Articles | Volume 16, issue 8
https://doi.org/10.5194/essd-16-3579-2024
© 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/essd-16-3579-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
12 Aug 2024
Data description paper |
| 12 Aug 2024
| 12 Aug 2024
Operational and experimental snow observation systems in the upper Rofental: data from 2017 to 2023
Michael Warscher
CORRESPONDING AUTHOR
Department of Geography, University of Innsbruck, 6020 Innsbruck, Austria
Thomas Marke
Department of Geography, University of Innsbruck, 6020 Innsbruck, Austria
Erwin Rottler
Department of Geography, University of Innsbruck, 6020 Innsbruck, Austria
Ulrich Strasser
Department of Geography, University of Innsbruck, 6020 Innsbruck, Austria
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Geosci. Model Dev., 17, 6775–6797, https://doi.org/10.5194/gmd-17-6775-2024, https://doi.org/10.5194/gmd-17-6775-2024, 2024
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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).
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Revised manuscript not accepted
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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.
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The mass balance of very small glaciers is often governed by anomalous snow accumulation, winter precipitation being multiplied by snow redistribution processes, or by suppressed snow ablation driven by micrometeorological effects lowering net radiation and turbulent heat exchange. In this study we discuss the relative contribution of snow accumulation (avalanches) versus micrometeorology (katabatic flow) on the mass balance of the lowest perennial ice field of the Alps, the Ice Chapel.
Jan Schmieder, Florian Hanzer, Thomas Marke, Jakob Garvelmann, Michael Warscher, Harald Kunstmann, and Ulrich Strasser
Hydrol. Earth Syst. Sci., 20, 5015–5033, https://doi.org/10.5194/hess-20-5015-2016, https://doi.org/10.5194/hess-20-5015-2016, 2016
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We present novel research on the spatiotemporal variability of snowmelt isotopic content in a high-elevation catchment with complex terrain
to improve the isotope-based hydrograph separation method. A modelling approach was used to weight the plot-scale snowmelt isotopic content
with melt rates for the north- and south-facing slope. The investigations showed that it is important to sample at least north- and south-facing slopes,
because of distinct isotopic differences between both slopes.
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This article describes the extension of the ESCIMO.spread spreadsheet-based point energy balance snow model by (i) an advanced approach for precipitation phase detection, (ii) a concept for cold and liquid water storage consideration and (iii) a canopy sub-model that allows one to quantify the effect of a forest canopy on the meteorological conditions inside the forest as well as the simulation of snow accumulation and ablation inside a forest stand.
Ulrich Strasser, Michael Warscher, Erwin Rottler, and Florian Hanzer
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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).
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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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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.
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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.
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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
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Florian Hanzer, Kristian Förster, Johanna Nemec, and Ulrich Strasser
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Kristian Förster, Florian Hanzer, Elena Stoll, Adam A. Scaife, Craig MacLachlan, Johannes Schöber, Matthias Huttenlau, Stefan Achleitner, and Ulrich Strasser
Hydrol. Earth Syst. Sci., 22, 1157–1173, https://doi.org/10.5194/hess-22-1157-2018, https://doi.org/10.5194/hess-22-1157-2018, 2018
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Ulrich Strasser, Thomas Marke, Ludwig Braun, Heidi Escher-Vetter, Irmgard Juen, Michael Kuhn, Fabien Maussion, Christoph Mayer, Lindsey Nicholson, Klaus Niedertscheider, Rudolf Sailer, Johann Stötter, Markus Weber, and Georg Kaser
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A hydrometeorological and glaciological data set is presented with recordings from several research sites in the Rofental (1891–3772 m a.s.l., Ötztal Alps, Austria). The data sets are spanning 150 years and represent a unique pool of high mountain observations, enabling combined research of atmospheric, cryospheric and hydrological processes in complex terrain, and the development of state-of-the-art hydroclimatological and glacier mass balance models.
Jan Schmieder, Florian Hanzer, Thomas Marke, Jakob Garvelmann, Michael Warscher, Harald Kunstmann, and Ulrich Strasser
Hydrol. Earth Syst. Sci., 20, 5015–5033, https://doi.org/10.5194/hess-20-5015-2016, https://doi.org/10.5194/hess-20-5015-2016, 2016
Short summary
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We present novel research on the spatiotemporal variability of snowmelt isotopic content in a high-elevation catchment with complex terrain
to improve the isotope-based hydrograph separation method. A modelling approach was used to weight the plot-scale snowmelt isotopic content
with melt rates for the north- and south-facing slope. The investigations showed that it is important to sample at least north- and south-facing slopes,
because of distinct isotopic differences between both slopes.
