Statistically combine climate models with remote sensing to provide high-resolution snow projections for the near and distant future
The cryosphere in the European Alps is expected to change substantially with global warming. Existing approaches to infer future snow conditions rely on physical models, either on regional climate models (RCMs) or snow-hydrological models, which are both computationally very intensive. To achieve a high-resolution output for such a large area as the Alps is almost impossible. In CliRSnow, empirical models derived from remote sensing (RS) are employed to provide an innovative and fast solution to increase the precision in future projections of snow cover from RCMs for the whole Alpine area. This will be achieved by correcting the bias in snow cover from RCMs and increasing the spatial resolution with RS snow cover data. Such an approach has now become feasible, because the data that forms its basis is on the verge of being sufficient in time (RS: MODIS time series since 2000) and space (RCM: EURO-CORDEX horizontal resolution at approx. 12.5km).
Contact Person: Michael Matiu
- Project duration: -
- Project status:
- Funding: Excellence Science (Horizon 2020 /EU funding /Project)
- Institutes: Institute for Earth Observation, Center for Climate Change and Transformation
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