The Statistics and Horizontal Structure of Anomalous Weather Regimes in the Community Climate Model

Abstract

The statistics, horizontal structure, and linear barotropic dynamics of anomalous weather regimes are evaluated in a 15-winter integration of the NCAR Community Climate Model (CCM2). Statistical and ensemble analyses of simulated regimes are contrasted with parallel analyses derived from NCEP?NCAR reanalyses. The CCM2 replicates much of the structure of observed frequency distributions for anomalous weather regimes over the North Pacific and North Atlantic regions. The main differences are a northward shift and longitudinal broadening of the North Pacific frequency maximum and a weakening and southward shift of the North Atlantic maximum. Ensemble analyses reveal that simulated North Pacific regimes attain a more isotropic horizontal anomaly structure than observed cases, which are zonally elongated. The E-vector diagnoses indicate that North Pacific cases in the CCM2 are also associated with much weaker local barotropic energy conversions from the climatological-mean flow. This is partly due to the relatively weak climatological-mean diffluence simulated by the CCM2 in the jet exit region over the eastern North Pacific. The model?s North Atlantic regimes have horizontal anomaly patterns quite similar to observed cases, except for a southwestward shift relative to observations. Both simulated and observed North Atlantic cases exhibit robust local barotropic interactions with the climatological-mean flow, with the strongest conversions shifted southwestward in the model. The results suggest a larger role for mechanisms besides barotropic instability in maintaining anomalous weather regimes over the North Pacific in the CCM2. The model?s North Atlantic events occur southwest of observed cases apparently in order to more efficiently utilize the available ?barotropic energy reservoir? in the model climatology. The authors conclude that for GCMs to properly represent important dynamical characteristics of anomalous weather regimes, it is paramount that the model accurately depict the climatological-mean stationary wave field.