Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Eurasian cooling in response to Arctic sea-ice loss is not proved by maximum covariance analysis

Matters Arising to this article was published on 02 February 2021

The Original Article was published on 14 January 2019

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Fig. 1: The co-varying mode of Eurasian surface temperature between ERA-Interim and the AMIP simulations.

Data availability

The ERA-Interim reanalysis is publicly available from ECMWF (https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era-interim). The AMIP FACTS simulations are publicly available from the National Oceanic and Atmospheric Administration (https://www.esrl.noaa.gov/psd/repository/alias/factsdocs).

References

  1. 1.

    Shepherd, T. G. Effects of a warming Arctic. Science 353, 989–990 (2016).

    CAS  Article  Google Scholar 

  2. 2.

    Mori, M., Kosaka, Y., Watanabe, M., Nakamura, H. & Kimoto, M. A reconciled estimate of the influence of Arctic sea-ice loss on recent Eurasian cooling. Nat. Clim. Change 9, 123–129 (2019).

    Article  Google Scholar 

  3. 3.

    Bretherton, C. S., Smith, C. & Wallace, J. M. An intercomparison of methods for finding coupled patterns in climate data. J. Clim. 5, 541–560 (1992).

    Article  Google Scholar 

  4. 4.

    Wallace, J. M., Smith, C. & Bretherton, C. S. Singular value decomposition of wintertime sea surface temperature and 500-mb height anomalies. J. Clim. 5, 561–576 (1992).

    Article  Google Scholar 

  5. 5.

    Screen, J. & Blackport, R. Is sea-ice-driven Eurasian cooling too weak in models? Nat. Clim. Change 9, 934–936 (2019).

    Article  Google Scholar 

Download references

Acknowledgements

The authors acknowledge Masato Mori and Hisashi Nakamura for useful feedback. G.Z. and T.G.S. were supported by the ERC advanced grant 339390. P.C. was supported by an Imperial College Research Fellowship and NERC grant NE/T006250/1.

Author information

Affiliations

Authors

Contributions

G.Z. conceived the study and performed the analyses. All the authors contributed to interpreting the results and writing the manuscript.

Corresponding author

Correspondence to Giuseppe Zappa.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Peer review informationNature Climate Change thanks Hans Chen and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 The singular vectors.

The pair of singular vectors composing the first co-varying surface temperature mode between the a) ERA-Interim and b) AMIP simulations via the maximum covariance analysis proposed in Mori et al.2. As in Fig. 1, the vectors are scaled to correspond to unit standard deviation in the expansion coefficients.

Extended Data Fig. 2 The robustness of the co-varying mode to model differences.

Homogeneous (top) and heterogeneous (bottom) regression maps of sea level pressure in the AMIP simulations obtained by separately performing the maximum covariance analysis for each individual model and using all the available ensemble members: 17 members are used for AM3, 12 for GEOS-5, 20 for CAM4, and 50 for all other models. Stippling shows statistical significance at the 5% level as in Fig. 1.

Extended Data Fig. 3 The potential confounding role of the SSTs.

Heterogeneous map of the SSTs associated to the co-varying mode in the AMIP simulations. Stippling denotes statistical significance at the 5% level. The potential of these SST anomalies, such as the ENSO- like pattern in the tropical Pacific, to force the circulation signals associated to the co-varying mode in Fig. 1f is discussed in the Supplementary Information (Supplementary Figure 2).

Supplementary information

Supplementary Information

Methodology, Supplementary Discussion and Figs. 1 and 2.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Zappa, G., Ceppi, P. & Shepherd, T.G. Eurasian cooling in response to Arctic sea-ice loss is not proved by maximum covariance analysis. Nat. Clim. Chang. 11, 106–108 (2021). https://doi.org/10.1038/s41558-020-00982-8

Download citation

Further reading

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing