Articles | Volume 17, issue 9
https://doi.org/10.5194/tc-17-3785-2023
© Author(s) 2023. 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-17-3785-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Unveiling spatial variability within the Dotson Melt Channel through high-resolution basal melt rates from the Reference Elevation Model of Antarctica
Ann-Sofie Priergaard Zinck
CORRESPONDING AUTHOR
Department of Geoscience & Remote Sensing, Delft University of Technology, Delft, the Netherlands
Institute for Marine and Atmospheric Research Utrecht (IMAU), Utrecht University, Utrecht, the Netherlands
Bert Wouters
Department of Geoscience & Remote Sensing, Delft University of Technology, Delft, the Netherlands
Institute for Marine and Atmospheric Research Utrecht (IMAU), Utrecht University, Utrecht, the Netherlands
Erwin Lambert
Research and Development Weather and Climate Modelling (RDWK), Royal Netherlands Meteorological Institute (KNMI), De Bilt, the Netherlands
Stef Lhermitte
Department of Earth and Environmental Sciences, Katholieke Universiteit Leuven, Leuven, Belgium
Department of Geoscience & Remote Sensing, Delft University of Technology, Delft, the Netherlands
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Ann-Sofie P. Zinck, Bert Wouters, Franka Jesse, and Stef Lhermitte
EGUsphere, https://doi.org/10.5194/egusphere-2025-573, https://doi.org/10.5194/egusphere-2025-573, 2025
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Ocean-driven basal melting of ice shelves can carve channels into the ice shelf base. These channels represent potential weak areas of the ice shelf. On George VI Ice shelf we discover a new channel which onset coincides with the 2015 El-Nino Southern Oscillation event. Since the channel has developed rapidly and is located within a highly channelized area close to the ice shelf front it poses a potential thread of ice shelf retreat.
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The Müller Ice Cap will soon set the scene for a new drilling project. To obtain an ice core with stratified layers and a good time resolution, thickness estimates are necessary for the planning. Here we present a new and fast method of estimating ice thicknesses from sparse data and compare it to an existing ice flow model. We find that the new semi-empirical method is insensitive to mass balance, is computationally fast, and provides good fits when compared to radar measurements.
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Due to recurrent melt and refreezing events in recent decades, the snow conditions over Greenland have changed. To observe this, we use a parameter (leading edge width; LeW) derived from satellite altimetry and analyse its spatial and temporal variations. By comparing the LeW variations with modelled firn parameters, we concluded that the 2012 melt event and the recent and increasingly frequent melt events have a long-lasting impact on the volume scattering of Greenland firn.
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Insights on management's impact on forest carbon stocks are crucial for sustainable forest management practices. However, accurately monitoring carbon stocks remains a technological challenge. This study estimates above-ground carbon stock in managed and unmanaged forests using passive optical, synthetic aperture radar (SAR), and light detection and ranging (lidar) remote sensing data. Results show promising potential in using multiple remote sensing predictors and publicly available high-resolution data for mapping forest carbon stocks.
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Earth Syst. Dynam., 16, 1303–1323, https://doi.org/10.5194/esd-16-1303-2025, https://doi.org/10.5194/esd-16-1303-2025, 2025
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Ocean warming around Antarctica leads to ice melting and sea-level rise. The meltwater that flows into the surrounding ocean can lead to enhanced warming of the seawater, thereby again increasing melting and sea-level rise. This process, however, is not currently included in climate models. Through a simple mathematical approach, we find that this process can lead to more melting and greater sea-level rise, possibly increasing the Antarctic contribution to 21st century sea-level rise by 80 %.
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This preprint is open for discussion and under review for The Cryosphere (TC).
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We produce annual maps of Antarctic surface melt volumes from 2012 to 2021 using satellite microwave data. We detect melting days from thresholds on the satellite signal and then use actual melt measurements from weather stations to convert those signals into water‑equivalent volumes. Our maps capture known melt hotspots and show slightly lower totals than climate models. This dataset supports climate and ice‑shelf studies.
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The Cryosphere, 19, 2495–2505, https://doi.org/10.5194/tc-19-2495-2025, https://doi.org/10.5194/tc-19-2495-2025, 2025
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The effect of ocean warming on Antarctic ice-sheet melting is a major source of uncertainty in estimates of future sea level rise. We compare five melt models to show that ocean warming strongly increases melting. Despite their calibration based on present-day melting, the models disagree on the amount of melt increase. In some important regions, the difference reaches a factor 100. We conclude that using various melt models is important to accurately estimate uncertainties in future sea level rise.
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The Cryosphere, 19, 2289–2314, https://doi.org/10.5194/tc-19-2289-2025, https://doi.org/10.5194/tc-19-2289-2025, 2025
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We present the first evaluation of Greenland ice sheet (GrIS) and climate feedbacks with a CMIP model. Under 4×CO2 forcing, lower elevations reduce GrIS summer blocking and incoming solar radiation and increase precipitation. Simulated increases of near-surface summer temperature are much lower than the 6 K km-1 lapse rate that is commonly used in non-coupled simulations. CO2 reduction to pre-industrial (PI) halts GrIS mass loss regardless of higher global warming and albedo than PI control.
