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
Related authors
Erwin Rottler, Brage Storebakken, Michael Warscher, Florian Hanzer, Elena Bertazza, and Ulrich Strasser
EGUsphere, https://doi.org/10.5194/egusphere-2025-3707, https://doi.org/10.5194/egusphere-2025-3707, 2025
This preprint is open for discussion and under review for The Cryosphere (TC).
Short summary
Short summary
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 goal is the assessment of differences in the modelling results induced by different snow model configurations. Our results suggests that differences showing up depending on the selected snowmelt method, land cover map and spatial resolution can be in the same range as the impact 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.
Pirmin Philipp Ebner, Franziska Koch, Valentina Premier, Carlo Marin, Florian Hanzer, Carlo Maria Carmagnola, Hugues François, Daniel Günther, Fabiano Monti, Olivier Hargoaa, Ulrich Strasser, Samuel Morin, and Michael Lehning
The Cryosphere, 15, 3949–3973, https://doi.org/10.5194/tc-15-3949-2021, https://doi.org/10.5194/tc-15-3949-2021, 2021
Short summary
Short summary
A service to enable real-time optimization of grooming and snow-making at ski resorts was developed and evaluated using both GNSS-measured snow depth and spaceborne snow maps derived from Copernicus Sentinel-2. The correlation to the ground observation data was high. Potential sources for the overestimation of the snow depth by the simulations are mainly the impact of snow redistribution by skiers, compensation of uneven terrain, or spontaneous local adaptions of the snow management.
Michael Warscher, Thomas Marke, and Ulrich Strasser
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2021-68, https://doi.org/10.5194/essd-2021-68, 2021
Revised manuscript not accepted
Short summary
Short summary
Continuous observations of snow and climate in high altitudes are still sparse. We present data from automatic weather and snow stations in the Ötztal Alps (Austria) that include continuous recordings of snow cover properties (snow depth, water equivalent, density, solid and liquid water content, snow temperature profiles, surface temperature, snow drift). The data can be used in different scientific fields, as well as in operational applications, i.e., avalanche warning and flood forecasting.
Michael Matiu, Alice Crespi, Giacomo Bertoldi, Carlo Maria Carmagnola, Christoph Marty, Samuel Morin, Wolfgang Schöner, Daniele Cat Berro, Gabriele Chiogna, Ludovica De Gregorio, Sven Kotlarski, Bruno Majone, Gernot Resch, Silvia Terzago, Mauro Valt, Walter Beozzo, Paola Cianfarra, Isabelle Gouttevin, Giorgia Marcolini, Claudia Notarnicola, Marcello Petitta, Simon C. Scherrer, Ulrich Strasser, Michael Winkler, Marc Zebisch, Andrea Cicogna, Roberto Cremonini, Andrea Debernardi, Mattia Faletto, Mauro Gaddo, Lorenzo Giovannini, Luca Mercalli, Jean-Michel Soubeyroux, Andrea Sušnik, Alberto Trenti, Stefano Urbani, and Viktor Weilguni
The Cryosphere, 15, 1343–1382, https://doi.org/10.5194/tc-15-1343-2021, https://doi.org/10.5194/tc-15-1343-2021, 2021
Short summary
Short summary
The first Alpine-wide assessment of station snow depth has been enabled by a collaborative effort of the research community which involves more than 30 partners, 6 countries, and more than 2000 stations. It shows how snow in the European Alps matches the climatic zones and gives a robust estimate of observed changes: stronger decreases in the snow season at low elevations and in spring at all elevations, however, with considerable regional differences.
Erwin Rottler, Brage Storebakken, Michael Warscher, Florian Hanzer, Elena Bertazza, and Ulrich Strasser
EGUsphere, https://doi.org/10.5194/egusphere-2025-3707, https://doi.org/10.5194/egusphere-2025-3707, 2025
This preprint is open for discussion and under review for The Cryosphere (TC).
Short summary
Short summary
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 goal is the assessment of differences in the modelling results induced by different snow model configurations. Our results suggests that differences showing up depending on the selected snowmelt method, land cover map and spatial resolution can be in the same range as the impact 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.
Lena Katharina Schmidt, Till Francke, Erwin Rottler, Theresa Blume, Johannes Schöber, and Axel Bronstert
Earth Surf. Dynam., 10, 653–669, https://doi.org/10.5194/esurf-10-653-2022, https://doi.org/10.5194/esurf-10-653-2022, 2022
Short summary
Short summary
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.
