Abstract
Abstract. Snow is a sensitive component of the climate system. In many parts of the world, water stored as snow is a vital resource for agriculture, tourism and the energy sector. As uncertainties in climate change assessments are still relatively large, it is important to investigate the interdependencies between internal climate variability and anthropogenic climate change and their impacts on snow cover. We use regional climate model data from a new single-model large ensemble with 50 members (ClimEX LE) as a driver for the physically based snow model SNOWPACK at eight locations across the Swiss Alps. We estimate the contribution of internal climate variability to uncertainties in future snow trends by applying a Mann–Kendall test for consecutive future periods of different lengths (between 30 and 100 years) until the end of the 21st century. Under RCP8.5, we find probabilities between 10 % and 60 % that there will be no significant negative trend in future mean snow depths over a period of 50 years. While it is important to understand the contribution of internal climate variability to uncertainties in future snow trends, it is likely that the variability of snow depth itself changes with anthropogenic forcing. We find that relative to the mean, interannual variability of snow increases in the future. A decrease in future mean snow depths, superimposed by increases in interannual variability, will exacerbate the already existing uncertainties that snow-dependent economies will have to face in the future.
Highlights
In large parts of the world, water stored in snow is a vital resource for water management with regard to agriculture and power generation
While we are gaining important insights into the dynamics of mean, maximum and interannual variability of snow depth and the role of internal climate variability (ICV) under climate change conditions, a number of important uncertainties and limitations must be taken into account, which span over the whole modeling process
Important boundary conditions are that our results are highly dependent on the choice of the emission scenario and the combination of global climate model (GCM) and regional climate model (RCM) as well as the selected bias adjustment approach
Summary
In large parts of the world, water stored in snow is a vital resource for water management with regard to agriculture and power generation. Several studies have analyzed trends in historical snow cover, but there is not a uniform pattern across the world. While there are many regions where snow cover and depth are decreasing, there are areas that show no trend or even increasing snow depths (Dyer and Mote, 2006; Schöner et al, 2019; Zhang and Ma, 2018). These contrasting findings can be attributed to spatial and temporal climate variability, from global to local scales
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
