The TEMPS project: The evolution of mountain permafrost in Switzerland

Transcription

1 The TEMPS project: The evolution of mountain permafrost in Switzerland Christian Hauck, Reynald Delaloye, Isabelle Gärtner-Roer, Andreas Hasler, Christin Hilbich, Martin Hoelzle, Robert Kenner, Sven Kotlarski, Christophe Lambiel, Rachel Lüthi, Antoine Marmy, Johann Müller, Jeannette Noetzli, Marcia Phillips, Jan Rajczak, Nadine Salzmann, Michael Schaepman, Christoph Schär, Benno Staub, Ingo Völksch Thanks to: Swiss National Science Foundation and PERMOS (FOEN) and all colleagues within the TEMPS project

2 Outline 1. What is TEMPS? 2. Methods & field sites 3. Example I: Permafrost evolution scenarios o Current degradation, causes and future evolution o Schilthorn, Berner Oberland 4. Example II: Drivers of rock glacier velocity o Geomorphological setting, GST, ice content, infiltration etc o Rock glaciers Murtèl, Becs-de-Bosson (Val de Rechy) 5. Example III: Effect of coarse blocky surface layer o Vertical convection and 2D air ventilation (chimney effect) o Talus slope Lapires, Valais 6. Conclusions 2

3 S U B - P R O J E C T 1 WHAT IS TEMPS? The overall objective of TEMPS is an improved understanding of the vulnerability of mountain regions to permafrost changes and to assess the current and future impacts on the Swiss Alps. TEMPS consists of 4 strongly collaborating and interrelated subprojects, with a specific focus on the determination of the current state, and on the dominant processes influencing the future evolution of permafrost in the Swiss Alps. R E S E A R C H T O P I C S MODEL-BASED ANALYSIS OBSERVATION- BASED ANALYSIS PERMAFROST PROCESSES EVOLUTION OF PERMAFROST A atmosphere ground-atmosphere exchange climate scenarios B subsurface processes active layer dynamics, degradation site-specific impacts C geometry change creep, subsidence potential instabilities D permafrost energy and mass transfer permafrost scenarios projects synergies 3

4 TEMPS Sub-projects Regional Climate Model analysis for Alpine permafrost research S. Kotlarski, J. Rajczak, N. Salzmann, C. Schär I *ETHZ, UNIFR RCM evaluation at the local scale; development of a downscaling/bias correction interface between RCM and local subsurface model; RCM scenario development Joint interpretation of meteorological, thermal and geophysical properties R. Delaloye, C Hilbich, C. Lambiel, J. Noetzli, B. Staub, I. Völksch, A. Hasler *UNIFR, UZH, UNIL Ice/water content quantification; response of geophysical/thermal properties to atmospheric changes; relation between ice/water content and movement Geometry changes and permafrost creep processes I. Gärtner-Roer, J. Müller, M. Phillips, R. Kenner, R. Lüthi, M. Schaepman I *UZH, SLF quantification of kinematics; rheological model improvement; determination of causes for observed movement and geometry changes Permafrost modelling of the sensitivity to climatic changes C. Hauck, C. Hoelzle, A. Marmy I *UNIFR permafrost model improvement; permafrost scenario development and analysis of sensitivity; uncertainty assessment of whole model chain *lead institute 4

5 2 METHODS & FIELD SITES a. GCM/RCM scenarios To analyse the climate evolution To generate consistent meteorological time series for the impact models c. GST analysis To analyse and monitor the spatial heterogeneity To get the upper boundary condition To analyse the snow conditions e. Kinematics To visualise and monitor the slope movement To analyse the 3D displacement b. Permafrost modelling To analyse the permafrost evolution To identify the dominant processes To analyse the permafrost degradation potential of specific field sites d. Geophysical techniques To analyse and monitor the ice and water content To visualise the subsurface (2D) To estimate the sediment thickness that can be mobilised f. Borehole temperature analysis For evidence of permafrost thaw To validate & calibrate the various models 5

6 Field sites PERMOS (Permafrost Monitoring Switzerland) 6

7 Models & simulations used within TEMPS a. Climate model data 13 different GCM/RCM chains for the A1B scenario (ENSEMBLES) - CH2011 data set b. 1D Subsurface model COUP Heat and mass transfer model Site-specific permafrost simulations for 6 TEMPS/PERMOS sites talks Rajczak/Kotlarski talk Marmy c. Geophysical 4-phase model Based on electric and seismic data 2-dimensional simulation of ice and water content changes talk Hilbich, poster Python/Mewes e. Air flow model for talus slopes Using Geostudio2012 To quantify the cooling effect as function of e.g. porosity Poster Wicky d. Rock glacier flow model Based on glaciological flow law Conservation of mass for surface evolution talk Müller f. Sediment transfer model Based on geomorphological mapping and digital elevation models talk Müller 7

8 3 EXAMPLE I: Permafrost evolution scenarios One of the main test sites Schilthorn (2970m), Berner Oberland: Evidence for permafrost degradation through borehole/geophysics Continuous ERT monitoring - Energy balance measurements Repeated seismic surveys - Borehole temperatures (-100m) Quantification of ice content changes (4PM) Numerical modelling (COUP) of future evolution Active layer thickening Schilthorn during the past 15 years Scientific questions: Causes for the strong degradation? Will this trend be continuing? 8

