Snow ice particle microphysical properties and fall speed from particle images taken in Kiruna (Sweden) 2014–2018 - Data 2 ... : Mikrofysikaliska egenskaper och fallhastighet av snöpartiklar från partikelbilder tagna i Kiruna (Sverige) 2014–2018 - Data 2 ...
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...
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Luleå University of Technology
2022
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Online Access: | https://dx.doi.org/10.5878/4pth-9m71 https://snd.se/catalogue/dataset/2021-125-2 |
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ftdatacite:10.5878/4pth-9m71 2024-04-28T08:27:29+00:00 Snow ice particle microphysical properties and fall speed from particle images taken in Kiruna (Sweden) 2014–2018 - Data 2 ... : Mikrofysikaliska egenskaper och fallhastighet av snöpartiklar från partikelbilder tagna i Kiruna (Sverige) 2014–2018 - Data 2 ... Kuhn, Thomas 2022 https://dx.doi.org/10.5878/4pth-9m71 https://snd.se/catalogue/dataset/2021-125-2 en eng Luleå University of Technology https://dx.doi.org/10.5878/mkm0-b191 https://dx.doi.org/10.3390/app10031163 https://dx.doi.org/10.5194/acp-21-7545-2021 https://dx.doi.org/10.5194/amt-13-1273-2020 https://dx.doi.org/10.5194/acp-21-18669-2021 info:eu-repo/semantics/openAccess Atmospheric conditions Atmosfäriska förhållanden snow fall speed snöfallshastighet snowfall snöfall snow crystals snökristaller snow snö Earth and Related Environmental Sciences Geovetenskap och miljövetenskap Natural Sciences Naturvetenskap Meteorology and Atmospheric Sciences Meteorologi och atmosfärforskning Climatology / Meteorology / Atmosphere Klimatologi och meteorologi dataset Dataset 2022 ftdatacite https://doi.org/10.5878/4pth-9m7110.5878/mkm0-b19110.3390/app1003116310.5194/acp-21-7545-202110.5194/amt-13-1273-202010.5194/acp-21-18669-2021 2024-04-02T12:33:12Z 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 ... : Instrumentet Dual Ice Crystal Imager (D-ICI) mäter samtidigt mikrofysikaliska egenskaper och fallhastighet av snöpartiklar. D-ICI tar bilder av partiklar från två olika riktningar med en upplösning av 4μm/pixel. Mätningar med D-ICI i Kiruna, norra Sverige (67.8N, 20.4E), under vintrarna 2014/2015 till 2017/2018 presenteras. Både bilder och egenskaper framtagna av dessa ingår i datasetet. Datasetet ligger till grund för artiklarna 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. (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 För mer information se den engelska katalogsidan: https://snd.gu.se/en/catalogue/study/2021-125 Beskrivning ... Dataset Kiruna Norra Sverige DataCite Metadata Store (German National Library of Science and Technology) |
institution |
Open Polar |
collection |
DataCite Metadata Store (German National Library of Science and Technology) |
op_collection_id |
ftdatacite |
language |
English |
topic |
Atmospheric conditions Atmosfäriska förhållanden snow fall speed snöfallshastighet snowfall snöfall snow crystals snökristaller snow snö Earth and Related Environmental Sciences Geovetenskap och miljövetenskap Natural Sciences Naturvetenskap Meteorology and Atmospheric Sciences Meteorologi och atmosfärforskning Climatology / Meteorology / Atmosphere Klimatologi och meteorologi |
spellingShingle |
Atmospheric conditions Atmosfäriska förhållanden snow fall speed snöfallshastighet snowfall snöfall snow crystals snökristaller snow snö Earth and Related Environmental Sciences Geovetenskap och miljövetenskap Natural Sciences Naturvetenskap Meteorology and Atmospheric Sciences Meteorologi och atmosfärforskning Climatology / Meteorology / Atmosphere Klimatologi och meteorologi Kuhn, Thomas Snow ice particle microphysical properties and fall speed from particle images taken in Kiruna (Sweden) 2014–2018 - Data 2 ... : Mikrofysikaliska egenskaper och fallhastighet av snöpartiklar från partikelbilder tagna i Kiruna (Sverige) 2014–2018 - Data 2 ... |
