Warming permafrost and active layer variability at Cime Bianche, Western European Alps

The objective of this paper is to provide a first synthesis on the state and recent evolution of permafrost at the monitoring site of Cime Bianche (3100 m a.s.l.) on the Italian side of the Western Alps. The analysis is based on 7 years of ground temperature observations in two boreholes and seven surface points. The analysis aims to quantify the spatial and temporal variability of ground surface temperature in relation to snow cover, the small-scale spatial variability of the active layer thickness and current temperature trends in deep permafrost.Results show that the heterogeneity of snow cover thickness, both in space and time, is the main factor controlling ground surface temperatures and leads to a mean range of spatial variability (2.5 ± 0.1 °C) which far exceeds the mean range of observed inter-annual variability (1.6 ± 0.1 °C). The active layer thickness measured in two boreholes at a distance of 30 m shows a mean difference of 2.0 ± 0.1 m with the active layer of one borehole consistently deeper. As revealed by temperature analysis and geophysical soundings, such a difference is mainly driven by the ice/water content in the sub-surface and not by the snow cover regimes. The analysis of deep temperature time series reveals that permafrost is warming. The detected trends are statistically significant starting from a depth below 8 m with warming rates between 0.1 and 0.01 °C yr⁻¹

USE OF UAS IN A HIGH MOUNTAIN LANDSCAPE: THE CASE OF GRAN SOMMETTA ROCK GLACIER (AO)

Photogrammetry has been used since long time to periodically control the evolution of landslides, either from aerial images as well as from ground. Landslides control and monitoring systems face a large variety of cases and situations: in hardly accessible environments, like glacial areas and high mountain locations, it is not simple finding a survey method and a measurement control system, which are capable to reliably assess, with low costs, the expected displacement and its accuracy. For this reason, the behaviour of these events presents the geologists and the surveyor each time with different challenges. The use of UAS (Unmanned Aerial System) represents, in this context, a recent and valid option to perform the data acquisition both in safety and quickly, avoiding hazards and risks for the operators while at the same time containing the costs. The paper presents an innovative monitoring system based on UAS-photogrammetry, GNSS survey and DSM change detection techniques to evaluate the Gran Sommetta rock glacier surface movements over the period 2012-2014. Since 2012, the surface movements of the glacier are monitored by ARPAVdA (a regional environmental protection agency) as a case study for the impact of climate change on high-mountain infrastructures. In such scenarios, in fact, a low-cost monitoring activity can provide important data to improve our knowledge about glacier dynamics connected to climate changes and to prevent risks in anthropic Alps areas. To evaluate the displacements of the rock glacier different techniques were proposed: the most reliable uses the orthophoto of the area and rely on a manual identification of corresponding features performed by a trained operator. To further limit the costs and improve the density of displacement information two automatic procedures were developed as well

Analysis of microseismic signals and temperature recordings for rock slope stability investigations in high mountain areas

Abstract. The permafrost degradation is a probable cause for the increase of rock instabilities and rock falls observed in recent years in high mountain areas, particularly in the Alpine region. The phenomenon causes the thaw of the ice filling rock discontinuities; the water deriving from it subsequently freezes again inducing stresses in the rock mass that may lead, in the long term, to rock falls. To investigate these processes, a monitoring system composed by geophones and thermometers was installed in 2007 at the Carrel hut (3829 m a.s.l., Matterhorn, NW Alps). In 2010, in the framework of the Interreg 2007–2013 Alcotra project no. 56 MASSA, the monitoring system has been empowered and renovated in order to meet project needs. In this paper, the data recorded by this renewed system between 6 October 2010 and 5 October 2011 are presented and 329 selected microseismic events are analysed. The data processing has concerned the classification of the recorded signals, the analysis of their distribution in time and the identification of the most important trace characteristics in time and frequency domain. The interpretation of the results has evidenced a possible correlation between the temperature trend and the event occurrence. The research is still in progress and the data recording and interpretation are planned for a longer period to better investigate the spatial-temporal distribution of microseismic activity in the rock mass, with specific attention to the relation of microseismic activity with temperatures. The overall goal is to verify the possibility to set up an effective monitoring system for investigating the stability of a rock mass under permafrost conditions, in order to supply the researchers with useful data to better understand the relationship between temperature and rock mass stability and, possibly, the technicians with a valid tool for decision-making

Sensitivity of snow models to the accuracy of meteorological forcings in mountain environments

