Articles | Volume 16, issue 2
https://doi.org/10.5194/tc-16-737-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-16-737-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
03 Mar 2022
Research article |
| 03 Mar 2022
| 03 Mar 2022
Overestimation and adjustment of Antarctic ice flow velocity fields reconstructed from historical satellite imagery
Center for Spatial Information Science and Sustainable Development
Applications, Tongji University, Shanghai, China
College of Surveying and Geo-Informatics, Tongji University, Shanghai,
China
Yuan Cheng
CORRESPONDING AUTHOR
Center for Spatial Information Science and Sustainable Development
Applications, Tongji University, Shanghai, China
College of Surveying and Geo-Informatics, Tongji University, Shanghai,
China
Haotian Cui
Center for Spatial Information Science and Sustainable Development
Applications, Tongji University, Shanghai, China
College of Surveying and Geo-Informatics, Tongji University, Shanghai,
China
Menglian Xia
Center for Spatial Information Science and Sustainable Development
Applications, Tongji University, Shanghai, China
College of Surveying and Geo-Informatics, Tongji University, Shanghai,
China
Xiaohan Yuan
Center for Spatial Information Science and Sustainable Development
Applications, Tongji University, Shanghai, China
College of Surveying and Geo-Informatics, Tongji University, Shanghai,
China
Zhen Li
Center for Spatial Information Science and Sustainable Development
Applications, Tongji University, Shanghai, China
College of Surveying and Geo-Informatics, Tongji University, Shanghai,
China
Shulei Luo
Center for Spatial Information Science and Sustainable Development
Applications, Tongji University, Shanghai, China
College of Surveying and Geo-Informatics, Tongji University, Shanghai,
China
Gang Qiao
Center for Spatial Information Science and Sustainable Development
Applications, Tongji University, Shanghai, China
College of Surveying and Geo-Informatics, Tongji University, Shanghai,
China
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Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W7, 1569–1573, https://doi.org/10.5194/isprs-archives-XLII-2-W7-1569-2017, https://doi.org/10.5194/isprs-archives-XLII-2-W7-1569-2017, 2017
H. Xiao, S. Liu, R. Li, and X. Tong
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W7, 1575–1577, https://doi.org/10.5194/isprs-archives-XLII-2-W7-1575-2017, https://doi.org/10.5194/isprs-archives-XLII-2-W7-1575-2017, 2017
Rongxing Li, Haifeng Xiao, Shijie Liu, and Xiaohua Tong
The Cryosphere Discuss., https://doi.org/10.5194/tc-2017-178, https://doi.org/10.5194/tc-2017-178, 2017
Revised manuscript not accepted
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Fracturing in the RFIS was slightly increased, particularly at its front, from 2003 to 2015. They do not seem to suggest an immediate significant impact on the stability of the shelf. However, with the rapid changes and 3D measurements of Rifts 1 and 2, the most active activities occurred at the front of the FIS from 2001 to 2016. A potential upcoming major calving event in FIS is estimated to occur in 2051. The stability of the ice shelf, particularly Rifts 1 and 2, should be closely monitored.
R. Li, W. Ye, F. Kong, G. Qiao, X. Tong, X. Ma, S. Guo, and Z. Wang
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B8, 521–524, https://doi.org/10.5194/isprs-archives-XLI-B8-521-2016, https://doi.org/10.5194/isprs-archives-XLI-B8-521-2016, 2016
Huan Xie, Gang Hai, Lei Chen, Shijie Liu, Jun Liu, Xiaohua Tong, and Rongxing Li
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B8, 549–553, https://doi.org/10.5194/isprs-archives-XLI-B8-549-2016, https://doi.org/10.5194/isprs-archives-XLI-B8-549-2016, 2016
Related subject area
Discipline: Ice sheets | Subject: Antarctic
Surface dynamics and history of the calving cycle of Astrolabe Glacier (Adélie Coast, Antarctica) derived from satellite imagery
Weak relationship between remotely detected crevasses and inferred ice rheological parameters on Antarctic ice shelves
Extensive palaeo-surfaces beneath the Evans–Rutford region of the West Antarctic Ice Sheet control modern and past ice flow
Towards the systematic reconnaissance of seismic signals from glaciers and ice sheets – Part 1: Event detection for cryoseismology
Towards the systematic reconnaissance of seismic signals from glaciers and ice sheets – Part 2: Unsupervised learning for source process characterization
Geometric amplification and suppression of ice-shelf basal melt in West Antarctica
Alpine topography of the Gamburtsev Subglacial Mountains, Antarctica, mapped from ice sheet surface morphology
Impact of boundary conditions on the modeled thermal regime of the Antarctic ice sheet
The staggered retreat of grounded ice in the Ross Sea, Antarctica, since the Last Glacial Maximum (LGM)
The effect of landfast sea ice buttressing on ice dynamic speedup in the Larsen B embayment, Antarctica
Widespread increase in discharge from West Antarctic Peninsula glaciers since 2018
Meteoric water and glacial melt in the southeastern Amundsen Sea: a time series from 1994 to 2020
Evaporative controls on Antarctic precipitation: an ECHAM6 model study using innovative water tracer diagnostics
Disentangling the drivers of future Antarctic ice loss with a historically calibrated ice-sheet model
Feedback mechanisms controlling Antarctic glacial cycle dynamics simulated with a coupled ice sheet–solid Earth model
Insights into the vulnerability of Antarctic glaciers from the ISMIP6 ice sheet model ensemble and associated uncertainty
Evaluation of four calving laws for Antarctic ice shelves
Englacial architecture of Lambert Glacier, East Antarctica
Mass changes of the northern Antarctic Peninsula Ice Sheet derived from repeat bi-static synthetic aperture radar acquisitions for the period 2013–2017
The evolution of future Antarctic surface melt using PISM-dEBM-simple
Characteristics and rarity of the strong 1940s westerly wind event over the Amundsen Sea, West Antarctica
The long–term sea–level commitment from Antarctica
Sensitivity of the MAR regional climate model snowpack to the parameterization of the assimilation of satellite-derived wet-snow masks on the Antarctic Peninsula
Stratigraphic noise and its potential drivers across the plateau of Dronning Maud Land, East Antarctica
Modes of Antarctic tidal grounding line migration revealed by Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) laser altimetry
A physics-based Antarctic melt detection technique: Combining AMSR-2, radiative transfer modeling, and firn modeling
Evaluating the impact of enhanced horizontal resolution over the Antarctic domain using a variable-resolution Earth system model
Statistically parameterizing and evaluating a positive degree-day model to estimate surface melt in Antarctica from 1979 to 2022
Widespread slowdown in thinning rates of West Antarctic ice shelves
Seasonal variability in Antarctic ice shelf velocities forced by sea surface height variations
Revisiting temperature sensitivity: how does Antarctic precipitation change with temperature?
Precision measurement of the index of refraction of deep glacial ice at radio frequencies at Summit Station, Greenland
Cosmogenic-nuclide data from Antarctic nunataks can constrain past ice sheet instabilities
Exploring ice sheet model sensitivity to ocean thermal forcing and basal sliding using the Community Ice Sheet Model (CISM)
High mid-Holocene accumulation rates over West Antarctica inferred from a pervasive ice-penetrating radar reflector
Seasonal and interannual variability of the landfast ice mass balance between 2009 and 2018 in Prydz Bay, East Antarctica
Megadunes in Antarctica: migration and characterization from remote and in situ observations
Slowdown of Shirase Glacier, East Antarctica, caused by strengthening alongshore winds
Timescales of outlet-glacier flow with negligible basal friction: theory, observations and modeling
Antarctic contribution to future sea level from ice shelf basal melt as constrained by ice discharge observations
Anthropogenic and internal drivers of wind changes over the Amundsen Sea, West Antarctica, during the 20th and 21st centuries
New 10Be exposure ages improve Holocene ice sheet thinning history near the grounding line of Pope Glacier, Antarctica
Antarctic surface climate and surface mass balance in the Community Earth System Model version 2 during the satellite era and into the future (1979–2100)
Inverting ice surface elevation and velocity for bed topography and slipperiness beneath Thwaites Glacier
Hysteretic evolution of ice rises and ice rumples in response to variations in sea level
Variability in Antarctic surface climatology across regional climate models and reanalysis datasets
Sensitivity of the Ross Ice Shelf to environmental and glaciological controls
High-resolution subglacial topography around Dome Fuji, Antarctica, based on ground-based radar surveys over 30 years
Cosmogenic nuclide dating of two stacked ice masses: Ong Valley, Antarctica
Clouds drive differences in future surface melt over the Antarctic ice shelves
Floriane Provost, Dimitri Zigone, Emmanuel Le Meur, Jean-Philippe Malet, and Clément Hibert
The Cryosphere, 18, 3067–3079, https://doi.org/10.5194/tc-18-3067-2024, https://doi.org/10.5194/tc-18-3067-2024, 2024
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The recent calving of Astrolabe Glacier in November 2021 presents an opportunity to better understand the processes leading to ice fracturing. Optical-satellite imagery is used to retrieve the calving cycle of the glacier ice tongue and to measure the ice velocity and strain rates in order to document fracture evolution. We observed that the presence of sea ice for consecutive years has favoured the glacier extension but failed to inhibit the growth of fractures that accelerated in June 2021.
