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https://doi.org/10.5194/acp-2020-1056
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-2020-1056
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  26 Oct 2020

26 Oct 2020

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This preprint is currently under review for the journal ACP.

Shape dependence of snow crystal fall speed

Sandra Vázquez-Martín1, Thomas Kuhn1, and Salomon Eliasson2 Sandra Vázquez-Martín et al.
  • 1Luleå University of Technology (LTU), Department of Computer Science, Electrical and Space Engineering, Division of Space Technology, 98 128, Kiruna, Sweden
  • 2Swedish Meteorological and Hydrological Institute (SMHI), 601 76, Norrköping, Sweden

Abstract. Improved snowfall predictions require accurate knowledge of the properties of ice crystals and snow particles, such as their size, cross-sectional area, shape, and fall speed. In particular, the shape is an important parameter as it strongly influences the scattering properties of these ice particles, and thus their response to remote sensing techniques such as radar measurements. The fall speed of ice particles is a critical parameter for the representation of ice clouds and snow in atmospheric numerical models, as it determines the rate of removal of ice from the modelled clouds. They are also required for snowfall predictions alongside other properties such as ice particle size, cross-sectional area, and shape. For example, shape is important as it strongly influences the scattering properties of these ice particles, and thus their response to remote sensing techniques.

This work analyses fall speed as a function of shape and other properties using ground-based in-situ measurements. The measurements for this study were done in Kiruna, Sweden during the snowfall seasons of 2014 to 2019, using the ground-based in-situ instrument Dual Ice Crystal Imager (D-ICI). The resulting data consist of high-resolution images of falling hydrometeors from two viewing geometries that are used to determine size (maximum dimension), cross-sectional area, area ratio, orientation, and the fall speed of individual particles. The selected dataset covers sizes from about 0.06 to 3.2 mm and fall speeds from 0.06 to 1.6 m s−1.

The particles are shape-classified into 15 different shape groups depending on their shape and morphology. For these 15 shape groups relationships are studied, firstly, between size and cross-sectional area, then between fall speed and size or cross-sectional area. The data show in general low correlations to fitted fall-speed relationships due to large spread observed in fall speed. After binning the data according to size or cross-sectional area, correlations improve and we can report reliable parameterizations of fall speed vs. size or cross-sectional area for part of the shapes. The effects of orientation and area ratio on the fall speed are also studied, and measurements show that vertically orientated particles fall faster on average. However, most particles for which orientation can be defined fall horizontally.

Sandra Vázquez-Martín et al.

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Short summary
In this work, we present new fall speed measurements of natural snow particles and ice crystals. We study the particle fall speed relationships and how they depend on particle shape. We analyse these relationships as a function of particle size, cross-sectional area, and area ratio for different particle shape groups. We also investigate the dependence of the particle fall speed on the orientation as it has a large impact on the cross-sectional area.
In this work, we present new fall speed measurements of natural snow particles and ice crystals....
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