Articles | Volume 14, issue 9
https://doi.org/10.5194/tc-14-2909-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-14-2909-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
04 Sep 2020
Research article |
| 04 Sep 2020
| 04 Sep 2020
Anthropogenic climate change versus internal climate variability: impacts on snow cover in the Swiss Alps
Fabian Willibald
CORRESPONDING AUTHOR
Planning of Landscape and Urban Systems, Institute for Spatial and
Landscape Planning, ETH Zurich, Zurich, Switzerland
Institute of Science, Technology and Policy, ETH Zurich, Zurich,
Switzerland
Sven Kotlarski
Federal Office of Meteorology and Climatology MeteoSwiss,
Zurich-Airport, Switzerland
Adrienne Grêt-Regamey
Planning of Landscape and Urban Systems, Institute for Spatial and
Landscape Planning, ETH Zurich, Zurich, Switzerland
Institute of Science, Technology and Policy, ETH Zurich, Zurich,
Switzerland
Ralf Ludwig
Department of Geography, Ludwig-Maximilians-University Munich,
Munich, Germany
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Benjamin Poschlod, Laura Sailer, Alexander Sasse, Anastasia Vogelbacher, and Ralf Ludwig
EGUsphere, https://doi.org/10.5194/egusphere-2025-2483, https://doi.org/10.5194/egusphere-2025-2483, 2025
This preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).
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Europe was hit by severe droughts in recent years resulting in extreme low flow conditions in rivers. Here, we investigate future climate change effects on river droughts in Bavaria. We find increasing severity for the low peak discharge and low flow duration in a warmer climate. This is caused by hotter and drier summers, where the joint occurrence of heat and drought intensifies. Further, we show that conditions in the year before the drought gain more importance in a warmer climate.
Paul C. Astagneau, Raul R. Wood, Mathieu Vrac, Sven Kotlarski, Pradeebane Vaittinada Ayar, Bastien François, and Manuela I. Brunner
EGUsphere, https://doi.org/10.5194/egusphere-2024-3966, https://doi.org/10.5194/egusphere-2024-3966, 2025
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To study floods and droughts are likely to change in the future, we use climate projections from climate models. However, we first need to adjust the systematic biases of these projections at the catchment scale before using them in hydrological models. Our study compares statistical methods that can adjust these biases, but specifically for climate projections that enable a quantification of internal climate variability. We provide recommendations on the most appropriate methods.
Christoph Marty, Adrien Michel, Tobias Jonas, Cynthia Steijn, Regula Muelchi, and Sven Kotlarski
EGUsphere, https://doi.org/10.5194/egusphere-2025-413, https://doi.org/10.5194/egusphere-2025-413, 2025
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This work presents the first long-term (since 1962), daily, 1 km gridded dataset of snow depth and water storage for Switzerland. Its quality was assessed by comparing yearly, monthly, and weekly values to a higher-quality model and in-situ measurements. Results show good overall performance, though some limitations exist at low elevations and short timescales. Despite this, the dataset effectively captures trends, offering valuable insights for climate monitoring and elevation-based changes.
Adrien Michel, Johannes Aschauer, Tobias Jonas, Stefanie Gubler, Sven Kotlarski, and Christoph Marty
Geosci. Model Dev., 17, 8969–8988, https://doi.org/10.5194/gmd-17-8969-2024, https://doi.org/10.5194/gmd-17-8969-2024, 2024
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We present a method to correct snow cover maps (represented in terms of snow water equivalent) to match better-quality maps. The correction can then be extended backwards and forwards in time for periods when better-quality maps are not available. The method is fast and gives good results. It is then applied to obtain a climatology of the snow cover in Switzerland over the past 60 years at a resolution of 1 d and 1 km. This is the first time that such a dataset has been produced.
