• Kiladis, G. N., J. Dias, K. H. Straub, M. C. Wheeler, S. N. Tulich, K. Kikuchi, K. M. Weickmann, and M. J. Ventrice, 2014: A comparison of OLR and circulation-based indices for tracking the MJO. Mon. Wea. Rev., 142, 16971715, https://doi.org/10.1175/MWR-D-13-00301.1.

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    Daily eigenvalues corresponding to an EOF analysis of 30–96-day eastward OLR between 20°S and 20°N derived using a 121-day sliding window (as explained in detail in the text of the original paper).

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CORRIGENDUM

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  • 1 NOAA/Earth System Research Laboratory, Physical Sciences Division, Boulder, Colorado
  • | 2 CIRES, University of Colorado Boulder, and NOAA/Earth System Research Laboratory, Boulder, Colorado
  • | 3 Department of Earth and Environmental Sciences, Susquehanna University, Selinsgrove, Pennsylvania
  • | 4 Centre for Australian Weather, and Climate Research, Melbourne, Victoria, Australia
  • | 5 International Pacific Research Center, University of Hawai‘i at Mānoa, Honolulu, Hawaii
  • | 6 The Weather Company, Andover, Massachusetts
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In an earlier study (Kiladis et al. 2014), we introduced an all-season OLR-based MJO index (OMI). We recently became aware of a factor of 2 plotting error in Fig. 1 of that paper. The time series of variance explained by the first two principal components of the EOF analysis should be about half of what is displayed in the figure. Those values are mentioned in the text once and this should to be corrected as follows:

These track each other well, differing by only 1%–2% throughout, and peak during mid-January at greater than 65% (33%) of the total

In an earlier study (Kiladis et al. 2014), we introduced an all-season OLR-based MJO index (OMI). We recently became aware of a factor of 2 plotting error in Fig. 1 of that paper. The time series of variance explained by the first two principal components of the EOF analysis should be about half of what is displayed in the figure. Those values are mentioned in the text once and this should to be corrected as follows:

These track each other well, differing by only 1%–2% throughout, and peak during mid-January at greater than 65% (33%) of the total

© 2020 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Current affiliation: NOAA/Earth System Research Laboratory, Physical Sciences Division, Boulder, Colorado.

Corresponding author: George N. Kiladis, george.kiladis@noaa.gov

In an earlier study (Kiladis et al. 2014), we introduced an all-season OLR-based MJO index (OMI). We recently became aware of a factor of 2 plotting error in Fig. 1 of that paper. The time series of variance explained by the first two principal components of the EOF analysis should be about half of what is displayed in the figure. Those values are mentioned in the text once and this should to be corrected as follows:

These track each other well, differing by only 1%–2% throughout, and peak during mid-January at greater than 65% (33%) of the total

In an earlier study (Kiladis et al. 2014), we introduced an all-season OLR-based MJO index (OMI). We recently became aware of a factor of 2 plotting error in Fig. 1 of that paper. The time series of variance explained by the first two principal components of the EOF analysis should be about half of what is displayed in the figure. Those values are mentioned in the text once and this should to be corrected as follows:

These track each other well, differing by only 1%–2% throughout, and peak during mid-January at greater than 65% (33%) of the total

© 2020 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Current affiliation: NOAA/Earth System Research Laboratory, Physical Sciences Division, Boulder, Colorado.

Corresponding author: George N. Kiladis, george.kiladis@noaa.gov

In an earlier study (Kiladis et al. 2014), we introduced an all-season OLR-based MJO index (OMI). We recently became aware of a factor of 2 plotting error in Fig. 1 of that paper. The time series of variance explained by the first two principal components of the EOF analysis should be about half of what is displayed in the figure. Those values are mentioned in the text once and this should to be corrected as follows:

These track each other well, differing by only 1%–2% throughout, and peak during mid-January at greater than 65% (33%) of the total variance. The combined explained variance is minimized in late October, but is still above 53% (25%).

The corrected variances explained are shown between parentheses. For convenience, the corrected Fig. 1 from Kiladis et al. (2014) is shown here (see details in the original paper). This correction does not affect the interpretation of the results following Fig. 1 in the paper in any way.

Fig. 1.
Fig. 1.

Daily eigenvalues corresponding to an EOF analysis of 30–96-day eastward OLR between 20°S and 20°N derived using a 121-day sliding window (as explained in detail in the text of the original paper).

Citation: Monthly Weather Review 148, 2; 10.1175/MWR-D-19-0385.1

Acknowledgments

We are grateful to Christoph G. Hoffmann at Universität Greifswald who alerted us to this error when he attempted to reproduce our results.

REFERENCE

Kiladis, G. N., J. Dias, K. H. Straub, M. C. Wheeler, S. N. Tulich, K. Kikuchi, K. M. Weickmann, and M. J. Ventrice, 2014: A comparison of OLR and circulation-based indices for tracking the MJO. Mon. Wea. Rev., 142, 16971715, https://doi.org/10.1175/MWR-D-13-00301.1.

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