Microphysical properties and fall speed measurements of snow ice crystals using the Dual Ice Crystal Imager (D-ICI)

Kühn, Thomas; Vázquez-Martín, Sandra

doi:10.5194/amt-2019-352

Cited by 2 publications

(9 citation statements)

References 20 publications

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“…Our measurements have been carried out in Kiruna, Sweden (67.8 • N, 20.4 • E) using the D-ICI, the ground-based in situ instrument described in Kuhn and Vázquez-Martín [22]. Most of the measurements took place on the roof of the main building of the Swedish Institute of Space Physics (IRF) on the space campus at the height of about 15 m above the ground at an altitude of 425 m above mean sea level.…”

Section: Measurement Sitementioning

confidence: 99%

“…After falling through the inlet, in-focus particles are detected and then imaged twice, simultaneously from above and from the side. These dual images are taken using two high-resolution imaging systems (resolution of about 10 µm with a pixel resolution of 3.7 µm/px; for a detailed description, see [22]). The additional information provided by a second image improves the shape classification.…”

Section: Instrumentmentioning

confidence: 99%

“…Top-view images are used to determine particle size, cross-sectional area, area ratio, and aspect ratio by the automated process presented in detail in Kuhn and Vázquez-Martín [22]. The first steps are to remove the background features from uneven illumination and to remove out-of-focus particles.…”

Section: Image Processingmentioning

confidence: 99%

“…More than 10,000 images were taken during snowfall events from 2014 to 2019. As mentioned in Kuhn and Vázquez-Martín [22], we only consider particles that are completely in the field of view for analysis. In total, we found 3165 particles from 67 days that fulfilled these criteria and they make up the dataset further referred to in this study.…”

Section: Properties Of Shape Groupsmentioning

confidence: 99%

“…This shows that, with the D-ICI and the classification in shapes and shape groups, particle characteristics can be studied for groups of similar shapes. Since fall speed can be measured by analyzing side-view images taken by the D-ICI [22], the shape dependence of fall speed can also be studied. The resulting parameterizations of the snow microphysical properties may be useful for improving our understanding of precipitation in cold climates in addition to helping improve the cloud microphysical parameterizations in the climate and forecast models.…”

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confidence: 99%

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

2020

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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.

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Section: Measurement Sitementioning

confidence: 99%

Section: Instrumentmentioning

confidence: 99%

Section: Image Processingmentioning

confidence: 99%

Section: Properties Of Shape Groupsmentioning

confidence: 99%

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confidence: 99%

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

2020

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Mass of different snow crystal shapes derived from fall speed measurements

2021

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Abstract. Meteorological forecast and climate models require good knowledge of the microphysical properties of hydrometeors and the atmospheric snow and ice crystals in clouds, for instance, their size, cross-sectional area, shape, mass, and fall speed. Especially shape is an important parameter in that it strongly affects the scattering properties of ice particles and consequently their response to remote sensing techniques. The fall speed and mass of ice particles are other important parameters for both numerical forecast models and the representation of snow and ice clouds in climate models. In the case of fall speed, it is responsible for the rate of removal of ice from these models. The particle mass is a key quantity that connects the cloud microphysical properties to radiative properties. Using an empirical relationship between the dimensionless Reynolds and Best numbers, fall speed and mass can be derived from each other if particle size and cross-sectional area are also known. In this study, ground-based in situ measurements of snow particle microphysical properties are used to analyse mass as a function of shape and the other properties particle size, cross-sectional area, and fall speed. The measurements for this study were done in Kiruna, Sweden, during snowfall seasons of 2014 to 2019 and using the ground-based in situ Dual Ice Crystal Imager (D-ICI) instrument, which takes high-resolution side- and top-view images of natural hydrometeors. From these images, particle size (maximum dimension), cross-sectional area, and fall speed of individual particles are determined. The particles are shape-classified according to the scheme presented in our previous study, in which particles sort into 15 different shape groups depending on their shape and morphology. Particle masses of individual ice particles are estimated from measured particle size, cross-sectional area, and fall speed. The selected dataset covers sizes from about 0.1 to 3.2 mm, fall speeds from 0.1 to 1.6 m s−1, and masses from 0.2 to 450 µg. In our previous study, the fall speed relationships between particle size and cross-sectional area were studied. In this study, the same dataset is used to determine the particle mass, and consequently, the mass relationships between particle size, cross-sectional area, and fall speed are studied for these 15 shape groups. Furthermore, the mass relationships presented in this study are compared with the previous studies. For certain crystal habits, in particular columnar shapes, the maximum dimension is unsuitable for determining Reynolds number. Using a selection of columns, for which the simple geometry allows the verification of an empirical Best-number-to-Reynolds-number relationship, we show that Reynolds number and fall speed are more closely related to the diameter of the basal facet than the maximum dimension. The agreement with the empirical relationship is further improved using a modified Best number, a function of an area ratio based on the falling particle seen in the vertical direction.

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Microphysical properties and fall speed measurements of snow ice crystals using the Dual Ice Crystal Imager (D-ICI)

Cited by 2 publications

References 20 publications

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

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

Mass of different snow crystal shapes derived from fall speed measurements

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