Cristina Gerli, Sebastian Rosier, G. Hilmar Gudmundsson, and Sainan Sun
The Cryosphere, 18, 2677–2689, https://doi.org/10.5194/tc-18-2677-2024, https://doi.org/10.5194/tc-18-2677-2024, 2024
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Recent efforts have focused on using AI and satellite imagery to track crevasses for assessing ice shelf damage and informing ice flow models. Our study reveals a weak connection between these observed products and damage maps inferred from ice flow models. While there is some improvement in crevasse-dense regions, this association remains limited. Directly mapping ice damage from satellite observations may not significantly improve the representation of these processes within ice flow models.
Charlotte M. Carter, Michael J. Bentley, Stewart S. R. Jamieson, Guy J. G. Paxman, Tom A. Jordan, Julien A. Bodart, Neil Ross, and Felipe Napoleoni
The Cryosphere, 18, 2277–2296, https://doi.org/10.5194/tc-18-2277-2024, https://doi.org/10.5194/tc-18-2277-2024, 2024
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We use radio-echo sounding data to investigate the presence of flat surfaces beneath the Evans–Rutford region in West Antarctica. These surfaces may be what remains of laterally continuous surfaces, formed before the inception of the West Antarctic Ice Sheet, and we assess two hypotheses for their formation. Tectonic structures in the region may have also had a control on the growth of the ice sheet by focusing ice flow into troughs adjoining these surfaces.
Rebecca B. Latto, Ross J. Turner, Anya M. Reading, and J. Paul Winberry
The Cryosphere, 18, 2061–2079, https://doi.org/10.5194/tc-18-2061-2024, https://doi.org/10.5194/tc-18-2061-2024, 2024
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The study of icequakes allows for investigation of many glacier processes that are unseen by typical reconnaissance methods. However, detection of such seismic signals is challenging due to low signal-to-noise levels and diverse source mechanisms. Here we present a novel algorithm that is optimized to detect signals from a glacier environment. We apply the algorithm to seismic data recorded in the 2010–2011 austral summer from the Whillans Ice Stream and evaluate the resulting event catalogue.
Rebecca B. Latto, Ross J. Turner, Anya M. Reading, Sue Cook, Bernd Kulessa, and J. Paul Winberry
The Cryosphere, 18, 2081–2101, https://doi.org/10.5194/tc-18-2081-2024, https://doi.org/10.5194/tc-18-2081-2024, 2024
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Seismic catalogues are potentially rich sources of information on glacier processes. In a companion study, we constructed an event catalogue for seismic data from the Whillans Ice Stream. Here, we provide a semi-automated workflow for consistent catalogue analysis using an unsupervised cluster analysis. We discuss the defining characteristics of identified signal types found in this catalogue and possible mechanisms for the underlying glacier processes and noise sources.
Jan De Rydt and Kaitlin Naughten
The Cryosphere, 18, 1863–1888, https://doi.org/10.5194/tc-18-1863-2024, https://doi.org/10.5194/tc-18-1863-2024, 2024
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The West Antarctic Ice Sheet is losing ice at an accelerating pace. This is largely due to the presence of warm ocean water around the periphery of the Antarctic continent, which melts the ice. It is generally assumed that the strength of this process is controlled by the temperature of the ocean. However, in this study we show that an equally important role is played by the changing geometry of the ice sheet, which affects the strength of the ocean currents and thereby the melt rates.
Edmund J. Lea, Stewart S. R. Jamieson, and Michael J. Bentley
The Cryosphere, 18, 1733–1751, https://doi.org/10.5194/tc-18-1733-2024, https://doi.org/10.5194/tc-18-1733-2024, 2024
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We use the ice surface expression of the Gamburtsev Subglacial Mountains in East Antarctica to map the horizontal pattern of valleys and ridges in finer detail than possible from previous methods. In upland areas, valleys are spaced much less than 5 km apart, with consequences for the distribution of melting at the bed and hence the likelihood of ancient ice being preserved. Automated mapping techniques were tested alongside manual approaches, with a hybrid approach recommended for future work.
In-Woo Park, Emilia Kyung Jin, Mathieu Morlighem, and Kang-Kun Lee
The Cryosphere, 18, 1139–1155, https://doi.org/10.5194/tc-18-1139-2024, https://doi.org/10.5194/tc-18-1139-2024, 2024
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This study conducted 3D thermodynamic ice sheet model experiments, and modeled temperatures were compared with 15 observed borehole temperature profiles. We found that using incompressibility of ice without sliding agrees well with observed temperature profiles in slow-flow regions, while incorporating sliding in fast-flow regions captures observed temperature profiles. Also, the choice of vertical velocity scheme has a greater impact on the shape of the modeled temperature profile.
Matthew A. Danielson and Philip J. Bart
The Cryosphere, 18, 1125–1138, https://doi.org/10.5194/tc-18-1125-2024, https://doi.org/10.5194/tc-18-1125-2024, 2024
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The post-Last Glacial Maximum (LGM) retreat of the West Antarctic Ice Sheet in the Ross Sea was more significant than for any other Antarctic sector. Here we combined the available dates of retreat with new mapping of sediment deposited by the ice sheet during overall retreat. Our work shows that the post-LGM retreat through the Ross Sea was not uniform. This uneven retreat can cause instability in the present-day Antarctic ice sheet configuration and lead to future runaway retreat.
Trystan Surawy-Stepney, Anna E. Hogg, Stephen L. Cornford, Benjamin J. Wallis, Benjamin J. Davison, Heather L. Selley, Ross A. W. Slater, Elise K. Lie, Livia Jakob, Andrew Ridout, Noel Gourmelen, Bryony I. D. Freer, Sally F. Wilson, and Andrew Shepherd
The Cryosphere, 18, 977–993, https://doi.org/10.5194/tc-18-977-2024, https://doi.org/10.5194/tc-18-977-2024, 2024
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Here, we use satellite observations and an ice flow model to quantify the impact of sea ice buttressing on ice streams on the Antarctic Peninsula. The evacuation of 11-year-old landfast sea ice in the Larsen B embayment on the East Antarctic Peninsula in January 2022 was closely followed by major changes in the calving behaviour and acceleration (30 %) of the ocean-terminating glaciers. Our results show that sea ice buttressing had a negligible direct role in the observed dynamic changes.
Benjamin J. Davison, Anna E. Hogg, Carlos Moffat, Michael P. Meredith, and Benjamin J. Wallis
EGUsphere, https://doi.org/10.5194/egusphere-2024-232, https://doi.org/10.5194/egusphere-2024-232, 2024
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Using a new dataset of ice motion, we observed glacier acceleration on the west coast of the Antarctic Peninsula. The speed-up began around January 2021 but some glaciers sped-up earlier or later. All of those glaciers flow into the ocean where they melt – ship-based observations show that ocean temperatures near the glaciers have been unusually warm since 2018, likely causing them to melt faster and speed-up. As the ocean warms more in future, these glaciers may accelerate again.
Andrew N. Hennig, David A. Mucciarone, Stanley S. Jacobs, Richard A. Mortlock, and Robert B. Dunbar
The Cryosphere, 18, 791–818, https://doi.org/10.5194/tc-18-791-2024, https://doi.org/10.5194/tc-18-791-2024, 2024
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A total of 937 seawater paired oxygen isotope (δ18O)–salinity samples collected during seven cruises on the SE Amundsen Sea between 1994 and 2020 reveal a deep freshwater source with δ18O − 29.4±1.0‰, consistent with the signature of local ice shelf melt. Local mean meteoric water content – comprised primarily of glacial meltwater – increased between 1994 and 2020 but exhibited greater interannual variability than increasing trend.
