Revisiting particle sizing using greyscale optical array probes: evaluation using laboratory experiments and synthetic data

<p>In situ observations from research aircraft and instrumented ground sites are important contributions to developing our collective understanding of clouds and are used to inform and validate numerical weather and climate models. Unfortunately, biases in these datasets may be present, which...

Full description

Bibliographic Details
Main Authors: S. J. O'Shea, J. Crosier, J. Dorsey, W. Schledewitz, I. Crawford, S. Borrmann, R. Cotton, A. Bansemer
Format: Article
Language:English
Published: Copernicus Publications 2019-06-01
Series:Atmospheric Measurement Techniques
Online Access:https://www.atmos-meas-tech.net/12/3067/2019/amt-12-3067-2019.pdf
id doaj-e0e6f4c54e4f45ebbbd26de87e63f310
record_format Article
spelling doaj-e0e6f4c54e4f45ebbbd26de87e63f3102020-11-25T00:29:05ZengCopernicus PublicationsAtmospheric Measurement Techniques1867-13811867-85482019-06-01123067307910.5194/amt-12-3067-2019Revisiting particle sizing using greyscale optical array probes: evaluation using laboratory experiments and synthetic dataS. J. O'Shea0J. Crosier1J. Crosier2J. Dorsey3J. Dorsey4W. Schledewitz5I. Crawford6S. Borrmann7S. Borrmann8R. Cotton9A. Bansemer10School of Earth and Environmental Sciences, University of Manchester, Manchester, UKSchool of Earth and Environmental Sciences, University of Manchester, Manchester, UKNational Centre for Atmospheric Science, University of Manchester, Manchester, UKSchool of Earth and Environmental Sciences, University of Manchester, Manchester, UKNational Centre for Atmospheric Science, University of Manchester, Manchester, UKSchool of Earth and Environmental Sciences, University of Manchester, Manchester, UKSchool of Earth and Environmental Sciences, University of Manchester, Manchester, UKParticle Chemistry Department, Max Planck Institute for Chemistry, Mainz, GermanyInstitute for Atmospheric Physics, Johannes Gutenberg University, Mainz, GermanyMet Office, Exeter, UKNational Center for Atmospheric Research, Boulder, CO, USA<p>In situ observations from research aircraft and instrumented ground sites are important contributions to developing our collective understanding of clouds and are used to inform and validate numerical weather and climate models. Unfortunately, biases in these datasets may be present, which can limit their value. In this paper, we discuss artefacts which may bias data from a widely used family of instrumentation in the field of cloud physics, optical array probes (OAPs). Using laboratory and synthetic datasets, we demonstrate how greyscale analysis can be used to filter data, constraining the sample volume of the OAP and improving data quality, particularly at small sizes where OAP data are considered unreliable. We apply the new methodology to ambient data from two contrasting case studies: one warm cloud and one cirrus cloud. In both cases the new methodology reduces the concentration of small particles (&lt;60&thinsp;<span class="inline-formula">µ</span>m) by approximately an order of magnitude. This significantly improves agreement with a Mie-scattering spectrometer for the liquid case and with a holographic imaging probe for the cirrus case. Based on these results, we make specific recommendations to instrument manufacturers, instrument operators and data processors about the optimal use of greyscale OAPs. The data from monoscale OAPs are unreliable and should not be used for particle diameters below approximately 100&thinsp;<span class="inline-formula">µ</span>m.</p>https://www.atmos-meas-tech.net/12/3067/2019/amt-12-3067-2019.pdf
collection DOAJ
language English
format Article
sources DOAJ
author S. J. O'Shea
J. Crosier
J. Crosier
J. Dorsey
J. Dorsey
W. Schledewitz
I. Crawford
S. Borrmann
S. Borrmann
R. Cotton
A. Bansemer
spellingShingle S. J. O'Shea
J. Crosier
J. Crosier
J. Dorsey
J. Dorsey
W. Schledewitz
I. Crawford
S. Borrmann
S. Borrmann
R. Cotton
A. Bansemer
Revisiting particle sizing using greyscale optical array probes: evaluation using laboratory experiments and synthetic data
