Meteorological Factors Attribution Analysis of Aerosol Layer Structure Changes in Mie-Scattering Profiles Measured by Lidar

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.

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Publication Details

Journal
Remote Sensing
Published
2026-03-24
DOI
https://doi.org/10.3390/rs18070967
Primary Topic
Atmospheric aerosols and clouds
Type
article
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article

Meteorological Factors Attribution Analysis of Aerosol Layer Structure Changes in Mie-Scattering Profiles Measured by Lidar

Remote Sensing
Atmospheric aerosols and clouds
article

Meteorological Factors Attribution Analysis of Aerosol Layer Structure Changes in Mie-Scattering Profiles Measured by Lidar

article en

Abstract

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.

Remote SensingVol. 18(7)
Chinese Academy of Sciences (CN), JAC Motors (China) (CN), Anhui Institute of Optics and Fine Mechanics (CN)
Openalex Percentile: Top 8%
Atmospheric aerosols and clouds
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Meteorological Factors Attribution Analysis of Aerosol Layer Structure Changes in Mie-Scattering Profiles Measured by Lidar · Remote Sensing (2026) | TGRS Research Map | TGRS