SID-3 Liquid and Ice Phase Particle Size Distributions measured during ACLOUD

This data set contains particle size distributions of spherical and aspherical cloud particles between 5 and 45 microns with a 10-second time resolution calculated from the Small Ice Detector Mark 3 (SID-3). The SID-3 detects individual cloud particles passing a 532 nm laser beam using two nested tr...

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Main Authors: Järvinen, Emma, Schnaiter, M.
Format: Book
Language:unknown
Published: 2023
Subjects:
Online Access:https://publikationen.bibliothek.kit.edu/1000159945
https://doi.org/10.35097/1602
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spelling ftubkarlsruhe:oai:EVASTAR-Karlsruhe.de:1000159945 2023-07-30T04:01:43+02:00 SID-3 Liquid and Ice Phase Particle Size Distributions measured during ACLOUD Järvinen, Emma Schnaiter, M. 2023-06-29 https://publikationen.bibliothek.kit.edu/1000159945 https://doi.org/10.35097/1602 unknown https://publikationen.bibliothek.kit.edu/1000159945 https://doi.org/10.35097/1602 https://creativecommons.org/licenses/by/4.0/deed.de info:eu-repo/semantics/openAccess Arctic mixed-phase clouds ice crystals small ice ddc:550 Earth sciences info:eu-repo/classification/ddc/550 doc-type:ResearchData Dataset info:eu-repo/semantics/book info:eu-repo/semantics/publishedVersion 2023 ftubkarlsruhe https://doi.org/10.35097/1602 2023-07-09T22:09:09Z This data set contains particle size distributions of spherical and aspherical cloud particles between 5 and 45 microns with a 10-second time resolution calculated from the Small Ice Detector Mark 3 (SID-3). The SID-3 detects individual cloud particles passing a 532 nm laser beam using two nested trigger detectors. The trigger signal is recorded as a histogram with a maximum rate of 11 kHz that can be used to derive particle size distributions by using the procedure described in Vochezer et al. (2016), doi:10.5194/amt-9-159-2016. For a sub-set of triggered particles a two-dimensional (2-D) scattering pattern is recorded that can be analysed for particle sphericity by a specifically developed image analysis software. Occasionally, coincidence sampling in the camera field of view causes optical distortions of the 2-D scattering patterns of liquid droplets and, consequently, a misclassification of such scattering patterns to be aspherical by the classification software. For the subsequent identification and re-classification of coincidence scattering patterns a machine learning (ML) algorithm was developed. From the numbers of observed spherical and aspherical 2-D scattering patterns the fractions of spherical and aspherical particles are derived. Multiplication of those number-based fractions with the total particle size distribution yields phase-specific particle size distribution. The uncertainty due to the fact that the imaged particles are a subset of all sampled particles can be estimated from the Clopper–Pearson confidence limits. The data was collected during the Arctic CLoud Observations Using airborne measurements during polar Day (ACLOUD) campaign, which was conducted northwest of Svalbard (Norway) between May 23 and June 6, 2017. The measurement area comprises an area north of Svalbard, approximately between 78 and 82°N. The SID-3 instrument was installed in the Polar-6 aircraft during the ACLOUD campaign. The data is in NetCDF format and contains the total number concentration, the total particle size ... Book Arctic Svalbard KITopen (Karlsruhe Institute of Technologie) Arctic Norway Svalbard
institution Open Polar
collection KITopen (Karlsruhe Institute of Technologie)
op_collection_id ftubkarlsruhe
language unknown
topic Arctic
mixed-phase
clouds
ice crystals
small ice
ddc:550
Earth sciences
info:eu-repo/classification/ddc/550
spellingShingle Arctic
mixed-phase
clouds
ice crystals
small ice
ddc:550
Earth sciences
info:eu-repo/classification/ddc/550
Järvinen, Emma
Schnaiter, M.
SID-3 Liquid and Ice Phase Particle Size Distributions measured during ACLOUD
topic_facet Arctic
mixed-phase
clouds
ice crystals
small ice
ddc:550
Earth sciences
info:eu-repo/classification/ddc/550
description This data set contains particle size distributions of spherical and aspherical cloud particles between 5 and 45 microns with a 10-second time resolution calculated from the Small Ice Detector Mark 3 (SID-3). The SID-3 detects individual cloud particles passing a 532 nm laser beam using two nested trigger detectors. The trigger signal is recorded as a histogram with a maximum rate of 11 kHz that can be used to derive particle size distributions by using the procedure described in Vochezer et al. (2016), doi:10.5194/amt-9-159-2016. For a sub-set of triggered particles a two-dimensional (2-D) scattering pattern is recorded that can be analysed for particle sphericity by a specifically developed image analysis software. Occasionally, coincidence sampling in the camera field of view causes optical distortions of the 2-D scattering patterns of liquid droplets and, consequently, a misclassification of such scattering patterns to be aspherical by the classification software. For the subsequent identification and re-classification of coincidence scattering patterns a machine learning (ML) algorithm was developed. From the numbers of observed spherical and aspherical 2-D scattering patterns the fractions of spherical and aspherical particles are derived. Multiplication of those number-based fractions with the total particle size distribution yields phase-specific particle size distribution. The uncertainty due to the fact that the imaged particles are a subset of all sampled particles can be estimated from the Clopper–Pearson confidence limits. The data was collected during the Arctic CLoud Observations Using airborne measurements during polar Day (ACLOUD) campaign, which was conducted northwest of Svalbard (Norway) between May 23 and June 6, 2017. The measurement area comprises an area north of Svalbard, approximately between 78 and 82°N. The SID-3 instrument was installed in the Polar-6 aircraft during the ACLOUD campaign. The data is in NetCDF format and contains the total number concentration, the total particle size ...
format Book
author Järvinen, Emma
Schnaiter, M.
author_facet Järvinen, Emma
Schnaiter, M.
author_sort Järvinen, Emma
title SID-3 Liquid and Ice Phase Particle Size Distributions measured during ACLOUD
title_short SID-3 Liquid and Ice Phase Particle Size Distributions measured during ACLOUD
title_full SID-3 Liquid and Ice Phase Particle Size Distributions measured during ACLOUD
title_fullStr SID-3 Liquid and Ice Phase Particle Size Distributions measured during ACLOUD
title_full_unstemmed SID-3 Liquid and Ice Phase Particle Size Distributions measured during ACLOUD
title_sort sid-3 liquid and ice phase particle size distributions measured during acloud
publishDate 2023
url https://publikationen.bibliothek.kit.edu/1000159945
https://doi.org/10.35097/1602
geographic Arctic
Norway
Svalbard
geographic_facet Arctic
Norway
Svalbard
genre Arctic
Svalbard
genre_facet Arctic
Svalbard
op_relation https://publikationen.bibliothek.kit.edu/1000159945
https://doi.org/10.35097/1602
op_rights https://creativecommons.org/licenses/by/4.0/deed.de
info:eu-repo/semantics/openAccess
op_doi https://doi.org/10.35097/1602
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