Kristian Förster, Felix Oesterle, Florian Hanzer, Johannes Schöber, Matthias Huttenlau, and Ulrich Strasser
Proc. IAHS, 374, 143–150, https://doi.org/10.5194/piahs-374-143-2016, https://doi.org/10.5194/piahs-374-143-2016, 2016
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We present first results of a coupled seasonal prediction modelling system that runs at monthly time steps for a small catchment in the Austrian Alps. Meteorological forecasts are obtained from the CFSv2 model which are downscaled to the Alpine Water balance And Runoff Estimation model AWARE. Initial conditions are obtained using the physically based, hydro-climatological snow model AMUNDSEN. In this way, ensemble simulations of the coupled model are compared to observations.
Florian Hanzer, Kay Helfricht, Thomas Marke, and Ulrich Strasser
The Cryosphere, 10, 1859–1881, https://doi.org/10.5194/tc-10-1859-2016, https://doi.org/10.5194/tc-10-1859-2016, 2016
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The hydroclimatological model AMUNDSEN is set up to simulate snow and ice accumulation, ablation, and runoff for a study region in the Ötztal Alps (Austria) in the period 1997–2013. A new validation concept is introduced and demonstrated by evaluating the model performance using several independent data sets, e.g. snow depth measurements, satellite-derived snow maps, lidar data, glacier mass balances, and runoff measurements.
Kristian Förster, Florian Hanzer, Benjamin Winter, Thomas Marke, and Ulrich Strasser
Geosci. Model Dev., 9, 2315–2333, https://doi.org/10.5194/gmd-9-2315-2016, https://doi.org/10.5194/gmd-9-2315-2016, 2016
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For many applications in geoscientific modelling hourly meteorological time series are required, which generally cover shorter periods of time compared to daily time series. We present an open-source MEteoroLOgical observation time series DISaggregation Tool (MELODIST) capable of disaggregating temperature, precipitation, humidity, wind speed, and shortwave radiation (i.e. making 24 out of 1 value). Results indicate a good reconstruction of diurnal features at five sites in different climates.
T. Marke, E. Mair, K. Förster, F. Hanzer, J. Garvelmann, S. Pohl, M. Warscher, and U. Strasser
Geosci. Model Dev., 9, 633–646, https://doi.org/10.5194/gmd-9-633-2016, https://doi.org/10.5194/gmd-9-633-2016, 2016
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This article describes the extension of the ESCIMO.spread spreadsheet-based point energy balance snow model by (i) an advanced approach for precipitation phase detection, (ii) a concept for cold and liquid water storage consideration and (iii) a canopy sub-model that allows one to quantify the effect of a forest canopy on the meteorological conditions inside the forest as well as the simulation of snow accumulation and ablation inside a forest stand.
K. Förster, G. Meon, T. Marke, and U. Strasser
Hydrol. Earth Syst. Sci., 18, 4703–4720, https://doi.org/10.5194/hess-18-4703-2014, https://doi.org/10.5194/hess-18-4703-2014, 2014
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Four snow models of different complexity (temperature-index vs. energy balance models) are compared using observed and dynamically downscaled atmospheric analysis data as input. Biases in simulated precipitation lead to lower model performance. However, simulated meteorological conditions are proven to be a valuable meteorological data source as they provide model input in regions with limited availability of observations and allow the application of energy balance approaches.
Related subject area
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Lars Kaleschke, Xiangshan Tian-Kunze, Stefan Hendricks, and Robert Ricker
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Weixin Zhu, Siqi Liu, Shiming Xu, and Lu Zhou
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In the polar ocean, wind waves generate and propagate into the sea ice cover, forming marginal ice zones (MIZs). Using ESA's CryoSat-2, we construct a 12-year dataset of the MIZ in the Atlantic Arctic, a key region for climate change and human activities. The dataset is validated with high-resolution observations by ICESat2 and Sentinel-1. MIZs over 300 km wide are found under storms in the Barents Sea. The new dataset serves as the basis for research areas, including wave–ice interactions.
