Spatial and temporal variability of snow density and snow temperature at high mountain sites

Measurements of the glacier mass balance are of great climatic relevance, as glaciers serve as reliable indicators of climate change. They respond directly and sensitively to changes in long-term atmospheric conditions. They virtually ‘live’ on the same time scale as climate change. To understand how a glacier reacts to the prevailing climate and its changes, glacier mass balance measurements are conducted on some glaciers either annually or every six months. The winter mass balance measurement, usually performed in early May when the snow thickness on glaciers is at its greatest, assesses the increase in mass during the winter months. This involves measuring snow depth at multiple points using either a probe or radar and, for a subset of snow profiles also the snow density, to be able to convert the measured snow depths into mass. The point measurements are then spatially interpolated and aggregated to calculate the total mass change. With snow depths averaging over four metres, accurately determining vertical snow density is a complex undertaking. This master's thesis examines how well the spatial and temporal variability of snow density can be approximated using meteorological and topographical parameters as well as the errors associated with these approximations. The analysis is based on a dataset of snow density and snow temperature measurements from more than 500 snow profiles taken over a period of more than 40 years on three glaciers in the Hohe Sonnblick area in the Hohe Tauern region in the Austrian Alps. High-resolution topographical parameters such as location, altitude, slope inclination and exposure of the snow profiles along with daily climate data from the TAWES Sonnblick station are used as predictors. The aim of this thesis is to improve snow density measurements and to optimize and enable improved modelling of the glacier mass balance.