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Abstract Sensitivities of the backscattering properties to the microphysical properties (in particular, size and shape) of mineral dust aerosols are examined based on TAMUdust2020, a comprehensive single‐scattering property database of irregular aerosol particles. We develop the bulk mineral dust particle models based on size‐resolved particle ensembles with randomly distorted shapes and spectrally resolved complex refractive indices, which are constrained by using in situ observations reported in the literature. The light detection and ranging (lidar) ratio is more sensitive to particle shape than particle size, while the depolarization ratio depends strongly on particle size. The simulated bulk backscattering properties (i.e., the lidar ratio and the depolarization ratio) of typical mineral dust particles with effective radii of 0.5–3 µm are reasonably consistent with lidar observations made during several field campaigns. The present dust bulk optical property models are applicable to lidar‐based remote sensing of dust aerosol properties.
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Single-scattering properties of ellipsoidal dust aerosols constrained by measured dust shape distributions
Abstract. Most global aerosol models approximate dust as sphericalparticles, whereas most remote sensing retrieval algorithms approximate dust as spheroidal particles with a shape distribution that conflicts withmeasurements. These inconsistent and inaccurate shape assumptions generatebiases in dust single-scattering properties. Here, we obtain dustsingle-scattering properties by approximating dust as triaxial ellipsoidalparticles with observationally constrained shape distributions. We findthat, relative to the ellipsoidal dust optics obtained here, the sphericaldust optics used in most aerosol models underestimate dust single-scattering albedo, mass extinction efficiency, and asymmetry parameter for almost all dust sizes in both the shortwave and longwave spectra. We further find that the ellipsoidal dust optics are in substantially better agreement with observations of the scattering matrix and linear depolarization ratio than the spheroidal dust optics used in most retrieval algorithms. However, relative to observations, the ellipsoidal dust optics overestimate the lidar ratio by underestimating the backscattering intensity by a factor of ∼2. This occurs largely because the computational method used to simulate ellipsoidal dust optics (i.e., the improved geometric optics method) underestimates the backscattering intensity by a factor of ∼2 relative to other computational methods (e.g., the physical geometric optics method). We conclude that the ellipsoidal dust optics with observationally constrained shape distributions can help improve global aerosol models and possibly remote sensing retrieval algorithms that do not use the backscattering signal.
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- Award ID(s):
- 1856389
- PAR ID:
- 10546046
- Publisher / Repository:
- Huang_2023_ACP_dust_optical_properties
- Date Published:
- Journal Name:
- Atmospheric Chemistry and Physics
- Volume:
- 23
- Issue:
- 4
- ISSN:
- 1680-7324
- Page Range / eLocation ID:
- 2557 to 2577
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.5194/acp-23-2557-2023
