A Large-scale Validation of Snowpack Simulations in Support of Avalanche Forecasting Focusing on Critical Layers

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Location: Deutsche Nationalbibliothek Frankfurt am Main

Extent: Online-Ressource

Language: Englisch

Bibliographic citation: A Large-scale Validation of Snowpack Simulations in Support of Avalanche Forecasting Focusing on Critical Layers ; day:13 ; month:04 ; year:2023 ; pages:1-38 ; extent:38
EGUsphere ; (13.04.2023), 1-38 (gesamt 38)

Creator: Herla, Florian
Haegeli, Pascal
Horton, Simon
Mair, Patrick

DOI: 10.5194/egusphere-2023-420

URN: urn:nbn:de:101:1-2023042005291303620586

Rights: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.

Last update: 14.08.2025, 10:47 AM CEST

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Herla, Florian
Haegeli, Pascal
Horton, Simon
Mair, Patrick

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Using snow depth observation to provide insight into the quality of regional-scale snowpack simulations for avalanche forecasting

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Prediction of natural dry-snow avalanche activity using physics-based snowpack simulations

Data efficient Random Forest model for avalanche forecasting

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A large-scale validation of snowpack simulations in support of avalanche forecasting focusing on critical layers

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Snow profile alignment and similarity assessment for aggregating, clustering, and evaluating snowpack model output for avalanche forecasting

Snow profile alignment and similarity assessment for aggregating, clustering, and evaluating of snowpack model output for avalanche forecasting

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Prediction of natural dry-snow avalanche activity using physics-based snowpack simulations

Data efficient Random Forest model for avalanche forecasting

Spatio-temporal avalanche forecasting with Support Vector Machines

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On the importance of snowpack stability, its frequency distribution, and avalanche size in assessing the avalanche danger level: a data-driven approach

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A Large-scale Validation of Snowpack Simulations in Support of Avalanche Forecasting Focusing on Critical Layers

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Other Objects (12)

A large-scale validation of snowpack simulations in support of avalanche forecasting focusing on critical layers

On the importance of snowpack stability, the frequency distribution of snowpack stability, and avalanche size in assessing the avalanche danger level

Snow profile alignment and similarity assessment for aggregating, clustering, and evaluating snowpack model output for avalanche forecasting

Snow profile alignment and similarity assessment for aggregating, clustering, and evaluating of snowpack model output for avalanche forecasting

Using snow depth observations to provide insight into the quality of snowpack simulations for regional-scale avalanche forecasting

Using snow depth observation to provide insight into the quality of regional-scale snowpack simulations for avalanche forecasting

Combining modelled snowpack stability with machine learning to predict avalanche activity

Prediction of natural dry-snow avalanche activity using physics-based snowpack simulations

Data efficient Random Forest model for avalanche forecasting

Spatio-temporal avalanche forecasting with Support Vector Machines

Spatial snowpack properties in a snow-avalanche release area: An extreme dry-slab avalanche case on Mt. Nodanishoji, Japan, in 2021

On the importance of snowpack stability, its frequency distribution, and avalanche size in assessing the avalanche danger level: a data-driven approach

A large-scale validation of snowpack simulations in support of avalanche forecasting focusing on critical layers

On the importance of snowpack stability, the frequency distribution of snowpack stability, and avalanche size in assessing the avalanche danger level

Snow profile alignment and similarity assessment for aggregating, clustering, and evaluating snowpack model output for avalanche forecasting

Snow profile alignment and similarity assessment for aggregating, clustering, and evaluating of snowpack model output for avalanche forecasting

Using snow depth observations to provide insight into the quality of snowpack simulations for regional-scale avalanche forecasting

Using snow depth observation to provide insight into the quality of regional-scale snowpack simulations for avalanche forecasting

Combining modelled snowpack stability with machine learning to predict avalanche activity

Prediction of natural dry-snow avalanche activity using physics-based snowpack simulations

Data efficient Random Forest model for avalanche forecasting

Spatio-temporal avalanche forecasting with Support Vector Machines

Spatial snowpack properties in a snow-avalanche release area: An extreme dry-slab avalanche case on Mt. Nodanishoji, Japan, in 2021

On the importance of snowpack stability, its frequency distribution, and avalanche size in assessing the avalanche danger level: a data-driven approach

A large-scale validation of snowpack simulations in support of avalanche forecasting focusing on critical layers

On the importance of snowpack stability, the frequency distribution of snowpack stability, and avalanche size in assessing the avalanche danger level

Snow profile alignment and similarity assessment for aggregating, clustering, and evaluating snowpack model output for avalanche forecasting

Snow profile alignment and similarity assessment for aggregating, clustering, and evaluating of snowpack model output for avalanche forecasting

Using snow depth observations to provide insight into the quality of snowpack simulations for regional-scale avalanche forecasting

Using snow depth observation to provide insight into the quality of regional-scale snowpack simulations for avalanche forecasting

Combining modelled snowpack stability with machine learning to predict avalanche activity

Prediction of natural dry-snow avalanche activity using physics-based snowpack simulations

Data efficient Random Forest model for avalanche forecasting

Spatio-temporal avalanche forecasting with Support Vector Machines

Spatial snowpack properties in a snow-avalanche release area: An extreme dry-slab avalanche case on Mt. Nodanishoji, Japan, in 2021

On the importance of snowpack stability, its frequency distribution, and avalanche size in assessing the avalanche danger level: a data-driven approach

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