| 03 Jul 2025
Detecting and understanding slow glacier flow under climate change: A case study on Vernagtferner, Austria
Abstract. Long-term surface velocity observations of glaciers reflect the dynamics of glacier ice and its interaction with the mass balance, including variations due to climate change. In this study, we investigate the surface velocities of a slow-flowing glacier which is influenced by strong surface melt and negative mass balance during the last decades. The annual stake measurements date back to 1966 and allow the study of ice dynamics for more than five decades. We observed a strong relationship between the surface velocity and ice thickness, especially in the case of the glacier's response to thinning. A series of slightly positive mass balances led to a minor glacier advance around 1980, associated with a considerable speed-up of the glacier. With the onset of the negative mass balances, the velocity has decreased steadily until today. Based on recent in-situ measurements, a seasonal variation of surface velocities can be identified, with around 30 % higher summer velocities in relation to the annual average. In order to investigate the current ice surface flow, we analyze the potential and limitations of remote sensing for slow-flowing glaciers. Standard remote sensing techniques did not provide reliable results due to the combination of low ice flow and high ablation, and the associated difficulty in establishing coherence and identifying stable features in the remote sensing products. Instead, manual feature tracking based on a combination of stake measurements and the investigation of unpiloted aerial vehicle (UAV) surveys, and airborne imagery was used to generate a reference dataset for the period 2018–2023. With an average velocity of 1 m yr−1 and a maximum displacement rate of 4 m yr−1 in the central part of the glacier, it gives a clear picture of the low present-day glacier flow.
General comments
The manuscript reports on the temporal evolution of surface velocity of the glacier Vernagtferner in the Eastern Alps with focus on a period of major slowdown in recent years after the glacier broke up in several parts. The presented velocity data are based on in situ stake measurements and manual feature tracking in optical airborne images. The presented material and related discussion cover two main topics: (i) the presentation and description of the derived velocity field and of factors responsible for slow-down, including a review of the glacier behaviour since 1966; (ii) an overview on specific remote sensing products on glacier velocity, leading to the conclusion that these products are not suitable for application to slowly moving glaciers. Topic (i) is an interesting case study on a glacier in retreat, demonstrating the impact of long-term negative mass balance and related glacier thinning on a previously quite active Alpine glacier. Factors responsible for the decline are discussed, but an in depth assessment of the governing processes is missing. The presented material on topic (ii) does not contain any novel aspects. In summary, the paper presents an interesting case study on slow-down of an Alpine glacier in decay but has substantial shortcomings. Major revisions and shortening (in particular regarding topic ii) are required.
Specific Comments
Satellite remote sensing: Major parts of the manuscript refer to spaceborne remote sensing of glacier velocities (Introduction line 45 to 53, Sections 3.2, 3.3.1, 4.3.1, Section 5.2, Fig.2, Fig. 9). These sections refer to properties and suitability of particular products, but do not provide any novel information on methods, accuracy assessment and constraints regarding remote sensing techniques and products for mapping glacier surface motion. During more than three decades results of detailed performance analyses on glacier surface velocity methods and products have been reported in publications and product specification documents, both for so-called “standard satellite remote sensing products” as well as for products derived from data of different satellite missions. These publications show that the pixel size and errors of the “standard products” (based on offset tracking) do not match the accuracy and spatial detail required for mapping very slow velocities at comparatively small spatial scale as observed on Vernagtferner. Taking this into account, the sections on satellite remote sensing can be largely shortened and replaced by references on documents and publications specifying performance numbers for specific satellite-based velocity products. Furthermore, Figures 2 and 9 can be omitted because there is no need showing examples of deficient velocity maps using input data that are not matching the technical requirements needed for velocity retrievals of the study glacier.
Analysis and interpretation of surface velocities: The new velocity data, presented in the manuscript, refer to the period 2018 to 2023 when maximum velocities of Vernagtferner were below 5 m yr-1. The presented velocities are horizontal displacements referring to individual points on a main branch of the glacier, based on manual feature tracking in optical airborne images and on stake measurements. Considering the average velocity of 1 m yr-1, it is obvious that the magnitude of vertical surface lowering exceeds that of the horizontal displacements. Consequently, the vertical displacement of the surface (mass depletion due to surface/atmosphere exchange processes) is the dominating component for the glacier mass balance in the current state and ice dynamics plays a minor role. In this context, quantitative information on the annual mass balance (respectively the related topographic change) and its spatial pattern during the study period would be of interest.
Line 45 to 53: This is a one-sided introduction on space-borne remote sensing applications for ice velocity monitoring. The statement on the use of space-borne remote sensing “particularly in Antarctica” does not reflect the actual situation in which ice velocity products are generated routinely on behalf of various organizations, covering at large all global land ice areas. Several of these products exploit also radar repeat-pass interferometry in regions and seasons where coherence is preserved.
Line 56-57: Temporal decorrelation is not a particular problem for slowly flowing glaciers, but rather for fast movement, particularly in shear margins where interferometric fringes are often tightly spaced or aliased.
Line 86: Horizontal displacement and surface velocity are not the same.
Line 113-118: Whereas time spans of TerraSAR-X repeat-pass data are 11 days, there are other high resolution SAR constellations offering shorter repeat-pass sequences, well suitable for glacier velocity mapping based on the motion-related interferometric phase. For example, successful glacier monitoring applications have been reported for 1-day, 3-day and 4-day interferometric repeat pass pairs of the COSMO Sky-Med constellation, providing high accuracy velocity products. Coherence tracking applies cross-correlation matching of templates and thus has a spatial resolution and sensitivity similar to feature tracking.
Figure 3: Please provide information on the time periods (years) to which the time sequences of the individual stakes refer.
Figure 5 caption: Please provide reference for the source of the ice thickness data 1970.
Section 4.2, Seasonal variation: The summer velocities are based on measurements in summer 2022, the ablation period of the mass balance year 2021/22 with the largest mass deficit of the 2018 to 2023 period in the Eastern Alps. Consequently, it is unclear if the number for the seasonal velocity increase 2022 is representative for the whole period.
Figure 8: The presentation of a few numbers (velocities, exact dates) in the form of a table would be more appropriate than the display within a diagram.
Line 200: The statement that it is “not possible to (semi-) automatically produce a reliable surface velocity map from aerial or satellite imagery for slow-flowing Vernagtferner ….” is rather speculative, not taking into account capabilities of advanced airborne and spaceborne observation systems and analysis techniques. For example, several large satellite constellations with very high resolution SAR sensors are in space since several years. Some of these constellations provide repeat interferometric observations of excellent quality with repeat-pass intervals from one day onwards, as for example ICEYE InSAR products show.
Line 223ff: Taking into account that the annual melt losses, amounting up to several meters, may cause significant changes of surface features, the estimates of feature position accuracy seem to be rather optimistic. For example, in line 53 it is stated that “surface features (e.g. crevasses) change considerably during this period”, a possible source for increased uncertainties in feature tracking. Furthermore, oblique views sideways of the central flowline may introduce errors, in particular if the surface elevation at the time of the survey is not exactly known. Please provide information on the procedures in which way these issues are taken into account.
Section 5.1, Ice dynamics: Basic mechanisms related to slow-down of glacier flow are addressed, as well as possible causes for seasonal variations. However, quantitative estimates on the impact and magnitude of the different processes at the study glacier and their interactions during the observation period are missing. For contributing to the advancement of understanding of processes governing the slow-down of retreating glaciers, quantitative estimates would be essential. Furthermore, hints on the significance of the study results in respect to the general glacier behaviour in this region would be of interest.