Matthias O. Willen, Bert Wouters, Taco Broerse, Eric Buchta, and Veit Helm
The Cryosphere, 19, 2213–2227, https://doi.org/10.5194/tc-19-2213-2025, https://doi.org/10.5194/tc-19-2213-2025, 2025
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Collapse of the West Antarctic Ice Sheet in the Amundsen Sea Embayment is likely in the near future. Vertical uplift of bedrock due to glacial isostatic adjustment stabilizes the ice sheet and may delay its collapse. So far, only spatially and temporally sparse GPS measurements have been able to observe this bedrock motion. We have combined satellite data and quantified a region-wide bedrock motion that independently matches GPS measurements. This can improve ice sheet predictions.
Ann-Sofie P. Zinck, Bert Wouters, Franka Jesse, and Stef Lhermitte
EGUsphere, https://doi.org/10.5194/egusphere-2025-573, https://doi.org/10.5194/egusphere-2025-573, 2025
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Ocean-driven basal melting of ice shelves can carve channels into the ice shelf base. These channels represent potential weak areas of the ice shelf. On George VI Ice shelf we discover a new channel which onset coincides with the 2015 El-Nino Southern Oscillation event. Since the channel has developed rapidly and is located within a highly channelized area close to the ice shelf front it poses a potential thread of ice shelf retreat.
Franka Jesse, Erwin Lambert, and Roderik S. W. van de Wal
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We introduce the coupling of a sub-shelf melt model with an ice sheet model to explore how horizontal meltwater flow below ice shelves affects ice sheet mass loss over time. We show that accurately modelling the meltwater flow direction leads to distinct feedbacks and transient volume loss, not captured by melt parameterisations that simplify flow direction. Our results highlight the importance of refining the meltwater flow representation in ice sheet models to improve sea level projections.
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The Cryosphere, 19, 37–61, https://doi.org/10.5194/tc-19-37-2025, https://doi.org/10.5194/tc-19-37-2025, 2025
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Ice shelves, the floating extensions of Antarctica’s ice sheet, play a crucial role in preventing mass ice loss, and understanding their stability is crucial. If surface meltwater lakes drain rapidly through fractures, the ice shelf can destabilize. We analyzed satellite images of three years from the Shackleton Ice Shelf and found that lake drainages occurred in areas where damage is present and developing, and coincided with rising tides, offering insights into the drivers of this process.
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Snowfall measurements at high latitudes are crucial for estimating ice sheet mass balance. Spaceborne radar and radiometer missions help estimate snowfall but face uncertainties. This work evaluates uncertainties in snowfall estimates from a fixed near-nadir radar (CloudSat-like) and a conically scanning radar (WIVERN-like), determining that WIVERN will provide much better estimates than CloudSat, and at much smaller spatial and temporal scales.
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Determining the net balance of snow accumulation on the surface of Antarctica is challenging. Sentinel-1 satellite sensors, which can see through snow, offer a promising method. However, linking their signals to snow amounts is complex due to snow's internal structure and limited on-the-ground data. This study found a connection between satellite signals and snow levels at three locations in Dronning Maud Land. Using models and field data, the method shows potential for wider use in Antarctica.
Jordi Bolibar, Facundo Sapienza, Fabien Maussion, Redouane Lguensat, Bert Wouters, and Fernando Pérez
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We developed a new modelling framework combining numerical methods with machine learning. Using this approach, we focused on understanding how ice moves within glaciers, and we successfully learnt a prescribed law describing ice movement for 17 glaciers worldwide as a proof of concept. Our framework has the potential to discover important laws governing glacier processes, aiding our understanding of glacier physics and their contribution to water resources and sea-level rise.
Lena G. Buth, Valeria Di Biase, Peter Kuipers Munneke, Stef Lhermitte, Sanne B. M. Veldhuijsen, Sophie de Roda Husman, Michiel R. van den Broeke, and Bert Wouters
EGUsphere, https://doi.org/10.5194/egusphere-2023-2000, https://doi.org/10.5194/egusphere-2023-2000, 2023
Preprint archived
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Liquid meltwater which is stored in air bubbles in the compacted snow near the surface of Antarctica can affect ice shelf stability. In order to detect the presence of such firn aquifers over large scales, satellite remote sensing is needed. In this paper, we present our new detection method using radar satellite data as well as the results for the whole Antarctic Peninsula. Firn aquifers are found in the north and northwest of the peninsula, in agreement with locations predicted by models.
Erwin Lambert, André Jüling, Roderik S. W. van de Wal, and Paul R. Holland
The Cryosphere, 17, 3203–3228, https://doi.org/10.5194/tc-17-3203-2023, https://doi.org/10.5194/tc-17-3203-2023, 2023
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A major uncertainty in the study of sea level rise is the melting of the Antarctic ice sheet by the ocean. Here, we have developed a new model, named LADDIE, that simulates this ocean-driven melting of the floating parts of the Antarctic ice sheet. This model simulates fine-scale patterns of melting and freezing and requires significantly fewer computational resources than state-of-the-art ocean models. LADDIE can be used as a new tool to force high-resolution ice sheet models.