Pirmin Philipp Ebner, Franziska Koch, Valentina Premier, Carlo Marin, Florian Hanzer, Carlo Maria Carmagnola, Hugues François, Daniel Günther, Fabiano Monti, Olivier Hargoaa, Ulrich Strasser, Samuel Morin, and Michael Lehning
The Cryosphere, 15, 3949–3973, https://doi.org/10.5194/tc-15-3949-2021, https://doi.org/10.5194/tc-15-3949-2021, 2021
Short summary
Short summary
A service to enable real-time optimization of grooming and snow-making at ski resorts was developed and evaluated using both GNSS-measured snow depth and spaceborne snow maps derived from Copernicus Sentinel-2. The correlation to the ground observation data was high. Potential sources for the overestimation of the snow depth by the simulations are mainly the impact of snow redistribution by skiers, compensation of uneven terrain, or spontaneous local adaptions of the snow management.
Erwin Rottler, Axel Bronstert, Gerd Bürger, and Oldrich Rakovec
Hydrol. Earth Syst. Sci., 25, 2353–2371, https://doi.org/10.5194/hess-25-2353-2021, https://doi.org/10.5194/hess-25-2353-2021, 2021
Short summary
Short summary
The mesoscale hydrological model (mHM) forced with an ensemble of climate projection scenarios was used to assess potential future changes in flood seasonality in the Rhine River basin. Results indicate that future changes in flood characteristics are controlled by increases in precipitation sums and diminishing snowpacks. The decreases in snowmelt can counterbalance increasing precipitation, resulting in only small and transient changes in streamflow maxima.
Michael Warscher, Thomas Marke, and Ulrich Strasser
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2021-68, https://doi.org/10.5194/essd-2021-68, 2021
Revised manuscript not accepted
Short summary
Short summary
Continuous observations of snow and climate in high altitudes are still sparse. We present data from automatic weather and snow stations in the Ötztal Alps (Austria) that include continuous recordings of snow cover properties (snow depth, water equivalent, density, solid and liquid water content, snow temperature profiles, surface temperature, snow drift). The data can be used in different scientific fields, as well as in operational applications, i.e., avalanche warning and flood forecasting.
Michael Matiu, Alice Crespi, Giacomo Bertoldi, Carlo Maria Carmagnola, Christoph Marty, Samuel Morin, Wolfgang Schöner, Daniele Cat Berro, Gabriele Chiogna, Ludovica De Gregorio, Sven Kotlarski, Bruno Majone, Gernot Resch, Silvia Terzago, Mauro Valt, Walter Beozzo, Paola Cianfarra, Isabelle Gouttevin, Giorgia Marcolini, Claudia Notarnicola, Marcello Petitta, Simon C. Scherrer, Ulrich Strasser, Michael Winkler, Marc Zebisch, Andrea Cicogna, Roberto Cremonini, Andrea Debernardi, Mattia Faletto, Mauro Gaddo, Lorenzo Giovannini, Luca Mercalli, Jean-Michel Soubeyroux, Andrea Sušnik, Alberto Trenti, Stefano Urbani, and Viktor Weilguni
The Cryosphere, 15, 1343–1382, https://doi.org/10.5194/tc-15-1343-2021, https://doi.org/10.5194/tc-15-1343-2021, 2021
Short summary
Short summary
The first Alpine-wide assessment of station snow depth has been enabled by a collaborative effort of the research community which involves more than 30 partners, 6 countries, and more than 2000 stations. It shows how snow in the European Alps matches the climatic zones and gives a robust estimate of observed changes: stronger decreases in the snow season at low elevations and in spring at all elevations, however, with considerable regional differences.
Cited articles
Allen, R. G., Pereira, L. S., Raes, D., and Smith, M.: Crop evapotranspiration - Guidelines for computing crop water requirements, FAO Irrigation and Drainage Paper No. 56, 174 pp., ISBN 92-5-104219-5, https://www.fao.org/3/x0490e/x0490e00.htm (last access: 9 September 2024), 1998.
Anderson, E. A.: A point energy and mass balance model of a snow cover. NOAA Technical Report NWS 19, 1–172, https://repository.library.noaa.gov/view/noaa/6392 (last access: 9 September 2024), 1976.
Asztalos, J., Kirnbauer, R., Escher-Vetter, H., and Braun, L.: A distributed energy balance snowmelt model as a component of a flood forecasting system for the Inn river, Proceedings of the Alpine*Snow*Workshop, edited by: Strasser, U. and Vogel M., 5–6 October 2006, Munich, Germany, Research report 53, National Park Berchtesgaden, ISBN 13 978-3-922325-60-4, 2007.
Barnes, S. L.: A technique for maximising details in numerical weather map analysis. J. Appl. Meteor., 3, 396–409, 1964.
