Articles | Volume 19, issue 8
https://doi.org/10.5194/tc-19-2963-2025
© Author(s) 2025. 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-19-2963-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
12 Aug 2025
Research article |
| 12 Aug 2025
| 12 Aug 2025
Bias in modeled Greenland Ice Sheet melt revealed by ASCAT
Geodesy and Earth Observation, DTU-Space, Technical University of Denmark, Lyngby, Denmark
National Centre for Climate Research, Danish Meteorological Institute (DMI), Copenhagen, Denmark
Nicolaj Hansen
National Centre for Climate Research, Danish Meteorological Institute (DMI), Copenhagen, Denmark
Ruth Mottram
National Centre for Climate Research, Danish Meteorological Institute (DMI), Copenhagen, Denmark
Thomas Nagler
Environmental Earth Observation Information Technology (ENVEO) IT GmBH, Innsbruck, Austria
Stefan Scheiblauer
Environmental Earth Observation Information Technology (ENVEO) IT GmBH, Innsbruck, Austria
Sebastian B. Simonsen
Geodesy and Earth Observation, DTU-Space, Technical University of Denmark, Lyngby, Denmark
Louise S. Sørensen
Geodesy and Earth Observation, DTU-Space, Technical University of Denmark, Lyngby, Denmark
Jan Wuite
Environmental Earth Observation Information Technology (ENVEO) IT GmBH, Innsbruck, Austria
Anne M. Solgaard
Glaciology and Climate, Geological Survey of Denmark and Greenland (GEUS), Copenhagen, Denmark
Related authors
No articles found.
Hideo Aochi, Masumi Yamada, Tung-Cheng Ho, Gonéri Le Cozannet, Arno Christian Hammann, and Ruth Mottram
EGUsphere, https://doi.org/10.5194/egusphere-2025-3803, https://doi.org/10.5194/egusphere-2025-3803, 2025
This preprint is open for discussion and under review for Natural Hazards and Earth System Sciences (NHESS).
Short summary
Short summary
The 2017 Landslide-made tsunami in Greenland occurred in a context of global warming and heavily impacted local communities. We analyze this event using seismic data to reconstruct the whole chain of processes from the landslide to the tsunami. Our results validate a new approach to analyze crustal deformations caused by tsunami propagation in fjords, suggesting that alert systems based on seismic data are feasible, potentially allowing to reduce tsunami risks in polar regions.
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
Short summary
Short summary
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.
Heiko Goelzer, Constantijn J. Berends, Fredrik Boberg, Gael Durand, Tamsin 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
EGUsphere, https://doi.org/10.5194/egusphere-2025-3098, https://doi.org/10.5194/egusphere-2025-3098, 2025
This preprint is open for discussion and under review for The Cryosphere (TC).
Short summary
Short summary
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.
Benjamin J. Davison, Anna E. Hogg, Thomas Slater, Richard Rigby, and Nicolaj Hansen
Earth Syst. Sci. Data, 17, 3259–3281, https://doi.org/10.5194/essd-17-3259-2025, https://doi.org/10.5194/essd-17-3259-2025, 2025
Short summary
Short summary
Grounding line discharge is a measure of the amount of ice entering the ocean from an ice mass. This paper describes a dataset of grounding line discharge for the Antarctic Ice Sheet and each of its glaciers. The dataset shows that Antarctic Ice Sheet grounding line discharge has increased since 1996.
Sofie Hedetoft, Olivia Bang Brinck, Ruth Mottram, Andrea M. U. Gierisch, Steffen Malskær Olsen, Martin Olesen, Nicolaj Hansen, Anders Anker Bjørk, Erik Loebel, Anne Solgaard, and Peter Thejll
EGUsphere, https://doi.org/10.5194/egusphere-2025-1907, https://doi.org/10.5194/egusphere-2025-1907, 2025
Short summary
Short summary
Iceberg mélange is the jumble of icebergs in front of some glaciers that calve into the sea. Some studies suggest mélange might help to control the retreat of glaciers. We studied 3 glaciers in NW Greenland where we used GPS sensors and satellites to track ice movement. We found that glaciers push forward and calve all year, including when mélange and landfast sea ice are present, suggesting mélange is not important in supporting glaciers, but may influence the seasonal calving cycle.
Gavin A. Schmidt, Kenneth D. Mankoff, Jonathan L. Bamber, Dustin Carroll, David M. Chandler, Violaine Coulon, Benjamin J. Davison, Matthew H. England, Paul R. Holland, Nicolas C. Jourdain, Qian Li, Juliana M. Marson, Pierre Mathiot, Clive R. McMahon, Twila A. Moon, Ruth Mottram, Sophie Nowicki, Anne Olivé Abelló, Andrew G. Pauling, Thomas Rackow, and Damien Ringeisen
EGUsphere, https://doi.org/10.5194/egusphere-2025-1940, https://doi.org/10.5194/egusphere-2025-1940, 2025
Short summary
Short summary
The impact of increasing mass loss from the Greenland and Antarctic ice sheets has not so far been included in historical climate model simulations. This paper describes the protocols and data available for modeling groups to add this anomalous freshwater to their ocean modules to better represent the impacts of these fluxes on ocean circulation, sea ice, salinity and sea level.
Kirk M. Scanlan, Anja Rutishauser, and Sebastian B. Simonsen
The Cryosphere, 19, 1221–1239, https://doi.org/10.5194/tc-19-1221-2025, https://doi.org/10.5194/tc-19-1221-2025, 2025
Short summary
Short summary
An ice sheet's surface modulates its response to climate change, and it is therefore critical to monitor how it evolves through time. Here, we investigate novel measurements of Greenland surface roughness based on the strength of reflected local airborne and pan-Greenland satellite radar signals. These measurements respond to roughness at scales typically larger than those considered in mass balance modelling while highlighting the scale dependency of surface roughness that is often overlooked.
Annett Bartsch, Xaver Muri, Markus Hetzenecker, Kimmo Rautiainen, Helena Bergstedt, Jan Wuite, Thomas Nagler, and Dmitry Nicolsky
The Cryosphere, 19, 459–483, https://doi.org/10.5194/tc-19-459-2025, https://doi.org/10.5194/tc-19-459-2025, 2025
Short summary
Short summary
We developed a robust freeze–thaw detection approach, applying a constant threshold to Copernicus Sentinel-1 data that is suitable for tundra regions. All global, coarser-resolution products, tested with the resulting benchmarking dataset, are of value for freeze–thaw retrieval, although differences were found depending on the seasons, particularly during the spring and autumn transition.
Richard Parsons, Sainan Sun, G. Hilmar Gudmundsson, Jan Wuite, and Thomas Nagler
The Cryosphere, 18, 5789–5801, https://doi.org/10.5194/tc-18-5789-2024, https://doi.org/10.5194/tc-18-5789-2024, 2024
Short summary
Short summary
In 2022, multi-year landfast sea ice in Antarctica's Larsen B embayment disintegrated, after which time an increase in the rate at which Crane Glacier discharged ice into the ocean was observed. As the fast ice was joined to the glacier terminus, it could provide resistance against the glacier's flow, slowing down the rate of ice discharge. We used numerical modelling to quantify this resistive stress and found that the fast ice provided significant support to Crane prior to its disintegration.
