REGIONAL AND LOCAL-SCALE EVALUATION OF 2002 MM5 METEOROLOGICAL FIELDS FOR VARIOUS AIR QUALITY MODELING APPLICATIONS
2007
Prognostic meteorological models are often used in a retrospective mode to provide inputs to air quality models. In turn, these air quality models are used for environmental planning. The meteorological inputs govern the advection, diffusion, chemical transformation, and eventual deposition of pollutants within regional air quality models such as the Community Multi-scale Air Quality (CMAQ) modeling system (Byun and Schere, 2006). The air quality models have traditionally been subjected to a rigorous performance assessment, but in many cases the meteorological inputs to these models are accepted as is, even though this component of the modeling arguably contains equal uncertainty. Before initiating the air quality simulations, it is important to identify the biases and errors associated with the meteorological modeling inputs. The goal of the meteorological evaluation should be to move toward an understanding of how the bias and error of the meteorological input data may impact the resultant AQ modeling. Typically, there are two specific objectives. First, determine if the meteorological model output fields represent a reasonable approximation of the actual meteorology that occurred during the modeling period (i.e., the "operational" evaluation). The second goal should be to identify how the existing biases and errors in the meteorological predictions may affect the air quality modeling results (i.e., the "phenomenological" evaluation). Once these two sets of information are generated, it is important to highlight the parts of the analysis expected to most influence the air quality model.
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