Articles | Volume 8, issue 2
https://doi.org/10.5194/tc-8-743-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/tc-8-743-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
28 Apr 2014
Research article |
| 28 Apr 2014
Empirical estimation of present-day Antarctic glacial isostatic adjustment and ice mass change
B. C. Gunter
School of Aerospace Engineering, Georgia Institute of Technology, 270 Ferst Dr. NW, Atlanta, GA 30332-0150, USA
Geoscience and Remote Sensing, Delft University of Technology, P.O. Box 5048, 2600 GA, Delft, the Netherlands
O. Didova
Geoscience and Remote Sensing, Delft University of Technology, P.O. Box 5048, 2600 GA, Delft, the Netherlands
R. E. M. Riva
Geoscience and Remote Sensing, Delft University of Technology, P.O. Box 5048, 2600 GA, Delft, the Netherlands
S. R. M. Ligtenberg
Institute for Marine and Atmospheric Research Utrecht, Utrecht University, P.O. Box 80.005, 3508 TA, Utrecht, the Netherlands
J. T. M. Lenaerts
Institute for Marine and Atmospheric Research Utrecht, Utrecht University, P.O. Box 80.005, 3508 TA, Utrecht, the Netherlands
M. A. King
School of Civil Engineering and Geosciences, Newcastle University, Newcastle upon Tyne NE1 7RU, UK
School of Geography and Environmental Studies, University of Tasmania, Hobart 7001, Australia
M. R. van den Broeke
Institute for Marine and Atmospheric Research Utrecht, Utrecht University, P.O. Box 80.005, 3508 TA, Utrecht, the Netherlands
T. Urban
The University of Texas at Austin, Center for Space Research, 3925 West Braker Ln, Ste 200, Austin, TX 78759, USA
Related authors
No articles found.
Jenan Rajavarathan, Matt King, Christopher Watson, and Nicolaj Hansen
The Cryosphere, 20, 5099–5113, https://doi.org/10.5194/tc-20-5099-2026, https://doi.org/10.5194/tc-20-5099-2026, 2026
Short summary
Short summary
Antarctic surface mass balance (SMB) is a source of major uncertainty in ice-sheet mass balance estimates, but its evaluation remains limited. We introduce a novel method using continuous, bedrock-fixed GPS vertical displacements as a spatially integrated constraint on low-frequency SMB variability over hundreds of kilometres. Applied across Antarctica, it reveals systematic, region-dependent differences with modelled SMB-driven displacements, guiding SMB model refinement.
Marte Gé Hofsteenge, Willem Jan van de Berg, Christiaan van Dalum, Kristiina Verro, Maurice van Tiggelen, and Michiel van den Broeke
The Cryosphere, 20, 4747–4766, https://doi.org/10.5194/tc-20-4747-2026, https://doi.org/10.5194/tc-20-4747-2026, 2026
Short summary
Short summary
We use a regional climate model to study how surface melt on Antarctic ice shelves responds to air temperature. The relationship is strongly non-linear, mainly due to feedbacks in surface albedo, with other energy sources also contributing. Currently colder, drier, and more stable ice shelves will experience more melt at the same temperature than ice shelves in wetter climates, highlighting their vulnerability to fracturing, ice shelf instability, and contributions to global sea-level rise.
Sanne B. M. Veldhuijsen, Peter Kuipers Munneke, Willem Jan van de Berg, Michiel R. van den Broeke, and Luke D. Trusel
EGUsphere, https://doi.org/10.5194/egusphere-2026-3453, https://doi.org/10.5194/egusphere-2026-3453, 2026
This preprint is open for discussion and under review for The Cryosphere (TC).
Short summary
Short summary
Antarctica has floating ice shelves around its perimeter that provide stability to the ice sheet. As temperature rises, snow on the ice shelves may melt away, and ponding of meltwater may cause the ice shelves to collapse. If that happens, Antarctica may start to lose ice faster than before, resulting in accelerated sea-level rise. The tool presented in this article will be used in simulations of future climate to determine when climate change leads to collapse of the ice shelves in Antarctica.
Xiaojun Ma, Matt King, Jonathan Bamber, Bin Liu, Wenke Sun, and Qiuyu Wang
EGUsphere, https://doi.org/10.5194/egusphere-2026-3461, https://doi.org/10.5194/egusphere-2026-3461, 2026
This preprint is open for discussion and under review for The Cryosphere (TC).
