In addition to melting, ice flows from glaciers and ice sheets into the oceans; therefore, accelerating flow has the potential to largely influence sea-level rise. In contrast to its high importance, there remain considerable challenges for better understanding ice acceleration and hence for predicting future glacier response to climate change. Instead of focusing on a single technique, MAMMAMIA aims for overcoming these challenges by using multiple methods, including different field measurements, satellite remote sensing and numerical modeling. To this end, the project will collect a comprehensive dataset of glacier flow, using multiple methods, mutually complementing each other. While current satellite remote sensing provides spatial velocity fields at the glacier surface, these come at a relatively low temporal resolution of 1-2 weeks. In contrast, tracking surface velocities using GPS allows temporal resolutions of 1 day and below, but only for individual points. Glacier-seismology makes use of geophones that continuously scan the glacier for signals generated by glacier flow such as sliding or crevassing. These will be complemented by measurements of surface melting, water pressure at the glacier base, ice temperature and thickness. Computational methods will contribute to complete the picture needed to get an improved insight into the controls of ice acceleration.
The COVID-19 pandemic disturbed the project schedule and field activities planned for 2020 had to be postponed. With some adaptations to overcome limitations due to travel restrictions, we have been able to conduct these activities in 2021 and instrumented the Kongsvegen glacier in Svalbard. Two surface arrays of geophones continuously operate on the glacier to detect and locate seismicity, one in the upper and one in the lower part of the glacier. Continuous velocity measurements by GPS are conducted at several locations along the centerline. In addition, two boreholes have been drilled to provide access to the glacier base and have been instrumented with geophones and sensors to measure water pressure, sediment strength and ice temperature profiles. A field visit in fall confirmed the overall good performance of the instrumentation, retrieved data from the summer period and conducted maintenance work to ensure that the measurement system is ready for the winter period. Project personnel has been recruited and data processing work has been started.
Transfer of land-based ice masses into the oceans is a strong contributor to ongoing sea level rise; both, melt-water runoff, as well as ice discharge into the oceans are expected to increase with continued climate warming. Dynamic instabilities allow for larger, more rapid ice mass loss than surface melt, and Earth history has experienced several episodes of rapid ice sheet decay with severe impact on sea level, climate and ecology. There is considerable variability in the way glaciers respond to climate change; some glaciers become dynamically inactive and exhibit moderate rates of mass loss, whereas others feature dynamic instabilities and discharge large amounts of ice. For instance, the drastic acceleration of a single basin of the Austfonna ice capsince 2012 doubled sea-level contribution from the entire
Svalbard archipelago. The discovery of widespread acceleration of the Greenland Ice Sheet in the early 2000s sparked intense research activity on the hydraulic lubrication of glacier beds. Since then, a wealth of new observations in unprecedented quality, detail and coverage suggest the existence of additional, hitherto neglected, cryo-hydrological feedbacks. This incomplete process understanding gives rise to considerable uncertainties about future evolution of sea level, as acknowledged by the Intergovernmental Panel on Climate Change. MAMMAMIA addresses these crucial knowledge gaps to ultimately facilitate improved assessments of the dynamic stability of polar ice masses.
The project will monitor the subglacial sliding motion of arctic, poly-thermal glaciers and investigate the role of meltwater supply to control these processes. Fusing dedicated field experiments, remote sensing and modelling, will not only advance process parameterization, but also foster multidisciplinary contributions in theory, methodology and outreach, acting as a catalyst for research innovation.