Impact of global to regional meteorology downscaling to the regional air quality simulation

Three global (or semi-global) meteorology simulations, during Aug. 2010, have been utilized to initiate regional meteorology simulations, and their impacts on regional air quality simulations are studied. Weather Research and Forecasting (WRF) simulations with same physical options, but initiated with three different global meteorology model outputs (North American Mesoscale Model (NAM), Global Forecast System (GFS), and Global/Regional Integrated Model system (GRIMs)), are utilized to simulate regional air quality using Community Multi-scale Air Quality/ Sparse Matrix Operator Kernel Emission (CMAQ/SMOKE) modeling system. Variations in key meteorological variables critical to air quality simulation (e.g. surface temperature, wind speed, boundary layer, and cloud fraction) are compared, and their impact on forecast pollutant concentrations were investigated using surface observations from numerous observational sources, including the Meteorological Assimilation Data Ingest System (MADIS), the EPA AIRNow/AQS, the Interagency Monitoring of Protected Visual Environments (IMPROVE) data. Results show perturbations in meteorological fields result in various sensitivities in regional air quality for different regions. For California region, small perturbation in cloud fraction resulted in considerable variation on surface ozone production. For eastern US, variations in surface temperature caused biogenic emission difference in southeastern US region, and resulted in difference in surface ozone concentrations in this region. Locations of surface temperature bias are also well associated with surface ozone bias, implying potential explanation for the surface ozone bias during summertime in the southeastern US region.