Articles | Volume 20, issue 8
https://doi.org/10.5194/tc-20-4327-2026
© Author(s) 2026. 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-20-4327-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
07 Aug 2026
Research article |
| 07 Aug 2026
| 07 Aug 2026
A State-Space Model for Monitoring Greenland Ice Sheet Surface Elevation Change from CryoSat-2
DTU Space, Elektrovej 328, 2800 Kgs Lyngby, Denmark
Sebastian B. Simonsen
DTU Space, Elektrovej 328, 2800 Kgs Lyngby, Denmark
Karina Nielsen
DTU Space, Elektrovej 328, 2800 Kgs Lyngby, Denmark
Mai Winstrup
DTU Space, Elektrovej 328, 2800 Kgs Lyngby, Denmark
Baptiste Vandecrux
Department of Glaciology and Climate, Geological Survey of Denmark and Greenland, Øster Voldgade 10, 1350 Copenhagen K, Denmark
Department of Earth Sciences, University at Buffalo, 413 Hochstetter Hall, Buffalo NY 14260, United States
Beata Csatho
Department of Earth Sciences, University at Buffalo, 413 Hochstetter Hall, Buffalo NY 14260, United States
Anton Schenk
Department of Earth Sciences, University at Buffalo, 413 Hochstetter Hall, Buffalo NY 14260, United States
Louise Sandberg Sørensen
DTU Space, Elektrovej 328, 2800 Kgs Lyngby, Denmark
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Baptiste Vandecrux, Robert S. Fausto, Jason E. Box, Federico Covi, Regine Hock, Åsa K. Rennermalm, Achim Heilig, Jakob Abermann, Dirk van As, Elisa Bjerre, Xavier Fettweis, Paul C. J. P. Smeets, Peter Kuipers Munneke, Michiel R. van den Broeke, Max Brils, Peter L. Langen, Ruth Mottram, and Andreas P. Ahlstrøm
The Cryosphere, 18, 609–631, https://doi.org/10.5194/tc-18-609-2024, https://doi.org/10.5194/tc-18-609-2024, 2024
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How fast is the Greenland ice sheet warming? In this study, we compiled 4500+ temperature measurements at 10 m below the ice sheet surface (T10m) from 1912 to 2022. We trained a machine learning model on these data and reconstructed T10m for the ice sheet during 1950–2022. After a slight cooling during 1950–1985, the ice sheet warmed at a rate of 0.7 °C per decade until 2022. Climate models showed mixed results compared to our observations and underestimated the warming in key regions.
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
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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
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Earth Syst. Sci. Data, 15, 5467–5489, https://doi.org/10.5194/essd-15-5467-2023, https://doi.org/10.5194/essd-15-5467-2023, 2023
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Denis Felikson, Sophie Nowicki, Isabel Nias, Beata Csatho, Anton Schenk, Michael J. Croteau, and Bryant Loomis
The Cryosphere, 17, 4661–4673, https://doi.org/10.5194/tc-17-4661-2023, https://doi.org/10.5194/tc-17-4661-2023, 2023
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We narrow the spread in model simulations of the Greenland Ice Sheet using velocity change, dynamic thickness change, and mass change observations. We find that the type of observation chosen can lead to significantly different calibrated probability distributions. Further work is required to understand how to best calibrate ensembles of ice sheet simulations because this will improve probability distributions of projected sea-level rise, which is crucial for coastal planning and adaptation.
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
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Youjiang Shen, Karina Nielsen, Menaka Revel, Dedi Liu, and Dai Yamazaki
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Earth Syst. Sci. Data, 15, 1597–1616, https://doi.org/10.5194/essd-15-1597-2023, https://doi.org/10.5194/essd-15-1597-2023, 2023
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By measuring changes in the volume, gravitational attraction, and ice flow of Greenland and Antarctica from space, we can monitor their mass gain and loss over time. Here, we present a new record of the Earth’s polar ice sheet mass balance produced by aggregating 50 satellite-based estimates of ice sheet mass change. This new assessment shows that the ice sheets have lost (7.5 x 1012) t of ice between 1992 and 2020, contributing 21 mm to sea level rise.
