Reanalysis-based contextualization of real-time snow cover monitoring from space

Abstract

Satellite remote sensing provides real time information on the extent of the snow cover. However, the period of record is generally too short to build a climatology from these data, preventing their use as climatic indicator. Here we show that reanalysis data can be used to reconstruct a 30-year snow cover time series that fits well the satellite observations. This climatology can then be used to put the current state of the snow cover into perspective. We implemented this approach to provide real time information on the snow cover area in the Alps through a web application.

Remote sensing of mountain snow from space: status and recommendations

“…This is especially the case with the Sentinel-1, Sentinel-2 and Landsat datasets, but it will be the case with upcoming missions like NISAR. Snow scientists increasingly rely on commercial cloud geoprocessing platforms such as Google Earth Engine and Microsoft Planetary Computer to process remote sensing datasets (Crumley et al, 2020;Notarnicola, 2020;Gascoin et al, 2022;Gagliano et al, 2023). High performance and cloud computing is also becoming critical to perform intensive computations for machine and deep learning and ensemble-based data assimilation.…”