Barnett, T. P., Adam, J. C., and Lettenmaier, D. P.: Potential impacts of a warming climate on water availability in snow- dominated regions, Nature, 438, 303–309, https://doi.org/10.1038/nature04141, 2005.
Bavay, M. and Egger, T.: MeteoIO 2.4.2: a preprocessing library for meteorological data, Geosci. Model Dev., 7, 3135–3151, https://doi.org/10.5194/gmd-7-3135-2014, 2014.
Bernhardt, M. and Schulz, K.: SnowSlide: A simple routine for calculating gravitational snow transport, Geophys. Res. Lett., 37, L11502, https://doi.org/10.1029/2010GL043086, 2010.
Blöschl, G.: Scaling issues in snow hydrology, Hydrol. Process., 13, 2149–2175, 1999.
Blöschl, G. and Kirnbauer, R.: Point snowmelt models with different degrees of complexity–internal processes, J. Hydrol., 129, 127–147, https://doi.org/10.1016/0022-1694(91)90048-M, 1991.
Braun, L. N.: Simulation of snowmelt-runoff in lowland and lower alpine regions of Switzerland, PhD thesis, ETH Zurich, 1984.
Corripio, J.: Vectorial algebra algorithms for calculating terrain parameters from DEMs and solar radiation modelling in mountainous terrain, Int. J. Geogr. Inf. Sci., 17, 1–23, https://doi.org/10.1080/713811744, 2003.
De Gregorio, L., Callegari, M., Marin, C., Zebisch, M., Bruzzone, L., Demir, B., Strasser, U., Marke, T., Günther, D., Nadalet, R., and Notarnicola, C.: A novel data fusion technique for snow cover retrieval, J. Sel. Top. Appl. Earth Obs., 12, 8, https://doi.org/10.1109/JSTARS.2019.2920676, 2019a.
De Gregorio, L., Günther, D., Callegari, M., Strasser, U., Zebisch, M., Bruzzone, L., and Notarnicola, C.: Improving SWE Estimation by Fusion of Snow Models with Topographic and Remotely Sensed Data, Remote Sens., 11, 2033, https://doi.org/10.3390/rs11172033, 2019b.
Department of Geography, University of Innsbruck: Continuous meteorological and snow hydrological measurements for 2013–2023 from three automatic weather stations (AWS) in the upper Rofental, Ötztal Alps, Austria, GFZ Data Services [data set], https://doi.org/10.5880/fidgeo.2023.037, 2024.
Ebner, P. P., Koch, F., Premier, V., Marin, C., Hanzer, F., Carmagnola, C. M., François, H., Günther, D., Monti, F., Hargoaa, O., Strasser, U., Morin, S., and Lehning, M.: Evaluating a prediction system for snow management, The Cryosphere, 15, 3949–3973, https://doi.org/10.5194/tc-15-3949-2021, 2021.
Essery, R., Rutter, N., Pomeroy, J., Baxter, R., Staehli, M., Gustafsson, D., Barr, A., Bartlett, P., and Elder, K.: SNOWMIP2: An evaluation of forest snow process simulations, B. Am. Meteorol. Soc., 90, 1120–1136, https://doi.org/10.1175/2009BAMS2629.1, 2009.
Essery, R., Morin, S., Lejeune, Y., and Ménard C. B.: A comparison of 1701 snow models using observations from an alpine site, Adv. Water Res., 55, 131–148, https://doi.org/10.1016/j.advwatres.2012.07.013, 2013.
Essery, R.: A factorial snowpack model (FSM 1.0), Geosci. Model Dev., 8, 3867–3876, https://doi.org/10.5194/gmd-8-3867-2015, 2015.
Etchevers, P., Martin, E., Brown, R., Fierz, C., Lejeune, Y., Bazile, E., Boone, A., Dai, Y.-J., Essery, R. L. E., Fernandez, Y., Gusev, Y., Jordan, R., Foren, V., Kowalczyk, E., Nasonova, N. O., Pyles, R. D., Schlosser, A., Shmakin, A. B., Smirnova, T. G., Strasser, U., Verseghy, D., Yamazaki, T., and Yang, Z.-L.: Validation of the surface energy budget simulated by several snow models (SnowMIP project), Ann. Glaciol., 38, 150–158, https://doi.org/10.3189/172756404781814825, 2004.
Fischer, A., Seiser, B., Stocker Waldhuber, M., Mitterer, C., and Abermann, J.: Tracing glacier changes in Austria from the Little Ice Age to the present using a lidar-based high-resolution glacier inventory in Austria, The Cryosphere, 9, 753–766, https://doi.org/10.5194/tc-9-753-2015, 2015.
