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.