Qinggang Gao, Louise C. Sime, Alison J. McLaren, Thomas J. Bracegirdle, Emilie Capron, Rachael H. Rhodes, Hans Christian Steen-Larsen, Xiaoxu Shi, and Martin Werner
The Cryosphere, 18, 683–703, https://doi.org/10.5194/tc-18-683-2024, https://doi.org/10.5194/tc-18-683-2024, 2024
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Antarctic precipitation is a crucial component of the climate system. Its spatio-temporal variability impacts sea level changes and the interpretation of water isotope measurements in ice cores. To better understand its climatic drivers, we developed water tracers in an atmospheric model to identify moisture source conditions from which precipitation originates. We find that mid-latitude surface winds exert an important control on moisture availability for Antarctic precipitation.
Violaine Coulon, Ann Kristin Klose, Christoph Kittel, Tamsin Edwards, Fiona Turner, Ricarda Winkelmann, and Frank Pattyn
The Cryosphere, 18, 653–681, https://doi.org/10.5194/tc-18-653-2024, https://doi.org/10.5194/tc-18-653-2024, 2024
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We present new projections of the evolution of the Antarctic ice sheet until the end of the millennium, calibrated with observations. We show that the ocean will be the main trigger of future ice loss. As temperatures continue to rise, the atmosphere's role may shift from mitigating to amplifying Antarctic mass loss already by the end of the century. For high-emission scenarios, this may lead to substantial sea-level rise. Adopting sustainable practices would however reduce the rate of ice loss.
Torsten Albrecht, Meike Bagge, and Volker Klemann
EGUsphere, https://doi.org/10.5194/egusphere-2023-2990, https://doi.org/10.5194/egusphere-2023-2990, 2023
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We performed coupled ice sheet – solid Earth simulations and discovered a positive (forebulge) feedback mechanisms for advancing grounding lines, supporting a comparably larger West Antarctic Ice Sheet at Last Glacial Maximum. During deglaciation we found the stabilizing GIA feedback to dominate grounding line retreat in the Ross Sea, where a weak Earth structure is prevalent. This may have consequences for the contemporary and future ice sheet stability and potential rates of sea level rise.
Hélène Seroussi, Vincent Verjans, Sophie Nowicki, Antony J. Payne, Heiko Goelzer, William H. Lipscomb, Ayako Abe-Ouchi, Cécile Agosta, Torsten Albrecht, Xylar Asay-Davis, Alice Barthel, Reinhard Calov, Richard Cullather, Christophe Dumas, Benjamin K. Galton-Fenzi, Rupert Gladstone, Nicholas R. Golledge, Jonathan M. Gregory, Ralf Greve, Tore Hattermann, Matthew J. Hoffman, Angelika Humbert, Philippe Huybrechts, Nicolas C. Jourdain, Thomas Kleiner, Eric Larour, Gunter R. Leguy, Daniel P. Lowry, Chistopher M. Little, Mathieu Morlighem, Frank Pattyn, Tyler Pelle, Stephen F. Price, Aurélien Quiquet, Ronja Reese, Nicole-Jeanne Schlegel, Andrew Shepherd, Erika Simon, Robin S. Smith, Fiammetta Straneo, Sainan Sun, Luke D. Trusel, Jonas Van Breedam, Peter Van Katwyk, Roderik S. W. van de Wal, Ricarda Winkelmann, Chen Zhao, Tong Zhang, and Thomas Zwinger
The Cryosphere, 17, 5197–5217, https://doi.org/10.5194/tc-17-5197-2023, https://doi.org/10.5194/tc-17-5197-2023, 2023
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Mass loss from Antarctica is a key contributor to sea level rise over the 21st century, and the associated uncertainty dominates sea level projections. We highlight here the Antarctic glaciers showing the largest changes and quantify the main sources of uncertainty in their future evolution using an ensemble of ice flow models. We show that on top of Pine Island and Thwaites glaciers, Totten and Moscow University glaciers show rapid changes and a strong sensitivity to warmer ocean conditions.
Joel A. Wilner, Mathieu Morlighem, and Gong Cheng
The Cryosphere, 17, 4889–4901, https://doi.org/10.5194/tc-17-4889-2023, https://doi.org/10.5194/tc-17-4889-2023, 2023
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We use numerical modeling to study iceberg calving off of ice shelves in Antarctica. We examine four widely used mathematical descriptions of calving (
calving laws), under the assumption that Antarctic ice shelf front positions should be in steady state under the current climate forcing. We quantify how well each of these calving laws replicates the observed front positions. Our results suggest that the eigencalving and von Mises laws are most suitable for Antarctic ice shelves.
Rebecca J. Sanderson, Kate Winter, S. Louise Callard, Felipe Napoleoni, Neil Ross, Tom A. Jordan, and Robert G. Bingham
The Cryosphere, 17, 4853–4871, https://doi.org/10.5194/tc-17-4853-2023, https://doi.org/10.5194/tc-17-4853-2023, 2023
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Ice-penetrating radar allows us to explore the internal structure of glaciers and ice sheets to constrain past and present ice-flow conditions. In this paper, we examine englacial layers within the Lambert Glacier in East Antarctica using a quantitative layer tracing tool. Analysis reveals that the ice flow here has been relatively stable, but evidence for former fast flow along a tributary suggests that changes have occurred in the past and could change again in the future.
Thorsten Seehaus, Christian Sommer, Thomas Dethinne, and Philipp Malz
The Cryosphere, 17, 4629–4644, https://doi.org/10.5194/tc-17-4629-2023, https://doi.org/10.5194/tc-17-4629-2023, 2023
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Existing mass budget estimates for the northern Antarctic Peninsula (>70° S) are affected by considerable limitations. We carried out the first region-wide analysis of geodetic mass balances throughout this region (coverage of 96.4 %) for the period 2013–2017 based on repeat pass bi-static TanDEM-X acquisitions. A total mass budget of −24.1±2.8 Gt/a is revealed. Imbalanced high ice discharge, particularly at former ice shelf tributaries, is the main driver of overall ice loss.
Julius Garbe, Maria Zeitz, Uta Krebs-Kanzow, and Ricarda Winkelmann
The Cryosphere, 17, 4571–4599, https://doi.org/10.5194/tc-17-4571-2023, https://doi.org/10.5194/tc-17-4571-2023, 2023
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We adopt the novel surface module dEBM-simple in the Parallel Ice Sheet Model (PISM) to investigate the impact of atmospheric warming on Antarctic surface melt and long-term ice sheet dynamics. As an enhancement compared to traditional temperature-based melt schemes, the module accounts for changes in ice surface albedo and thus the melt–albedo feedback. Our results underscore the critical role of ice–atmosphere feedbacks in the future sea-level contribution of Antarctica on long timescales.
Gemma K. O'Connor, Paul R. Holland, Eric J. Steig, Pierre Dutrieux, and Gregory J. Hakim
The Cryosphere, 17, 4399–4420, https://doi.org/10.5194/tc-17-4399-2023, https://doi.org/10.5194/tc-17-4399-2023, 2023
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Glaciers in West Antarctica are rapidly melting, but the causes are unknown due to limited observations. A leading hypothesis is that an unusually large wind event in the 1940s initiated the ocean-driven melting. Using proxy reconstructions (e.g., using ice cores) and climate model simulations, we find that wind events similar to the 1940s event are relatively common on millennial timescales, implying that ocean variability or climate trends are also necessary to explain the start of ice loss.
Ann Kristin Klose, Violaine Coulon, Frank Pattyn, and Ricarda Winkelmann
The Cryosphere Discuss., https://doi.org/10.5194/tc-2023-156, https://doi.org/10.5194/tc-2023-156, 2023
Revised manuscript accepted for TC
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We systematically assess the long-term sea-level response from Antarctica to warming projected over the next centuries with two ice-sheet models. We show that this committed Antarctic sea-level contribution is substantially higher than the transient sea-level change projected for the coming decades. A low-emission scenario already poses a considerable risk of multi-meter sea-level increase over the next millennia, while additional East Antarctic ice loss unfolds under the high-emission pathway.
