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<p>Assessing future changes of weather-related variables in mountainous areas poses significant challenges, partly due to the inherent complexity of orographic effects and the associated atmospheric dynamics, which further amplify the difficulty. Additionally, mountains exhibit region-specific changes, making it essential to analyze single areas separately. In recent decades, elevation-dependent warming and its future projections have been studied extensively compared to other variables. However, understanding the drivers and interconnections among various elevation patterns requires a comprehensive analysis of results from model simulations. This study focuses on the European Alpine region and uses the large EURO-CORDEX ensemble to investigate elevation-dependent patterns of change between the historical period (1981–2010) and future projections (2071–2100, RCP8.5) across 18 climate variables, including surface and air temperature, long- and shortwave radiation, humidity, cloud cover, and snow cover. In particular, we assess whether these elevation-dependent patterns are consistent across simulations during the winter and spring seasons, and we investigate potential driving mechanisms behind these changes. We find strong elevation-dependent patterns for minimum temperature, diurnal temperature range, and specific humidity. Significant correlations are also observed between changes of surface temperature and diurnal temperature range, minimum temperature, specific humidity, downward longwave radiation, and shortwave radiation balance. These relationships exhibit a clear elevation dependence, possibly primarily driven by changes in snow cover and soil properties, which also influence surface heat fluxes. At the same time, the results indicate that variables heavily influenced by model parameterization (e.g. heat fluxes and snow cover fraction) exhibit little to no coherence within the ensemble. This underscores the importance of adopting an ensemble-based approach when developing climate scenarios for future adaptation plans in order to capture the full range of possible outcomes.</p>

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Future elevation-dependent changes in meteorological variables across the european alps and their possible links to surface temperature: insights from the EURO-CORDEX ensemble

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月28日

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  • Anna Napoli,
  • Michael Matiu,
  • Sven Kotlarski,
  • Dino Zardi,
  • Alberto Bellin,
  • Bruno Majone

摘要

Assessing future changes of weather-related variables in mountainous areas poses significant challenges, partly due to the inherent complexity of orographic effects and the associated atmospheric dynamics, which further amplify the difficulty. Additionally, mountains exhibit region-specific changes, making it essential to analyze single areas separately. In recent decades, elevation-dependent warming and its future projections have been studied extensively compared to other variables. However, understanding the drivers and interconnections among various elevation patterns requires a comprehensive analysis of results from model simulations. This study focuses on the European Alpine region and uses the large EURO-CORDEX ensemble to investigate elevation-dependent patterns of change between the historical period (1981–2010) and future projections (2071–2100, RCP8.5) across 18 climate variables, including surface and air temperature, long- and shortwave radiation, humidity, cloud cover, and snow cover. In particular, we assess whether these elevation-dependent patterns are consistent across simulations during the winter and spring seasons, and we investigate potential driving mechanisms behind these changes. We find strong elevation-dependent patterns for minimum temperature, diurnal temperature range, and specific humidity. Significant correlations are also observed between changes of surface temperature and diurnal temperature range, minimum temperature, specific humidity, downward longwave radiation, and shortwave radiation balance. These relationships exhibit a clear elevation dependence, possibly primarily driven by changes in snow cover and soil properties, which also influence surface heat fluxes. At the same time, the results indicate that variables heavily influenced by model parameterization (e.g. heat fluxes and snow cover fraction) exhibit little to no coherence within the ensemble. This underscores the importance of adopting an ensemble-based approach when developing climate scenarios for future adaptation plans in order to capture the full range of possible outcomes.