Diana Francis, Ricardo Fonseca, Kyle S. Mattingly, Stef Lhermitte, and Catherine Walker
The Cryosphere, 17, 3041–3062, https://doi.org/10.5194/tc-17-3041-2023, https://doi.org/10.5194/tc-17-3041-2023, 2023
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Role of Foehn Winds in ice and snow conditions at the Pine Island Glacier, West Antarctica.
Inès N. Otosaka, Andrew Shepherd, Erik R. Ivins, Nicole-Jeanne Schlegel, Charles Amory, Michiel R. van den Broeke, Martin Horwath, Ian Joughin, Michalea D. King, Gerhard Krinner, Sophie Nowicki, Anthony J. Payne, Eric Rignot, Ted Scambos, Karen M. Simon, Benjamin E. Smith, Louise S. Sørensen, Isabella Velicogna, Pippa L. Whitehouse, Geruo A, Cécile Agosta, Andreas P. Ahlstrøm, Alejandro Blazquez, William Colgan, Marcus E. Engdahl, Xavier Fettweis, Rene Forsberg, Hubert Gallée, Alex Gardner, Lin Gilbert, Noel Gourmelen, Andreas Groh, Brian C. Gunter, Christopher Harig, Veit Helm, Shfaqat Abbas Khan, Christoph Kittel, Hannes Konrad, Peter L. Langen, Benoit S. Lecavalier, Chia-Chun Liang, Bryant D. Loomis, Malcolm McMillan, Daniele Melini, Sebastian H. Mernild, Ruth Mottram, Jeremie Mouginot, Johan Nilsson, Brice Noël, Mark E. Pattle, William R. Peltier, Nadege Pie, Mònica Roca, Ingo Sasgen, Himanshu V. Save, Ki-Weon Seo, Bernd Scheuchl, Ernst J. O. Schrama, Ludwig Schröder, Sebastian B. Simonsen, Thomas Slater, Giorgio Spada, Tyler C. Sutterley, Bramha Dutt Vishwakarma, Jan Melchior van Wessem, David Wiese, Wouter van der Wal, and Bert Wouters
Earth Syst. Sci. Data, 15, 1597–1616, https://doi.org/10.5194/essd-15-1597-2023, https://doi.org/10.5194/essd-15-1597-2023, 2023
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By measuring changes in the volume, gravitational attraction, and ice flow of Greenland and Antarctica from space, we can monitor their mass gain and loss over time. Here, we present a new record of the Earth’s polar ice sheet mass balance produced by aggregating 50 satellite-based estimates of ice sheet mass change. This new assessment shows that the ice sheets have lost (7.5 x 1012) t of ice between 1992 and 2020, contributing 21 mm to sea level rise.
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.
Lena G. Buth, Bert Wouters, Sanne B. M. Veldhuijsen, Stef Lhermitte, Peter Kuipers Munneke, and Michiel R. van den Broeke
The Cryosphere Discuss., https://doi.org/10.5194/tc-2022-127, https://doi.org/10.5194/tc-2022-127, 2022
Manuscript not accepted for further review
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Liquid meltwater which is stored in air bubbles in the compacted snow near the surface of Antarctica can affect ice shelf stability. In order to detect the presence of such firn aquifers over large scales, satellite remote sensing is needed. In this paper, we present our new detection method using radar satellite data as well as the results for the whole Antarctic Peninsula. Firn aquifers are found in the north and northwest of the peninsula, in agreement with locations predicted by models.
Bas Altena, Andreas Kääb, and Bert Wouters
The Cryosphere, 16, 2285–2300, https://doi.org/10.5194/tc-16-2285-2022, https://doi.org/10.5194/tc-16-2285-2022, 2022
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Repeat overflights of satellites are used to estimate surface displacements. However, such products lack a simple error description for individual measurements, but variation in precision occurs, since the calculation is based on the similarity of texture. Fortunately, variation in precision manifests itself in the correlation peak, which is used for the displacement calculation. This spread is used to make a connection to measurement precision, which can be of great use for model inversion.
Weiran Li, Cornelis Slobbe, and Stef Lhermitte
The Cryosphere, 16, 2225–2243, https://doi.org/10.5194/tc-16-2225-2022, https://doi.org/10.5194/tc-16-2225-2022, 2022
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This study proposes a new method for correcting the slope-induced errors in satellite radar altimetry. The slope-induced errors can significantly affect the height estimations of ice sheets if left uncorrected. This study applies the method to radar altimetry data (CryoSat-2) and compares the performance with two existing methods. The performance is assessed by comparison with independent height measurements from ICESat-2. The assessment shows that the method performs promisingly.
F. Dahle, J. Tanke, B. Wouters, and R. Lindenbergh
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., V-2-2022, 237–244, https://doi.org/10.5194/isprs-annals-V-2-2022-237-2022, https://doi.org/10.5194/isprs-annals-V-2-2022-237-2022, 2022
Ann-Sofie Priergaard Zinck and Aslak Grinsted
The Cryosphere, 16, 1399–1407, https://doi.org/10.5194/tc-16-1399-2022, https://doi.org/10.5194/tc-16-1399-2022, 2022
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The Müller Ice Cap will soon set the scene for a new drilling project. To obtain an ice core with stratified layers and a good time resolution, thickness estimates are necessary for the planning. Here we present a new and fast method of estimating ice thicknesses from sparse data and compare it to an existing ice flow model. We find that the new semi-empirical method is insensitive to mass balance, is computationally fast, and provides good fits when compared to radar measurements.
