M., 2016. Recent speed-up of an Alpine rock glacier: an updated chronology of the kinematics of Outer Hochebenkar rock glacier based on geodetic measurements. ABSTRACT.Surface velocities have been regularly monitored at the rock glacier in Outer Hochebenkar,Ötztal Alps, Austria since the early 1950s. This study provides an update to previously published surface velocity time series, showing mean profile velocities of four cross profiles since the beginning of the measurements (1951,1954, 1997; depending on the profile), as well as single block displacements from 1998 to 2015. Profiles P1, P2 and P3 have moved between 42 and 90 m, at mean velocities between 0.70 and 1.48 m yr -1 , since they were first established in the early 1950s (1951/54). Profile P0, established in 1997, has since moved 13 m or 0.75 m yr -1 . An acceleration can be observed at all profiles since the late 1990s, with a particularly sharp velocity increase since 2010. All profiles reached a new maximum velocity in 2015, with 1.98 m yr -1 at the slowest profile (P0) and 6.37 m yr -1 at the fastest profile (P1).Year-to-year variations in profile velocities cannot be clearly attributed to inter-annual variations of climatic parameters like mean annual air temperature, summer temperature, positive degree days, or precipitation. However, higher correlation is found between velocities and cumulative anomalies of air temperature (mean annual air temperature and positive degree days) and summer precipitation, suggesting that these parameters play a key role for the movement of the rock glacier. The lower profiles (P0, P1) show more pronounced year-to-year variations than the upper profiles (P2, P3). It is considered likely that processes other than climatic forcing (e.g. sliding, topography) contribute to the different velocity patterns at the four profiles.

Abstract. The density of new snow is operationally monitored by meteorological or hydrological services at daily time intervals, or occasionally measured in local field studies. However, meteorological conditions and thus settling of the freshly deposited snow rapidly alter the new snow density until measurement. Physically based snow models and nowcasting applications make use of hourly weather data to determine the water equivalent of the snowfall and snow depth. In previous studies, a number of empirical parameterizations were developed to approximate the new snow density by meteorological parameters. These parameterizations are largely based on new snow measurements derived from local in situ measurements. In this study a data set of automated snow measurements at four stations located in the European Alps is analysed for several winter seasons. Hourly new snow densities are calculated from the height of new snow and the water equivalent of snowfall. Considering the settling of the new snow and the old snowpack, the average hourly new snow density is 68 kg m −3 , with a standard deviation of 9 kg m −3 . Seven existing parameterizations for estimating new snow densities were tested against these data, and most calculations overestimate the hourly automated measurements. Two of the tested parameterizations were capable of simulating low new snow densities observed at sheltered inner-alpine stations. The observed variability in new snow density from the automated measurements could not be described with satisfactory statistical significance by any of the investigated parameterizations. Applying simple linear regressions between new snow density and wet bulb temperature based on the measurements' data resulted in significant relationships (r 2 > 0.5 and p ≤ 0.05) for single periods at individual stations only. Higher new snow density was calculated for the highest elevated and most wind-exposed station location. Whereas snow measurements using ultrasonic devices and snow pillows are appropriate for calculating station mean new snow densities, we recommend instruments with higher accuracy e.g. optical devices for more reliable investigations of the variability of new snow densities at sub-daily intervals.

