Modeling future Snow Line Elevation dynamics in the Alps based on long remote sensing time-series

Abstract

The inter and intra-annual dynamics of seasonal snow are of key interest in the tourism-based economies of many Alpine regions as well as for millions of people in the adjacent European lowlands when it comes to freshwater supply and electricity generation. However, accurate snow observations over long periods of time and at large spatial scales are especially challenging in inaccessible mountainous areas. This can be overcome by using data from Earth Observation satellites, which have been constantly monitoring the Earth’s surface for almost 40 years. On a catchment basis, we derive the Snow Line Elevation (SLE) from Landsat data for the entire Alpine region and model the spatio-temporal dynamics in monthly time-series ranging from 1984 to today. Based on the historical observations we model future SLE dynamics comparing different uni-variate and multi-variate approaches and assess them for their ability to generate multi-year forecasts from EO-derived time series data. These forecasts can enable local and regional stakeholders to adapt to a potentially changing snow regime under climate change.