Permafrost and related thermo-hydro-mechanical processes are thought to
influence high alpine rock wall stability, but a lack of field measurements
means that the characteristics and processes of rock wall permafrost are
poorly understood. To help remedy this situation, in 2005 work began to
install a monitoring system at the Aiguille du Midi (3842 m a.s.l). This
paper presents temperature records from nine surface sensors (eight years of
records) and three 10 m deep boreholes (4 years of records), installed at
locations with different surface and bedrock characteristics. In line with
previous studies, our temperature data analyses showed that:
micro-meteorology controls the surface temperature, active layer thicknesses
are directly related to aspect and ranged from
The last few decades have seen an increase in rockfall activity from steep, high-altitude rock walls in the Mont Blanc Massif (Western European Alps) (Ravanel and Deline, 2010; Deline et al., 2012). Several studies of recent rock avalanches and rockfalls in mid-latitude alpine ranges have ascribed such increases to climate-related permafrost degradation (Deline, 2001; Gruber et al., 2004a; Huggel et al., 2005, 2008; Fischer et al., 2006; Allen et al., 2009; Ravanel et al., 2010, 2012; Deline et al., 2011). Rockfall magnitude and frequency are thought to be linked to the timing and depth of permafrost degradation, which can range from a seasonal deepening of the active layer to long-term, deep-seated warming in response to a climate signal (Gruber and Haeberli, 2007). Local warming of cold permafrost may be induced by advection and the related erosion of cleft ice (Hasler et al., 2011b), which can lead to unexpected bedrock failures. As Krautblatter et al. (2011) noted, before being able to predict permafrost-related hazards, it is necessary to develop a better understanding of the thermo-hydro-mechanical processes involved, which means collecting rock temperature measurements and developing modelling strategies.
Measurement strategies and numerical experiments have been used to
investigate the thermal conditions and characteristics of near-vertical and
virtually snow-free alpine rock walls that are directly coupled with the
atmosphere (Gruber et al., 2003, 2004b; Noetzli et al., 2007). These studies
have shown the domination of topographical controls on steep bedrock
permafrost distribution, with a typical surface temperature difference of
7–8
As part of our research into geomorphic activity in the Mont Blanc Massif, in 2005 we started a long-term permafrost-monitoring programme at the Aiguille du Midi (AdM), currently the highest instrumented bedrock permafrost site in the European Alps (3842 m a.s.l). This monitoring program was designed to characterize and determine the thermal state of the permafrost and active layer, and to collect temperature data under variable snow-cover and structural conditions that could be used to calibrate and validate high-resolution numerical experiments on permafrost thermal processes.
In this paper we describe the monitoring programme at the AdM, and present
temperature data from nine surface mini-loggers and three 10 m deep
boreholes. Due to the morphology of the AdM, the monitoring network is
concentrated in a very small area; however, the data obtained allowed us to
address the following questions:
How much of the surface temperature variability over this small area is
due to topography and snow cover? How much of the variability in the active layer is due to the topography
of the steep rock walls? What are the thermal effects of snow and fractures on sub-surface
temperatures at the AdM?
We used 8 years of surface records and 4 years of borehole to analyse
seasonal and annual variations in temperature patterns, in the active layer,
and in the permafrost thermal regime. We discuss our results in the light of
previous research and provide new empirical evidence for the effects of snow
and fractures on permafrost in steep rock walls.
Location of the Mont Blanc Massif and the Aiguille du Midi (red triangle) (modified from Le Roy, 2012).
The AdM lies on the NW side of the Mont Blanc Massif (Fig. 1). Its summit
(45.88
We chose the AdM as a monitoring site for the following scientific and logistical reasons: (i) permafrost is extremely likely due to the AdM's high altitude and the presence of cold-based hanging glaciers on its north face; (ii) the morphology of the peak offers a range of aspects, slope angles and fracture densities that are representative of many other rock walls in the massif; (iii) the easy access by cable car from Chamonix and the availability of services (e.g. electricity) at the summit station. Monitoring equipment was installed as part of the PERMAdataROC (2006–2008) and PermaNET (2008–2011) projects, funded by the European Union and run jointly by EDYTEM Lab (France), ARPA VdA (Italy), and the Universities of Zurich (Switzerland), Bonn and Munich (Germany). As such, it complements other rock wall observation sites – for example, those within the Swiss Permafrost Monitoring Network (PERMOS).
