Articles | Volume 19, issue 9
https://doi.org/10.5194/tc-19-3897-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/tc-19-3897-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
16 Sep 2025
Research article |
| 16 Sep 2025
| 16 Sep 2025
Seasonal and interannual variability in freshwater sources for Greenland's fjords
Department of Estuarine and Delta Systems, NIOZ Royal Netherlands Institute of Sea Research, Yerseke, the Netherlands
Institute for Marine and Atmospheric Research, Utrecht University, Utrecht, the Netherlands
Willem Jan van de Berg
Institute for Marine and Atmospheric Research, Utrecht University, Utrecht, the Netherlands
Brice Noël
Laboratory of Climatology, Department of Geography, SPHERES research unit, University of Liège, Liège, Belgium
Lorenz Meire
Department of Estuarine and Delta Systems, NIOZ Royal Netherlands Institute of Sea Research, Yerseke, the Netherlands
Greenland Climate Research Centre (GCRC), Greenland Institute of Natural Resources, Nuuk, Greenland
Michiel R. van den Broeke
Institute for Marine and Atmospheric Research, Utrecht University, Utrecht, the Netherlands
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Tim van den Akker, William H. Lipscomb, Gunter R. Leguy, Willem Jan van de Berg, and Roderik S. W. van de Wal
The Cryosphere, 20, 1405–1425, https://doi.org/10.5194/tc-20-1405-2026, https://doi.org/10.5194/tc-20-1405-2026, 2026
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The Antarctic Ice Sheet is currently thinning, especially at major outlet glaciers. Including present-day ice thinning rates in models is a modeller's choice and can affect future projections. This study quantifies the impact of current imbalance on forced future projections, revealing strong regional and short-term (up to 2100) effects when these mass change rates are included.
Benjamin Heurgue, Charles Amory, Christoph Kittel, Fredrik Boberg, Gaël Durand, Vincent Favier, Xavier Fettweis, Quentin Glaude, Heiko Goelzer, Nicolaj Hansen, Nicolas C. Jourdain, Ruth Mottram, Martin Olesen, Willem Jan Van de Berg, Michiel R. Van den Broeke, and René R. Wijngaard
EGUsphere, https://doi.org/10.5194/egusphere-2026-624, https://doi.org/10.5194/egusphere-2026-624, 2026
This preprint is open for discussion and under review for The Cryosphere (TC).
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We studied how the Antarctic ice sheet surface mass balance may change by 2100 using three high-resolution climate models forced by the same future climate scenario. While the models agree for present-day conditions, they project very different futures, especially over floating ice shelves. These differences mainly come from how melting, refreezing, and temperature are represented. Our results show that future sea level projections strongly depend on how well models simulate today’s climate.
Thirza N. Feenstra, Willem Jan van de Berg, Gerd-Jan van Zadelhoff, David P. Donovan, Christiaan T. van Dalum, and Michiel R. van den Broeke
Atmos. Meas. Tech., 19, 1323–1344, https://doi.org/10.5194/amt-19-1323-2026, https://doi.org/10.5194/amt-19-1323-2026, 2026
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Cloud representation brings large uncertainties in polar climate modeling. We show the first evaluation of Greenland clouds in the Regional Atmospheric Climate Model (RACMO2.4) with new EarthCARE satellite data. Comparing lidar and radar observations and retrieved cloud profiles with co-located RACMO output, we find RACMO captures low ice clouds but underestimates high clouds, mid-altitude liquid clouds, and snowfall. These results highlight EarthCARE's potential to improve polar climate models.
Tesse E. A. van den Aker, Peter Kuipers Munneke, Willem Jan van de Berg, Walter W. Immerzeel, and Michiel R. van den Broeke
EGUsphere, https://doi.org/10.5194/egusphere-2026-462, https://doi.org/10.5194/egusphere-2026-462, 2026
This preprint is open for discussion and under review for The Cryosphere (TC).
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The firn layer, i.e. permanent snow, regulates how an ice sheet responds to climate change. Firn models are forced with with climate data at time steps from sub-daily to annual in literature, however, implications are barely evaluated. We test the impact of different climate forcing time steps on the modeled firn layer. We conclude that the climate forcing time step (1) affects firn model output, (2) can lead to non-physical behaviour, and (3) that resolving at least a diurnal cycle is required.
Raf Antwerpen, Marco Tedesco, Pierre Gentine, Willem Jan van de Berg, and Xavier Fettweis
EGUsphere, https://doi.org/10.5194/egusphere-2025-6143, https://doi.org/10.5194/egusphere-2025-6143, 2026
This preprint is open for discussion and under review for The Cryosphere (TC).
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We study why Greenland ice melts faster by improving how ice brightness is represented. This is important because it controls how much sunlight is absorbed by the ice. Using satellite data and a new transparent machine learning method trained with climate model information, we capture how the shape of the ice sheet, temperature, and meltwater change ice brightness. Our approach outperforms existing climate models and can reduce uncertainty in future sea level rise projections.