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Abstract. This study investigates rock glacier destabilization based on the results of a unique in situ and remote-sensing-based monitoring network focused on the kinematics of the rock glacier in Äußeres Hochebenkar (Austrian Alps). We consolidate, homogenize, and extend existing time series to generate a comprehensive dataset consisting of 14 digital surface models covering a 68-year time period, as well as in situ measurements of block displacement since the early 1950s. The digital surface models are derived from historical aerial imagery and, more recently, airborne and uncrewed-aerial-vehicle-based laser scanning (ALS and ULS, respectively). High-resolution 3D ALS and ULS point clouds are available at annual temporal resolution from 2017 to 2021. Additional terrestrial laser scanning data collected in bi-weekly intervals during the summer of 2019 are available from the rock glacier front. Using image correlation techniques, we derive velocity vectors from the digital surface models, thereby adding rock-glacier-wide spatial context to the point-scale block displacement measurements. Based on velocities, surface elevation changes, analyses of morphological features, and computations of the bulk creep factor and strain rates, we assess the combined datasets in terms of rock glacier destabilization. To additionally investigate potential rotational components of the movement of the destabilized section of the rock glacier, we integrate in situ data of block displacement with ULS point clouds and compute changes in the rotation angles of single blocks during recent years. The time series shows two cycles of destabilization in the lower section of the rock glacier. The first lasted from the early 1950s until the mid-1970s. The second began around 2017 after approximately 2 decades of more gradual acceleration and is currently ongoing. Both destabilization periods are characterized by high velocities and the development of morphological destabilization features on the rock glacier surface. Acceleration in the most recent years has been very pronounced, with velocities reaching 20–30 m a−1 in 2020–2021. These values are unprecedented in the time series and suggest highly destabilized conditions in the lower section of the rock glacier, which shows signs of translational and rotational landslide-like movement. Due to the length and granularity of the time series, the cyclic destabilization process at the Äußeres Hochebenkar rock glacier is well resolved in the dataset. Our study highlights the importance of interdisciplinary, long-term, and continuous high-resolution 3D monitoring to improve process understanding and model development related to rock glacier rheology and destabilization.

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Abstract. As Alpine glaciers become snow-free in summer, more dark, bare ice is exposed, decreasing local albedo and increasing surface melting. To include this feedback mechanism in models of future deglaciation, it is important to understand the processes governing broadband and spectral albedo at a local scale. However, few in situ reflectance data have been measured in the ablation zones of mountain glaciers. As a contribution to this knowledge gap, we present spectral reflectance data (hemispherical–conical–reflectance factor) from 325 to 1075 nm collected along several profile lines in the ablation zone of Jamtalferner, Austria. Measurements were timed to closely coincide with a Sentinel-2 and Landsat 8 overpass and are compared to the respective ground reflectance (bottom-of-atmosphere) products. The brightest spectra have a maximum reflectance of up to 0.7 and consist of clean, dry ice. In contrast, reflectance does not exceed 0.2 for dark spectra where liquid water and/or fine-grained debris are present. Spectra can roughly be grouped into dry ice, wet ice, and dirt or rocks, although gradations between these groups occur. Neither satellite captures the full range of in situ reflectance values. The difference between ground and satellite data is not uniform across satellite bands, between Landsat and Sentinel, and to some extent between ice surface types (underestimation of reflectance for bright surfaces, overestimation for dark surfaces). We highlight the need for further, systematic measurements of in situ spectral reflectance properties, their variability in time and space, and in-depth analysis of time-synchronous satellite data.

An overview of climatological and meteorological conditions and their seasonal variability in the Denali summit region is presented, based on the NCEP–NCAR reanalysis 1 dataset for the 1948–2018 period. At the Denali grid cell, a warming trend of +0.02°C significant at the 95% level is found—equivalent to a temperature increase of 1.4°C over the time period. The number of very cold days (<−35°C) during the climbing season (April–July) has decreased by approximately a day per decade. The number of very windy days (≥20 m s−1) during the climbing season also shows a decreasing trend for the majority of the time series. To assess synoptic patterns that affect the Denali region, a self-organizing map algorithm was applied to the geopotential height (GPH) field extracted from the reanalysis data. In winter, the synoptic situation in the Denali region is dominated by frequent zonal flow and negative GPH anomalies associated with the polar front. As the polar front moves north during the seasonal cycle, patterns shift to largely positive GPH anomalies and more meridional flow. Extreme wind speeds unfavorable for climbing occur in all seasons and are associated mainly with the polar jet passing directly over Denali, or cyclogenesis in the Bering Sea. The frequency of occurrence of strongly zonal, low GPH patterns during the main climbing season (April–July) shows a slight decrease in recent years.