Carolin Boos, Sophie Reinermann, Raul Wood, Ralf Ludwig, Anne Schucknecht, David Kraus, and Ralf Kiese
EGUsphere, https://doi.org/10.5194/egusphere-2024-2864, https://doi.org/10.5194/egusphere-2024-2864, 2024
Preprint archived
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We applied a biogeochemical model on grasslands in the pre-Alpine Ammer region in Germany and analyzed the influence of soil and climate on annual yields. In drought affected years, total yields were decreased by 4 %. Overall, yields decrease with rising elevation, but less so in drier and hotter years, whereas soil organic carbon has a positive impact on yields, especially in drier years. Our findings imply, that adapted management in the region allows to mitigate yield losses from drought.
Florian Willkofer, Raul R. Wood, and Ralf Ludwig
Hydrol. Earth Syst. Sci., 28, 2969–2989, https://doi.org/10.5194/hess-28-2969-2024, https://doi.org/10.5194/hess-28-2969-2024, 2024
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Severe flood events pose a threat to riverine areas, yet robust estimates of the dynamics of these events in the future due to climate change are rarely available. Hence, this study uses data from a regional climate model, SMILE, to drive a high-resolution hydrological model for 98 catchments of hydrological Bavaria and exploits the large database to derive robust values for the 100-year flood events. Results indicate an increase in frequency and intensity for most catchments in the future.
Julia Miller, Andrea Böhnisch, Ralf Ludwig, and Manuela I. Brunner
Nat. Hazards Earth Syst. Sci., 24, 411–428, https://doi.org/10.5194/nhess-24-411-2024, https://doi.org/10.5194/nhess-24-411-2024, 2024
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We assess the impacts of climate change on fire danger for 1980–2099 in different landscapes of central Europe, using the Canadian Forest Fire Weather Index (FWI) as a fire danger indicator. We find that today's 100-year FWI event will occur every 30 years by 2050 and every 10 years by 2099. High fire danger (FWI > 21.3) becomes the mean condition by 2099 under an RCP8.5 scenario. This study highlights the potential for severe fire events in central Europe from a meteorological perspective.
Elizaveta Felsche and Ralf Ludwig
Nat. Hazards Earth Syst. Sci., 21, 3679–3691, https://doi.org/10.5194/nhess-21-3679-2021, https://doi.org/10.5194/nhess-21-3679-2021, 2021
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This study applies artificial neural networks to predict drought occurrence in Munich and Lisbon, with a lead time of 1 month. An analysis of the variables that have the highest impact on the prediction is performed. The study shows that the North Atlantic Oscillation index and air pressure 1 month before the event have the highest importance for the prediction. Moreover, it shows that seasonality strongly influences the goodness of prediction for the Lisbon domain.
Nicola Maher, Sebastian Milinski, and Ralf Ludwig
Earth Syst. Dynam., 12, 401–418, https://doi.org/10.5194/esd-12-401-2021, https://doi.org/10.5194/esd-12-401-2021, 2021
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
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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.
Benjamin Poschlod, Ralf Ludwig, and Jana Sillmann
Earth Syst. Sci. Data, 13, 983–1003, https://doi.org/10.5194/essd-13-983-2021, https://doi.org/10.5194/essd-13-983-2021, 2021
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This study provides a homogeneous data set of 10-year rainfall return levels based on 50 simulations of the Canadian Regional Climate Model v5 (CRCM5). In order to evaluate its quality, the return levels are compared to those of observation-based rainfall of 16 European countries from 32 different sources. The CRCM5 is able to capture the general spatial pattern of observed extreme precipitation, and also the intensity is reproduced in 77 % of the area for rainfall durations of 3 h and longer.
Fabian von Trentini, Emma E. Aalbers, Erich M. Fischer, and Ralf Ludwig
Earth Syst. Dynam., 11, 1013–1031, https://doi.org/10.5194/esd-11-1013-2020, https://doi.org/10.5194/esd-11-1013-2020, 2020
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We compare the inter-annual variability of three single-model initial-condition large ensembles (SMILEs), downscaled with three regional climate models over Europe for seasonal temperature and precipitation, the number of heatwaves, and maximum length of dry periods. They all show good consistency with observational data. The magnitude of variability and the future development are similar in many cases. In general, variability increases for summer indicators and decreases for winter indicators.