Tim van den Akker, William H. Lipscomb, Gunter R. Leguy, Willem Jan van de Berg, and Roderik S. W. van de Wal
The Cryosphere, 20, 1217–1235, https://doi.org/10.5194/tc-20-1217-2026, https://doi.org/10.5194/tc-20-1217-2026, 2026
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Ice sheet models to simulate future sea level rise require parameterizations, like for the friction at the bedrock. Studies have quantified the effect of using different parameterizations, and some have concluded that projections are sensitive to the choice of the specific parameterization. In this study, we show that you can make an ice sheet model sensitive to the basal friction parameterization, and that for different modellers choices you can also make the model insensitive to this.
Ida Haven, Hans Christian Steen-Larsen, Laura J. Dietrich, Sonja Wahl, Jason E. Box, Michiel R. van den Broeke, Alun Hubbard, Stephan T. Kral, Joachim Reuder, and Maurice van Tiggelen
The Cryosphere, 20, 573–593, https://doi.org/10.5194/tc-20-573-2026, https://doi.org/10.5194/tc-20-573-2026, 2026
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Three independent Eddy-Covariance measurement systems deployed on top of the Greenland Ice Sheet are compared. Using this dataset, we evaluate the reproducibility and quantify the differences between the systems. The fidelity of two regional climate models in capturing the seasonal variability in the latent and sensible heat flux between the snow surface and the atmosphere is assessed. We identify differences between observations and model simulations, especially during the winter period.
Horst Machguth, Andrew Tedstone, Peter Kuipers Munneke, Max Brils, Brice Noël, Nicole Clerx, Nicolas Jullien, Xavier Fettweis, and Michiel van den Broeke
The Cryosphere, 20, 427–452, https://doi.org/10.5194/tc-20-427-2026, https://doi.org/10.5194/tc-20-427-2026, 2026
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Due to increasing air temperatures, surface melt expands to higher elevations on the Greenland ice sheet. This is visible on satellite imagery in the form of rivers of meltwater running across the surface of the ice sheet. We compare model results of meltwater at high elevations on the ice sheet to satellite observations. We find that each of the models shows strengths and weaknesses. A detailed look into the model results reveals potential reasons for the differences between models.
Valeria Di Biase, Peter Kuipers Munneke, Bert Wouters, Michiel R. van den Broeke, and Maurice van Tiggelen
The Cryosphere, 20, 87–96, https://doi.org/10.5194/tc-20-87-2026, https://doi.org/10.5194/tc-20-87-2026, 2026
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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.
Heiko Goelzer, Constantijn J. Berends, Fredrik Boberg, Gael Durand, Tamsin L. Edwards, Xavier Fettweis, Fabien Gillet-Chaulet, Quentin Glaude, Philippe Huybrechts, Sébastien Le clec'h, Ruth Mottram, Brice Noël, Martin Olesen, Charlotte Rahlves, Jeremy Rohmer, Michiel van den Broeke, and Roderik S. W. van de Wal
The Cryosphere, 19, 6887–6906, https://doi.org/10.5194/tc-19-6887-2025, https://doi.org/10.5194/tc-19-6887-2025, 2025
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We present an ensemble of ice sheet model projections for the Greenland ice sheet. The focus is on providing projections that improve our understanding of the range future sea-level rise and the inherent uncertainties over the next 100 to 300 years. Compared to earlier work we more fully account for some of the uncertainties in sea-level projections. We include a wider range of climate model output, more climate change scenarios and we extend projections schematically up to year 2300.
Fredrik Boberg, Nicolaj Hansen, Ruth Mottram, Xavier Fettweis, and Michiel R. van den Broeke
EGUsphere, https://doi.org/10.5194/egusphere-2025-4360, https://doi.org/10.5194/egusphere-2025-4360, 2025
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An ensemble of regional climate model simulations is used to estimate the 21st century change in precipitation on the Greenland ice sheet. For the end of the century, the change is in the range 40 to 170 Gt per year, depending on the emission scenario. Using annual values of 2 m air temperature and precipitation, we estimate an increase in precipitation of 35 Gt per year for every degree of warming.
Nicole A. Loeb, Alex Crawford, Brice Noël, and Julienne Stroeve
The Cryosphere, 19, 5403–5422, https://doi.org/10.5194/tc-19-5403-2025, https://doi.org/10.5194/tc-19-5403-2025, 2025
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We examine how extreme precipitation days affect the seasonal mass balance (SMB) of land ice in Greenland and the Eastern Canadian Arctic in historical and future simulations. Past extreme precipitation led to higher SMB with snowfall. Future extreme precipitation may lead to the loss of ice mass as more falls as rain rather than snow in some regions, such as southwestern Greenland. Across the region, extreme precipitation becomes more important to seasonal SMB in the future, warmer climate.