Short summary
Short summary
Satellite records of glacier change are only about two decades long, so short-term climate swings can strongly affect estimated trends. Using satellite gravity data, we show that the largest year-to-year changes in global glacier mass come from the Arctic and are linked to the North Atlantic Oscillation and Pacific Decadal Oscillation. Accounting for these effects makes Alaska’s estimated ice loss about one-third larger, improving interpretation of glacier change and future sea-level rise.
Fredrik Boberg, Xavier Fettweis, Nicolaj Hansen, Ruth Mottram, and Michiel R. van den Broeke
The Cryosphere, 20, 2947–2960, https://doi.org/10.5194/tc-20-2947-2026, https://doi.org/10.5194/tc-20-2947-2026, 2026
Short summary
Short summary
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.
Samuel M. Tax, Maurice van Tiggelen, Thirza N. Feenstra, Paul C. J. P. Smeets, Srinidhi N. Gadde, Christiaan T. van Dalum, Willem Jan van de Berg, and Michiel R. van den Broeke
EGUsphere, https://doi.org/10.5194/egusphere-2026-1926, https://doi.org/10.5194/egusphere-2026-1926, 2026
Short summary
Short summary
Strong winds can lift snow into the air, which influences the energy exchange between the surface and the atmosphere. We studied this phenomenon over the Greenland Ice Sheet using observations and a climate model. We found that blowing snow traps heat near the surface like a blanket and reflects incoming sunlight like a mirror. Simulating these processes increases the net energy at the surface and improves model accuracy. Therefore, we recommend including these effects in climate models.
Mirko Scheinert, Weisen Shen, Richard C. Aster, Lambert Caron, Michael D. Hartinger, Matt A. King, Andrew Lloyd, Anya M. Reading, J. Paul Winberry, Terry Wilson, Lucilla Alfonsi, Michael J. Bentley, Eric Buchta, Thomas Y. Chen, Peter J. Clarke, Jörg Ebbing, Olaf Eisen, Natalya Gomez, Esra Günaydın, Samantha Hansen, Erik R. Ivins, Achraf Koulali, Grace A. Nield, Frederick Richards, Mahmut O. Selbesoglu, Stephanie Sherman, Pippa L. Whitehouse, and Matthias Willen
EGUsphere, https://doi.org/10.5194/egusphere-2025-6370, https://doi.org/10.5194/egusphere-2025-6370, 2026
Short summary
Short summary
With an ongoing mass loss the Antarctic Ice Sheet contributes to global-mean sea level rise at a rate of 0.4 mm/a. Thus, it plays a key role in global climate and provides a natural laboratory to study processes that interlink cryosphere, solid Earth, atmosphere and ocean. We discuss how GNSS and seismic networks in Antarctica were used to significantly advance our understanding of these processes, and how they should be maintained and extended to answer key science questions in the future.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
John Bright Ayabilah, Matt King, Danielle Udy, and Tessa Vance
The Cryosphere, 20, 1237–1255, https://doi.org/10.5194/tc-20-1237-2026, https://doi.org/10.5194/tc-20-1237-2026, 2026
Short summary
Short summary
Large-scale climate modes significantly influence Antarctic Ice Sheet (AIS) mass variability. This study investigates AIS variability during different El Niño-Southern Oscillation (ENSO) periods using GRACE data (2002–2022). Results show strong spatial variability driven by changes in the Amundsen Sea Low (ASL) and Southern Annular Mode (SAM). This highlights the importance of understanding these patterns for future ice mass estimates and sea level rise predictions.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
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.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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.
Anneke L. Vries, Willem Jan van de Berg, Brice Noël, Lorenz Meire, and Michiel R. van den Broeke
The Cryosphere, 19, 3897–3914, https://doi.org/10.5194/tc-19-3897-2025, https://doi.org/10.5194/tc-19-3897-2025, 2025
Short summary
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.
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
Short summary
Short summary
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.