Andrea Böhnisch, Ralf Ludwig, and Martin Leduc
Earth Syst. Dynam., 11, 617–640, https://doi.org/10.5194/esd-11-617-2020, https://doi.org/10.5194/esd-11-617-2020, 2020
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North Atlantic air pressure variations influencing European climate variables are simulated in coarse-resolution global climate models (GCMs). As single-model runs do not sufficiently describe variations of their patterns, several model runs with slightly diverging initial conditions are analyzed. The study shows that GCM and regional climate model (RCM) patterns vary in a similar range over the same domain, while RCMs add consistent fine-scale information due to their higher spatial resolution.
Ana Casanueva, Sven Kotlarski, Sixto Herrera, Andreas M. Fischer, Tord Kjellstrom, and Cornelia Schwierz
Geosci. Model Dev., 12, 3419–3438, https://doi.org/10.5194/gmd-12-3419-2019, https://doi.org/10.5194/gmd-12-3419-2019, 2019
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Given the large number of available data sets and products currently produced for climate impact studies, it is challenging to distil the most accurate and useful information for climate services. This work presents a comparison of methods widely used to generate climate projections, from different sources and at different spatial resolutions, in order to assess the role of downscaling and statistical post-processing (bias correction).
Winfried Hoke, Tina Swierczynski, Peter Braesicke, Karin Lochte, Len Shaffrey, Martin Drews, Hilppa Gregow, Ralf Ludwig, Jan Even Øie Nilsen, Elisa Palazzi, Gianmaria Sannino, Lars Henrik Smedsrud, and ECRA network
Adv. Geosci., 46, 1–10, https://doi.org/10.5194/adgeo-46-1-2019, https://doi.org/10.5194/adgeo-46-1-2019, 2019
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The European Climate Research Alliance is a bottom-up association of European research institutions helping to facilitate the development of climate change research, combining the capacities of national research institutions and inducing closer ties between existing national research initiatives, projects and infrastructures. This article briefly introduces the network's structure and organisation, as well as project management issues and prospects.
Enrica Perra, Monica Piras, Roberto Deidda, Claudio Paniconi, Giuseppe Mascaro, Enrique R. Vivoni, Pierluigi Cau, Pier Andrea Marras, Ralf Ludwig, and Swen Meyer
Hydrol. Earth Syst. Sci., 22, 4125–4143, https://doi.org/10.5194/hess-22-4125-2018, https://doi.org/10.5194/hess-22-4125-2018, 2018
Prisco Frei, Sven Kotlarski, Mark A. Liniger, and Christoph Schär
The Cryosphere, 12, 1–24, https://doi.org/10.5194/tc-12-1-2018, https://doi.org/10.5194/tc-12-1-2018, 2018
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Snowfall is central to Alpine environments, and its future changes will be associated with pronounced impacts. We here assess future snowfall changes in the European Alps based on an ensemble of state-of-the-art regional climate model experiments and on two different greenhouse gas emission scenarios. The results reveal pronounced changes in the Alpine snowfall climate with considerable snowfall reductions at low and mid-elevations but also snowfall increases at high elevations in midwinter.
Erwin Isaac Polanco, Amr Fleifle, Ralf Ludwig, and Markus Disse
Hydrol. Earth Syst. Sci., 21, 4907–4926, https://doi.org/10.5194/hess-21-4907-2017, https://doi.org/10.5194/hess-21-4907-2017, 2017
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In this research, SWAT was used to model the upper Blue Nile Basin where comparisons between ground and CFSR data were done. Furthermore, this paper introduced the SWAT error index (SEI), an additional tool to measure the level of error of hydrological models. This work proposed an approach or methodology that can effectively be followed to create better and more efficient hydrological models.
