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Open AccessArticle

Multi-View Polarimetric Scattering Cloud Tomography and Retrieval of Droplet Size

1
Viterbi Faculty of Electrical Engineering, Technion - Israel Institute of Technology, Haifa 3200003, Israel
2
Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA
3
Department of Atmospheric Sciences, University of Illinois, Champaign, IL 61820, USA
*
Author to whom correspondence should be addressed.
Current Address: Computing and Mathematical Sciences Department, California Institute of Technology, Pasadena, CA 91125, USA.
Remote Sens. 2020, 12(17), 2831; https://doi.org/10.3390/rs12172831
Received: 30 July 2020 / Revised: 26 August 2020 / Accepted: 28 August 2020 / Published: 1 September 2020
Tomography aims to recover a three-dimensional (3D) density map of a medium or an object. In medical imaging, it is extensively used for diagnostics via X-ray computed tomography (CT). We define and derive a tomography of cloud droplet distributions via passive remote sensing. We use multi-view polarimetric images to fit a 3D polarized radiative transfer (RT) forward model. Our motivation is 3D volumetric probing of vertically-developed convectively-driven clouds that are ill-served by current methods in operational passive remote sensing. Current techniques are based on strictly 1D RT modeling and applied to a single cloudy pixel, where cloud geometry defaults to that of a plane-parallel slab. Incident unpolarized sunlight, once scattered by cloud-droplets, changes its polarization state according to droplet size. Therefore, polarimetric measurements in the rainbow and glory angular regions can be used to infer the droplet size distribution. This work defines and derives a framework for a full 3D tomography of cloud droplets for both their mass concentration in space and their distribution across a range of sizes. This 3D retrieval of key microphysical properties is made tractable by our novel approach that involves a restructuring and differentiation of an open-source polarized 3D RT code to accommodate a special two-step optimization technique. Physically-realistic synthetic clouds are used to demonstrate the methodology with rigorous uncertainty quantification. View Full-Text
Keywords: polarization; 3D radiative transfer; inverse problems; tomography; remote sensing; convective clouds; cloud microphysics polarization; 3D radiative transfer; inverse problems; tomography; remote sensing; convective clouds; cloud microphysics
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MDPI and ACS Style

Levis, A.; Schechner, Y.Y.; Davis, A.B.; Loveridge, J. Multi-View Polarimetric Scattering Cloud Tomography and Retrieval of Droplet Size. Remote Sens. 2020, 12, 2831.

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