Eric Buchta, Mirko Scheinert, Matt A. King, Terry Wilson, Achraf Koulali, Peter J. Clarke, Demián Gómez, Eric Kendrick, Christoph Knöfel, and Peter Busch
Earth Syst. Sci. Data, 17, 1761–1780, https://doi.org/10.5194/essd-17-1761-2025, https://doi.org/10.5194/essd-17-1761-2025, 2025
Short summary
Short summary
Geodetic GPS measurements in Antarctica have been used to track bedrock displacement, which is vital for understanding geodynamic processes such as plate motion and glacial isostatic adjustment. However, the potential of GPS data has been limited by its partially fragmented availability and unreliable metadata. A new dataset, which spans the period from 1995 to 2021, offers consistently processed coordinate time series for 286 GPS sites and promises to enhance future geodynamic research.
Andrew O. Hoffman, Michelle L. Maclennan, Jan Lenaerts, Kristine M. Larson, and Knut Christianson
The Cryosphere, 19, 713–730, https://doi.org/10.5194/tc-19-713-2025, https://doi.org/10.5194/tc-19-713-2025, 2025
Short summary
Short summary
Traditionally, glaciologists use global navigation satellite systems (GNSSs) to measure the surface elevation and velocity of glaciers to understand processes associated with ice flow. Using the interference of GNSS signals that bounce off of the ice sheet surface, we measure the surface height change near GNSS receivers in the Amundsen Sea Embayment (ASE). From surface height change, we infer daily accumulation rates that we use to understand the drivers of extreme precipitation in the ASE.
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
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.
Lena G. Buth, Valeria Di Biase, Peter Kuipers Munneke, Stef Lhermitte, Sanne B. M. Veldhuijsen, Sophie de Roda Husman, Michiel R. van den Broeke, and Bert Wouters
EGUsphere, https://doi.org/10.5194/egusphere-2023-2000, https://doi.org/10.5194/egusphere-2023-2000, 2023
Preprint archived
Short summary
Short summary
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.
Rajashree Tri Datta, Adam Herrington, Jan T. M. Lenaerts, David P. Schneider, Luke Trusel, Ziqi Yin, and Devon Dunmire
The Cryosphere, 17, 3847–3866, https://doi.org/10.5194/tc-17-3847-2023, https://doi.org/10.5194/tc-17-3847-2023, 2023
Short summary
Short summary
Precipitation over Antarctica is one of the greatest sources of uncertainty in sea level rise estimates. Earth system models (ESMs) are a valuable tool for these estimates but typically run at coarse spatial resolutions. Here, we present an evaluation of the variable-resolution CESM2 (VR-CESM2) for the first time with a grid designed for enhanced spatial resolution over Antarctica to achieve the high resolution of regional climate models while preserving the two-way interactions of ESMs.
Eric Keenan, Nander Wever, Jan T. M. Lenaerts, and Brooke Medley
Geosci. Model Dev., 16, 3203–3219, https://doi.org/10.5194/gmd-16-3203-2023, https://doi.org/10.5194/gmd-16-3203-2023, 2023
Short summary
Short summary
Ice sheets gain mass via snowfall. However, snowfall is redistributed by the wind, resulting in accumulation differences of up to a factor of 5 over distances as short as 5 km. These differences complicate estimates of ice sheet contribution to sea level rise. For this reason, we have developed a new model for estimating wind-driven snow redistribution on ice sheets. We show that, over Pine Island Glacier in West Antarctica, the model improves estimates of snow accumulation variability.
Mattia Poinelli, Michael Schodlok, Eric Larour, Miren Vizcaino, and Riccardo Riva
The Cryosphere, 17, 2261–2283, https://doi.org/10.5194/tc-17-2261-2023, https://doi.org/10.5194/tc-17-2261-2023, 2023
Short summary
Short summary
Rifts are fractures on ice shelves that connect the ice on top to the ocean below. The impact of rifts on ocean circulation below Antarctic ice shelves has been largely unexplored as ocean models are commonly run at resolutions that are too coarse to resolve the presence of rifts. Our model simulations show that a kilometer-wide rift near the ice-shelf front modulates heat intrusion beneath the ice and inhibits basal melt. These processes are therefore worthy of further investigation.
Megan Thompson-Munson, Nander Wever, C. Max Stevens, Jan T. M. Lenaerts, and Brooke Medley
The Cryosphere, 17, 2185–2209, https://doi.org/10.5194/tc-17-2185-2023, https://doi.org/10.5194/tc-17-2185-2023, 2023
Short summary
Short summary
To better understand the Greenland Ice Sheet’s firn layer and its ability to buffer sea level rise by storing meltwater, we analyze firn density observations and output from two firn models. We find that both models, one physics-based and one semi-empirical, simulate realistic density and firn air content when compared to observations. The models differ in their representation of firn air content, highlighting the uncertainty in physical processes and the paucity of deep-firn measurements.
