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

Nature Climate Change volume 11, pages 106–108 (2021)Cite this article

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Matters Arising to this article was published on 02 February 2021

The Original Article was published on 14 January 2019

arising from Masato Mori et al. Nature Climate Change https://doi.org/10.1038/s41558-018-0379-3 (2019)

The extent to which the ongoing decline in Arctic sea ice affects mid-latitude climate has received great attention and polarized opinions. The basic issue is whether the interannual variability in Arctic sea ice is the cause of, or the response to, variability in midlatitude atmospheric circulation1. Mori et al.2 claim to have reconciled previous conflicting studies by showing that a consistent midlatitude climate response to interannual sea-ice anomalies can be identified between the European Centre for Medium-Range Weather Forecasts (ECMWF) Interim Reanalysis (ERA-Interim), taken as observations, and an ensemble of atmosphere-only climate model simulations. Here we demonstrate that such a conclusion cannot be drawn, due to issues with the interpretation of the maximum covariance analysis performed. After applying the approach of Mori et al.2 to the output from a simple statistical model, we conclude that a predominant atmospheric forcing of the sea-ice variability, rather than the converse, is a more plausible explanation of the results presented in Mori et al.2.

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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

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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.

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Authors and Affiliations

  1. Department of Meteorology, University of Reading, Reading, UK

    Giuseppe Zappa & Theodore G. Shepherd

  2. Istituto di Scienze dell’Atmosfera e del Clima, Consiglio Nazionale delle Ricerche (ISAC-CNR), Bologna, Italy

    Giuseppe Zappa

  3. Grantham Institute for Climate Change and the Environment, Imperial College, London, UK

    Paulo Ceppi

Authors
  1. Giuseppe Zappa
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  2. Paulo Ceppi
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  3. Theodore G. Shepherd
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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.

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The authors declare no competing interests.

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

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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.

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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

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