Sanne B. M. Veldhuijsen, Willem Jan van de Berg, Peter Kuipers Munneke, Nicolaj Hansen, Fredrik Boberg, Christoph Kittel, Charles Amory, and Michiel R. van den Broeke
The Cryosphere, 19, 5157–5173, https://doi.org/10.5194/tc-19-5157-2025, https://doi.org/10.5194/tc-19-5157-2025, 2025
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Perennial firn aquifers (PFAs), year-round bodies of liquid water within firns, can potentially impact ice-shelf and ice-sheet stability. We developed a fast XGBoost firn emulator to predict the 21st-century distribution of PFAs in Antarctica for 12 climatic forcing datasets. Our findings suggest that, in low-emission scenarios, PFAs remain confined to the Antarctic Peninsula. However, in a high-emission scenario, PFAs are projected to expand to a region in West Antarctica and East Antarctica.
René R. Wijngaard, Willem Jan van de Berg, Christiaan T. van Dalum, Adam R. Herrington, and Xavier J. Levine
Weather Clim. Dynam., 6, 1241–1266, https://doi.org/10.5194/wcd-6-1241-2025, https://doi.org/10.5194/wcd-6-1241-2025, 2025
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We used the variable-resolution Community Earth System Model to simulate present-day and future Arctic temperature and precipitation extremes using global grids (~111 km) with and without regional refinement (~28 km) and a storyline approach. Refined grids generally perform better for precipitation extremes, while unrefined grids perform better for temperature extremes. Future projections show increases in high temperature and wet precipitation extremes and decreases in low temperature extremes.
Kristiina Verro, Cecilia Äijälä, Roberta Pirazzini, Ruzica Dadic, Damien Maure, Willem Jan van de Berg, Giacomo Traversa, Christiaan T. van Dalum, Petteri Uotila, Xavier Fettweis, Biagio Di Mauro, and Milla Johansson
The Cryosphere, 19, 4409–4436, https://doi.org/10.5194/tc-19-4409-2025, https://doi.org/10.5194/tc-19-4409-2025, 2025
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Accurately representing Antarctic sea ice is essential for reliable climate and ocean model predictions. We evaluated how different models simulate the sea ice's sunlight reflectivity (called albedo) using field and satellite data. Models with simple albedo schemes performed well in limited cases but missed key processes. The advanced scheme in the MetROMS-UHel ocean model provided the most accurate results, including observed day–night albedo changes observed during a field campaign.
Ella Gilbert, José Abraham Torres-Alavez, Marte G. Hofsteenge, Willem Jan van de Berg, Fredrik Boberg, Ole Bøssing Christensen, Christiaan Timo van Dalum, Xavier Fettweis, Siddharth Gumber, Nicolaj Hansen, Christoph Kittel, Clara Lambin, Damien Maure, Ruth Mottram, Martin Olesen, Andrew Orr, Tony Phillips, Maurice van Tiggelen, Kristiina Verro, and Priscilla A. Mooney
EGUsphere, https://doi.org/10.5194/egusphere-2025-4214, https://doi.org/10.5194/egusphere-2025-4214, 2025
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Here we present a new dataset – the PolarRES ensemble – of four state-of-the-art regional climate models, which capture the full complexity of Antarctica's climate. The ensemble out-performs other available tools, advancing our ability to explore Antarctic climate. While it still has limitations, the PolarRES ensemble offers a novel and exciting way of evaluating climate processes and features, and we encourage researchers to use the data, which are freely available.
Christiaan T. van Dalum, Willem Jan van de Berg, Michiel R. van den Broeke, and Maurice van Tiggelen
The Cryosphere, 19, 4061–4090, https://doi.org/10.5194/tc-19-4061-2025, https://doi.org/10.5194/tc-19-4061-2025, 2025
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In this study, we present a new surface mass balance (SMB) and near-surface climate product for Antarctica with the regional climate model RACMO2.4p1. We assess the impact of major model updates on the climate of Antarctica. Locally, the SMB has changed substantially but also agrees well with observations. In addition, we show that the SMB components, surface energy budget, albedo, pressure, temperature, and wind speed compare well with in situ and remote sensing observations.
Maurice van Tiggelen, Paul C. J. P. Smeets, Carleen H. Reijmer, Peter Kuipers Munneke, and Michiel R. van den Broeke
Earth Syst. Sci. Data, 17, 4933–4955, https://doi.org/10.5194/essd-17-4933-2025, https://doi.org/10.5194/essd-17-4933-2025, 2025
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This paper describes the measurements from the 19 IMAU (Institute for Marine and Atmospheric research Utrecht) automatic weather stations that operated on the Antarctic ice sheet from 1995 through 2022. These stations also measured the net surface radiation and surface height change, allowing for the quantification of the surface energy and mass balance at hourly resolution. These data are invaluable for the evaluation of atmospheric models and for the detection of climatological changes.
