Annual application and evaluation of the online coupled WRF–CMAQ system over North America under AQMEII phase 2

We present an application of the online coupled Weather Research and Forecasting–Community Multiscale Air Quality (WRF–CMAQ) modeling system to two annual simulations over North America performed under Phase 2 of the Air Quality Model Evaluation International Initiative (AQMEII). Operational evaluation shows that model performance is comparable to earlier annual applications of the uncoupled WRF/CMAQ modeling system Results also indicate that factors such as changes in the underlying emissions inventory and chemical boundary conditions likely exert a larger influence on overall model performance than feedback effects. A comparison of the simulated Aerosol Optical Depth (AOD) against observations reveals a tendency toward underprediction in all seasons despite a general overprediction of PM2.5 during wintertime. Summertime sensitivity simulations without feedback effects are used to quantify the average impact of the simulated direct feedback effect on temperature, PBL heights, ozone and PM2.5 concentrations. Model results for 2006 and 2010 are analyzed to compare modeled changes between these years to those seen in observations. The results for summertime average daily maximum 8-h ozone showed that the model tends to underestimate the observed decrease in concentrations. The results for total and speciated PM2.5 vary between seasons, networks and species, but the WRF–CMAQ simulations do capture the substantial decreases in observed PM2.5 concentrations in summer and fall. These 2010–2006 PM2.5 decreases result in simulated increases of summer mean clear-sky shortwave radiation between 5 and 10 W/m2. The WRF–CMAQ configuration without direct feedback effects simulates smaller changes in summertime PM2.5 concentrations, indicating that the direct feedback effect enhances the air quality benefits arising from emission controls and that coupled modeling systems are necessary to quantify such feedback effects.