Filling and drainage of a subglacial lake beneath the Flade Isblink ice cap, northeast Greenland

The generation, transport, storage and drainage of meltwater beneath the ice sheet play important roles in the Greenland ice sheet (GrIS) system. Active subglacial lakes, common features in Antarctica, have recently been detected beneath GrIS and may impact ice sheet hydrology. Despite their potential importance, few repeat subglacial lake filling and drainage events have been identified under Greenland Ice Sheet. Here we examine the surface elevation change of a collapse basin at the Flade Isblink ice cap, northeast Greenland, which formed due to sudden subglacial lake drainage in 2011. We estimate the subglacial lake volume evolution using multi-temporal ArcticDEM data and ICESat-2 altimetry data acquired between 2012 and 2021. Our long-term observations show that the subglacial lake was continuously filled by surface meltwater, with basin surface rising by up to 55 m during 2012–2021 and we estimate 138.2 × 106 m3 of meltwater was transported into the subglacial lake between 2012 and 2017. A second rapid drainage event occurred in late August 2019, which induced an abrupt ice dynamic response. Comparison between the two drainage events shows that the 2019 drainage released much less water than the 2011 event. We conclude that multiple factors, e.g., the volume of water stored in the subglacial lake and bedrock relief, regulate the episodic filling and drainage of the lake. By comparing the surface meltwater production and the subglacial lake volume change, we find only ~64 % of the surface meltwater successfully descended to the bed, suggesting potential processes such as meltwater refreezing and firn aquifer storage, need to be further quantified.

Potential technological solution for sampling the bottom sediments of the subglacial lake Vostok: relevance and formulation of investigation goals

The subglacial Lake Vostok in Antarctic is a unique natural phenomenon, its comprehensive study involves sampling of water and bottom surface rocks. For further study of the lake, it is necessary to drill a new access well and develop environmentally safe technologies for its exploration. This article discusses existing and potential technologies for sampling bottom surface rocks of subglacial lakes. All these technologies meet environmental safety requirements and are conducive for sampling. The authors have proposed an alternative technology, using a walking device, which, due to its mobility, enables selective sampling of rocks across a large area from a single access well. The principal issues, related to the implementation of the proposed technology, are investigated within this article. This report is prepared by a team of specialists with many years of experience in drilling at the Vostok Station in Antarctic and in experimental work on the design of equipment and non-standard means of mechanization for complicated mining, geological and climatic conditions.

Radiometric analysis of digitized Z-scope records in archival radar sounding film

The earliest airborne geophysical campaigns over Antarctica and Greenland in the 1960s and 1970s collected ice penetrating radar data on 35 mm optical film. Early subglacial topographic and englacial stratigraphic analyses of these data were foundational to the field of radioglaciology. Recent efforts to digitize and release these data have resulted in geometric and ice-thickness analysis that constrain subsurface change over multiple decades but stop short of radiometric interpretation. The primary challenge for radiometric analysis is the poorly-characterized compression applied to Z-scope records and the sparse sampling of A-scope records. Here, we demonstrate the information richness and radiometric interpretability of Z-scope records. Z-scope pixels have uncalibrated fast-time, slow-time, and intensity scales. We develop approaches for mapping each of these scales to physical units (microseconds, seconds, and signal to noise ratio). We then demonstrate the application of this calibration and analysis approach to a flight in the interior of East Antarctica with subglacial lakes and to a reflight of an East Antarctic ice shelf that was observed by both archival and modern radar. These results demonstrate the potential use of Z-scope signals to extend the baseline of radiometric observations of the subsurface by decades.

New large subglacial lake in Princess Elizabeth Land, East Antarctica, detected by airborne geophysical observations

Knowledge of subglacial lakes is important for understanding the stability of the Antarctica Ice Sheet (AIS) and its contribution to the global sea-level change. We designed an intensified airborne campaign to collect geophysical data in Princess Elizabeth Land (PEL), East Antarctica, during the 2015–2019 CHINARE expeditions. We developed an innovative method to build a set of evidence of a newly detected subglacial lake, Lake Zhongshan. Adaptive RES data analysis allowed us to detect the lake surface and extent. We quantified the lake depth and volume via gravity modeling. Another dataset collected at Lake Vostok provided the ground truth. The results revealed that Lake Zhongshan, located at 73°26'53"S, 80°30'39"E and ~3,603 m below surface, has an area of 328 ± 1 km2, making it the only one in PEL and the fifth largest in Antarctica. These findings are important for understanding subglacial hydrodynamics in PEL, as well as the stability of the AIS.