Fangbo Pan, Lingmei Jiang, Gongxue Wang, Jinmei Pan, Jinyu Huang, Cheng Zhang, Huizhen Cui, Jianwei Yang, Zhaojun Zheng, Shengli Wu, and Jiancheng Shi
Earth Syst. Sci. Data, 16, 2501–2523, https://doi.org/10.5194/essd-16-2501-2024, https://doi.org/10.5194/essd-16-2501-2024, 2024
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Wiebke Margitta Kolbe, Rasmus T. Tonboe, and Julienne Stroeve
Earth Syst. Sci. Data, 16, 1247–1264, https://doi.org/10.5194/essd-16-1247-2024, https://doi.org/10.5194/essd-16-1247-2024, 2024
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Current satellite-based sea-ice climate data records (CDRs) usually begin in October 1978 with the first multichannel microwave radiometer data. Here, we present a sea ice dataset based on the single-channel Electrical Scanning Microwave Radiometer (ESMR) that operated from 1972-1977 onboard NASA’s Nimbus 5 satellite. The data were processed using modern methods and include uncertainty estimations in order to provide an important, easy-to-use reference period of good quality for current CDRs.
Thomas Lavergne and Emily Down
Earth Syst. Sci. Data, 15, 5807–5834, https://doi.org/10.5194/essd-15-5807-2023, https://doi.org/10.5194/essd-15-5807-2023, 2023
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Sea ice in the Arctic and Antarctic can move several tens of kilometers per day due to wind and ocean currents. By analysing thousands of satellite images, we measured how sea ice has been moving every single day from 1991 through to 2020. We compare our data to how buoys attached to the ice moved and find good agreement. Other scientists will now use our data to better understand if climate change has modified the way sea ice moves and in what way.
Jean Emmanuel Sicart, Victor Ramseyer, Ghislain Picard, Laurent Arnaud, Catherine Coulaud, Guilhem Freche, Damien Soubeyrand, Yves Lejeune, Marie Dumont, Isabelle Gouttevin, Erwan Le Gac, Frédéric Berger, Jean-Matthieu Monnet, Laurent Borgniet, Éric Mermin, Nick Rutter, Clare Webster, and Richard Essery
Earth Syst. Sci. Data, 15, 5121–5133, https://doi.org/10.5194/essd-15-5121-2023, https://doi.org/10.5194/essd-15-5121-2023, 2023
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Forests strongly modify the accumulation, metamorphism and melting of snow in midlatitude and high-latitude regions. Two field campaigns during the winters 2016–17 and 2017–18 were conducted in a coniferous forest in the French Alps to study interactions between snow and vegetation. This paper presents the field site, instrumentation and collection methods. The observations include forest characteristics, meteorology, snow cover and snow interception by the canopy during precipitation events.
Ying Chen, Ruibo Lei, Xi Zhao, Shengli Wu, Yue Liu, Pei Fan, Qing Ji, Peng Zhang, and Xiaoping Pang
Earth Syst. Sci. Data, 15, 3223–3242, https://doi.org/10.5194/essd-15-3223-2023, https://doi.org/10.5194/essd-15-3223-2023, 2023
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The sea ice concentration product derived from the Microwave Radiation Image sensors on board the FengYun-3 satellites can reasonably and independently identify the seasonal and long-term changes of sea ice, as well as extreme cases of annual maximum and minimum sea ice extent in polar regions. It is comparable with other sea ice concentration products and applied to the studies of climate and marine environment.
Adrià Fontrodona-Bach, Bettina Schaefli, Ross Woods, Adriaan J. Teuling, and Joshua R. Larsen
Earth Syst. Sci. Data, 15, 2577–2599, https://doi.org/10.5194/essd-15-2577-2023, https://doi.org/10.5194/essd-15-2577-2023, 2023
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We provide a dataset of snow water equivalent, the depth of liquid water that results from melting a given depth of snow. The dataset contains 11 071 sites over the Northern Hemisphere, spans the period 1950–2022, and is based on daily observations of snow depth on the ground and a model. The dataset fills a lack of accessible historical ground snow data, and it can be used for a variety of applications such as the impact of climate change on global and regional snow and water resources.
Francesco Avanzi, Simone Gabellani, Fabio Delogu, Francesco Silvestro, Flavio Pignone, Giulia Bruno, Luca Pulvirenti, Giuseppe Squicciarino, Elisabetta Fiori, Lauro Rossi, Silvia Puca, Alexander Toniazzo, Pietro Giordano, Marco Falzacappa, Sara Ratto, Hervè Stevenin, Antonio Cardillo, Matteo Fioletti, Orietta Cazzuli, Edoardo Cremonese, Umberto Morra di Cella, and Luca Ferraris
Earth Syst. Sci. Data, 15, 639–660, https://doi.org/10.5194/essd-15-639-2023, https://doi.org/10.5194/essd-15-639-2023, 2023
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Snow cover has profound implications for worldwide water supply and security, but knowledge of its amount and distribution across the landscape is still elusive. We present IT-SNOW, a reanalysis comprising daily maps of snow amount and distribution across Italy for 11 snow seasons from September 2010 to August 2021. The reanalysis was validated using satellite images and snow measurements and will provide highly needed data to manage snow water resources in a warming climate.
