Scientific Committee on Antarctic Research

The Antarctic Ice Sheet is the largest potential contributor to future global sea level, with a maximum contribution of approximately 58 m. The flow of grounded ice towards the ocean is largely restricted by floating ice shelves, which fringe ~75% of the Antarctic coastline. This buttressing effect can be diminished or lost entirely following partial or complete ice-shelf disintegration events, leading to an acceleration of ice discharge. The vulnerability of ice shelves to fracture and disintegration is influenced by a range of factors, including the ponding of surface and subsurface meltwater, which can induce flexural stresses and promote fracture through the ice-shelf column.While the widespread extent of surface meltwater systems across numerous Antarctic ice shelves during the austral summer is now well documented, meltwater storage within the ice-shelf subsurface remains poorly understood. Liquid water can persist perennially beneath the ice-shelf surface if sufficiently insulated by surrounding and overlying layers of firn, snow, and/or ice. Due to their year-round persistence, buried meltwater lakes introduce a potential mechanism for hydrofracture outside of the melt season, with important implications for ice-shelf stability.In situ surveys in Antarctica are logistically challenging and limited in spatial extent, rendering spaceborne remote sensing an indispensable tool for monitoring ice-shelf processes at a continental scale. However, the growing volume of satellite observation poses data-analysis challenges typical of the ‘Big Data’ era; remote-sensing datasets are often high-dimensional, unstructured, and large in sample size, with rapidly increasing spatiotemporal coverage and low-cost availability. These characteristics limit the scalability of manual interpretation or traditional thresholding approaches for pan-Antarctic applications. In contrast, machine-learning methods are ideal for extracting patterns and features from large databases of satellite imagery. In light of this, machine learning offers great potential for the detection of subsurface meltwater across Antarctic ice shelves at a continental scale, if challenges relating to the sampling and labelling of training data, as well as class imbalance, are addressed carefully. An active learning strategy can help to reduce data redundancy and labelling requirements in deep learning, while also improving model performance in the presence of class imbalance. Here, we present a systematic training-data sampling strategy applied to all major Antarctic ice shelves. We employ a stratified random sampling approach to mitigate strong regional imbalances in data availability and create a curated training data subset that combines an equal number of random and expert-selected samples. This dataset is used to initialise an active learning framework for training a deep-learning model to detect subsurface lakes in Antarctica. We evaluate model performance across multiple configurations and present fine-tuning of model hyperparameters.

<strong class="journal-contentHeaderColor">Abstract.</strong> Identifying and monitoring unstable slopes is essential for preventing both direct and cascading disasters triggered by landslides. To this end, we introduce TerraTrack, an open-source, cloud-based, end-to-end optical feature tracking tool for slow-moving landslide detection and monitoring. The tool is designed to run on the Sentinel-2 Level 1 harmonized collection. Users can define the area of interest, automatically download and pre-process Sentinel-2 data, and compute displacements using different feature tracking techniques. Outputs include a landslide binary mask, velocity maps and time series. The tool can operate entirely in the Google Colaboratory cloud environment. Hence, it removes the need for local computational resources and for a fast internet connection, avoids software conflicts, and is accessible even to those with limited experience in Python programming. We validated the workflow on cases with independent displacement measurements, including the Slumgullion, Chaos Canyon, and Tessina-Lamosano landslides, showing that its results are consistent with independent estimates. Owing to its ease of use and versatility, the tool is a valuable resource for the multi-hazard and landslide communities, complementing InSAR for monitoring surface motion in space and time. The tool can estimate motion shortly after the satellite imagery is acquired, making it an asset for early warning systems that rely on time of failure estimates (i.e., inverse velocity) or predictive modelling of future motion, within the limitations of satellite-based approaches. Lastly, its capacity to identify unstable slopes can guide targeted, detailed investigations into landslide dynamics, enhancing situational awareness and supporting risk mitigation at scale.

The global ocean faces unprecedented challenges from overfishing, pollution, and climate change. The Central Arctic Ocean Fisheries Agreement is a rare, if not unprecedented, example of precautionary action in marine management. Further action is needed to address other forms of industrial activity in the region. Done well, this example can provide a model for sustainable ocean management around the world, based on sound evidence, inclusive governance, and long-term thinking.

ABSTRACT The value of the angles of the fields of view of collimated mobile detectors for sensing discrete sources of radiation of natural origin of potassium, uranium, thorium by isotopes 40K, 214Bi of the uranium decay chain, 208Tl of the thorium decay chain and technogenic iodine and caesium by isotopes 131I, 137Cs, 134Cs is substantiated. It was found that for the search for discrete sources of gamma radiation of anthropogenic origin, the field of view of the collimated detector is 49.590°, which allows to go beyond the 80% attenuation not higher than 79.2% − 77.3% for a height of 50 m. To search for discrete sources of gamma radiation of natural origin, the field of view angle is 37.382°. With variations in source depths of 0.15 m and 0.25 m, soil density of 2700 kg m−3 and 1600 kg m−3, survey heights of 10 m, 30 m, 50 m, and energies of the studied radionuclides, this allows to go beyond the 80% attenuation to levels that do not exceed 73.5% for a survey height of 10 m, 73.0% for a survey height of 30 m, 72.4% for a survey height of 50 m. A mathematical model of gamma radiation intensity attenuation at the boundary of the detector field of view angle compared to its centre was developed, taking into account: the location of the gamma radiation source under the soil surface and on the surface, the height of the detector, the field of view angle, the mass attenuation coefficients of air and soil, and their integrity. A criterion was developed to take into account the maximum velocity of the air carrier movement, taking into account the deformation of the detector field of view during one gamma-ray collection cycle, which allows taking into account the energy dependence of the field of view for a particular radionuclide.