Mai Winstrup, Heidi Ranndal, Signe Hillerup Larsen, Sebastian B. Simonsen, Kenneth D. Mankoff, Robert S. Fausto, and Louise Sandberg Sørensen
Earth Syst. Sci. Data, 16, 5405–5428, https://doi.org/10.5194/essd-16-5405-2024, https://doi.org/10.5194/essd-16-5405-2024, 2024
Short summary
Short summary
Surface topography across the marginal zone of the Greenland Ice Sheet is constantly evolving. Here we present an annual series (2019–2022) of summer digital elevation models (PRODEMs) for the Greenland Ice Sheet margin, covering all outlet glaciers from the ice sheet. The PRODEMs are based on fusion of CryoSat-2 radar altimetry and ICESat-2 laser altimetry. With their high spatial and temporal resolution, the PRODEMs will enable detailed studies of the changes in marginal ice sheet elevations.
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
EGUsphere, https://doi.org/10.5194/egusphere-2024-2855, https://doi.org/10.5194/egusphere-2024-2855, 2024
Short summary
Short summary
Perennial firn aquifers (PFAs), year-round bodies of liquid water within firn, can potentially impact ice-shelf and ice-sheet stability. We developed a fast XGBoost firn emulator to predict 21st-century distribution of PFAs in Antarctica for 12 climatic forcings datasets. Our findings suggest that under low emission scenarios, PFAs remain confined to the Antarctic Peninsula. However, under a high-emission scenario, PFAs are projected to expand to a region in West Antarctica and East Antarctica.
Renée M. Fredensborg Hansen, Henriette Skourup, Eero Rinne, Arttu Jutila, Isobel R. Lawrence, Andrew Shepherd, Knut V. Høyland, Jilu Li, Fernando Rodriguez-Morales, Sebastian B. Simonsen, Jeremy Wilkinson, Gaelle Veyssiere, Donghui Yi, René Forsberg, and Taniâ G. D. Casal
EGUsphere, https://doi.org/10.5194/egusphere-2024-2854, https://doi.org/10.5194/egusphere-2024-2854, 2024
Short summary
Short summary
In December 2022, an airborne campaign collected unprecedented coincident multi-frequency radar and lidar data over sea ice along a CryoSat-2 and ICESat-2 (CRYO2ICE) orbit in the Weddell Sea useful for evaluating microwave penetration. We found limited snow penetration at Ka- and Ku-bands, with significant contributions from the air-snow interface, contradicting traditional assumptions. These findings challenge current methods for comparing air- and spaceborne altimeter estimates of sea ice.
Nanna B. Karlsson, Dustin M. Schroeder, Louise Sandberg Sørensen, Winnie Chu, Jørgen Dall, Natalia H. Andersen, Reese Dobson, Emma J. Mackie, Simon J. Köhn, Jillian E. Steinmetz, Angelo S. Tarzona, Thomas O. Teisberg, and Niels Skou
Earth Syst. Sci. Data, 16, 3333–3344, https://doi.org/10.5194/essd-16-3333-2024, https://doi.org/10.5194/essd-16-3333-2024, 2024
Short summary
Short summary
In the 1970s, more than 177 000 km of observations were acquired from airborne radar over the Greenland ice sheet. The radar data contain information on not only the thickness of the ice, but also the properties of the ice itself. This information was recorded on film rolls and subsequently stored. In this study, we document the digitization of these film rolls that shed new and unprecedented detailed light on the Greenland ice sheet 50 years ago.
Nicolaj Hansen, Andrew Orr, Xun Zou, Fredrik Boberg, Thomas J. Bracegirdle, Ella Gilbert, Peter L. Langen, Matthew A. Lazzara, Ruth Mottram, Tony Phillips, Ruth Price, Sebastian B. Simonsen, and Stuart Webster
The Cryosphere, 18, 2897–2916, https://doi.org/10.5194/tc-18-2897-2024, https://doi.org/10.5194/tc-18-2897-2024, 2024
Short summary
Short summary
We investigated a melt event over the Ross Ice Shelf. We use regional climate models and a firn model to simulate the melt and compare the results with satellite data. We find that the firn model aligned well with observed melt days in certain parts of the ice shelf. The firn model had challenges accurately simulating the melt extent in the western sector. We identified potential reasons for these discrepancies, pointing to limitations in the models related to representing the cloud properties.
Aslak Grinsted, Nicholas Mossor Rathmann, Ruth Mottram, Anne Munck Solgaard, Joachim Mathiesen, and Christine Schøtt Hvidberg
The Cryosphere, 18, 1947–1957, https://doi.org/10.5194/tc-18-1947-2024, https://doi.org/10.5194/tc-18-1947-2024, 2024
Short summary
Short summary
Ice fracture can cause glacier crevassing and calving. These natural hazards can also modulate the flow and evolution of ice sheets. In a new study, we use a new high-resolution dataset to determine a new failure criterion for glacier ice. Surprisingly, the strength of ice depends on the mode of deformation, and this has potential implications for the currently used flow law of ice.
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
Short summary
Short summary
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.
Laura Melling, Amber Leeson, Malcolm McMillan, Jennifer Maddalena, Jade Bowling, Emily Glen, Louise Sandberg Sørensen, Mai Winstrup, and Rasmus Lørup Arildsen
The Cryosphere, 18, 543–558, https://doi.org/10.5194/tc-18-543-2024, https://doi.org/10.5194/tc-18-543-2024, 2024
Short summary
Short summary
Lakes on glaciers hold large volumes of water which can drain through the ice, influencing estimates of sea level rise. To estimate water volume, we must calculate lake depth. We assessed the accuracy of three satellite-based depth detection methods on a study area in western Greenland and considered the implications for quantifying the volume of water within lakes. We found that the most popular method of detecting depth on the ice sheet scale has higher uncertainty than previously assumed.
Louise Sandberg Sørensen, Rasmus Bahbah, Sebastian B. Simonsen, Natalia Havelund Andersen, Jade Bowling, Noel Gourmelen, Alex Horton, Nanna B. Karlsson, Amber Leeson, Jennifer Maddalena, Malcolm McMillan, Anne Solgaard, and Birgit Wessel
The Cryosphere, 18, 505–523, https://doi.org/10.5194/tc-18-505-2024, https://doi.org/10.5194/tc-18-505-2024, 2024
Short summary
Short summary
Under the right topographic and hydrological conditions, lakes may form beneath the large ice sheets. Some of these subglacial lakes are active, meaning that they periodically drain and refill. When a subglacial lake drains rapidly, it may cause the ice surface above to collapse, and here we investigate how to improve the monitoring of active subglacial lakes in Greenland by monitoring how their associated collapse basins change over time.
Anja Løkkegaard, Kenneth D. Mankoff, Christian Zdanowicz, Gary D. Clow, Martin P. Lüthi, Samuel H. Doyle, Henrik H. Thomsen, David Fisher, Joel Harper, Andy Aschwanden, Bo M. Vinther, Dorthe Dahl-Jensen, Harry Zekollari, Toby Meierbachtol, Ian McDowell, Neil Humphrey, Anne Solgaard, Nanna B. Karlsson, Shfaqat A. Khan, Benjamin Hills, Robert Law, Bryn Hubbard, Poul Christoffersen, Mylène Jacquemart, Julien Seguinot, Robert S. Fausto, and William T. Colgan
The Cryosphere, 17, 3829–3845, https://doi.org/10.5194/tc-17-3829-2023, https://doi.org/10.5194/tc-17-3829-2023, 2023
Short summary
Short summary
This study presents a database compiling 95 ice temperature profiles from the Greenland ice sheet and peripheral ice caps. Ice viscosity and hence ice flow are highly sensitive to ice temperature. To highlight the value of the database in evaluating ice flow simulations, profiles from the Greenland ice sheet are compared to a modeled temperature field. Reoccurring discrepancies between modeled and observed temperatures provide insight on the difficulties faced when simulating ice temperatures.