topic_facet |
Atmospheric conditions Atmosfäriska förhållanden snow fall speed snöfallshastighet snowfall snöfall snow crystals snökristaller snow snö Earth and Related Environmental Sciences Geovetenskap och miljövetenskap Natural Sciences Naturvetenskap Meteorology and Atmospheric Sciences Meteorologi och atmosfärforskning Climatology / Meteorology / Atmosphere Klimatologi och meteorologi |
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 ... : Instrumentet Dual Ice Crystal Imager (D-ICI) mäter samtidigt mikrofysikaliska egenskaper och fallhastighet av snöpartiklar. D-ICI tar bilder av partiklar från två olika riktningar med en upplösning av 4μm/pixel. Mätningar med D-ICI i Kiruna, norra Sverige (67.8N, 20.4E), under vintrarna 2014/2015 till 2017/2018 presenteras. Både bilder och egenskaper framtagna av dessa ingår i datasetet. Datasetet ligger till grund för artiklarna 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. (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 För mer information se den engelska katalogsidan: https://snd.gu.se/en/catalogue/study/2021-125 Beskrivning ... |
format |
Dataset |
author |
Kuhn, Thomas |
author_facet |
Kuhn, Thomas |
author_sort |
Kuhn, Thomas |
title |
Snow ice particle microphysical properties and fall speed from particle images taken in Kiruna (Sweden) 2014–2018 - Data 2 ... : Mikrofysikaliska egenskaper och fallhastighet av snöpartiklar från partikelbilder tagna i Kiruna (Sverige) 2014–2018 - Data 2 ... |
title_short |
Snow ice particle microphysical properties and fall speed from particle images taken in Kiruna (Sweden) 2014–2018 - Data 2 ... : Mikrofysikaliska egenskaper och fallhastighet av snöpartiklar från partikelbilder tagna i Kiruna (Sverige) 2014–2018 - Data 2 ... |
title_full |
Snow ice particle microphysical properties and fall speed from particle images taken in Kiruna (Sweden) 2014–2018 - Data 2 ... : Mikrofysikaliska egenskaper och fallhastighet av snöpartiklar från partikelbilder tagna i Kiruna (Sverige) 2014–2018 - Data 2 ... |
title_fullStr |
Snow ice particle microphysical properties and fall speed from particle images taken in Kiruna (Sweden) 2014–2018 - Data 2 ... : Mikrofysikaliska egenskaper och fallhastighet av snöpartiklar från partikelbilder tagna i Kiruna (Sverige) 2014–2018 - Data 2 ... |
title_full_unstemmed |
Snow ice particle microphysical properties and fall speed from particle images taken in Kiruna (Sweden) 2014–2018 - Data 2 ... : Mikrofysikaliska egenskaper och fallhastighet av snöpartiklar från partikelbilder tagna i Kiruna (Sverige) 2014–2018 - Data 2 ... |
title_sort |
snow ice particle microphysical properties and fall speed from particle images taken in kiruna (sweden) 2014–2018 - data 2 ... : mikrofysikaliska egenskaper och fallhastighet av snöpartiklar från partikelbilder tagna i kiruna (sverige) 2014–2018 - data 2 ... |
publisher |
Luleå University of Technology |
publishDate |
2022 |
url |
https://dx.doi.org/10.5878/4pth-9m71 https://snd.se/catalogue/dataset/2021-125-2 |
genre |
Kiruna Norra Sverige |
genre_facet |
Kiruna Norra Sverige |
op_relation |
https://dx.doi.org/10.5878/mkm0-b191 https://dx.doi.org/10.3390/app10031163 https://dx.doi.org/10.5194/acp-21-7545-2021 https://dx.doi.org/10.5194/amt-13-1273-2020 https://dx.doi.org/10.5194/acp-21-18669-2021 |
op_rights |
info:eu-repo/semantics/openAccess |
op_doi |
https://doi.org/10.5878/4pth-9m7110.5878/mkm0-b19110.3390/app1003116310.5194/acp-21-7545-202110.5194/amt-13-1273-202010.5194/acp-21-18669-2021 |
_version_ |
1797586400005062656 |