SnowShifts : an exciting new ERC project starting in 2026 !
© 2026 EPFL
"SnowShifts : current and future shifts of snow regimes in extreme environments" : a new project funded by European Research Council.
The UN Decade of Action on Cryospheric Sciences aims to reduce uncertainties regarding the causes and effects of changes in snow, ice, and permafrost. Snow is a major contributor to these uncertainties due to the incomplete understanding and representation of snow processes in climate models. SnowShifts seeks to significantly enhance our comprehension of snow volume and mass, their non-linear dynamics and properties and, specifically, snow regime shifts within the Earth and climate systems.
Illustration : Ice and rock at Vesthaugen (Photo: Hendrik Huwald) - Princess Elisabeth expedition 2019.
- Main contributors :
- UNIVERSITETET I OSLO, Professor Andreas Kääb, coordinator.
- UNIVERSITAET FUER BODENKULTUR WIEN, Professor Franziska Koch, host.
- EPFL, CRYOS laboratory, Professor Michael Lehning, host.
- Funding : European Research Council / HORIZON-ERC-SYG
- Duration : 6 years
- Abstract :
The UN Decade of Action on Cryospheric Sciences aims to reduce uncertainties regarding the causes and effects of changes in snow, ice, and permafrost. Snow is a major contributor to these uncertainties due to the incomplete understanding and representation of snow processes in climate models. SnowShifts seeks to significantly enhance our comprehension of snow volume and mass, their non-linear dynamics and properties and, specifically, snow regime shifts within the Earth and climate systems.
This will be achieved through a novel combination of in-situ and remote sensing observations, along with high-end numeric model developments. Innovative technologies such as photon-counting space-borne laser altimeters, terrestrial superconducting gravimeters, and novel scale-bridging approaches and downscaling of satellite gravimetry in extreme snow environments will be integrated with the latest multi-sensor satellite data and modelling. This will enable the retrieval of snow volume, mass, extent, and other properties, such as snow albedo, at unprecedented spatio-temporal resolutions. The combined observational and modelling advancements will define and describe trends and shifts in snow climates ranging from high-latitude polar regions to mid-latitude high-mountain ranges.
This project will provide future snow scenarios for at least three socio-economic pathways refining current global and regional climate models, exploring and defining potential non-linearities in snow changes. SnowShifts will not only demonstrate the accuracy of our new models in reproducing snow quantities and dynamics, but will also generate extensive datasets characterising snow in remote and understudied regions. The new representations of snow processes will be a major outcome permitting the scientific community to incorporate the knowledge gained into climate and land surface models, and to replace in parts computationally expensive model components with machine learning emulators.