Yan Huang, Jiahui Xu, Jingyi Xu, Yelei Zhao, Bailang Yu, Hongxing Liu, Shujie Wang, Wanjia Xu, Jianping Wu, and Zhaojun Zheng
Earth Syst. Sci. Data, 14, 4445–4462, https://doi.org/10.5194/essd-14-4445-2022, https://doi.org/10.5194/essd-14-4445-2022, 2022
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Reliable snow cover information is important for understating climate change and hydrological cycling. We generate long-term daily gap-free snow products over the Tibetan Plateau (TP) at 500 m resolution from 2002 to 2021 based on the hidden Markov random field model. The accuracy is 91.36 %, and is especially improved during snow transitional period and over complex terrains. This dataset has great potential to study climate change and to facilitate water resource management in the TP.
Cited articles
Angelstam, P., Manton, M., Elbakidze, M., Sijtsma, F., Adamescu, M. C., Avni, N., Beja, P., Bezak, P., Zyablikova, I., Cruz, F., Bretagnolle, V., Díaz-Delgado, R., Ens, B., Fedoriak, M., Flaim, G., Gingrich, S., Lavi-Neeman, M., Medinets, S., Melecis, V., Muñoz-Rojas, J., Schäckermann, J., Stocker-Kiss, A., Setälä, H., Stryamets, N., Taka, M., Tallec, G., Tappeiner, U., Törnblom, J., and Yamelynets, T.: LTSER platforms as a place-based transdisciplinary research infrastructure: learning landscape approach through evaluation, Landscape Ecol., 34, 1461–1484, https://doi.org/10.1007/s10980-018-0737-6, 2019. a
Barnett, T. P., Adam, J. C., and Lettenmaier, D. P.: Potential impacts of a warming climate on water availability in snow-dominated regions, Nat. Rev., 438, 303–309, https://doi.org/10.1038/nature04141, 2005. a
Beniston, M., Farinotti, D., Stoffel, M., Andreassen, L. M., Coppola, E., Eckert, N., Fantini, A., Giacona, F., Hauck, C., Huss, M., Huwald, H., Lehning, M., López-Moreno, J.-I., Magnusson, J., Marty, C., Morán-Tejéda, E., Morin, S., Naaim, M., Provenzale, A., Rabatel, A., Six, D., Stötter, J., Strasser, U., Terzago, S., and Vincent, C.: The European mountain cryosphere: a review of its current state, trends, and future challenges, The Cryosphere, 12, 759–794, https://doi.org/10.5194/tc-12-759-2018, 2018. a, b
Blöschl, G., Bierkens, M. F. P., Chambel, A., Cudennec, C., Destouni, G., Fiori, A., Kirchner, J. W., McDonnell, J. J., Savenije, H. H. G., Sivapalan, M., Stumpp, C., Toth, E., Volpi, E., Carr, G., Lupton, C., Salinas, J., Széles, B., Viglione, A., Aksoy, H., Allen, S. T., Amin, A.,,réassian, V., Arheimer, B., Aryal, S. K., Baker, V., Bardsley, E., Barendrecht, M. H., Bartosova, A., Batelaan, O., Berghuijs, W. R., Beven, K., Blume, T., Bogaard, T., Borges de Amorim, P., Böttcher, M. E., Boulet, G., Breinl, K., Brilly, M., Brocca, L., Buytaert, W., Castellarin, A., Castelletti, A., Chen, X., Chen, Y., Chen, Y., Chifflard, P., Claps, P., Clark, M. P., Collins, A. L., Croke, B., Dathe, A., David, P. C., de Barros, F. P. J., de Rooij, G., Di Baldassarre, G., Driscoll, J. M., Duethmann, D., Dwivedi, R., Eris, E., Farmer, W. H., Feiccabrino, J., Ferguson, G., Ferrari, E., Ferraris, S., Fersch, B., Finger, D., Foglia, L., Fowler, K., Gartsman, B., Gascoin, S., Gaume, E., Gelfan, A., Geris, J., Gharari, S., Gleeson, T., Glendell, M., Gonzalez