On the Evaluation of Regional-scale Photochemical Air Quality Modeling Systems

This work provides a comprehensive view of the process of evaluating regional-scale (~2002000 km) three-dimensional numerical photochemical air quality modeling systems, including meteorological, emissions, and air quality components. We have examined approaches to the evaluation of regional air quality modeling systems, as they are currently used in a variety of applications. From this examination, we conclude that such models cannot be validated in the formal sense, but rather can be shown to have predictive and diagnostic value. A framework for model evaluation is introduced here to provide a context for the evaluation process. The objectives of the model evaluation process include determining the suitability of a modeling system for a specific application, distinguishing the performance between different models through confidence-testing of model results, and guiding further model development. The evaluation framework presents some methods for operational, diagnostic, dynamic, and probabilistic model evaluation. Operational evaluation techniques include statistical and graphical analyses aimed at determining whether the estimated values of the modeled variables are comparable to measurements in an overall sense. Diagnostic evaluation focuses on processoriented analyses that determine whether the individual processes and components of the model system are working correctly, both independently and in combination. Dynamic evaluation assesses the ability of the air quality model to predict changes in air quality given changes in source emissions or meteorology, the principal forces that drive the air quality model. Probabilistic evaluation attempts to assess the level of confidence in the model predictions through techniques such as ensemble model simulations. Current and emerging needs for observational data from the model evaluation perspective are also discussed, as well as the