Nicolaj Hansen, Louise Sandberg Sørensen, Giorgio Spada, Daniele Melini, Rene Forsberg, Ruth Mottram, and Sebastian B. Simonsen
The Cryosphere Discuss., https://doi.org/10.5194/tc-2023-104, https://doi.org/10.5194/tc-2023-104, 2023
Preprint withdrawn
Short summary
Short summary
We use ICESat-2 to estimate the surface elevation change over Greenland and Antarctica in the period of 2018 to 2021. Numerical models have been used the compute the firn compaction and the vertical bedrock movement so non-mass-related elevation changes can be taken into account. We have made a parameterization of the surface density so we can convert the volume change to mass change. We find that Antarctica has lost 135.7±27.3 Gt per year, and the Greenland ice sheet 237.5±14.0 Gt per year.
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
Short summary
Short summary
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.
Karla Boxall, Frazer D. W. Christie, Ian C. Willis, Jan Wuite, and Thomas Nagler
The Cryosphere, 16, 3907–3932, https://doi.org/10.5194/tc-16-3907-2022, https://doi.org/10.5194/tc-16-3907-2022, 2022
Short summary
Short summary
Using high-spatial- and high-temporal-resolution satellite imagery, we provide the first evidence for seasonal flow variability of land ice draining to George VI Ice Shelf (GVIIS), Antarctica. Ultimately, our findings imply that other glaciers in Antarctica may be susceptible to – and/or currently undergoing – similar ice-flow seasonality, including at the highly vulnerable and rapidly retreating Pine Island and Thwaites glaciers.
Ioanna Karagali, Magnus Barfod Suhr, Ruth Mottram, Pia Nielsen-Englyst, Gorm Dybkjær, Darren Ghent, and Jacob L. Høyer
The Cryosphere, 16, 3703–3721, https://doi.org/10.5194/tc-16-3703-2022, https://doi.org/10.5194/tc-16-3703-2022, 2022
Short summary
Short summary
Ice surface temperature (IST) products were used to develop the first multi-sensor, gap-free Level 4 (L4) IST product of the Greenland Ice Sheet (GIS) for 2012, when a significant melt event occurred. For the melt season, mean IST was −15 to −1 °C, and almost the entire GIS experienced at least 1 to 5 melt days. Inclusion of the L4 IST to a surface mass budget (SMB) model improved simulated surface temperatures during the key onset of the melt season, where biases are typically large.
Juha Lemmetyinen, Juval Cohen, Anna Kontu, Juho Vehviläinen, Henna-Reetta Hannula, Ioanna Merkouriadi, Stefan Scheiblauer, Helmut Rott, Thomas Nagler, Elisabeth Ripper, Kelly Elder, Hans-Peter Marshall, Reinhard Fromm, Marc Adams, Chris Derksen, Joshua King, Adriano Meta, Alex Coccia, Nick Rutter, Melody Sandells, Giovanni Macelloni, Emanuele Santi, Marion Leduc-Leballeur, Richard Essery, Cecile Menard, and Michael Kern
Earth Syst. Sci. Data, 14, 3915–3945, https://doi.org/10.5194/essd-14-3915-2022, https://doi.org/10.5194/essd-14-3915-2022, 2022
Short summary
Short summary
The manuscript describes airborne, dual-polarised X and Ku band synthetic aperture radar (SAR) data collected over several campaigns over snow-covered terrain in Finland, Austria and Canada. Colocated snow and meteorological observations are also presented. The data are meant for science users interested in investigating X/Ku band radar signatures from natural environments in winter conditions.
Frank Paul, Livia Piermattei, Désirée Treichler, Lin Gilbert, Luc Girod, Andreas Kääb, Ludivine Libert, Thomas Nagler, Tazio Strozzi, and Jan Wuite
The Cryosphere, 16, 2505–2526, https://doi.org/10.5194/tc-16-2505-2022, https://doi.org/10.5194/tc-16-2505-2022, 2022
Short summary
Short summary
Glacier surges are widespread in the Karakoram and have been intensely studied using satellite data and DEMs. We use time series of such datasets to study three glacier surges in the same region of the Karakoram. We found strongly contrasting advance rates and flow velocities, maximum velocities of 30 m d−1, and a change in the surge mechanism during a surge. A sensor comparison revealed good agreement, but steep terrain and the two smaller glaciers caused limitations for some of them.
Ludivine Libert, Jan Wuite, and Thomas Nagler
The Cryosphere, 16, 1523–1542, https://doi.org/10.5194/tc-16-1523-2022, https://doi.org/10.5194/tc-16-1523-2022, 2022
Short summary
Short summary
Open fractures are important to monitor because they weaken the ice shelf structure. We propose a novel approach using synthetic aperture radar (SAR) interferometry for automatic delineation of ice shelf cracks. The method is applied to Sentinel-1 images of Brunt Ice Shelf, Antarctica, and the propagation of the North Rift, which led to iceberg calving in February 2021, is traced. It is also shown that SAR interferometry is more sensitive to rifting than SAR backscatter and optical imagery.
Nicolaj Hansen, Sebastian B. Simonsen, Fredrik Boberg, Christoph Kittel, Andrew Orr, Niels Souverijns, J. Melchior van Wessem, and Ruth Mottram
The Cryosphere, 16, 711–718, https://doi.org/10.5194/tc-16-711-2022, https://doi.org/10.5194/tc-16-711-2022, 2022
Short summary
Short summary
We investigate the impact of different ice masks when modelling surface mass balance over Antarctica. We used ice masks and data from five of the most used regional climate models and a common mask. We see large disagreement between the ice masks, which has a large impact on the surface mass balance, especially around the Antarctic Peninsula and some of the largest glaciers. We suggest a solution for creating a new, up-to-date, high-resolution ice mask that can be used in Antarctic modelling.
Martin Horwath, Benjamin D. Gutknecht, Anny Cazenave, Hindumathi Kulaiappan Palanisamy, Florence Marti, Ben Marzeion, Frank Paul, Raymond Le Bris, Anna E. Hogg, Inès Otosaka, Andrew Shepherd, Petra Döll, Denise Cáceres, Hannes Müller Schmied, Johnny A. Johannessen, Jan Even Øie Nilsen, Roshin P. Raj, René Forsberg, Louise Sandberg Sørensen, Valentina R. Barletta, Sebastian B. Simonsen, Per Knudsen, Ole Baltazar Andersen, Heidi Ranndal, Stine K. Rose, Christopher J. Merchant, Claire R. Macintosh, Karina von Schuckmann, Kristin Novotny, Andreas Groh, Marco Restano, and Jérôme Benveniste
Earth Syst. Sci. Data, 14, 411–447, https://doi.org/10.5194/essd-14-411-2022, https://doi.org/10.5194/essd-14-411-2022, 2022
Short summary
Short summary
Global mean sea-level change observed from 1993 to 2016 (mean rate of 3.05 mm yr−1) matches the combined effect of changes in water density (thermal expansion) and ocean mass. Ocean-mass change has been assessed through the contributions from glaciers, ice sheets, and land water storage or directly from satellite data since 2003. Our budget assessments of linear trends and monthly anomalies utilise new datasets and uncertainty characterisations developed within ESA's Climate Change Initiative.