Data from the monitoring equipment on the AdM were completed by data from ARPA VdA's weather stations, which measured air temperature and relative humidity, incoming and outgoing shortwave and longwave solar radiation, wind speed, and wind direction on the south and north faces between 2006 and 2010. Electrical Resistivity Tomography (ERT) and Induced Polarization (IP) have been measured since 2008 in conjunction with the universities of Bonn and Munich. High-resolution (cm scale) triangulated irregular networks (TIN) of rock walls and galleries of the AdM were obtained from terrestrial laser scanning. In July 2012, six crack-meters equipped with wireless sensors were installed in major fractures in the Piton Central and Piton Nord in order to complement existing studies of cleft dilatations and shearing movements in rock wall permafrost, to check the stability of the AdM and to test an early warning system. Finally, two GPR surveys were performed along vertical transects in 2013 and 2014. Not all of these data were used in the present study but they will contribute to future research.
The Aiguille du Midi with snow camera, air temperature, rock surface temperature and borehole logger locations. Pictures: S. Gruber (top left and right, bottom left); P. Deline (bottom right).
The present study is based on rock surface temperatures taken at the top of
the AdM (between 3815 and 3825 m a.s.l.; Fig. 2) since 2005 by a network of
mini-loggers (GeoPrecision PT1000 sensors, accuracy
Instrument positions. BH: borehole thermistor chains, X1 and X2: rock surface temperature loggers, AT: air temperature. Estimated snow accumulation: from automatic cameras and probes for BH_S and BH_E (winter 2012 and 2013), from field observation for S3 and BH_N.
In September 2009, three boreholes were drilled in the lower section of the Piton Central, at between 3738 and 3753 m a.s.l.
In order to minimize possible thermal disturbances caused by air ventilation
in the galleries and heating from staff rooms, the boreholes were drilled
several tens of metres below the galleries running through the AdM. The
criteria used to decide the exact location of each borehole were the aspect,
fracturing, roughness and angle of the rock wall (Fig. 2). Each borehole
was drilled perpendicular to the rock surface and to a depth of 11 m.
Borehole depths were constrained by the drilling equipment and the funding
available. The boreholes on the northeast (BH_E) and south
(BH_S) faces were drilled in fractured rock walls that slope
at 65 and 55
The boreholes were drilled between 14 and 27 September 2009
by a team of five people (two mountain guides, plus three
members of the EDYTEM Lab) who had to contend with very variable weather and
challenging logistics. For each borehole it was necessary to: (i) install a
safety line for the workers, (ii) set up a rope system to carry the
equipment from the galleries to the drill site, (iii) install a work
platform for the three drillers, (iv) anchor a base on which to fix a rack
way, (v) drill the hole using a 380 V Weka Diamond-Core DK 22 electric
drill, (vi) insert into the hole a polyethylene PE100 tube (outer diameter:
40 mm; inner diameter: 29 mm) sealed at its bottom, and (vii) remove the work
platform. In addition to the difficult environment and harsh weather, the
drilling work was complicated by the heterogeneity and hardness of the
granite, which took a heavy toll on the equipment (11 diamond heads worn out
or broken, a dozen steel tubes damaged, and a motor broken). At first we
tried to drill 46 mm diameter boreholes but we had to increase the diameter
to 66 mm so we could use a more robust pipe string. Cooling required
1 to 3 m
Borehole positions and components. Left: horizontal cross-section through the AdM's Piton Central. Borehole positions are marked in red. Right: 10 m length, 15-node thermistor chain installed in the boreholes.
The three boreholes were fitted with 10 m length Stump thermistor chains, each
with 15 nodes (YSI 44031 sensors, accuracy
In order to aid interpretation of the rock temperature data, we collated air temperature data (AT, Table 1) collected by Météo France at a station 3 m above the top of the Piton Central (3845 m a.s.l.) since 2007. Data prior to 2007 (1989–2006) are very fragmented due to insufficient equipment maintenance and are not used in this study.
Two automatic cameras have taken six pictures a day of the south and
northeast borehole sites since January 2012. In addition, five graduated
stakes were placed around each borehole in order to evaluate the spatial
variability of snow accumulation from the photographs. Visual analysis of
the photos taken during the winters of 2012 and 2013 showed a thick
spatially homogeneous snow cover (
Data availability after gap filling. Wi: December, January,
February; Sp: March, April, May; Su: June, July, August; Fa: September,
October, November. Red
sections indicate where gaps
The borehole time series were all continuous except for short periods for
BH_S, as this logger was removed from September 2012 to
January 2013 and from October 2013 to January 2014 to prevent it being
damaged by engineering work close to the borehole. Gaps in the 0.3 m
temperature and AT time series were filled in so we could calculate seasonal
and annual means (see Table 2). First, we calculated daily means from rock
temperature time series for days with complete records. Then, we filled
short gaps (
Smith and Riseborough (2002) defined Surface Offset (SO) as the difference between local air temperature and ground surface temperature. SO is a parameter in the TTOP model (Temperature at the Top of Permafrost, Smith and Riseborough, 1996), originally developed to define the functional relation between air and ground temperatures in polar lowlands and later applied to high-latitude mountainous terrain (Juliussen and Humlum, 2007). SO can be used to quantify the overall effect of ground cover and ground surface parameters on the surface energy balance.