Marte Gé Hofsteenge, Willem Jan van de Berg, Christiaan van Dalum, Kristiina Verro, Maurice van Tiggelen, and Michiel van den Broeke
EGUsphere, https://doi.org/10.5194/egusphere-2025-4176, https://doi.org/10.5194/egusphere-2025-4176, 2025
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We use a regional climate model to study how surface melt on Antarctic ice shelves responds to air temperature changes. The relationship is strongly non-linear, mainly due to feedbacks in surface reflectivity, with other energy sources also contributing. Currently colder, drier, and more stable ice shelves will experience more melt at the same temperature than wetter ice shelves, highlighting their vulnerability to fracturing, ice shelf instability, and contributions to global sea-level rise.
Mikkel Langgaard Lauritzen, Anne Solgaard, Nicholas Mossor Rathmann, Bo Møllesøe Vinther, Aslak Grindsted, Brice Noël, Guðfinna Aðalgeirsdóttir, and Christine Schøtt Hvidberg
The Cryosphere, 19, 3599–3622, https://doi.org/10.5194/tc-19-3599-2025, https://doi.org/10.5194/tc-19-3599-2025, 2025
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We studied the Holocene (past 11 700 years) to understand how the Greenland Ice Sheet has changed. Using 841 computer simulations, we tested different scenarios and matched them to historical ice elevation data, confirming our model's accuracy. Results show that Greenland's melting has raised sea levels by about 5.3 m since the Holocene began and by around 12 mm in just the past 500 years.
Shfaqat A. Khan, Helene Seroussi, Mathieu Morlighem, William Colgan, Veit Helm, Gong Cheng, Danjal Berg, Valentina R. Barletta, Nicolaj K. Larsen, William Kochtitzky, Michiel van den Broeke, Kurt H. Kjær, Andy Aschwanden, Brice Noël, Jason E. Box, Joseph A. MacGregor, Robert S. Fausto, Kenneth D. Mankoff, Ian M. Howat, Kuba Oniszk, Dominik Fahrner, Anja Løkkegaard, Eigil Y. H. Lippert, Alicia Bråtner, and Javed Hassan
Earth Syst. Sci. Data, 17, 3047–3071, https://doi.org/10.5194/essd-17-3047-2025, https://doi.org/10.5194/essd-17-3047-2025, 2025
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The surface elevation of the Greenland Ice Sheet is changing due to surface mass balance processes and ice dynamics, each exhibiting distinct spatiotemporal patterns. Here, we employ satellite and airborne altimetry data with fine spatial (1 km) and temporal (monthly) resolutions to document this spatiotemporal evolution from 2003 to 2023. This dataset of fine-resolution altimetry data in both space and time will support studies of ice mass loss and be useful for GIS ice sheet modeling.
Emily Glen, Amber Leeson, Alison F. Banwell, Jennifer Maddalena, Diarmuid Corr, Olivia Atkins, Brice Noël, and Malcolm McMillan
The Cryosphere, 19, 1047–1066, https://doi.org/10.5194/tc-19-1047-2025, https://doi.org/10.5194/tc-19-1047-2025, 2025
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We compare surface meltwater features from optical satellite imagery in the Russell–Leverett glacier catchment during high (2019) and low (2018) melt years. In the high melt year, features appear at higher elevations, meltwater systems are more connected, small lakes are more frequent, and slush is more widespread. These findings provide insights into how a warming climate, where high melt years become common, could alter meltwater distribution and dynamics on the Greenland Ice Sheet.
Tim van den Akker, William H. Lipscomb, Gunter R. Leguy, Jorjo Bernales, Constantijn J. Berends, Willem Jan van de Berg, and Roderik S. W. van de Wal
The Cryosphere, 19, 283–301, https://doi.org/10.5194/tc-19-283-2025, https://doi.org/10.5194/tc-19-283-2025, 2025
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In this study, we present an improved way of representing ice thickness change rates in an ice sheet model. We apply this method using two ice sheet models of the Antarctic Ice Sheet. We found that the two largest outlet glaciers on the Antarctic Ice Sheet, Thwaites Glacier and Pine Island Glacier, will collapse without further warming on a timescale of centuries. This would cause a sea level rise of about 1.2 m globally.
Jana Krause, Dustin Carroll, Juan Höfer, Jeremy Donaire, Eric P. Achterberg, Emilio Alarcón, Te Liu, Lorenz Meire, Kechen Zhu, and Mark J. Hopwood
The Cryosphere, 18, 5735–5752, https://doi.org/10.5194/tc-18-5735-2024, https://doi.org/10.5194/tc-18-5735-2024, 2024
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Here we analysed calved ice samples from both the Arctic and Antarctic to assess the variability in the composition of iceberg meltwater. Our results suggest that low concentrations of nitrate and phosphate in ice are primarily from the ice matrix, whereas sediment-rich layers impart a low concentration of silica and modest concentrations of iron and manganese. At a global scale, there are very limited differences in the nutrient composition of ice.
