Sea ice, snow and melt pond example data from MOSAiC transect observations
This data set contains in-situ observation of sea ice, snow and melt pond properties from two days in winter (January 23, 2020) and summer (July 7, 2020) during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition. It originates from two sensors: Broad-band...
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ftzenodo:oai:zenodo.org:5155244 2023-05-15T15:03:52+02:00 Sea ice, snow and melt pond example data from MOSAiC transect observations Stefan Hendricks Polona Itkin Melinda Webster Luisa von Albedyll Arttu Jutila Ian Raphael Antonia Immerz Matthias Jaggi Christian Haas 2021-08-03 https://zenodo.org/record/5155244 https://doi.org/10.5281/zenodo.5155244 eng eng doi:10.5281/zenodo.5155243 https://zenodo.org/record/5155244 https://doi.org/10.5281/zenodo.5155244 oai:zenodo.org:5155244 info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/4.0/legalcode cryosphere sea ice snow on sea ice melt ponds MOSAiC Arctic Ocean info:eu-repo/semantics/other dataset 2021 ftzenodo https://doi.org/10.5281/zenodo.515524410.5281/zenodo.5155243 2023-03-11T04:06:54Z This data set contains in-situ observation of sea ice, snow and melt pond properties from two days in winter (January 23, 2020) and summer (July 7, 2020) during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition. It originates from two sensors: Broad-band electromagnetic induction sensor (Geophex GEM-2) measuring the combined thickness of the sea ice and snow layers A GPS snow depth probe (Snow-Hydro MagnaProbe) measuring the thickness of the snow layer and melt ponds depth during summer Both sensors were operated coincidently along transect loops while different loops were used in both days. This data set is a subset of similar weekly activities between October 2019 and September 2020. This publication intends to provide a preview of the data properties and approximate changes between the winter and summer periods. It also has to be noted, that the final data of the EM induction sensor might differ from this release, which is based on a quick-look processing directly after data acquisition. GEM-2 data files The file format of GEM-2 data is a text file with comma-separated values. Notable parameters are: ‘time’: UTC time ‘longitude’: Longitude in degrees east (fill value: 0.0) ‘latitude’: Latitude in degrees north (fill value: 0.0) ‘`f{frequency}Hz_hcp_{i:Inphase|q:Quadrature}`: total (ice + snow) thickness of the sea ice and snow layers in meter for different channels* *The channels correspond to the real (Inphase) or imaginary (Quadrature) part of the EM signal at a given frequency. The variable name in the csv file is to be read as `f{frequency}Hz_hcp_{i:Inphase|q:Quadrature}`. It is recommended to use the Inphase component of the 18.325 kHz frequency (variable `f18325Hz_hcp_i`) for analysis. MagnaProbe data files The file format of MagnaProbe data is a text file with comma-separated values. Notable parameters are: `timestamp`: Timestamp `longitude_a`: longitude degree in degrees east `longitude_b`: longitude minute `latitude_a`: latitude degree in degrees north ... Dataset Arctic Arctic Ocean Sea ice Zenodo Arctic Arctic Ocean |
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ftzenodo |
language |
English |
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cryosphere sea ice snow on sea ice melt ponds MOSAiC Arctic Ocean |
spellingShingle |
cryosphere sea ice snow on sea ice melt ponds MOSAiC Arctic Ocean Stefan Hendricks Polona Itkin Melinda Webster Luisa von Albedyll Arttu Jutila Ian Raphael Antonia Immerz Matthias Jaggi Christian Haas Sea ice, snow and melt pond example data from MOSAiC transect observations |
topic_facet |
cryosphere sea ice snow on sea ice melt ponds MOSAiC Arctic Ocean |
description |
This data set contains in-situ observation of sea ice, snow and melt pond properties from two days in winter (January 23, 2020) and summer (July 7, 2020) during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition. It originates from two sensors: Broad-band electromagnetic induction sensor (Geophex GEM-2) measuring the combined thickness of the sea ice and snow layers A GPS snow depth probe (Snow-Hydro MagnaProbe) measuring the thickness of the snow layer and melt ponds depth during summer Both sensors were operated coincidently along transect loops while different loops were used in both days. This data set is a subset of similar weekly activities between October 2019 and September 2020. This publication intends to provide a preview of the data properties and approximate changes between the winter and summer periods. It also has to be noted, that the final data of the EM induction sensor might differ from this release, which is based on a quick-look processing directly after data acquisition. GEM-2 data files The file format of GEM-2 data is a text file with comma-separated values. Notable parameters are: ‘time’: UTC time ‘longitude’: Longitude in degrees east (fill value: 0.0) ‘latitude’: Latitude in degrees north (fill value: 0.0) ‘`f{frequency}Hz_hcp_{i:Inphase|q:Quadrature}`: total (ice + snow) thickness of the sea ice and snow layers in meter for different channels* *The channels correspond to the real (Inphase) or imaginary (Quadrature) part of the EM signal at a given frequency. The variable name in the csv file is to be read as `f{frequency}Hz_hcp_{i:Inphase|q:Quadrature}`. It is recommended to use the Inphase component of the 18.325 kHz frequency (variable `f18325Hz_hcp_i`) for analysis. MagnaProbe data files The file format of MagnaProbe data is a text file with comma-separated values. Notable parameters are: `timestamp`: Timestamp `longitude_a`: longitude degree in degrees east `longitude_b`: longitude minute `latitude_a`: latitude degree in degrees north ... |
format |
Dataset |
author |
Stefan Hendricks Polona Itkin Melinda Webster Luisa von Albedyll Arttu Jutila Ian Raphael Antonia Immerz Matthias Jaggi Christian Haas |
author_facet |
Stefan Hendricks Polona Itkin Melinda Webster Luisa von Albedyll Arttu Jutila Ian Raphael Antonia Immerz Matthias Jaggi Christian Haas |
author_sort |
Stefan Hendricks |
title |
Sea ice, snow and melt pond example data from MOSAiC transect observations |
title_short |
Sea ice, snow and melt pond example data from MOSAiC transect observations |
title_full |
Sea ice, snow and melt pond example data from MOSAiC transect observations |
title_fullStr |
Sea ice, snow and melt pond example data from MOSAiC transect observations |
title_full_unstemmed |
Sea ice, snow and melt pond example data from MOSAiC transect observations |
title_sort |
sea ice, snow and melt pond example data from mosaic transect observations |
publishDate |
2021 |
url |
https://zenodo.org/record/5155244 https://doi.org/10.5281/zenodo.5155244 |
geographic |
Arctic Arctic Ocean |
geographic_facet |
Arctic Arctic Ocean |
genre |
Arctic Arctic Ocean Sea ice |
genre_facet |
Arctic Arctic Ocean Sea ice |
op_relation |
doi:10.5281/zenodo.5155243 https://zenodo.org/record/5155244 https://doi.org/10.5281/zenodo.5155244 oai:zenodo.org:5155244 |
op_rights |
info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/4.0/legalcode |
op_doi |
https://doi.org/10.5281/zenodo.515524410.5281/zenodo.5155243 |
_version_ |
1766335711175245824 |