Data Assimilation of Ceilometer Aerosol Extinction Coefficient Profile Contributes to Predictions of the Three‐Dimensional Structures of Aerosols in East China

Abstract Ceilometer aerosol extinction coefficient (AExtC) profiles in Hangzhou city (HZ) in East China are assimilated from 1 to 31 December 2020 by applying the WRFDA‐Chem model system. The analysis field obtained from data assimilation (DA) is set as the chemical initial condition (IC) for WRF‐Chem (Weather Research and Forecasting model coupled with Chemistry) aerosol prediction. Observations, including ceilometer AExtC profiles in HZ, ground PM 2.5 in East China are adopted to verify the analysis and predictions. The RMSE (root mean square error between model and observation) improvements for ceilometer AExtC, and PM 2.5 persist for at least 18 forecast hours, with the mean RMSE decreasing by 13% and 8%, respectively. Moreover, the contributions of different observation systems (ceilometer profiles versus ground PM 2.5 ) to predicting three‐dimensional (3D) aerosol structures are also investigated. The contribution of ceilometer DA is comparable to that of direct PM 2.5 DA to the PM 2.5 predictions in HZ and its environs, with RMSE decreased by 8% and 10%, respectively. In areas far from the assimilation stations' locations (HZ city), ceilometer DA showed an even better performance. The performance of ground PM 2.5 DA is inferior to that of the direct ceilometer DA experiment in predicting ceilometer AExtC vertical profiles. The joint assimilation of ceilometer and PM 2.5 data was conducted. Best 3D aerosol structure predictions are obtained through the joint DA of ceilometer profiles and ground PM 2.5 .