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

Levis, Aviad and Schechner, Yoav Y. and Davis, Anthony B. and Loveridge, Jesse (2020) Multi-View Polarimetric Scattering Cloud Tomography and Retrieval of Droplet Size. Remote Sensing, 12 (17). Art. No. 2831. ISSN 2072-4292. https://resolver.caltech.edu/CaltechAUTHORS:20200911-133129971

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Abstract

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.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.3390/rs12172831DOIArticle
ORCID:
AuthorORCID
Loveridge, Jesse0000-0002-7127-6907
Additional Information:© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). Received: 30 July 2020 / Revised: 26 August 2020 / Accepted: 28 August 2020 / Published: 1 September 2020. (This article belongs to the Special Issue Remote Sensing of Cloud and Aerosol Properties in a Three-Dimensional Atmosphere) We thank I. Koren, D. Rosenfeld, A. Aides, D. Diner, L. Di Girolamo, and G. Matheou for support and fruitful discussions. We acknowledge F. Evans and A. Doicu for the online vSHDOM code. The authors are grateful to the US-Israel Binational Science Foundation (BSF grant 2016325) for continuously facilitating our international collaboration. Aviad Levis’ work was partially supported as a Zuckerman Foundation STEM Leadership Fellow. Yoav Schechner is a Landau Fellow supported by the Taub Foundation. His work was conducted in the Ollendorff Minerva Center (BMBF). Anthony Davis’ work was carried out at JPL/Caltech, supported by NASA’s SMD/ESD/(RST+TASNPP) and ESTO/AIST programs. That research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration (80NM0018D0004). Support for Jesse Loveridge’s work from JPL under contract #147871 is gratefully acknowledged. This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (grant agreement No 810370: CloudCT). Author Contributions. Conceptualization, A.L. and Y.Y.S.; methodology, A.L., Y.Y.S., A.B.D.; software, A.L., J.L.; validation, A.L. and J.L.; formal analysis, A.L.; investigation, A.L.; resources, Y.Y.S.; data curation, A.L. and J.L.; writing—original draft preparation, A.L.; writing—review and editing, A.L., Y.Y.S., A.B.D. and J.L.; visualization, A.L.; supervision, Y.Y.S.; project administration, A.L. and Y.Y.S.; funding acquisition, Y.Y.S. All authors have read and agreed to the published version of the manuscript. The authors declare no conflict of interest.
Funders:
Funding AgencyGrant Number
Binational Science Foundation (USA-Israel)2016325
Zuckerman FoundationUNSPECIFIED
Massachusetts Institute of Technology (MIT)UNSPECIFIED
Henry and Marilyn Taub FoundationUNSPECIFIED
NASA80NM0018D0004
JPL147871
European Research Council (ERC)810370
Subject Keywords:polarization; 3D radiative transfer; inverse problems; tomography; remote sensing; convective clouds; cloud microphysics
Issue or Number:17
Record Number:CaltechAUTHORS:20200911-133129971
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20200911-133129971
Official Citation: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.
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:105329
Collection:CaltechAUTHORS
Deposited By: George Porter
Deposited On:15 Sep 2020 20:35
Last Modified:15 Sep 2020 20:35

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