Förster, K., Hanzer, F., Winter, B., Marke, T., and Strasser, U.: An open-source MEteoroLOgical observation time series DISaggregation Tool (MELODIST v0.1.1), Geosci. Model Dev., 9, 2315–2333, https://doi.org/10.5194/gmd-9-2315-2016, 2016.
Freudiger, D., Kohn, I., Seibert, J., Stahl, K., and Weiler, M.: Snow redistribution for the hydrological modeling of alpine catchments, WIREs Water, 4, e1232, https://doi.org/10.1002/wat2.1232, 2017.
Goodison, B. E., Louie, P., and Yang, D.: WMO solid precipitation measurement intercomparison, Tech. Rep. WMO/TD 872, Geneva, 1998.
Gruber, S.: A mass-conserving fast algorithm to parameterize gravitational transport and deposition using digital elevation models, Water Resour. Res., 43, W06412, https://doi.org/10.1029/2006WR004868, 2007.
Grünewald, T., Stötter, J., Pomeroy, J. W., Dadic, R., Moreno Baños, I., Marturià, J., Spross, M., Hopkinson, C., Burlando, P., and Lehning, M.: Statistical modelling of the snow depth distribution in open alpine terrain, Hydrol. Earth Syst. Sci., 17, 3005–3021, https://doi.org/10.5194/hess-17-3005-2013, 2013.
Grünewald, T., Bühler, Y., and Lehning, M.: Elevation dependency of mountain snow depth, The Cryosphere, 8, 2381–2394, https://doi.org/10.5194/tc-8-2381-2014, 2014.
Günther, D., Marke, T., Essery, R., and Strasser, U.: Uncertainties in Snowpack Simulations – Assessing the Impact of Model Structure, Parameter and Forcing Data Error on Point-Scale Energy-Balance Snow Model Performance, Water Resour. Res., 55, 2779–2800, https://doi.org/10.1029/2018WR023403, 2019.
Günther, D., Hanzer, F., Warscher, M., Essery, R., and Strasser, U.: Including parameter uncertainty in an intercomparison of physically-based snow models, Front. Earth Sci., 8, 542599, https://doi.org/10.3389/feart.2020.542599, 2020.
Hanzer, F., Marke, T., and Strasser, U.: Distributed, explicit modelling of technical snow production for a ski area in the Schladming Region (Austrian Alps), Cold Reg. Sci. Technol., 108, 113–124, https://doi.org/10.1016/j.coldregions.2014.08.003, 2014.
Hanzer, F., Helfricht, K., Marke, T., and Strasser, U.: Multilevel spatiotemporal validation of snow/ice mass balance and runoff modeling in glacierized catchments, The Cryosphere, 10, 1859–1881, https://doi.org/10.5194/tc-10-1859-2016, 2016.
Hanzer, F., Förster, K., Nemec, J., and Strasser, U.: Projected cryospheric and hydrological impacts of 21st century climate change in the ötztal Alps (Austria) simulated using a physically based approach, Hydrol. Earth Syst. Sci., 22, 1593–1614, https://doi.org/10.5194/hess-22-1593-2018, 2018.
Hanzer, F., Carmagnola, C. M., Ebner, P. P., Koch, F., Monti, F., Bavay, M., Bernhardt, M., Lafaysse, M., Lehning, M., Strasser, U., François, H., and Morin, S.: Simulation of snow management in Alpine ski resorts using three different snow models, Cold Reg. Sci. Technol., 172, 102995, https://doi.org/10.1016/j.coldregions.2020.102995, 2020.
Hanzer, F., Warscher, M., and Strasser, U.: openAMUNDSEN example data (v1.0), Zenodo [sample], https://doi.org/10.5281/zenodo.13740611, 2024a.
Hanzer, F., Warscher, M., and Strasser, U.: openAMUNDSEN v1.0.0 (v1.0.0), Zenodo [code], https://doi.org/10.5281/zenodo.11859175, 2024b.
Harris, C. R., Millman, K. J., van der Walt, S. J., Gommers, R., Virtanen, P., Cournapeau, D., Wieser, E., Taylor, J., Berg, S., Smith, N. J., Kern, R., Picus, M., Hoyer, S., van Kerkwijk, M. H., Brett, M., Haldane, A., del Río, J. F., Wiebe, M., Peterson, P., Gérard-Marchant, P., Sheppard, K., Reddy, T., Weckesser, W., Abbassi, H., Gohlke, C., and Oliphant, T. E.: Array programming with NumPy, Nature, 585, 7825, https://doi.org/10.1038/s41586-020-2649-2, 2020.
