User-tailored climate scenarios in the Alpine space: The new Swiss CH2025 scenarios
(2) Swiss Academy of Sciences SCNAT
(3) Center for Climate Systems Modeling C2SM, ETH Zurich
Abstract
Climate change scenarios are a cornerstone for understanding future weather and climate conditions and for climate adaptation, yet their development remains particularly challenging in complex mountain environments. The European Alps are warming faster than the global average, and recent updates such as the Swiss Climate CH2025 scenarios (www.climate-scenarios.ch) project substantial further changes in temperature, precipitation patterns, snow cover, and climate extremes over the coming decades. Translating climate model-based projections into both reliable and actionable information for the Alps requires addressing strong spatial heterogeneity driven by elevation, topography, and land-surface processes.
A key challenge lies in the downscaling of climate model outputs to the fine spatial and temporal scales needed to capture Alpine weather dynamics. Orographic effects, local circulation patterns, and elevation-dependent warming are often insufficiently resolved, leading to uncertainties that are especially relevant for extremes such as heavy precipitation, heatwaves, droughts, and snow-related processes. These uncertainties are compounded by limited long-term observations at high elevations and by non-linear feedbacks linked to snow, glaciers, and permafrost.
Using the Climate CH2025 framework, we discuss methodological aspects of scenario construction for the Alpine space and present a dedicated analysis for the Swiss National Park. This case study illustrates how regional climate signals manifest in a protected high-mountain environment and highlights sensitivities in seasonal temperature evolution, precipitation regimes, and snow conditions. The results underscore both the value and the limitations of current climate scenarios for Alpine applications, and their implications for interpreting future weather and climate in mountain regions.
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