Development of an Aggregation and Episode Selection Scheme to Support the Models-3 Community Multiscale Air Quality Model

Abstract

The development of an episode selection and aggregation approach, designed to support distributional estimation for use with the Models-3 Community Multiscale Air Quality (CMAQ) model, is described. The approach utilized cluster analysis of the 700-hPa east?west and north?south wind field components over the time period of 1984?92 to define homogeneous meteorological clusters. Alternative schemes were compared using relative efficiencies and meteorological considerations. An optimal scheme was defined to include 20 clusters (five per season), and a stratified sample of 40 events was selected from the 20 clusters using a systematic sampling technique. The light-extinction coefficient, which provides a measure of visibility, was selected as the primary evaluative parameter for two reasons. First, this parameter can serve as a surrogate for particulate matter with diameter of less than 2.5 ?m, for which few observational data exist. Second, of the air quality parameters simulated by CMAQ, this visibility parameter has one of the most spatially and temporally comprehensive observational datasets. Results suggest that the approach reasonably characterizes synoptic-scale flow patterns and leads to strata that explain the variation in extinction coefficient and other parameters (temperature and relative humidity) used in this analysis, and therefore the approach can be used to achieve improved estimates of these parameters relative to estimates obtained using other methods. Moreover, defining seasonally based clusters further improves the ability of the clusters to explain the variation in these parameters and therefore leads to more precise estimates.