Srinidhi Gadde and Willem Jan van de Berg
The Cryosphere, 18, 4933–4953, https://doi.org/10.5194/tc-18-4933-2024, https://doi.org/10.5194/tc-18-4933-2024, 2024
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Blowing-snow sublimation is the major loss term in the mass balance of Antarctica. In this study we update the blowing-snow representation in the Regional Atmospheric Climate Model (RACMO). With the updates, results compare well with observations from East Antarctica. Also, the continent-wide variation of blowing snow compares well with satellite observations. Hence, the updates provide a clear step forward in producing a physically sound and reliable estimate of the mass balance of Antarctica.
Maria T. Kappelsberger, Martin Horwath, Eric Buchta, Matthias O. Willen, Ludwig Schröder, Sanne B. M. Veldhuijsen, Peter Kuipers Munneke, and Michiel R. van den Broeke
The Cryosphere, 18, 4355–4378, https://doi.org/10.5194/tc-18-4355-2024, https://doi.org/10.5194/tc-18-4355-2024, 2024
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The interannual variations in the height of the Antarctic Ice Sheet (AIS) are mainly due to natural variations in snowfall. Precise knowledge of these variations is important for the detection of any long-term climatic trends in AIS surface elevation. We present a new product that spatially resolves these height variations over the period 1992–2017. The product combines the strengths of atmospheric modeling results and satellite altimetry measurements.
Christiaan T. van Dalum, Willem Jan van de Berg, Srinidhi N. Gadde, Maurice van Tiggelen, Tijmen van der Drift, Erik van Meijgaard, Lambertus H. van Ulft, and Michiel R. van den Broeke
The Cryosphere, 18, 4065–4088, https://doi.org/10.5194/tc-18-4065-2024, https://doi.org/10.5194/tc-18-4065-2024, 2024
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We present a new version of the polar Regional Atmospheric Climate Model (RACMO), version 2.4p1, and show first results for Greenland, Antarctica and the Arctic. We provide an overview of all changes and investigate the impact that they have on the climate of polar regions. By comparing the results with observations and the output from the previous model version, we show that the model performs well regarding the surface mass balance of the ice sheets and near-surface climate.
Xueyu Zhang, Lin Liu, Brice Noël, and Zhicai Luo
EGUsphere, https://doi.org/10.5194/egusphere-2024-1726, https://doi.org/10.5194/egusphere-2024-1726, 2024
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This study indicates that the overall characteristics of the upper firn density in the percolation zone could be captured by the choice of appropriate model configurations and climatic forcing, which is necessary for understanding the current mass balance of the GrIS and predicting its future. The modelled firn density in this study generally aligns well with observations from 16 cores, with the relative bias in density ranging from 0.36 % to 6 % at Dye-2 and being within ±5 % at KAN_U.
Sanne B. M. Veldhuijsen, Willem Jan van de Berg, Peter Kuipers Munneke, and Michiel R. van den Broeke
The Cryosphere, 18, 1983–1999, https://doi.org/10.5194/tc-18-1983-2024, https://doi.org/10.5194/tc-18-1983-2024, 2024
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We use the IMAU firn densification model to simulate the 21st-century evolution of Antarctic firn air content. Ice shelves on the Antarctic Peninsula and the Roi Baudouin Ice Shelf in Dronning Maud Land are particularly vulnerable to total firn air content (FAC) depletion. Our results also underline the potentially large vulnerability of low-accumulation ice shelves to firn air depletion through ice slab formation.
Baptiste Vandecrux, Robert S. Fausto, Jason E. Box, Federico Covi, Regine Hock, Åsa K. Rennermalm, Achim Heilig, Jakob Abermann, Dirk van As, Elisa Bjerre, Xavier Fettweis, Paul C. J. P. Smeets, Peter Kuipers Munneke, Michiel R. van den Broeke, Max Brils, Peter L. Langen, Ruth Mottram, and Andreas P. Ahlstrøm
The Cryosphere, 18, 609–631, https://doi.org/10.5194/tc-18-609-2024, https://doi.org/10.5194/tc-18-609-2024, 2024
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How fast is the Greenland ice sheet warming? In this study, we compiled 4500+ temperature measurements at 10 m below the ice sheet surface (T10m) from 1912 to 2022. We trained a machine learning model on these data and reconstructed T10m for the ice sheet during 1950–2022. After a slight cooling during 1950–1985, the ice sheet warmed at a rate of 0.7 °C per decade until 2022. Climate models showed mixed results compared to our observations and underestimated the warming in key regions.
