This study presents a reanalysis of the glaciologically obtained annual glacier mass balances at Hintereisferner, Ötztal Alps, Austria, for the period 2001–2011. The reanalysis is accomplished through a comparison with geodetically derived mass changes, using annual high-resolution airborne laser scanning (ALS). The grid-based adjustments for the method-inherent differences are discussed along with associated uncertainties and discrepancies of the two methods of mass balance measurements. A statistical comparison of the two datasets shows no significant difference for seven annual, as well as the cumulative, mass changes over the 10-year record. Yet, the statistical view hides significant differences in the mass balance years 2002/03 (glaciological minus geodetic records = +0.92 m w.e.), 2005/06 (+0.60 m w.e.), and 2006/07 (−0.45 m w.e.). We conclude that exceptional meteorological conditions can render the usual glaciological observational network inadequate. Furthermore, we consider that ALS data reliably reproduce the annual mass balance and can be seen as validation or calibration tools for the glaciological method.

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.

Observations of glacier mass changes are key to understanding the response of glaciers to climate change and related impacts, such as regional runoff, ecosystem changes, and global sea level rise. Spaceborne optical and radar sensors make it possible to quantify glacier elevation changes, and thus multi-annual mass changes, on a regional and global scale. However, estimates from a growing number of studies show a wide range of results with differences often beyond uncertainty bounds. Here, we present the outcome of a community-based inter-comparison experiment using spaceborne optical stereo (ASTER) and synthetic aperture radar interferometry (TanDEM-X) data to estimate elevation changes for defined glaciers and target periods that pose different assessment challenges. Using provided or self-processed digital elevation models (DEMs) for five test sites, 12 research groups provided a total of 97 spaceborne elevation-change datasets using various processing approaches. Validation with airborne data showed that using an ensemble estimate is promising to reduce random errors from different instruments and processing methods but still requires a more comprehensive investigation and correction of systematic errors. We found that scene selection, DEM processing, and co-registration have the biggest impact on the results. Other processing steps, such as treating spatial data voids, differences in survey periods, or radar penetration, can still be important for individual cases. Future research should focus on testing different implementations of individual processing steps (e.g. co-registration) and addressing issues related to temporal corrections, radar penetration, glacier area changes, and density conversion. Finally, there is a clear need for our community to develop best practices, use open, reproducible software, and assess overall uncertainty to enhance inter-comparison and empower physical process insights across glacier elevation-change studies.

In this study, we use Pléiades tri-stereo data to generate a digital elevation model (DEM) from the Pléiades images using a workflow employing semi-global matching (SGM). We examine the DEM accuracy in complex mountain glaciated terrain by comparing the new DEMs with an independent high-quality DEM based on airborne laser scanning (ALS) data for a study area in the Austrian Alps, and with ground control points for a study area in the Khumbu Himal of Nepal. The DEMs derived using the SGM algorithm compare well to the independent high-quality ALS DEM, and the workflow produces models of sufficient quality to resolve ground control points, which are based on Pléiades imagery that are of sufficient quality to perform high spatio-temporal resolution assessments of remote areas for which no field data is available. The relative accuracy is sufficient to investigate glacier surface elevation changes below one meter, and can therefore be applied over relatively short periods of time, such as those required for annual and seasonal assessments of change. The annual geodetic mass balance for the Alpine case derived from our DEM compares well to the glaciological mass balance, and multitemporal DEM analysis is used to resolve the seasonal changes of five glaciers in the Khumbu Himal, revealing that glaciological processes such as accumulation, ablation, and glacier movement mainly take place during the summer season, with the winter season being largely inactive in the year sampled.

Records of glacier mass balance represent important data in climate science and their uncertainties affect calculations of sea level rise and other societally relevant environmental projections. In order to reduce and quantify uncertainties in mass balance series obtained by direct glaciological measurements, we present a detailed reanalysis workflow which was applied to the 10-year record (2004 to 2013) of seasonal mass balance of Langenferner, a small glacier in the European Eastern Alps. The approach involves a methodological homogenization of available point values and the creation of pseudo-observations of point mass balance for years and locations without measurements by the application of a process-based model constrained by snow line observations. We examine the uncertainties related to the extrapolation of point data using a variety of methods and consequently present a more rigorous uncertainty assessment than is usually reported in the literature. Results reveal that the reanalyzed balance record considerably differs from the original one mainly for the first half of the observation period. For annual balances these misfits reach the order of > 300 kg m⁻² and could primarily be attributed to a lack of measurements in the upper glacier part and to the use of outdated glacier outlines. For winter balances respective differences are smaller (up to 233 kg m⁻²) and they originate primarily from methodological inhomogeneities in the original series. Remaining random uncertainties in the reanalyzed series are mainly determined by the extrapolation of point data to the glacier scale and are on the order of ±79 kg m⁻² for annual and ±52 kg m⁻² for winter balances with values for single years/seasons reaching ±136 kg m⁻². A comparison of the glaciological results to those obtained by the geodetic method for the period 2005 to 2013 based on airborne laser-scanning data reveals that no significant bias of the reanalyzed record is detectable.

A terrestrial laser scanner (TLS) of the type RIEGL VZ-6000 has been permanently installed and automated at Hintereisferner glacier located in the Ötztal Alps, Austria, to identify snow (re)distribution from surface height changes. A first case study is presented that shows and discusses detected snow distribution at the glacier after a snowfall event, together with concurrent snow erosion and deposition caused by avalanches. The paper shows the potential of a TLS system in a high mountain environment, which is also applicable to other environmental mapping applications. It introduces the setup of the TLS system, its automation procedure, and a first and preliminary uncertainty analysis. TLS data are generally influenced by four uncertainty sources: atmospheric conditions, scanning geometry, mechanical properties, and surface reflectance properties. The first three sources have significant influence on the TLS data at Hintereisferner, whereby the total accuracy of the TLS system is estimated to be in a range of a few decimetres, subject to ongoing more detailed data analysis.