Fredrik Boberg, Ruth Mottram, Nicolaj Hansen, Shuting Yang, and Peter L. Langen
The Cryosphere, 16, 17–33, https://doi.org/10.5194/tc-16-17-2022, https://doi.org/10.5194/tc-16-17-2022, 2022
Short summary
Short summary
Using the regional climate model HIRHAM5, we compare two versions (v2 and v3) of the global climate model EC-Earth for the Greenland and Antarctica ice sheets. We are interested in the surface mass balance of the ice sheets due to its importance when making estimates of future sea level rise. We find that the end-of-century change in the surface mass balance for Antarctica is 420 Gt yr−1 (v2) and 80 Gt yr−1 (v3), and for Greenland it is −290 Gt yr−1 (v2) and −1640 Gt yr−1 (v3).
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
Short summary
Short summary
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.
Helmut Rott, Stefan Scheiblauer, Jan Wuite, Lukas Krieger, Dana Floricioiu, Paola Rizzoli, Ludivine Libert, and Thomas Nagler
The Cryosphere, 15, 4399–4419, https://doi.org/10.5194/tc-15-4399-2021, https://doi.org/10.5194/tc-15-4399-2021, 2021
Short summary
Short summary
We studied relations between interferometric synthetic aperture radar (InSAR) signals and snow–firn properties and tested procedures for correcting the penetration bias of InSAR digital elevation models at Union Glacier, Antarctica. The work is based on SAR data of the TanDEM-X mission, topographic data from optical sensors and field measurements. We provide new insights on radar signal interactions with polar snow and show the performance of penetration bias retrievals using InSAR coherence.
Nicolaj Hansen, Peter L. Langen, Fredrik Boberg, Rene Forsberg, Sebastian B. Simonsen, Peter Thejll, Baptiste Vandecrux, and Ruth Mottram
The Cryosphere, 15, 4315–4333, https://doi.org/10.5194/tc-15-4315-2021, https://doi.org/10.5194/tc-15-4315-2021, 2021
Short summary
Short summary
We have used computer models to estimate the Antarctic surface mass balance (SMB) from 1980 to 2017. Our estimates lies between 2473.5 ± 114.4 Gt per year and 2564.8 ± 113.7 Gt per year. To evaluate our models, we compared the modelled snow temperatures and densities to in situ measurements. We also investigated the spatial distribution of the SMB. It is very important to have estimates of the Antarctic SMB because then it is easier to understand global sea level changes.
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
Short summary
Short summary
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.
Amy Solomon, Céline Heuzé, Benjamin Rabe, Sheldon Bacon, Laurent Bertino, Patrick Heimbach, Jun Inoue, Doroteaciro Iovino, Ruth Mottram, Xiangdong Zhang, Yevgeny Aksenov, Ronan McAdam, An Nguyen, Roshin P. Raj, and Han Tang
Ocean Sci., 17, 1081–1102, https://doi.org/10.5194/os-17-1081-2021, https://doi.org/10.5194/os-17-1081-2021, 2021
Short summary
Short summary
Freshwater in the Arctic Ocean plays a critical role in the global climate system by impacting ocean circulations, stratification, mixing, and emergent regimes. In this review paper we assess how Arctic Ocean freshwater changed in the 2010s relative to the 2000s. Estimates from observations and reanalyses show a qualitative stabilization in the 2010s due to a compensation between a freshening of the Beaufort Gyre and a reduction in freshwater in the Amerasian and Eurasian basins.
Robert S. Fausto, Dirk van As, Kenneth D. Mankoff, Baptiste Vandecrux, Michele Citterio, Andreas P. Ahlstrøm, Signe B. Andersen, William Colgan, Nanna B. Karlsson, Kristian K. Kjeldsen, Niels J. Korsgaard, Signe H. Larsen, Søren Nielsen, Allan Ø. Pedersen, Christopher L. Shields, Anne M. Solgaard, and Jason E. Box
Earth Syst. Sci. Data, 13, 3819–3845, https://doi.org/10.5194/essd-13-3819-2021, https://doi.org/10.5194/essd-13-3819-2021, 2021
Short summary
Short summary
The Programme for Monitoring of the Greenland Ice Sheet (PROMICE) has been measuring climate and ice sheet properties since 2007. Here, we present our data product from weather and ice sheet measurements from a network of automatic weather stations mainly located in the melt area of the ice sheet. Currently the PROMICE automatic weather station network includes 25 instrumented sites in Greenland.
Anne Solgaard, Anders Kusk, John Peter Merryman Boncori, Jørgen Dall, Kenneth D. Mankoff, Andreas P. Ahlstrøm, Signe B. Andersen, Michele Citterio, Nanna B. Karlsson, Kristian K. Kjeldsen, Niels J. Korsgaard, Signe H. Larsen, and Robert S. Fausto
Earth Syst. Sci. Data, 13, 3491–3512, https://doi.org/10.5194/essd-13-3491-2021, https://doi.org/10.5194/essd-13-3491-2021, 2021
Short summary
Short summary
The PROMICE Ice Velocity product is a time series of Greenland Ice Sheet ice velocity mosaics spanning September 2016 to present. It is derived from Sentinel-1 SAR data and has a spatial resolution of 500 m. Each mosaic spans 24 d (two Sentinel-1 cycles), and a new one is posted every 12 d (every Sentinel-1A cycle). The spatial comprehensiveness and temporal consistency make the product ideal for monitoring and studying ice-sheet-wide ice discharge and dynamics of glaciers.
Helle Astrid Kjær, Patrick Zens, Ross Edwards, Martin Olesen, Ruth Mottram, Gabriel Lewis, Christian Terkelsen Holme, Samuel Black, Kasper Holst Lund, Mikkel Schmidt, Dorthe Dahl-Jensen, Bo Vinther, Anders Svensson, Nanna Karlsson, Jason E. Box, Sepp Kipfstuhl, and Paul Vallelonga
The Cryosphere Discuss., https://doi.org/10.5194/tc-2020-337, https://doi.org/10.5194/tc-2020-337, 2021
Manuscript not accepted for further review
Short summary
Short summary
We have reconstructed accumulation in 6 firn cores and 8 snow cores in Northern Greenland and compared with a regional Climate model over Greenland. We find the model underestimate precipitation especially in north-eastern part of the ice cap- an important finding if aiming to reconstruct surface mass balance.
Temperatures at 10 meters depth at 6 sites in Greenland were also determined and show a significant warming since the 1990's of 0.9 to 2.5 °C.
Fredrik Boberg, Ruth Mottram, Nicolaj Hansen, Shuting Yang, and Peter L. Langen
The Cryosphere Discuss., https://doi.org/10.5194/tc-2020-331, https://doi.org/10.5194/tc-2020-331, 2020
Manuscript not accepted for further review
Short summary
Short summary
Using the regional climate model HIRHAM5, we compare two versions (v2 and v3) of the global climate model EC-Earth for the Greenland and Antarctica ice sheets. We are interested in the surface mass balance of the ice sheets due to its importance when making estimates of the future sea level rise. We find that the end-of-century change of the surface mass balance for Antarctica is +150 Gt yr−1 (v2) and −710 Gt yr−1 (v3) and for Greenland the numbers are −210 Gt yr−1 (v2) and −1150 Gt yr−1 (v3).