Antoine Marmy, Jan Rajczak, Reynald Delaloye, Christin Hilbich, Martin Hoelzle, Sven Kotlarski, Christophe Lambiel, Jeannette Noetzli, Marcia Phillips, Nadine Salzmann, Benno Staub, and Christian Hauck
The Cryosphere, 10, 2693–2719, https://doi.org/10.5194/tc-10-2693-2016, https://doi.org/10.5194/tc-10-2693-2016, 2016
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This paper presents a new semi-automated method to calibrate the 1-D soil model COUP. It is the first time (as far as we know) that this approach is developed for mountain permafrost. It is applied at six test sites in the Swiss Alps. In a second step, the calibrated model is used for RCM-based simulations with specific downscaling of RCM data to the borehole scale. We show projections of the permafrost evolution at the six sites until the end of the century and according to the A1B scenario.
I. Beck, R. Ludwig, M. Bernier, T. Strozzi, and J. Boike
Earth Surf. Dynam., 3, 409–421, https://doi.org/10.5194/esurf-3-409-2015, https://doi.org/10.5194/esurf-3-409-2015, 2015
S. Kotlarski, K. Keuler, O. B. Christensen, A. Colette, M. Déqué, A. Gobiet, K. Goergen, D. Jacob, D. Lüthi, E. van Meijgaard, G. Nikulin, C. Schär, C. Teichmann, R. Vautard, K. Warrach-Sagi, and V. Wulfmeyer
Geosci. Model Dev., 7, 1297–1333, https://doi.org/10.5194/gmd-7-1297-2014, https://doi.org/10.5194/gmd-7-1297-2014, 2014
M. J. Muerth, B. Gauvin St-Denis, S. Ricard, J. A. Velázquez, J. Schmid, M. Minville, D. Caya, D. Chaumont, R. Ludwig, and R. Turcotte
Hydrol. Earth Syst. Sci., 17, 1189–1204, https://doi.org/10.5194/hess-17-1189-2013, https://doi.org/10.5194/hess-17-1189-2013, 2013
J. A. Velázquez, J. Schmid, S. Ricard, M. J. Muerth, B. Gauvin St-Denis, M. Minville, D. Chaumont, D. Caya, R. Ludwig, and R. Turcotte
Hydrol. Earth Syst. Sci., 17, 565–578, https://doi.org/10.5194/hess-17-565-2013, https://doi.org/10.5194/hess-17-565-2013, 2013
Related subject area
Discipline: Snow | Subject: Climate Interactions
Projection of snowfall extremes in the French Alps as a function of elevation and global warming level
Changes in March mean snow water equivalent since the mid-20th century and the contributing factors in reanalyses and CMIP6 climate models
Spatio-temporal reconstruction of winter glacier mass balance in the Alps, Scandinavia, Central Asia and western Canada (1981–2019) using climate reanalyses and machine learning
Impacts of snow assimilation on seasonal snow and meteorological forecasts for the Tibetan Plateau
Synoptic control over winter snowfall variability observed in a remote site of Apennine Mountains (Italy), 1884–2015
Land–atmosphere interactions in sub-polar and alpine climates in the CORDEX Flagship Pilot Study Land Use and Climate Across Scales (LUCAS) models – Part 2: The role of changing vegetation
Snow conditions in northern Europe: the dynamics of interannual variability versus projected long-term change
Historical Northern Hemisphere snow cover trends and projected changes in the CMIP6 multi-model ensemble
Optimization of over-summer snow storage at midlatitudes and low elevation
An efficient surface energy–mass balance model for snow and ice
Spring snow albedo feedback over northern Eurasia: Comparing in situ measurements with reanalysis products
Erwan Le Roux, Guillaume Evin, Raphaëlle Samacoïts, Nicolas Eckert, Juliette Blanchet, and Samuel Morin
The Cryosphere, 17, 4691–4704, https://doi.org/10.5194/tc-17-4691-2023, https://doi.org/10.5194/tc-17-4691-2023, 2023
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We assess projected changes in snowfall extremes in the French Alps as a function of elevation and global warming level for a high-emission scenario. On average, heavy snowfall is projected to decrease below 3000 m and increase above 3600 m, while extreme snowfall is projected to decrease below 2400 m and increase above 3300 m. At elevations in between, an increase is projected until +3 °C of global warming and then a decrease. These results have implications for the management of risks.
