25 Oct 2022
25 Oct 2022
Status: this preprint is currently under review for the journal ACP.

Single-scattering properties of ellipsoidal dust aerosols constrained by measured dust shape distributions

Yue Huang1,a, Jasper F. Kok1, Masanori Saito2, and Olga Muñoz3 Yue Huang et al.
  • 1Department of Atmospheric and Oceanic Sciences, University of California, Los Angeles, CA 90095, USA
  • 2Department of Atmospheric Sciences, Texas A&M University, College Station, TX 77843, USA
  • 3Instituto de Astrofísica de Andalucía (IAA-CSIC), Granada 18008, Spain
  • anow at: the Earth Institute, Columbia University, New York, NY 10025, USA, and NASA Goddard Institute for Space Studies (GISS), New York, NY 10025, USA

Abstract. Most global aerosol models approximate dust as spherical particles, whereas most remote sensing retrieval algorithms approximate dust as spheroidal particles with a shape distribution that conflicts with measurements. These inconsistent and inaccurate shape assumptions generate biases in dust single-scattering properties. Here, we obtain dust single-scattering properties by approximating dust as tri-axial ellipsoidal particles with observationally constrained shape distributions. We find that, relative to the ellipsoidal dust optics obtained here, the spherical dust 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.

Yue Huang et al.

Status: open (until 17 Dec 2022)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on acp-2022-633', Lei Bi, 16 Nov 2022 reply

Yue Huang et al.

Yue Huang et al.


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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 over the current dust optical models used in models and retrieval algorithms, as quantified by comparisons against laboratory and field observations of dust optics.