Abstract
Depletion of stratospheric ozone in the Southern Hemisphere (SH) during the late twentieth century cooled local air temperature, which resulted in stronger stratospheric westerly winds near 60° S and altered SH surface climate. However, Antarctic ozone has been recovering since around 2001 thanks to the implementation of the Montreal Protocol, which banned production and consumption of ozone-depleting substances. Here we show that the post-2001 increase in ozone has resulted in significant changes to trends in SH temperature and circulation. The trends are generally of opposite sign to those that resulted from stratospheric ozone losses, including a warming of the SH polar lower stratosphere and a weakening of the SH stratospheric polar vortex. Observed post-2001 trends of temperature and circulation in the stratosphere are about 50–75% smaller in magnitude than the trends during the ozone depletion era. The response is broadly consistent with expectations based on modelled depletion-era trends and variability of both ozone and reactive chlorine. The differences in observed stratospheric trends between the recovery and depletion periods are statistically significant (P < 0.05), providing evidence for the emergence of dynamical impacts of the healing of the Antarctic ozone hole.
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Data availability
TOMS/OMI ozone data are available from https://ozoneaq.gsfc.nasa.gov/. ERA5 data are available from https://cds.climate.copernicus.eu/cdsapp#!/search?text=ERA5. MERRA2 data are available from https://disc.gsfc.nasa.gov/datasets?keywords=%22MERRA-2%22&page=1&source=Models%2FAnalyses%20MERRA-2. JRA55 data are available from https://rda.ucar.edu/datasets/ds628.1/. Model output from the ten-member ensembles used in the analysis presented here is available at https://doi.org/10.7910/DVN/YGWVSB. WACCM–CCMI and WACCM–CMIP6 model output are available from https://www.earthsystemgrid.org.
Code availability
Computer code is available from the corresponding author upon reasonable request.
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Acknowledgements
Helpful discussion and comments by D. Kim are gratefully acknowledged. B.Z. and S.S. were supported by grants from the National Science Foundation NSF 1539972 and 1848863, and a gift to MIT from an anonymous donor. D.W.J.T. is supported by NSF AGS-1848785. Q.F. is supported by NSF AGS‐1821437. We would like to acknowledge high-performance computing support from Cheyenne (https://doi.org/10.5065/D6RX99HX) provided by NCAR’s Computational and Information Systems Laboratory, sponsored by the National Science Foundation.
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B.Z. and S.S. designed the study. B.Z., S.S., D.W.J.T. and Q.F. analysed and interpreted the results. B.Z. led the writing, and all authors contributed to the editing of the manuscript and approved the final version.
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Extended data
Extended Data Fig. 1 Trends and trend differences for different turnaround years.
Ozone and circulation trends for ozone depletion era (filled circles), ozone recovery era (open circles), and their differences (squares) for turnaround year defined as (a–d) 1999, (e–h) 2000, (i–l) 2001, and (m–p) 2002. Vertical lines indicate the 95% confidence intervals on the trends.
Extended Data Fig. 2 GHG contribution to WACCM geopotential height trends.
WACCM ensemble mean geopotential height trends (m/decade) for 2001–2018 for (a) ODS+GHG, (b) GHG-only, and (c) the difference (approximately the ODS-only response).
Extended Data Fig. 3 ODS-forced trends.
As Fig. 6, but for ODS+GHG minus GHG-only.
Extended Data Fig. 4. WACCM-CMIP6 trend differences.
WACCM-CMIP6 November-December Southern Hemisphere trend differences between 1979–2001 and 2001-2018 in ozone, temperature, and geopotential height. Hatching indicates regions where the trend differences are not significantly different from the distributions of trend differences in the control run (p > 0.05; Methods).
Extended Data Fig. 5 WACCM CCMI and CMIP6 temperature trends.
SH ND WACCM ensemble mean zonal-mean temperature trends for CCMI (a, c) and CMIP6 (b, d) for the ozone depletion (a, b) and recovery (c, d) periods. Hatching indicates regions where the trend differences are not significantly different from the distributions of trend differences in the control runs (p > 0.05; Methods).
Extended Data Fig. 6
WACCM-CCMI temperature trends. SH ND zonal-mean temperature trends for the WACCM-CCMI ensemble mean calculated using (a,d) linear regression, equation 1, (b,e) equation 2 using scaled differences over 10 year periods, and (c,f) the difference for the periods (a–c) 1975–2001 and (d–f) 2001–2018 using the two methods.
Extended Data Fig. 8 Trend differences arising from trend calculation methods: the role of ensemble size.
SH ND zonal-mean temperature trend shown in each panel is the difference between using the linear trend (for example, as in Extended Data Fig. 6a) and differencing the climatologies (for example, as in Extended Data Fig. 6b) for the average of 1 ≤ n ≤ 9 ensemble members (the difference for n = 10 is shown in Extended Data Fig. 6c).
Extended Data Fig. 9 JRA55 temperature trends.
SH ND zonal-mean temperature linear trends for JRA55 for (a) 1975–2001, (b) 1979–2001, and (c) the difference.
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Zambri, B., Solomon, S., Thompson, D.W.J. et al. Emergence of Southern Hemisphere stratospheric circulation changes in response to ozone recovery. Nat. Geosci. 14, 638–644 (2021). https://doi.org/10.1038/s41561-021-00803-3
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DOI: https://doi.org/10.1038/s41561-021-00803-3
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