Zhongyang Hu, Peter Kuipers Munneke, Stef Lhermitte, Maaike Izeboud, and Michiel van den Broeke
The Cryosphere, 15, 5639–5658, https://doi.org/10.5194/tc-15-5639-2021, https://doi.org/10.5194/tc-15-5639-2021, 2021
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Antarctica is shrinking, and part of the mass loss is caused by higher temperatures leading to more snowmelt. We use computer models to estimate the amount of melt, but this can be inaccurate – specifically in the areas with the most melt. This is because the model cannot account for small, darker areas like rocks or darker ice. Thus, we trained a computer using artificial intelligence and satellite images that showed these darker areas. The model computed an improved estimate of melt.
Jan Bouke Pronk, Tobias Bolch, Owen King, Bert Wouters, and Douglas I. Benn
The Cryosphere, 15, 5577–5599, https://doi.org/10.5194/tc-15-5577-2021, https://doi.org/10.5194/tc-15-5577-2021, 2021
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About 10 % of Himalayan glaciers flow directly into lakes. This study finds, using satellite imagery, that such glaciers show higher flow velocities than glaciers without ice–lake contact. In particular near the glacier tongue the impact of a lake on the glacier flow can be dramatic. The development of current and new meltwater bodies will influence the flow of an increasing number of Himalayan glaciers in the future, a scenario not currently considered in regional ice loss projections.
Weiran Li, Stef Lhermitte, and Paco López-Dekker
The Cryosphere, 15, 5309–5322, https://doi.org/10.5194/tc-15-5309-2021, https://doi.org/10.5194/tc-15-5309-2021, 2021
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Surface meltwater lakes have been observed on several Antarctic ice shelves in field studies and optical images. Meltwater lakes can drain and refreeze, increasing the fragility of the ice shelves. The combination of synthetic aperture radar (SAR) backscatter and interferometric information (InSAR) can provide the cryosphere community with the possibility to continuously assess the dynamics of the meltwater lakes, potentially helping to facilitate the study of ice shelves in a changing climate.
Rajashree Tri Datta and Bert Wouters
The Cryosphere, 15, 5115–5132, https://doi.org/10.5194/tc-15-5115-2021, https://doi.org/10.5194/tc-15-5115-2021, 2021
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The ICESat-2 laser altimeter can detect the surface and bottom of a supraglacial lake. We introduce the Watta algorithm, automatically calculating lake surface, corrected bottom, and (sub-)surface ice at high resolution adapting to signal strength. ICESat-2 depths constrain full lake depths of 46 lakes over Jakobshavn glacier using multiple sources of imagery, including very high-resolution Planet imagery, used for the first time to extract supraglacial lake depths empirically using ICESat-2.
Annelies Voordendag, Marion Réveillet, Shelley MacDonell, and Stef Lhermitte
The Cryosphere, 15, 4241–4259, https://doi.org/10.5194/tc-15-4241-2021, https://doi.org/10.5194/tc-15-4241-2021, 2021
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The sensitivity of two snow models (SNOWPACK and SnowModel) to various parameterizations and atmospheric forcing biases is assessed in the semi-arid Andes of Chile in winter 2017. Models show that sublimation is a main driver of ablation and that its relative contribution to total ablation is highly sensitive to the selected albedo parameterization and snow roughness length. The forcing and parameterizations are more important than the model choice, despite differences in physical complexity.
Maurice van Tiggelen, Paul C. J. P. Smeets, Carleen H. Reijmer, Bert Wouters, Jakob F. Steiner, Emile J. Nieuwstraten, Walter W. Immerzeel, and Michiel R. van den Broeke
The Cryosphere, 15, 2601–2621, https://doi.org/10.5194/tc-15-2601-2021, https://doi.org/10.5194/tc-15-2601-2021, 2021
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We developed a method to estimate the aerodynamic properties of the Greenland Ice Sheet surface using either UAV or ICESat-2 elevation data. We show that this new method is able to reproduce the important spatiotemporal variability in surface aerodynamic roughness, measured by the field observations. The new maps of surface roughness can be used in atmospheric models to improve simulations of surface turbulent heat fluxes and therefore surface energy and mass balance over rough ice worldwide.
Diana Francis, Kyle S. Mattingly, Stef Lhermitte, Marouane Temimi, and Petra Heil
The Cryosphere, 15, 2147–2165, https://doi.org/10.5194/tc-15-2147-2021, https://doi.org/10.5194/tc-15-2147-2021, 2021
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The unexpected September 2019 calving event from the Amery Ice Shelf, the largest since 1963 and which occurred almost a decade earlier than expected, was triggered by atmospheric extremes. Explosive twin polar cyclones provided a deterministic role in this event by creating oceanward sea surface slope triggering the calving. The observed record-anomalous atmospheric conditions were promoted by blocking ridges and Antarctic-wide anomalous poleward transport of heat and moisture.
