Evaluating a prediction system for snow management
International audience 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 PRO...
Published in: | The Cryosphere |
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Main Authors: | , , , , , , , , , , , , |
Other Authors: | , , , , , |
Format: | Article in Journal/Newspaper |
Language: | English |
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HAL CCSD
2021
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Online Access: | https://hal-insu.archives-ouvertes.fr/insu-03668376 https://hal-insu.archives-ouvertes.fr/insu-03668376/document https://hal-insu.archives-ouvertes.fr/insu-03668376/file/tc-15-3949-2021.pdf https://doi.org/10.5194/tc-15-3949-2021 |
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English |
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[SDU]Sciences of the Universe [physics] |
spellingShingle |
[SDU]Sciences of the Universe [physics] Ebner, Pirmin Philipp Koch, Franziska Premier, Valentina Marin, Carlo Hanzer, Florian Carmagnola, Carlo Maria François, Hugues Günther, Daniel Monti, Fabiano Hargoaa, Olivier Strasser, Ulrich Morin, Samuel Lehning, Michael Evaluating a prediction system for snow management |
topic_facet |
[SDU]Sciences of the Universe [physics] |
description |
International audience 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. |
author2 |
Centre national de recherches météorologiques (CNRM) Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP) Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3) Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales Toulouse (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3) Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales Toulouse (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS) Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA) |
format |
Article in Journal/Newspaper |
author |
Ebner, Pirmin Philipp Koch, Franziska Premier, Valentina Marin, Carlo Hanzer, Florian Carmagnola, Carlo Maria François, Hugues Günther, Daniel Monti, Fabiano Hargoaa, Olivier Strasser, Ulrich Morin, Samuel Lehning, Michael |
author_facet |
Ebner, Pirmin Philipp Koch, Franziska Premier, Valentina Marin, Carlo Hanzer, Florian Carmagnola, Carlo Maria François, Hugues Günther, Daniel Monti, Fabiano Hargoaa, Olivier Strasser, Ulrich Morin, Samuel Lehning, Michael |
author_sort |
Ebner, Pirmin Philipp |
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 |
HAL CCSD |
publishDate |
2021 |
url |
https://hal-insu.archives-ouvertes.fr/insu-03668376 https://hal-insu.archives-ouvertes.fr/insu-03668376/document https://hal-insu.archives-ouvertes.fr/insu-03668376/file/tc-15-3949-2021.pdf https://doi.org/10.5194/tc-15-3949-2021 |
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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 https://hal-insu.archives-ouvertes.fr/insu-03668376 The Cryosphere, 2021, 15, pp.3949-3973. ⟨10.5194/tc-15-3949-2021⟩ |
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info:eu-repo/semantics/altIdentifier/doi/10.5194/tc-15-3949-2021 insu-03668376 https://hal-insu.archives-ouvertes.fr/insu-03668376 https://hal-insu.archives-ouvertes.fr/insu-03668376/document https://hal-insu.archives-ouvertes.fr/insu-03668376/file/tc-15-3949-2021.pdf BIBCODE: 2021TCry.15.3949E doi:10.5194/tc-15-3949-2021 |
op_rights |
http://creativecommons.org/licenses/by/ info:eu-repo/semantics/OpenAccess |
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 |
container_start_page |
3949 |
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3973 |
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1766216285532717056 |
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ftunivnantes:oai:HAL:insu-03668376v1 2023-05-15T18:32:13+02:00 Evaluating a prediction system for snow management Ebner, Pirmin Philipp Koch, Franziska Premier, Valentina Marin, Carlo Hanzer, Florian Carmagnola, Carlo Maria François, Hugues Günther, Daniel Monti, Fabiano Hargoaa, Olivier Strasser, Ulrich Morin, Samuel Lehning, Michael Centre national de recherches météorologiques (CNRM) Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP) Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3) Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales Toulouse (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3) Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales Toulouse (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS) Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA) 2021 https://hal-insu.archives-ouvertes.fr/insu-03668376 https://hal-insu.archives-ouvertes.fr/insu-03668376/document https://hal-insu.archives-ouvertes.fr/insu-03668376/file/tc-15-3949-2021.pdf https://doi.org/10.5194/tc-15-3949-2021 en eng HAL CCSD info:eu-repo/semantics/altIdentifier/doi/10.5194/tc-15-3949-2021 insu-03668376 https://hal-insu.archives-ouvertes.fr/insu-03668376 https://hal-insu.archives-ouvertes.fr/insu-03668376/document https://hal-insu.archives-ouvertes.fr/insu-03668376/file/tc-15-3949-2021.pdf BIBCODE: 2021TCry.15.3949E doi:10.5194/tc-15-3949-2021 http://creativecommons.org/licenses/by/ info:eu-repo/semantics/OpenAccess The Cryosphere https://hal-insu.archives-ouvertes.fr/insu-03668376 The Cryosphere, 2021, 15, pp.3949-3973. ⟨10.5194/tc-15-3949-2021⟩ [SDU]Sciences of the Universe [physics] info:eu-repo/semantics/article Journal articles 2021 ftunivnantes https://doi.org/10.5194/tc-15-3949-2021 2023-03-08T01:46:07Z International audience 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 Université de Nantes: HAL-UNIV-NANTES The Sentinel ENVELOPE(73.317,73.317,-52.983,-52.983) The Cryosphere 15 8 3949 3973 |