Patterns of Glacier Change in Austria: Variability Assessment and a New Classification Scheme for Glacier State

Abstract:

Drawing on existing inventories and new data, we take stock of glacier change in Austria during the last 50 years. By combining time series of mass balance and ice thickness data with remote sensing based digital terrain models (DTMs), we contextualise the role of long-term monitoring sites as sentinels of regional change. From the DTMs we extract elevation profiles of surface elevation change as well as surface change frequency distributions for individual glaciers as well as on a regional level. We quantify volume loss, the variability of surface elevation change and how it has changed over time, and discuss the implications for the representativity of long-term monitoring sites. Additionally, we apply a machine learning based pattern detection algorithm to surface change distributions and develop a classification scheme for regional analysis of glacier state. Volume loss and trends in variability of surface elevation change differ depending on glacier characteristics. In general, variability is increasing at lower elevations and roughly constant at higher elevations. Surface elevation change distributions increasingly indicate processes of glacier disintegration. Change rates have increased in recent years and are highest at large glaciers that still extend to low elevations. Ice thickness and the spatial distribution of glacier surface elevation change are more homogeneous at glaciers in lower elevation regions. The more uniform thinning in these regions will result in deglaciation within a few decades.