Climate Dynamics

, Volume 52, Issue 7–8, pp 4057–4089 | Cite as

Quantifying the agreement between observed and simulated extratropical modes of interannual variability

  • Jiwoo LeeEmail author
  • Kenneth R. Sperber
  • Peter J. Gleckler
  • Céline J. W. Bonfils
  • Karl E. Taylor


Using historical simulations of the Coupled Model Intercomparison Project-5 (CMIP5) and multiple observationally-based datasets, we employ skill metrics to analyze the fidelity of the simulated Northern Annular Mode, the North Atlantic Oscillation, the Pacific North America pattern, the Southern Annular Mode, the Pacific Decadal Oscillation, the North Pacific Oscillation, and the North Pacific Gyre Oscillation. We assess the benefits of a unified approach to evaluate these modes of variability, which we call the common basis function (CBF) approach, based on projecting model anomalies onto observed empirical orthogonal functions (EOFs). The CBF approach circumvents issues with conventional EOF analysis, eliminating, for example, corrections of arbitrarily assigned, but inconsistent, signs of the EOF’s/PC’s being compared. It also avoids the problem that sometimes the first observed EOF is more similar to a higher order model EOF, particularly if the simulated EOFs are not well separated. Compared to conventional EOF analysis of models, the CBF approach indicates that models compare significantly better with observations in terms of pattern correlation and root-mean-squared-error (RMSE) than heretofore suggested. In many cases, models are doing a credible job at capturing the observationally-based estimates of patterns; however, errors in simulated amplitudes can be large and more egregious than pattern errors. In the context of the broad distribution of errors in the CMIP5 ensemble, sensitivity tests demonstrate that our results are relatively insensitive to methodological considerations (CBF vs. conventional approach), observational uncertainties in pattern (as determined by using multiple datasets), and internal variability (when multiple realizations from the same model are compared). The skill metrics proposed in this study can provide a useful summary of the ability of models to reproduce the observed EOF patterns and amplitudes. Additionally, the skill metrics can be used as a tool to objectively highlight where potential model improvements might be made. We advocate more systematic and objective testing of simulated extratropical variability, especially during the non-dominant seasons of each mode, when many models are performing relatively poorly.


CMIP5 model evaluation Modes of variability EOF Metrics Common basis function 



This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. The efforts of the authors are supported by the Regional and Global Climate Modeling Program of the United States Department of Energy’s Office of Science. The authors thank Ben Santer for helpful discussions and suggesting the use of tcor2 as one of our EOF swapping methods. We acknowledge the efforts of Paul Durack, Sasha Ames, Jeff Painter and Cameron Harr for maintaining the CMIP database, and Dean Williams, Charles Doutriaux, Denis Nadeau and their team for developing and maintaining the CDAT analysis package and ESGF. We thank reviewers for their comments. We acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modelling groups for producing and making available their model output. The CMIP data is available at ESGF. The Twentieth Century Reanalysis (20CR), HadSLP2r, and ERSSTv3b data are provided by the NOAA/Earth System Research Laboratory (ESRL)/Physical Sciences Division (PSD) from their website at Support for the 20CR Project dataset is provided by the U.S. Department of Energy, Office of Science Innovative and Novel Computational Impact on Theory and Experiment (DOE INCITE) program, and Office of Biological and Environmental Research (BER), and by the National Oceanic and Atmospheric Administration Climate Program Office. The ERA Interim and ERA-20C data sets are available through ECMWF’s website at The HadISST data is available through UK Met Office’s website at

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Conflict of interest

This document was prepared as an account of work sponsored by an agency of the United States government. Neither the United States government nor Lawrence Livermore National Security, LLC, nor any of their employees makes any warranty, expressed or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States government or Lawrence Livermore National Security, LLC. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States government or Lawrence Livermore National Security, LLC, and shall not be used for advertising or product endorsement purposes.


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Program for Climate Model Diagnosis and Intercomparison (PCMDI)Lawrence Livermore National Laboratory (LLNL)LivermoreUSA

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