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Some of the highest specific mass change rates in Antarctica are reported for the Antarctic Peninsula. However, the existing estimates for the northern Antarctic Peninsula (<70 ∘ S) are either spatially limited or are affected by considerable uncertainties. The complex topography, frequent cloud cover, limitations in ice thickness information, boundary effects, and uncertain glacial–isostatic adjustment estimates affect the ice sheet mass change estimates using altimetry, gravimetry, or the input-output method. Within this study, the first assessment of the geodetic mass balance throughout the ice sheet of the northern Antarctic Peninsula is carried out employing bi-static synthetic aperture radar (SAR) data from the TanDEM-X satellite mission. Repeat coverages from the austral winters of 2013 and 2017 are employed. Overall, coverage of 96.4 % of the study area by surface elevation change measurements and a total mass budget of -24.1±2.8 Gt a -1 are revealed. The spatial distribution of the surface elevation and mass changes points out that the former ice shelf tributary glaciers of the Prince Gustav Channel, Larsen A and B, and Wordie ice shelves are the hotspots of ice loss in the study area and highlights the long-lasting dynamic glacier adjustments after the ice shelf break-up events. The highest mass change rate is revealed for the Airy–Seller–Fleming glacier system at -4.9±0.6 Gt a -1 , and the highest average surface elevation change rate of -2.30±0.03 m a -1 is observed at Drygalski Glacier. The comparison of the ice mass budget with anomalies in the climatic mass balance indicates, that for wide parts of the southern section of the study area, the mass changes can be partly attributed to changes in the climatic mass balance. However, imbalanced high ice discharge drives the overall ice loss. The previously reported connection between mid-ocean warming along the southern section of the west coast and increased frontal glacier recession does not repeat in the pattern of the observed glacier mass losses, excluding in Wordie Bay. The obtained results provide information on ice surface elevation and mass changes for the entire northern Antarctic Peninsula on unprecedented spatially detailed scales and with high precision and will be beneficial for subsequent analysis and modeling. [ABSTRACT FROM AUTHOR]

The fracturing of glaciers and ice shelves in Antarctica influences their dynamics and stability. Hence, data on the evolving distribution of crevasses are required to better understand the evolution of the ice sheet, though such data have traditionally been difficult and time-consuming to generate. Here, we present an automated method of mapping crevasses on grounded and floating ice with the application of convolutional neural networks to Sentinel-1 synthetic aperture radar backscatter data. We apply this method across Antarctica to images acquired between 2015 and 2022, producing a 7.5-year record of composite fracture maps at monthly intervals and 50 m spatial resolution and showing the distribution of crevasses around the majority of the ice sheet margin. We develop a method of quantifying changes to the density of ice shelf fractures using a time series of crevasse maps and show increases in crevassing on Thwaites and Pine Island ice shelves over the observational period, with observed changes elsewhere in the Amundsen Sea dominated by the advection of existing crevasses. Using stress fields computed using the BISICLES ice sheet model, we show that much of this structural change has occurred in buttressing regions of these ice shelves, indicating a recent and ongoing link between fracturing and the developing dynamics of the Amundsen Sea sector. [ABSTRACT FROM AUTHOR]

Wilkes Land, East Antarctica, has been losing mass at an accelerating rate over recent decades in response to enhanced oceanic forcing. Overlying the Aurora Subglacial Basin, it has been referred to as the "weak underbelly" of the East Antarctic Ice Sheet and is drained by several major outlet glaciers. Despite their potential importance, few of these glaciers have been studied in detail. This includes the six outlet glaciers which drain into Vincennes Bay, a region recently discovered to have the warmest intrusions of modified Circumpolar Deep Water (mCDW) ever recorded in East Antarctica. Here, we use satellite imagery; differential synthetic aperture radar interferometry (DInSAR); and remotely sensed datasets of ice-surface velocity, ice-surface elevation and grounding line position to investigate ice dynamics between 1963 and 2022. Our results support previous observations of extensive grounding line retreat at Vanderford Glacier, measured at 18.6 km between 1996 and 2020. The persistent grounding line retreat, averaging 0.8 km yr -1 , places Vanderford Glacier as the fastest retreating glacier in East Antarctica, and the third fastest in Antarctica, across decadal timescales. Such rapid retreat is consistent with the hypothesis that warm mCDW is able to access deep cavities formed below the Vanderford Ice Shelf, driving high rates of basal melting close to the grounding line. With a retrograde slope observed inland along the Vanderford Trench, such oceanic forcing may have significant implications for the future stability of Vanderford Glacier. [ABSTRACT FROM AUTHOR]