Evaluation of six geothermal heat flux maps for the Antarctic Lambert-Amery glacial system

Basal thermal conditions play an important role in ice sheet dynamics, and they are sensitive to geothermal heat flux (GHF). Here we estimate the basal thermal conditions, including basal temperature, basal melt rate, and friction heat underneath the Lambert-Amery glacier system in east Antarctica, using a combination of a forward model and an inversion from a 3D ice flow model. We assess the sensitivity and uncertainty of basal thermal conditions using six different GHFs. We evaluate the modelled results using all available observed subglacial lakes. There are very large differences in modelled spatial pattern of temperate basal conditions using the different GHFs. The two most-recent GHF fields inverted from aerial geomagnetic observations have higher values of GHF in the region, produce a larger warm-based area, and match the observed subglacial lakes better than the other GHFs. The fast flowing glacier region has a lower modelled basal friction coefficient, faster basal velocity, with higher basal frictional heating in the range of 50–2000 mW m−2 than the base under slower flowing glaciated areas. The modelled basal melt rate reaches ten to hundreds of mm per year locally in Lambert, Lepekhin and Kronshtadtskiy glaciers feeding the Amery ice shelf, and ranges from 0–5 mm yr−1 on the temperate base of the vast inland region.

Basal Water Storage Variations beneath Antarctic Ice Sheet Inferred from Multi-source Satellite Data

Antarctic basal water storage variations (BWSV) refer to the mass variations of liquid water beneath Antarctic ice sheet. Identifying these variations is critical to understand the behaviour of ice sheet, yet it is rarely accessible to direct observation. We presented a layered gravity density forward/inversion method for estimating Antarctic BWSV from multi- source satellite observation data, and relevant models. Results reveal spatial variability of BWSV with the mean rate of 43 ± 13 Gt/yr during 2003–2009, which is 21 Gt/yr lower than basal melting rate. This indicates that the basal meltwater beneath Antarctic ice sheet is decreasing with the rate of −21 ± 13 Gt/yr, accounting for 28 % of the mass balance rate (−76 Gt/yr, Shepherd et al. (2018)), and the basal water migrations between basal drainage systems and oceans is non-ignorable in estimating basal mass balance of Antarctic ice sheet. Similar spatial distribution of basal water increases regions and locations of active subglacial lakes indicates that basal water storage in most active subglacial lakes is increasing. In most region of Antarctic ice sheet except Amundsen Sea coast region, the comparison of spatial BWSV and ice velocity displays a positive correlation between considerable basal water increases and rapid/accelerated ice flows, which indicates that BWSV appear to have an important effect on ice flows. Accordingly, we infer that further enhanced flow velocities are expected if basal water continues to increase in these regions.

