Aerosol optical properties of haze episodes in eastern China based on remote-sensing observations and WRF-Chem simulations

The ability for remote-sensing sensors and global/regional models to describe aerosol optical properties (AOPs) is critical to reducing the uncertainty in aerosol radiative forcing associated with climate change, and improving model prediction accuracy. In this study, remote-sensing observations and WRF-Chem simulations were used to evaluate AOPs over Eastern China during a severe winter haze event, in terms of aerosol optical depth (AOD), Angstrom exponent (AE) and aerosol extinction profiles (AEP). This study also characterizes whether the inclusion of aerosol radiative feedbacks (ARFs) may improve the ability of WRF-Chem to acquire AOPs during haze episodes. Three simulation scenarios were considered: the non-radiation feedback (NRF), aerosol direct effect (ADE), as well as combined ADE and aerosol indirect effect (ADE + AIE). The results indicate that the satellite AOD products could represent the spatiotemporal distribution characteristics of the haze event. The AOD retrieved by the MODIS C6.1 DB algorithm was highly consistent with ground-based observations. A comparison between simulations and observations demonstrated that WRF-Chem, including the ADE or ADE + ALE scheme, may improve AOPs simulation in heavily polluted areas. The most significant improvements occurred in the Sichuan basin (SB) and North China Plain (NCP) (AOD = 50-70%; AE = 10-20%). In particular, the ADE + AIE scheme was the most obvious for AOD improvement, followed by AE. The AEP was also qualitatively analyzed through simulations and observations, and the result showed that the model overestimates aerosol extinction coefficients in NCP. However, the model is still able to represent the entire AEP contour over East China. Similar to AOD and AE, the model can also improve AEP simulation by adding ADE or ADE + AIE scheme, especially in SB. In summary, it is found that the ability of WRF-Chem to simulate the AOPs was significantly enhanced, particularly for regions loading with heavy aerosol during haze events in Eastern China. (C) 2020 Elsevier B.V. All rights reserved.