Modeling spatially distributed snow instability at a regional scale using Alpine3D
Assessing the avalanche danger level requires snow stratigraphy and instability data. As such data are usually sparse, we investigated whether distributed snow cover modeling can be used to provide information on spatial instability patterns relevant for regional avalanche forecasting. Using Alpine3...
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Cambridge University Press
2021
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Online Access: | https://doi.org/10.1017/jog.2021.61 https://doaj.org/article/c906d489c1f24d3e8500549822d6d37a |
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ftdoajarticles:oai:doaj.org/article:c906d489c1f24d3e8500549822d6d37a 2023-05-15T16:57:33+02:00 Modeling spatially distributed snow instability at a regional scale using Alpine3D Bettina Richter Jürg Schweizer Mathias W. Rotach Alec van Herwijnen 2021-12-01T00:00:00Z https://doi.org/10.1017/jog.2021.61 https://doaj.org/article/c906d489c1f24d3e8500549822d6d37a EN eng Cambridge University Press https://www.cambridge.org/core/product/identifier/S0022143021000617/type/journal_article https://doaj.org/toc/0022-1430 https://doaj.org/toc/1727-5652 doi:10.1017/jog.2021.61 0022-1430 1727-5652 https://doaj.org/article/c906d489c1f24d3e8500549822d6d37a Journal of Glaciology, Vol 67, Pp 1147-1162 (2021) Avalanches snow snow mechanics Environmental sciences GE1-350 Meteorology. Climatology QC851-999 article 2021 ftdoajarticles https://doi.org/10.1017/jog.2021.61 2023-03-12T01:30:57Z Assessing the avalanche danger level requires snow stratigraphy and instability data. As such data are usually sparse, we investigated whether distributed snow cover modeling can be used to provide information on spatial instability patterns relevant for regional avalanche forecasting. Using Alpine3D, we performed spatially distributed simulations to evaluate snow instability for the winter season 2016–17 in the region of Davos, Switzerland. Meteorological data from automatic weather stations were interpolated to 100 m horizontal resolution and precipitation was scaled with snow depth measurements from airborne laser scanning. Modeled snow instability metrics assessed for two different weak layers suggested that the weak layer closer to the snow surface was more variable. Initially, it was less stable than the weak layer closer to the ground, yet it stabilized faster as the winter progressed. In spring, the simulated snowpack on south-facing slopes stabilized faster than on north-facing slopes, in line with the regional avalanche forecast. In the winter months January to March 2017, simulated instability metrics did not suggest that the snowpack on south-facing slopes was more stable, as reported in the regional avalanche forecast. Although a validation with field data is lacking, these model results still show the potential and challenges of distributed modeling for supporting operational avalanche forecasting. Article in Journal/Newspaper Journal of Glaciology Directory of Open Access Journals: DOAJ Articles Journal of Glaciology 67 266 1147 1162 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
Avalanches snow snow mechanics Environmental sciences GE1-350 Meteorology. Climatology QC851-999 |
spellingShingle |
Avalanches snow snow mechanics Environmental sciences GE1-350 Meteorology. Climatology QC851-999 Bettina Richter Jürg Schweizer Mathias W. Rotach Alec van Herwijnen Modeling spatially distributed snow instability at a regional scale using Alpine3D |
topic_facet |
Avalanches snow snow mechanics Environmental sciences GE1-350 Meteorology. Climatology QC851-999 |
description |
Assessing the avalanche danger level requires snow stratigraphy and instability data. As such data are usually sparse, we investigated whether distributed snow cover modeling can be used to provide information on spatial instability patterns relevant for regional avalanche forecasting. Using Alpine3D, we performed spatially distributed simulations to evaluate snow instability for the winter season 2016–17 in the region of Davos, Switzerland. Meteorological data from automatic weather stations were interpolated to 100 m horizontal resolution and precipitation was scaled with snow depth measurements from airborne laser scanning. Modeled snow instability metrics assessed for two different weak layers suggested that the weak layer closer to the snow surface was more variable. Initially, it was less stable than the weak layer closer to the ground, yet it stabilized faster as the winter progressed. In spring, the simulated snowpack on south-facing slopes stabilized faster than on north-facing slopes, in line with the regional avalanche forecast. In the winter months January to March 2017, simulated instability metrics did not suggest that the snowpack on south-facing slopes was more stable, as reported in the regional avalanche forecast. Although a validation with field data is lacking, these model results still show the potential and challenges of distributed modeling for supporting operational avalanche forecasting. |
format |
Article in Journal/Newspaper |
author |
Bettina Richter Jürg Schweizer Mathias W. Rotach Alec van Herwijnen |
author_facet |
Bettina Richter Jürg Schweizer Mathias W. Rotach Alec van Herwijnen |
author_sort |
Bettina Richter |
title |
Modeling spatially distributed snow instability at a regional scale using Alpine3D |
title_short |
Modeling spatially distributed snow instability at a regional scale using Alpine3D |
title_full |
Modeling spatially distributed snow instability at a regional scale using Alpine3D |
title_fullStr |
Modeling spatially distributed snow instability at a regional scale using Alpine3D |
title_full_unstemmed |
Modeling spatially distributed snow instability at a regional scale using Alpine3D |
title_sort |
modeling spatially distributed snow instability at a regional scale using alpine3d |
publisher |
Cambridge University Press |
publishDate |
2021 |
url |
https://doi.org/10.1017/jog.2021.61 https://doaj.org/article/c906d489c1f24d3e8500549822d6d37a |
genre |
Journal of Glaciology |
genre_facet |
Journal of Glaciology |
op_source |
Journal of Glaciology, Vol 67, Pp 1147-1162 (2021) |
op_relation |
https://www.cambridge.org/core/product/identifier/S0022143021000617/type/journal_article https://doaj.org/toc/0022-1430 https://doaj.org/toc/1727-5652 doi:10.1017/jog.2021.61 0022-1430 1727-5652 https://doaj.org/article/c906d489c1f24d3e8500549822d6d37a |
op_doi |
https://doi.org/10.1017/jog.2021.61 |
container_title |
Journal of Glaciology |
container_volume |
67 |
container_issue |
266 |
container_start_page |
1147 |
op_container_end_page |
1162 |
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1766049109747171328 |