The subglacial landscape and hydrology of Antarctica mapped from space

<p><b>To narrow uncertainties in the Antarctic ice sheet's contribution to sea level rise, we present a collection of novel machine learning and automated satellite remote sensing methods which use ice surface observations to infer the subglacial nature of Antarctica. A super-resolution deep neural network called DeepBedMap was designed and trained to produce a high-resolution (250 m) bed elevation model of Antarctica called DeepBedMap_DEM that preserves bed roughness details useful for catchment- to continent-scale ice sheet modelling. This DeepBedMap_DEM is compared with a smoother, medium-resolution (500 m) BedMachine topography in a basal inversion experiment over Pine Island Glacier, with results motivating more research into the interacting roles of subglacial hydrology which influences skin drag and high resolution bed topographies which influences form drag. Active subglacial lakes in Antarctica were mapped using an unsupervised density-based classification method on ICESat-2 point cloud data from 2018-2020, yielding 194 active subglacial lakes, including 36 new lakes in the 86-88°S area not detected by the previous ICESat (2003-2009) mission. This thesis showcases both the rich diversity in subglacial landscapes and the dynamic nature of subglacial hydrology in Antarctica, forming a foundation enabling the accurate modelling of overland ice flow in critical regions of the vulnerable West Antarctic Ice Sheet.</b></p> <p>Plain language summaryAntarctica has a lot of ice, but we're unsure how fast ice can slide into the sea and cause water to go up in beaches around the world. So we teach computers to solve hard math problems that tell us how fast sea water might go up. These computers are fed with lots of pictures taken from cameras up in the sky and space. Ice sits on top of rock in Antarctica, and with practice, the computers get pretty good at telling us how high and bumpy the rock is. The rock under the ice appears quite bumpy, and ice probably doesn't like sliding over bumpy rocks since it's rough. Sometimes though, ice may not mind sliding over rough bits of rock if the rock moves along with it, or if water gets in between the rock and ice to makes things slippery, but we ask our smart computers to be sure. There are also lasers from space shooting down at earth and bouncing back to tell us how ice in Antarctica is going up or down. Once in a while, they tell us that ice in parts of Antarctica moved up or down a bit too fast. Smart people think these are lakes hiding under the ice, filling up with water or draining, and we found many of these lakes over Antarctica, especially in an area called Whillans Ice Stream on the Siple Coast. We hope that the computers can keep learning faster because there's a lot of pictures showing ice moving pretty fast, and it doesn't look like there's much time before a big chunk of ice might break away in Antarctica and flood beaches around the world.</p> <p>Code availabilityPython code for reproducing the methods in this thesis are publicly available at https://github.com/weiji14/deepbedmap for Chapter 2 (DeepBedMap), https://github.com/weiji14/pyissm for Chapter 3 (Basal inversion); and https://github.com/weiji14/deepicedrain for Chapter 4 (ICESat-2 subglacial lakes).</p>

The subglacial landscape and hydrology of Antarctica mapped from space

<p><b>To narrow uncertainties in the Antarctic ice sheet's contribution to sea level rise, we present a collection of novel machine learning and automated satellite remote sensing methods which use ice surface observations to infer the subglacial nature of Antarctica. A super-resolution deep neural network called DeepBedMap was designed and trained to produce a high-resolution (250 m) bed elevation model of Antarctica called DeepBedMap_DEM that preserves bed roughness details useful for catchment- to continent-scale ice sheet modelling. This DeepBedMap_DEM is compared with a smoother, medium-resolution (500 m) BedMachine topography in a basal inversion experiment over Pine Island Glacier, with results motivating more research into the interacting roles of subglacial hydrology which influences skin drag and high resolution bed topographies which influences form drag. Active subglacial lakes in Antarctica were mapped using an unsupervised density-based classification method on ICESat-2 point cloud data from 2018-2020, yielding 194 active subglacial lakes, including 36 new lakes in the 86-88°S area not detected by the previous ICESat (2003-2009) mission. This thesis showcases both the rich diversity in subglacial landscapes and the dynamic nature of subglacial hydrology in Antarctica, forming a foundation enabling the accurate modelling of overland ice flow in critical regions of the vulnerable West Antarctic Ice Sheet.</b></p> <p>Plain language summaryAntarctica has a lot of ice, but we're unsure how fast ice can slide into the sea and cause water to go up in beaches around the world. So we teach computers to solve hard math problems that tell us how fast sea water might go up. These computers are fed with lots of pictures taken from cameras up in the sky and space. Ice sits on top of rock in Antarctica, and with practice, the computers get pretty good at telling us how high and bumpy the rock is. The rock under the ice appears quite bumpy, and ice probably doesn't like sliding over bumpy rocks since it's rough. Sometimes though, ice may not mind sliding over rough bits of rock if the rock moves along with it, or if water gets in between the rock and ice to makes things slippery, but we ask our smart computers to be sure. There are also lasers from space shooting down at earth and bouncing back to tell us how ice in Antarctica is going up or down. Once in a while, they tell us that ice in parts of Antarctica moved up or down a bit too fast. Smart people think these are lakes hiding under the ice, filling up with water or draining, and we found many of these lakes over Antarctica, especially in an area called Whillans Ice Stream on the Siple Coast. We hope that the computers can keep learning faster because there's a lot of pictures showing ice moving pretty fast, and it doesn't look like there's much time before a big chunk of ice might break away in Antarctica and flood beaches around the world.</p> <p>Code availabilityPython code for reproducing the methods in this thesis are publicly available at https://github.com/weiji14/deepbedmap for Chapter 2 (DeepBedMap), https://github.com/weiji14/pyissm for Chapter 3 (Basal inversion); and https://github.com/weiji14/deepicedrain for Chapter 4 (ICESat-2 subglacial lakes).</p>