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AN AGGREGATION AND EPISODE SELECTION SCHEME FOR EPA'S MODELS-3 CMAQ
Citation:
Eder, B K., R. D. Cohn, S K. LeDuc, AND R L. Dennis. AN AGGREGATION AND EPISODE SELECTION SCHEME FOR EPA'S MODELS-3 CMAQ. Presented at 12th Conference on Applied Climatology, Asheville, NC, May 8-11, 2000.
Impact/Purpose:
The goal of this task is to thoroughly characterize the performance of the emissions, meteorological and chemical/transport modeling components of the Models-3 system, with an emphasis on the chemical/transport model, CMAQ. Emissions-based models are composed of highly complex scientific hypotheses concerning natural processes that can be evaluated through comparison with observations, but not validated. Both performance and diagnostic evaluation together with sensitivity analyses are needed to establish credibility and build confidence within the client and scientific community in the simulations results for policy and scientific applications. The characterization of the performance of Models-3/CMAQ is also a tool for the model developers to identify aspects of the modeling system that require further improvement.
Description:
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 u and v wind field components over the time period 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 PM-2.5, for which little 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 data sets. 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 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.