Evaluation of Non-Spherical Particle Models for Mineral Dust in Multi-Wavelength Polarization Lidar Applications: Comparison of Spheroid, Super-Ellipsoid, and Irregular-Hexagonal Models

Mineral dust aerosols play an important role in the Earth’s radiation budget and climate system, and their optical properties strongly influence the accuracy of polarization lidar retrievals. Developing realistic optical models is therefore essential for representing dust scattering and polarization behaviors. This study compares three shape models—spheroid, super-ellipsoid, and irregular-hexagonal—in reproducing the optical characteristics of mineral dust at wavelengths of 355, 532, and 1064 nanometers. By combining theoretical simulations with multi-wavelength field and laboratory observations, the suitability of each model is evaluated. Optimal combinations of particle shape and refractive index are obtained using the sum of squared errors criterion. The results show that both the irregular-hexagonal and super-ellipsoid models reproduce the observed relationships between the particle linear depolarization ratio and the lidar ratio, whereas the spheroid model fails to capture high depolarization values. Shape mixing analyses indicate that the irregular-hexagonal model is relatively insensitive to morphological variation, while the super-ellipsoid model exhibits higher adaptability. When measurement uncertainties are considered, the super-ellipsoid model performs best under low error conditions, whereas the irregular-hexagonal model remains more robust under high error conditions. These findings highlight the importance of realistic shape distributions in dust optical modeling and support more reliable polarization lidar retrievals.

Authors

Institutions

Publication Details

Journal
Remote Sensing
Published
2025-11-24
DOI
https://doi.org/10.3390/rs17233804
Primary Topic
Atmospheric aerosols and clouds
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Evaluation of Non-Spherical Particle Models for Mineral Dust in Multi-Wavelength Polarization Lidar Applications: Comparison of Spheroid, Super-Ellipsoid, and Irregular-Hexagonal Models

Laibin Wang, Dong Liu
Remote Sensing
Atmospheric aerosols and clouds
article

Evaluation of Non-Spherical Particle Models for Mineral Dust in Multi-Wavelength Polarization Lidar Applications: Comparison of Spheroid, Super-Ellipsoid, and Irregular-Hexagonal Models

Laibin Wang, Dong Liu
article en

Abstract

Mineral dust aerosols play an important role in the Earth’s radiation budget and climate system, and their optical properties strongly influence the accuracy of polarization lidar retrievals. Developing realistic optical models is therefore essential for representing dust scattering and polarization behaviors. This study compares three shape models—spheroid, super-ellipsoid, and irregular-hexagonal—in reproducing the optical characteristics of mineral dust at wavelengths of 355, 532, and 1064 nanometers. By combining theoretical simulations with multi-wavelength field and laboratory observations, the suitability of each model is evaluated. Optimal combinations of particle shape and refractive index are obtained using the sum of squared errors criterion. The results show that both the irregular-hexagonal and super-ellipsoid models reproduce the observed relationships between the particle linear depolarization ratio and the lidar ratio, whereas the spheroid model fails to capture high depolarization values. Shape mixing analyses indicate that the irregular-hexagonal model is relatively insensitive to morphological variation, while the super-ellipsoid model exhibits higher adaptability. When measurement uncertainties are considered, the super-ellipsoid model performs best under low error conditions, whereas the irregular-hexagonal model remains more robust under high error conditions. These findings highlight the importance of realistic shape distributions in dust optical modeling and support more reliable polarization lidar retrievals.

Remote SensingVol. 17(23)
University of Science and Technology of China (CN), Hefei University of Technology (CN), Chinese Academy of Sciences (CN), Anhui Institute of Optics and Fine Mechanics (CN)
Openalex Percentile: Top 66%
Atmospheric aerosols and clouds
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.