Snow cover data across Nordenskiöldland, Svalbard, from point measurements during 2014-2016 ...
Snow depths and bulk densities of the annual snow layer were measured at 69 different locations on glaciers across Nordenskiöldland, Svalbard, during the spring seasons of the period 2014–2016. Sampling locations lie along nine transects extending over 17 individual glaciers. Several of the location...
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Online Access: | https://dx.doi.org/10.1594/pangaea.896581 https://doi.pangaea.de/10.1594/PANGAEA.896581 |
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ftdatacite:10.1594/pangaea.896581 2024-09-15T18:07:56+00:00 Snow cover data across Nordenskiöldland, Svalbard, from point measurements during 2014-2016 ... Möller, Marco Möller, Rebecca 2018 text/tab-separated-values https://dx.doi.org/10.1594/pangaea.896581 https://doi.pangaea.de/10.1594/PANGAEA.896581 en eng PANGAEA https://dx.doi.org/10.5194/essd-2018-158 Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 Event label Latitude of event Longitude of event Elevation of event DATE/TIME Number Randolph Glacier Inventory 6.0, glacier ID Snow thickness Snow thickness, uncertainty Density, snow Density, snow, uncertainty Snow water equivalent Snow water equivalent, uncertainty Flag Ice measurement dataset Supplementary Dataset Dataset 2018 ftdatacite https://doi.org/10.1594/pangaea.89658110.5194/essd-2018-158 2024-08-01T10:58:30Z Snow depths and bulk densities of the annual snow layer were measured at 69 different locations on glaciers across Nordenskiöldland, Svalbard, during the spring seasons of the period 2014–2016. Sampling locations lie along nine transects extending over 17 individual glaciers. Several of the locations were visited repeatedly, leading to a total of 109 point measurements, on which we report in this study. Snow water equivalents were calculated for each point measurement. In the dataset, snow depth and density measurements are accompanied by appropriate uncertainties which are rigorously transferred to the calculated snow water equivalents using a straightforward Monte Carlo simulation-style procedure. The final dataset can be downloaded from the Pangaea data repository (https://www.pangaea.de; https://doi.org/10.1594/PANGAEA.896581). Snow cover data indicate a general and statistically significant increase of snow depths and water equivalents with terrain elevation. A significant increase of both quantities ... : Supplement to: Möller, Marco; Möller, Rebecca (2019): Snow cover variability across glaciers in Nordenskiöldland (Svalbard) from point measurements in 2014–2016. Earth System Science Data Discussions ... Dataset glacier Svalbard DataCite |
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Open Polar |
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ftdatacite |
language |
English |
topic |
Event label Latitude of event Longitude of event Elevation of event DATE/TIME Number Randolph Glacier Inventory 6.0, glacier ID Snow thickness Snow thickness, uncertainty Density, snow Density, snow, uncertainty Snow water equivalent Snow water equivalent, uncertainty Flag Ice measurement |
spellingShingle |
Event label Latitude of event Longitude of event Elevation of event DATE/TIME Number Randolph Glacier Inventory 6.0, glacier ID Snow thickness Snow thickness, uncertainty Density, snow Density, snow, uncertainty Snow water equivalent Snow water equivalent, uncertainty Flag Ice measurement Möller, Marco Möller, Rebecca Snow cover data across Nordenskiöldland, Svalbard, from point measurements during 2014-2016 ... |
topic_facet |
Event label Latitude of event Longitude of event Elevation of event DATE/TIME Number Randolph Glacier Inventory 6.0, glacier ID Snow thickness Snow thickness, uncertainty Density, snow Density, snow, uncertainty Snow water equivalent Snow water equivalent, uncertainty Flag Ice measurement |
description |
Snow depths and bulk densities of the annual snow layer were measured at 69 different locations on glaciers across Nordenskiöldland, Svalbard, during the spring seasons of the period 2014–2016. Sampling locations lie along nine transects extending over 17 individual glaciers. Several of the locations were visited repeatedly, leading to a total of 109 point measurements, on which we report in this study. Snow water equivalents were calculated for each point measurement. In the dataset, snow depth and density measurements are accompanied by appropriate uncertainties which are rigorously transferred to the calculated snow water equivalents using a straightforward Monte Carlo simulation-style procedure. The final dataset can be downloaded from the Pangaea data repository (https://www.pangaea.de; https://doi.org/10.1594/PANGAEA.896581). Snow cover data indicate a general and statistically significant increase of snow depths and water equivalents with terrain elevation. A significant increase of both quantities ... : Supplement to: Möller, Marco; Möller, Rebecca (2019): Snow cover variability across glaciers in Nordenskiöldland (Svalbard) from point measurements in 2014–2016. Earth System Science Data Discussions ... |
format |
Dataset |
author |
Möller, Marco Möller, Rebecca |
author_facet |
Möller, Marco Möller, Rebecca |
author_sort |
Möller, Marco |
title |
Snow cover data across Nordenskiöldland, Svalbard, from point measurements during 2014-2016 ... |
title_short |
Snow cover data across Nordenskiöldland, Svalbard, from point measurements during 2014-2016 ... |
title_full |
Snow cover data across Nordenskiöldland, Svalbard, from point measurements during 2014-2016 ... |
title_fullStr |
Snow cover data across Nordenskiöldland, Svalbard, from point measurements during 2014-2016 ... |
title_full_unstemmed |
Snow cover data across Nordenskiöldland, Svalbard, from point measurements during 2014-2016 ... |
title_sort |
snow cover data across nordenskiöldland, svalbard, from point measurements during 2014-2016 ... |
publisher |
PANGAEA |
publishDate |
2018 |
url |
https://dx.doi.org/10.1594/pangaea.896581 https://doi.pangaea.de/10.1594/PANGAEA.896581 |
genre |
glacier Svalbard |
genre_facet |
glacier Svalbard |
op_relation |
https://dx.doi.org/10.5194/essd-2018-158 |
op_rights |
Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 |
op_doi |
https://doi.org/10.1594/pangaea.89658110.5194/essd-2018-158 |
_version_ |
1810445293304414208 |