Scattering properties and lidar characteristics of Asian dust particles based on realistic shape models

Abstract. The lidar backscattering properties of Asian dust particles, namely the lidar ratio (S) and backscattering depolarization ratio (δ), were studied using a discrete dipole approximation (DDA) model. The three-dimensional morphology of the dust particles was reconstructed in fine detail using the focused ion beam (FIB) tomography technique. An index based on the symmetry of the scattering matrix was developed to assess the convergence of random orientation computation using DDA. Both S and δ exhibit an asymptotic trend with dust particle size: the S initially decreases, while the δ increases with size, before both approach their asymptotic values. The lidar properties were found to have statistically insignificant dependence on effective sphericity. The presence of strongly absorbing minerals, such as magnetite, can greatly reduce the dust's single-scattering albedo and δ. Utilizing the robust asymptotic trend behavior, two parameterization schemes were developed: one to estimate the δ of a single dust particle given its size and the other to estimate the δ of dust particles with a lognormal particle size distribution given the effective radius. The parameterization scheme was compared with results based on the TAMUdust2020 database, showing hexahedrons to reasonably represent realistic geometries with similar physical properties.

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Publication Details

Journal
Atmospheric chemistry and physics
Published
2025-10-22
DOI
https://doi.org/10.5194/acp-25-13359-2025
Citations
1
Primary Topic
Atmospheric aerosols and clouds
Type
article
Field-Weighted Citation Impact
1.11

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article

Scattering properties and lidar characteristics of Asian dust particles based on realistic shape models

Qianqian Song, Jianyu Zheng, Ping Xian Yang, Jiachen Ding et al.
1 citations
Atmospheric chemistry and physics
Atmospheric aerosols and clouds
1.11
article

Scattering properties and lidar characteristics of Asian dust particles based on realistic shape models

Qianqian Song, Jianyu Zheng, Ping Xian Yang, Jiachen Ding, Masanori Saito, A. Luna, Zhibo Zhang, Hongbin Yu
article en
1 citations

Abstract

Abstract. The lidar backscattering properties of Asian dust particles, namely the lidar ratio (S) and backscattering depolarization ratio (δ), were studied using a discrete dipole approximation (DDA) model. The three-dimensional morphology of the dust particles was reconstructed in fine detail using the focused ion beam (FIB) tomography technique. An index based on the symmetry of the scattering matrix was developed to assess the convergence of random orientation computation using DDA. Both S and δ exhibit an asymptotic trend with dust particle size: the S initially decreases, while the δ increases with size, before both approach their asymptotic values. The lidar properties were found to have statistically insignificant dependence on effective sphericity. The presence of strongly absorbing minerals, such as magnetite, can greatly reduce the dust's single-scattering albedo and δ. Utilizing the robust asymptotic trend behavior, two parameterization schemes were developed: one to estimate the δ of a single dust particle given its size and the other to estimate the δ of dust particles with a lognormal particle size distribution given the effective radius. The parameterization scheme was compared with results based on the TAMUdust2020 database, showing hexahedrons to reasonably represent realistic geometries with similar physical properties.

Atmospheric chemistry and physicsVol. 25(20)
University of Wyoming (US), Goddard Space Flight Center (US), Goddard College (US), University of Maryland, Baltimore County (US), Texas A&M University (US)
National Science Foundation, National Aeronautics and Space Administration, University of Maryland, Baltimore County, Nuclear Safety and Security Commission, Directorate for Geosciences, Science Mission Directorate, Division of Atmospheric and Geospace Sciences
Openalex Percentile: Top 18%
Atmospheric aerosols and clouds
1.11
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