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A STUDY OF PROCESS CONTRIBUTIONS TO OZONE FORMATION DURING THE 2004 ICARTT PERIOD USING THE ETA- CMAQ FORECAST MODEL OVER THE NORTHEASTERN U.S.
Citation:
YU, S., R. MATHUR, K. L. SCHERE, D. KANG, J. PLEIM, JEFF O. YOUNG, AND T. L. OTTE. A STUDY OF PROCESS CONTRIBUTIONS TO OZONE FORMATION DURING THE 2004 ICARTT PERIOD USING THE ETA- CMAQ FORECAST MODEL OVER THE NORTHEASTERN U.S. Presented at 28th NATO/CCMS International Technical Meeting, Lepzig, GERMANY, May 15 - 19, 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:
First, this study evaluates the Eta-CMAQ forecast model performances for O3, and related chemical species with the observational data from the aircraft (NOAA P-3 and NASA DC-8) flights, Lidar and ozonesonde during the 2004 International Consortium for Atmospheric Research on Transport and Transformation (ICARTT) field experiments. The spatial and temporal performance of the model for surface O3 over the northeastern U.S during this period is also examined through comparison with observations from the U.S. EPA Air Quality System (AQS) network. Secondly, the contributions of various physical and chemical processes governing the distribution of O3 during this period are investigated through detailed analysis of model process budgets using the integrated process rate analysis (IPR).