Bevacqua, A., González-Dugo, M. P., Grimaldi, S., Gupta, A. B., Guse, B., Han, D., Hannah, D., Harpold, A., Haun, S., Heal, K., Helfricht, K., Herrnegger, M., Hipsey, M., Hlaváčiková, H., Hohmann, C., Holko, L., Hopkinson, C., Hrachowitz, M., Illangasekare, T. H., Inam, A., Innocente, C., Istanbulluoglu, E., Jarihani, B., Kalantari, Z., Kalvans, A., Khanal, S., Khatami, S., Kiesel, J., Kirkby, M., Knoben, W., Kochanek, K., Kohnová, S., Kolechkina, A., Krause, S., Kreamer, D., Kreibich, H., Kunstmann, H., Lange, H., Liberato, M. L. R., Lindquist, E., Link, T., Liu, J., Loucks, D. P., Luce, C., Mahé, G., Makarieva, O., Malard, J., Mashtayeva, S., Maskey, S., Mas-Pla, J., Mavrova-Guirguinova, M., Mazzoleni, M., Mernild, S., Misstear, B. D., Montanari, A., Müller-Thomy, H., Nabizadeh, A., Nardi, F., Neale, C., Nesterova, N., Nurtaev, B., Odongo, V. O., Panda, S., Pande, S., Pang, Z., Papacharalampous, G., Perrin, C., Pfister, L., Pimentel, R., Polo, M. J., Post, D., Prieto Sierra, C., Ramos, M.-H., Renner, M., Reynolds, J. E., Ridolfi, E., Rigon, R., Riva, M., Robertson, D. E., Rosso, R., Roy, T., Sá, J. H. M., Salvadori, G., Sandells, M., Schaefli, B., Schumann, A., Scolobig, A., Seibert, J., Servat, E., Shafiei, M., Sharma, A., Sidibe, M., Sidle, R. C., Skaugen, T., Smith, H., Spiessl, S. M., Stein, L., Steinsland, I., Strasser, U., Su, B., Szolgay, J., Tarboton, D., Tauro, F., Thirel, G., Tian, F., Tong, R., Tussupova, K., Tyralis, H., Uijlenhoet, R., van Beek, R., van der Ent, R. J., van der Ploeg, M., Van Loon, A. F., van Meerveld, I., van Nooijen, R., van Oel, P. R., Vidal, J.-P., von Freyberg, J., Vorogushyn, S., Wachniew, P., Wade, A. J., Ward, P., Westerberg, I. K., White, C., Wood, E. F., Woods, R., Xu, Z., Yilmaz, K. K., and Zhang, Y.: Twenty-three unsolved problems in hydrology (UPH) – a community perspective, Hydrol. Sci. J., 64, 1141–1158, https://doi.org/10.1080/02626667.2019.1620507, 2019. a
Chritin, V., Bolognesi, R., and Gubler, H.: Flowcapt: a new acoustic sensor to measure snowdrift and wind velocity for avalanche forecasting, Cold Reg. Sci. Technol., 30, 125–133, https://doi.org/10.1016/S0165-232X(99)00012-9, 1999. a
Cierco, F.-X., Naaim-Bouvet, F., and Bellot, H.: Acoustic sensors for snowdrift measurements: How should they be used for research purposes?, Cold Reg. Sci. Technol., 49, 74–87, https://doi.org/10.1016/j.coldregions.2007.01.002, 2007. a
De Gregorio, L., Callegari, M., Marin, C., Zebisch, M., Bruzzone, L., Demir, B., Strasser, U., Marke, M., Günther, D., Nadalet, R., and Notarnicola, C.: A Novel Data Fusion Technique for Snow Cover Retrieval, IEEE J-STARS, 12, 2862–2877, https://doi.org/10.1109/JSTARS.2019.2920676, 2019. a
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, 2019. a
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. a, b
EEA Geospatial Data Catalogue: CORINE Land Cover 2018 (vector), Europe, 6-yearly – version 2020_20u1, May 2020, EEA Geospatial Data Catalogue [data set], https://doi.org/10.2909/71c95a07-e296-44fc-b22b-415f42acfdf0, 2019. a
Egli, L., Jonas, T., and Meister, R.: Comparison of different automatic methods for estimating snow water equivalent, Cold Reg. Sci. Technol., 57, 107–115, https://doi.org/10.1016/j.coldregions.2009.02.008, 2009. a
Goger, B., Stiperski, I., Nicholson, L., and Sauter, T.: Large-eddy simulations of the atmospheric boundary layer over an Alpine glacier: Impact of synoptic flow direction and governing processes, Q. J. Roy. Meteor. Soc., 148, 1319–1343, https://doi.org/10.1002/qj.4263, 2022. a
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. a
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. a
He, S. and Ohara, N.: A new formula for estimating the threshold wind speed for snow movement, J. Adv. Model. Earth Syst., 9, 2514–2525, https://doi.org/10.1002/2017MS000982, 2017. a