Jouni Räisänen
The Cryosphere, 17, 1913–1934, https://doi.org/10.5194/tc-17-1913-2023, https://doi.org/10.5194/tc-17-1913-2023, 2023
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Changes in snow amount since the mid-20th century are studied, focusing on the mechanisms that have changed the water equivalent of the snowpack (SWE). Both reanalysis and climate model data show a decrease in SWE in most of the Northern Hemisphere. The total winter precipitation has increased in most areas, but this has been compensated for by reduced snowfall-to-precipitation ratio and enhanced snowmelt. However, the details and magnitude of these trends vary between different data sets.
Matteo Guidicelli, Matthias Huss, Marco Gabella, and Nadine Salzmann
The Cryosphere, 17, 977–1002, https://doi.org/10.5194/tc-17-977-2023, https://doi.org/10.5194/tc-17-977-2023, 2023
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Spatio-temporal reconstruction of winter glacier mass balance is important for assessing long-term impacts of climate change. However, high-altitude regions significantly lack reliable observations, which is limiting the calibration of glaciological and hydrological models. We aim at improving knowledge on the spatio-temporal variations in winter glacier mass balance by exploring the combination of data from reanalyses and direct snow accumulation observations on glaciers with machine learning.
Wei Li, Jie Chen, Lu Li, Yvan J. Orsolini, Yiheng Xiang, Retish Senan, and Patricia de Rosnay
The Cryosphere, 16, 4985–5000, https://doi.org/10.5194/tc-16-4985-2022, https://doi.org/10.5194/tc-16-4985-2022, 2022
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Snow assimilation over the Tibetan Plateau (TP) may influence seasonal forecasts over this region. To investigate the impacts of snow assimilation on the seasonal forecasts of snow, temperature and precipitation, twin ensemble reforecasts are initialized with and without snow assimilation above 1500 m altitude over the TP for spring and summer in 2018. The results show that snow assimilation can improve seasonal forecasts over the TP through the interaction between land and atmosphere.
Vincenzo Capozzi, Carmela De Vivo, and Giorgio Budillon
The Cryosphere, 16, 1741–1763, https://doi.org/10.5194/tc-16-1741-2022, https://doi.org/10.5194/tc-16-1741-2022, 2022
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This work documents the snowfall variability observed from late XIX century to recent years in Montevergine (southern Italy) and discusses its relationship with large-scale atmospheric circulation. The main results lie in the absence of a trend until mid-1970s, in the strong reduction of the snowfall quantity and frequency from mid-1970s to 1990s and in the increase of both variables from early 2000s. In the past 50 years, the nivometric regime has been strongly modulated by AO and NAO indices.
Priscilla A. Mooney, Diana Rechid, Edouard L. Davin, Eleni Katragkou, Natalie de Noblet-Ducoudré, Marcus Breil, Rita M. Cardoso, Anne Sophie Daloz, Peter Hoffmann, Daniela C. A. Lima, Ronny Meier, Pedro M. M. Soares, Giannis Sofiadis, Susanna Strada, Gustav Strandberg, Merja H. Toelle, and Marianne T. Lund
The Cryosphere, 16, 1383–1397, https://doi.org/10.5194/tc-16-1383-2022, https://doi.org/10.5194/tc-16-1383-2022, 2022
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We use multiple regional climate models to show that afforestation in sub-polar and alpine regions reduces the radiative impact of snow albedo on the atmosphere, reduces snow cover, and delays the start of the snowmelt season. This is important for local communities that are highly reliant on snowpack for water resources and winter tourism. However, models disagree on the amount of change particularly when snow is melting. This shows that more research is needed on snow–vegetation interactions.
