Predicting avalanche danger in northern Norway using statistical models
<p>Snow avalanches are one of the most impactful natural hazards in mountainous areas. Thus, the assessment and forecasting of avalanche danger are of great importance for the protection of life and property. A changing climate may lead to changes in avalanche danger, although the manifestatio...
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Copernicus Publications
2025-05-01
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| Series: | The Cryosphere |
| Online Access: | https://tc.copernicus.org/articles/19/1849/2025/tc-19-1849-2025.pdf |
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| author | K.-U. Eiselt R. G. Graversen R. G. Graversen |
| author_facet | K.-U. Eiselt R. G. Graversen R. G. Graversen |
| author_sort | K.-U. Eiselt |
| collection | DOAJ |
| description | <p>Snow avalanches are one of the most impactful natural hazards in mountainous areas. Thus, the assessment and forecasting of avalanche danger are of great importance for the protection of life and property. A changing climate may lead to changes in avalanche danger, although the manifestation is unclear. Since climate change is regionally different, an assessment of potential avalanche-danger changes should be conducted on a regional basis. Here the focus is on avalanche danger in the Troms region in northern Norway, i.e. a region in the Arctic. To estimate the linkage between avalanche danger and weather conditions in this region, we utilise expert assessments of regional avalanche-danger level (ADL), the 3 km Norwegian Reanalysis (NORA3), and snow-cover information from the snow model seNorge. Random forest (RF) models are trained and optimised for a binary case and for a four-level case. The binary-case RF model exhibits a much higher overall accuracy (76 %) than the four-level case RF model (57 %), which is due to the latter model often misclassifying ADL 1 as ADL 2 and ADL 4 as ADL 3. Still, the misclassification difference is seldom larger than one ADL, and the distribution of the frequencies of the different ADLs is reproduced. The most important predictive features are related to new snow and wind accumulated and averaged over several days. The binary-case RF model is used to hindcast avalanche-day frequency (ADF) from 1970 to 2024. In this period, the spring season (March–May) shows a small increase in ADF, whereas the winter season (December–February) exhibits negative trends. Moreover, the ADF is found to be correlated with the Arctic Oscillation (AO) index especially in winter, although this correlation appears to have deteriorated in recent years. Given recent advances in skill of representing the AO in decadal prediction systems, this is an encouraging result for the predictability of future avalanche-danger tendencies in northern Norway.</p> |
| format | Article |
| id | doaj-art-dc5aedab302c412cbab6267a8b63756d |
| institution | DOAJ |
| issn | 1994-0416 1994-0424 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | Copernicus Publications |
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| series | The Cryosphere |
| spelling | doaj-art-dc5aedab302c412cbab6267a8b63756d2025-08-20T02:58:19ZengCopernicus PublicationsThe Cryosphere1994-04161994-04242025-05-01191849187110.5194/tc-19-1849-2025Predicting avalanche danger in northern Norway using statistical modelsK.-U. Eiselt0R. G. Graversen1R. G. Graversen2Department of Physics and Technology, University of Tromsø, Tromsø, NorwayDepartment of Physics and Technology, University of Tromsø, Tromsø, NorwayNorwegian Meteorological Institute, Tromsø Office, Norway<p>Snow avalanches are one of the most impactful natural hazards in mountainous areas. Thus, the assessment and forecasting of avalanche danger are of great importance for the protection of life and property. A changing climate may lead to changes in avalanche danger, although the manifestation is unclear. Since climate change is regionally different, an assessment of potential avalanche-danger changes should be conducted on a regional basis. Here the focus is on avalanche danger in the Troms region in northern Norway, i.e. a region in the Arctic. To estimate the linkage between avalanche danger and weather conditions in this region, we utilise expert assessments of regional avalanche-danger level (ADL), the 3 km Norwegian Reanalysis (NORA3), and snow-cover information from the snow model seNorge. Random forest (RF) models are trained and optimised for a binary case and for a four-level case. The binary-case RF model exhibits a much higher overall accuracy (76 %) than the four-level case RF model (57 %), which is due to the latter model often misclassifying ADL 1 as ADL 2 and ADL 4 as ADL 3. Still, the misclassification difference is seldom larger than one ADL, and the distribution of the frequencies of the different ADLs is reproduced. The most important predictive features are related to new snow and wind accumulated and averaged over several days. The binary-case RF model is used to hindcast avalanche-day frequency (ADF) from 1970 to 2024. In this period, the spring season (March–May) shows a small increase in ADF, whereas the winter season (December–February) exhibits negative trends. Moreover, the ADF is found to be correlated with the Arctic Oscillation (AO) index especially in winter, although this correlation appears to have deteriorated in recent years. Given recent advances in skill of representing the AO in decadal prediction systems, this is an encouraging result for the predictability of future avalanche-danger tendencies in northern Norway.</p>https://tc.copernicus.org/articles/19/1849/2025/tc-19-1849-2025.pdf |
| spellingShingle | K.-U. Eiselt R. G. Graversen R. G. Graversen Predicting avalanche danger in northern Norway using statistical models The Cryosphere |
| title | Predicting avalanche danger in northern Norway using statistical models |
| title_full | Predicting avalanche danger in northern Norway using statistical models |
| title_fullStr | Predicting avalanche danger in northern Norway using statistical models |
| title_full_unstemmed | Predicting avalanche danger in northern Norway using statistical models |
| title_short | Predicting avalanche danger in northern Norway using statistical models |
| title_sort | predicting avalanche danger in northern norway using statistical models |
| url | https://tc.copernicus.org/articles/19/1849/2025/tc-19-1849-2025.pdf |
| work_keys_str_mv | AT kueiselt predictingavalanchedangerinnorthernnorwayusingstatisticalmodels AT rggraversen predictingavalanchedangerinnorthernnorwayusingstatisticalmodels AT rggraversen predictingavalanchedangerinnorthernnorwayusingstatisticalmodels |