Sea level rise contribution from the Antarctic ice sheet is influenced by changes in glacier and ice shelf front position. Still, little is known about seasonal glacier and ice shelf front fluctuations as the manual delineation of calving fronts from remote sensing imagery is very time-consuming. The major challenge of automatic calving front extraction is the low contrast between floating glacier and ice shelf fronts and the surrounding sea ice. Additionally, in previous decades, remote sensing imagery over the often cloud-covered Antarctic coastline was limited. Nowadays, an abundance of Sentinel-1 imagery over the Antarctic coastline exists and could be used for tracking glacier and ice shelf front movement. To exploit the available Sentinel-1 data, we developed a processing chain allowing automatic extraction of the Antarctic coastline from Seninel-1 imagery and the creation of dense time series to assess calving front change. The core of the proposed workflow is a modified version of the deep learning architecture U-Net. This convolutional neural network (CNN) performs a semantic segmentation on dual-pol Sentinel-1 data and the Antarctic TanDEM-X digital elevation model (DEM). The proposed method is tested for four training and test areas along the Antarctic coastline. The automatically extracted fronts deviate on average 78 m in training and 108 m test areas. Spatial and temporal transferability is demonstrated on an automatically extracted 15-month time series along the Getz Ice Shelf. Between May 2017 and July 2018, the fronts along the Getz Ice Shelf show mostly an advancing tendency with the fastest moving front of DeVicq Glacier with 726 ± 20 m/yr.

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The contribution of Antarctica’s ice sheet to global sea-level rise depends on the very dynamic behavior of glaciers and ice shelves. One important parameter of ice-sheet dynamics is the location of glacier and ice-shelf fronts. Numerous remote sensing studies on Antarctic glacier and ice-shelf front positions exist, but no long-term record on circum-Antarctic front dynamics has been established so far. The article outlines the potential of remote sensing to map, extract, and measure calving front dynamics. Furthermore, this review provides an overview of the spatial and temporal availability of Antarctic calving front observations for the first time. Single measurements are compiled to a circum-Antarctic record of glacier and ice shelf retreat/advance. We find sufficient frontal records for the Antarctic Peninsula and Victoria Land, whereas on the West Antarctic Ice Sheet (WAIS), measurements only concentrate on specific glaciers and ice sheets. Frontal records for the East Antarctic Ice Sheet exist since the 1970s. Studies agree on the general retreat of calving fronts along the Antarctic Peninsula. East Antarctic calving fronts also showed retreating tendencies between 1970s until the early 1990s, but have advanced since the 2000s. Exceptions of this general trend are Victoria Land, Wilkes Land, and the northernmost Dronning Maud Land. For the WAIS, no clear trend in long-term front fluctuations could be identified, as observations of different studies vary in space and time, and fronts highly fluctuate. For further calving front analysis, regular mapping intervals as well as glacier morphology should be included. We propose to exploit current and future developments in Earth observations to create frequent standardized measurements for circum-Antarctic assessments of glacier and ice-shelf front dynamics in regard to ice-sheet mass balance and climate forcing.

Abstract. The safety band of Antarctica, consisting of floating glacier tongues and ice shelves, buttresses ice discharge of the Antarctic Ice Sheet. Recent disintegration events of ice shelves along with glacier retreat indicate a weakening of this important safety band. Predicting calving front retreat is a real challenge due to complex ice dynamics in a data-scarce environment that are unique for each ice shelf and glacier. We explore the extent to which easy-to-access remote sensing and modeling data can help to define environmental conditions leading to calving front retreat. For the first time, we present a circum-Antarctic record of glacier and ice shelf front change over the last two decades in combination with environmental variables such as air temperature, sea ice days, snowmelt, sea surface temperature, and wind direction. We find that the Antarctic Ice Sheet area decreased by −29 618 ± 1193 km2 in extent between 1997–2008 and gained an area of 7108 ± 1029 km2 between 2009 and 2018. Retreat concentrated along the Antarctic Peninsula and West Antarctica including the biggest ice shelves (Ross and Ronne). In several cases, glacier and ice shelf retreat occurred in conjunction with one or several changes in environmental variables. Decreasing sea ice days, intense snowmelt, weakening easterlies, and relative changes in sea surface temperature were identified as enabling factors for retreat. In contrast, relative increases in mean air temperature did not correlate with calving front retreat. For future studies a more appropriate measure for atmospheric forcing should be considered, including above-zero-degree days and temperature extreme events. To better understand drivers of glacier and ice shelf retreat, it is critical to analyze the magnitude of basal melt through the intrusion of warm Circumpolar Deep Water that is driven by strengthening westerlies and to further assess surface hydrology processes such as meltwater ponding, runoff, and lake drainage.