Annual and seasonal surface offsets calculated from sensors at 0.3 m depth. ASOs are shown for all the available years. SSOs are the mean values for the available seasons for each logger listed in Table 2.
We calculated annual SOs (ASO), using mean annual air temperature (MAAT) and
mean annual ground surface temperature (MAGST), and seasonal SOs (SSO) from
seasonal means for winter (December to February), spring (from March to
May), summer (from June to August) and fall (from September to November),
using time series measured at depths of 0.3 m (boreholes and E2, S2, W2, N2)
and 0.1 m (E1, S1, W1, N1) – points we considered representative of surface
conditions. We applied a standard lapse rate of 0.006
Daily temperature records at 0.3 m depth for snow-covered sensors for the 2010–2011 and 2011–2012 hydrological years.
Maximum and minimum ASOs were 9.3
From 2011 to 2012, the changes in ASO at snow-covered and shady sensors such
as BH_E and BH_N were greater
(
Daily temperature curves for the snow-covered sensors are smoothed compared
to air temperature oscillation during cold periods (Fig. 5). The S3 and
BH_S temperature curves were strongly smoothed from
mid-November 2010 to January (BH_S) or April 2011 (gap for
S3), and from early December 2011 to mid-May 2012. Both sensors recorded a
period of almost constant 0
Normally on steep, snow-free bedrock in the high mountains, the MAGST is
higher than MAAT, mainly because of direct solar radiation (Gruber et al.,
2004b) but also due to a contribution from reflected solar radiation from
large, bright glacier surfaces below measurement points (PERMOS, 2013). In
the European Alps, the ASO can be up to 10
The differences in ASOs between snow-covered and snow-free sensors on
similar aspects show that snow has a substantial effect on the annual energy
balance. According to empirical and numerical studies (Hanson and Hoelzle,
2004; Luetschg et al., 2008), snow cover must be at least 0.6–0.8 m thick to
insulate the rock surface from the air temperature, but snow cover on steep
rock walls is usually thinner than this insulating threshold (Gruber and
Haeberli, 2009). The differences between BH_N and
BH_E in terms of ASOs and SSOs can probably be ascribed to
variations in mean snow cover thickness (Table 1), and demonstrate that the
insulating effect of snow can occur locally also in steep rock walls. On the
north face, ASOs were higher at snow-covered sensors (BH_N)
than at snow-free sensors (N1 and N2), showing that thermo-insulation by
snow significantly increases the MAGST. On the south face, ASOs were lower
at the snow-covered sensors (BH_S and S3) than at the
snow-free sensors (S1 and S2), indicating that snow lowers the MAGST. This
reduced warming effect could result from the combination of (i) thin snow
cover with negligible thermo-insulation, (ii) a higher surface albedo, and (iii)
melt energy consumption (Harris and Corte, 1992; Pogliotti, 2011). The
latter two factors seem to be prevalent at the AdM because snow cover on the
south face is often greater than 1 m thick during winter (Sect. 3.2) leading
to a marked smoothing of daily temperature oscillations (Fig. 5). These
results extend previous studies on thin snow accumulations (Hasler et al.,
2011a). The importance of this reduced warming effect on sunny faces is
probably reinforced by the fact that snow is present for much of the year at
such altitudes, as suggested by (i) the high fall SSOs (early snow
accumulation) for snow-covered sensors, (ii) their low summer SSOs, and
(iii) by the nearly constant temperature close to 0
Different interannual changes were recorded at snow-covered and snow-free sensors. The PERMOS study (2013) has reported analogous differences in interannual variability between rock walls and gentle snow-covered terrain. Interannual changes at the snow-free sensors were mainly related to differences in insolation due to cloud cover. It may be that differences in interannual changes from one aspect to another are also due to variations in cloud formation from year to year. Energy balance models have shown that convective cloud formation can cause differences in the spatial distribution of MAGST over a single rock peak (Noetzli et al., 2007). On shady faces, the effect of solar radiation control is greatly reduced and snow cover may be the most important factor affecting interannual changes. Consequently, the temperature at a snow-covered sensor can increase from one year to the next if snow insulation from the atmospheric temperature increases, while the temperature at a snow-free sensor may drop due to reduced insolation. In the case of sun-exposed and snow-covered sensors, such as S3, the balance between warming and cooling effects leads to smaller interannual ASO changes than at sensors in shadier locations, where temperature are mostly controlled by the warming effect of snow insulation. Thus, the influence of snow cover on the surface temperature of high-altitude rock walls is a due to a combination of topography, snow depth and micro-meteorology.