Perennial Firn Aquifers (PFA&amp;#8217;s) facilitate meltwater storage within an ice sheet&amp;#8217;s firn layer. They have been extensively mapped across the Greenland Ice Sheet, largely using Operation Ice Bridge and Sentinel-1 data. However, in Antarctica, observations of PFA&amp;#8217;s are limited to the Antarctic Peninsula, where the combination of high accumulation and ablation aids in the formation and insulation of extensive sub-surface meltwater reservoirs. On ice shelves, PFA&amp;#8217;s have the potential to drive ice-shelf damage via hydrofracture, and it is therefore crucial that we have a better understanding of their presence beyond the Antarctic Peninsula.&amp;#160;To begin to improve our understanding for PFA&amp;#8217;s elsewhere in Antarctica, we conduct a study on the Nivlisen Ice Shelf, an ice-shelf often characterised by extensive surface meltwater networks in Dronning Maud Land, East Antarctica. In addition to high rates of ablation, Nivlisen Ice Shelf also experiences high accumulation rates, making the ice-shelf a good candidate for the formation of PFAs. To investigate this theory, we utilise a method previously applied on the Greenland Ice Sheet, and exploit the low backscatter values returned in C-band synthetic aperture radar (SAR) data to detect potential PFA&amp;#8217;s. C-band SAR data is obtained from Sentinel-1 and RADARSAT Constellation Mission (RCM), and is complemented with L-band SAR imagery. With both the NASA-ISRO Synthetic Aperture Radar (NISAR) and Copernicus ROSE-L satellites planned for future launches, we hope that our work will allow us to better understand the value of combined C- and L- band research for for studies of buried meltwater across both the Greenland and Antarctic Ice Sheets.&amp;#160;&amp;#160;

Abstract The relevance of education and outreach (E&amp;O) activities about the Antarctic Treaty has been recognized at the Antarctic Treaty Consultative Meetings (ATCM) and at the Committee for Environmental Protection (CEP). This study examines the key topics and the target audiences detailed in papers submitted to the ATCM on E&amp;O. Since the Antarctic Treaty entered into force in 1961, a total of 216 ATCM papers on E&amp;O have been produced. The number of papers has increased substantially since the mid-1990s. ‘Science’ (76.9%) and ‘Wildlife/Biodiversity/Environment’ (75.5%) were the most addressed topics in these papers, while the ‘Public’ (81.0%) and those attending ‘Schools’ (69.0%) are the main target audiences. ‘Science’ in ATCM papers increased ~120-fold from 1961–1997 to 2015–2023, while ATCM papers discussing engagement with the ‘Public’ increased ~40-fold during the same period. ‘Climate change’ was first mentioned in 2006, and the number of papers per year increased fourfold by 2015–2023. This study shows the increasing interest in E&amp;O through time, addressing key topics to relevant audiences related to the Antarctic region. From an educational perspective, attention should be paid to emerging topics (e.g. equity, diversity and inclusion), and the engagement of early-career professionals and educators should be made a priority.

Surface meltwater on Antarctic ice shelves is comprised of slush (saturated firn), and ponded water (lakes and streams). Often, slush forms as a precursor to ponded water, and its formation leads subsequently to water collecting in basins or flowing across ice shelf surfaces. Where slush and/or ponded water refreeze at the end of a melt season, the firn air content of ice shelves may be lowered. This can increase ice shelves&amp;#8217; susceptibility to future meltwater ponding, making them more vulnerable to potential hydrofracture and break-up. Slush and ponded water also have a lower albedo than snow or dry firn, further increasing ice-shelf surface melt under warmer climates. To date, most satellite-derived estimates of surface water on ice shelves have identified only ponded water, potentially underestimating the extent of surface meltwater. Here, we use a previously developed random forest classifier to produce a novel, continent-wide dataset of slush and ponded water extent across all Antarctic ice shelves between 2013 and 2021. Our dataset is comprised of monthly meltwater products for the austral summers (November-March where data availability allows), from which continent-wide, regional, and individual ice-shelf trends are investigated.The continent-wide total meltwater coverage (assessed between November and February) was greatest during January 2017, reaching 6078 km2. Notably, we find that including the slush extent in total meltwater calculations increases surface water extent by a mean of 56% during the melt-season peak (January). However, we identify marked inter-regional variation, with slush accounting for 71% of January&amp;#8217;s total surface meltwater extent in Dronning Maud Land, but only 46% in the Antarctic Peninsula. This indicates that until now, the extent of surface meltwater across Antarctica&amp;#8217;s ice shelves has been largely under-estimated on ice shelf, regional, and continent-wide scales, which has significant repercussions for calculations of the surface and sub-surface energy and mass balance of ice shelves, the long-term storage of meltwater on ice shelves, and predictions of future ice shelf stability.