Huss, M. and Farinotti, D.: Distributed ice thickness and volume of all glaciers around the globe, J. Geophys. Res.-Earth Surf., 117, F04010, https://doi.org/10.1029/2012JF002523, 2012.
Helfricht, K.: Analysis of the spatial and temporal variation of seasonal snow accumulation in Alpine catchments using airborne laser scanning, PhD thesis, Innsbruck, 2014.
Hoyer, S. and Hamman, J.: xarray: N-D labeled Arrays and Datasets in Python, J. Open Res. Soft., 5, 10, https://doi.org/10.5334/jors.148, 2017.
Jordan, R.: A one-dimensional temperature model for a snow cover: Technical documentation for SNTHERM, 89, Tech. rep., Hanover, NH, 1991.
Kochendorfer, J., Rasmussen, R., Wolff, M., Baker, B., Hall, M. E., Meyers, T., Landolt, S., Jachcik, A., Isaksen, K., Brækkan, R., and Leeper, R.: The quantification and correction of wind-induced precipitation measurement errors, Hydrol. Earth Syst. Sci., 21, 1973–1989, https://doi.org/10.5194/hess-21-1973-2017, 2017.
Koivusalo, H., Heikinheimo, M., and Karvonen, T.: Test of a simple two-layer parameterisation to simulate the energy balance and temperature of a snow pack, Theor. Appl. Clim., 70, 65–79, https://doi.org/10.1007/s007040170006, 2001.
Kratzert, F., Gauch, M., Nearing, G., Hochreiter, S., and Klotz, D.: Niederschlags-Abfluss-Modellierung mit Long Short-Term Memory (LSTM), Österr. Wasser- und Abfallw., https://doi.org/10.1007/s00506-021-00767-z, 2021.
Krinner, G., Derksen, C., Essery, R., Flanner, M., Hagemann, S., Clark, M., Hall, A., Rott, H., Brutel-Vuilmet, C., Kim, H., Ménard, C. B., Mudryk, L., Thackeray, C., Wang, L., Arduini, G., Balsamo, G., Bartlett, P., Boike, J., Boone, A., Chéruy, F., Colin, J., Cuntz, M., Dai, Y., Decharme, B., Derry, J., Ducharne, A., Dutra, E., Fang, X., Fierz, C., Ghattas, J., Gusev, Y., Haverd, V., Kontu, A., Lafaysse, M., Law, R., Lawrence, D., Li, W., Marke, T., Marks, D., Ménégoz, M., Nasonova, O., Nitta, T., Niwano, M., Pomeroy, J., Raleigh, M. S., Schaedler, G., Semenov, V., Smirnova, T. G., Stacke, T., Strasser, U., Svenson, S., Turkov, D., Wang, T., Wever, N., Yuan, H., Zhou, W., and Zhu, D.: ESM-SnowMIP: assessing snow models and quantifying snow-related climate feedbacks, Geosci. Model Dev., 11, 5027–5049, https://doi.org/10.5194/gmd-11-5027-2018, 2018.
Lam, S. K., Pitrou, A., and Seibert, S.: Numba: A llvm-based python jit compiler, Proceedings of the Second Workshop on the LLVM Compiler Infrastructure in HPC, 15 November 2015, Austin, TX, USA, 1–6, 2015.
Lam, R., Sanchez-Gonzalez, A., Wilson, M., Wirnsberger, P., Fortunato, M., Alet, F., Ravuri, S., Ewalds, T., Eaton-Rosen, Z., Hu, W., Merose, A., Hoyer, S., Holland, G., Vinyals, O., Stott, J., Pritzel, A., Mohamed, S., and Battaglia, P.: Learning skillfull medium-range global weather forecasting, Science, 382, 1416–1421, https://doi.org/10.1126/science.adi2336, 2023.
Lehning, M., Bartelt, P., Brown, B., Russi, T., Stockli, U., and Zimmerli, M.: SNOWPACK model calculations for avalanche warning based upon a new network of weather and snow stations, Cold Reg. Sci. Technol., 30, 145–157, https://doi.org/10.1016/S0165-232X(99)00022-1, 1999.
Lindström, G.: A Simple Automatic Calibration Routine for the HBV Model. Nord. Hydrol., 28, 153–168, ISSN 0029-1277, E-ISSN 1996-9694, 1997.
Liston, G. E. and Elder, K.: A meteorological distribution system for high-resolution terrestrial modeling (MicroMet), J. Hydrometeor., 7, 217–234, https://doi.org/10.1175/JHM486.1, 2006.