Kristian Svennevig, Trine Dahl-Jensen, Marie Keiding, John Peter Merryman Boncori, Tine B. Larsen, Sara Salehi, Anne Munck Solgaard, and Peter H. Voss
Earth Surf. Dynam., 8, 1021–1038, https://doi.org/10.5194/esurf-8-1021-2020, https://doi.org/10.5194/esurf-8-1021-2020, 2020
Short summary
Short summary
The 17 June 2017 Karrat landslide in Greenland caused a tsunami that killed four people. We apply a multidisciplinary workflow to reconstruct a timeline of events and find that three historic landslides occurred in 2009, 2016, and 2017. We also find evidence of much older periods of landslide activity. Three newly discovered active slopes might pose a future hazard. We speculate that the trigger for the recent events is melting permafrost due to a warming climate.
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
Short summary
Short summary
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.
Baptiste Vandecrux, Ruth Mottram, Peter L. Langen, Robert S. Fausto, Martin Olesen, C. Max Stevens, Vincent Verjans, Amber Leeson, Stefan Ligtenberg, Peter Kuipers Munneke, Sergey Marchenko, Ward van Pelt, Colin R. Meyer, Sebastian B. Simonsen, Achim Heilig, Samira Samimi, Shawn Marshall, Horst Machguth, Michael MacFerrin, Masashi Niwano, Olivia Miller, Clifford I. Voss, and Jason E. Box
The Cryosphere, 14, 3785–3810, https://doi.org/10.5194/tc-14-3785-2020, https://doi.org/10.5194/tc-14-3785-2020, 2020
Short summary
Short summary
In the vast interior of the Greenland ice sheet, snow accumulates into a thick and porous layer called firn. Each summer, the firn retains part of the meltwater generated at the surface and buffers sea-level rise. In this study, we compare nine firn models traditionally used to quantify this retention at four sites and evaluate their performance against a set of in situ observations. We highlight limitations of certain model designs and give perspectives for future model development.
Christine S. Hvidberg, Aslak Grinsted, Dorthe Dahl-Jensen, Shfaqat Abbas Khan, Anders Kusk, Jonas Kvist Andersen, Niklas Neckel, Anne Solgaard, Nanna B. Karlsson, Helle Astrid Kjær, and Paul Vallelonga
The Cryosphere, 14, 3487–3502, https://doi.org/10.5194/tc-14-3487-2020, https://doi.org/10.5194/tc-14-3487-2020, 2020
Short summary
Short summary
The Northeast Greenland Ice Stream (NEGIS) extends around 600 km from its onset in the interior of Greenland to the coast. Several maps of surface velocity and topography in Greenland exist, but accuracy is limited due to the lack of validation data. Here we present results from a 5-year GPS survey in an interior section of NEGIS. We use the data to assess a list of satellite-derived ice velocity and surface elevation products and discuss the implications for the ice stream flow in the area.
Cited articles
Abdalati, W. and Steffen, K.: Passive microwave derived snow melt regions on the Greenland Ice Sheet, Geophys. Res. Lett., 22, 787–790, https://doi.org/10.1029/95GL00433, 1995. a
Antwerpen, R. M., Tedesco, M., Fettweis, X., Alexander, P., and van de Berg, W. J.: Assessing bare-ice albedo simulated by MAR over the Greenland ice sheet (2000–2021) and implications for meltwater production estimates, The Cryosphere, 16, 4185–4199, https://doi.org/10.5194/tc-16-4185-2022, 2022. a
Ashcraft, I. S. and Long, D. G.: Comparison of methods for melt detection over Greenland using active and passive microwave measurements, Int. J. Remote Sens., 27, 2469–2488, https://doi.org/10.1080/01431160500534465, 2006. a, b, c
Box, J. E., Fettweis, X., Stroeve, J. C., Tedesco, M., Hall, D. K., and Steffen, K.: Greenland ice sheet albedo feedback: thermodynamics and atmospheric drivers, The Cryosphere, 6, 821–839, https://doi.org/10.5194/tc-6-821-2012, 2012. a, b, c
Brangers, I., Lievens, H., Miège, C., Demuzere, M., Brucker, L., and De Lannoy, G. J. M.: Sentinel 1 detects firn aquifers in the Greenland Ice Sheet, Geophys. Res. Lett., 47, e2019GL085192, https://doi.org/10.1029/2019GL085192, 2020. a
Brun, E., David, P., Sudul, M., and Brunot, G.: A numerical model to simulate snow-cover stratigraphy for operational avalanche forecasting, J. Glaciol., 38, 13–22, https://doi.org/10.3189/S0022143000009552, 1992. a, b, c
Chandler, D. M., Wadham, J. L., Lis, G. P., Cowton, T., Sole, A., Bartholomew, I., Telling, J., Nienow, P., Bagshaw, E. B., Mair, D., Vinen, S., and Hubbard, A.: Evolution of the subglacial drainage system beneath the Greenland Ice Sheet revealed by tracers, Nat. Geosci., 6, 195–198, https://doi.org/10.1038/ngeo1737, 2013. a
Colosio, P., Tedesco, M., Ranzi, R., and Fettweis, X.: Surface melting over the Greenland ice sheet derived from enhanced resolution passive microwave brightness temperatures (1979–2019), The Cryosphere, 15, 2623–2646, https://doi.org/10.5194/tc-15-2623-2021, 2021. a, b
Cuffey, K. and Paterson, W. S. B.: The Physics of Glaciers, Butterworth-Heinemann/Elsevier, Burlington, MA, 4th edn., oCLC: ocn488732494, ISBN 9780123694614, 2010. a
Cureton, E. E.: Rank-biserial correlation, Psychometrika, 21, 287–290, https://doi.org/10.1007/BF02289138, 1956. a
Davis, J. and Goadrich, M.: The relationship between Precision-Recall and ROC curves, in: Proceedings of the 23rd international conference on Machine learning, ICML '06, Association for Computing Machinery, New York, NY, USA, https://doi.org/10.1145/1143844.1143874, 233–240, 2006. a
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A. C. M., Van De Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B., Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P., Köhler, M., Matricardi, M., McNally, A. P., Monge-Sanz, B. M., Morcrette, J.-J., Park, B.-K., Peubey, C., De Rosnay, P., Tavolato, C., Thépaut, J.-N., and Vitart, F.: The ERA-Interim reanalysis: configuration and performance of the data assimilation system, Q. J. Roy. Meteor. Soc., 137, 553–597, https://doi.org/10.1002/qj.828, 2011. a