Atmospheric Measurement Techniques
author_facet S. J. O'Shea
J. Crosier
J. Crosier
J. Dorsey
J. Dorsey
W. Schledewitz
I. Crawford
S. Borrmann
S. Borrmann
R. Cotton
A. Bansemer
author_sort S. J. O'Shea
title Revisiting particle sizing using greyscale optical array probes: evaluation using laboratory experiments and synthetic data
title_short Revisiting particle sizing using greyscale optical array probes: evaluation using laboratory experiments and synthetic data
title_full Revisiting particle sizing using greyscale optical array probes: evaluation using laboratory experiments and synthetic data
title_fullStr Revisiting particle sizing using greyscale optical array probes: evaluation using laboratory experiments and synthetic data
title_full_unstemmed Revisiting particle sizing using greyscale optical array probes: evaluation using laboratory experiments and synthetic data
title_sort revisiting particle sizing using greyscale optical array probes: evaluation using laboratory experiments and synthetic data
publisher Copernicus Publications
series Atmospheric Measurement Techniques
issn 1867-1381
1867-8548
publishDate 2019-06-01
description <p>In situ observations from research aircraft and instrumented ground sites are important contributions to developing our collective understanding of clouds and are used to inform and validate numerical weather and climate models. Unfortunately, biases in these datasets may be present, which can limit their value. In this paper, we discuss artefacts which may bias data from a widely used family of instrumentation in the field of cloud physics, optical array probes (OAPs). Using laboratory and synthetic datasets, we demonstrate how greyscale analysis can be used to filter data, constraining the sample volume of the OAP and improving data quality, particularly at small sizes where OAP data are considered unreliable. We apply the new methodology to ambient data from two contrasting case studies: one warm cloud and one cirrus cloud. In both cases the new methodology reduces the concentration of small particles (&lt;60&thinsp;<span class="inline-formula">µ</span>m) by approximately an order of magnitude. This significantly improves agreement with a Mie-scattering spectrometer for the liquid case and with a holographic imaging probe for the cirrus case. Based on these results, we make specific recommendations to instrument manufacturers, instrument operators and data processors about the optimal use of greyscale OAPs. The data from monoscale OAPs are unreliable and should not be used for particle diameters below approximately 100&thinsp;<span class="inline-formula">µ</span>m.</p>
url https://www.atmos-meas-tech.net/12/3067/2019/amt-12-3067-2019.pdf
work_keys_str_mv AT sjoshea revisitingparticlesizingusinggreyscaleopticalarrayprobesevaluationusinglaboratoryexperimentsandsyntheticdata
AT jcrosier revisitingparticlesizingusinggreyscaleopticalarrayprobesevaluationusinglaboratoryexperimentsandsyntheticdata
AT jcrosier revisitingparticlesizingusinggreyscaleopticalarrayprobesevaluationusinglaboratoryexperimentsandsyntheticdata
AT jdorsey revisitingparticlesizingusinggreyscaleopticalarrayprobesevaluationusinglaboratoryexperimentsandsyntheticdata
AT jdorsey revisitingparticlesizingusinggreyscaleopticalarrayprobesevaluationusinglaboratoryexperimentsandsyntheticdata
AT wschledewitz revisitingparticlesizingusinggreyscaleopticalarrayprobesevaluationusinglaboratoryexperimentsandsyntheticdata
AT icrawford revisitingparticlesizingusinggreyscaleopticalarrayprobesevaluationusinglaboratoryexperimentsandsyntheticdata
AT sborrmann revisitingparticlesizingusinggreyscaleopticalarrayprobesevaluationusinglaboratoryexperimentsandsyntheticdata
AT sborrmann revisitingparticlesizingusinggreyscaleopticalarrayprobesevaluationusinglaboratoryexperimentsandsyntheticdata
AT rcotton revisitingparticlesizingusinggreyscaleopticalarrayprobesevaluationusinglaboratoryexperimentsandsyntheticdata
AT abansemer revisitingparticlesizingusinggreyscaleopticalarrayprobesevaluationusinglaboratoryexperimentsandsyntheticdata
_version_ 1725333468229926912