Marke, T.: Development and Application of a Model Interface To couple Land Surface Models with Regional Climate Models For Climate Change Risk Assessment In the Upper Danube Watershed. Dissertation, Ludwig-Maximilians-Universität München, München, 188 pp., https://doi.org/10.5282/edoc.9162, 2008.
Marke, T., Strasser, U., Hanzer, F., Wilcke, R., Gobiet, A., and Stötter, J.: Scenarios of future snow conditions in Styria (Austrian Alps), J. Hydrometeor., 16, 261–277, https://doi.org/10.1175/JHM-D-14-0035.1, 2015.
Marke, T., Mair, E., Förster, K., Hanzer, F., Garvelmann, J., Pohl, S., Warscher, M., and Strasser, U.: ESCIMO.spread (v2): parameterization of a spreadsheet-based energy balance snow model for inside-canopy conditions, Geosci. Model Dev., 9, 633–646, https://doi.org/10.5194/gmd-9-633-2016, 2016.
Marke, T., Hanzer, F., Olefs, M., and Strasser, U.: Simulation of Past Changes in the Austrian Snow Cover 1948–2009, J. Hydrometeor., 19, 1529–1545, https://doi.org/10.1175/JHM-D-17-0245.1, 2018.
Mauser, W., Prasch, M., and Strasser, U.: Physically based Modelling of Climate Change Impact on Snow Cover Dynamics in Alpine Regions using a Stochastic Weather Generator. Proceedings of the International Congress on Modelling and Simulation MODSIM07 2007, Christchurch, New Zealand, 2007.
McKinney, W.: Data Structures for Statistical Computing in Python. Proceedings of the 9th Python in Science Conference, 56–61, https://doi.org/10.25080/Majora-92bf1922-00a, 2010.
Menard, C., Essery, R., Krinner, G., Arduini, G., Bartlett, P., Boone, A., Brutel-Vuilmet, C., Burke, E., Cuntz, M., Dai, Y., Decharme, B., Dutra, E., Fang, L., Fierz, C., Gusev, Y., Hagemann, S., Haverd, V., Kim, H., Lafaysse, M., Marke, T., Nasonova, O., Nitta, T., Niwano, M., Pomeroy, J., Schaedler, G., Semenov, V., Smirnova, T., Strasser, U., Swenson, S., Turkov, D., Wever, N., and Yuan, H.: Scientific and human errors in a snow model intercomparison, B. Am. Meteorol. Soc., published online, E61–E79, https://doi.org/10.1175/BAMS-D-19-0329.1, 2021.
Mott, R., Winstral, A., Cluzet, B., Helbig, N., Magnusson, J., Mazzotti, G., Quéno, L., Schirmer, M., Webster, C., and Jonas, T.: Operational snow-hydrological modeling for Switzerland, Front. Earth Sci., 11, 1228158, https://doi.org/10.3389/feart.2023.1228158, 2023.
Nash, J. E.: A unit hydrograph study, with particular reference to British catchments, Proc. Inst. Civ. Eng., 17, 249–282, 1960.
Ohmura, A.: Physical basis for the temperature–based melt–index method, J. Appl. Meteor., 40, 753–761, 2001.
Pellicciotti, F., Brock, B., Strasser, U., Burlando, P., Funk, M., and Corripio, J.: An enhanced temperature-index glacier melt model including shortwave radiation balance: development and testing for Haut Glacier D'Arolla, Switzerland, J. Glaciol., 51, 573–587, https://doi.org/10.3189/172756505781829124, 2005.
Pfeiffer, J., Zieher, T., Schmieder, J., Rutzinger, M., and Strasser, U.: Spatio-temporal assessment of the hydrological drivers of an active deep-seated gravitational slope deformation – the Vögelsberg landslide in Tyrol (Austria), Earth Surf. Proc. Landf., 46, 1865–1881, https://doi.org/10.1002/esp.5129, 2021.
Podsiadło, I., Paris, C., Callegari, M., Marin, C., Günther, D., Strasser, U., Notarnicola, C., and Bruzzone, L.: Integrating models and remote sensing data for distributed glacier mass balance estimation, J. Sel. Top. Appl. Earth Obs., 13, 6177–6194, https://doi.org/10.1109/JSTARS.2020.3028653, 2020.
Quéno, L., Mott, R., Morin, P., Cluzet, B., Mazzotti, G., and Jonas, T.: Snow redistribution in an intermediate-complexity snow hydrology modelling framework, The Cryosphere, 18, 3533–3557, https://doi.org/10.5194/tc-18-3533-2024, 2024.
