Benchmarking Performance Changes in the Simulation of Extratropical Modes of Variability across CMIP Generations

• Published in: Journal of climate 2021-09, Vol.34 (17), p.6945-6969
• Main Authors: Lee, Jiwoo, Sperber, Kenneth R., Gleckler, Peter J., Taylor, Karl E., Bonfils, Céline J. W.
• Format: Article
• Language: English
• Subjects: Amplitude; Amplitudes; Anomalies; Antarctic Oscillation; Arctic Oscillation; Atmospheric forcing; Atmospheric models; Basis functions; Climate; climate model evaluation; Climate models; CMIP; Empirical orthogonal functions; ENVIRONMENTAL SCIENCES; Errors; extratropical modes of variability; interannual variability; Intercomparison; metrics; Modelling; Modes; North Atlantic Oscillation; North Pacific Oscillation; Ocean-atmosphere system; Orthogonal functions; Pacific Decadal Oscillation; Seasons; Simulation; Southern Hemisphere; Variability
• ISSN: 0894-8755; 1520-0442
• DOI: 10.1175/JCLI-D-20-0832.1

We evaluate extratropical modes of variability in the three most recent phases of the Coupled Model Intercomparison Project (CMIP3, CMIP5, and CMIP6) to gauge improvement of climate models over time. A suite of high-level metrics is employed to objectively evaluate how well climate models simulate the observed northern annular mode (NAM), North Atlantic Oscillation (NAO), Pacific–North America pattern (PNA), southern annular mode (SAM), Pacific decadal oscillation (PDO), North Pacific Oscillation (NPO), and North Pacific Gyre Oscillation (NPGO). We apply a common basis function (CBF) approach that projects model anomalies onto observed empirical orthogonal functions (EOFs), together with the traditional EOF approach, to CMIP Historical and AMIP models. We find simulated spatial patterns of those modes have been significantly improved in the newer models, although the skill improvement is sensitive to the mode and season considered. We identify some potential contributions to the pattern improvement of certain modes (e.g., the Southern Hemisphere jet and high-top vertical coordinate); however, the performance changes are likely attributed to gradual improvement of the base climate and multiple relevant processes. Less performance improvement is evident in the mode amplitude of these modes and systematic overestimation of the mode amplitude in spring remains in the newer climate models. We find that the postdominant season amplitude errors in atmospheric modes are not limited to coupled runs but are often already evident in AMIP simulations. This suggests that rectifying the egregious postdominant season amplitude errors found in many models can be addressed in an atmospheric-only framework, making it more tractable to address in the model development process.