Evaluating a prediction system for snow management
The evaluation of snowpack models capable of accounting for snow management in ski resorts is a major step towards acceptance of such models in supporting the daily decision-making process of snow production managers. In the framework of the EU Horizon 2020 (H2020) project PROSNOW, a service to enab...
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ftdoajarticles:oai:doaj.org/article:3a30f69934aa48e798d843b98016ff8b 2023-05-15T18:32:25+02:00 Evaluating a prediction system for snow management P. P. Ebner F. Koch V. Premier C. Marin F. Hanzer C. M. Carmagnola H. François D. Günther F. Monti O. Hargoaa U. Strasser S. Morin M. Lehning 2021-08-01T00:00:00Z https://doi.org/10.5194/tc-15-3949-2021 https://doaj.org/article/3a30f69934aa48e798d843b98016ff8b EN eng Copernicus Publications https://tc.copernicus.org/articles/15/3949/2021/tc-15-3949-2021.pdf https://doaj.org/toc/1994-0416 https://doaj.org/toc/1994-0424 doi:10.5194/tc-15-3949-2021 1994-0416 1994-0424 https://doaj.org/article/3a30f69934aa48e798d843b98016ff8b The Cryosphere, Vol 15, Pp 3949-3973 (2021) Environmental sciences GE1-350 Geology QE1-996.5 article 2021 ftdoajarticles https://doi.org/10.5194/tc-15-3949-2021 2022-12-31T12:37:11Z The evaluation of snowpack models capable of accounting for snow management in ski resorts is a major step towards acceptance of such models in supporting the daily decision-making process of snow production managers. In the framework of the EU Horizon 2020 (H2020) project PROSNOW, a service to enable real-time optimization of grooming and snow-making in ski resorts was developed. We applied snow management strategies integrated in the snowpack simulations of AMUNDSEN, Crocus, and SNOWPACK–Alpine3D for nine PROSNOW ski resorts located in the European Alps. We assessed the performance of the snow simulations for five winter seasons (2015–2020) using both ground-based data (GNSS-measured snow depth) and spaceborne snow maps (Copernicus Sentinel-2). Particular attention has been devoted to characterizing the spatial performance of the simulated piste snow management at a resolution of 10 m. The simulated results showed a high overall accuracy of more than 80 % for snow-covered areas compared to the Sentinel-2 data. Moreover, the correlation to the ground observation data was high. Potential sources for local differences in the snow depth between the simulations and the measurements are mainly the impact of snow redistribution by skiers; compensation of uneven terrain when grooming; or spontaneous local adaptions of the snow management, which were not reflected in the simulations. Subdividing each individual ski resort into differently sized ski resort reference units (SRUs) based on topography showed a slight decrease in mean deviation. Although this work shows plausible and robust results on the ski slope scale by all three snowpack models, the accuracy of the results is mainly dependent on the detailed representation of the real-world snow management practices in the models. As snow management assessment and prediction systems get integrated into the workflow of resort managers, the formulation of snow management can be refined in the future. Article in Journal/Newspaper The Cryosphere Directory of Open Access Journals: DOAJ Articles The Sentinel ENVELOPE(73.317,73.317,-52.983,-52.983) The Cryosphere 15 8 3949 3973 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
Environmental sciences GE1-350 Geology QE1-996.5 |
spellingShingle |
Environmental sciences GE1-350 Geology QE1-996.5 P. P. Ebner F. Koch V. Premier C. Marin F. Hanzer C. M. Carmagnola H. François D. Günther F. Monti O. Hargoaa U. Strasser S. Morin M. Lehning Evaluating a prediction system for snow management |
topic_facet |
Environmental sciences GE1-350 Geology QE1-996.5 |
description |
The evaluation of snowpack models capable of accounting for snow management in ski resorts is a major step towards acceptance of such models in supporting the daily decision-making process of snow production managers. In the framework of the EU Horizon 2020 (H2020) project PROSNOW, a service to enable real-time optimization of grooming and snow-making in ski resorts was developed. We applied snow management strategies integrated in the snowpack simulations of AMUNDSEN, Crocus, and SNOWPACK–Alpine3D for nine PROSNOW ski resorts located in the European Alps. We assessed the performance of the snow simulations for five winter seasons (2015–2020) using both ground-based data (GNSS-measured snow depth) and spaceborne snow maps (Copernicus Sentinel-2). Particular attention has been devoted to characterizing the spatial performance of the simulated piste snow management at a resolution of 10 m. The simulated results showed a high overall accuracy of more than 80 % for snow-covered areas compared to the Sentinel-2 data. Moreover, the correlation to the ground observation data was high. Potential sources for local differences in the snow depth between the simulations and the measurements are mainly the impact of snow redistribution by skiers; compensation of uneven terrain when grooming; or spontaneous local adaptions of the snow management, which were not reflected in the simulations. Subdividing each individual ski resort into differently sized ski resort reference units (SRUs) based on topography showed a slight decrease in mean deviation. Although this work shows plausible and robust results on the ski slope scale by all three snowpack models, the accuracy of the results is mainly dependent on the detailed representation of the real-world snow management practices in the models. As snow management assessment and prediction systems get integrated into the workflow of resort managers, the formulation of snow management can be refined in the future. |
format |
Article in Journal/Newspaper |
author |
P. P. Ebner F. Koch V. Premier C. Marin F. Hanzer C. M. Carmagnola H. François D. Günther F. Monti O. Hargoaa U. Strasser S. Morin M. Lehning |
author_facet |
P. P. Ebner F. Koch V. Premier C. Marin F. Hanzer C. M. Carmagnola H. François D. Günther F. Monti O. Hargoaa U. Strasser S. Morin M. Lehning |
author_sort |
P. P. Ebner |
title |
Evaluating a prediction system for snow management |
title_short |
Evaluating a prediction system for snow management |
title_full |
Evaluating a prediction system for snow management |
title_fullStr |
Evaluating a prediction system for snow management |
title_full_unstemmed |
Evaluating a prediction system for snow management |
title_sort |
evaluating a prediction system for snow management |
publisher |
Copernicus Publications |
publishDate |
2021 |
url |
https://doi.org/10.5194/tc-15-3949-2021 https://doaj.org/article/3a30f69934aa48e798d843b98016ff8b |
long_lat |
ENVELOPE(73.317,73.317,-52.983,-52.983) |
geographic |
The Sentinel |
geographic_facet |
The Sentinel |
genre |
The Cryosphere |
genre_facet |
The Cryosphere |
op_source |
The Cryosphere, Vol 15, Pp 3949-3973 (2021) |
op_relation |
https://tc.copernicus.org/articles/15/3949/2021/tc-15-3949-2021.pdf https://doaj.org/toc/1994-0416 https://doaj.org/toc/1994-0424 doi:10.5194/tc-15-3949-2021 1994-0416 1994-0424 https://doaj.org/article/3a30f69934aa48e798d843b98016ff8b |
op_doi |
https://doi.org/10.5194/tc-15-3949-2021 |
container_title |
The Cryosphere |
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15 |
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8 |
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3949 |
op_container_end_page |
3973 |
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1766216523426299904 |