A study of meteorology-aerosol joint data assimilation on autumn PM_2.5 concentration simulation

Compared with the pollution accumulation process under stable condition in winter, the autumn meteorological conditions are more complex and local. The uncertainty of the meteorological condition simulation brings greater difficulty to the autumn aerosol simulation, and the online meteorology-aerosol joint assimilation are rarely considered in current model simulations. The WRF/Chem model and GSI three-dimensional variational data assimilation system were used to carry out 4 groups of simulation and assimilation experiments (in 6 h cycle frequency) for October 2015, and the influences of meteorology-aerosol joint data assimilation on autumn aerosol simulation were discussed. Results show that the WRF/Chem could simulate the regional air pollution events in autumn in China, but there existed overestimates/underestimates in the Middle East/Northwest China. Assimilation of PM_2.5 observations improved the simulation results, and the 6 h forecast deviation was reduced to less than 6 μg/m³. For the North China Plain, PM_2.5 pollution in autumn was closely related to special meteorological conditions, e.g. high humidity, convergence of wind field, and regional transport. Therefore, the assimilation of conventional meteorological data in addition to surface PM_2.5 assimilation better captured the meteorology-pollution process and the correlation coefficient of PM_2.5 concentration forecast was increased from 0.86 to 0.89. Joint meteorology-aerosol data assimilation can help to more accurately simulate autumn aerosol pollution process in China, and thus can better serve scientific researches on pollution mechanism and meteorology-aerosol interaction under the framework of meteorological forecast.