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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/amt-2018-435
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-2018-435
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 07 Jan 2019

Research article | 07 Jan 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Atmospheric Measurement Techniques (AMT).

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

Sebastian J. O'Shea1, Jonathan Crosier1,2, James Dorsey1,2, Waldemar Schledewitz1, Ian Crawford1, Stephan Borrmann3,4, Richard Cotton5, and Aaron Bansemer6 Sebastian J. O'Shea et al.
  • 1School of Earth and Environmental Sciences, University of Manchester, Manchester, UK
  • 2National Centre for Atmospheric Science, University of Manchester, Manchester, UK
  • 3Particle Chemistry Department, Max Planck Institute for Chemistry, Mainz, Germany
  • 4Institute for Atmospheric Physics, Johannes Gutenberg University, Mainz, Germany
  • 5Met Office, Exeter, UK
  • 6National Center for Atmospheric Research, Boulder CO, USA

Abstract. 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 (< 60 µm) 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 OAP’s. We also raise the issue of bias in OAP’s which have no greyscale capability.

Sebastian J. O'Shea et al.
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Status: final response (author comments only)
Status: final response (author comments only)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Sebastian J. O'Shea et al.
Sebastian J. O'Shea et al.
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Short summary
Optical array probe measurements of clouds are widely used to inform and validate numerical weather and climate models. In this paper, we discuss artefacts which may bias data from these instruments. Using laboratory and synthetic datasets, we demonstrate how greyscale analysis can be used to filter data, constraining the sample volume, and improving data quality particularly at small sizes where their measurements are considered unreliable.
Optical array probe measurements of clouds are widely used to inform and validate numerical...
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