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.
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
Short summary
Short summary
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.
Michelle L. Maclennan, Jan T. M. Lenaerts, Christine A. Shields, Andrew O. Hoffman, Nander Wever, Megan Thompson-Munson, Andrew C. Winters, Erin C. Pettit, Theodore A. Scambos, and Jonathan D. Wille
The Cryosphere, 17, 865–881, https://doi.org/10.5194/tc-17-865-2023, https://doi.org/10.5194/tc-17-865-2023, 2023
Short summary
Short summary
Atmospheric rivers are air masses that transport large amounts of moisture and heat towards the poles. Here, we use a combination of weather observations and models to quantify the amount of snowfall caused by atmospheric rivers in West Antarctica which is about 10 % of the total snowfall each year. We then examine a unique event that occurred in early February 2020, when three atmospheric rivers made landfall over West Antarctica in rapid succession, leading to heavy snowfall and surface melt.
Carolina M. L. Camargo, Riccardo E. M. Riva, Tim H. J. Hermans, Eike M. Schütt, Marta Marcos, Ismael Hernandez-Carrasco, and Aimée B. A. Slangen
Ocean Sci., 19, 17–41, https://doi.org/10.5194/os-19-17-2023, https://doi.org/10.5194/os-19-17-2023, 2023
Short summary
Short summary
Sea-level change is mainly caused by variations in the ocean’s temperature and salinity and land ice melting. Here, we quantify the contribution of the different drivers to the regional sea-level change. We apply machine learning techniques to identify regions that have similar sea-level variability. These regions reduce the observational uncertainty that has limited the regional sea-level budget so far and highlight how large-scale ocean circulation controls regional sea-level change.
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
Short summary
Short summary
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.
Devon Dunmire, Jan T. M. Lenaerts, Rajashree Tri Datta, and Tessa Gorte
The Cryosphere, 16, 4163–4184, https://doi.org/10.5194/tc-16-4163-2022, https://doi.org/10.5194/tc-16-4163-2022, 2022
Short summary
Short summary
Earth system models (ESMs) are used to model the climate system and the interactions of its components (atmosphere, ocean, etc.) both historically and into the future under different assumptions of human activity. The representation of Antarctica in ESMs is important because it can inform projections of the ice sheet's contribution to sea level rise. Here, we compare output of Antarctica's surface climate from an ESM with observations to understand strengths and weaknesses within the model.
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
Short summary
Short summary
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.
Carolina M. L. Camargo, Riccardo E. M. Riva, Tim H. J. Hermans, and Aimée B. A. Slangen
Earth Syst. Dynam., 13, 1351–1375, https://doi.org/10.5194/esd-13-1351-2022, https://doi.org/10.5194/esd-13-1351-2022, 2022
Short summary
Short summary
The mass loss from Antarctica, Greenland and glaciers and variations in land water storage cause sea-level changes. Here, we characterize the regional trends within these sea-level contributions, taking into account mass variations since 1993. We take a comprehensive approach to determining the uncertainties of these sea-level changes, considering different types of errors. Our study reveals the importance of clearly quantifying the uncertainties of sea-level change trends.
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
Short summary
Short summary
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.
Ole Richter, David E. Gwyther, Matt A. King, and Benjamin K. Galton-Fenzi
The Cryosphere, 16, 1409–1429, https://doi.org/10.5194/tc-16-1409-2022, https://doi.org/10.5194/tc-16-1409-2022, 2022
Short summary
Short summary
Tidal currents may play an important role in Antarctic ice sheet retreat by changing the rate at which the ocean melts glaciers. Here, using a computational ocean model, we derive the first estimate of present-day tidal melting that covers all of Antarctica. Our results suggest that large-scale ocean models aiming to accurately predict ice melt rates will need to account for the effects of tides. The inclusion of tide-induced friction at the ice–ocean interface should be prioritized.
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
Short summary
Short summary
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.