Daily temperature records in the AdM boreholes from December 2009 to December 2013.
Four years of data from the three boreholes allowed us to describe daily
temperature patterns (Fig. 6), mean annual temperature–depth (
Mean
Active layer thickness (ALT) varied with aspect, with means of ca. 3 m at BH_E, 5.5 m at BH_S, and 2.2 m at BH_N (Fig. 6). Interannual variability during the monitoring period was ca. 0.7 m for each borehole (Table 3). Maximum ALTs occurred in 2012 at BH_N (2.5 m deep) and in 2013 at BH_E (3.4 m deep). At BH_S, data are missing for 2012 and 2013, but 2010 and 2011 data show a maximum ALT in 2011 of 5.9 m. The length of the thawing period, marked by continuous positive temperatures at the uppermost thermistor, also varied according to aspect. It was longest at BH_S, starting in June (April in 2011), but with isolated thawing days already in March (e.g. in 2012). In general, the surface at BH_S refroze in October, but total refreezing of the active layer did not occur until December in 2010 and 2011. The 2011–2012 freezing period was particularly mild and short (3–4 months) at BH_S. This pattern was not as marked at BH_E, which even recorded its lowest surface temperature in 2011–2012. BH_N had the longest freezing periods because temperatures in the rock sub-surface remained positive only from June to October. In 2011, thawing did not start until August. BH_E had the most balanced thawing and freezing periods (ca. 6 months each).
Borehole and air temperature records.
ALT: active layer thickness.
MART
The timing of maximum ALT depended on aspect and year (Table 3). In 2010 and
2011, maximum ALT occurred earliest at BH_E, even though the
active layer was thicker at BH_E than at BH_N.
In 2012 and 2013, BH_N was the first site to reach maximum
ALT. In 2010, maximum ALT at BH_S occurred very late, 3
months after BH_E. Although the BH_S active
layer had mostly thawed by mid-July, thawing continued steadily until the
end of October. Maximum ALT always occurred later at BH_S
than at the other boreholes, but the lowering of the 0
Annual temperature–depth
The zero annual amplitude depth is
The minimum and mean annual
The coexistence of warm and cold permafrost, and the opposite temperature gradients at BH_S and BH_N, probably due to lateral heat fluxes, are in accordance with the results of numerical simulations (Noetzli et al., 2007).
In terms of the permafrost thermal regime, the values recorded at
BH_N were below
The spatial and temporal variability of ALT is consistent with values
reported for Swiss boreholes in bedrock (PERMOS, 2013). For example, the
thickness and timing of the ALT in BH_E are similar to those
recorded at the Matterhorn–Hörnligrat site (3295 m a.s.l, vertical
borehole on a crest), with values ranging from 2.89 to 3.66 m between 2008
and 2010, and with maximum ALT occurring between early September and early
October. Early studies considered that in bedrock slopes, changes in ALT are
strongly controlled by summer air temperature, as indicated by the ALT at
Schilthorn (2909 m a.s.l) which was twice as thick as usual (from 4–5 m to
The different patterns of ALT variability at the three AdM boreholes (Table 3) suggest that the air temperature is not the only controlling factor. The relatively mild and short 2011–2012 freezing period at BH_S may have been due to snow insulation, as suggested by the subsequent period of constant temperature from the surface to a depth of 3 m (Fig. 6). This isothermal period coincided with the zero-curtain effect observed at the surface temperature from April to mid-May 2012 (see Sects. 5.2 and 5.3, Fig. 5). As reported by Hoelzle et al. (1999), thick, long-lasting snow cover reduces both freezing of the active layer by insulating it from low temperatures and thawing of the active layer by late snow melting. Such an effect on the active layer freeze–thaw cycles has been reported by studies in gentle mountain terrains, but has not been observed in steep bedrock permafrost (Gruber et al., 2004a). A comparison of temperature variations at BH_E and BH_N clearly shows the effect of snow insulation (Fig. 5). Most notably, winter surface temperatures are always warmer and less variable at BH_N than at BH_E (Fig. 5) and at depth (Fig. 7b). Snow appears to have a warming effect at depths of up to 1.4 m. In terms of ALT, the different trends between BH_E and BH_N during the period 2011–2013 (Table 3) may be due to the effect of long-lasting snow cover at BH_N modifying its response to the climate signal. Conversely, the reduced ALT at BH_E in 2011, in contrast with BH_S and BH_N, may be the result of variations in the effect of summer snow fall on these different faces. Unfortunately, the cameras and snow stakes that would have allowed us to check this hypothesis were not installed in 2012 (Sect. 3.2). Further studies are needed to verify this hypothesis.
