Statistically combine climate models with remote sensing to provide high-resolution snow projections for the near and distant future.
Snow in the European Alps - past, present, and future
Combining in-situ observations, remote sensing, and climate models
Post-doctoral fellowship funded by the EU Horizon 2020 Marie Skłodowska-Curie Actions
October 2018 - September 2021 (part time; 24 months full time equivalent)
The aim of CliRSnow is to provide high-resolution snow cover climatologies and projections by exploiting statistical relationships between earth observation data (remote sensing and in-situ) and climate models.
The main objectives are:
Statistical post-processing of climate model output using earth observation data for snow cover fraction.
Bias adjusted and downscaled output from regional climate models (RCMs) for the Greater Alpine Region using earth observation data.
First alpine wide study on ground snow depth observation
Homogenized dataset of over 2000 series of daily snow observations.
Python code to remove clouds in Eurac’s MODIS snow maps
Data descriptor of Eurac’s MODIS almost cloudfree snow maps
Biases and Their Relationship to Orography, Temperature, and Precipitation Mismatches
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 795310.