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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-2019-36
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-2019-36
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 22 Feb 2019

Research article | 22 Feb 2019

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

A High Speed Particle Phase Discriminator (PPD-HS) for the classification of airborne particles, as tested in a continuous flow diffusion chamber

Fabian Mahrt1, Jörg Wieder1, Remo Dietlicher1,a, Helen R. Smith2, Chris Stopford2, and Zamin A. Kanji1 Fabian Mahrt et al.
  • 1Institute for Atmospheric and Climate Science, ETH Zurich, 8092 Zurich, Switzerland
  • 2Centre for Atmospheric and Climate Physics, University of Hertfordshire, Hatfield, Hertfordshire, AL10 9AB, United Kingdom
  • anow at: Center for Climate System Modeling, ETH Zurich, 8092 Zurich, Switzerland

Abstract. A new instrument, the High Speed Particle Phase Discriminator (PPD-HS) developed at the University of Hertfordshire, for sizing individual cloud hydrometeors and determining their phase is described herein. PPD-HS performs an in-situ analysis of the spatial intensity distribution of near forward scattered light for individual hydrometeors yielding shape properties. Discrimination of spherical and aspherical particles is based on an analysis of the symmetry of the recorded scattering patterns. Scattering patterns are collected onto two linear detector arrays, reducing the complete 2D scattering pattern to scattered light intensities captured onto two linear, one dimensional strips of light sensitive pixels. Using this reduced scattering information, we calculate symmetry indicators that are used for particle shape and ultimately phase analysis. This reduction of information allows for detection rates of a few hundred particles per second.

Here, we present a comprehensive analysis of instrument performance using both spherical and aspherical particles, generated in a well-controlled laboratory setting using a Vibrating Orifice Aerosol Generator (VOAG) and covering a size range of approximately 3–32 micron. We use supervised machine learning to train a random forest model on the VOAG data sets that can be used to classify any particles detected by PPD-HS. Classification results show that the PPD-HS can successfully discriminate between spherical and aspherical particles, with misclassification below 5 % for diameters > 3 micro meter. This phase discrimination method is subsequently applied to classify simulated cloud particles produced in a continuous flow diffusion chamber setup. We report observations of small, near-spherical ice crystals at early stages of the ice nucleation experiments, where shape analysis fails to correctly determine the particle phase. Nevertheless, in case of simultaneous presence of cloud droplets and ice crystals, the introduced particle shape indicators allow for a clear distinction between these two classes independent of optical particle size. We conclude that PPD-HS constitutes a powerful new instrument to size and discriminate phase of cloud hydrometeors and thus study microphysical properties of mixed-phase clouds, that represent a major source of uncertainty in aerosol indirect effect for future climate projections.

Fabian Mahrt et al.
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Short summary
A new instrument, the High Speed Particle Phase Discriminator (PPD-HS), is presented, with the goal to quantify liquid and ice fraction in conditions relevant for mixed-phase clouds. PPD-HS captures the near forward spatial intensity distribution of scattered light on a single particle basis. Symmetry analysis of the scattering pattern is used to determine the shape of the particles, with cloud droplets and ice crystals producing symmetrical and asymmetrical scattering patterns, respectively.
A new instrument, the High Speed Particle Phase Discriminator (PPD-HS), is presented, with the...
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