Pattern-Based Evaluation of Coupled Meteorological and Air Quality Models.

Abstract A novel pattern-based model evaluation technique is proposed and demonstrated for air quality models (AQMs) driven by meteorological model (MM) output. The evaluation technique is applied directly to the MM output; however, it is ultimately used to gauge the performance of the driven AQM. This evaluation of AQM performance based on MM performance is a major advance over traditional evaluation methods. First, meteorological cluster analysis is used to assign the days of a historical measurement period among a small number of weather patterns having distinct air quality characteristics. The clustering algorithm groups days sharing similar empirical orthogonal function (EOF) representations of their measurements. In this study, EOF analysis is used to extract space–time patterns in the surface wind field reflecting both synoptic and mesoscale influences. Second, simulated wind fields are classified among the determined weather patterns using the measurement-derived EOFs. For a given period, the leve...