Grace A. Nield, Matt A. King, Rebekka Steffen, and Bas Blank
Geosci. Model Dev., 15, 2489–2503, https://doi.org/10.5194/gmd-15-2489-2022, https://doi.org/10.5194/gmd-15-2489-2022, 2022
Short summary
Short summary
We present a finite-element model of post-seismic solid Earth deformation built in the software package Abaqus for the purpose of calculating post-seismic deformation in the far field of major earthquakes. The model is benchmarked against an existing open-source post-seismic model demonstrating good agreement. The advantage over existing models is the potential for simple modification to include 3-D Earth structure, non-linear rheologies and alternative or multiple sources of stress change.
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
Short summary
Short summary
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.
Karen E. Alley, Christian T. Wild, Adrian Luckman, Ted A. Scambos, Martin Truffer, Erin C. Pettit, Atsuhiro Muto, Bruce Wallin, Marin Klinger, Tyler Sutterley, Sarah F. Child, Cyrus Hulen, Jan T. M. Lenaerts, Michelle Maclennan, Eric Keenan, and Devon Dunmire
The Cryosphere, 15, 5187–5203, https://doi.org/10.5194/tc-15-5187-2021, https://doi.org/10.5194/tc-15-5187-2021, 2021
Short summary
Short summary
We present a 20-year, satellite-based record of velocity and thickness change on the Thwaites Eastern Ice Shelf (TEIS), the largest remaining floating extension of Thwaites Glacier (TG). TG holds the single greatest control on sea-level rise over the next few centuries, so it is important to understand changes on the TEIS, which controls much of TG's flow into the ocean. Our results suggest that the TEIS is progressively destabilizing and is likely to disintegrate over the next few decades.
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.
Cited articles
Bamber, J. and Riva, R.: The sea level fingerprint of recent ice mass fluxes, The Cryosphere, 4, 621–627, https://doi.org/10.5194/tc-4-621-2010, 2010.
Bettadpur, S.: CSR Level-2 Processing Standards Document for Product Release 04 GRACE 327-742, Center for Space Research, 3.1 Edn., http://podaac.jpl.nasa.gov/gravity/grace-documentation (last accessed 18 April 2014), 2007.
Borsa, A. A., Moholdt, G., Fricker, H. A., and Brunt, K. M.: A range correction for ICESat and its potential impact on ice-sheet mass balance studies, The Cryosphere, 8, 345–357, https://doi.org/10.5194/tc-8-345-2014, 2014.
Chambers, D. P. and Bonin, J. A.: Evaluation of Release-05 GRACE time-variable gravity coefficients over the ocean, Ocean Sci., 8, 859–868, https://doi.org/10.5194/os-8-859-2012, 2012.
Chen, J. L., Wilson, C. R., Blankenship, D. D., and Tapley, B. D.: Antarctic mass rates from GRACE, Geophys. Res. Lett., 33, L11502, https://doi.org/10.1029/2006GL026369, 2006.
Cheng, M. and Tapley, B. D.: Variations in the Earth's oblateness during the past 28 years, J. Geophys. Res., 109, B09402, https://doi.org/10.1029/2004JB003028, 2004.
Cheng, M., Ries, J. C., and Tapley, B. D.: Variations of the Earth's figure axis from satellite laser ranging and GRACE, J. Geophys. Res.-Earth, 116, B01409, https://doi.org/10.1029/2010JB000850, 2011.
Ewert, H., Popov, S. V., Richter, A., Schwabe, J., Scheinert, M., and Dietrich, R.: Precise analysis of ICESat altimetry data and assessment of the hydrostatic equilibrium for subglacial Lake Vostok, East Antarctica, Geophys. J. Int., 191, 557–568, https://doi.org/10.1111/j.1365-246X.2012.05649.x, 2012.
Ferguson, A., Davis, C., and Cavanaugh, J.: An autoregressive model for analysis of ice sheet elevation change time series, Geoscience and Remote Sensing, IEEE Trans. Geosci. Remote Sens., 42, 2426–2436, https://doi.org/10.1109/TGRS.2004.836788, 2004.
Groh, A., Ewert, H., Scheinert, M., Fritsche, M., Rülke, A., Richter, A., Rosenau, R., and Dietrich, R.: An investigation of Glacial Isostatic Adjustment over the Amundsen Sea sector, West Antarctica, Global Planet. Change, 98–99, 45–53, https://doi.org/10.1016/j.gloplacha.2012.08.001, 2012.
