Shape Dependence of Falling Snow Crystals’ Microphysical Properties Using an Updated Shape Classification

Author:

Vázquez-Martín SandraORCID,Kuhn ThomasORCID,Eliasson SalomonORCID

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.

Publisher

MDPI AG

Subject

Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science

Cited by 7 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Revisiting Diagrams of Ice Growth Environments;Bulletin of the American Meteorological Society;2022-11

2. Exploring Snowfall Variability through the High-Latitude Measurement of Snowfall (HiLaMS) Field Campaign;Bulletin of the American Meteorological Society;2022-08

3. Mass of different snow crystal shapes derived from fall speed measurements;Atmospheric Chemistry and Physics;2021-12-23

4. Advanced Deep Learning-Based Supervised Classification of Multi-Angle Snowflake Camera Images;Journal of Atmospheric and Oceanic Technology;2021-06-15

5. Shape dependence of snow crystal fall speed;Atmospheric Chemistry and Physics;2021-05-18

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