Improvement in the Computational Efficiency of Physical Geometric Optics Method in Simulating Light Scattering by Large Faceted Dielectric Particles
Abstract
This presentation will show the recent improvement in the computational efficiency of the Physical Geometric Optics Method (PGOM) by a method of accelerating the near-to-far field mapping. The PGOM was developed to compute the single-scattering properties of faceted dielectric particles. As a geometric optics approximation method, the PGOM computation results have been shown to be consistent with those obtained using the numerically exact invariant imbedding T-matrix (II-TM) method for size parameter 150. It takes PGOM about ten seconds on a personal laptop to compute particle single-scattering properties including the scattering phase matrix, extinction efficiency, and single-scattering albedo for one orientation. In the practical application of atmospheric and ocean remote sensing, we usually assume the particle is fully or partially randomly oriented. For particles with large size parameters, obtaining the corresponding averages requires computations for more than ten thousand orientations to obtain accurate orientation-averaged results; acceleration of single orientation computations can thus result in significant savings of CPU time.
The PGOM computes near fields using the beam tracing method. The near fields are mapped to far field by evaluating electromagnetic volume or surface integral. We find that the phase interferences among high beam tracing order (more than two) fields are negligible except for forward and backscattering directions, particularly for particles with large size parameters. We implement the high beam tracing order near-to-far field mapping with a simplified mapping algorithm. The intensity mapping algorithm ignores the phase interferences and is very efficient, thus increasing the computational efficiency of PGOM. In this presentation, we will show the application of the improved PGOM and comparisons with the II-TM results.- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2019
- Bibcode:
- 2019AGUFM.A21Q2624D
- Keywords:
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- 3311 Clouds and aerosols;
- ATMOSPHERIC PROCESSES;
- 3359 Radiative processes;
- ATMOSPHERIC PROCESSES;
- 3360 Remote sensing;
- ATMOSPHERIC PROCESSES;
- 3367 Theoretical modeling;
- ATMOSPHERIC PROCESSES