Application of Radon Transform to Multi-Angle Measurements Made by the Research Scanning Polarimeter: A New Approach to Cloud Tomography. Part I: Theory and Tests on Simulated Data

The Research Scanning Polarimeter (RSP) is an airborne along-track scanner measuring the polarized and total reflectances in 9 spectral channels. The RSP was a prototype for the Aerosol Polarimetery Sensor (APS) launched on-board the NASA Glory satellite. Currently the retrieval algorithms developed...

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Autores principales: Mikhail D. Alexandrov, Claudia Emde, Bastiaan Van Diedenhoven, Brian Cairns
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Publicado: Frontiers Media S.A. 2021
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spelling oai:doaj.org-article:ee801c76b25c4b1ca757109be21af27e2021-11-22T06:30:40ZApplication of Radon Transform to Multi-Angle Measurements Made by the Research Scanning Polarimeter: A New Approach to Cloud Tomography. Part I: Theory and Tests on Simulated Data2673-618710.3389/frsen.2021.791130https://doaj.org/article/ee801c76b25c4b1ca757109be21af27e2021-11-01T00:00:00Zhttps://www.frontiersin.org/articles/10.3389/frsen.2021.791130/fullhttps://doaj.org/toc/2673-6187The Research Scanning Polarimeter (RSP) is an airborne along-track scanner measuring the polarized and total reflectances in 9 spectral channels. The RSP was a prototype for the Aerosol Polarimetery Sensor (APS) launched on-board the NASA Glory satellite. Currently the retrieval algorithms developed for the RSP are being adopted for the measurements of the space-borne polarimeters on the upcoming NASA’s Plankton, Aerosol, Cloud Ocean Ecosystem (PACE) satellite mission. The RSP’s uniquely high angular resolution coupled with the high frequency of measurements allows for characterization of liquid water cloud droplet sizes using the polarized rainbow structure. It also provides geometric constraints on the cumulus cloud’s 2D cross section yielding the cloud’s geometric shape estimates. In this study we further build on the latter technique to develop a new tomographic approach to retrieval of cloud internal structure from remote sensing measurements. While tomography in the strict definition is a technique based on active measurements yielding a tomogram (directional optical thickness as a function of angle and offset of the view ray), we developed a “semi-tomographic” approach in which tomogram of the cloud is estimated from passive observations instead of being measured directly. This tomogram is then converted into 2D spatial distribution of the extinction coefficient using inverse Radon transform (filtered backprojection) which is the standard tomographic procedure used e.g., in medical CT scans. This algorithm is computationally inexpensive compared to techniques relying on highly-multi-dimensional least-square fitting; it does not require iterative 3D RT simulations. The resulting extinction distribution is defined up to an unknown constant factor, so we discuss the ways to calibrate it using additional independent measurements. In the next step we use the profile of the droplet size distribution parameters from the cloud’s side (derived by fitting the polarized rainbows) to convert the 2D extinction distribution into that of the droplet number concentration. We illustrate and validate the proposed technique using 3D-RT-simulated RSP observations of a LES-generated Cu cloud. Quantitative comparisons between the retrieved and the original optical and microphysical parameters are presented.Mikhail D. AlexandrovMikhail D. AlexandrovClaudia EmdeBastiaan Van DiedenhovenBrian CairnsFrontiers Media S.A.articlecloudstomographyradon transformresearch scanning polarimeterreflectanceairborne remote sensingGeophysics. Cosmic physicsQC801-809Meteorology. ClimatologyQC851-999ENFrontiers in Remote Sensing, Vol 2 (2021)
institution DOAJ
collection DOAJ
language EN
topic clouds
tomography
radon transform
research scanning polarimeter
reflectance
airborne remote sensing
Geophysics. Cosmic physics
QC801-809
Meteorology. Climatology
QC851-999
spellingShingle clouds
tomography
radon transform
research scanning polarimeter
reflectance
airborne remote sensing
Geophysics. Cosmic physics
