The evolution of mountain permafrost in the context of climate change:: towards a comprehensive analysis of permafrost monitoring data from the Swiss Alps

• Main Authors: Staub, Benno, Delaloye, Reynald
• Language: English
• Published: 2016
• Subjects: permafrost
• Online Access: http://doc.rero.ch/record/261348/files/StaubB.pdf

In the Swiss Alps, permafrost occurs discontinuously and commonly has a temperature close to 0 °C. A reduction of Alpine permafrost area and volume is expected in the course of atmospheric warming, but to date, limited evidence is available for Alpine permafrost degradation. Permafrost warming or thaw is accompanied by structural changes in the subsurface, which endanger infrastructure by increasing kinematic activity or slope instability. Changes in the permafrost impact sediment transport to the valley bottom as well as gravitational natural hazards such as rock falls, landslides or debris flows. For these reasons, the quantitative analysis of past and potential future changes in the Alpine permafrost is of great interest and importance. The objective of this PhD project was to investigate observational data from the Swiss Permafrost Monitoring Network PERMOS using an interdisciplinary approach and to develop new methods for the homogenisation and quantitative analysis of long-term monitoring data. The main focus was on assessing changes in the energy fluxes at the ground surface as a function of the snow cover, as well as on evaluating permafrost response to different meteorological conditions and events. This PhD project was part of the research project The Evolution of Mountain Permafrost in Switzerland (TEMPS, 2011-2015), which used combined observational and model-based approaches and aimed at improving the consistency and completeness of permafrost monitoring data. One achievement of this PhD thesis consists of the development of data processing algorithms for filling data gaps in temperature time series and the quantification of resulting uncertainties. Moreover, algorithms for the approximation of the thermal insulation effect of the snow cover based on ground surface temperature (GST) data were developed. This was of particular importance because snow information is usually not available for the points of interest. Furthermore, possibilities for estimating temperature variations at depth based on GST ...