Snow Line Elevation Trends in the Alps, Pyrenees, and Andes Mountains, derived from 40-year Landsat snow cover time series

Kurzfassung

Climate change is affecting the snow cover in mountain regions all around the world. With temperatures increasing, snow melt starts earlier every year on both Hemispheres, leading to various effects such as changes in the runoff regime, albedo, vegetation dynamics, animal habitats, floods, and impacts on tourism and hydropower generation. Because temperatures are expected to increase even more in the upcoming years, a detailed trend analysis of past developments is desired to understand the potential effects in the future. because climate models are oftentimes too coarse to produce reliable results for the complex terrain of mountain regions, time series of high-resolution remote sensing data offer a great alternative. At the German Aerospace Center (DLR), methods to derive Snow Line Elevation (SLE) statistics based on long-term time series of Landsat data have been developed which can be utilized to derive monthly SLEs for every mountain catchment around the globe where Landsat data is available. The challenges when dealing with Landsat time series comprise aspects such as considerable data gaps caused by cloud cover, different data availability throughout the years and Landsat generations, and the generally difficult to handle conditions in steep mountain terrain. The derived SLEs can be analyzed to identify trends in autumn or spring, delineating to which extent the snow cover is retreating each year. These trends can be further analyzed to identify the trend significance, or can be used to predict the potential future SLE retreat. The developed methods have been applied to the European Alps, the Pyrenees, and some catchments in the Chilean Andes Mountains close to Santiago de Chile. The analysis of the SLEs has revealed significant trends in all three regions, with SLEs retreating up to 20 meters per year during spring. These snow cover changes can pose significant challenges to flora, fauna, and humans in the affected regions and beyond.