Thomas Dethinne, Quentin Glaude, Ghislain Picard, Christoph Kittel, Patrick Alexander, Anne Orban, and Xavier Fettweis
The Cryosphere, 17, 4267–4288, https://doi.org/10.5194/tc-17-4267-2023, https://doi.org/10.5194/tc-17-4267-2023, 2023
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We investigate the sensitivity of the regional climate model
Modèle Atmosphérique Régional(MAR) to the assimilation of wet-snow occurrence estimated by remote sensing datasets. The assimilation is performed by nudging the MAR snowpack temperature. The data assimilation is performed over the Antarctic Peninsula for the 2019–2021 period. The results show an increase in the melt production (+66.7 %) and a decrease in surface mass balance (−4.5 %) of the model for the 2019–2020 melt season.
Nora Hirsch, Alexandra Zuhr, Thomas Münch, Maria Hörhold, Johannes Freitag, Remi Dallmayr, and Thomas Laepple
The Cryosphere, 17, 4207–4221, https://doi.org/10.5194/tc-17-4207-2023, https://doi.org/10.5194/tc-17-4207-2023, 2023
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Stable water isotopes from firn cores provide valuable information on past climates, yet their utility is hampered by stratigraphic noise, i.e. the irregular deposition and wind-driven redistribution of snow. We found stratigraphic noise on the Antarctic Plateau to be related to the local accumulation rate, snow surface roughness and slope inclination, which can guide future decisions on sampling locations and thus increase the resolution of climate reconstructions from low-accumulation areas.
Bryony I. D. Freer, Oliver J. Marsh, Anna E. Hogg, Helen Amanda Fricker, and Laurie Padman
The Cryosphere, 17, 4079–4101, https://doi.org/10.5194/tc-17-4079-2023, https://doi.org/10.5194/tc-17-4079-2023, 2023
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We develop a method using ICESat-2 data to measure how Antarctic grounding lines (GLs) migrate across the tide cycle. At an ice plain on the Ronne Ice Shelf we observe 15 km of tidal GL migration, the largest reported distance in Antarctica, dominating any signal of long-term migration. We identify four distinct migration modes, which provide both observational support for models of tidal ice flexure and GL migration and insights into ice shelf–ocean–subglacial interactions in grounding zones.
Marissa Eileen Dattler, Brooke Medley, and C. Max Stevens
The Cryosphere Discuss., https://doi.org/10.5194/tc-2023-136, https://doi.org/10.5194/tc-2023-136, 2023
Revised manuscript accepted for TC
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We develop an algorithm based on combining models and satellites observations to identify the presence of surface melt on the Antarctic Ice Sheet. We compare two sites to observations taken in the field and find that this method works similarly to previous methods. Unlike other previous methods, this algorithm is based on physical parameters and updates to this method could allow this algorithm to quantify the amount of melt water present on the Antarctic Ice instead of simply detecting it.
Rajashree Tri Datta, Adam Herrington, Jan T. M. Lenaerts, David P. Schneider, Luke Trusel, Ziqi Yin, and Devon Dunmire
The Cryosphere, 17, 3847–3866, https://doi.org/10.5194/tc-17-3847-2023, https://doi.org/10.5194/tc-17-3847-2023, 2023
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Precipitation over Antarctica is one of the greatest sources of uncertainty in sea level rise estimates. Earth system models (ESMs) are a valuable tool for these estimates but typically run at coarse spatial resolutions. Here, we present an evaluation of the variable-resolution CESM2 (VR-CESM2) for the first time with a grid designed for enhanced spatial resolution over Antarctica to achieve the high resolution of regional climate models while preserving the two-way interactions of ESMs.
Yaowen Zheng, Nicholas R. Golledge, Alexandra Gossart, Ghislain Picard, and Marion Leduc-Leballeur
The Cryosphere, 17, 3667–3694, https://doi.org/10.5194/tc-17-3667-2023, https://doi.org/10.5194/tc-17-3667-2023, 2023
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Positive degree-day (PDD) schemes are widely used in many Antarctic numerical ice sheet models. However, the PDD approach has not been systematically explored for its application in Antarctica. We have constructed a novel grid-cell-level spatially distributed PDD (dist-PDD) model and assessed its accuracy. We suggest that an appropriately parameterized dist-PDD model can be a valuable tool for exploring Antarctic surface melt beyond the satellite era.
Fernando S. Paolo, Alex S. Gardner, Chad A. Greene, Johan Nilsson, Michael P. Schodlok, Nicole-Jeanne Schlegel, and Helen A. Fricker
The Cryosphere, 17, 3409–3433, https://doi.org/10.5194/tc-17-3409-2023, https://doi.org/10.5194/tc-17-3409-2023, 2023
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We report on a slowdown in the rate of thinning and melting of West Antarctic ice shelves. We present a comprehensive assessment of the Antarctic ice shelves, where we analyze at a continental scale the changes in thickness, flow, and basal melt over the past 26 years. We also present a novel method to estimate ice shelf change from satellite altimetry and a time-dependent data set of ice shelf thickness and basal melt rates at an unprecedented resolution.
Cyrille Mosbeux, Laurie Padman, Emilie Klein, Peter D. Bromirski, and Helen A. Fricker
The Cryosphere, 17, 2585–2606, https://doi.org/10.5194/tc-17-2585-2023, https://doi.org/10.5194/tc-17-2585-2023, 2023
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Antarctica's ice shelves (the floating extension of the ice sheet) help regulate ice flow. As ice shelves thin or lose contact with the bedrock, the upstream ice tends to accelerate, resulting in increased mass loss. Here, we use an ice sheet model to simulate the effect of seasonal sea surface height variations and see if we can reproduce observed seasonal variability of ice velocity on the ice shelf. When correctly parameterised, the model fits the observations well.
Lena Nicola, Dirk Notz, and Ricarda Winkelmann
The Cryosphere, 17, 2563–2583, https://doi.org/10.5194/tc-17-2563-2023, https://doi.org/10.5194/tc-17-2563-2023, 2023
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For future sea-level projections, approximating Antarctic precipitation increases through temperature-scaling approaches will remain important, as coupled ice-sheet simulations with regional climate models remain computationally expensive, especially on multi-centennial timescales. We here revisit the relationship between Antarctic temperature and precipitation using different scaling approaches, identifying and explaining regional differences.
Christoph Welling and the RNO-G Collaboration
EGUsphere, https://doi.org/10.5194/egusphere-2023-745, https://doi.org/10.5194/egusphere-2023-745, 2023
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We report in the measurement of the index of refraction in glacial ice at radio frequencies. We show that radio echos from within the ice can be associated with specific features of the ice conductivity, and use this to determine the wave velocity. This measurement is especially relevant for the Radio Neutrino Observatory Greenland (RNO-G), a neutrino detection experiment currently under construction at Summit Station, Greenland.
Anna Ruth W. Halberstadt, Greg Balco, Hannah Buchband, and Perry Spector
The Cryosphere, 17, 1623–1643, https://doi.org/10.5194/tc-17-1623-2023, https://doi.org/10.5194/tc-17-1623-2023, 2023
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This paper explores the use of multimillion-year exposure ages from Antarctic bedrock outcrops to benchmark ice sheet model predictions and thereby infer ice sheet sensitivity to warm climates. We describe a new approach for model–data comparison, highlight an example where observational data are used to distinguish end-member models, and provide guidance for targeted sampling around Antarctica that can improve understanding of ice sheet response to climate warming in the past and future.
Mira Berdahl, Gunter Leguy, William H. Lipscomb, Nathan M. Urban, and Matthew J. Hoffman
The Cryosphere, 17, 1513–1543, https://doi.org/10.5194/tc-17-1513-2023, https://doi.org/10.5194/tc-17-1513-2023, 2023
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Contributions to future sea level from the Antarctic Ice Sheet remain poorly constrained. One reason is that ice sheet model initialization methods can have significant impacts on how the ice sheet responds to future forcings. We investigate the impacts of two key parameters used during model initialization. We find that these parameter choices alone can impact multi-century sea level rise by up to 2 m, emphasizing the need to carefully consider these choices for sea level rise predictions.