Xavier Fettweis, Stefan Hofer, Uta Krebs-Kanzow, Charles Amory, Teruo Aoki, Constantijn J. Berends, Andreas Born, Jason E. Box, Alison Delhasse, Koji Fujita, Paul Gierz, Heiko Goelzer, Edward Hanna, Akihiro Hashimoto, Philippe Huybrechts, Marie-Luise Kapsch, Michalea D. King, Christoph Kittel, Charlotte Lang, Peter L. Langen, Jan T. M. Lenaerts, Glen E. Liston, Gerrit Lohmann, Sebastian H. Mernild, Uwe Mikolajewicz, Kameswarrao Modali, Ruth H. Mottram, Masashi Niwano, Brice Noël, Jonathan C. Ryan, Amy Smith, Jan Streffing, Marco Tedesco, Willem Jan van de Berg, Michiel van den Broeke, Roderik S. W. van de Wal, Leo van Kampenhout, David Wilton, Bert Wouters, Florian Ziemen, and Tobias Zolles
The Cryosphere, 14, 3935–3958, https://doi.org/10.5194/tc-14-3935-2020, https://doi.org/10.5194/tc-14-3935-2020, 2020
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We evaluated simulated Greenland Ice Sheet surface mass balance from 5 kinds of models. While the most complex (but expensive to compute) models remain the best, the faster/simpler models also compare reliably with observations and have biases of the same order as the regional models. Discrepancies in the trend over 2000–2012, however, suggest that large uncertainties remain in the modelled future SMB changes as they are highly impacted by the meltwater runoff biases over the current climate.
Christiaan T. van Dalum, Willem Jan van de Berg, Stef Lhermitte, and Michiel R. van den Broeke
The Cryosphere, 14, 3645–3662, https://doi.org/10.5194/tc-14-3645-2020, https://doi.org/10.5194/tc-14-3645-2020, 2020
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The reflectivity of sunlight, which is also known as albedo, is often inadequately modeled in regional climate models. Therefore, we have implemented a new snow and ice albedo scheme in the regional climate model RACMO2. In this study, we evaluate a new RACMO2 version for the Greenland ice sheet by using observations and the previous model version. RACMO2 output compares well with observations, and by including new processes we improve the ability of RACMO2 to make future climate projections.
Thore Kausch, Stef Lhermitte, Jan T. M. Lenaerts, Nander Wever, Mana Inoue, Frank Pattyn, Sainan Sun, Sarah Wauthy, Jean-Louis Tison, and Willem Jan van de Berg
The Cryosphere, 14, 3367–3380, https://doi.org/10.5194/tc-14-3367-2020, https://doi.org/10.5194/tc-14-3367-2020, 2020
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Ice rises are elevated parts of the otherwise flat ice shelf. Here we study the impact of an Antarctic ice rise on the surrounding snow accumulation by combining field data and modeling. Our results show a clear difference in average yearly snow accumulation between the windward side, the leeward side and the peak of the ice rise due to differences in snowfall and wind erosion. This is relevant for the interpretation of ice core records, which are often drilled on the peak of an ice rise.
Cited articles
Andersen, O., Knudsen, P., and Stenseng, L.: The DTU13 MSS (Mean Sea Surface)
and MDT (Mean Dynamic Topography) from 20 Years of Satellite Altimetry, in:
IGFS 2014, edited by: Jin, S. and Barzaghi, R., 111–121, Springer
International Publishing, Cham, https://doi.org/10.1007/1345_2015_182, 2015. a
Bentley, M. J., Ó Cofaigh, C., Anderson, J. B., Conway, H., Davies, B.,
Graham, A. G., Hillenbrand, C.-D., Hodgson, D. A., Jamieson, S. S., Larter,
R. D., Mackintosh, A., Smith, J. A., Verleyen, E., Ackert, R. P., Bart,
P. J., Berg, S., Brunstein, D., Canals, M., Colhoun, E. A., Crosta, X.,
Dickens, W. A., Domack, E., Dowdeswell, J. A., Dunbar, R., Ehrmann, W.,
Evans, J., Favier, V., Fink, D., Fogwill, C. J., Glasser, N. F., Gohl, K.,
Golledge, N. R., Goodwin, I., Gore, D. B., Greenwood, S. L., Hall, B. L.,
Hall, K., Hedding, D. W., Hein, A. S., Hocking, E. P., Jakobsson, M.,
Johnson, J. S., Jomelli, V., Jones, R. S., Klages, J. P., Kristoffersen, Y.,
Kuhn, G., Leventer, A., Licht, K., Lilly, K., Lindow, J., Livingstone, S. J.,
Massé, G., McGlone, M. S., McKay, R. M., Melles, M., Miura, H.,
Mulvaney, R., Nel, W., Nitsche, F. O., O'Brien, P. E., Post, A. L., Roberts,
