Articles | Volume 17, issue 17
https://doi.org/10.5194/gmd-17-6775-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-17-6775-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
12 Sep 2024
Model description paper |
| 12 Sep 2024
| 12 Sep 2024
openAMUNDSEN v1.0: an open-source snow-hydrological model for mountain regions
Ulrich Strasser
CORRESPONDING AUTHOR
Department of Geography, University of Innsbruck, Innrain 52, 6020 Innsbruck, Austria
Michael Warscher
Department of Geography, University of Innsbruck, Innrain 52, 6020 Innsbruck, Austria
Erwin Rottler
Department of Geography, University of Innsbruck, Innrain 52, 6020 Innsbruck, Austria
Florian Hanzer
Department of Geography, University of Innsbruck, Innrain 52, 6020 Innsbruck, Austria
lumiosys GmbH, Innrain 52, 6020 Innsbruck, Austria
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This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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We developed openAMUNDSEN-DA, an open source framework for ensemble based snow data assimilation coupled to the fully distributed snow hydrological model openAMUNDSEN. It represents uncertainty by perturbing meteorological forcing and assimilates in situ and satellite snow observations using a sequential particle filter. The framework provides a reproducible workflow for observation preprocessing, ensemble simulation, assimilation, diagnostics, plots, maps and reporting in mountain regions.
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In this study, we simulate the snow cover in a complex mountain area under historical conditions and for a time period characterized by a 1 °C warming using a large number of different snow models. Our objective is the assessment of differences in the modelling results induced by different snow model configurations. We find that differences stemming from the choice of snowmelt method, land cover map and spatial resolution can be comparable in magnitude to the effect of a 1°C warming.
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Continuous observations of snow and climate at high altitudes are still sparse. We present a unique collection of weather and snow cover data from three automatic weather stations at remote locations in the Ötztal Alps (Austria) that include continuous recordings of snow cover properties. The data are available over multiple winter seasons and enable new insights for snow hydrological research. The data are also used in operational applications, i.e., for avalanche warning and flood forecasting.
Franz Wagner, Erwin Rottler, and Ulrich Strasser
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Short summary
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We developed openAMUNDSEN-DA, an open source framework for ensemble based snow data assimilation coupled to the fully distributed snow hydrological model openAMUNDSEN. It represents uncertainty by perturbing meteorological forcing and assimilates in situ and satellite snow observations using a sequential particle filter. The framework provides a reproducible workflow for observation preprocessing, ensemble simulation, assimilation, diagnostics, plots, maps and reporting in mountain regions.
Erwin Rottler, Brage Storebakken, Michael Warscher, Florian Hanzer, Elena Bertazza, and Ulrich Strasser
The Cryosphere, 20, 2351–2373, https://doi.org/10.5194/tc-20-2351-2026, https://doi.org/10.5194/tc-20-2351-2026, 2026
Short summary
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In this study, we simulate the snow cover in a complex mountain area under historical conditions and for a time period characterized by a 1 °C warming using a large number of different snow models. Our objective is the assessment of differences in the modelling results induced by different snow model configurations. We find that differences stemming from the choice of snowmelt method, land cover map and spatial resolution can be comparable in magnitude to the effect of a 1°C warming.
Michael Warscher, Thomas Marke, Erwin Rottler, and Ulrich Strasser
Earth Syst. Sci. Data, 16, 3579–3599, https://doi.org/10.5194/essd-16-3579-2024, https://doi.org/10.5194/essd-16-3579-2024, 2024
Short summary
Short summary
Continuous observations of snow and climate at high altitudes are still sparse. We present a unique collection of weather and snow cover data from three automatic weather stations at remote locations in the Ötztal Alps (Austria) that include continuous recordings of snow cover properties. The data are available over multiple winter seasons and enable new insights for snow hydrological research. The data are also used in operational applications, i.e., for avalanche warning and flood forecasting.
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Climate change fundamentally alters glaciated high-alpine areas, but it is unclear how this affects riverine sediment transport. As a first step, we aimed to identify the most important processes and source areas in three nested catchments in the Ötztal, Austria, in the past 15 years. We found that areas above 2500 m were crucial and that summer rainstorms were less influential than glacier melt. These findings provide a baseline for studies on future changes in high-alpine sediment dynamics.
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Short summary
openAMUNDSEN is a fully distributed open-source snow-hydrological model for mountain catchments. It includes process representations of an empirical, semi-empirical, and physical nature. It uses temperature, precipitation, humidity, radiation, and wind speed as forcing data and is computationally efficient, of a modular nature, and easily extendible. The Python code is available on GitHub (https://github.com/openamundsen/openamundsen), including documentation (https://doc.openamundsen.org).
openAMUNDSEN is a fully distributed open-source snow-hydrological model for mountain catchments....