Julien A. Bodart, Robert G. Bingham, Duncan A. Young, Joseph A. MacGregor, David W. Ashmore, Enrica Quartini, Andrew S. Hein, David G. Vaughan, and Donald D. Blankenship
The Cryosphere, 17, 1497–1512, https://doi.org/10.5194/tc-17-1497-2023, https://doi.org/10.5194/tc-17-1497-2023, 2023
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Estimating how West Antarctica will change in response to future climatic change depends on our understanding of past ice processes. Here, we use a reflector widely visible on airborne radar data across West Antarctica to estimate accumulation rates over the past 4700 years. By comparing our estimates with current atmospheric data, we find that accumulation rates were 18 % greater than modern rates. This has implications for our understanding of past ice processes in the region.
Na Li, Ruibo Lei, Petra Heil, Bin Cheng, Minghu Ding, Zhongxiang Tian, and Bingrui Li
The Cryosphere, 17, 917–937, https://doi.org/10.5194/tc-17-917-2023, https://doi.org/10.5194/tc-17-917-2023, 2023
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The observed annual maximum landfast ice (LFI) thickness off Zhongshan (Davis) was 1.59±0.17 m (1.64±0.08 m). Larger interannual and local spatial variabilities for the seasonality of LFI were identified at Zhongshan, with the dominant influencing factors of air temperature anomaly, snow atop, local topography and wind regime, and oceanic heat flux. The variability of LFI properties across the study domain prevailed at interannual timescales, over any trend during the recent decades.
Giacomo Traversa, Davide Fugazza, and Massimo Frezzotti
The Cryosphere, 17, 427–444, https://doi.org/10.5194/tc-17-427-2023, https://doi.org/10.5194/tc-17-427-2023, 2023
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Megadunes are fields of huge snow dunes present in Antarctica and on other planets, important as they present mass loss on the leeward side (glazed snow), on a continent characterized by mass gain. Here, we studied megadunes using remote data and measurements acquired during past field expeditions. We quantified their physical properties and migration and demonstrated that they migrate against slope and wind. We further proposed automatic detections of the glazed snow on their leeward side.
Bertie W. J. Miles, Chris R. Stokes, Adrian Jenkins, Jim R. Jordan, Stewart S. R. Jamieson, and G. Hilmar Gudmundsson
The Cryosphere, 17, 445–456, https://doi.org/10.5194/tc-17-445-2023, https://doi.org/10.5194/tc-17-445-2023, 2023
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Satellite observations have shown that the Shirase Glacier catchment in East Antarctica has been gaining mass over the past 2 decades, a trend largely attributed to increased snowfall. Our multi-decadal observations of Shirase Glacier show that ocean forcing has also contributed to some of this recent mass gain. This has been caused by strengthening easterly winds reducing the inflow of warm water underneath the Shirase ice tongue, causing the glacier to slow down and thicken.
Johannes Feldmann and Anders Levermann
The Cryosphere, 17, 327–348, https://doi.org/10.5194/tc-17-327-2023, https://doi.org/10.5194/tc-17-327-2023, 2023
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Here we present a scaling relation that allows the comparison of the timescales of glaciers with geometric similarity. According to the relation, thicker and wider glaciers on a steeper bed slope have a much faster timescale than shallower, narrower glaciers on a flatter bed slope. The relation is supported by observations and simplified numerical simulations. We combine the scaling relation with a statistical analysis of the topography of 13 instability-prone Antarctic outlet glaciers.
Eveline C. van der Linden, Dewi Le Bars, Erwin Lambert, and Sybren Drijfhout
The Cryosphere, 17, 79–103, https://doi.org/10.5194/tc-17-79-2023, https://doi.org/10.5194/tc-17-79-2023, 2023
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The Antarctic ice sheet (AIS) is the largest uncertainty in future sea level estimates. The AIS mainly loses mass through ice discharge, the transfer of land ice into the ocean. Ice discharge is triggered by warming ocean water (basal melt). New future estimates of AIS sea level contributions are presented in which basal melt is constrained with ice discharge observations. Despite the different methodology, the resulting projections are in line with previous multimodel assessments.
Paul R. Holland, Gemma K. O'Connor, Thomas J. Bracegirdle, Pierre Dutrieux, Kaitlin A. Naughten, Eric J. Steig, David P. Schneider, Adrian Jenkins, and James A. Smith
The Cryosphere, 16, 5085–5105, https://doi.org/10.5194/tc-16-5085-2022, https://doi.org/10.5194/tc-16-5085-2022, 2022
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The Antarctic Ice Sheet is losing ice, causing sea-level rise. However, it is not known whether human-induced climate change has contributed to this ice loss. In this study, we use evidence from climate models and palaeoclimate measurements (e.g. ice cores) to suggest that the ice loss was triggered by natural climate variations but is now sustained by human-forced climate change. This implies that future greenhouse-gas emissions may influence sea-level rise from Antarctica.
Jonathan R. Adams, Joanne S. Johnson, Stephen J. Roberts, Philippa J. Mason, Keir A. Nichols, Ryan A. Venturelli, Klaus Wilcken, Greg Balco, Brent Goehring, Brenda Hall, John Woodward, and Dylan H. Rood
The Cryosphere, 16, 4887–4905, https://doi.org/10.5194/tc-16-4887-2022, https://doi.org/10.5194/tc-16-4887-2022, 2022
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Glaciers in West Antarctica are experiencing significant ice loss. Geological data provide historical context for ongoing ice loss in West Antarctica, including constraints on likely future ice sheet behaviour in response to climatic warming. We present evidence from rare isotopes measured in rocks collected from an outcrop next to Pope Glacier. These data suggest that Pope Glacier thinned faster and sooner after the last ice age than previously thought.
Devon Dunmire, Jan T. M. Lenaerts, Rajashree Tri Datta, and Tessa Gorte
The Cryosphere, 16, 4163–4184, https://doi.org/10.5194/tc-16-4163-2022, https://doi.org/10.5194/tc-16-4163-2022, 2022
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Earth system models (ESMs) are used to model the climate system and the interactions of its components (atmosphere, ocean, etc.) both historically and into the future under different assumptions of human activity. The representation of Antarctica in ESMs is important because it can inform projections of the ice sheet's contribution to sea level rise. Here, we compare output of Antarctica's surface climate from an ESM with observations to understand strengths and weaknesses within the model.
Helen Ockenden, Robert G. Bingham, Andrew Curtis, and Daniel Goldberg
The Cryosphere, 16, 3867–3887, https://doi.org/10.5194/tc-16-3867-2022, https://doi.org/10.5194/tc-16-3867-2022, 2022
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Hills and valleys hidden under the ice of Thwaites Glacier have an impact on ice flow and future ice loss, but there are not many three-dimensional observations of their location or size. We apply a mathematical theory to new high-resolution observations of the ice surface to predict the bed topography beneath the ice. There is a good correlation with ice-penetrating radar observations. The method may be useful in areas with few direct observations or as a further constraint for other methods.
A. Clara J. Henry, Reinhard Drews, Clemens Schannwell, and Vjeran Višnjević
The Cryosphere, 16, 3889–3905, https://doi.org/10.5194/tc-16-3889-2022, https://doi.org/10.5194/tc-16-3889-2022, 2022
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We used a 3D, idealised model to study features in coastal Antarctica called ice rises and ice rumples. These features regulate the rate of ice flow into the ocean. We show that when sea level is raised or lowered, the size of these features and the ice flow pattern can change. We find that the features depend on the ice history and do not necessarily fully recover after an equal increase and decrease in sea level. This shows that it is important to initialise models with accurate ice geometry.
Jeremy Carter, Amber Leeson, Andrew Orr, Christoph Kittel, and J. Melchior van Wessem
The Cryosphere, 16, 3815–3841, https://doi.org/10.5194/tc-16-3815-2022, https://doi.org/10.5194/tc-16-3815-2022, 2022
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Climate models provide valuable information for studying processes such as the collapse of ice shelves over Antarctica which impact estimates of sea level rise. This paper examines variability across climate simulations over Antarctica for fields including snowfall, temperature and melt. Significant systematic differences between outputs are found, occurring at both large and fine spatial scales across Antarctica. Results are important for future impact assessments and model development.
Francesca Baldacchino, Mathieu Morlighem, Nicholas R. Golledge, Huw Horgan, and Alena Malyarenko
The Cryosphere, 16, 3723–3738, https://doi.org/10.5194/tc-16-3723-2022, https://doi.org/10.5194/tc-16-3723-2022, 2022
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Understanding how the Ross Ice Shelf will evolve in a warming world is important to the future stability of Antarctica. It remains unclear what changes could drive the largest mass loss in the future and where places are most likely to trigger larger mass losses. Sensitivity maps are modelled showing that the RIS is sensitive to changes in environmental and glaciological controls at regions which are currently experiencing changes. These regions need to be monitored in a warming world.