IPCC: IPCC Special Report on the Ocean and Cryosphere in a Changing Climate, edited by: Pörtner, H.-O., Roberts, D. C., Masson-Delmotte, V., Zhai, P., Tignor, M., Poloczanska, E., Mintenbeck, K., Alegría, A., Nicolai, M., Okem, A., Petzold, J., Rama, B., and Weyer, N. M., Cambridge University Press, Cambridge, UK and New York, NY, USA, 755 pp., https://doi.org/10.1017/9781009157964, 2019. a
Jaedicke, C.: Acoustic snowdrift measurements: experiences from the FlowCapt instrument, Cold Reg. Sci. Technol., 32, 71–81, https://doi.org/10.1016/S0165-232X(01)00017-9, 2001. a
Johnson, J. B. and Schaefer, G. L.: The influence of thermal, hydrologic, and snow deformation mechanisms on snow water equivalent pressure sensor accuracy, Hydrol. Process., 16, 3529–3542, https://doi.org/10.1002/hyp.1236, 2002. a
Johnson, J. B. and Marks, D.: The detection and correction of snow water equivalent pressure sensor errors, Hydrol. Process., 18, 3513–3525, https://doi.org/10.1002/hyp.5795, 2004. a, b
Klug, C., Bollmann, E., Galos, S. P., Nicholson, L., Prinz, R., Rieg, L., Sailer, R., Stötter, J., and Kaser, G.: Geodetic reanalysis of annual glaciological mass balances (2001–2011) of Hintereisferner, Austria, The Cryosphere, 12, 833–849, https://doi.org/10.5194/tc-12-833-2018, 2018. a
Kuhn, M., Abermann, J., Olefs, M., Fischer, A., and Lambrecht, A.: Gletscher im Klimawandel: Aktuelle Monitoring-Programme und Forschungen zur Auswirkung auf den Gebietsabfluss im Ötztal, Mitt. hydr. Dienst Österr., 86, 31–47, 2006. a
Lehning, M., Naaim, F., Naaim, M., Brabec, B., Doorschot, J., Durand, Y., Guyomarc’h, G., Michaux, J.-L., and Zimmerli, M.: Snow drift: acoustic sensors for avalanche warning and research, Nat. Hazards Earth Syst. Sci., 2, 121–128, https://doi.org/10.5194/nhess-2-121-2002, 2002. a, b
Lejeune, Y., Dumont, M., Panel, J.-M., Lafaysse, M., Lapalus, P., Le Gac, E., Lesaffre, B., and Morin, S.: 57 years (1960–2017) of snow and meteorological observations from a mid-altitude mountain site (Col de Porte, France, 1325 m of altitude), Earth Syst. Sci. Data, 11, 71–88, https://doi.org/10.5194/essd-11-71-2019, 2019. a
Lundquist, J. D., Vano, J., Gutmann, E., Hogan, D., Schwat, E., Haugeneder, M., Mateo, M., Oncley, S., Roden, C., Osenga, E., and Carver, L. (2024): Sublimation of Snow, B. Am. Meteorol. Soc., 105, E975–E990, https://doi.org/10.1175/BAMS-D-23-0191.1, 2024. a, b
Marty, C. and Meister, R.: Long-term snow and weather observations at Weissfluhjoch and its relation to other high-altitude observatories in the Alps, Theor. Appl. Climatol., 110, 573–583, https://doi.org/10.1007/s00704-012-0584-3, 2012. a
Matiu, M., Crespi, A., Bertoldi, G., Carmagnola, C. M., Marty, C., Morin, S., Schöner, W., Cat Berro, D., Chiogna, G., De Gregorio, L., Kotlarski, S., Majone, B., Resch, G., Terzago, S., Valt, M., Beozzo, W., Cianfarra, P., Gouttevin, I., Marcolini, G., Notarnicola, C., Petitta, M., Scherrer, S. C., Strasser, U., Winkler, M., Zebisch, M., Cicogna, A., Cremonini, R., Debernardi, A., Faletto, M., Gaddo, M., Giovannini, L., Mercalli, L., Soubeyroux, J.-M., Sušnik, A., Trenti, A., Urbani, S., and Weilguni, V.: Observed snow depth trends in the European Alps: 1971 to 2019, The Cryosphere, 15, 1343–1382, https://doi.org/10.5194/tc-15-1343-2021, 2021. a
Ménard, C. B., Essery, R., Barr, A., Bartlett, P., Derry, J., Dumont, M., Fierz, C., Kim, H., Kontu, A., Lejeune, Y., Marks, D., Niwano, M., Raleigh, M., Wang, L., and Wever, N.: Meteorological and evaluation datasets for snow modelling at 10 reference sites: description of in situ and bias-corrected reanalysis data, Earth Syst. Sci. Data, 11, 865–880, https://doi.org/10.5194/essd-11-865-2019, 2019. a
