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Springtime arctic ozone depletion forces northern hemisphere climate anomalies

Nature Geoscience volume 15, pages 541–547 (2022)Cite this article

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Abstract

Large-scale chemical depletion of ozone due to anthropogenic emissions occurs over Antarctica as well as, to a lesser degree, the Arctic. Surface climate predictability in the Northern Hemisphere might be improved due to a previously proposed, albeit uncertain, link to springtime ozone depletion in the Arctic. Here we use observations and targeted chemistry–climate experiments from two models to isolate the surface impacts of ozone depletion from complex downward dynamical influences. We find that springtime stratospheric ozone depletion is consistently followed by surface temperature and precipitation anomalies with signs consistent with a positive Arctic Oscillation, namely, warm and dry conditions over southern Europe and Eurasia and moistening over northern Europe. Notably, we show that these anomalies, affecting large portions of the Northern Hemisphere, are driven substantially by the loss of stratospheric ozone. This is due to ozone depletion leading to a reduction in short-wave radiation absorption, when in turn causing persistent negative temperature anomalies in the lower stratosphere and a delayed break-up of the polar vortex. These results indicate that the inclusion of interactive ozone chemistry in atmospheric models can considerably improve the predictability of Northern Hemisphere surface climate on seasonal timescales.

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Fig. 1: Surface climate following springtime Arctic ozone depletion.
Fig. 2: The AO index following winters with extreme ozone loss.
Fig. 3: Simulation set-up and ozone feedback mechanism.
Fig. 4: Influence of ozone depletion on stratosphere–troposphere coupling.
Fig. 5: Impact of ozone feedbacks on short-wave and dynamical heating.

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Data availability

The modelling data used in this study are available in the ETH Research Collection. Data for WACCM are available at https://www.research-collection.ethz.ch/handle/20.500.11850/52715565. Data for SOCOL-MPIOM are available at https://www.research-collection.ethz.ch/handle/20.500.11850/54603966. The MERRA2 reanalysis data can be downloaded from the Goddard Earth Sciences Data and Information Services Center (GES DIC) (https://disc.gsfc.nasa.gov/datasets?keywords=%22MERRA-2%22&page=1&source=Models%2FAnalyses%20MERRA-2).

Code availability

All codes and scripts used for the analysis in this study are available from the corresponding author upon reasonable request.

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Acknowledgements

We are grateful for the assistance from U. Beyerle in data management and thank S. Muthers for support in the chemistry–climate modelling with SOCOL-MPIOM. Support from the Swiss National Science Foundation through Ambizione Grant PZ00P2_180043 for M.F. and G.C and projects PP00P2_170523 and PP00P2_198896 to D.D. is gratefully acknowledged.

Author information

Authors and Affiliations

  1. Institute for Atmospheric and Climate Science, ETH Zürich, Zürich, Switzerland

    Marina Friedel, Gabriel Chiodo, Andrea Stenke, Daniela I. V. Domeisen & Thomas Peter

  2. Institute of Biogeochemistry and Pollutant Dynamics, ETH Zürich, Zürich, Switzerland

    Andrea Stenke

  3. Eawag, Swiss Federal Institute of Aquatic Science and Technology, Dübendorf, Switzerland

    Andrea Stenke

  4. University of Lausanne, Lausanne, Switzerland

    Daniela I. V. Domeisen

  5. Department of Geosciences, Princeton University, Princeton, NJ, USA

    Stephan Fueglistaler

  6. Program in Atmospheric and Oceanic Sciences, Princeton University, Princeton, NJ, USA

    Stephan Fueglistaler

  7. School of Engineering, ZHAW, Winterthur, Switzerland

    Julien G. Anet

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  1. Marina Friedel
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Contributions

G.C. conceived the modelling experiments. G.C., M.F., A.S. and J.A. conducted the modelling experiments. M.F. and G.C. processed the data. M.F., G.C., T.P., D.D. and S.F. analysed and interpreted the results. M.F. wrote the paper with input from all authors.

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Correspondence to Marina Friedel.