Rasmussen, R., Baker, B., Kochendorfer, J., Meyers, T., Landolt, S., Fischer, A. P., Black, J., Thériault, J. M., Kucera, P., Gochis, D., Smith, C., Nitu, R., Hall, M., Ikeda, K., and Gutman, E.: How well are we measuring snow? The NOAA/FAA/NCAR Winter Precipitation Test Bed, B. Am. Meteorol. Soc., 93, 811–829, https://doi.org/10.1175/BAMS-D-11-00052.1, 2012.
Rohrer, M. B.: Die Schneedecke im schweizerischen Alpenraum und ihre Modellierung, Zürcher Geographische Schriften, 49, 178, 1992.
Rutter, N., Essery, R. L. E., Pomeroy, J., Altimir, N., Andreadis, K., Baker, I., Barr, A., Bartlett, P., Elder, K., Ellis, C., Feng, X., Gelfan, A., Goodbody, G., Gusev, Y., Gustafsson, D., Hellström, R., Hirota, T., Jonas, T., Koren, V., Li, W.-P., Luce, C., Martin, E., Nasonova, O., Pumpanen, J., Pyles, D., Samuelsson, P., Sandells, M., Schädler, G., Shmakin, A., Smirnova, T., Stähli, M., Stöckli, R., Strasser, U., Su, H., Suzuki, K., Takata, K., Tanaka, K., Thompson, E., Vesala, T., Viterbo, P., Wiltshire, A., Xue, Y., and Yamazaki, T.: Evaluation of forest snow processes models (SnowMIP2), J. Geophys. Res., 114, D06111, https://doi.org/10.1029/2008JD011063, 2009.
Sauter, T., Arndt, A., and Schneider, C.: COSIPY v1.3 – an open-source coupled snowpack and ice surface energy and mass balance model, Geosci. Model Dev., 13, 5645–5662, https://doi.org/10.5194/gmd-13-5645-2020, 2020.
Seibert, J. and Bergström, S.: A retrospective on hydrological catchment modelling based on half a century with the HBV model, Hydrol. Earth Syst. Sci., 26, 1371–1388, https://doi.org/10.5194/hess-26-1371-2022, 2022.
Seidl, R., Rammer, W., Scheller, R. M., and Spies, T. A.: An individual-based process model to simulate landscape-scale forest ecosystem dynamics, Ecol. Mod., 231, 87–100, https://doi.org/10.1016/j.ecolmodel.2012.02.015, 2012.
Sicart, J. E., Ramseyer, V., Picard, G., Arnaud, L., Coulaud, C., Freche, G., Soubeyrand, D., Lejeune, Y., Dumont, M., Gouttevin, I., Le Gac, E., Berger, F., Monnet, J.-M., Borgniet, L., Mermin, É., Rutter, N., Webster, C., and Essery, R.: Snow accumulation and ablation measurements in a midlatitude mountain coniferous forest (Col de Porte, France, 1325 m altitude): the Snow Under Forest (SnoUF) field campaign data set, Earth Syst. Sci. Data, 15, 5121–5133, https://doi.org/10.5194/essd-15-5121-2023, 2023.
Strasser, U.: Die Modellierung der Gebirgsschneedecke im Nationalpark Berchtesgaden. Modelling of the mountain snow cover in the Berchtesgaden National Park. Berchtesgaden National Park research report, Nr. 55, Berchtesgaden, ISBN 978-3-922325-62-8, 2008.
Strasser, U. and Marke, T.: ESCIMO.spread – a spreadsheet-based point snow surface energy balance model to calculate hourly snow water equivalent and melt rates for historical and changing climate conditions, Geosci. Model Dev., 3, 643–652, https://doi.org/10.5194/gmd-3-643-2010, 2010.
Strasser, U. and Mauser, W.: Modelling the Spatial and Temporal Variations of the Water Balance for the Weser Catchment 1965–1994, J. Hydrol., 254/1-4, 199–214, https://doi.org/10.1016/S0022-1694(01)00492-9, 2001.
Strasser, U., Etchevers, P., and Lejeune, Y.: Intercomparision of two Snow Models with Different Complexity Using Data from an Alpine Site, Nordic Hydrol., 33, 15–26, https://doi.org/10.2166/nh.2002.0002, 2002.
Strasser, U., Corripio, J., Brock, B., Pellicciotti, F., Burlando, P., and Funk, M.: Spatial and Temporal Variability of Meteorological Variables at Haut Glacier d'Arolla (Switzerland) During the Ablation Season 2001: Measurements and Simulations, J. Geophys. Res., 109, D03103, https://doi.org/10.1029/2003JD003973, 2004.