Exact information on the calving front positions of marine- or lake-terminating glaciers is a fundamental glacier variable for analyzing ongoing glacier change processes and assessing other variables like frontal ablation rates. In recent years, researchers started implementing algorithms that can automatically detect the calving fronts on satellite imagery. Most studies use optical images, as calving fronts are often easy to distinguish in these images due to the sufficient spatial resolution and the presence of different spectral bands, allowing the separation of ice features. However, detecting calving fronts on synthetic aperture radar (SAR) images is highly desirable, as SAR images can also be acquired during the polar night and are independent of weather conditions (e.g., cloud cover), facilitating year-round monitoring worldwide. In this paper, we present a benchmark dataset of SAR images from multiple regions of the globe with corresponding manually defined labels providing information on the position of the calving front (https://doi.org/10.1594/PANGAEA.940950). With this dataset, different approaches for the detection of glacier calving fronts can be implemented, tested, and their performance fairly compared so that the most effective approach can be determined. The dataset consists of 681 samples, making it large enough to train deep learning segmentation models. It is the first dataset to provide long-term glacier calving front information from multi-mission data. As the dataset includes glaciers from Antarctica, Greenland, and Alaska, the wide applicability of models trained and tested on this dataset is ensured. The test set is independent of the training set so that the generalization capabilities of the models can be evaluated. We provide two sets of labels: one binary segmentation label to discern the calving front from the background, and one label for multi-class segmentation of different landscape classes. Unlike other calving front datasets, the presented dataset contains not only the labels but also the corresponding preprocessed and geo-referenced SAR images as PNG files. The ease of access to the dataset will allow scientists from other fields, such as data science, to contribute their expertise. With this benchmark dataset, we enable comparability between different front detection algorithms and improve the reproducibility of front detection studies. Moreover, we present one baseline model for each kind of label type. Both models are based on the U-Net, one of the most popular deep learning segmentation architectures. In the following two post-processing procedures, the segmentation results are converted into 1-pixel-wide front delineations. By providing both types of labels, both approaches can be used to address the problem. To assess the performance of different models, we suggest first reviewing the segmentation results using the recall, precision, F1 score, and the Jaccard index. Second, the front delineation can be evaluated by calculating the mean distance error to the labeled front. The presented vanilla models provide a baseline of 150 m ± 24 m mean distance error for the Mapple Glacier in Antarctica and 840 m ± 84 m for the Columbia Glacier in Alaska, which has a more complex calving front, consisting of multiple sections, compared with a laterally well constrained, single calving front of Mapple Glacier. [ABSTRACT FROM AUTHOR]

Surface meltwater drains on several Antarctic ice shelves, resulting in surface and sub-surface lakes that are potentially critical for the ice shelf collapse. Despite these phenomena, our understanding and assessment of the drainage and refreezing of these lakes is limited, mainly due to lack of field observations and to the limitations of optical satellite imagery during polar night and in cloudy conditions. This paper explores the potential of backscatter intensity and of interferometric coherence and phase from synthetic aperture radar (SAR) imagery as an alternative to assess the dynamics of meltwater lakes. In four case study regions over Amery and Roi Baudouin ice shelves, East Antarctica, we examine spatial and temporal variations in SAR backscatter intensity and interferometric (InSAR) coherence and phase over several lakes derived from Sentinel-1A/B C-band SAR imagery. Throughout the year, the lakes are observed in a completely frozen state, in a partially frozen state with a floating ice lid and as open-water lakes. Our analysis reveals that the meltwater lake delineation is challenging during the melting period when the contrast between melting snow and lakes is indistinguishable. Despite this finding, we show using a combination of backscatter and InSAR observations that lake dynamics can be effectively captured during other non-summertime months. Moreover, our findings highlight the utility of InSAR-based observations for discriminating between refrozen ice and sub-surface meltwater and indicate the potential for phase-based detection and monitoring of rapid meltwater drainage events. The potential of this technique to monitor these meltwater change events is, however, strongly determined by the satellite revisit interval and potential changes in scattering properties due to snowfall or melt events. [ABSTRACT FROM AUTHOR]