Gunter, B., Urban, T., Riva, R., Helsen, M., Harpold, R., Poole, S., Nagel, P., Schutz, B., and Tapley, B.: A comparison of coincident GRACE and ICESat data over Antarctica, J. Geodesy, 83, 1051–1060, https://doi.org/10.1007/s00190-009-0323-4, 2009.
Gunter, B., Riva, R., Urban, T., Harpold, R., Schutz, B., Nagel, P., and Helsen, M.: Evaluation of GRACE and ICESat Mass Change Estimates Over Antarctica, in: Gravity, Geoid and Earth Observation, edited by: Mertikas, S. P., vol. 135 of International Association of Geodesy Symposia, 563–569, Springer Berlin Heidelberg, https://doi.org/10.1007/978-3-642-10634-7_75, 2010.
Horwath, M. and Dietrich, R.: Signal and error in mass change inferences from GRACE}: the case of {Antarctica, Geophys. J. Int., 177, 849–864, https://doi.org/0.1111/j.1365-246X.2009.04139.x, 2009.
Hughes, G. B. and Chraibi, M.: Calculating Ellipse Overlap Areas, http://arxiv.org/abs/1106.3787 (last access: 18 April 2014), 2011.
Ivins, E. R. and James, T. S.: Antarctic glacial isostatic adjustment: a new assessment, Antarct. Sci., 17, 541–553, 2005.
Jacob, T., Wahr, J., Pfeffer, W., and Swenson, S.: Recent contributions of glaciers and ice caps to sea level rise, Nature, 482, 514–518, 2012.
Kaspers, K. A., van de Wal, R. S. W., van den Broeke, M. R., Schwander, J., van Lipzig, N. P. M., and Brenninkmeijer, C. A. M.: Model calculations of the age of firn air across the Antarctic continent, Atmos. Chem. Phys., 4, 1365–1380, https://doi.org/10.5194/acp-4-1365-2004, 2004.
King, M. A., Bingham, R. J., Moore, P., Whitehouse, P. L., Bentley, M. J., and Milne, G. A.: Lower satellite-gravimetry estimates of Antarctic sea-level contribution, Nature, 491, 586–589, https://doi.org/10.1038/nature11621, 2012.
Klees, R., Revtova, E. A., Gunter, B. C., Ditmar, P., Oudman, E., Winsemius, H. C., and Savenije, H. H. G.: The design of an optimal filter for monthly GRACE gravity models, Geophys. J. Int., 175, 417–432, https://doi.org/10.1111/j.1365-246X.2008.03922.x, 2008.
Kusche, J.: Approximate decorrelation and non-isotropic smoothing of time-variable GRACE-type gravity field models, J. Geodesy, 81, 733–749, https://doi.org/10.1007/s00190-007-0143-3, 2007.
Lenaerts, J. T. M., van den Broeke, M. R., van de Berg, W. J., van Meijgaard, E., and Kuipers Munneke, P.: A new, high-resolution surface mass balance map of Antarctica (1979–2010) based on regional atmospheric climate modeling, Geophys. Res. Lett., 39, L04501, https://doi.org/10.1029/2011GL050713, 2012.
Ligtenberg, S. R. M., Helsen, M. M., and van den Broeke, M. R.: An improved semi-empirical model for the densification of Antarctic firn, The Cryosphere, 5, 809–819, https://doi.org/10.5194/tc-5-809-2011, 2011.
Liu, X., Ditmar, P., Siemes, C., Slobbe, D., Revtova, E., Klees, R., Riva, R., and Zhao, Q.: DEOS Mass Transport model (DMT-1) based on GRACE satellite data: methodology, validation, and application to estimating the ice mass balance of Greenland, Geophys. J. Int., 181, 769–788, 2010.
Nield, G. A., Whitehouse, P. L., King, M. A., Clarke, P. J., and Bentley, M. J.: Increased ice loading in the Antarctic Peninsula since the 1850s and its effect on glacial isostatic adjustment, Geophys. Res. Lett., 39, L17504, https://doi.org/10.1029/2012GL052559, 2012.
Peltier, W.: Global glacial isostasy and the surface of the ice-age Earth: The ICE-5G (VM2) Model and GRACE, Annu. Rev. Earth Pl. Sc., 32, 111–149, 2004.
