Improving the WRF-Chem forecast of PM_2.5 over North China in autumn with data assimilation

Assimilation of the initial aerosol field can improve the accuracy of coupled meteorology-aerosol forecasts in WRF-Chem. To discuss the influence of aerosol assimilation on coupled model forecasts at different times for a heavy haze pollution process in October 2015, an experimental study of joint meteorology-aerosol assimilation and short-term forecast at four different times of a day was conducted. The results show that assimilating aerosol observations on the basis of assimilated meteorological data can improve the overestimation of simulation caused by the emission source inventory with large uncertainty, and reduce the positive bias of PM_2.5 in the initial field. With decreased PM_2.5 concentration in the initial field, the reduction of surface radiation caused by aerosols is weakened, which increases downward shortwave radiation in the 6 h forecast in the daytime. The response of near-surface temperature and humidity to radiation changes (warming and humidity reduction) during the daytime is spatially coincident over a large area and temporally synchronized, and continues even at night under the influence of circular rolling forecast. The structure of the near-surface warming and humidity reduction contributes to upward development of the boundary layer, which in turn promotes upward transport of aerosols and ultimately attenuates the overestimation of surface PM_2.5 in the forecast. Consequently, the improvement of the initial PM_2.5 information due to aerosol assimilation makes the 6 h coupled forecasts more accurate.