Dethinne, T., Glaude, Q., Picard, G., Kittel, C., Alexander, P., Orban, A., and Fettweis, X.: Sensitivity of the MAR regional climate model snowpack to the parameterization of the assimilation of satellite-derived wet-snow masks on the Antarctic Peninsula, The Cryosphere, 17, 4267–4288, https://doi.org/10.5194/tc-17-4267-2023, 2023. a, b
ECMWF: IFS Documentation CY33R1 – Part IV: Physical Processes, https://www.ecmwf.int/node/9227 (last access: 14 December 2023) 2009. a
Ettema, J., van den Broeke, M. R., van Meijgaard, E., van de Berg, W. J., Box, J. E., and Steffen, K.: Climate of the Greenland ice sheet using a high-resolution climate model – Part 1: Evaluation, The Cryosphere, 4, 511–527, https://doi.org/10.5194/tc-4-511-2010, 2010. a
Fausto, R. S., Andersen, S. B., Ahlstrøm, A. P., As, D. v., Box, J. E., Binder, D., Citterio, M., Colgan, W., Haubner, K., Hansen, K., Karlsson, N. B., Mankoff, K. D., Pedersen, A. Ø, Solgaard, A., and Vandecrux, B.: The Greenland ice sheet – snowline elevations at the end of the melt seasons from 2000 to 2017, Geol. Surv. Den. Greenl., 41, 71–74, https://doi.org/10.34194/geusb.v41.4346, 2018. a
Fausto, R. S., van As, D., Mankoff, K. D., Vandecrux, B., Citterio, M., Ahlstrøm, A. P., Andersen, S. B., Colgan, W., Karlsson, N. B., Kjeldsen, K. K., Korsgaard, N. J., Larsen, S. H., Nielsen, S., Pedersen, A. Ø., Shields, C. L., Solgaard, A. M., and Box, J. E.: Programme for Monitoring of the Greenland Ice Sheet (PROMICE) automatic weather station data, Earth Syst. Sci. Data, 13, 3819–3845, https://doi.org/10.5194/essd-13-3819-2021, 2021. a
Fettweis, X., Tedesco, M., van den Broeke, M., and Ettema, J.: Melting trends over the Greenland ice sheet (1958–2009) from spaceborne microwave data and regional climate models, The Cryosphere, 5, 359–375, https://doi.org/10.5194/tc-5-359-2011, 2011. a, b
Fettweis, X., Franco, B., Tedesco, M., van Angelen, J. H., Lenaerts, J. T. M., van den Broeke, M. R., and Gallée, H.: Estimating the Greenland ice sheet surface mass balance contribution to future sea level rise using the regional atmospheric climate model MAR, The Cryosphere, 7, 469–489, https://doi.org/10.5194/tc-7-469-2013, 2013. a
Fettweis, X., Box, J. E., Agosta, C., Amory, C., Kittel, C., Lang, C., van As, D., Machguth, H., and Gallée, H.: Reconstructions of the 1900–2015 Greenland ice sheet surface mass balance using the regional climate MAR model, The Cryosphere, 11, 1015–1033, https://doi.org/10.5194/tc-11-1015-2017, 2017. a, b, c
Fettweis, X., Hofer, S., Krebs-Kanzow, U., Amory, C., Aoki, T., Berends, C. J., Born, A., Box, J. E., Delhasse, A., Fujita, K., Gierz, P., Goelzer, H., Hanna, E., Hashimoto, A., Huybrechts, P., Kapsch, M.-L., King, M. D., Kittel, C., Lang, C., Langen, P. L., Lenaerts, J. T. M., Liston, G. E., Lohmann, G., Mernild, S. H., Mikolajewicz, U., Modali, K., Mottram, R. H., Niwano, M., Noël, B., Ryan, J. C., Smith, A., Streffing, J., Tedesco, M., van de Berg, W. J., van den Broeke, M., van de Wal, R. S. W., van Kampenhout, L., Wilton, D., Wouters, B., Ziemen, F., and Zolles, T.: GrSMBMIP: intercomparison of the modelled 1980–2012 surface mass balance over the Greenland Ice Sheet, The Cryosphere, 14, 3935–3958, https://doi.org/10.5194/tc-14-3935-2020, 2020. a, b, c, d
Figa-Saldaña, J., Wilson, J. J., Attema, E., Gelsthorpe, R., Drinkwater, M. R., and Stoffelen, A.: The advanced scatterometer (ASCAT) on the meteorological operational (MetOp) platform: a follow on for European wind scatterometers, Can. J. Remote Sens., 28, 404–412, https://doi.org/10.5589/m02-035, 2002. a
Forster, R. R., Box, J. E., Van Den Broeke, M. R., Miège, C., Burgess, E. W., Van Angelen, J. H., Lenaerts, J. T. M., Koenig, L. S., Paden, J., Lewis, C., Gogineni, S. P., Leuschen, C., and McConnell, J. R.: Extensive liquid meltwater storage in firn within the Greenland ice sheet, Nat. Geosci., 7, 95–98, https://doi.org/10.1038/ngeo2043, 2014. a
Gallée, H. and Schayes, G.: Development of a three-dimensional meso-γ primitive equation model: katabatic winds simulation in the area of Terra Nova Bay, Antarctica, Mon. Weather Rev., 122, 671–685, https://doi.org/10.1175/1520-0493(1994)122<0671:DOATDM>2.0.CO;2, 1994. a
Glaude, Q., Noel, B., Olesen, M., Van Den Broeke, M., Van De Berg, W. J., Mottram, R., Hansen, N., Delhasse, A., Amory, C., Kittel, C., Goelzer, H., and Fettweis, X.: A factor two difference in 21st century Greenland Ice Sheet surface mass balance projections from three regional climate models under a strong warming scenario (SSP5 8.5), Geophys. Res. Lett., 51, e2024GL111902, https://doi.org/10.1029/2024GL111902, 2024. a
Goelzer, H., Nowicki, S., Payne, A., Larour, E., Seroussi, H., Lipscomb, W. H., Gregory, J., Abe-Ouchi, A., Shepherd, A., Simon, E., Agosta, C., Alexander, P., Aschwanden, A., Barthel, A., Calov, R., Chambers, C., Choi, Y., Cuzzone, J., Dumas, C., Edwards, T., Felikson, D., Fettweis, X., Golledge, N. R., Greve, R., Humbert, A., Huybrechts, P., Le clec'h, S., Lee, V., Leguy, G., Little, C., Lowry, D. P., Morlighem, M., Nias, I., Quiquet, A., Rückamp, M., Schlegel, N.-J., Slater, D. A., Smith, R. S., Straneo, F., Tarasov, L., van de Wal, R., and van den Broeke, M.: The future sea-level contribution of the Greenland ice sheet: a multi-model ensemble study of ISMIP6, The Cryosphere, 14, 3071–3096, https://doi.org/10.5194/tc-14-3071-2020, 2020. a
Harper, J., Humphrey, N., Pfeffer, W. T., Brown, J., and Fettweis, X.: Greenland ice-sheet contribution to sea-level rise buffered by meltwater storage in firn, Nature, 491, 240–243, https://doi.org/10.1038/nature11566, 2012. a
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., De Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J.: The ERA5 global reanalysis, Q. J. Roy. Meteor. Soc., 146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020. a, b, c
How, P., Abermann, J., Ahlstrøm, A., Andersen, S., Box, J. E., Citterio, M., Colgan, W., Fausto, R., Karlsson, N., Jakobsen, J., Langley, K., Larsen, S., Mankoff, K., Pedersen, A., Rutishauser, A., Shield, C., Solgaard, A., Van As, D., Vandecrux, B., and Wright, P.: PROMICE and GC-Net automated weather station data in Greenland, GEUS Dataverse [data set], https://doi.org/10.22008/FK2/IW73UU, 2022. a, b