Remote sensing technologies are integral to monitoring the mountain cryosphere in a warming world. Satellite missions and field-based platforms have transformed understanding of the processes driving changes in mountain glacier dynamics, snow cover, lake evolution, and the associated emergence of hazards (e.g. avalanches, floods, landslides). Sensors and platforms are becoming more bespoke, with innovation being driven by the commercial sector, and image repositories are more frequently open access, leading to the democratisation of data analysis and interpretation. Cloud computing, artificial intelligence, and machine learning are rapidly transforming our ability to handle this exponential increase in data. This review therefore provides a timely opportunity to synthesise current capabilities in remote sensing of the mountain cryosphere. Scientific and commercial applications were critically examined, recognising the technologies that have most advanced the discipline. Low-cost sensors can also be deployed in the field, using microprocessors and telecommunications equipment to connect mountain glaciers to stakeholders for real-time monitoring. The potential for novel automated pipelines that can process vast volumes of data is also discussed, from reimagining historical aerial imagery to produce elevation models, to automatically delineating glacier boundaries. Finally, the applications of these emerging techniques that will benefit scientific research avenues and real-world societal programmes are discussed.

<p>Antarctica`s coastline is constantly changing by moving ice shelf margins and glacier tongues. This can influence the discharge of the Antarctic Ice Sheet if ice shelf areas with buttressing forces are involved. By now, glacier and ice shelf front changes are not tracked continuously due to time-consuming manual work. Hence, dynamics of the calving front position are often simplified by using the steady-state-calving assumption for modelling. To provide modelers with frequent and continuous time series of calving front change, we introduce the ice shelf front monitoring service “IceLines”. IceLines monitors major Antarctic ice shelf fronts based on Sentinel-1 radar imagery. The data set is automatically updated on a monthly basis and can be accessed via the EOC GeoService (geoservice.dlr.de) hosted by DLR. IceLines automatically downloads and pre-processes Sentinel-1 data for 36 selected shelves and glaciers, extracts the calving front based on a deep neural network and optimizes the result by post-processing. The processing chain of IceLines presents unprecedented dense time series of calving front change during the era of Sentinel-1 (2014-today). Whereas many previous challenges for automatic calving front detection were tackled (e.g. various glacier morphologies, backscatter changes, different polarizations), some limitations exist for ice shelves with excessive surface melt during summer or dry snow facies close to the front. We will present the current implementation, the derived calving front time series and validation results of IceLines. Discussions with the modelling community are welcome to further improve the IceLines data set for ice sheet and ice shelf modelling applications.</p>

Abstract. The safety band of Antarctica consisting of floating glacier tongues and ice shelves buttresses ice discharge of the Antarctic Ice Sheet. Recent disintegration events of ice shelves and glacier retreat indicate a weakening of this important safety band. Predicting calving front retreat is a real challenge due to complex ice dynamics in a data-scarce environment being unique for each ice shelf and glacier. We explore to what extent easy to access remote sensing and modelling data can help to define environmental conditions leading to calving front retreat. For the first time, we present a circum-Antarctic record of glacier and ice shelf front retreat over the last two decades in combination with environmental variables such as air temperature, sea ice days, snowmelt, sea surface temperature and wind direction. We find that the Antarctic ice sheet area shrank 29,618 ± 29 km2 in extent between 1997–2008 and gained an area of 7,108 ± 144.4 km2 between 2009 and 2018. Retreat concentrated along the Antarctic Peninsula and West Antarctica including the biggest ice shelves Ross and Ronne. Glacier and ice shelf retreat comes along with one or several changes in environmental variables. Decreasing sea ice days, intense snow melt, weakening easterlies and relative changes in sea surface temperature were identified as enabling factors for retreat. In contrast, relative increases in air temperature did not correlate with calving front retreat. To better understand drivers of glacier and ice shelf retreat it is of high importance to analyse the magnitude of basal melt through the intrusion of warm Circumpolar Deep Water (CDW) driven by strengthening westerlies and to further assess surface hydrology processes such as meltwater ponding, runoff and lake drainage.

The hydrological drought in Northern Italy in 2022 was, in large part, the consequence of a snow drought in the Italian Alps in the winter of 2021/22 and the resulting deficit of melt water runoff. In this communication, we assessed the snow-cover dynamics in nine Alpine Italian catchments using long time series of satellite-derived snow line elevation (SLE) measurements. We compared the SLE of the hydrological year 2021/22 to the long-term dynamics of 1985–2021. In early 2022, the SLE was located several hundred meters above the expected median values in all of the nine catchments. This resulted in deficits of snow-covered area of up to 83% in the Western Alps (catchment of Sesia, March 2022) and up to 61% in the Eastern Alps (Brenta, March 2022) compared to the long-term median. Although snow-cover data from optical satellite imagery do not contain information about snow depth and water content, in a preliminary qualitative analysis, the derived SLE dynamics show good agreement with the Standardized Snowpack Index (SSPI) which is based on the snow water equivalent (SWE). While the exact relationships between SLE, SWE, and runoff have to be explored further on the catchment basis, long-time series of SLE may have potential for use in drought early warning systems.