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Nature Geoscience thanks Robyn Schofield and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editor: James Super, in collaboration with the Nature Geoscience team.

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Extended data

Extended Data Fig. 1 Surface climate following springtime Arctic ozone depletion in SOCOL-MPIOM.

Composites of sea level pressure (a, d, g), surface temperature (b, e, h) and precipitation (c, f, i) in SOCOL-MPIOM INT-3D (top row), CLIM-3D (middle row) and CLIM-2D (bottom row) after ozone minima in the 25% of winters with most extreme ozone loss (average over the 30 days after the ozone minimum date). Stippling shows significance on a 4.6% level following a bootstrapping test. Further discussion on this Figure is found in the supplementary information (section S1).

Extended Data Fig. 2 The Arctic Oscillation (AO) index following winters with extreme ozone.

The box plot shows the distribution of the mean AO index (20 - 90° N) at 1000 hPa in the 30 days following the ozone minimum for WACCM and SOCOL-MPIOM (INT-3D (red), CLIM-3D (blue) and CLIM-2D (grey)) and MERRA2 (left box). Triangles and numbers indicate the mean AO index in the 30 days after the ozone minima averaged over the 25% most extreme winters. The upper and lower edges of the boxes show the upper and lower quartile, the whiskers represent the maximum and minimum values of the respective distribution. Grey lines show averages over model simulations. Further discussion on this Figure is found in the supplementary information (sections S1, S2).

Extended Data Fig. 3 Influence of ozone depletion on stratosphere-troposphere coupling in SOCOL-MPIOM.

Composites of Northern Annular Mode (NAM) indices (20 - 90° N) around the ozone minima in SOCOL-MPIOM INT-3D (a), CLIM-3D (b) and CLIM-2D (c). Day zero indicates the ozone minimum date. Stippling shows significance on a 4.6% level following a bootstrapping test. Further discussion on this Figure is found in the supplementary information (section S1).

Extended Data Fig. 4 Impact of ozone feedbacks on shortwave and dynamical heating in WACCM and SOCOL-MPIOM.

Differences of polar cap (60-90° N) temperature (a-d), ozone (e-h), shortwave heating (i-l) and dynamical heating (m-p) anomalies between INT-3D and CLIM-3D as well as between INT-3D and CLIM-2D around the ozone minima in WACCM (first and second column) and SOCOL-MPIOM (third and fourth column). Day zero indicates the ozone minimum date. Contour lines in the temperature plot show temperature anomalies around the ozone minima in CLIM with a contour interval of 1.5 K. Stippling shows significance on a 4.6% level following a bootstrapping test. Further discussion on this Figure is found in the supplementary information (section S1).

Extended Data Fig. 5 Influence of ozone feedbacks on surface climate in WACCM.

Difference in mean SLP (a, d), surface temperature (b, e) and precipitation (c, f) anomalies in INT-3D minus CLIM-3D (upper row) and INT-3D minus CLIM-2D (bottom row) for the 25% of years with the lowest springtime ozone concentrations in WACCM (average over the 30 days after the ozone minimum date). Stippling shows significance on a 4.6% level following a bootstrapping test. Further discussion on this Figure is found in the supplementary information (section S2).

Extended Data Fig. 6 Influence of ozone feedbacks on surface climate in SOCOL.

Difference in mean SLP (a, d), surface temperature (b, e) and precipitation (c, f) anomalies in INT-3D - CLIM-3D (upper row) and INT-3D - CLIM-2D (bottom row) for the 25% of years with the lowest spring ozone concentrations in SOCOL-MPIOM (average over the 30 days after the ozone minimum date). Stippling shows significance on a 4.6% level following a bootstrapping test. Further discussion on this Figure is found in the supplementary information (section S2).

Supplementary information

Supplementary Information

Supplementary Figs. 1–10, Tables 1 and 2 and discussion.

Extended data

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Friedel, M., Chiodo, G., Stenke, A. et al. Springtime arctic ozone depletion forces northern hemisphere climate anomalies. Nat. Geosci. 15, 541–547 (2022). https://doi.org/10.1038/s41561-022-00974-7

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