Morin, S., Lejeune, Y., Lesaffre, B., Panel, J.-M., Poncet, D., David, P., and Sudul, M.: An 18-yr long (1993–2011) snow and meteorological dataset from a mid-altitude mountain site (Col de Porte, France, 1325 m alt.) for driving and evaluating snowpack models, Earth Syst. Sci. Data, 4, 13–21, https://doi.org/10.5194/essd-4-13-2012, 2012. a
Mott, R., Stiperski, I., and Nicholson, L.: Spatio-temporal flow variations driving heat exchange processes at a mountain glacier, The Cryosphere, 14, 4699–4718, https://doi.org/10.5194/tc-14-4699-2020, 2020. a
Musselman, K. N., Clark, M. P., Liu, C., Ikeda, K., and Rasmussen, R.: Slower snowmelt in a warmer world, Nat. Clim. Change, 7, 214–219, https://doi.org/10.1038/nclimate3225, 2017. a
Naaim-Bouvet, F., Bellot, H., Nishimura, K., Genthon, C., Palerme, C., Guyomarc’h, G., and Vionnet, V.: Detection of snowfall occurrence during blowing snow events using photoelectric sensors, Cold Reg. Sci. Technol., 106, 11–21, https://doi.org/10.1016/j.coldregions.2014.05.005, 2014. a
Ohl, C., Johst, K., Meyerhoff, J., Beckenkamp, M. Grüsgen, V., and Drechsler, M.: Long-term socio-ecological research (LTSER) for biodiversity protection – a complex systems approach for the study of dynamic human-nature interactions, Ecol. Complex., 7, 170–178, https://doi.org/10.1016/j.ecocom.2009.10.002, 2010. a
Ohmura, A.: Enhanced temperature variability in high-altitude climate change, Theor. Appl. Climatol., 110, 499–508, https://doi.org/10.1007/s00704-012-0687-x, 2012. a
Pepin, N., Bradley, R. S., Diaz, H. F., Baraer, M., Caceres, E. B., Forsythe, N., Fowler, H., Greenwood, G., Hashmi, M. Z., Liu, X. D., Miller, J. R., Ning, L. Ohmura, A., Palazzi, E., Rangwala, I., Schöner, W., Severskiy, I., Shahgedanova, M., Wang, M. B.,Williamson S. N., and Yang, D. Q.: Elevation-dependent warming in mountain regions of the world, Nat. Clim. Change, 5, 424–430, https://doi.org/10.1038/nclimate2563, 2015. a
Pepin, N. C., Arnone, E., Gobiet, A., Haslinger, K., Kotlarski, S., Notarnicola, C., Palazzi, E., Seibert, P., Serafin, S. Schöner, W., Terzago, S., Thornton, J. M., Vuille, M., and Adler, C.: Climate changes and their elevational patterns in the mountains of the world, Rev. Geophys., 60, e2020RG000730, https://doi.org/10.1029/2020RG000730, 2022. a
Pradhananga, D., Pomeroy, J. W., Aubry-Wake, C., Munro, D. S., Shea, J., Demuth, M. N., Kirat, N. H., Menounos, B., and Mukherjee, K.: Hydrometeorological, glaciological and geospatial research data from the Peyto Glacier Research Basin in the Canadian Rockies, Earth Syst. Sci. Data, 13, 2875–2894, https://doi.org/10.5194/essd-13-2875-2021, 2021. a
Rastner, P., Prinz, R., Notarnicola, C., Nicholson, L., Sailer, R., Schwaizer, G., and Paul, F.: On the Automated Mapping of Snow Cover on Glaciers and Calculation of Snow Line Altitudes from Multi-Temporal Landsat Data, Remote Sens., 11, 1410, https://doi.org/10.3390/rs11121410, 2019. a
Rieg, L., Klug, C., Nicholson, L., and Sailer, R.: Pléiades Tri-Stereo Data for Glacier Investigations – Examples from the European Alps and the Khumbu Himal, Remote Sens., 10, 1563, https://doi.org/10.3390/rs10101563, 2018. a
Sato, T., Kimura, T., Ishimaru, T., and Maruyama, T.: Field test of a new snow-particle counter (SPC) system, Ann. Glaciol., 18, 149–154, https://doi.org/10.3189/S0260305500011411, 1993. a
Schattan, P., Baroni, G., Oswald, S. E., Schöber, J., Fey, C., Kormann, C., Huttenlau, M., and Achleitner, S.: Continuous monitoring of snowpack dynamics in alpine terrain by aboveground neutron sensing, Water Resour. Res., 53, 3615–3634, https://doi.org/10.1002/2016WR020234, 2017. a