Shun Tsutaki, Shuji Fujita, Kenji Kawamura, Ayako Abe-Ouchi, Kotaro Fukui, Hideaki Motoyama, Yu Hoshina, Fumio Nakazawa, Takashi Obase, Hiroshi Ohno, Ikumi Oyabu, Fuyuki Saito, Konosuke Sugiura, and Toshitaka Suzuki
The Cryosphere, 16, 2967–2983, https://doi.org/10.5194/tc-16-2967-2022, https://doi.org/10.5194/tc-16-2967-2022, 2022
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We constructed an ice thickness map across the Dome Fuji region, East Antarctica, from improved radar data and previous data that had been collected since the late 1980s. The data acquired using the improved radar systems allowed basal topography to be identified with higher accuracy. The new ice thickness data show the bedrock topography, particularly the complex terrain of subglacial valleys and highlands south of Dome Fuji, with substantially high detail.
Marie Bergelin, Jaakko Putkonen, Greg Balco, Daniel Morgan, Lee B. Corbett, and Paul R. Bierman
The Cryosphere, 16, 2793–2817, https://doi.org/10.5194/tc-16-2793-2022, https://doi.org/10.5194/tc-16-2793-2022, 2022
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Glacier ice contains information on past climate and can help us understand how the world changes through time. We have found and sampled a buried ice mass in Antarctica that is much older than most ice on Earth and difficult to date. Therefore, we developed a new dating application which showed the ice to be 3 million years old. Our new dating solution will potentially help to date other ancient ice masses since such old glacial ice could yield data on past environmental conditions on Earth.
Christoph Kittel, Charles Amory, Stefan Hofer, Cécile Agosta, Nicolas C. Jourdain, Ella Gilbert, Louis Le Toumelin, Étienne Vignon, Hubert Gallée, and Xavier Fettweis
The Cryosphere, 16, 2655–2669, https://doi.org/10.5194/tc-16-2655-2022, https://doi.org/10.5194/tc-16-2655-2022, 2022
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Model projections suggest large differences in future Antarctic surface melting even for similar greenhouse gas scenarios and warming rates. We show that clouds containing a larger amount of liquid water lead to stronger melt. As surface melt can trigger the collapse of the ice shelves (the safety band of the Antarctic Ice Sheet), clouds could be a major source of uncertainties in projections of sea level rise.
Cited articles
Altena, B. and Kääb, A.: Weekly Glacier Flow Estimation from Dense
Satellite Time Series Using Adapted Optical Flow Technology, Front. Earth.
Sci., 5, 53, https://doi.org/10.3389/feart.2017.00053, 2017.
Bamber, J. L., Vaughan, D. G., and Joughin, I.: Widespread complex flow in
the interior of the Antarctic ice sheet, Science, 287, 1248–1250,
https://doi.org/10.1126/science.287.5456.1248, 2000.
Berthier, E., Raup, B., and Scambos, T.: New velocity map and mass-balance
estimate of Mertz Glacier, East Antarctica, derived from Landsat sequential
imagery, J. Glaciol., 49, 503–511,
https://doi.org/10.3189/172756503781830377, 2003.
Bindschadler, R., Vornberger, P., Blankenship, D., Scambos, T., and Jacobel,
R.: Surface velocity and mass balance of Ice Streams D and E, West
Antarctica, J. Glaciol., 42, 461–475,
https://doi.org/10.3189/S0022143000003452, 1996.
Bindschadler, R., Vornberger, P., Fleming, A., Fox, A., Mullins, J., Binnie,
D., Paulsen, S. J., Granneman, B., and Gorodetzky, D.: The Landsat Image
Mosaic of Antarctica, Remote Sens. Environ., 112, 4214–4226,
https://doi.org/10.1016/j.rse.2008.07.006, 2008.
Bindschadler, R. A. and Scambos, T. A.: Satellite-Image-Derived Velocity
Field of an Antarctic Ice Stream, Science, 252, 242–246,
https://doi.org/10.1126/science.252.5003.242, 1991.
Chander, G., Markham, B. L., and Helder, D. L.: Summary of current
radiometric calibration coefficients for Landsat MSS, TM, ETM+, and EO-1
ALI sensors, Remote Sens. Environ., 113, 893–903,
https://doi.org/10.1016/j.rse.2009.01.007, 2009.
Cheng, Y., Li, X., Qiao, G., Ye, W., Huang, Y., Li, Y., Wang, K., Tian, Y., Tong, X., and Li, R.: Ice flow velocity mapping of East Antarctica from 1963 to 1989, International Society for Photogrammetry and Remote Sensing (ISPRS) Geospatial Week 2019, Enschede, the Netherlands, 10–14 June 2019, XLII-2/W13, https://doi.org/10.5194/isprs-archives-XLII-2-W13-1735-2019, 2019.
Chenillat, F., Blanke, B., Grima, N., Franks, P. J. S., Capet, X., and
Riviere, P.: Quantifying tracer dynamics in moving fluids: a combined
Eulerian-Lagrangian approach, Front. Earth Sci., 3, 43,
https://doi.org/10.3389/fenvs.2015.00043, 2015.
Chu, P. C. and Fan, C.: Accuracy Progressive Calculation of Lagrangian
Trajectories from a Gridded Velocity Field, J. Atmos. Ocean. Tech., 31,
1615–1627, https://doi.org/10.1175/JTECH-D-13-00204.1, 2014.
Church, J. A., Monselesan, D., Gregory, J. M., and Marzeion, B.: Evaluating
the ability of process based models to project sea-level change, Environ.
Res. Lett., 8, 014051, https://doi.org/10.1088/1748-9326/8/1/014051, 2013.
Cram, T. A., Persing, J., Montgomery, M. T., and Braun, S. A.: A lagrangian
trajectory view on transport and mixing processes between the eye, eyewall,
and environment using a high-resolution simulation of Hurricane Bonnie
(1998), J. Atmos. Sci., 64, 1835–1856, https://doi.org/10.1175/JAS3921.1,
2007.
Cuffey, K. M. and Paterson, W. S. B.: Physics of Glaciers, 4th edn., Academic Press, Burlington, USA, ISBN-13 978-0123694614, ISBN-10 0123694612, 2010.
Danesi, S., Dubbini, M., Morelli, A., Vittuari, L., and Bannister, S.: Joint geophysical observations of ice stream dynamics, in: Geodetic and Geophysical Observations in Antarctica, Springer, Berlin, Heidelberg, https://doi.org/10.1007/978-3-540-74882-3_16, 2008.
Debella-Gilo, M. and Kääb, A.: Sub-pixel precision image matching
for measuring surface displacements on mass movements using normalized
cross-correlation, Remote Sens. Environ., 115, 130–142,
https://doi.org/10.1016/j.rse.2010.08.012, 2011.
Debella-Gilo, M. and Kääb, A.: Monitoring slow-moving landslides
using spatially adaptive least squares image matching, in:
Landslide Science and Practice, Springer, Berlin, Heidelberg,
https://www.springerprofessional.de/monitoring-slow-moving-landslides-using-spatially-adaptive-least/3919286 (last access: 26 February 2022), 2013.
DeConto, R. M. and Pollard, D.: Contribution of Antarctica to past and
future sea-level rise, Nature, 531, 591–597,
https://doi.org/10.1038/nature17145, 2016.
Euler, C., Riemer, M., Kremer, T., and Schömer, E.: Lagrangian
Description of Air Masses Associated with Latent Heat Release in Tropical
Storm Karl (2016) during Extratropical Transition, Mon. Weather Rev.,
147, 2657–2676, https://doi.org/10.1175/MWR-D-18-0422.1, 2019.
Feng, T., Mi, H., Scaioni, M., Qiao, G., Lu, P., Wang, W., Tong, X., and Li,
R.: Measurement of Surface Changes in a Scaled-Down Landslide Model Using
High-Speed Stereo Image Sequences, Photogramm. Eng. Rem. S., 82, 547–557,
https://doi.org/10.14358/PERS.82.7.547, 2016.
