Climate-trend analysis of air temperature and precipitation in the Extended Alpine Region (1961-2020)

The Alpine area is one of the most vulnerable and sensitive regions to the continuous warming of climate and it is considered an important hotspot of climate change. In particular, climate change is expected to exert a strong influence on all components of the hydrological cycle, including river regimes, with consequent effects on the services offered by the freshwater ecosystem, as well as on water availability for users, thus affecting several socio-economic sectors. Climate change assessment in the Alpine region relies on direct application of climate observations and, thus, their quality may strongly impact climate and hydrological studies results and predictions in terms of reliability, accuracy and precision. Here, we present an extended climatological-trend analysis focused on the Alpine region over the 1961-2020 period. The potential of a recently developed and unprecedented observational dataset, addressing the key issues in terms of spatial density, data quality, time resolution and completeness, was exploited. About 300 time series of air temperature and 1000 of precipitation, covering homogeneously the extent and the elevation gradient of this area, were selected depending on World Meteorological Organization (WMO) requirements. Climatological and trend analysis was carried out on different time scales considering both mean values and a selection of ETCCDI indices. The phenomena of elevation-dependent warming (EDW) and precipitation change (EDPC) were also assessed. A pca-based clustering approach was applied to identify climatic regions and evaluate the spatial-dependency of trends. A further analysis concerned the relationship between detrended time series and the main teleconnection patterns.The present study aims to provide a reliable analysis of the evolution of key climate variables in the Alpine region. Being a study based on the most comprehensive spatial coverage in this area to date, the related results significantly increase the amount of information available to involved stakeholders to prevent and quickly plan for disaster management, risk mitigation and formulating proper locally relevant adaptation strategies.