) and China Southern. Eugene Rozanov acknowledges partial support from the Swiss National Science Foundation under Grants 200021 169241 (VEC) and 200020 182239 (POLE) and the gained information will be used to improve the CCM SOCOL. Robyn Schofield and Kane Stone acknowledge support from the ARC 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). We also acknowledge Bodeker Scientific, supported through the Deep South National Science Challenge, for providing the combined total column ozone database. We thank Dan Marsh for useful discussions during the course of this study, and three anonymous reviewers whose comments helped to significantly improve the manuscript.