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Reinhard Schiemann National Centre for Atmospheric Science, Department of Meteorology, University of Reading, Reading, United Kingdom

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Marie-Estelle Demory National Centre for Atmospheric Science, Department of Meteorology, University of Reading, Reading, United Kingdom

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Len C. Shaffrey National Centre for Atmospheric Science, Department of Meteorology, University of Reading, Reading, United Kingdom

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Jane Strachan National Centre for Atmospheric Science, Department of Meteorology, University of Reading, Reading, United Kingdom

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Pier Luigi Vidale National Centre for Atmospheric Science, Department of Meteorology, University of Reading, Reading, United Kingdom

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Matthew S. Mizielinski Met Office Hadley Centre, Exeter, United Kingdom

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Malcolm J. Roberts Met Office Hadley Centre, Exeter, United Kingdom

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Mio Matsueda Center for Computational Sciences, University of Tsukuba, Japan, and Department of Physics, University of Oxford, Oxford, United Kingdom

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Michael F. Wehner Lawrence Berkeley National Laboratory, Berkeley, California

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Thomas Jung European Centre for Medium-Range Weather Forecasts, Reading, United Kingdom, and Alfred Wegener Institute, Bremerhaven, Germany

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Current affiliation: Met Office Hadley Centre, Exeter, United Kingdom.

Denotes content that is immediately available upon publication as open access.

This article is licensed under a Creative Commons Attribution 4.0 license (http://creativecommons.org/licenses/by/4.0/).

© 2017 American Meteorological Society.

Corresponding authore-mail: R. Schiemann, r.k.schiemann@reading.ac.uk

Current affiliation: Met Office Hadley Centre, Exeter, United Kingdom.

Denotes content that is immediately available upon publication as open access.

This article is licensed under a Creative Commons Attribution 4.0 license (http://creativecommons.org/licenses/by/4.0/).

© 2017 American Meteorological Society.

Corresponding authore-mail: R. Schiemann, r.k.schiemann@reading.ac.uk

In Schiemann et al. (2017), a mistake occurred in Fig. 11 in how the area-weighted correlation and root-mean-square error (RMSE) were calculated. The corrected figure appears below. This has no impact on the interpretation of the figure and on the conclusions of the paper. Any future quantitative comparisons will need to refer to the corrected version of the figure. We regret any inconvenience this may cause.

Fig. 11.
Fig. 11.

Blocking frequency root-mean-square error and spatial correlation with respect to the reanalysis blocking frequency field shown in Fig. 1 for the Atlantic–European sector (45°–75°N, 280°–80°E). (a)–(d) The four different models; small symbols correspond to ensemble members and large/thickened symbols to the ensemble mean (see Table 2): results are shown for coarse resolution (upside down triangles), medium resolution (circles), and high resolution (triangles); and DJF (blue), MAM (green), JJA (red), and SON (orange).

Citation: Journal of Climate 30, 12; 10.1175/JCLI-D-17-0091.1

REFERENCE

Schiemann, R., and Coauthors, 2017: The resolution sensitivity of Northern Hemisphere blocking in four 25-km atmospheric global circulation models. J. Climate, 30, 337358, doi:10.1175/JCLI-D-16-0100.1.

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  • Schiemann, R., and Coauthors, 2017: The resolution sensitivity of Northern Hemisphere blocking in four 25-km atmospheric global circulation models. J. Climate, 30, 337358, doi:10.1175/JCLI-D-16-0100.1.

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  • Fig. 11.

    Blocking frequency root-mean-square error and spatial correlation with respect to the reanalysis blocking frequency field shown in Fig. 1 for the Atlantic–European sector (45°–75°N, 280°–80°E). (a)–(d) The four different models; small symbols correspond to ensemble members and large/thickened symbols to the ensemble mean (see Table 2): results are shown for coarse resolution (upside down triangles), medium resolution (circles), and high resolution (triangles); and DJF (blue), MAM (green), JJA (red), and SON (orange).

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