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AN OPERATIONAL EVALUATION OF THE ETA - CMAQ AIR QUALITY FORECAST MODEL
Citation:
EDER, B. K., D. KANG, R. MATHUR, S. YU, AND K. L. SCHERE. AN OPERATIONAL EVALUATION OF THE ETA - CMAQ AIR QUALITY FORECAST MODEL. ATMOSPHERIC ENVIRONMENT. Elsevier Science Ltd, New York, NY, 40(26):4894-4905, (2006).
Impact/Purpose:
The objectives of this task include: (1) to continuously evaluate and analyze the forecast results to provide diagnostic information on model performance and inadequacies to guide further evolution and refinements to the CMAQ model, and (2) extending the utility of the daily air quality forecast model data being produced by NOAA's National Weather Service (NWS) as part of a NOAA/EPA collaboration in air quality forecasting, to EPA mission-oriented activities. These objectives include developing and maintaining a long-term database of air quality modeling results (ozone and PM2.5), performing periodic analysis and assessments using the data, and making the air quality database available and accessible to States, Regions, RPO's and others to use as input data for regional/local scale air quality modeling for policy/regulatory purposes.
Description:
The National Oceanic and Atmospheric Administration (NOAA), in partnership with the United States Environmental Protection Agency (EPA), are developing an operational, nationwide Air Quality Forecasting (AQF) system. An experimental phase of this program, which couples NOAA's Eta meteorological model with EPA's Community Multiscale Air Quality (CMAQ) model, began operation in June of 2004 and has been providing forecasts of ozone (O3) concentrations over the northeastern United States. An important component of this AQF system has been the development and implementation of an evaluation protocol. Accordingly, a suite of statistical metrics that facilitates evaluation of both discrete- and categorical-type forecasts was developed and applied to the system in order to characterize its performance. The results reveal that the AQF system performed reasonably well in this inaugural season (mean domain wide correlation coefficient = 0.59), despite anomalously cool and wet conditions that were not conducive to the formation of O3. Due in part to these conditions, the AQF system overpredicted concentrations, resulting in a mean bias of +10.2 ppb (normalized mean bias = +22.8%). In terms of error, the domain-wide root mean square error averaged 15.7 ppb (normalized mean error = 28.1%) for the period. Examination of the discrete and categorical metrics on a daily basis revealed that the AQF system's level of performance was closely related to the synoptic-scale meteorology impacting the domain. The model performed very well during periods when anticyclones, characterized by clear skies, dominated. Conversely, periods characterized by extensive cloud associated with fronts and/or cyclones, resulted in poor model performance. Subsequent analysis revealed that factors associated with CMAQ's cloud cover scheme contributed to this overprediction. Accordingly, changes to the cloud schemes are currently underway that are expected to significantly improve the AQF system's performance in anticipation of its second year of operation.