Pritchard, H. D., Arthern, R. J., Vaughan, D. G., and Edwards, L. A.: Extensive dynamic thinning on the margins of the Greenland and Antarctic ice sheets, Nature, 461, 971–975, https://doi.org/10.1038/nature08471, 2009.
Rignot, E., Bamber, J., van den Broeke, M., Davis, C., Li, Y., van de Berg, W., and van Meijgaard, E.: Recent Antarctic ice mass loss from radar interferometry and regional climate modelling, Nat. Geosci., 1, 106–110, https://doi.org/10.1038/ngeo102, 2008.
Riva, R. E. M., Gunter, B. C., Urban, T. J., Vermeersen, B. L. A., Lindenbergh, R. C., Helsen, M. M., Bamber, J. L., van den Broeke, M. R., and Schutz, B. E.: Glacial Isostatic Adjustment over Antarctica from combined ICESat and GRACE satellite data, Earth Planet. Sc. Lett., 288, 516–523, https://doi.org/10.1016/j.epsl.2009.10.013, 2009.
Sasgen, I., Konrad, H., Ivins, E. R., Van den Broeke, M. R., Bamber, J. L., Martinec, Z., and Klemann, V.: Antarctic ice-mass balance 2003 to 2012: regional reanalysis of GRACE satellite gravimetry measurements with improved estimate of glacial-isostatic adjustment based on GPS uplift rates, The Cryosphere, 7, 1499–1512, https://doi.org/10.5194/tc-7-1499-2013, 2013.
Save, H., Bettadpur, S., and Tapley, B.: Reducing errors in the GRACE gravity solutions using regularization, J. Geodesy, 86, 695–711, https://doi.org/10.1007/s00190-012-0548-5, 2012.
Scambos, T. A., Bohlander, J. A., Shuman, C. A., and Skvarca, P.: Glacier acceleration and thinning after ice shelf collapse in the Larsen B embayment, Antarctica, Geophys. Res. Lett., 31, L18402, https://doi.org/10.1029/2004GL020670, 2004.
Seo, K.-W., Wilson, C. R., Chen, J., and Waliser, D. E.: GRACE's spatial aliasing error, Geophys. J. Int., 172, 41–48, https://doi.org/10.1111/j.1365-246X.2007.03611.x, 2008.
Shepherd, A., Ivins, E. R., A, G., Barletta, V. R., Bentley, M. J., Bettadpur, S., Briggs, K. H., Bromwich, D. H., Forsberg, R., Galin, N., Horwath, M., Jacobs, S., Joughin, I., King, M. A., Lenaerts, J. T. M., Li, J., Ligtenberg, S. R. M., Luckman, A., Luthcke, S. B., McMillan, M., Meister, R., Milne, G., Mouginot, J., Muir, A., Nicolas, J. P., Paden, J., Payne, A. J., Pritchard, H., Rignot, E., Rott, H., Sørensen, L. S., Scambos, T. A., Scheuchl, B., Schrama, E. J. O., Smith, B., Sundal, A. V., van Angelen, J. H., van de Berg, W. J., van den Broeke, M. R., Vaughan, D. G., Velicogna, I., Wahr, J., Whitehouse, P. L., Wingham, D. J., Yi, D., Young, D., and Zwally, H. J.: A Reconciled Estimate of Ice-Sheet Mass Balance, Science, 338, 1183–1189, https://doi.org/10.1126/science.1228102, 2012.
Siegfried, M., Hawley, R., and Burkhart, J.: High-Resolution Ground-Based GPS Measurements Show Intercampaign Bias in ICESat Elevation Data Near Summit, Greenland, IEEE T. Geosci. Remote, 49, 3393–3400, https://doi.org/10.1109/TGRS.2011.2127483, 2011.
Siemes, C., Ditmar, P., Riva, R., Slobbe, D., Liu, X., and Farahani, H.: Estimation of mass change trends in the Earth's system on the basis of GRACE satellite data, with application to Greenland, J. Geodesy, 87, 69–87, https://doi.org/10.1007/s00190-012-0580-5, 2013.
Simon, K., James, T., and Ivins, E.: Ocean loading effects on the prediction of Antarctic glacial isostatic uplift and gravity rates, J. Geodesy, 84, 305–317, https://doi.org/10.1007/s00190-010-0368-4, 2010.
