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Characterising optical array particle imaging probes: implications for small-ice-crystal observations

O'Shea, S. ORCID: https://orcid.org/0000-0002-0489-1723, Crosier, J. ORCID: https://orcid.org/0000-0002-3086-4729, Dorsey, J., Gallagher, L., Schledewitz, W., Bower, K. ORCID: https://orcid.org/0000-0002-9802-3264, Schlenczek, O. ORCID: https://orcid.org/0000-0001-7247-465X, Borrmann, S. ORCID: https://orcid.org/0000-0002-4774-9380, Cotton, R., Westbrook, C. and Ulanowski, Z. ORCID: https://orcid.org/0000-0003-4761-6980 (2021) Characterising optical array particle imaging probes: implications for small-ice-crystal observations. Atmospheric Measurement Techniques, 14 (3). pp. 1917-1939. ISSN 1867-8548

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To link to this item DOI: 10.5194/amt-14-1917-2021

Abstract/Summary

The cloud particle concentration, size, and shape data from optical array probes (OAPs) are routinely used to parameterise cloud properties and constrain remote sensing retrievals. This paper characterises the optical response of OAPs using a combination of modelling, laboratory, and field experiments. Significant uncertainties are found to exist with such probes for ice crystal measurements. We describe and test two independent methods to constrain a probe's sample volume that remove the most severely mis-sized particles: (1) greyscale image analysis and (2) co-location using stereoscopic imaging. These methods are tested using field measurements from three research flights in cirrus. For these cases, the new methodologies significantly improve agreement with a holographic imaging probe compared to conventional data-processing protocols, either removing or significantly reducing the concentration of small ice crystals (< 200 µm) in certain conditions. This work suggests that the observational evidence for a ubiquitous mode of small ice particles in ice clouds is likely due to a systematic instrument bias. Size distribution parameterisations based on OAP measurements need to be revisited using these improved methodologies.

Item Type:Article
Refereed:Yes
Divisions:Science > School of Mathematical, Physical and Computational Sciences > Department of Meteorology
ID Code:98369
Publisher:Copernicus

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