S. J., Saunders, K. M., Selkirk, P. M., Simms, A. R., Spiegel, C., Stolldorf,
T. D., Sugden, D. E., van der Putten, N., van Ommen, T., Verfaillie, D.,
Vyverman, W., Wagner, B., White, D. A., Witus, A. E., and Zwartz, D.: A
community-based geological reconstruction of Antarctic Ice Sheet deglaciation
since the Last Glacial Maximum, Quaternary Sci. Rev., 100, 1–9,
https://doi.org/10.1016/j.quascirev.2014.06.025, 2014. a, b
Chartrand, A. M. and Howat, I. M.: Basal Channel Evolution on the Getz Ice
Shelf, West Antarctica, J. Geophys. Res.-Earth, 125, e2019JF005293,
https://doi.org/10.1029/2019JF005293, 2020. a, b
Chartrand, R.: Numerical Differentiation of Noisy, Nonsmooth Data,
ISRN Applied Mathematics, 2011, 1–11, https://doi.org/10.5402/2011/164564, 2011. a, b, c
Chartrand, R.: Numerical differentiation of noisy, nonsmooth, multidimensional
data, in: 2017 IEEE Global Conference on Signal and Information Processing
(GlobalSIP), 2018-Janua, Montreal, QC, Canada
14–16 November 2017, 244–248, IEEE,
https://doi.org/10.1109/GlobalSIP.2017.8308641, 2017. a
Dehecq, A., Gourmelen, N., Shepherd, A., Cullen, R., Trouv, E., Dehecq, A.,
Gourmelen, N., Shepherd, A., Cullen, R., and Trouv, E.: Evaluation of
CryoSat-2 for height retrieval over the Himalayan range, CryoSat-2 third
user workshop, Dresden, Germany,
https://hal.science/hal-00973393, 2013. a
Dutrieux, P., Vaughan, D. G., Corr, H. F. J., Jenkins, A., Holland, P. R., Joughin, I., and Fleming, A. H.: Pine Island glacier ice shelf melt distributed at kilometre scales, The Cryosphere, 7, 1543–1555, https://doi.org/10.5194/tc-7-1543-2013, 2013. a, b
European Space Agency: CryoSat-2 Product Handbook, Paris, France, C2-LI-ACS-ESL-5319, Dec. 2019, https://earth.esa.int/eogateway/documents/20142/37627/CryoSat-Baseline-D-Product-Handbook.pdf (last access: 30 August 2023), 2019. a
Favier, L., Jourdain, N. C., Jenkins, A., Merino, N., Durand, G., Gagliardini, O., Gillet-Chaulet, F., and Mathiot, P.: Assessment of sub-shelf melting parameterisations using the ocean–ice-sheet coupled model NEMO(v3.6)–Elmer/Ice(v8.3) , Geosci. Model Dev., 12, 2255–2283, https://doi.org/10.5194/gmd-12-2255-2019, 2019. a
Gardner, A., Fahnestock, M., and Scambos., T.: MEaSUREs ITS_LIVE Regional
Glacier and Ice Sheet Surface Velocities, Version 1, NASA National Snow and
Ice Data Center Distributed Active Archive Center [data set],
https://doi.org/10.5067/6II6VW8LLWJ7, 2022. a, b
Gladish, C. V., Holland, D. M., Holland, P. R., and Price, S. F.: Ice-shelf
basal channels in a coupled ice/ocean model, J. Glaciol., 58,
1227–1244, https://doi.org/10.3189/2012JoG12J003, 2012. a
Gorelick, N., Hancher, M., Dixon, M., Ilyushchenko, S., Thau, D., and Moore,
R.: Google Earth Engine: Planetary-scale geospatial analysis for everyone,
Remote Sens. Environ., 202, 18–27, https://doi.org/10.1016/j.rse.2017.06.031,
2017. a
Gourmelen, N., Goldberg, D. N., Snow, K., Henley, S. F., Bingham, R. G.,
Kimura, S., Hogg, A. E., Shepherd, A., Mouginot, J., Lenaerts, J. T. M.,
Ligtenberg, S. R. M., and Berg, W. J.: Channelized Melting Drives Thinning
Under a Rapidly Melting Antarctic Ice Shelf, Geophys. Res. Lett.,
44, 9796–9804, https://doi.org/10.1002/2017GL074929, 2017. a, b, c, d, e, f, g, h, i, j, k, l, m, n, o, p, q, r
Gray, L., Burgess, D., Copland, L., Cullen, R., Galin, N., Hawley, R., and Helm, V.: Interferometric swath processing of Cryosat data for glacial ice topography, The Cryosphere, 7, 1857–1867, https://doi.org/10.5194/tc-7-1857-2013, 2013. a
Helm, V., Humbert, A., and Miller, H.: Elevation and elevation change of Greenland and Antarctica derived from CryoSat-2, The Cryosphere, 8, 1539–1559, https://doi.org/10.5194/tc-8-1539-2014, 2014. a
Howat, I. M., Porter, C., Smith, B. E., Noh, M.-J., and Morin, P.: The Reference Elevation Model of Antarctica, The Cryosphere, 13, 665–674, https://doi.org/10.5194/tc-13-665-2019, 2019 (data available at: https://www.pgc.umn.edu/data/rema/, last access: 1 September 2023). a, b, c, d
Jacobs, S., Helmer, H., Doake, C. S. M., Jenkins, A., and Frolich, R. M.:
Melting of ice shelves and the mass balance of Antarctica, J.