Slobbe, D., Lindenbergh, R., and Ditmar, P.: Estimation of volume change rates of Greenland's ice sheet from ICESat data using overlapping footprints, Remote Sens. Environ., 112, 4204–4213, https://doi.org/10.1016/j.rse.2008.07.004, 2008.
Strang, G. and Borre, K.: Linear Algebra, Geodesy, and GPS, Wellesley-Cambridge Press, Wellesley, MA, 1997.
Swenson, S. and Wahr, J.: Post-processing removal of correlated errors in GRACE data, J. Geophys. Res., 33, L08402, https://doi.org/10.1029/2005GL025285, 2006.
Swenson, S., Chambers, D., and Wahr, J.: Estimating Geocenter Variations from a Combination of GRACE and Ocean Model Output, J. Geophys. Res., 13, B08410, https://doi.org/10.1029/2007JB005338, 2008.
Thomas, I. D., King, M. A., Bentley, M. J., Whitehouse, P. L., Penna, N. T., Williams, S. D. P., Riva, R. E. M., Lavallee, D. A., Clarke, P. J., King, E. C., Hindmarsh, R. C. A., and Koivula, H.: Widespread low rates of Antarctic glacial isostatic adjustment revealed by GPS observations, Geophys. Res. Lett., 38, L22302, https://doi.org/10.1029/2011GL049277, 2011.
Thompson, P. F., Bettadpur, S. V., and Tapley, B. D.: Impact of short period, non-tidal, temporal mass variability on GRACE gravity estimates, Geophys. Res. Lett., 31, L06619, https://doi.org/10.1029/2003GL019285, 2004.
Urban, T. and Schutz, B. E.: ICESat sea level comparisons, Geophys. Res. Lett., 32, L23S10, https://doi.org/10.1029/2005GL024306, 2005.
Velicogna, I. and Wahr, J.: A method for separating Antarctic postglacial rebound and ice mass balance using future ICESat Geoscience Laser Altimeter System, Gravity Recovery and Climate Experiment, and GPS satellite data, J. Geophys. Res.-Earth, 107, ETG 20-1–ETG 20-11, https://doi.org/10.1029/2001JB000708, 2002.
Velicogna, I. and Wahr, J.: Time-variable gravity observations of ice sheet mass balance: Precision and limitations of the GRACE satellite data, Geophys. Res. Lett., 40, 3055–3063, https://doi.org/10.1002/grl.50527, 2013.
Wahr, J., Molenaar, M., and Bryan, F.: Time variability of the Earth's gravity field: Hydrological and oceanic effects and their possible detection using GRACE, J. Geophys. Res., 103, 30205–30230, https://doi.org/10.1029/98JB02844, 1998.
Wahr, J., Wingham, D., and Bentley, C.: A method of combining ICESat and GRACE satellite data to constrain Antarctic mass balance, J. Geophys. Res., 105, 16279–16294, 2000.
Whitehouse, P. L., Bentley, M. J., Milne, G. A., King, M. A., and Thomas, I. D.: A new glacial isostatic adjustment model for Antarctica: calibrated and tested using observations of relative sea-level change and present-day uplift rates, Geophys. J. Int., 190, 1464–1482, https://doi.org/10.1111/j.1365-246X.2012.05557.x, 2012.
Williams, S. D., Moore, P., King, M. A., and Whitehouse, P. L.: Revisiting GRACE Antarctic ice mass trends and accelerations considering autocorrelation, Earth Planet. Sc. Lett., 385, 12–21, https://doi.org/10.1016/j.epsl.2013.10.016, 2014.
Zwally, J. H., Schutz, R., Bentley, C., Bufton, J., Herring, T., Minster, J., Spinhirne, J., and Thomas, R.: GLAS/ICESat L2 Antarctic and Greenland Ice Sheet Altimetry Data. Version 33. GLA12., Boulder, Colorado USA: National Snow and Ice Data Center, 2011.
Zwally, J. H., Giovinetto, M. B., Beckley, M. A., and Saba, J. L.: Antarctic and Greenland Drainage Systems, GSFC Cryospheric Sciences Laboratory, http://icesat4.gsfc.nasa.gov/cryo_data/ant_grn_drainage_systems.php (last access: 18 April 2014), 2012.
