Glaciers play a pivotal role in climate change. Their rapid melting is a highly visible sign of the changes occurring on our planet, and their disappearance affects the water balance of a region. Moreover, the melting of polar ice caps feeds the global rise in sea levels. It is not so easy, however, to keep track of the exact development of glaciers, as they are – at least for the time being – too large and too numerous for individual monitoring. Hence, it is particularly important to develop models that record the physical processes behind the change in a glacier as precisely as possible – and that can also be transferred as easily as possible to other areas that deny exact observation.
The project “Snow cover dynamics and mass balance on mountain glaciers” brings together a team of researchers from the Universities of Innsbruck and Erlangen-Nuremberg in Germany with the aim of developing and improving such glacier models. They analyse the changes in mass balance and energy flows around the glaciers “in high temporal and spatial resolution” in order to improve accounting for precipitation distributions, snowdrifts and local weather phenomena. “The smaller the mountain glaciers become, the more important these very small-scale phenomena become for their modelling,” says Brigitta Goger of the Department of Atmospheric and Cryospheric Sciences at the University of Innsbruck. Together with glaciologist Georg Kaser and other colleagues, Goger is designing strategies for a more close-meshed physical description of the glaciers.
Brigitta Goger holds a post-doc position at the Department of Atmospheric and Cryospheric Sciences at the University of Innsbruck, where she wrote her doctoral thesis on high-resolution weather prediction models. Previously she studied meteorology at the University of Vienna. The principal investigator Georg Kaser is one of Austria’s most renowned climate researchers. Funded by the FWF with EUR 405,000, the international project “Snow cover dynamics and mass balance on mountain glaciers” is set to run until 2023.
Measurements on the Tyrolean Hintereisferner
The project team has chosen the Hintereisferner as the starting point for their work. The Hintereisferner is a comparatively large glacier covering an area of six square kilometres, but nevertheless easily accessible. It is situated in the rear Ötztal valley near the border between Tyrol and Italy – not far from the place where the mummified ice man nicknamed “Ötzi” was found. What recommends the Hintereisferner is the fact that it is one of the best researched glaciers in Austria and the Alps in general. A measurement infrastructure, globally unparalleled in this form, has been in place here since 2016: a permanently installed laser scanner that is remotely controlled from Innsbruck and can produce daily scans of the glacier surface. Changes in height, volume and mass can be calculated from the terrain models that are produced on the basis of the extensive measurement data. Complementing the traditional compilation of mass balance using level bars, this technical tool is an important aid for Goger and the research team to produce advanced modelling of glacier physics.
In the first phase of the project, Annelies Voordendag, a PhD student at the Department of Atmospheric and Cryospheric Sciences, had the task of investigating how accurate and how prone to error the measurement system was. These factors depend on aspects such as measurement distance, weather and wind, and are thus essential for meaningful models using them as a basis. “We have learned that we are able to achieve measuring accuracy with maximum deviations of about ten centimetres – that is good enough also to be able to derive the daily snowdrift from the terrain models,” says Goger, who is using the data to develop her own “snowdrift module” for glacier modelling.
Interaction between ice and atmosphere
The results will enable the researchers to interrelate the data on the glacier surface, which changes daily because of precipitation, melt or snowdrifts, with an atmospheric model. As Goger points out, the air movements above the glacier are particularly complex: “The heat exchange between the ice surface and the atmosphere above it is very inhomogeneous, and this has a great influence on local air movements. This is yet another aspect that influences the glacier’s mass balance.” Moreover, the ice masses are usually surrounded by a cold layer of air, which counteracts warm currents near the surface and slows down faster melting. The modelling could also provide information on how much mass a glacier can lose without losing this “protective shield”.
Just as the measurement data from the laser scanner improve the glacier models, the findings from the models should provide information about sources of error and inaccuracy in the measurements – thus leading to further improvements. Upcoming publications in the context of the project, which was recently extended by one year, will provide information about this improved accuracy of measurements of snowdrift. In addition, Goger is also working on a first winter case study showing a simulation of snowdrift based on the measurement data. According to Goger, researchers in other regions of the world could thereby profit from these computational approaches: “If the models work well with the Hintereisferner, other colleagues, in Canada, for example, who have to deal with much larger ice masses, could also try them out – and optimise them for their own areas of investigation.”
Goger B., Stiperski I., Nicholson L., Sauter T.: Large-eddy Simulations of the Atmospheric Boundary Layer over an Alpine Glacier: Impact of Synoptic Flow Direction and Governing Processes, 2021 (Preprint)
Goger B., Stiperski I. and the SCHISM Team: The Impact of Large-scale Flow Direction on the Formation of a Glacier Boundary Layer: Two LES Case Studies, EGU General Assembly 2021
Voordendag AB, Goger B., Klug C., Prinz R., Rutzinger M., Kaser G.: Automated and permanent long-range terrestrial laser scanning in a high mointain environment: setup and first results, International Society for Photogrammetry and Remote Sensing ISPRS Vol. 2 2021