9 SCHILTHORN, 2970m, Berner Oberland Site and measurement setup E Schilthorn summit (2970 m asl) SCV E30 ERT Monitoring horizontal profile SCH: 49 electrodes (30 until 07/2012) 2 m spacing since 1999 vertical profile SCV: 44 electrodes 4 m spacing since 2006 W E44 Additional measurements and sensors 3 boreholes (14/100/100m deep) 1 meteo station (snow height, air temp., radiation, etc.) 5 soil moisture sensors (12 60 cm deep) Refraction seismic monitoring profile GPR profiles etc. SCH E1 meteo station 5 soil moisture sensors BH1 ca. 100 m E1 SCV BH2 BH3 E49

10 Causes for degradation & future evolution Low ice content and air temperature increase Schilthorn has low ice content and warm permafrost temperatures Schilthorn unsaturated (40-50%) Stockhorn unsaturated (70-80%) (Python 2015) Based on geophysical measurements and 4-phase model calculations 10

11 Causes for degradation & future evolution Low ice content and air temperature increase Consistent climate time series (past-future) Quantile mapping see talk J. Rajczak et al. 11

12 Causes for degradation & future evolution Temperature [ C] Temperature Sum [K] Low ice content and air temperature increase Schilthorn Mean Annual Temperature Schilthorn Freezing Degree Day Sum Year Modelrange [14 Regional Climate Models] Best Estimate Best Estimate [20 y. running mean] Upper & lower Modelrange [20 y. running mean] Observations Year Quantile mapping see talk J. Rajczak et al. 12

13 Causes for degradation & future evolution Low ice content and air temperature increase Simulated permafrost evolution 13

14 4 EXAMPLE II: KINEMATICS ROCK GLACIER Data from Terrestrial Laser Scanning (TLS) Rock glacier Murtèl Vertical Movements Climate change and rock glaciers: velocity change and subsidence! talk R. Kenner et al. 14

15 Drivers of rock glacier velocity Example Becs-de-Bosson rock glacier (Réchy, VS) (mean of 5 GPS monitoring points around logger REC_S003) Thermal regime at depth is the main factor for changing displacement rates Snow melt Infiltration may induce additional heat to larger depths talk B. Staub et al. 15

16 Drivers of rock glacier velocity Example Becs-de-Bosson rock glacier (Réchy, VS) (mean of 5 GPS monitoring points around logger REC_S003) Thermal regime at depth is the main factor for changing displacement rates Snow melt Infiltration may induce additional heat to larger depths talk B. Staub et al. 16

17 Rock glacier processes Infiltration heat input Measured data Synthetical case studies Geophysical Survey Sediment transport Synthetical reference model Poster B. Mewes et al. Talk J. Müller et al.

18 Ice content in rock glaciers : effect on future evolution? Different ice-saturations detectable for different landforms: Large intra-site and inter-site variablity! e.g. in different rock glaciers maximum ice content may vary between ~ 10-45% relative to the respective porosity, this mostly corresponds to almost saturated or (super-)saturated conditions DIRRU UNSATURATED (90%) MURTÈL SATURATED (100%) 40% 40% RÉCHY UNSATURATED (90%) MURAGL UNSATURATED (90%) 25% 45% (Hauck et al. 2011) LAC DES VAUX UNSATURATED (90%) 15% 18

19 Ice content in rock glaciers : effect on future evolution? Different ice-saturations detectable for different landforms: Large intra-site and inter-site variablity! e.g. in different rock glaciers maximum ice content may vary between ~ 10-45% relative to the respective porosity, this mostly corresponds to almost saturated or (super-)saturated conditions Schilthorn (2900 m asl) Rock glacier Murtèl (2600 m asl) [Scherler et al., JGR 2013] 19

20 5 EXAMPLE III: Effect of coarse blocky surface layer Permafrost talus slopes with (locally) high ice content Talus slope Lapires (LAV) unsaturated (80%) 30 Two effects of coarse blocky layer: (1) Vertical convection (2) 2D air ventilation (chimney effect) 20

21 Rock glaciers (convection) versus Talus slopes (ventilation) without convection with convection [Scherler et al. 2014] COUP simulation of thermal regime rock glacier Murtèl 21

22 Rock glaciers (convection) versus Talus slopes (ventilation) without ventilation with ventilation [Wicky 2015] Talus slope simulation with Geostudio see Poster J. Wicky 22

23 6 CONCLUSION 1. The evolution of mountain permafrost On the long term, air temperature change (due to climatic changes) has the largest impact on mountain permafrost due to its continuous increase Therefore the overall evolution is a degradation! 2. Influencing factors - snow Variability in begin/end of snow cover is responsible for high variance in permafrost time series 3. Influencing factors substrate, topoclimate The substrate (incl. also the ice content) plays the important role regarding the time scale of degradation ( damping) Radiation depends on the topoclimatic setting (constant with time), its temporal change is reflected also in the air temperature change 4. Current ( ) situation: much warmer than during the rest of the measurement period an extreme event (such as 2003) would have a much larger impact than in

24 SINERGIA project funded by SNF/FNS The Evolution of Mountain Permafrost in Switzerland (TEMPS) Universities of Fribourg, Lausanne & Zürich, ETH Zürich, SLF Davos Thanks for your attention