Xueyu Zhang, Lin Liu, Brice Noël, and Zhicai Luo
EGUsphere, https://doi.org/10.5194/egusphere-2024-122, https://doi.org/10.5194/egusphere-2024-122, 2024
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In this study, an improved firn densification model is developed by integrating the Bucket scheme and Darcy’s law to assess the capillary retention, refreezing, and runoff of liquid water within the firn layer. This model captures high-density peaks (~917 kg · m-3) or the features of high-density layers caused by the refreezing of liquid water. In general, the modelled firn depth-density profiles at KAN_U and Dye-2 agree well with the in situ measurements.
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
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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.
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.
Sanne B. M. Veldhuijsen, Willem Jan van de Berg, Max Brils, Peter Kuipers Munneke, and Michiel R. van den Broeke
The Cryosphere, 17, 1675–1696, https://doi.org/10.5194/tc-17-1675-2023, https://doi.org/10.5194/tc-17-1675-2023, 2023
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Firn is the transition of snow to glacier ice and covers 99 % of the Antarctic ice sheet. Knowledge about the firn layer and its variability is important, as it impacts satellite-based estimates of ice sheet mass change. Also, firn contains pores in which nearly all of the surface melt is retained. Here, we improve a semi-empirical firn model and simulate the firn characteristics for the period 1979–2020. We evaluate the performance with field and satellite measures and test its sensitivity.
Marte G. Hofsteenge, Nicolas J. Cullen, Carleen H. Reijmer, Michiel van den Broeke, Marwan Katurji, and John F. Orwin
The Cryosphere, 16, 5041–5059, https://doi.org/10.5194/tc-16-5041-2022, https://doi.org/10.5194/tc-16-5041-2022, 2022
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In the McMurdo Dry Valleys (MDV), foehn winds can impact glacial meltwater production and the fragile ecosystem that depends on it. We study these dry and warm winds at Joyce Glacier and show they are caused by a different mechanism than that found for nearby valleys, demonstrating the complex interaction of large-scale winds with the mountains in the MDV. We find that foehn winds increase sublimation of ice, increase heating from the atmosphere, and increase the occurrence and rates of melt.
Raf M. Antwerpen, Marco Tedesco, Xavier Fettweis, Patrick Alexander, and Willem Jan van de Berg
The Cryosphere, 16, 4185–4199, https://doi.org/10.5194/tc-16-4185-2022, https://doi.org/10.5194/tc-16-4185-2022, 2022
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The ice on Greenland has been melting more rapidly over the last few years. Most of this melt comes from the exposure of ice when the overlying snow melts. This ice is darker than snow and absorbs more sunlight, leading to more melt. It remains challenging to accurately simulate the brightness of the ice. We show that the color of ice simulated by Modèle Atmosphérique Régional (MAR) is too bright. We then show that this means that MAR may underestimate how fast the Greenland ice is melting.
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.
Max Brils, Peter Kuipers Munneke, Willem Jan van de Berg, and Michiel van den Broeke
Geosci. Model Dev., 15, 7121–7138, https://doi.org/10.5194/gmd-15-7121-2022, https://doi.org/10.5194/gmd-15-7121-2022, 2022
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Firn covers the Greenland ice sheet (GrIS) and can temporarily prevent mass loss. Here, we present the latest version of our firn model, IMAU-FDM, with an application to the GrIS. We improved the density of fallen snow, the firn densification rate and the firn's thermal conductivity. This leads to a higher air content and 10 m temperatures. Furthermore we investigate three case studies and find that the updated model shows greater variability and an increased sensitivity in surface elevation.
Tiago Silva, Jakob Abermann, Brice Noël, Sonika Shahi, Willem Jan van de Berg, and Wolfgang Schöner
The Cryosphere, 16, 3375–3391, https://doi.org/10.5194/tc-16-3375-2022, https://doi.org/10.5194/tc-16-3375-2022, 2022
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To overcome internal climate variability, this study uses k-means clustering to combine NAO, GBI and IWV over the Greenland Ice Sheet (GrIS) and names the approach as the North Atlantic influence on Greenland (NAG). With the support of a polar-adapted RCM, spatio-temporal changes on SEB components within NAG phases are investigated. We report atmospheric warming and moistening across all NAG phases as well as large-scale and regional-scale contributions to GrIS mass loss and their interactions.
Christiaan T. van Dalum, Willem Jan van de Berg, and Michiel R. van den Broeke
The Cryosphere, 16, 1071–1089, https://doi.org/10.5194/tc-16-1071-2022, https://doi.org/10.5194/tc-16-1071-2022, 2022
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In this study, we improve the regional climate model RACMO2 and investigate the climate of Antarctica. We have implemented a new radiative transfer and snow albedo scheme and do several sensitivity experiments. When fully tuned, the results compare well with observations and snow temperature profiles improve. Moreover, small changes in the albedo and the investigated processes can lead to a strong overestimation of melt, locally leading to runoff and a reduced surface mass balance.