Iceberg calving is the main process that facilitates the dynamic mass loss of ice sheets into the ocean, which accounts for approximately half of the mass loss of the Antarctic ice sheet. Fine-scale calving variability observations can help reveal the calving mechanisms and identify the principal processes that influence how the changing climate affects global sea level through the ice shelf buttressing effect on the Antarctic ice sheet. Iceberg calving from entire ice shelves for short time intervals or from specific ice shelves for long time intervals has been monitored before, but there is still a lack of consistent, long-term, and high-precision records on independent calving events for all of the Antarctic ice shelves. In this study, a 15-year annual iceberg calving product measuring every independent calving event larger than 1 km2 over all of the Antarctic ice shelves that occurred from August 2005 to August 2020 was developed based on 16 years of continuous satellite observations. First, the expansion of the ice shelf frontal coastline was simulated according to ice velocity; following this, the calved areas, which are considered to be the differences between the simulated coastline, were manually delineated, and the actual coastline was derived from the corresponding satellite imagery, based on multisource optical and synthetic aperture radar (SAR) images. The product provides detailed information on each calving event, including the associated year of occurrence, area, size, average thickness, mass, recurrence interval, and measurement uncertainties. A total of 1975 annual calving events larger than 1 km2 were detected on the Antarctic ice shelves from August 2005 to August 2020. The average annual calved area was measured as 3549.1 km2 with an uncertainty value of 14.3 km2 , and the average calving rate was measured as 770.3 Gtyr-1 with an uncertainty value of 29.5 Gtyr-1. The number of calving events, calved area, and calved mass fluctuated moderately during the first decade, followed by a dramatic increase from 2015/2016 to 2019/2020. During the dataset period, large ice shelves, such as the Ronne–Filchner and Ross ice shelves, advanced with low calving frequency, whereas small- and medium-sized ice shelves retreated and calved more frequently. Iceberg calving of ice shelves is most prevalent in West Antarctica, followed by the Antarctic Peninsula and Wilkes Land in East Antarctica. The annual iceberg calving event dataset of Antarctic ice shelves provides consistent and precise calving observations with the longest time coverage. The dataset provides multidimensional variables for each independent calving event that can be used to study detailed spatial–temporal variations in Antarctic iceberg calving. The dataset can also be used to study ice sheet mass balance, calving mechanisms, and responses of iceberg calving to climate change. The dataset, entitled "Annual iceberg calving dataset of the Antarctic ice shelves (2005–2020)", is shared via the National Tibetan Plateau Data Center: 10.11888/Glacio.tpdc.271250 (Qi et al., 2021). In addition, the average annual calving rate of 18.4±6.7 Gtyr-1 for calving events smaller than 1 km2 of the Antarctic ice shelves and the calving rate of 166.7±15.2 Gtyr-1 for the marine-terminating glaciers were estimated. [ABSTRACT FROM AUTHOR]

Iceberg calving is the main process that facilitates the dynamic mass loss of ice sheets into the ocean, which accounts for approximately half of the net mass loss of all Antarctic ice shelves. Fine-scale calving variability observations can help reveal the involved calving mechanisms and identify the principal processes that influence how the changing climate affects the mass loss of ice sheets. Iceberg calving from specific ice shelves or regions has been monitored before, but there is still a lack of consistent, long-term and high-precision records on independent calving events for all Antarctic ice shelves. In this study, we developed a circum-Antarctic annual iceberg calving product measuring every independent calving event larger than 1 km2 that occurred from August 2005 to August 2019. We first simulated the expansion of the coastline according to ice velocity, and then manually delineated the calved areas, which are considered to be the differences between the simulated coastline and the actual coastline derived from the corresponding satellite imagery, based on 15 years of continuous multisource optical and synthetic aperture radar images. This product provides detailed information on each calving event, including the associated year of occurrence, area, size, average thickness, mass, recurrence interval, type, and measurement uncertainties. In total, 1786 annual calving events occurred on the Antarctic ice shelves from August 2005 to August 2019. The average annual calving area was measured as 3411.4 km2 with an uncertainty value of 17.1 km2, and the average calving rate was measured as 771.1 Gt/yr with an uncertainty value of 10.2 Gt/yr. The calving frequency, area, and mass fluctuated moderately during the first decade, followed by a dramatic increase from 2015/16 to 2018/19. During the dataset period, large ice shelves, such as the Ronne-Filchner, Ross and Amery Ice Shelves, advanced with low calving frequency, while small and medium-sized ice shelves retreated and calved more frequently. Iceberg calving is most prevalent in West Antarctica, followed by the Antarctic Peninsula and Wilkes Land in East Antarctica. The annual circum-Antarctic iceberg calving dataset provides consistent and precise calving observations with the longest time coverage. The dataset provides multidimensional variables for each independent calving event that can be used to study detailed spatiotemporal variations in Antarctic iceberg calving. The dataset can also be used to study ice sheet mass balance, calving mechanisms and the responses of iceberg calving to climate change. The dataset is shared via Global Change Data Repository (href="http://www.geodoi.ac.cn/WebEn/doi.aspx?Id=1516), and entitled Annual iceberg calving dataset of the Antarctic ice shelves (2005-2019) with DOI: https://doi.org/10.3974/geodb.2020.04.09.V1. [ABSTRACT FROM AUTHOR]

