Articles | Volume 23, issue 4
https://doi.org/10.5194/acp-23-2557-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-23-2557-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
23 Feb 2023
Research article |
| 23 Feb 2023
| 23 Feb 2023
Single-scattering properties of ellipsoidal dust aerosols constrained by measured dust shape distributions
Department of Atmospheric and Oceanic Sciences, University of
California, Los Angeles, CA 90095, USA
now at: Earth Institute, Columbia University, New York, NY 10025,
USA
NASA Goddard Institute for Space Studies (GISS), New York, NY
10025, USA
Jasper F. Kok
Department of Atmospheric and Oceanic Sciences, University of
California, Los Angeles, CA 90095, USA
Masanori Saito
Department of Atmospheric Sciences, Texas A&M University, College Station, TX 77843, USA
Olga Muñoz
Instituto de Astrofísica de Andalucía (IAA-CSIC), Granada
18008, Spain
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- Inter-comparison of different order-scattering models for accurate sensing in dusty conditions S. Nejjari et al. https://doi.org/10.1016/j.jqsrt.2025.109760
- Numerical investigation on size retrieval error for coated dust aerosol with different shape distributions based on spherical shape assumption and the effects on radiative estimation J. Liu et al. https://doi.org/10.1016/j.jqsrt.2025.109792
- Update Granada–Amsterdam Light Scattering Database O. Muñoz et al. https://doi.org/10.1016/j.jqsrt.2024.109252
- The scattering properties of aerosol particles with topological structures Y. Li & W. Wu https://doi.org/10.1016/j.jqsrt.2026.109937
- Scattering-physics-constrained neural network framework for retrieving dust microphysical properties from scattering matrix measurements Y. Xi & L. Bi https://doi.org/10.1016/j.jqsrt.2026.109859
- Insights into microphysical and optical properties of typical mineral dust within urban snowpack via wet and dry deposition in Changchun, northeastern China T. Shi et al. https://doi.org/10.5194/tc-19-2821-2025
- A model-based estimate for the direct radiative effect of atmospheric microplastics Q. Pang et al. https://doi.org/10.1016/j.atmosenv.2025.121305
- Retrieval of microphysical properties of dust aerosols from extinction, backscattering and depolarization lidar measurements using various particle scattering models Y. Chang et al. https://doi.org/10.5194/acp-25-6787-2025
- Investigating the link between mineral dust hematite content and intensive optical properties by means of lidar measurements and aerosol modeling S. Gómez Maqueo Anaya et al. https://doi.org/10.5194/acp-25-9737-2025
- Scattering properties and lidar characteristics of Asian dust particles based on realistic shape models A. La Luna et al. https://doi.org/10.5194/acp-25-13359-2025
- Suitability of a group of spheroids with a lognormal shape distribution for modeling the scattering and polarimetric properties of irregular particles J. Luo et al. https://doi.org/10.1016/j.jqsrt.2025.109732
- A new process-based and scale-aware desert dust emission scheme for global climate models – Part II: Evaluation in the Community Earth System Model version 2 (CESM2) D. Leung et al. https://doi.org/10.5194/acp-24-2287-2024
- Cooling from aerosol–radiation interaction of anthropogenic coarse particles in China X. Wang et al. https://doi.org/10.1038/s41612-024-00773-4
- Desert dust exerts twice the longwave radiative heating estimated by climate models J. Kok et al. https://doi.org/10.1038/s41467-026-70952-9
- A systematic bias in present models of circumsolar radiation M. Kocifaj https://doi.org/10.1016/j.solener.2023.112036
Saved (final revised paper)
Latest update: 03 Jun 2026
Short summary
Global aerosol models and remote sensing retrievals use dust optical models with inconsistent and inaccurate dust shape approximations. Here, we present a new dust optical model constrained by measured dust shape distributions. This new dust optical model is an improvement on the current dust optical models used in models and retrieval algorithms, as quantified by comparisons against laboratory and field observations of dust optics.
Global aerosol models and remote sensing retrievals use dust optical models with inconsistent...
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