Husman, S. d. R., Hu, Z., Wouters, B., Munneke, P. K., Veldhuijsen, S., and Lhermitte, S.: Remote sensing of surface melt on Antarctica: opportunities and challenges, IEEE J. Sel. Top. Appl., 16, 2462–2480, https://doi.org/10.1109/JSTARS.2022.3216953, 2023. a, b, c
Koenig, L. S., Lampkin, D. J., Montgomery, L. N., Hamilton, S. L., Turrin, J. B., Joseph, C. A., Moutsafa, S. E., Panzer, B., Casey, K. A., Paden, J. D., Leuschen, C., and Gogineni, P.: Wintertime storage of water in buried supraglacial lakes across the Greenland Ice Sheet, The Cryosphere, 9, 1333–1342, https://doi.org/10.5194/tc-9-1333-2015, 2015. a
Krebs-Kanzow, U., Rodehacke, C. B., and Lohmann, G.: Brief communication: Surface energy balance differences over Greenland between ERA5 and ERA-Interim, The Cryosphere, 17, 5131–5136, https://doi.org/10.5194/tc-17-5131-2023, 2023. a, b, c
Langen, P. L., Mottram, R. H., Christensen, J. H., Boberg, F., Rodehacke, C. B., Stendel, M., Van As, D., Ahlstrøm, A. P., Mortensen, J., Rysgaard, S., Petersen, D., Svendsen, K. H., Aðalgeirsdóttir, G., and Cappelen, J.: Quantifying energy and mass fluxes controlling Godthåbsfjord freshwater input in a 5-km simulation (1991–2012), J. Climate, 28, 3694–3713, https://doi.org/10.1175/JCLI-D-14-00271.1, 2015. a, b
Langen, P. L., Fausto, R. S., Vandecrux, B., Mottram, R. H., and Box, J. E.: Liquid water flow and retention on the Greenland Ice Sheet in the regional climate model HIRHAM5: local and large-scale impacts, Front. Earth Sci., 4, https://doi.org/10.3389/feart.2016.00110, 2017 (data available at: https://ensemblesrt3.dmi.dk/data/prudence/temp/nichan/Daily2D_GrIS/, last access: 11 July 2025). a, b, c, d, e, f, g
Lindsley, R. D. and Long, D. G.: Adapting the sir algorithm to ASCAT, in: 2010 IEEE International Geoscience and Remote Sensing Symposium, 7–12 July 2024, Athens, Greece, https://doi.org/10.1109/IGARSS.2010.5650207, 3402–3405, 2010. a, b, c
Long, D. G.: Polar applications of spaceborne scatterometers, IEEE J. Sel. Top. Appl., 10, 2307–2320, https://doi.org/10.1109/JSTARS.2016.2629418, 2017. a, b, c, d
Long, D. G. and Drinkwater, M. R.: Greenland ice-sheet surface properties observed by the Seasat-A scatterometer at enhanced resolution, J. Glaciol., 40, 213–230, https://doi.org/10.3189/S0022143000007310, 1994. a, b, c
Long, D., Hardin, P., and Whiting, P.: Resolution enhancement of spaceborne scatterometer data, IEEE T. Geosci. Remote, 31, 700–715, https://doi.org/10.1109/36.225536, 1993. a
Lucas Picher, P., Wulff Nielsen, M., Christensen, J. H., Aðalgeirsdóttir, G., Mottram, R., and Simonsen, S. B.: Very high resolution regional climate model simulations over Greenland: identifying added value, J. Geophys. Res.-Atmos., 117, 2011JD016267, https://doi.org/10.1029/2011JD016267, 2012. a
Mann, H. B. and Whitney, D. R.: On a test of whether one of two random variables is stochastically larger than the other, Ann. Math. Stat., 18, 50–60, https://doi.org/10.1214/aoms/1177730491, 1947. a, b
Mätzler, C.: Applications of the interaction of microwaves with the natural snow cover, Remote Sensing Reviews, 2, 259–387, https://doi.org/10.1080/02757258709532086, 1987. a
Nagler, T., Wuite, J., Rott, H., Scheiblauer, S., Puggaard, A., and Prieto, D. F.: Monitoring Ice Sheet Melt and Refreeze Using Active Microwave Measurements, in: IGARSS 2024–2024 IEEE International Geoscience and Remote Sensing Symposium, 25–30 July 2010, Honolulu, Hawaii, USA, https://doi.org/10.1109/IGARSS53475.2024.10640970, 49–52, 2024 (data available at: https://cryoportal.enveo.at/data/, last access: 5 August 2025). a, b, c, d
Nghiem, S., Steffen, K., Kwok, R., and Tsai, W. Y.: Detection of snowmelt regions on the Greenland ice sheet using diurnal backscatter change, J. Glaciol., 47, 539–547, https://doi.org/10.3189/172756501781831738, 2001. a
Nghiem, S. V., Hall, D. K., Mote, T. L., Tedesco, M., Albert, M. R., Keegan, K., Shuman, C. A., DiGirolamo, N. E., and Neumann, G.: The extreme melt across the Greenland ice sheet in 2012, Geophys. Res. Lett., 39, 2012GL053611, https://doi.org/10.1029/2012GL053611, 2012. a
Noël, B., van de Berg, W. J., Machguth, H., Lhermitte, S., Howat, I., Fettweis, X., and van den Broeke, M. R.: A daily, 1 km resolution data set of downscaled Greenland ice sheet surface mass balance (1958–2015), The Cryosphere, 10, 2361–2377, https://doi.org/10.5194/tc-10-2361-2016, 2016. a
Noël, B., van de Berg, W. J., van Wessem, J. M., van Meijgaard, E., van As, D., Lenaerts, J. T. M., Lhermitte, S., Kuipers Munneke, P., Smeets, C. J. P. P., van Ulft, L. H., van de Wal, R. S. W., and van den Broeke, M. R.: Modelling the climate and surface mass balance of polar ice sheets using RACMO2 – Part 1: Greenland (1958–2016), The Cryosphere, 12, 811–831, https://doi.org/10.5194/tc-12-811-2018, 2018. a, b
Noël, B., Van De Berg, W. J., Lhermitte, S., and Van Den Broeke, M. R.: Rapid ablation zone expansion amplifies north Greenland mass loss, Science Advances, 5, eaaw0123, https://doi.org/10.1126/sciadv.aaw0123, 2019. a, b
Otosaka, I. N., Shepherd, A., Ivins, E. R., Schlegel, N.-J., Amory, C., van den Broeke, M. R., Horwath, M., Joughin, I., King, M. D., Krinner, G., Nowicki, S., Payne, A. J., Rignot, E., Scambos, T., Simon, K. M., Smith, B. E., Sørensen, L. S., Velicogna, I., Whitehouse, P. L., A, G., Agosta, C., Ahlstrøm, A. P., Blazquez, A., Colgan, W., Engdahl, M. E., Fettweis, X., Forsberg, R., Gallée, H., Gardner, A., Gilbert, L., Gourmelen, N., Groh, A., Gunter, B. C., Harig, C., Helm, V., Khan, S. A., Kittel, C., Konrad, H., Langen, P. L., Lecavalier, B. S., Liang, C.-C., Loomis, B. D., McMillan, M., Melini, D., Mernild, S. H., Mottram, R., Mouginot, J., Nilsson, J., Noël, B., Pattle, M. E., Peltier, W. R., Pie, N., Roca, M., Sasgen, I., Save, H. V., Seo, K.-W., Scheuchl, B., Schrama, E. J. O., Schröder, L., Simonsen, S. B., Slater, T., Spada, G., Sutterley, T. C., Vishwakarma, B. D., van Wessem, J. M., Wiese, D., van der Wal, W., and Wouters, B.: Mass balance of the Greenland and Antarctic ice sheets from 1992 to 2020, Earth Syst. Sci. Data, 15, 1597–1616, https://doi.org/10.5194/essd-15-1597-2023, 2023. a