Schmidt, L. K., Francke, T., Grosse, P. M., Mayer, C., and Bronstert, A.: Reconstructing five decades of sediment export from two glacierized high-alpine catchments in Tyrol, Austria, using nonparametric regression, Hydrol. Earth Syst. Sci., 27, 1841–1863, https://doi.org/10.5194/hess-27-1841-2023, 2023. a
Schmieder, J., Garvelmann, J., Marke, T., and Strasser, U.: Spatio‐temporal tracer variability in the glacier melt end‐member – How does it affect hydrograph separation results?, Hydrol. Proc., 32, 1828–1843, https://doi.org/10.1002/hyp.11628, 2018. a
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. a
Stähli, M., Stacheder, M., Gustafsson, D., Schlaeger, S., Schneebeli, M., and Brandelik, A.: A new in situ sensor for large-scale snow-cover monitoring, Ann. Glaciol., 38, 273–278, https://doi.org/10.3189/172756404781814933, 2004. a, b
Stoll, E., Hanzer, F., Oesterle, F,; Nemec, J., Schöber, J., Huttenlau, M., and Förster, K.: What Can We Learn from Comparing Glacio-Hydrological Models?, Atmosphere, 11, 981, https://doi.org/10.3390/atmos11090981, 2020. a
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 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. a, b, c
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. a, b, c, d, e, f, g, h, i
Strasser, U., Warscher, M., Rottler, E., and Hanzer, F.: openAMUNDSEN v 0.8.3: an open source snow-hydrological model for mountain regions, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2024-193, 2024. a
Trenberth, K. E.: Changes in precipitation with climate change, Clim. Res., 47, 123–138, 2011. a
Trouvilliez, A., Naaim-Bouvet, F., Bellot, H., Genthon, C., and Gallée, H.: Evaluation of the FlowCapt Acoustic Sensor for the Aeolian Transport of Snow, J. Atmos. Ocean. Tech., 32, 1630–1641, https://doi.org/10.1175/JTECH-D-14-00104.1, 2015. a, b, c
Voordendag, A., Goger, B., Klug, C., Prinz, R., Rutzinger, M., Sauter, T., and Kaser, G.: Uncertainty assessment of a permanent long-range terrestrial laser scanning system for the quantification of snow dynamics on Hintereisferner (Austria), Front. Earth Sci., 11, 1085416, https://doi.org/10.3389/feart.2023.1085416, 2023a. a
Voordendag, A., Prinz, R., Schuster, L., and Kaser, G.: Brief communication: The Glacier Loss Day as an indicator of a record-breaking negative glacier mass balance in 2022, The Cryosphere, 17, 3661–3665, https://doi.org/10.5194/tc-17-3661-2023, 2023b. a
Voordendag, A., Goger, B., Prinz, R., Sauter, T., Mölg, T., Saigger, M., and Kaser, G.: A novel framework to investigate wind-driven snow redistribution over an Alpine glacier: combination of high-resolution terrestrial laser scans and large-eddy simulations, The Cryosphere, 18, 849–868, https://doi.org/10.5194/tc-18-849-2024, 2024. a
Wang, Q., Wang, M., and Fan, X.: Seasonal patterns of warming amplification of high-elevation stations across the globe, Int. J. Climatol., 38, 3466–3473, https://doi.org/10.1002/joc.5509, 2018. a
Wu, X., Che, T., Li, X., Wang, N., and Yang, X.: Slower Snowmelt in Spring Along with Climate Warming Across the Northern Hemisphere, Geophys. Res. Lett., 45, 12331–12339, https://doi.org/10.1029/2018GL079511, 2018. a
Zolles, T., Maussion, F., Galos, S. P., Gurgiser, W., and Nicholson, L.: Robust uncertainty assessment of the spatio-temporal transferability of glacier mass and energy balance models, The Cryosphere, 13, 469–489, https://doi.org/10.5194/tc-13-469-2019, 2019. a
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.
Continuous observations of snow and climate at high altitudes are still sparse. We present a...
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