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Antarctica is of great importance in terms of global warming, the sustainability of resources, and the conservation of biodiversity. However, due to 99.66% of the continent being covered in ice and snow, geological research and geoscientific study in Antarctica face huge challenges. Geophysical surveys play a crucial role in enhancing comprehension of the fundamental structure of Antarctica. This study used bibliometric analysis to analyze citation data retrieved from the Web of Science for the period from 1982 to 2022 with geophysical research on Antarctica as the topic. According to the analysis results, the amount of Antarctic geophysical research has been steadily growing over the past four decades as related research countries/regions have become increasingly invested in issues pertaining to global warming and sustainability, and international cooperation is in sight. Moreover, based on keyword clustering and an analysis of highly cited papers, six popular research topics have been identified: Antarctic ice sheet instability and sea level change, Southern Ocean and Sea Ice, tectonic activity of the West Antarctic rift system, the paleocontinental rift and reorganization, magmatism and volcanism, and subglacial lakes and subglacial hydrology. This paper provides a detailed overview of these popular research topics and discusses the applications and advantages of the geophysical methods used in each field. Finally, based on keywords regarding abrupt changes, we identify and examine the thematic evolution of the nexus over three consecutive sub-periods (i.e., 1990–1995, 1996–2005, and 2006–2022). The relevance of using geophysics to support numerous and diverse scientific activities in Antarctica becomes very clear after analyzing this set of scientific publications, as is the importance of using multiple geophysical methods (satellite, airborne, surface, and borehole technology) to revolutionize the acquisition of new data in greater detail from inaccessible or hard-to-reach areas. Many of the advances that they have enabled be seen in the Antarctic terrestrial areas (detailed mapping of the geological structures of West and East Antarctica), ice, and snow (tracking glaciers and sea ice, along with the depth and features of ice sheets). These valuable results help identify potential future research opportunities in the field of Antarctic geophysical research and aid academic professionals in keeping up with recent advances. [ABSTRACT FROM AUTHOR]

Antarctic basal water storage variation (BWSV) refers to mass changes of basal water beneath the Antarctic ice sheet (AIS). Identifying these variations is critical for understanding Antarctic basal hydrology variations and basal heat conduction, yet they are rarely accessible due to a lack of direct observation. This paper proposes a layered gravity density forward/inversion iteration method to investigate Antarctic BWSV based on multi-source satellite observations and relevant models. During 2003–2009, BWSV increased at an average rate of 43 ± 23 Gt/yr, which accounts for 29% of the previously documented total mass loss rate (−76 ± 20 Gt/yr) of AIS. Major uncertainty arises from satellite gravimetry, satellite altimetry, the glacial isostatic adjustment (GIA) model, and the modelled basal melting rate. We find that increases in basal water mainly occurred in regions with widespread active subglacial lakes, such as the Rockefeller Plateau, Siple Coast, Institute Ice Stream regions, and marginal regions of East Antarctic Ice Sheet (EAIS), which indicates the increased water storage in these active subglacial lakes, despite the frequent water drainage events. The Amundsen Sea coast experienced a significant loss during the same period, which is attributed to the basal meltwater discharging into the Amundsen Sea through basal channels. [ABSTRACT FROM AUTHOR]

Antarctica is covered by a thick ice sheet, and the application of geophysical methods is necessary to image the subglacial structures for studying the hydrologic systems and tectonic deformations in the Antarctic continent. The magnetotelluric (MT) method is one of the best approaches to obtain the subglacial electrical resistivities. However, only a very small volume of data has been collected so far in Antarctica using this method. In this paper, we report on a broadband MT profile collected at 10 sites in the south of the Chinese Zhongshan Station at Prydz Bay, and a 3D resistivity model was constructed by inversion of these data. This 3D model shows two low resistivity zones at a depth shallower than 6 km. They are consistent with the low-velocity zones in the previous shear-wave model and can be interpreted as the result of interconnected fluids associated with a downward migration of subglacial water. In addition, a distinct eastward dipping low resistivity zoneis present in the crust, which extends from the top surface to the lower crust. Since its location coincides with the highly positive magnetization named Amery Lineament, it is proposed that this eastward dipping low resistivity zoneextending in the entire crust probably reveals the geometry structure of the Amery Lineament at depth. Besides, it can be inferred from this new 3D resistivity model that the Amery Lineament is at least a crustal-scale structure, which probably outcrops on the land surface but was covered by the ice sheets in the study area. [ABSTRACT FROM AUTHOR]

The seasonal temperature trends and ice phenology in the Great Slave Lake (GSL) are significantly influenced by inflow from the Slave River. The river undergoes a sequence of mechanical break-ups all the way to the GSL, initiating the GSL break-up process. Additionally, upstream water management practices impact the discharge of the Slave River and, consequently, the ice break-up of the GSL. Therefore, monitoring the break-up process at the Slave River Delta (SRD), where the river meets the lake, is crucial for understanding the cascading effects of upstream activities on GSL ice break-up. This research aimed to use Random Forest (RF) models to monitor the ice break-up processes at the SRD using a combination of satellite images with relatively high spatial resolution, including Landsat-5, Landsat-8, Sentinel-2a, and Sentinel-2b. The RF models were trained using selected training pixels to classify ice, open water, and cloud. The onset of break-up was determined by data-driven thresholds on the ice fraction in images with less than 20% cloud coverage. Analysis of break-up timing from 1984 to 2023 revealed a significant earlier trend using the Mann–Kendall test with a p-value of 0.05. Furthermore, break-up data in recent years show a high degree of variability in the break-up rate using images in recent years with better temporal resolution. [ABSTRACT FROM AUTHOR]

