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Shape Dependence of Falling Snow Crystals' Microphysical Properties Using an Updated Shape Classification
SMHI, Research Department, Atmospheric remote sensing.ORCID iD: 0000-0002-1391-961X
2020 (English)In: Applied Sciences, E-ISSN 2076-3417, Vol. 10, no 3, article id 1163Article in journal (Refereed) Published
Abstract [en]

We present ground-based in situ snow measurements in Kiruna, Sweden, using the ground-based in situ instrument Dual Ice Crystal Imager (D-ICI). D-ICI records dual high-resolution images from above and from the side of falling natural snow crystals and other hydrometeors with particle sizes ranging from 50 mu m to 4 mm. The images are from multiple snowfall seasons during the winters of 2014/2015 to 2018/2019, which span from the beginning of November to the middle of May. From our images, the microphysical properties of individual particles, such as particle size, cross-sectional area, area ratio, aspect ratio, and shape, can be determined. We present an updated classification scheme, which comprises a total of 135 unique shapes, including 34 new snow crystal shapes. This is useful for other studies that are using previous shape classification schemes, in particular the widely used Magono-Lee classification. To facilitate the study of the shape dependence of the microphysical properties, we further sort these individual particle shapes into 15 different shape groups. Relationships between the microphysical properties are determined for each of these shape groups.

Place, publisher, year, edition, pages
2020. Vol. 10, no 3, article id 1163
National Category
Meteorology and Atmospheric Sciences
Research subject
Remote sensing
Identifiers
URN: urn:nbn:se:smhi:diva-5682DOI: 10.3390/app10031163ISI: 000525305900434OAI: oai:DiVA.org:smhi-5682DiVA, id: diva2:1429930
Available from: 2020-05-13 Created: 2020-05-13 Last updated: 2020-05-13Bibliographically approved

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Eliasson, Salomon

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