Shape Dependence of Falling Snow Crystals’ Microphysical Properties Using an Updated Shape Classification
Source abstract
Abstract
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 μ 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.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Cryospheric studies and observations · Meteorological Phenomena and Simulations · Arctic and Antarctic ice dynamics
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Division of Space Technology, Department of Computer Science, Electrical and Space Engineering, Luleå University of Technology (LTU), 98 128 Kiruna, Sweden
Swedish Meteorological and Hydrological Institute (SMHI), 601 76 Norrköping, Sweden
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