Jouni Räisänen
The Cryosphere, 15, 1677–1696, https://doi.org/10.5194/tc-15-1677-2021, https://doi.org/10.5194/tc-15-1677-2021, 2021
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Interannual variability of snow amount in northern Europe is studied. In the coldest areas, total winter precipitation governs snow amount variability. In warmer regions, the fraction of snowfall that survives without melting is more important. Since winter temperature and precipitation are positively correlated, there is often more snow in milder winters in the coldest areas. However, in model simulations of a warmer future climate, snow amount decreases nearly everywhere in northern Europe.
Lawrence Mudryk, María Santolaria-Otín, Gerhard Krinner, Martin Ménégoz, Chris Derksen, Claire Brutel-Vuilmet, Mike Brady, and Richard Essery
The Cryosphere, 14, 2495–2514, https://doi.org/10.5194/tc-14-2495-2020, https://doi.org/10.5194/tc-14-2495-2020, 2020
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We analyze how well updated state-of-the-art climate models reproduce observed historical snow cover extent and snow mass and how they project that these quantities will change up to the year 2100. Overall the updated models better represent historical snow extent than previous models, and they simulate stronger historical trends in snow extent and snow mass. They project that spring snow extent will decrease by 8 % for each degree Celsius that the global surface air temperature increases.
Hannah S. Weiss, Paul R. Bierman, Yves Dubief, and Scott D. Hamshaw
The Cryosphere, 13, 3367–3382, https://doi.org/10.5194/tc-13-3367-2019, https://doi.org/10.5194/tc-13-3367-2019, 2019
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Climate change is devastating winter tourism. High-elevation, high-latitude ski centers have turned to saving snow over the summer. We present results of two field seasons to test and optimize over-summer snow storage at a midlatitude, low-elevation nordic ski center in the northeastern USA. In 2018, we tested coverings and found success overlaying 20 cm of wet woodchips with a reflective sheet. In 2019, we employed this strategy to a large pile and stored sufficient snow to open the ski season.
Andreas Born, Michael A. Imhof, and Thomas F. Stocker
The Cryosphere, 13, 1529–1546, https://doi.org/10.5194/tc-13-1529-2019, https://doi.org/10.5194/tc-13-1529-2019, 2019
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We present a new numerical model to simulate the surface energy and mass balance of snow and ice. While similar models exist and cover a wide range of complexity from empirical models to those that simulate the microscopic structure of individual snow grains, we aim to strike a balance between physical completeness and numerical efficiency. This new model will enable physically accurate simulations over timescales of hundreds of millennia, a key requirement of investigating ice age cycles.
Martin Wegmann, Emanuel Dutra, Hans-Werner Jacobi, and Olga Zolina
The Cryosphere, 12, 1887–1898, https://doi.org/10.5194/tc-12-1887-2018, https://doi.org/10.5194/tc-12-1887-2018, 2018
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An important factor for Earth's climate is the high sunlight reflectivity of snow. By melting, it reveals darker surfaces and sunlight is converted to heat. We investigate how well this process is represented in reanalyses data sets compared to observations over Russia. We found snow processes to be well represented, but reflectivity variability needs to be improved. Our results highlight the need for a better representation of this key climate change feedback process in modelled data.
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Short summary
Climate change will significantly reduce snow cover, but the extent remains disputed. We use regional climate model data as a driver for a snow model to investigate the impacts of climate change and climate variability on snow. We show that natural climate variability is a dominant source of uncertainty in future snow trends. We show that anthropogenic climate change will change the interannual variability of snow. Those factors will increase the vulnerabilities of snow-dependent economies.
Climate change will significantly reduce snow cover, but the extent remains disputed. We use...
