Spatio-temporal reconstruction of winter glacier mass balance in the Alps, Scandinavia, Central Asia and western Canada (1981-2019) using climate reanalyses and machine learning ...
Spatio-temporal reconstruction of winter glacier mass balance is important for assessing long-term impacts of climate change. However, high-altitude regions significantly lack reliable observations, which is limiting the calibration of glaciological and hydrological models. Reanalysis products provi...
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Online Access: | https://dx.doi.org/10.3929/ethz-b-000603056 http://hdl.handle.net/20.500.11850/603056 |
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ftdatacite:10.3929/ethz-b-000603056 2024-04-28T08:20:18+00:00 Spatio-temporal reconstruction of winter glacier mass balance in the Alps, Scandinavia, Central Asia and western Canada (1981-2019) using climate reanalyses and machine learning ... Guidicelli, Matteo Huss, Matthias Gabella, Marco Salzmann, Nadine 2023 application/pdf https://dx.doi.org/10.3929/ethz-b-000603056 http://hdl.handle.net/20.500.11850/603056 en eng ETH Zurich article-journal Text ScholarlyArticle Journal Article 2023 ftdatacite https://doi.org/10.3929/ethz-b-000603056 2024-04-02T12:32:08Z Spatio-temporal reconstruction of winter glacier mass balance is important for assessing long-term impacts of climate change. However, high-altitude regions significantly lack reliable observations, which is limiting the calibration of glaciological and hydrological models. Reanalysis products provide estimates of snow precipitation also for remote high-mountain regions, but this data come with inherent uncertainty, and assessing their biases is difficult given the low quantity and quality of available (long-term) in situ observations. In this study, we aim at improving knowledge on the spatio-temporal variations in winter glacier mass balance by exploring the combination of data from reanalyses and direct snow accumulation observations on glaciers using machine learning. We use the winter mass balance data of 95 glaciers distributed over the European Alps, western Canada, Central Asia and Scandinavia and compare them with the total precipitation from the ERA5 and the MERRA-2 reanalysis products during the ... : The Cryosphere, 17 (2) ... Article in Journal/Newspaper glacier* 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 |
description |
Spatio-temporal reconstruction of winter glacier mass balance is important for assessing long-term impacts of climate change. However, high-altitude regions significantly lack reliable observations, which is limiting the calibration of glaciological and hydrological models. Reanalysis products provide estimates of snow precipitation also for remote high-mountain regions, but this data come with inherent uncertainty, and assessing their biases is difficult given the low quantity and quality of available (long-term) in situ observations. In this study, we aim at improving knowledge on the spatio-temporal variations in winter glacier mass balance by exploring the combination of data from reanalyses and direct snow accumulation observations on glaciers using machine learning. We use the winter mass balance data of 95 glaciers distributed over the European Alps, western Canada, Central Asia and Scandinavia and compare them with the total precipitation from the ERA5 and the MERRA-2 reanalysis products during the ... : The Cryosphere, 17 (2) ... |
format |
Article in Journal/Newspaper |
author |
Guidicelli, Matteo Huss, Matthias Gabella, Marco Salzmann, Nadine |
spellingShingle |
Guidicelli, Matteo Huss, Matthias Gabella, Marco Salzmann, Nadine Spatio-temporal reconstruction of winter glacier mass balance in the Alps, Scandinavia, Central Asia and western Canada (1981-2019) using climate reanalyses and machine learning ... |
author_facet |
Guidicelli, Matteo Huss, Matthias Gabella, Marco Salzmann, Nadine |
author_sort |
Guidicelli, Matteo |
title |
Spatio-temporal reconstruction of winter glacier mass balance in the Alps, Scandinavia, Central Asia and western Canada (1981-2019) using climate reanalyses and machine learning ... |
title_short |
Spatio-temporal reconstruction of winter glacier mass balance in the Alps, Scandinavia, Central Asia and western Canada (1981-2019) using climate reanalyses and machine learning ... |
title_full |
Spatio-temporal reconstruction of winter glacier mass balance in the Alps, Scandinavia, Central Asia and western Canada (1981-2019) using climate reanalyses and machine learning ... |
title_fullStr |
Spatio-temporal reconstruction of winter glacier mass balance in the Alps, Scandinavia, Central Asia and western Canada (1981-2019) using climate reanalyses and machine learning ... |
title_full_unstemmed |
Spatio-temporal reconstruction of winter glacier mass balance in the Alps, Scandinavia, Central Asia and western Canada (1981-2019) using climate reanalyses and machine learning ... |
title_sort |
spatio-temporal reconstruction of winter glacier mass balance in the alps, scandinavia, central asia and western canada (1981-2019) using climate reanalyses and machine learning ... |
publisher |
ETH Zurich |
publishDate |
2023 |
url |
https://dx.doi.org/10.3929/ethz-b-000603056 http://hdl.handle.net/20.500.11850/603056 |
genre |
glacier* |
genre_facet |
glacier* |
op_doi |
https://doi.org/10.3929/ethz-b-000603056 |
_version_ |
1797583259946713088 |