Snow models are usually evaluated at sites providing high-quality meteorological data, so that the uncertainty in the meteorological input data can be neglected when assessing model performances. However, high-quality input data are rarely available in mountain areas and, in practical applications, the meteorological forcing used to drive snow models is typically derived from spatial interpolation of the available in situ data or from reanalyses, whose accuracy can be considerably lower. In order to fully characterize the performances of a snow model, the model sensitivity to errors in the input data should be quantified. In this study we test the ability of six snow models to reproduce snow water equivalent, snow density and snow depth when they are forced by meteorological input data with gradually lower accuracy. The SNOWPACK, GEOTOP, HTESSEL, UTOPIA, SMASH and S3M snow models are forced, first, with high-quality measurements performed at the experimental site of Torgnon, located at 2160ma.s.l. in the Italian Alps (control run). Then, the models are forced by data at gradually lower temporal and/or spatial resolution, obtained by (i) sampling the original Torgnon 30 min time series at 3, 6, and 12 h, (ii) spatially interpolating neighbouring in situ station measurements and (iii) extracting information from GLDAS, ERA5 and ERA-Interim reanalyses at the grid point closest to the Torgnon site. Since the selected models are characterized by different degrees of complexity, from highly sophisticated multi-layer snow models to simple, empirical, single-layer snow schemes, we also discuss the results of these experiments in relation to the model complexity. The results show that, when forced by accurate 30 min resolution weather station data, the single-layer, intermediatecomplexity snow models HTESSEL and UTOPIA provide similar skills to the more sophisticated multi-layer model SNOWPACK, and these three models show better agreement with observations and more robust performances over different seasons compared to the lower-complexity models SMASH and S3M. All models forced by 3-hourly data provide similar skills to the control run, while the use of 6- A nd 12-hourly temporal resolution forcings may lead to a reduction in model performances if the incoming shortwave radiation is not properly represented. The SMASH model generally shows low sensitivity to the temporal degradation of the input data. Spatially interpolated data from neighbouring stations and reanalyses are found to be adequate forcings, provided that temperature and precipitation variables are not affected by large biases over the considered period. However, a simple bias-adjustment technique applied to ERA-Interim temperatures allowed all models to achieve similar performances to the control run. Regardless of their complexity, all models show weaknesses in the representation of the snow density

Saharan dust events in the European Alps: role in snowmelt and geochemical characterization

The input of mineral dust from arid regions impacts snow optical properties. The induced albedo reduction generally alters the melting dynamics of the snowpack, resulting in earlier snowmelt. In this paper, we evaluate the impact of dust depositions on the melting dynamics of snowpack at a high-elevation site (2160&thinsp;m) in the European Alps (Torgnon, Aosta Valley, Italy) during three hydrological years (2013–2016). These years were characterized by several Saharan dust events that deposited significant amounts of mineral dust in the European Alps. We quantify the shortening of the snow season due to dust deposition by comparing observed snow depths and those simulated with the Crocus model accounting, or not, for the impact of impurities. The model was run and tested using meteorological data from an automated weather station. We propose the use of repeated digital images for tracking dust deposition and resurfacing in the snowpack. The good agreement between model prediction and digital images allowed us to propose the use of an RGB index (i.e. snow darkening index – SDI) for monitoring dust on snow using images from a digital camera. We also present a geochemical characterization of dust reaching the Alpine chain during spring in 2014. Elements found in dust were classified as a function of their origin and compared with Saharan sources. A strong enrichment in Fe was observed in snow containing Saharan dust. In our case study, the comparison between modelling results and observations showed that impurities deposited in snow anticipated the disappearance of snow up to 38&thinsp;d a out of a total 7 months of typical snow duration. This happened for the season 2015–2016 that was characterized by a strong dust deposition event. During the other seasons considered here (2013–2014 and 2014–2015), the snow melt-out date was 18 and 11&thinsp;d earlier, respectively. We conclude that the effect of the Saharan dust is expected to reduce snow cover duration through the snow-albedo feedback. This process is known to have a series of further hydrological and phenological feedback effects that should be characterized in future research.</p

The triggering factors of the Móafellshyrna debris slide in northern Iceland: Intense precipitation, earthquake activity and thawing of mountain permafrost

On the 20th September 2012, a large debris slide occurred in the Móafellshyrna Mountain in the Tröllaskagi peninsula, central north Iceland. Our work describes and discusses the relative importance of the three factors that may have contributed to the failure of the slope: intense precipitation, earthquake activity and thawing of ground ice. We use data from weather stations, seismometers, witness reports and field observations to examine these factors. The slide initiated after an unusually warm and dry summer followed by a month of heavy precipitation. Furthermore, the slide occurred after three seismic episodes, whose epicentres were located ~60km NNE of Móafellshyrna Mountain. The main source of material for the slide was ice-rich colluvium perched on a topographic bench. Blocks of ice-cemented colluvium slid and then broke off the frontal part of the talus slope, and the landslide also involved a component of debris slide, which mobilized around 312,000-480,000m(3) (as estimated from field data and aerial images of erosional morphologies). From our analysis we infer that intense precipitation and seismic activity prior to the slide are the main preparatory factors for the slide. The presence of ice-cemented blocks in the slide's deposits leads us to infer that deep thawing of ground ice was likely the final triggering factor. Ice-cemented blocks of debris have been observed in the deposits of two other recent landslides in northern Iceland, in the Torfufell Mountain and the Árnesfjall Mountain. This suggests that discontinuous mountain permafrost is degrading in Iceland, consistent with the decadal trend of increasing atmospheric temperature in Iceland. This study highlights a newly identified hazard in Iceland: landslides as a result of ground ice thaw. Knowledge of the detailed distribution of mountain permafrost in colluvium on the island is poorly constrained and should be a priority for future research in order to identify zones at risk from this hazard