Mass of different snow crystal shapes derived from fall speed measurements
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 st...
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ftcopernicus:oai:publications.copernicus.org:acpd93367 2023-05-15T17:04:22+02:00 Mass of different snow crystal shapes derived from fall speed measurements Vázquez-Martín, Sandra Kuhn, Thomas Eliasson, Salomon 2021-03-16 application/pdf https://doi.org/10.5194/acp-2021-203 https://acp.copernicus.org/preprints/acp-2021-203/ eng eng doi:10.5194/acp-2021-203 https://acp.copernicus.org/preprints/acp-2021-203/ eISSN: 1680-7324 Text 2021 ftcopernicus https://doi.org/10.5194/acp-2021-203 2021-03-22T17:22:15Z 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 both for numerical forecast models and for 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 work, 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 instrument Dual Ice Crystal Imager (D-ICI), 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 work, 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 mm to 3.2 mm, fall speeds from 0.1 m s −1 to 1.6 m s −1 , and masses from close to 0.2 μg to 320 μg. In our previous work, the fall speed relationships between particle size and cross-sectional area were studied. In this work, 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. Text Kiruna Copernicus Publications: E-Journals Kiruna |
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Copernicus Publications: E-Journals |
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English |
description |
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 both for numerical forecast models and for 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 work, 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 instrument Dual Ice Crystal Imager (D-ICI), 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 work, 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 mm to 3.2 mm, fall speeds from 0.1 m s −1 to 1.6 m s −1 , and masses from close to 0.2 μg to 320 μg. In our previous work, the fall speed relationships between particle size and cross-sectional area were studied. In this work, 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. |
format |
Text |
author |
Vázquez-Martín, Sandra Kuhn, Thomas Eliasson, Salomon |
spellingShingle |
Vázquez-Martín, Sandra Kuhn, Thomas Eliasson, Salomon Mass of different snow crystal shapes derived from fall speed measurements |
author_facet |
Vázquez-Martín, Sandra Kuhn, Thomas Eliasson, Salomon |
author_sort |
Vázquez-Martín, Sandra |
title |
Mass of different snow crystal shapes derived from fall speed measurements |
title_short |
Mass of different snow crystal shapes derived from fall speed measurements |
title_full |
Mass of different snow crystal shapes derived from fall speed measurements |
title_fullStr |
Mass of different snow crystal shapes derived from fall speed measurements |
title_full_unstemmed |
Mass of different snow crystal shapes derived from fall speed measurements |
title_sort |
mass of different snow crystal shapes derived from fall speed measurements |
publishDate |
2021 |
url |
https://doi.org/10.5194/acp-2021-203 https://acp.copernicus.org/preprints/acp-2021-203/ |
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Kiruna |
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Kiruna |
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Kiruna |
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Kiruna |
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eISSN: 1680-7324 |
op_relation |
doi:10.5194/acp-2021-203 https://acp.copernicus.org/preprints/acp-2021-203/ |
op_doi |
https://doi.org/10.5194/acp-2021-203 |
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