The vertical distribution of atmospheric aerosol layers plays a fundamental role in understanding their climatic and environmental effects. Using one year of lidar observations in Jinhua, together with ground-based meteorological measurements and ERA5 reanalysis data, this study develops an integrated analytical framework to investigate the structural characteristics of aerosol layers in Mie-scattering profiles and their meteorological driving factors. K-means clustering identifies three representative aerosol layer structure types: single-layer concave, single-layer convex, and multi-layer profiles. By combining the Boruta algorithm with a random forest model, the dominant meteorological factors associated with each structure type are quantified across four boundary-layer stages (00–06, 06–12, 12–18, 18–24 LT). Temperature, humidity, wind speed, wind direction, divergence, and vertical velocity exhibit distinct influences across different boundary-layer conditions, revealing differentiated regulatory mechanisms governing aerosol layer structure change. The proposed framework establishes a coupled perspective between atmospheric dynamic/thermodynamic processes and aerosol layer structure formation, providing a basis for refined modeling of aerosol evolution and improved understanding of aerosol–meteorology interactions.
Yu et al. (Tue,) studied this question.