Glaciol., 38, 375–387, https://doi.org/10.1017/S0022143000002252, 1992. a
Jenkins, A., Shoosmith, D., Dutrieux, P., Jacobs, S., Kim, T. W., Lee, S. H.,
Ha, H. K., and Stammerjohn, S.: West Antarctic Ice Sheet retreat in the
Amundsen Sea driven by decadal oceanic variability, Nat. Geosci., 11,
733–738, https://doi.org/10.1038/s41561-018-0207-4, 2018. a
Kalnay, E., Kanamitsu, M., Kistler, R., Collins, W., Deaven, D., Gandin, L.,
Iredell, M., Saha, S., White, G., Woollen, J., Zhu, Y., Leetmaa, A.,
Reynolds, R., Chelliah, M., Ebisuzaki, W., Higgins, W., Janowiak, J., Mo,
K. C., Ropelewski, C., Wang, J., Jenne, R., and Joseph, D.: The NCEP/NCAR
40-Year Reanalysis Project, B. Am. Meteorol. Soc.,
77, 437–471, https://doi.org/10.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;2, 1996. a
Lambert, E., Jüling, A., van de Wal, R. S. W., and Holland, P. R.: Modelling Antarctic ice shelf basal melt patterns using the one-layer Antarctic model for dynamical downscaling of ice–ocean exchanges (LADDIE v1.0), The Cryosphere, 17, 3203–3228, https://doi.org/10.5194/tc-17-3203-2023, 2023. a, b, c, d, e
Lazeroms, W. M. J., Jenkins, A., Gudmundsson, G. H., and van de Wal, R. S. W.: Modelling present-day basal melt rates for Antarctic ice shelves using a parametrization of buoyant meltwater plumes, The Cryosphere, 12, 49–70, https://doi.org/10.5194/tc-12-49-2018, 2018. a
Lilien, D. A., Joughin, I., Smith, B., and Shean, D. E.: Changes in flow of Crosson and Dotson ice shelves, West Antarctica, in response to elevated melt, The Cryosphere, 12, 1415–1431, https://doi.org/10.5194/tc-12-1415-2018, 2018. a
Lindbäck, K., Moholdt, G., Nicholls, K. W., Hattermann, T., Pratap, B., Thamban, M., and Matsuoka, K.: Spatial and temporal variations in basal melting at Nivlisen ice shelf, East Antarctica, derived from phase-sensitive radars, The Cryosphere, 13, 2579–2595, https://doi.org/10.5194/tc-13-2579-2019, 2019. a, b, c
Matsuoka, K., Skoglund, A., Roth, G., de Pomereu, J., Griffiths, H., Headland,
R., Herried, B., Katsumata, K., Le Brocq, A., Licht, K., Morgan, F., Neff,
P. D., Ritz, C., Scheinert, M., Tamura, T., Van de Putte, A., van den Broeke,
M., von Deschwanden, A., Deschamps-Berger, C., Van Liefferinge, B., Tronstad,
S., and Melvær, Y.: Quantarctica, an integrated mapping environment for
Antarctica, the Southern Ocean, and sub-Antarctic islands,
Environ. Modell. Softw., 140, 105015, https://doi.org/10.1016/j.envsoft.2021.105015,
2021. a
Moholdt, G., Padman, L., and Fricker, H. A.: Basal mass budget of Ross and
Filchner-Ronne ice shelves, Antarctica, derived from Lagrangian analysis of
ICESat altimetry, J. Geophys. Res.-Earth, 119,
2361–2380, https://doi.org/10.1002/2014JF003171, 2014. a, b, c
Morlighem, M., Goldberg, D., Dias dos Santos, T., Lee, J., and Sagebaum, M.:
Mapping the Sensitivity of the Amundsen Sea Embayment to Changes in External
Forcings Using Automatic Differentiation, Geophys. Res. Lett., 48,
1–8, https://doi.org/10.1029/2021GL095440, 2021. a
Nilsson, J., Gardner, A., Sandberg Sørensen, L., and Forsberg, R.: Improved retrieval of land ice topography from CryoSat-2 data and its impact for volume-change estimation of the Greenland Ice Sheet, The Cryosphere, 10, 2953–2969, https://doi.org/10.5194/tc-10-2953-2016, 2016. a
Noble, T. L., Rohling, E. J., Aitken, A. R. A., Bostock, H. C., Chase, Z.,
Gomez, N., Jong, L. M., King, M. A., Mackintosh, A. N., McCormack, F. S.,
McKay, R. M., Menviel, L., Phipps, S. J., Weber, M. E., Fogwill, C. J.,
Gayen, B., Golledge, N. R., Gwyther, D. E., Hogg, A. M., Martos, Y. M.,
Pena‐Molino, B., Roberts, J., Flierdt, T., and Williams, T.: The
Sensitivity of the Antarctic Ice Sheet to a Changing Climate: Past, Present,
and Future, Rev. Geophys., 58, 1–89, https://doi.org/10.1029/2019RG000663,
2020. a
Pavlis, N. K., Holmes, S. A., Kenyon, S. C., and Factor, J. K.: The
development and evaluation of the Earth Gravitational Model 2008 (EGM2008),
J. Geophys. Res.-Sol. Ea., 117, B04406,
https://doi.org/10.1029/2011JB008916, 2012. a
Rignot, E., Jacobs, S., Mouginot, J., and Scheuchl, B.: Ice-shelf melting
around antarctica, Science, 341, 266–270, https://doi.org/10.1126/science.1235798,
2013. a, b
Ritz, C., Edwards, T. L., Durand, G., Payne, A. J., Peyaud, V., and Hindmarsh,
R. C. A.: Potential sea-level rise from Antarctic ice-sheet instability
constrained by observations, Nature, 528, 115–118,
https://doi.org/10.1038/nature16147, 2015. a
Roberts, J., Galton-Fenzi, B. K., Paolo, F. S., Donnelly, C., Gwyther, D. E.,
Padman, L., Young, D., Warner, R., Greenbaum, J., Fricker, H. A., Payne,
A. J., Cornford, S., Le Brocq, A., van Ommen, T., Blankenship, D., and
Siegert, M. J.: Ocean forced variability of Totten Glacier mass loss,
Geological Society, London, Special Publications, 461, 175–186,
https://doi.org/10.1144/SP461.6, 2018. a, b
Schoof, C.: Ice sheet grounding line dynamics: Steady states, stability, and
hysteresis, J. Geophys. Res., 112, F03S28,
https://doi.org/10.1029/2006JF000664, 2007. a, b
Sergienko, O. V.: Basal channels on ice shelves, J. Geophys.