Frezzotti, M., Capra, A., and Vittuari, L.: Comparison between glacier ice
velocities inferred from GPS and sequential satellite images, Ann. Glaciol.,
27, 54–60, https://doi.org/10.3189/1998AoG27-1-54-60, 1998.
Frezzotti, M., Tabacco, I. E., and Zirizzotti, A.: Ice discharge of eastern
Dome C drainage area, Antarctica, determined from airborne radar survey and
satellite image analysis, J. Glaciol., 46, 253–264,
https://doi.org/10.3189/172756500781832855, 2000.
Fürst, J. J., Durand, G., Gillet-Chaulet, F., Tavard, L., Rankl, M.,
Braun, M., and Gagliardini, O.: The safety band of Antarctic ice shelves,
Nat. Clim. Change, 6, 479–482, https://doi.org/10.1038/nclimate2912, 2016.
Gardner, A. S., Moholdt, G., Scambos, T., Fahnstock, M., Ligtenberg, S., van den Broeke, M., and Nilsson, J.: Increased West Antarctic and unchanged East Antarctic ice discharge over the last 7 years, The Cryosphere, 12, 521–547, https://doi.org/10.5194/tc-12-521-2018, 2018.
Gardner, A. S., Fahnestock, M. A., and Scambos, T. A.: ITS_LIVE Regional Glacier and Ice Sheet Surface Velocities, National Snow and Ice Data Center [data set], https://its-live.jpl.nasa.gov/ (last access: 26 February 2022), 2019.
Glenn, S. M., Miles, T. N., Serokal, G. N., Xu, Y., Forney, R. K., Yu, F.,
Roarty, H., Schofield, O., and Kohut, J.: Stratified coastal ocean
interactions with tropical cyclones, Nat. Commun., 7, 10887(2016),
https://doi.org/10.1038/ncomms10887, 2016.
Greene, C. A., Blankenship, D. D., Gwyther, D. E., Silvano, A., and van
Wijk, E.: Wind causes Totten Ice Shelf melt and acceleration, Science
Advances, 3, e1701681, https://doi.org/10.1126/sciadv.1701681, 2017.
Greene, C. A., Young, D. A., Gwyther, D. E., Galton-Fenzi, B. K., and Blankenship, D. D.: Seasonal dynamics of Totten Ice Shelf controlled by sea ice buttressing, The Cryosphere, 12, 2869–2882, https://doi.org/10.5194/tc-12-2869-2018, 2018.
Greene, C. A., Gardner, A. S., and Andrews, L. C.: Detecting seasonal ice dynamics in satellite images, The Cryosphere, 14, 4365–4378, https://doi.org/10.5194/tc-14-4365-2020, 2020.
Halliday, D., Resnick, R., and Walker, J.: Fundamentals of physics, 10th edn., John Wiley & Sons, ISBN 111823071X, 9781118230718, 2013.
Heid, T. and Kääb, A.: Evaluation of existing image matching
methods for deriving glacier surface displacements globally from optical
satellite imagery, Remote Sens. Environ., 118, 339–355,
https://doi.org/10.1016/j.rse.2011.11.024, 2012.
IPCC: The Ocean and Cryosphere in a Changing Climate: A Special Report of the Intergovernmental Panel on Climate Change, Working Group II Technical Support Unit, 756 pp., https://www.ipcc.ch/srocc/ (last access: 26 February 2022), 2019.
Joughin, I., Shean, D. E., Smith, B. E., and Floricioiu, D.: A decade of variability on Jakobshavn Isbræ: ocean temperatures pace speed through influence on mélange rigidity, The Cryosphere, 14, 211–227, https://doi.org/10.5194/tc-14-211-2020, 2020.
Joughin, I., Shapero, D., Smith, B., Dutrieux, P., and Barham, M.: Ice-shelf retreat drives recent Pine Island Glacier speedup, Science Advances, 7, eabg3080, https://doi.org/10.1126/sciadv.abg3080, 2021.
Kim, K.: Satellite mapping and automated feature extraction: geographic information system-based change detection of the Antarctic coast, Doctoral dissertation, The Ohio State University, Columbus, Ohio, 171 pp., http://rave.ohiolink.edu/etdc/view?acc_num=osu1072898409 (last access: 26 February 2022), 2004.
Li, J. and Roy, D. P.: A Global Analysis of Sentinel-2A, Sentinel-2B and Landsat-8 Data Revisit Intervals and Implications for Terrestrial Monitoring, Remote Sens., 9, 902, https://doi.org/10.3390/rs9090902, 2017.
Li, R.: Potential of high-resolution satellite imagery for national mapping
products, Photogramm. Eng. Rem. S., 64, 1165–1169, 1998.
Li, R., Hwangbo, J., Chen, Y., and Di, K.: Rigorous Photogrammetric
Processing of HiRISE Stereo Imagery for Mars Topographic Mapping, IEEE T.
Geosci. Remote, 49, 2558–2572, https://doi.org/10.1109/TGRS.2011.2107522,
2011.
Li, R., Ye, W., Qiao, G., Tong, X., Liu, S., Kong, F., and Ma, X.: A New
Analytical Method for Estimating Antarctic Ice Flow in the 1960s From
Historical Optical Satellite Imagery, IEEE T. Geosci. Remote, 55,
2771–2785, https://doi.org/10.1109/TGRS.2017.2654484, 2017.
Li, X., Rignot, E., Morlighem, M., Mouginot, J., and Scheuchl, B.: Grounding
line retreat of Totten Glacier, East Antarctica, 1996 to 2013, Geophys. Res.
Lett., 42, 8049–8056, https://doi.org/10.1002/2015GL065701, 2015.
Li, X., Rignot, E., Mouginot, J., and Scheuchl, B.: Ice flow dynamics and
mass loss of Totten Glacier, East Antarctica, from 1989 to 2015, Geophys.
Res. Lett., 43, 6366–6373, https://doi.org/10.1002/2016GL069173, 2016.
Lillesand, T. R. W. K.: Remote sensing and image interpretation, 7th edn., John Wiley & Sons, ISBN-13 978-1118343289, ISBN-10 111834328X, 2015.
McGlone, J. C.: Manual of Photogrammetry, sixth edn., ASPRS Publications, Maryland, MD, USA, ISBN-10 1570830991, ISBN-13 978-1570830990, 2013.
Montgomery, D. C., Peck, E. A., and Vining, G. G.: Introduction to Linear Regression Analysis, 6th edn., John Wiley & Sons, ISBN-10 1119578728, ISBN-13 978-1119578727, 2021.
Moon, J., Cho, Y., and Lee, H.: Flow Velocity Change of David Glacier, East
Antarctica, from 2016 to 2020 Observed by Sentinel-1A SAR Offset Tracking
Method, Korean Journal of Remote Sensing, 37, 1–11,
https://doi.org/10.7780/kjrs.2021.37.1.1, 2021.
Morlighem, M., Rignot, E., Binder, T., Blankenship, D., Drews, R., Eagles,
G., Eisen, O., Ferraccioli, F., Forsberg, R., Fretwell, P., Goel, V.,
Greenbaum, J. S., Gudmundsson, H., Guo, J., Helm, V., Hofstede, C., Howat,
I., Humbert, A., Jokat, W., Karlsson, N. B., Lee, W. S., Matsuoka, K.,
Millan, R., Mouginot, J., Paden, J., Pattyn, F., Roberts, J., Rosier, S.,
Ruppel, A., Seroussi, H., Smith, E. C., Steinhage, D., Sun, B., Broeke, M.
R. V. D., Ommen, T. D. V., Wessem, M. V., and Young, D. A.: Deep glacial
troughs and stabilizing ridges unveiled beneath the margins of the Antarctic
ice sheet, Nat. Geosci., 13, 132–137,
https://doi.org/10.1038/s41561-019-0510-8, 2020.
Nakamura, K., Doi, K., and Shibuya, K.: Fluctuations in the flow velocity of
the Antarctic Shirase Glacier over an 11-year period, Polar Sci., 4,
443–455, https://doi.org/10.1016/j.polar.2010.04.010, 2010.
Rignot, E., Mouginot, J., and Scheuchl, B.: Ice Flow of the Antarctic Ice
Sheet, Science, 333, 1427–1430, 2011a.
Rignot, E., Velicogna, I., van den Broeke, M. R., Monaghan, A., and Lenaerts, J.: Acceleration of the contribution of the Greenland and Antarctic ice sheets to sea level rise, Geophys. Res. Lett., 38, L05503, https://doi.org/10.1029/2011GL046583, 2011b.
