摘要

To monitor the variability and the correlation of multiple atmospheric parameters in the whole troposphere and the lower stratosphere, a ground-based ultraviolet multifunctional Raman lidar system was established to simultaneously measure the atmospheric parameters in Xi'an (34.233 degrees N, 108.911 degrees E). A set of dichroic mirrors (DMs) and narrow-band interference filters (IFs) with narrow angles of incidence were utilized to construct a high-efficiency 5-channel polychromator. A series of high-quality data obtained from October 2013 to December 2015 under different weather conditions were used to investigate the functionality of the Raman lidar system and to study the variability of multiple atmospheric parameters in the whole stratosphere. Their conveying characteristics are also investigated using back trajectories with a hybrid single-particle Lagrangian integrated trajectory model (HYSPLIT). The lidar system can be operated efficiently under weather conditions with a cloud backscattering ratio of less than 18 and an atmospheric visibility of 3 km. We observed an obvious temperature inversion phenomenon at the tropopause height of 17-18 km and occasional temperature inversion layers below the boundary layer. The rapidly changing atmospheric water vapor is mostly concentrated at the lower troposphere, below similar to 4-5 km, accounting for similar to 90% of the total water vapor content at 0.5-10 km. The back trajectory analysis shows that the air flow from the northwest and the west mainly contributes to the transport of aerosols and water vapor over Xi'an. The simultaneous continuous observational results demonstrate the variability and correlation among the multiple atmospheric parameters, and the accumulated water vapor density in the bottom layer causes an increase in the aerosol extinction coefficient and enhances the relative humidity in the early morning. The long-term observations provide a large amount of reliable atmospheric data below the lower stratosphere, and can be used to study their correlation and to improve local climate change research.