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.
Kenneth D. Mankoff, Xavier Fettweis, Peter L. Langen, Martin Stendel, Kristian K. Kjeldsen, Nanna B. Karlsson, Brice Noël, Michiel R. van den Broeke, Anne Solgaard, William Colgan, Jason E. Box, Sebastian B. Simonsen, Michalea D. King, Andreas P. Ahlstrøm, Signe Bech Andersen, and Robert S. Fausto
Earth Syst. Sci. Data, 13, 5001–5025, https://doi.org/10.5194/essd-13-5001-2021, https://doi.org/10.5194/essd-13-5001-2021, 2021
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We estimate the daily mass balance and its components (surface, marine, and basal mass balance) for the Greenland ice sheet. Our time series begins in 1840 and has annual resolution through 1985 and then daily from 1986 through next week. Results are operational (updated daily) and provided for the entire ice sheet or by commonly used regions or sectors. This is the first input–output mass balance estimate to include the basal mass balance.
Ruth Mottram, Nicolaj Hansen, Christoph Kittel, J. Melchior van Wessem, Cécile Agosta, Charles Amory, Fredrik Boberg, Willem Jan van de Berg, Xavier Fettweis, Alexandra Gossart, Nicole P. M. van Lipzig, Erik van Meijgaard, Andrew Orr, Tony Phillips, Stuart Webster, Sebastian B. Simonsen, and Niels Souverijns
The Cryosphere, 15, 3751–3784, https://doi.org/10.5194/tc-15-3751-2021, https://doi.org/10.5194/tc-15-3751-2021, 2021
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We compare the calculated surface mass budget (SMB) of Antarctica in five different regional climate models. On average ~ 2000 Gt of snow accumulates annually, but different models vary by ~ 10 %, a difference equivalent to ± 0.5 mm of global sea level rise. All models reproduce observed weather, but there are large differences in regional patterns of snowfall, especially in areas with very few observations, giving greater uncertainty in Antarctic mass budget than previously identified.
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.
Christiaan T. van Dalum, Willem Jan van de Berg, and Michiel R. van den Broeke
The Cryosphere, 15, 1823–1844, https://doi.org/10.5194/tc-15-1823-2021, https://doi.org/10.5194/tc-15-1823-2021, 2021
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Absorption of solar radiation is often limited to the surface in regional climate models. Therefore, we have implemented a new radiative transfer scheme in the model RACMO2, which allows for internal heating and improves the surface reflectivity. Here, we evaluate its impact on the surface mass and energy budget and (sub)surface temperature, by using observations and the previous model version for the Greenland ice sheet. New results match better with observations and introduce subsurface melt.
Cited articles
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Fox-Kemper, B., Adcroft, A., Böning, C. W., Chassignet, E. P., Curchitser, E., Danabasoglu, G., Eden, C., England, M. H., Gerdes, R., Greatbatch, R. J., Griffies, S. M., Hallberg, R. W., Hanert, E., Heimbach, P., Hewitt, H. T., Hill, C. N., Komuro, Y., Legg, S., Sommer, J. L., Masina, S., Marsland, S. J., Penny, S. G., Qiao, F., Ringler, T. D., Treguier, A. M., Tsujino, H., Uotila, P., and Yeager, S. G.: Challenges and prospects in ocean circulation models, Frontiers in Marine Science, 6, 434281, https://doi.org/10.3389/FMARS.2019.00065, 2019. a
Gelderloos, R., Haine, T. W., and Almansi, M.: Subinertial Variability in Four Southeast Greenland Fjords in Realistic Numerical Simulations, J. Geophys. Res.-Oceans, 127, e2022JC018820, https://doi.org/10.1029/2022JC018820, 2022. a
Gillard, L. C., Hu, X., Myers, P. G., and Bamber, J. L.: Meltwater pathways from marine terminating glaciers of the Greenland ice sheet, Geophys. Res. Lett., 43, 873–10, https://doi.org/10.1002/2016GL070969, 2016. a, b
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Greene, C. A., Gardner, A. S., Wood, M., and Cuzzone, J. K.: Ubiquitous acceleration in Greenland Ice Sheet calving from 1985 to 2022, Nature, 625, 523–528, https://doi.org/10.1038/s41586-023-06863-2, 2024. a, b
Hallberg, R.: Using a resolution function to regulate parameterizations of oceanic mesoscale eddy effects, Ocean Model., 72, 92–103, https://doi.org/10.1016/J.OCEMOD.2013.08.007, 2013. a
