Impact of GOES Enhanced WRF Fields on Air Quality Model Performance Maudood N. Khan, Andrew White, Arastoo P. Biazar, and Dr. Richard T. McNider University of Alabama in Huntsville, Huntsville, Alabama Key Findings Regionally aggregated performance statistics do not indicated substantial improvement or degradation in CMAQ model performance as a result of using GOES enhanced WRF simulated fields Differences in O3 concentrations are largest in the west & north-west. Largest differences in PM are seen in the south and the east Differences in wind direction result in large difference in O3 concentration over the Gulf and the Pacific Ocean Simulation Average Difference (CONTROL minus ANALYTICAL) in Wind Direction overlaid on Simulation Average Difference in O3 concentration Meteorological Fields Background Clouds modify tropospheric chemistry by impacting photolysis rate, providing liquid water for scavenging of gases, and for aqueous phase chemical reactions. A new technique has been developed that utilizes observations from Geostationary Observational Environmental Satellite (GOES) to introduce within WRF positive/negative vertical motion that results in the creation/dissipation of clouds. Comparison of model prediction with (ANALYTICAL) and without GOES data (CONTROL) assimilation at the NWS stations did not indicate any consistent trend in Mean Bias for Wind Speed, Wind Direction and Water Vapor mixing ratio. Increase in cloud cover predicted by the ANALYTICAL simulation resulted in cooler temperatures across the domain. Ozone Performance This Research Aims to quantify changes in air quality model predictions that can be attributed to the use of GOES enhanced WRF predicted meteorological fields. Two simulations (i.e., CONTROL and ANALYTICAL) of the Community Multi-scale Air Quality Model (CMAQ) model simulations were conducted for a three-month period beginning July 1, 2013 on a 12-km resolution grid that spans continental United States. The predictions of O3, PM2.5, and PM10 are compared against observations recorded at air quality monitoring sites. The statistics for each site computed for the simulation period have been aggregated by RPO regions shown below. Gridded differences in simulated average concentrations have been presented. Modeling System PM2.5 Performance PM10 Performance 15th Community Modeling and Analysis System (CMAS) Conference in October 24-26, 2016, University of North Carolina, Chapel Hill, NC