Res.-Earth, 118, 1342–1355, https://doi.org/10.1002/jgrf.20105, 2013. a
Stanton, T. P., Shaw, W. J., Truffer, M., Corr, H. F. J., Peters, L. E.,
Riverman, K. L., Bindschadler, R., Holland, D. M., and Anandakrishnan, S.:
Channelized ice melting in the ocean boundary layer beneath Pine Island
Glacier, Antarctica., Science, 341, 1236–1239,
https://doi.org/10.1126/science.1239373, 2013. a
van Wessem, J. M., van de Berg, W. J., Noël, B. P. Y., van Meijgaard, E., Amory, C., Birnbaum, G., Jakobs, C. L., Krüger, K., Lenaerts, J. T. M., Lhermitte, S., Ligtenberg, S. R. M., Medley, B., Reijmer, C. H., van Tricht, K., Trusel, L. D., van Ulft, L. H., Wouters, B., Wuite, J., and van den Broeke, M. R.: Modelling the climate and surface mass balance of polar ice sheets using RACMO2 – Part 2: Antarctica (1979–2016), The Cryosphere, 12, 1479–1498, https://doi.org/10.5194/tc-12-1479-2018, 2018. a
Vaňková, I. and Nicholls, K. W.: Ocean Variability Beneath the
Filchner-Ronne Ice Shelf Inferred From Basal Melt Rate Time Series,
J. Geophys. Res.-Oceans, 127, 1–20,
https://doi.org/10.1029/2022JC018879, 2022. a, b, c
Veldhuijsen, S. B. M., van de Berg, W. J., Brils, M., Kuipers Munneke, P., and van den Broeke, M. R.: Characteristics of the 1979–2020 Antarctic firn layer simulated with IMAU-FDM v1.2A, The Cryosphere, 17, 1675–1696, https://doi.org/10.5194/tc-17-1675-2023, 2023. a
Watkins, R. H., Bassis, J. N., and Thouless, M. D.: Roughness of Ice Shelves
Is Correlated With Basal Melt Rates, Geophys. Res. Lett., 48, 1–8,
https://doi.org/10.1029/2021GL094743, 2021. a, b
Wearing, M. G., Stevens, L. A., Dutrieux, P., and Kingslake, J.: Ice‐Shelf
Basal Melt Channels Stabilized by Secondary Flow, Geophys. Res.
Lett., 48, 1–11, https://doi.org/10.1029/2021GL094872, 2021. a
Wunsch, C.: Bermuda sea level in relation to tides, weather, and baroclinic
fluctuations, Rev. Geophys., 10, 1–49,
https://doi.org/10.1029/RG010i001p00001, 1972. a
Yang, H. W., Kim, T.-W., Dutrieux, P., Wåhlin, A. K., Jenkins, A., Ha,
H. K., Kim, C. S., Cho, K.-H., Park, T., Lee, S. H., and Cho, Y.-K.:
Seasonal variability of ocean circulation near the Dotson Ice Shelf,
Antarctica, Nat. Commun., 13, 1138,
https://doi.org/10.1038/s41467-022-28751-5, 2022. a
Zinck, A.-S. P.: BURGEE, GitHub [code],
https://github.com/aszinck/BURGEE (last access: 27 June 2023), 2023.
a
Zinck, A.-S. P., Wouters, B., Lamber, E., and Lhermitte, S.:
Dataset belonging to the article: REMA reveals spatial variability within the Dotson Melt Channel, 4TU.ResearchData [data set], https://doi.org/10.4121/21841284, 2023. a, b
Short summary
The ice shelves in Antarctica are melting from below, which puts their stability at risk. Therefore, it is important to observe how much and where they are melting. In this study we use high-resolution satellite imagery to derive 50 m resolution basal melt rates of the Dotson Ice Shelf. With the high resolution of our product we are able to uncover small-scale features which may in the future help us to understand the state and fate of the Antarctic ice shelves and their (in)stability.
The ice shelves in Antarctica are melting from below, which puts their stability at risk....