Rignot, E., Mouginot, J., and Scheuchl, B.: Antarctic grounding line mapping
from differential satellite radar interferometry, Geophys. Res. Lett.,
38, L10504, https://doi.org/10.1029/2011GL047109, 2011c.
Rignot, E., Mouginot, J., Scheuchl, B., van den Broeke, M., van Wessem, M.
J., and Morlighem, M.: Four decades of Antarctic Ice Sheet mass balance from
1979–2017, P. Natl. Acad. Sci. USA, 116, 1095–1103,
https://doi.org/10.1073/pnas.1812883116, 2019.
Ruffner, K. C.: CORONA: America’s First Satellite Program, https://apps.dtic.mil/sti/citations/ADA499635 (last access: 26 February 2022), 1995.
Sabins Jr., F. and James, F. A.: Remote Sensing: Principles, Interpretation, and Applications, 4th edn., Waveland Press, ISBN-10 1478637102, ISBN-13 978-1478637103, 2020.
Scambos, T. A., Dutkiewicz, M. J., Wilson, J. C., and Bindschadler, R. A.:
Application of image cross-correlation to the measurement of glacier
velocity using satellite image data, Remote Sens. Environ., 42, 177–186,
https://doi.org/10.1016/0034-4257(92)90101-O, 1992.
Schenk, T.: Digital Photogrammetry, TerraScience, Laurelville, Ohio, ISBN-10 0967765315, 1999.
Shen, Q., Wang, H., Shum, C. K., Jiang, L., Hsu, H. T., and Dong, J.: Recent
high-resolution Antarctic ice velocity maps reveal increased mass loss in
Wilkes Land, East Antarctica, Sci. Rep.-UK, 8, 4477,
https://doi.org/10.1038/s41598-018-22765-0, 2018.
Shepherd, A., Ivins, E. R., Geruo, A., Barletta, V. R., Bentley, M. J., Bettadpur, S., Briggs, K. H., Bromwich, D. H., Forsberg, R., Galin, N., Horwath, M., Jacobs, S., Joughin, I., King, M. A., Lenaerts, J. T. M., Li, J., Ligtenberg, S. R. M., Luckman, A., Luthcke, S. B., McMillan, M., Meister, R., Milne, G., Mouginot, J., Muir, A., Nicolas, J. P., Paden, J., Payne, A. J., Pritchard, H., Rignot, E., Rott, H., Sorensen, L. S., Scambos, T. A., Scheuchl, B., Schrama, E. J. O., Smith, B., Sundal, A. V., van Angelen, J. H., van de Berg, W. J., van den Broeke, M. R., Vaughan, D. G., Velicogna, I., Wahr, J., Whitehouse, P. L., Wingham, D. J., Yi, D., Young, D., and Zwally, H. J.: A Reconciled Estimate of Ice-Sheet Mass Balance, Science, 338, 1183–1189, https://doi.org/10.1126/science.1228102, 2012.
Shepherd, A., Ivins, E., Rignot, E., Smith, B., van den Broeke, M., Velicogna, I., Whitehouse, P., Briggs, K., Joughin, I., Krinner, G., Nowicki, S., Payne, T., Scambos, T., Schlegel, N., Geruo, A., Agosta, C., Ahlstrom, A., Babonis, G., Barletta, V., Blazquez, A., Bonin, J., Csatho, B., Cullather, R., Felikson, D., Fettweis, X., Forsberg, R., Gallee, H., Gardner, A., Gilbert, L., Groh, A., Gunter, B., Hanna, E., Harig, C., Helm, V., Horvath, A., Horwath, M., Khan, S., Kjeldsen, K. K., Konrad, H., Langen, P., Lecavalier, B., Loomis, B., Luthcke, S., McMillan, M., Melini, D., Mernild, S., Mohajerani, Y., Moore, P., Mouginot, J., Moyano, G., Muir, A., Nagler, T., Nield, G., Nilsson, J., Noel, B., Otosaka, I., Pattle, M. E., Peltier, W. R., Pie, N., Rietbroek, R., Rott, H., Sandberg-Sorensen, L., Sasgen, I., Save, H., Scheuchl, B., Schrama, E., Schroeder, L., Seo, K., Simonsen, S., Slater, T., Spada, G., Sutterley, T., Talpe, M., Tarasov, L., van de Berg, W. J., van der Wal, W., van Wessem, M., Vishwakarma, B. D., Wiese, D., and Wouters, B.: Mass balance of the Antarctic Ice Sheet from 1992 to 2017, Nature, 558, 219–222, https://doi.org/10.1038/s41586-018-0179-y, 2018.
Shimizu, M. and Okutomi, M.: Sub-pixel estimation error cancellation on
area-based matching, Int. J. Comput. Vision, 63, 207–224,
https://doi.org/10.1007/s11263-005-6878-5, 2005.
Storey, J., Choate, M., and Lee, K.: Landsat 8 Operational Land Imager
On-Orbit Geometric Calibration and Performance, Remote Sens.-Basel, 6,
11127–11152, https://doi.org/10.3390/rs61111127, 2014.
van Sebille, E., Griffies, S. M., Abernathey, R., Adams, T. P., Berloff, P.,
Biastoch, A., Blanke, B., Chassignet, E. P., Cheng, Y., Cotter, C. J.,
Deleersnijder, E., Doos, K., Drake, H. F., Drijfhout, S., Gary, S. F.,
Heemink, A. W., Kjellsson, J., Koszalka, I. M., Lange, M., Lique, C.,
MacGilchrist, G. A., Marsh, R., Adame, C. G. M., McAdam, R., Nencioli, F.,
Paris, C. B., Piggott, M. D., Polton, J. A., Ruehs, S., Shah, S. H. A. M.,
Thomas, M. D., Wang, J., Wolfram, P. J., Zanna, L., and Zika, J. D.:
Lagrangian ocean analysis: Fundamentals and practices, Ocean Model.,
121, 49–75, https://doi.org/10.1016/j.ocemod.2017.11.008, 2018.
Wang, S., Liu, H., Yu, B., Zhou, G., and Cheng, X.: Revealing the early ice
flow patterns with historical Declassified Intelligence Satellite
Photographs back to 1960s, Geophys. Res. Lett., 43, 5758–5767,
https://doi.org/10.1002/2016GL068990, 2016.
Wulder, M. A., Loveland, T. R., Roy, D. P., Crawford, C. J., Masek, J. G.,
Woodcock, C. E., Allen, R. G., Anderson, M. C., Belward, A. S., Cohen, W.
B., Dwyer, J., Erb, A., Gao, F., Griffiths, P., Helder, D., Hermosillo, T.,
Hipple, J. D., Hostert, P., Hughes, M. J., Huntington, J., Johnson, D. M.,
Kennedy, R., Kilic, A., Li, Z., Lymburner, L., McCorkel, J., Pahlevan, N.,
Scambos, T. A., Schaaf, C., Schott, J. R., Sheng, Y., Storey, J., Vermote,
E., Vogelmann, J., White, J. C., Wynne, R. H., and Zhu, Z.: Current status
of Landsat program, science, and applications, Remote Sens. Environ.,
225, 127–147, https://doi.org/10.1016/j.rse.2019.02.015, 2019.
Ye, W., Qiao, G., Kong, F., Ma, X., Tong, X., and Li, R.: Improved geometric
modeling of 1960s KH-5 ARGON satellite images for regional antarctica
applications, Photogramm. Eng. Rem. S., 83, 477–491, 2017.
Zhou, C., Zhou, Y., Deng, F., Ai, S., Wang, Z., and E, D.: Seasonal and
interannual ice velocity changes of Polar Record Glacier, East Antarctica,
Ann. Glaciol., 55, 45–51, https://doi.org/10.3189/2014AoG66A185, 2014.
Short summary
Historical velocity maps of the Antarctic ice sheet are valuable for long-term ice flow dynamics analysis. We developed an innovative method for correcting overestimations existing in historical velocity maps. The method is validated rigorously using high-quality Landsat 8 images and then successfully applied to historical velocity maps. The historical change signatures are preserved and can be used for assessing the impact of long-term global climate changes on the ice sheet.
Historical velocity maps of the Antarctic ice sheet are valuable for long-term ice flow dynamics...