We present a new, fully automated method of mapping the Antarctic Ice Sheet's grounding zone using a repeat-track analysis and crossover analysis of newly acquired ICESat-2 laser altimeter data. We map the position of the landward limit of tidal flexure and the inshore limit of hydrostatic equilibrium, as demonstrated over the mountainous and hitherto difficult to survey grounding zone of Larsen C Ice Shelf. Since the start of data acquisition in 2018, our method has already achieved a near 9-fold increase in the number of grounding zone observations compared with ICESat, which operated between 2003 and 2009. We have improved coverage in particular over the previously poorly mapped the Bawden and Gipps ice rises and Hearst Island. Acting as a reliable proxy for the grounding line, which cannot be directly imaged by satellites, our ICESat-2-derived landward limit of tidal flexure locations agrees well with independently obtained measurements, with a mean absolute difference and standard deviation of 0.39 and 0.32 km, respectively, compared to interferometric synthetic-aperture-radar-based observations. Our results demonstrate the efficiency, density, and high spatial accuracy with which ICESat-2 can image complex grounding zones and its clear potential for future mapping of the pan-ice sheet grounding zone. [ABSTRACT FROM AUTHOR]

Differential interferometric synthetic aperture radar (DInSAR) is an essential tool for detecting ice-sheet motion near Antarctica's oceanic margin. These space-borne measurements have been used extensively in the past to map the location and retreat of ice-shelf grounding lines as an indicator for the onset of marine ice-sheet instability and to calculate the mass balance of ice sheets and individual catchments. The main difficulty in interpreting DInSAR is that images originate from a combination of several SAR images and do not indicate instantaneous ice deflection at the times of satellite data acquisitions. Here, we combine the sub-centimetre accuracy and spatial benefits of DInSAR with the temporal benefits of tide models to infer the spatio-temporal dynamics of ice–ocean interaction during the times of satellite overpasses. We demonstrate the potential of this synergy with TerraSAR-X data from the almost-stagnant southern McMurdo Ice Shelf (SMIS). We then validate our algorithm with GPS data from the fast-flowing Darwin Glacier, draining the Antarctic Plateau through the Transantarctic Mountains into the Ross Sea. We are able to reconstruct DInSAR-derived vertical displacements to 7 mm mean absolute residual error and generally improve traditional tide-model output by up to 39 % from 10.8 to 6.7 cm RMSE against GPS data from areas where ice is in local hydrostatic equilibrium with the ocean and by up to 74 % from 21.4 to 5.6 cm RMSE against GPS data in feature-rich coastal areas where tide models have not been applicable before. Numerical modelling then reveals Young's modulus of E=1.0±0.56 GPa and an ice viscosity of ν=10±3.65 TPa s when finite-element simulations of tidal flexure are matched to 16 d of tiltmeter data, supporting the hypothesis that strain-dependent anisotropy may significantly decrease effective viscosity compared to isotropic polycrystalline ice on large spatial scales. Applications of our method include the following: refining coarsely gridded tide models to resolve small-scale features at the spatial resolution and vertical accuracy of SAR imagery, separating elastic and viscoelastic contributions in the satellite-derived flexure measurement, and gaining information about large-scale ice heterogeneity in Antarctic ice-shelf grounding zones, the missing key to improving current ice-sheet flow models. The reconstruction of the individual components forming DInSAR images has the potential to become a standard remote-sensing method in polar tide modelling. Unlocking the algorithm's full potential to answer multi-disciplinary research questions is desired and demands collaboration within the scientific community. [ABSTRACT FROM AUTHOR]

Englacial layers in Antarctica and Greenland are indicators of the dynamic, rheological, and subglacial configuration of the ice sheets. Airborne radar sounder data is currently the primary remote sensing solution for directly observing englacial layers and imaging englacial structures at the glacier-catchment to ice-sheet scale. Traditional along-track synthetic aperture (SAR) processing can limit the detectability and interpretability of englacial layer geometry due to destructive interference in the processed signal. This reflection loss can destroy layer signals and obfuscate automatic or manual tracing and interpretation.To address this challenge, we provide a reconstruction algorithm to address the problem of destructive phase interference during the radargram formation. We develop and apply a novel SAR processor optimized for layer detection that enhances the Signal-to-Noise ratio of specular reflectors of any steepness. The algorithm also enables the automatic estimation of layer slope. Notably, this approach does not require layers to be long or continuous to produce usable slope fields, overcoming limitations of previous approaches developed for shallower and slower-flowing areas with intact layers. We illustrate the application of this new processing approach to create 2D slope fields for inverse modelling to constrain bed slipperiness flow history in ice sheet models using data acquired in by the British Antarctic Survey (BAS) Polarimetric radar Airborne Science Instrument (PASIN) in the Institute Ice Stream catchment of West Antarctica. [ABSTRACT FROM AUTHOR]