Lidar Ratio-Depolarization Ratio Relations of Atmospheric Dust Aerosols: The Super-Spheroid Model and High Spectral Resolution Lidar Observations

Distinct linear polarization of core-shell particles at near-backscattering directions

The degree of linear polarization (-P12/P11) of scattered light by particles with a core-shell structure may display a distinct negative minimum at near-backscattering directions. However, the specific range of microphysical parameters within which this phenomenon occurs and the underlying physical mechanism are still unclear. Therefore, this study systematically investigated the impacts of particle size, shell-core ratio and refractive index on the negative minimum of -P12/P11 at near-backscattering angles for both coated spheres and coated super-spheroids. The findings reveal that the pronounced negative minimum at near-backscattering angles mostly appeared when the size parameter defined in terms of the mean radius was smaller than approximately 14.5 (e.g., the mean radius is smaller than approximately 2 μm at 0.865 µm wavelength) and the shell-core ratio was in a range of 1.4-1.9. The presence of weakly- and moderately-absorptive shells would lead to pronounced negative polarization at near backscattering directions. However, as the core absorption increased, the amplitude of negative minimum decreased and then stabilized. As for coated super-spheroids, the non-sphericity of the shell tended to suppress the negative polarization at near-backscattering directions. As a result, the pronounced negative minimum (<-0.4) mostly appeared when the aspect ratio and roundness of the shell were close to unity (the overall shape of the particle was nearly-spherical). However, the negative minimum of -P12/P11 showed little dependence on the shape of the core. Furthermore, the Debye series approach was employed to investigate the underlying mechanism of the negative minimum of -P12/P11 for coated spheres. The results demonstrated that the interference among the partial waves underwent one internal reflection on the shell-medium interface and, without internal reflection on the core-shell interface, led to the pronounced negative polarization at near-backscattering angles. When the core absorption was significant, the interference became negligible and the amplitude of the negative minimum was suppressed. This study enhances our understanding the scattering characteristic of coated particles and has implications in aerosol classification and polarized remote sensing.

Quantifying the coherent backscatter enhancement of non-spherical particles with discrete dipole approximation

The prevailing backscattering peak associated with the scattering phase function of large non-absorptive particles can be interpreted with the coherent backscatter enhancement (CBE) theory, but has not been explicitly quantified with numerical simulations based on solving Maxwell's equations. In this paper, representative numerical simulations performed with the discrete-dipole-approximation (DDA) model are used to quantify the effect of CBE on the single-scattering phase function. For each scattering case, the particle volume was divided into multiple thin slices parallel to the incident beam. The dipole polarizations in the j'th slice in response to the incident field of the i'th slice were computed, and then the corresponding contribution to the scattering phase function was calculated. Interference between conjugate terms representing reversible wave paths is constructive at the backscattering direction, which corresponds to the CBE. Subsequently, the contribution of CBE to the scattering phase function was quantified by comparing the electric fields calculated with and without the interference between conjugate terms. Results from these numerical simulations are consistent with conclusions obtained from the CBE theory. The simulations also quantitatively explain why it is difficult to identify a CBE-induced backscattering peak for the phase function of small particles and strong-absorptive particles.

Jacobians of single-scattering optical properties of super-spheroids computed using neural networks

In atmospheric aerosol remote sensing and data assimilation studies, the Jacobians of the optical properties of non-spherical aerosol particles are required. Specifically, the partial derivatives of the extinction efficiency factor, single-scattering albedo, asymmetry factor, and scattering matrix should be obtained with respect to microphysical parameters, such as complex refractive indices, shape parameters and size parameters. When a look-up table (LUT) of optical properties of particles is available, the Jacobians traditionally can be calculated using the finite difference method (FDM), but the accuracy of the process depends on the resolution of microphysical parameters. In this paper, a deep learning scheme was proposed for computing Jacobians of the optical properties of super-spheroids, which is a flexible model of non-spherical atmospheric particles. Using the neural networks (NN), the error of the Jacobians in the FDM can be reduced by more than 60%, and the error reduction rate of the Jacobians of the scattering matrix elements can be more than 90%. We also tested the efficiency of the NN for computing the Jacobians. The computation takes 30 seconds for one million samples on a host with an NVIDIA GeForce RTX 3070 GPU. The accuracy and efficiency of the present NN scheme proves it is promising for applications in remote sensing and data assimilation studies.