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Keywords:

  • empirical orthogonal functions;
  • principal components;
  • air pollution;
  • ozone;
  • regional modeling;
  • global modeling

[1] Empirical orthogonal functions are used together with standard statistical metrics to evaluate the ability of models with different spatial resolutions to reproduce observed patterns of surface ozone (O3) in the eastern United States in the summer of 1995. We examine simulations with the regional Multiscale Air Quality Simulation Platform model (horizontal resolution of 36 km2) and the global GEOS-CHEM model (2° × 2.5° and 4° × 5°). As the model resolution coarsens, the ability to resolve local O3 maxima (O3 ≥ 90 ppbv) is compromised, but the spatial correlation improves. This result shows that synoptic-scale processes modulating O3 concentrations are easier to capture in models than processes occurring on smaller scales. Empirical orthogonal functions (EOFs) derived from the observed O3 fields reveal similar modes of variability when averaged onto the three model horizontal resolutions. The EOFs appear to represent (1) an east-west pattern associated with frontal passages, (2) a midwest-northeast pattern associated with migratory high-pressure systems, and (3) a southeast stagnation pattern linked to westward extension of the Bermuda High. All models capture the east-west and southeast EOFs, but the midwest-northeast EOF is misplaced in GEOS-CHEM. GEOS-CHEM captures the principal components of the observational EOFs when the model fields are projected onto these EOFs, implying that it can resolve the contribution of the EOFs to the observed variance. We conclude that coarse-resolution global models can successfully simulate the synoptic conditions leading to high-O3 episodes in the eastern United States.