Peterson, W., Birdsall, T., and Fox, W.: The theory of signal detectability, Transactions of the IRE Professional Group on Information Theory, 4, 171–212, https://doi.org/10.1109/TIT.1954.1057460, 1954. a
Picard, G., Leduc-Leballeur, M., Banwell, A. F., Brucker, L., and Macelloni, G.: The sensitivity of satellite microwave observations to liquid water in the Antarctic snowpack, The Cryosphere, 16, 5061–5083, https://doi.org/10.5194/tc-16-5061-2022, 2022. a
Puggaard, A.: anpug/4DG_meltmaps: v1.0.0 (v1.0.0), Zenodo [data set], https://doi.org/10.5281/zenodo.15480109, 2025. a
Rae, J. G. L., Aðalgeirsdóttir, G., Edwards, T. L., Fettweis, X., Gregory, J. M., Hewitt, H. T., Lowe, J. A., Lucas-Picher, P., Mottram, R. H., Payne, A. J., Ridley, J. K., Shannon, S. R., van de Berg, W. J., van de Wal, R. S. W., and van den Broeke, M. R.: Greenland ice sheet surface mass balance: evaluating simulations and making projections with regional climate models, The Cryosphere, 6, 1275–1294, https://doi.org/10.5194/tc-6-1275-2012, 2012. a
Rignot, E. and Mouginot, J.: Ice flow in Greenland for the International Polar Year 2008–2009, Geophys. Res. Lett., 39, L11501, https://doi.org/10.1029/2012GL051634, 2012. a, b, c
Roeckner, E., Bäuml, G., Bonaventura, L., Brokopf, R., Esch, M., Giorgetta, M., Hagemann, S., Kirchner, I., Kornblueh, L., Manzini, E., Rhodin, A., Schlese, U., Schulzweida, U., and Tompkins, A.: The atmospheric general circulation model ECHAM 5. PART I: model description, Max Planck Institute for Meteorology Report, https://pure.mpg.de/rest/items/item_995269_2/component/file_995268/content (last access: 4 August 2025) 349, 2003. a
Smith, L. C., Chu, V. W., Yang, K., Gleason, C. J., Pitcher, L. H., Rennermalm, A. K., Legleiter, C. J., Behar, A. E., Overstreet, B. T., Moustafa, S. E., Tedesco, M., Forster, R. R., LeWinter, A. L., Finnegan, D. C., Sheng, Y., and Balog, J.: Efficient meltwater drainage through supraglacial streams and rivers on the southwest Greenland ice sheet, P. Natl. Acad. Sci. USA, 112, 1001–1006, https://doi.org/10.1073/pnas.1413024112, 2015. a
Steffen, K., Vandecrux, B., Houtz, D., Abdalati, W., Bayou, N., Box, J., Colgan, W., Espona Pernas, L., Griessinger, N., Haas-Artho, D., Heilig, A., Hubert, A., Iosifescu Enescu, I., Johnson-Amin, N., Karlsson, N., Kurup Buchholz, R., McGrath, D., Cullen, N., Naderpour, R., Molotch, N., Pedersen, A., Perren, B., Philipps, T., Plattner, G.-K., Proksch, M., Revheim, M., Særrelse, M., Schneebli, M., Sampson, K., Starkweather, S., Steffen, S., Stroeve, J., Watler, B., Winton, Ø A., Zwally, J., and Ahlstrøm, A.: GC-Net Level 1 historical automated weather station, GEUS Dataverse [data set], https://doi.org/10.22008/FK2/VVXGUT, 2022. a, b
Tedesco, M.: Snowmelt detection over the Greenland ice sheet from SSM/I brightness temperature daily variations, Geophys. Res. Lett., 34, 2006GL028466, https://doi.org/10.1029/2006GL028466, 2007. a
Tedesco, M. and Fettweis, X.: Unprecedented atmospheric conditions (1948–2019) drive the 2019 exceptional melting season over the Greenland ice sheet, The Cryosphere, 14, 1209–1223, https://doi.org/10.5194/tc-14-1209-2020, 2020 (data available at: ftp://ftp.climato.be/fettweis/MARv3.12/Greenland, last access: May 2023). a, b, c, d, e
van Angelen, J. H., Lenaerts, J. T. M., Lhermitte, S., Fettweis, X., Kuipers Munneke, P., van den Broeke, M. R., van Meijgaard, E., and Smeets, C. J. P. P.: Sensitivity of Greenland Ice Sheet surface mass balance to surface albedo parameterization: a study with a regional climate model, The Cryosphere, 6, 1175–1186, https://doi.org/10.5194/tc-6-1175-2012, 2012. a
van den Broeke, M. R., Enderlin, E. M., Howat, I. M., Kuipers Munneke, P., Noël, B. P. Y., van de Berg, W. J., van Meijgaard, E., and Wouters, B.: On the recent contribution of the Greenland ice sheet to sea level change, The Cryosphere, 10, 1933–1946, https://doi.org/10.5194/tc-10-1933-2016, 2016. a, b, c
Vandecrux, B., Box, J. E., Ahlstrøm, A. P., Andersen, S. B., Bayou, N., Colgan, W. T., Cullen, N. J., Fausto, R. S., Haas-Artho, D., Heilig, A., Houtz, D. A., How, P., Iosifescu Enescu, I., Karlsson, N. B., Kurup Buchholz, R., Mankoff, K. D., McGrath, D., Molotch, N. P., Perren, B., Revheim, M. K., Rutishauser, A., Sampson, K., Schneebeli, M., Starkweather, S., Steffen, S., Weber, J., Wright, P. J., Zwally, H. J., and Steffen, K.: The historical Greenland Climate Network (GC-Net) curated and augmented level-1 dataset, Earth Syst. Sci. Data, 15, 5467–5489, https://doi.org/10.5194/essd-15-5467-2023, 2023. a
Vernon, C. L., Bamber, J. L., Box, J. E., van den Broeke, M. R., Fettweis, X., Hanna, E., and Huybrechts, P.: Surface mass balance model intercomparison for the Greenland ice sheet, The Cryosphere, 7, 599–614, https://doi.org/10.5194/tc-7-599-2013, 2013. a
WCRP Global Sea Level Budget Group: Global sea-level budget 1993–present, Earth Syst. Sci. Data, 10, 1551–1590, https://doi.org/10.5194/essd-10-1551-2018, 2018. a
Wismann, V.: Monitoring of seasonal snowmelt on Greenland with ERS scatterometer data, IEEE T. Geosci. Remote, 38, 1821–1826, https://doi.org/10.1109/36.851766, 2000. a, b, c, d
Short summary
Regional climate models are currently the only source for assessing the melt volume of the Greenland Ice Sheet on a global scale. This study compares the modeled melt volume with observations from weather stations and melt extent observed from the Advanced SCATterometer (ASCAT) to assess the performance of the models. It highlights the importance of critically evaluating model outputs with high-quality satellite measurements to improve the understanding of variability among models.
Regional climate models are currently the only source for assessing the melt volume of the...