QC801-809
Meteorology. Climatology
QC851-999
Mikhail D. Alexandrov
Mikhail D. Alexandrov
Claudia Emde
Bastiaan Van Diedenhoven
Brian Cairns
Application of Radon Transform to Multi-Angle Measurements Made by the Research Scanning Polarimeter: A New Approach to Cloud Tomography. Part I: Theory and Tests on Simulated Data
description The Research Scanning Polarimeter (RSP) is an airborne along-track scanner measuring the polarized and total reflectances in 9 spectral channels. The RSP was a prototype for the Aerosol Polarimetery Sensor (APS) launched on-board the NASA Glory satellite. Currently the retrieval algorithms developed for the RSP are being adopted for the measurements of the space-borne polarimeters on the upcoming NASA’s Plankton, Aerosol, Cloud Ocean Ecosystem (PACE) satellite mission. The RSP’s uniquely high angular resolution coupled with the high frequency of measurements allows for characterization of liquid water cloud droplet sizes using the polarized rainbow structure. It also provides geometric constraints on the cumulus cloud’s 2D cross section yielding the cloud’s geometric shape estimates. In this study we further build on the latter technique to develop a new tomographic approach to retrieval of cloud internal structure from remote sensing measurements. While tomography in the strict definition is a technique based on active measurements yielding a tomogram (directional optical thickness as a function of angle and offset of the view ray), we developed a “semi-tomographic” approach in which tomogram of the cloud is estimated from passive observations instead of being measured directly. This tomogram is then converted into 2D spatial distribution of the extinction coefficient using inverse Radon transform (filtered backprojection) which is the standard tomographic procedure used e.g., in medical CT scans. This algorithm is computationally inexpensive compared to techniques relying on highly-multi-dimensional least-square fitting; it does not require iterative 3D RT simulations. The resulting extinction distribution is defined up to an unknown constant factor, so we discuss the ways to calibrate it using additional independent measurements. In the next step we use the profile of the droplet size distribution parameters from the cloud’s side (derived by fitting the polarized rainbows) to convert the 2D extinction distribution into that of the droplet number concentration. We illustrate and validate the proposed technique using 3D-RT-simulated RSP observations of a LES-generated Cu cloud. Quantitative comparisons between the retrieved and the original optical and microphysical parameters are presented.
format article
author Mikhail D. Alexandrov
Mikhail D. Alexandrov
Claudia Emde
Bastiaan Van Diedenhoven
Brian Cairns
author_facet Mikhail D. Alexandrov
Mikhail D. Alexandrov
Claudia Emde
Bastiaan Van Diedenhoven
Brian Cairns
author_sort Mikhail D. Alexandrov
title Application of Radon Transform to Multi-Angle Measurements Made by the Research Scanning Polarimeter: A New Approach to Cloud Tomography. Part I: Theory and Tests on Simulated Data
title_short Application of Radon Transform to Multi-Angle Measurements Made by the Research Scanning Polarimeter: A New Approach to Cloud Tomography. Part I: Theory and Tests on Simulated Data
title_full Application of Radon Transform to Multi-Angle Measurements Made by the Research Scanning Polarimeter: A New Approach to Cloud Tomography. Part I: Theory and Tests on Simulated Data
title_fullStr Application of Radon Transform to Multi-Angle Measurements Made by the Research Scanning Polarimeter: A New Approach to Cloud Tomography. Part I: Theory and Tests on Simulated Data
title_full_unstemmed Application of Radon Transform to Multi-Angle Measurements Made by the Research Scanning Polarimeter: A New Approach to Cloud Tomography. Part I: Theory and Tests on Simulated Data
title_sort application of radon transform to multi-angle measurements made by the research scanning polarimeter: a new approach to cloud tomography. part i: theory and tests on simulated data
publisher Frontiers Media S.A.
publishDate 2021
url https://doaj.org/article/ee801c76b25c4b1ca757109be21af27e
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