Snow ice particle microphysical properties and fall speed from particle images taken in Kiruna (Sweden) 2014–2018

SND-ID: 2021-125

Creator/Principal investigator(s)

Thomas Kuhn - Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering orcid

Sandra Vázquez-Martín - Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering orcid

Description

Accurate predictions of snowfall require good knowledge of the microphysical properties of the snow ice crystals and particles. Shape is an important parameter as it strongly influences the scattering properties of the ice particles, and thus their response to remote sensing techniques such as radar measurements. The fall speed of ice particles is another important parameter for both numerical forecast models as well as representation of ice clouds and snow in climate models, as it is responsible for the rate of removal of ice from these models. The particle mass is also a key quantity as it connects the cloud microphysical properties to radiative properties.

The ground-based in-situ instrument Dual Ice Crystal Imager (D-ICI) has been used in Kiruna, Sweden, to determine snow ice particle properties and fall speed simultaneously. D-ICI takes two high-resolution images of the same falling ice particle from two different viewing directions, a top view and a side view. Both images have a pixel resolution of approximately 4 μm/pixel and an optical resolution of approximately 10 μm.

The top-vie

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Language

English

Research principal, contributors, and funding
Protection and ethical review

Data contains personal data

No

Method and time period

Time period(s) investigated

2014-10-19 – 2018-05-11

Geographic coverage

Geographic spread

Geographic location: Sweden, Norrbotten County, Kiruna Municipality

Geographic description: Measurement site in Kiruna, northern Sweden (67.8°N, 20.4°E).

Publications

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Vazquez-Martin, S., Kuhn, T., & Eliasson, S. (2020). Shape Dependence of Falling Snow Crystals’ Microphysical Properties Using an Updated Shape Classification. Applied Sciences, 10(3), Article 1163. https://doi.org/10.3390/app10031163
DOI: https://doi.org/10.3390/app10031163
URN: urn:nbn:se:smhi:diva-5682

Vázquez-Martín, S., Kuhn, T., & Eliasson, S. (2021). Shape dependence of snow crystal fall speed. Atmospheric Chemistry and Physics, 21(10), 7545–7565. https://doi.org/10.5194/acp-21-7545-2021
URN: urn:nbn:se:ltu:diva-82170
DOI: https://doi.org/10.5194/acp-21-7545-2021

Kuhn, T., & Vázquez-Martín, S. (2020). Microphysical properties and fall speed measurements of snow ice crystals using the Dual Ice Crystal Imager (D-ICI). Atmospheric Measurement Techniques, 13, 1273–1285. https://doi.org/10.5194/amt-13-1273-2020
DOI: https://doi.org/10.5194/amt-13-1273-2020
URN: urn:nbn:se:ltu:diva-78097

Vázquez-Martín, S., Kuhn, T., & Eliasson, S. (2021). Mass of different snow crystal shapes derived from fall speed measurements, Atmospheric Chemistry and Physics, 21(24), 18669–18688. https://doi.org/10.5194/acp-2021-203
DOI: https://doi.org/10.5194/acp-21-18669-2021

If you have published anything based on these data, please notify us with a reference to your publication(s). If you are responsible for the catalogue entry, you can update the metadata/data description in DORIS.

Dataset 1
Snow ice particle microphysical properties and fall speed from particle images taken with the Dual Ice Crystal Imager (D-ICI) in Kiruna (Sweden) 2014–2018

Description

The following description can also be found in the documentation file "Description_of_dataset.txt".

Data in Version 2 are identical to the data in Version 1, but they also contain ice particle mass as new variable.

The dataset is the basis of the articles:
Vázquez-Martín, S., Kuhn, T., & Eliasson, S. (2021): Shape dependence of snow crystal fall speed, Atmospheric Chemistry and Physics, 21(10), 7545–7565. https://doi.org/10.5194/acp-21-7545-2021
Vázquez-Martín, S., Kuhn, T., & Eliasson, S. (20

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Version 2

2021-12-20
https://doi.org/10.5878/2dnq-5x15

Variable(s) added : Added ice particle mass as new variable

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Citation

Thomas Kuhn, Sandra Vázquez-Martín. Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering (2021). Snow ice particle microphysical properties and fall speed from particle images taken with the Dual Ice Crystal Imager (D-ICI) in Kiruna (Sweden) 2014–2018. Swedish National Data Service. Version 2. https://doi.org/10.5878/2dnq-5x15

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Data format / data structure

Numeric

Still image

Creator/Principal investigator(s)

Thomas Kuhn - Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering orcid

Sandra Vázquez-Martín - Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering orcid

Time period(s) investigated

2014-10-19 – 2018-05-11

Variables

12

License

Creative Commons  Attribution 4.0 International (CC BY 4.0)
Dataset 2
Data 2

Description

Description

Version 1

Citation

Thomas Kuhn. Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering (2022). Data 2. Swedish National Data Service. Version 1. https://doi.org/10.5878/mkm0-b191

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Data format / data structure

Text

Creator/Principal investigator(s)

Thomas Kuhn - Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering orcid

Variables

2

Published: 2021-05-17
Last updated: 2022-03-28