Biological and Environmental Research - Earth and Environmental System Sciences
Earth and Environmental System Modeling
23 May 2014

A First Comprehensive Evaluation of WRF-Chem for Simulating Aerosols over East Asia





East Asia is one of the most polluted regions in the World. Large emissions of aerosol and precursor gases in East Asia result in heavy pollution from particulate matter, which has been suggested to play an important role in the radiative balance of the Earth-Atmosphere system and climate change at regional and global scales in recent decades. Due to the sparse observations, models have been used to simulate the seasonal variation and spatial transport of aerosol pollutants in East Asia and across the Pacific to North America. In this study, researchers at the University of Wyoming, DOE’s Pacific Northwest National Laboratory and Chinese Academy of Sciences for the first time systematically evaluate the community Weather Research and Forecasting (WRF) model with chemistry (WRF-Chem) for its ability to simulate aerosol pollution in East Asia.  The WRF-Chem model can generally reproduce the observed spatial distributions of aerosol concentration. The model also depicts the seasonal variation and transport of pollutions over East Asia. However, the model underestimates sulfate aerosol and organic carbon concentrations over mainland China by about a factor of 2, while overestimating nitrate aerosol concentration in autumn along the Yangtze River.  Anthropogenic aerosol radiative forcing is estimated to range from -5 to -20 W m-2 over land and -20 to -40 W m-2 over the adjacent oceans at the top of atmosphere, 5-30 W m-2 in the atmosphere and -15 to -40 W m-2 at the surface. Considering the significant underestimations of sulfate and organic carbon aerosols by WRF-Chem, the actual anthropogenic aerosol radiative forcing in East Asia can be even stronger. This study motivates the need to further constrain the estimates of anthropogenic aerosol radiative forcing in East Asia through measurements and improved modeling.