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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).
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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.
The authors declare no competing interests.
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.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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.
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.
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).
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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
Reply to: Eurasian cooling in response to Arctic sea-ice loss is not proved by maximum covariance analysis
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