Cloud Thermodynamic Phase Detection with Polarimetrically Sensitive Passive Sky Radiometers

The primary goal of this project has been to investigate if ground-based visible and near-infrared passive radiometers that have polarization sensitivity can determine the thermodynamic phase of overlying clouds, i.e. if they are comprised of liquid droplets or ice particles. While this knowledge is...

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Main Author: Knobelspiesse, Kirk D.
Format: Other/Unknown Material
Language:unknown
Published: 2014
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Online Access:http://hdl.handle.net/2060/20190001073
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spelling ftnasantrs:oai:casi.ntrs.nasa.gov:20190001073 2023-05-15T13:07:16+02:00 Cloud Thermodynamic Phase Detection with Polarimetrically Sensitive Passive Sky Radiometers Knobelspiesse, Kirk D. Unclassified, Unlimited, Publicly available November 6, 2014 application/pdf http://hdl.handle.net/2060/20190001073 unknown Document ID: 20190001073 http://hdl.handle.net/2060/20190001073 No Copyright, Work of the U.S. Government - Public use permitted CASI Geosciences (General) ARC-E-DAA-TN18310 Optical Technology Center (Optec) Colloquium; 6 Nov. 2014; Bozeman, MT; United States 2014 ftnasantrs 2019-07-20T23:05:45Z The primary goal of this project has been to investigate if ground-based visible and near-infrared passive radiometers that have polarization sensitivity can determine the thermodynamic phase of overlying clouds, i.e. if they are comprised of liquid droplets or ice particles. While this knowledge is important by itself for our understanding of the global climate, it can also help improve cloud property retrieval algorithms that use total (unpolarized) radiance to determine Cloud Optical Depth (COD). This is a potentially unexploited capability of some instruments in the NASA Aerosol Robotic Network (AERONET), which, if practical, could expand the products of that global instrument network at minimal additional cost. We performed simulations that found, for zenith observations, cloud thermodynamic phase is often expressed in the sign of the Q component of the Stokes polarization vector. We chose our reference frame as the plane containing solar and observation vectors, so the sign of Q indicates the polarization direction, parallel (negative) or perpendicular (positive) to that plane. Since the quantity of polarization is inversely proportional to COD, optically thin clouds are most likely to create a signal greater than instrument noise. Besides COD and instrument accuracy, other important factors for the determination of cloud thermodynamic phase are the solar and observation geometry (scattering angles between 40 and 60 degrees are best), and the properties of ice particles (pristine particles may have halos or other features that make them difficult to distinguish from water droplets at specific scattering angles, while extreme ice crystal aspect ratios polarize more than compact particles). We tested the conclusions of our simulations using data from polarimetrically sensitive versions of the Cimel 318 sun photometerradiometer that comprise AERONET. Most algorithms that exploit Cimel polarized observations use the Degree of Linear Polarization (DoLP), not the individual Stokes vector elements (such as Q). For this reason, we had no information about the accuracy of Cimel observed Q and the potential for cloud phase determination. Indeed, comparisons to ceilometer observations with a single polarized spectral channel version of the Cimel at a site in the Netherlands showed little correlation. Comparisons to Lidar observations with a more recently developed, multi-wavelength polarized Cimel in Maryland, USA, show more promise. This divergence between simulations and observations has prompted us to begin the development of a small test instrument called the Sky Polarization Radiometric Instrument for Test and Evaluation (SPRITE). This instrument is specifically devoted to the accurate observation of Q, and the testing of calibration and uncertainty assessment techniques, with the ultimate goal of understanding the practical feasibility of these measurements. Other/Unknown Material Aerosol Robotic Network NASA Technical Reports Server (NTRS)
institution Open Polar
collection NASA Technical Reports Server (NTRS)
op_collection_id ftnasantrs
language unknown
topic Geosciences (General)
spellingShingle Geosciences (General)
Knobelspiesse, Kirk D.
Cloud Thermodynamic Phase Detection with Polarimetrically Sensitive Passive Sky Radiometers
topic_facet Geosciences (General)
description The primary goal of this project has been to investigate if ground-based visible and near-infrared passive radiometers that have polarization sensitivity can determine the thermodynamic phase of overlying clouds, i.e. if they are comprised of liquid droplets or ice particles. While this knowledge is important by itself for our understanding of the global climate, it can also help improve cloud property retrieval algorithms that use total (unpolarized) radiance to determine Cloud Optical Depth (COD). This is a potentially unexploited capability of some instruments in the NASA Aerosol Robotic Network (AERONET), which, if practical, could expand the products of that global instrument network at minimal additional cost. We performed simulations that found, for zenith observations, cloud thermodynamic phase is often expressed in the sign of the Q component of the Stokes polarization vector. We chose our reference frame as the plane containing solar and observation vectors, so the sign of Q indicates the polarization direction, parallel (negative) or perpendicular (positive) to that plane. Since the quantity of polarization is inversely proportional to COD, optically thin clouds are most likely to create a signal greater than instrument noise. Besides COD and instrument accuracy, other important factors for the determination of cloud thermodynamic phase are the solar and observation geometry (scattering angles between 40 and 60 degrees are best), and the properties of ice particles (pristine particles may have halos or other features that make them difficult to distinguish from water droplets at specific scattering angles, while extreme ice crystal aspect ratios polarize more than compact particles). We tested the conclusions of our simulations using data from polarimetrically sensitive versions of the Cimel 318 sun photometerradiometer that comprise AERONET. Most algorithms that exploit Cimel polarized observations use the Degree of Linear Polarization (DoLP), not the individual Stokes vector elements (such as Q). For this reason, we had no information about the accuracy of Cimel observed Q and the potential for cloud phase determination. Indeed, comparisons to ceilometer observations with a single polarized spectral channel version of the Cimel at a site in the Netherlands showed little correlation. Comparisons to Lidar observations with a more recently developed, multi-wavelength polarized Cimel in Maryland, USA, show more promise. This divergence between simulations and observations has prompted us to begin the development of a small test instrument called the Sky Polarization Radiometric Instrument for Test and Evaluation (SPRITE). This instrument is specifically devoted to the accurate observation of Q, and the testing of calibration and uncertainty assessment techniques, with the ultimate goal of understanding the practical feasibility of these measurements.
format Other/Unknown Material
author Knobelspiesse, Kirk D.
author_facet Knobelspiesse, Kirk D.
author_sort Knobelspiesse, Kirk D.
title Cloud Thermodynamic Phase Detection with Polarimetrically Sensitive Passive Sky Radiometers
title_short Cloud Thermodynamic Phase Detection with Polarimetrically Sensitive Passive Sky Radiometers
title_full Cloud Thermodynamic Phase Detection with Polarimetrically Sensitive Passive Sky Radiometers
title_fullStr Cloud Thermodynamic Phase Detection with Polarimetrically Sensitive Passive Sky Radiometers
title_full_unstemmed Cloud Thermodynamic Phase Detection with Polarimetrically Sensitive Passive Sky Radiometers
title_sort cloud thermodynamic phase detection with polarimetrically sensitive passive sky radiometers
publishDate 2014
url http://hdl.handle.net/2060/20190001073
op_coverage Unclassified, Unlimited, Publicly available
genre Aerosol Robotic Network
genre_facet Aerosol Robotic Network
op_source CASI
op_relation Document ID: 20190001073
http://hdl.handle.net/2060/20190001073
op_rights No Copyright, Work of the U.S. Government - Public use permitted
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