Seasonal
According to a modelling study, the interannual variability of ALT is
greater on sun-exposed faces, as they respond as much to change in air
temperature as to changes in solar radiation (Gruber et al., 2004a). However,
our data did not conform to this prediction, as the change in ALT at
BH_S was similar to the ALTs at the shadier BH_E and BH_N. Furthermore, BH_S experienced the
smallest interannual changes at 10 m depth, and the shape of its
Interannual changes at BH_E and BH_N followed
variations in MAAT all along their profiles (except for BH_N
in 2011) suggesting that latent heat consumption did not occur (Fig. 7a).
From 2010 to 2011 the BH_N
The high altitude, morphology and accessibility of AdM make it an
exceptional site for investigating permafrost in steep rock walls. A
monitoring network installed on the AdM to investigate the thermal effects
of topography, snow cover and fractures on permafrost provided 8 years
of rock surface temperature and 4 years of borehole temperature data. The
results of our analyses of this new data set supported the findings of
previous field studies and a number of numerical experiments:
The thermal characteristics of the AdM's rock walls are typical of steep
bedrock permafrost. The spatial variability of surface temperature, active layer
thickness and timing, and the permafrost thermal regime are mainly controlled by topography. Borehole temperature data confirm the characteristics of the sub-surface
thermal regime predicted by numerical experiments, in particular the coexistence
within a single rock peak of warm and cold permafrost, which generates
lateral heat fluxes from warm to cold faces. MAGST around a single rock peak is controlled by micro-meteorological
parameters (variable cloud formation from year-to-year) when the rock face is
snow free, and by local accumulations where there is snow on the face.
Snow-free areas and snow-covered areas can show opposite trends. Surface temperature data confirm that thin (not-insulating) snow cover
can lower the surface temperature due to the low snow surface albedo. Sensors with thick snow cover showed evidence of a similar thermo-insulation
effect to that found on gentle mountain slopes, with smoothing of daily temperatures
in winter, a melting period marked by constant surface temperature of around
0 Thick snow accumulations warm MAGST of shady areas and increases interannual
changes compared with sunny areas which are cooled by snow blocking solar radiation,
and where interannual changes are reduced by the balance between the opposite
effects of thermo-insulation and strong albedo. Open fractures have a strong, localized cooling effect, possibly due to air
ventilation within the fracture. This cooling effect is greater in winter and the
heat sink mainly affects the 3–4 m below the fracture.
Our results also extended the results of previous studies:
The thermal characteristics of the AdM illustrate the complexity of the processes controlling the thermal regime of shallow layers in rock wall permafrost. Modelling these processes represents a major challenge but the data presented here provide a step towards achieving this goal. Studies into the controlling effect of snow cover are needed in order to determine the impact of thick accumulations and summer snow fall on ALT and permafrost changes. The current research project has already collected a large amount of data, including picture showing the evolution of the south and northeast faces of the AdM, snow-stake measurements, and borehole records. Further analyses of these data would help improve understanding of rockfall activity. Research into latent heat consumption in compact bedrock may also provide insight into ALT thickness and timing on some snow-covered rock walls, and into permafrost evolution over short timescales. The BH_N fracture could be used to investigate non-conductive heat transfers, for example by developing a heat conduction scheme. Ground-penetrating radar measurements of the northwest face, including BH_N, offer a detailed picture of the bedrock discontinuities and provide useful additional data for developing a heat flow model integrating bedrock structure. The combined use of crack-meters, air temperature measurement, and borehole data provides a promising avenue for developing understanding of the thermal and mechanical factors affecting rock wall instabilities.
The data set presented here was used for evaluation of statistical and numerical models designed to map the distribution of permafrost in the Mont Blanc Massif (Magnin et al., 2015) and to predict the distribution and evolution of the temperature field at the AdM over the next century (Noetzli et al., 2015). The statistical model will be used to determine bedrock temperatures and the related permafrost thermal regime at rockfall locations in order to analyse the relationship between bedrock temperature and rock failures.
We would like to thank S. Gruber, U. Morra di Cella, E. Cremonese and
E. Malet, for their help with equipment installation and data acquisition at
the Aiguille du Midi. The Chamonix