A statistical approach to modelling permafrost distribution in the European Alps or similar mountain ranges

Estimates of permafrost distribution in mountain regions are important for the assessment of climate change effects on natural and human systems. In order to make permafrost analyses and the establishment of guidelines for e.g. construction or hazard assessment comparable and compatible between regions, one consistent and traceable model for the entire Alpine domain is required. For the calibration of statistical models, the scarcity of suitable and reliable information about the presence or absence of permafrost makes the use of large areas attractive due to the larger data base available. We present a strategy and method for modelling permafrost distribution of entire mountain regions and provide the results of statistical analyses and model calibration for the European Alps. Starting from an integrated model framework, two statistical sub-models are developed, one for debris-covered areas (debris model) and one for steep bedrock (rock model). They are calibrated using rock glacier inventories and rock surface temperatures. To support the later generalization to surface characteristics other than those available for calibration, so-called offset terms have been introduced into the model that allow doing this in a transparent and traceable manner. For the debris model a generalized linear mixed-effect model (GLMM) is used to predict the probability of a rock glacier being intact as opposed to relict. It is based on the explanatory variables mean annual air temperature (MAAT), potential incoming solar radiation (PISR) and the mean annual sum of precipitation (PRECIP), and achieves an excellent discrimination (area under the receiver-operating char- acteristic, AUROC = 0.91). Surprisingly, the probability of a rock glacier being intact is positively associated with increasing PRECIP for given MAAT and PISR conditions. The rock model is based on a linear regression and was calibrated with mean annual rock surface temperatures (MARST). The explanatory variables are MAAT and PISR. The linear regression achieves a root mean square error (RMSE) of 1.6 ◦ C. The final model combines the two sub-models and accounts for the different scales used for model calibration. The modelling approach provides a theoretical basis for estimating mountain permafrost distribution over larger mountain ranges and can be expanded to more surface types and sub-models than considered, here. The analyses performed with the Alpine data set further provide quantitative insight into larger-area patterns as well as the model coefficients for a later spatial application. The transfer into a mapbased product, however, requires further steps such as the definition of offset terms that usually contain a degree of subjectivity

Brief communication: "An inventory of permafrost evidence for the European Alps"

The investigation and modelling of permafrost distribution, particularly in areas of discontinuous permafrost, is challenging due to spatial heterogeneity, remoteness of measurement sites and data scarcity. We have designed a strategy for standardizing different local data sets containing evidence of the presence or absence of permafrost into an inventory for the entire European Alps. With this brief communication, we present the structure and contents of this inventory. This collection of permafrost evidence not only highlights existing data and allows new analyses based on larger data sets, but also provides complementary information for an improved interpretation of monitoring results

Global Warming as a Predisposing Factor for Landslides in Glacial and Periglacial Areas: An Example from Western Alps (Aosta Valley, Italy)

Signals of global climate change are increasingly evident in the Alps where, in recent years, a growing number of landslides occurred in glacial and periglacial areas. In order to document such a case, a landslide is described and analysed, which affected the SE side of a rocky ridge and the Trajo Glacier below in the Gran Paradiso Massif (NW Italy) during the warm summer of 2017. It was a multiple rockfall of about ½ million m2, with vertical drop of ≈300 m, a runout distance of ≈900 m, and 17° of travel angle. Prompt field surveys, interpretation of Sentinel-2 satellite images, and an analysis of data from several weather stations, are used to reconstruct the phenomenon and its causes. This study highlights the geological structure of the area (which reflects the morphology and geo-mechanical characteristics of the slope) and the meteorological conditions during the months before the main failure. Moreover it reveals that the landslide was not a single event but developed over time through at least five failures. According to available information, several predisposing factors seem to have played an important such as the degradation of permafrost (probably affecting rock masses at depth), the alternation of freeze-thaw cycles, and the availability of a considerable amount of water from rainfall and snowmelt, infiltrating the rock mass

Rockglaciers of the Engadine

The Engadine is one of the rockglacier hot spots in the European Alps. Many rockglaciers in all states of activity (active, inactive, relict) are found, indicating the former and present occurrence of permafrost. This is due to continental climate conditions, high elevation, and high weathering rates. Rockglaciers are developed in valley bottoms, such as the Val Sassa and the Val da l’Acqua rockglacier, or in formerly glaciated cirques, such as the Muragl or the Murtèl rockglacier. Hence, the Engadine is the home of research on rockglaciers in Europe with the first studies on rockglaciers of the Swiss National Park one century ago. Engadine was also the first place in the world where boreholes in rockglaciers were drilled in 1987. Nowadays, several Engadine rockglaciers are monitored within the Permafrost Monitoring Network Switzerland (PERMOS)