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Hopwood, M. J., Carroll, D., Dunse, T., Hodson, A., Holding, J. M., Iriarte, J. L., Ribeiro, S., Achterberg, E. P., Cantoni, C., Carlson, D. F., Chierici, M., Clarke, J. S., Cozzi, S., Fransson, A., Juul-Pedersen, T., Winding, M. H. S., and Meire, L.: Review article: How does glacier discharge affect marine biogeochemistry and primary production in the Arctic?, The Cryosphere, 14, 1347–1383, https://doi.org/10.5194/tc-14-1347-2020, 2020. a, b
Huai, B., van den Broeke, M. R., Reijmer, C. H., and Noël, B.: A Daily 1-km Resolution Greenland Rainfall Climatology (1958–2020) From Statistical Downscaling of a Regional Atmospheric Climate Model, J. Geophys. Res.-Atmos., 127, e2022JD036688, https://doi.org/10.1029/2022JD036688, 2022. a, b
Igneczi, A. and Bamber, J. L.: A high-resolution pan-Arctic meltwater discharge dataset from 1950 to 2021, Earth Syst. Sci. Data, 17, 3203–3218, https://doi.org/10.5194/essd-17-3203-2025, 2025. a, b, c
Jackson, L. C., Alastrué de Asenjo, E., Bellomo, K., Danabasoglu, G., Haak, H., Hu, A., Jungclaus, J., Lee, W., Meccia, V. L., Saenko, O., Shao, A., and Swingedouw, D.: Understanding AMOC stability: the North Atlantic Hosing Model Intercomparison Project, Geosci. Model Dev., 16, 1975–1995, https://doi.org/10.5194/gmd-16-1975-2023, 2023. a
Jackson, R. H. and Straneo, F.: Heat, Salt, and Freshwater Budgets for a Glacial Fjord in Greenland, J. Phys. Oceanogr., 46, 2735–2768, https://doi.org/10.1175/JPO-D-15-0134.1, 2016. a
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Karlsson, N. B., Solgaard, A. M., Mankoff, K. D., Gillet-Chaulet, F., MacGregor, J. A., Box, J. E., Citterio, M., Colgan, W. T., Larsen, S. H., Kjeldsen, K. K., Korsgaard, N. J., Benn, D. I., Hewitt, I. J., and Fausto, R. S.: Greenland Ice Sheet Basal Melt, v2, Dataverse [data set], https://doi.org/10.22008/FK2/PLNUEO, 2021a. a
Karlsson, N. B., Solgaard, A. M., Mankoff, K. D., Gillet-Chaulet, F., MacGregor, J. A., Box, J. E., Citterio, M., Colgan, W. T., Larsen, S. H., Kjeldsen, K. K., Korsgaard, N. J., Benn, D. I., Hewitt, I. J., and Fausto, R. S.: A first constraint on basal melt-water production of the Greenland ice sheet, Nat. Commun., 12, 3461, https://doi.org/10.1038/s41467-021-23739-z, 2021b. a
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Khan, S. A., Colgan, W., Neumann, T. A., van den Broeke, M. R., Brunt, K. M., Noël, B., Bamber, J. L., Hassan, J., and Bjørk, A. A.: Accelerating Ice Loss From Peripheral Glaciers in North Greenland, Geophys. Res. Lett., 49, e2022GL098915, https://doi.org/10.1029/2022GL098915, 2022. a, b
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Kochtitzky, W., Copland, L., King, M., Hugonnet, R., Jiskoot, H., Morlighem, M., Millan, R., Khan, S. A., and Noël, B.: Closing Greenland's Mass Balance: Frontal Ablation of Every Greenlandic Glacier From 2000 to 2020, Geophys. Res. Lett., 50, e2023GL104095, https://doi.org/10.1029/2023GL104095, 2023. a
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Mankoff, K. D., Fettweis, X., Langen, P. L., Stendel, M., Kjeldsen, K. K., Karlsson, N. B., Noël, B., van den Broeke, M. R., Solgaard, A., Colgan, W., Box, J. E., Simonsen, S. B., King, M. D., Ahlstrøm, A. P., Andersen, S. B., and Fausto, R. S.: Greenland ice sheet mass balance from 1840 through next week, Earth Syst. Sci. Data, 13, 5001–5025, https://doi.org/10.5194/essd-13-5001-2021, 2021. a
Marson, J. M., Gillard, L. C., and Myers, P. G.: Distinct Ocean Responses to Greenland's Liquid Runoff and Iceberg Melt, J. Geophys. Res.-Oceans, 126, e2021JC017542, https://doi.org/10.1029/2021JC017542, 2021. a
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Short summary
Freshwater flows into Greenland's fjords from various sources. Solid ice discharge (e.g. calving icebergs) dominates freshwater input in the southeast and northwest. In contrast, in the southwest, runoff from the ice sheet and tundra are the most significant. Seasonal data revealed that fjord precipitation and tundra runoff contribute up to 11 % and 35 % of the monthly freshwater input, respectively. Our results provide valuable input for ocean models and for researchers studying fjord ecosystems.
Freshwater flows into Greenland's fjords from various sources. Solid ice discharge (e.g. calving...
