Abstract
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 2-D 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 µm. 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 µm. 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 the 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. From our laboratory experiments we conclude that PPD-HS constitutes a powerful new instrument to size and discriminate the phase of cloud hydrometeors. The working principle of PPD-HS forms a basis for future instruments to study microphysical properties of atmospheric mixed-phase clouds that represent a major source of uncertainty in aerosol-indirect effect for future climate projections.
Highlights
Microphysical processes in clouds involving ice particles contribute to major uncertainties in cloud formation, evolution and precipitation formation (Mülmenstädt et al, 2015) and subsequently to radiative properties associated with these clouds on both regional and global scales (Matus and L’Ecuyer, 2017; McCoy et al, 2016; Tan et al, 2016)
This is despite the knowledge that cloud particle size distributions comprised of a mixture of cloud droplets and ice crystals are affected by the presence of small ice particles (Lawson et al, 2001; Korolev et al, 2003)
A major challenge in mixed-phase clouds (MPCs) analysis remains the discrimination between cloud droplets and ice crystals
Summary
Microphysical processes in clouds involving ice particles contribute to major uncertainties in cloud formation, evolution and precipitation formation (Mülmenstädt et al, 2015) and subsequently to radiative properties associated with these clouds on both regional and global scales (Matus and L’Ecuyer, 2017; McCoy et al, 2016; Tan et al, 2016). The particle size can theoretically be measured if the wavelength of the incident light and refractive index of the particles under consideration are both known (Baumgardner et al, 2011). Such instruments are widely used for sizing and counting individual particles but usually do not offer techniques to determine cloud particle phase. The particle phase is often segregated based on particle size alone, whereby small, near-spherical particles are assumed to be liquid This is despite the knowledge that cloud particle size distributions comprised of a mixture of cloud droplets and ice crystals are affected by the presence of small ice particles (Lawson et al, 2001; Korolev et al, 2003). A distinction of ice and water particles purely by optical size is precarious (Heymsfield et al, 2006) and can lead to an overestimation of the number concentration of cloud droplets when both solid and liquid phases are present in the small size channels (Gardiner and Hallett, 1985)
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