With the increasing availability of SAR imagery in recent years, more research is being conducted using deep learning (DL) for the classification of ice and open water; however, ice and open water classification using conventional DL methods such as convolutional neural networks (CNNs) is not yet accurate enough to replace manual analysis for operational ice chart mapping. Understanding the uncertainties associated with CNN model predictions can help to quantify errors and, therefore, guide efforts on potential enhancements using more–advanced DL models and/or synergistic approaches. This paper evaluates an approach for estimating the aleatoric uncertainty [a measure used to identify the noise inherent in data] of CNN probabilities to map ice and open water with a custom loss function applied to RADARSAT–2 HH and HV observations. The images were acquired during the 2014 ice season of Lake Erie and Lake Ontario, two of the five Laurentian Great Lakes of North America. Operational image analysis charts from the Canadian Ice Service (CIS), which are based on visual interpretation of SAR imagery, are used to provide training and testing labels for the CNN model and to evaluate the accuracy of the model predictions. Bathymetry, as a variable that has an impact on the ice regime of lakes, was also incorporated during model training in supplementary experiments. Adding aleatoric loss and bathymetry information improved the accuracy of mapping water and ice. Results are evaluated quantitatively (accuracy metrics) and qualitatively (visual comparisons). Ice and open water scores were improved in some sections of the lakes by using aleatoric loss and including bathymetry. In Lake Erie, the ice score was improved by ∼2 on average in the shallow near–shore zone as a result of better mapping of dark ice (low backscatter) in the western basin. As for Lake Ontario, the open water score was improved by ∼6 on average in the deepest profundal off–shore zone. [ABSTRACT FROM AUTHOR]

Subglacial water bodies are critical components in analyzing the instability of the Antarctic ice sheet. Their detection and identification normally rely on geophysical and remote sensing methods such as airborne radar echo sounding (RES), ground seismic, and satellite/airborne altimetry and gravity surveys. In particular, RES surveys are able to detect basal terrain with a relatively high accuracy that can assist with the mapping of subglacial hydrology systems. Traditional RES processing methods for the identification of subglacial water bodies mostly rely on their brightness in radargrams and hydraulic flatness. In this study, we propose an automatic method with the main objective to differentiate the basal materials by quantitatively evaluating the shape of the A-scope waveform near the basal interface in RES radargrams, which has been seldom investigated. We develop an automatic algorithm mainly based on the traditional short-time Fourier transform (STFT) to quantify the shape of the A-scope waveform in radargrams. Specifically, with an appropriate window width applied on the main peak of each A-scope waveform in the RES radargram, STFT shows distinct and contrasting frequency responses at the ice-water interface and ice-rock interface, which is largely dependent upon their different reflection characteristics at the basal interface. We apply this method on 882 RES radargrams collected in the Antarctic's Gamburtsev Province (AGAP) in East Antarctica. There are 8822 identified A-scopes with the calculated detection value larger than the set threshold, out of the overall 1,515,065 valid A-scopes in these 882 RES radargrams. Although these identified A-scopes only takes 0.58% of the overall A-scope population, they show exceptionally continuous distribution to represent the subglacial water bodies. Through a comprehensive comparison with existing inventories of subglacial lakes, we successfully verify the validity and advantages of our method in identifying subglacial water bodies using the detection probability for other basal materials of theoretically the highest along-track resolution. The frequency signature obtained by the proposed joint time–frequency analysis provides a new corridor of investigation that can be further expanded to multivariable deep learning approaches for subglacial and englacial material characterization, as well as subglacial hydrology mapping. [ABSTRACT FROM AUTHOR]

In this study, elevation change and surface morphology of CookE2, one of the most active subglacial lakes in East Antarctica, were analyzed by using Differential Interferometric Synthetic Aperture Radar (DInSAR) and a newly adapted Time-Segmented Persistent Scatterer Interferometric Synthetic Aperture Radar (TS-PSInSAR) techniques. Firstly, several DInSAR pairs were used to study the surface morphology of the subglacial lake during the rapid discharge event in 2007 and the subsequent recharge in 2010 by using ALOS PALSAR data and the continuous recharge from 2018 to 2020 by using Sentinel-1 SAR data. For time-series observation from 2018 to 2020, however, simple integration of DInSAR deviates largely from the satellite altimeter data because errors from the horizontal flow of the surrounding ice field or atmospheric phase accumulate. Conventional PSInSAR deviates from the altimeter data if the LOS displacement exceeds 300 mm, i.e., approximately 1/4 of the slant range resolution of the Sentinel-1 SAR in Interferometric Wide-swath (IW) mode, during the time window. Therefore, a series of Time-Segmented PSInSAR with a 4-month time window could accurately distinguish 1.10 ± 0.01 m/year of highly linear (R2 = 0.99) surface rise rate of CookE2 and 0.63 m/year of horizontal deformation rate of the surrounding ice field from 2018 to 2020. [ABSTRACT FROM AUTHOR]