Snow stores a significant amount of water in mountain regions. The decrease of water storage in the snowpack can have relevant impacts on water supply for mountain and lowland areas that rely on snow melting. In this work, we modelled the Snow Water Equivalent (SWE) using daily snow depth (HS) data obtained from 19 historical HS measurement stations located in the southern European Alps (Italy). Then, we analysed the long-term (1930–2020) variability of the monthly Standardised SWE Index (SSWEI) and its links with climate change and large-scale atmospheric forcings (teleconnection indices). We found a marked variability in monthly SSWEI, with the lowermost values generally occurring in the last few decades (1991–2020), irrespective of elevation. In this recent period, highly negative values occurred at the snow season tails, mostly in spring. We found large-scale atmospheric patterns (North Atlantic Oscillation, Atlantic Multi-decadal Oscillation, and Artic Oscillation) and precipitation to be interconnected with SSWEI oscillations, although this relation changed after the 1980s, especially at low and medium elevations. This change occurred in correspondence of highly positive air temperature anomalies. In the last decades, we found increasing air temperature to be the main driver for the pronounced snow mass loss and persistent snow-drought conditions.
Long-term trend of snow water equivalent in the Italian Alps
Paola Cianfarra;
2022-01-01
Abstract
Snow stores a significant amount of water in mountain regions. The decrease of water storage in the snowpack can have relevant impacts on water supply for mountain and lowland areas that rely on snow melting. In this work, we modelled the Snow Water Equivalent (SWE) using daily snow depth (HS) data obtained from 19 historical HS measurement stations located in the southern European Alps (Italy). Then, we analysed the long-term (1930–2020) variability of the monthly Standardised SWE Index (SSWEI) and its links with climate change and large-scale atmospheric forcings (teleconnection indices). We found a marked variability in monthly SSWEI, with the lowermost values generally occurring in the last few decades (1991–2020), irrespective of elevation. In this recent period, highly negative values occurred at the snow season tails, mostly in spring. We found large-scale atmospheric patterns (North Atlantic Oscillation, Atlantic Multi-decadal Oscillation, and Artic Oscillation) and precipitation to be interconnected with SSWEI oscillations, although this relation changed after the 1980s, especially at low and medium elevations. This change occurred in correspondence of highly positive air temperature anomalies. In the last decades, we found increasing air temperature to be the main driver for the pronounced snow mass loss and persistent snow-drought conditions.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.