Preprints
https://doi.org/10.5194/egusphere-2026-3478
https://doi.org/10.5194/egusphere-2026-3478
06 Jul 2026
 | 06 Jul 2026
Status: this preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).

Modeling 21st century snow dynamics in Switzerland using high-resolution Climate CH2025 scenarios

Harsh Beria, Sven Kotlarski, Adrien Michel, Jan Magnusson, and Christoph Marty

Abstract. Snow is a key component of Alpine landscapes, providing numerous ecosystem and economic services that include hydropower production, winter tourism, groundwater recharge, and regulation of stream temperatures, with significant implications for aquatic ecosystems. In a warming climate, expected increases in winter precipitation do not necessarily lead to greater snow accumulation, as rising air temperatures shift precipitation from snowfall to rainfall and reduce the persistence of snow on the ground. This creates a need for future snow projections at locally relevant spatial scales to support adaptation for snow-dependent sectors.

Here, we present daily projections of snow water equivalent (SWE) for Switzerland at 1x1 km² resolution, based on the Climate CH2025 scenarios, which downscaled and bias-adjusted meteorological forcings from an ensemble of EURO-CORDEX regional climate models. SWE was simulated using a spatially distributed temperature-index snow model for 12 climate model chains, selected for their ability to accurately represent atmospheric forcings for modeling snow cover dynamics across Switzerland over the historical reference period (1991–2020). To reduce biases associated with the simplified degree-day-based snowmelt representation used here, simulated SWE was quantile mapped toward SPASS-CLQM, a new gridded climatological snow reference dataset for Switzerland.

We found that the univariate quantile mapping of meteorological forcings in Climate CH2025 models reduced precipitation under sub-freezing conditions, resulting in too little simulated snowfall in many model chains, which then propagated nearly linearly into biases in SWE. Simulated SWE in the final set of 12 models was additionally quantile mapped toward SPASS-CLQM, which substantially reduced SWE biases across elevation bands and was then applied to future simulations. By the end of century (2069–2099), projected SWE showed widespread declines across Switzerland relative to 1991–2020. Percentage September–May mean SWE losses exceeded 80 % below 1000 m a.s.l. for the highest emission pathway (RCP8.5), where snow became increasingly rare. At intermediate elevations (1000–2000 m a.s.l.), mean SWE declines of 50–90 % are projected, with the snowpack becoming increasingly ephemeral. Above 2000 m a.s.l., mean SWE reductions ranged from 20 to 70 %, indicating that even high-elevation seasonal snow storage would reduce substantially. These projections provide a spatially detailed basis for assessing future changes in Alpine snow resources and for informing the management of snow-dependent hydrological, ecological, and economic systems in a rapidly warming climate.

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Harsh Beria, Sven Kotlarski, Adrien Michel, Jan Magnusson, and Christoph Marty

Status: open (until 17 Aug 2026)

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Harsh Beria, Sven Kotlarski, Adrien Michel, Jan Magnusson, and Christoph Marty
Harsh Beria, Sven Kotlarski, Adrien Michel, Jan Magnusson, and Christoph Marty
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Latest update: 06 Jul 2026
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Short summary
Snow is a vital water store for Switzerland, supporting hydropower, winter tourism, and aquatic ecosystems. Using the latest Swiss climate projections, we project future snow water across Switzerland at high spatial resolution. By the end of this century under high emission scenarios, low-lying regions are projected to become nearly snow-free, while even high mountains lose much of their snow. These results can support planning for future Alpine water resources under a warming climate.
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