Persistent Alpine Warming Amplification and Its Underestimation in Climate Models

Mountain regions are often considered particularly sensitive to climate change, yet the magnitude and drivers of enhanced warming remain uncertain. Here we assess whether the Greater Alpine Region (GAR) represents a climate warming hotspot relative to surrounding parts of Western-Central Europe and how the past warming patterns are reflected in global climate models.

We analyse long-term mean temperature changes from observational and model-based datasets, including the ERA5 and ERA5-Land reanalysis, the E-OBS gridded dataset, and global climate model simulations assessed in the IPCC Sixth Assessment Report (CMIP6). Trends are evaluated for 1950–2025 and compared with global mean warming to estimate amplification ratios.

Observations and reanalyses consistently indicate strong mean warming across the GAR since 1950, with particularly rapid increases in all seasons during recent decades. The region exhibits an amplification ratio relative to the global mean warming of roughly 2 to 2.4 that has remained remarkably stable for the last 25 years.

Whether Alpine warming exceeds that of neighbouring lowland regions is less clear. ERA5 suggests stronger Alpine warming, whereas ERA5-Land and E-OBS indicate similar trends in the surrounding regions of Western-Central Europe. Higher-resolution national datasets show the strongest warming at the Alpine foothills compared to high elevations in recent decades.

CMIP6 global climate models substantially underestimate the observed warming over the GAR, producing an amplification ratio of only about 1.3. The reasons are still under discussion but likely include substantial uncertainties related to the impacts of regional circulation changes, aerosol forcing and land-atmosphere coupling.

Overall, the results indicate that Western–Central Europe including the GAR behave as a persistent regional warming hotspot and highlight a substantial mismatch between observed and modelled temperature change. Improving the representation of local climate processes in reanalyses, observational datasets, and climate models is therefore essential to better understand regional warming mechanisms and to produce reliable regional climate projections and impact assessments, especially in mountain environments.