Strasser, U., Bernhardt, M., Weber, M., Liston, G. E., and Mauser, W.: Is snow sublimation important in the alpine water balance?, The Cryosphere, 2, 53–66, https://doi.org/10.5194/tc-2-53-2008, 2008.
Strasser, U., Warscher, M., and Liston, G. E.: Modelling snow-canopy processes on an idealized mountain, J. Hydrometeor., 12, 663–677, https://doi.org/10.1175/2011JHM1344.1, 2011.
Strasser, U., Marke, T., Braun, L. N., Escher-Vetter, H., Juen, I., Kuhn, M., Maussion, F., Mayer, C., Nicholson, L., Niedertscheider, K., Sailer, R., Stötter, J., Weber, M., and Kaser, G.: The Rofental: a high Alpine research basin (1890 m–3770 m a.s.l.) in the ötztal Alps (Austria) with over 150 years of hydro-meteorological and glaciological observations, PANGAEA [data set], https://doi.org/10.1594/PANGAEA.876120, 2017.
Strasser, U., Marke, T., Braun, L., Escher-Vetter, H., Juen, I., Kuhn, M., Maussion, F., Mayer, C., Nicholson, L., Niedertscheider, K., Sailer, R., Stötter, J., Weber, M., and Kaser, G.: The Rofental: a high Alpine research basin (1890–3770 m a.s.l.) in the ötztal Alps (Austria) with over 150 years of hydrometeorological and glaciological observations, Earth Syst. Sci. Data, 10, 151–171, https://doi.org/10.5194/essd-10-151-2018, 2018.
Vionnet, V., Brun, E., Morin, S., Boone, A., Faroux, S., Le Moigne, P., Martin, E., and Willemet, J.-M.: The detailed snowpack scheme Crocus and its implementation in SURFEX v7.2, Geosci. Model Dev., 5, 773–791, https://doi.org/10.5194/gmd-5-773-2012, 2012.
Vionnet, V., Marsh, C. B., Menounos, B., Gascoin, S., Wayand, N. E., Shea, J., Mukherjee, K., and Pomeroy, J. W.: Multi-scale snowdrift-permitting modelling of mountain snowpack, The Cryosphere, 15, 743–769, https://doi.org/10.5194/tc-15-743-2021, 2021.
Vionnet, V., Verville, M., Fortin, V., Brugman, M., Abrahamowicz, M., Lemay, F., Thériault, M., Lafaysse, T., and Milbrandt, J.-A.: Snow level from post-processing of atmospheric model improves snowfall estimate and snowpack prediction in mountains, Water Resour. Res., 58, e2021WR031778, https://doi.org/10.1029/2021WR031778, 2022.
Viviroli, D., Dürr, H. H., Messerli, B., Meybeck, M., and Weingartner, R.: Mountains of the world, water towers for humanity: Typology, mapping, and global significance, Water Resour. Res., 43, W07447, https://doi.org/10.1029/2006wr005653, 2007.
Viviroli, D., Kummu, M., Meybeck, M., Kallio, M., and Wada, Y.: Increasing dependence of lowland populations on mountain water resources. Nature Sustainability, Nature Publishing Group, 3, 917–928, https://doi.org/10.1038/s41893-020-0559-9, 2020.
Warscher, M., Strasser, U., Kraller, G., Marke, T., Franz, H., and Kunstmann, H.: Performance of complex snow cover descriptions in a distributed hydrological model system: A case study for the high Alpine terrain of the Berchtesgaden Alps, Water Resour. Res., 49, 2619–2637, https://doi.org/10.1002/wrcr.20219, 2013.
Warscher, M., Marke, T., Rottler, E., and Strasser, U.: Operational and experimental snow observation systems in the upper Rofental: data from 2017 to 2023, Earth Syst. Sci. Data, 16, 3579–3599, https://doi.org/10.5194/essd-16-3579-2024, 2024.
Weber, M.: A parameterization for the turbulent fluxes over melting surfaces derived from eddy correlation measurements, in: Proceedings of the Alpine*Snow*Workshop, Munich, 5–6 October 2006, Germany, edited by: Strasser, U. and Vogel M., Berchtesgaden National Park research report 53, Berchtesgaden, ISBN13 978-3-922325-60-4, 2008.
Yokoyama, R., Shirasawa, M., and Pike, R. J.: Visualizing topography by openness: a new application of image processing to digital elevation models, Photogr. Eng. Rem. Sens., 68, 257–266, 2002.
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....