Monica Coppo Frias, Suxia Liu, Xingguo Mo, Karina Nielsen, Heidi Ranndal, Liguang Jiang, Jun Ma, and Peter Bauer-Gottwein
Hydrol. Earth Syst. Sci., 27, 1011–1032, https://doi.org/10.5194/hess-27-1011-2023, https://doi.org/10.5194/hess-27-1011-2023, 2023
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This paper uses remote sensing data from ICESat-2 to calibrate a 1D hydraulic model. With the model, we can make estimations of discharge and water surface elevation, which are important indicators in flooding risk assessment. ICESat-2 data give an added value, thanks to the 0.7 m resolution, which allows the measurement of narrow river streams. In addition, ICESat-2 provides measurements on the river dry portion geometry that can be included in the model.
Youjiang Shen, Dedi Liu, Liguang Jiang, Karina Nielsen, Jiabo Yin, Jun Liu, and Peter Bauer-Gottwein
Earth Syst. Sci. Data, 14, 5671–5694, https://doi.org/10.5194/essd-14-5671-2022, https://doi.org/10.5194/essd-14-5671-2022, 2022
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A data gap of 338 Chinese reservoirs with their surface water area (SWA), water surface elevation (WSE), and reservoir water storage change (RWSC) during 2010–2021. Validation against the in situ observations of 93 reservoirs indicates the relatively high accuracy and reliability of the datasets. The unique and novel remotely sensed dataset would benefit studies involving many aspects (e.g., hydrological models, water resources related studies, and more).
Giulia Sinnl, Mai Winstrup, Tobias Erhardt, Eliza Cook, Camilla Marie Jensen, Anders Svensson, Bo Møllesøe Vinther, Raimund Muscheler, and Sune Olander Rasmussen
Clim. Past, 18, 1125–1150, https://doi.org/10.5194/cp-18-1125-2022, https://doi.org/10.5194/cp-18-1125-2022, 2022
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A new Greenland ice-core timescale, covering the last 3800 years, was produced using the machine learning algorithm StratiCounter. We synchronized the ice cores using volcanic eruptions and wildfires. We compared the new timescale to the tree-ring timescale, finding good alignment both between the common signatures of volcanic eruptions and of solar activity. Our Greenlandic timescales is safe to use for the Late Holocene, provided one uses our uncertainty estimate.
Paolo Gabrielli, Theo Manuel Jenk, Michele Bertó, Giuliano Dreossi, Daniela Festi, Werner Kofler, Mai Winstrup, Klaus Oeggl, Margit Schwikowski, Barbara Stenni, and Carlo Barbante
Clim. Past Discuss., https://doi.org/10.5194/cp-2022-20, https://doi.org/10.5194/cp-2022-20, 2022
Revised manuscript not accepted
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We present a methodology that reduces the chronological uncertainty of an Alpine ice core record from the glacier Alto dell’Ortles, Italy. This chronology will allow the constraint of the Holocene climatic and environmental histories emerging from this archive of Central Europe. This method will allow to obtain accurate chronologies also from other ice cores from-low latitude/high-altitude glaciers that typically suffer from larger dating uncertainties compared with well dated polar records.
Michael J. MacFerrin, C. Max Stevens, Baptiste Vandecrux, Edwin D. Waddington, and Waleed Abdalati
Earth Syst. Sci. Data, 14, 955–971, https://doi.org/10.5194/essd-14-955-2022, https://doi.org/10.5194/essd-14-955-2022, 2022
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The vast majority of the Greenland ice sheet's surface is covered by pluriannual snow, also called firn, that accumulates year after year and is compressed into glacial ice. The thickness of the firn layer changes through time and responds to the surface climate. We present continuous measurement of the firn compaction at various depths for eight sites. The dataset will help to evaluate firn models, interpret ice cores, and convert remotely sensed ice sheet surface height change to mass loss.
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
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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
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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.
Kenneth D. Mankoff, Xavier Fettweis, Peter L. Langen, Martin Stendel, Kristian K. Kjeldsen, Nanna B. Karlsson, Brice Noël, Michiel R. van den Broeke, Anne Solgaard, William Colgan, Jason E. Box, Sebastian B. Simonsen, Michalea D. King, Andreas P. Ahlstrøm, Signe Bech Andersen, and Robert S. Fausto
Earth Syst. Sci. Data, 13, 5001–5025, https://doi.org/10.5194/essd-13-5001-2021, https://doi.org/10.5194/essd-13-5001-2021, 2021
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We estimate the daily mass balance and its components (surface, marine, and basal mass balance) for the Greenland ice sheet. Our time series begins in 1840 and has annual resolution through 1985 and then daily from 1986 through next week. Results are operational (updated daily) and provided for the entire ice sheet or by commonly used regions or sectors. This is the first input–output mass balance estimate to include the basal mass balance.
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
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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
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We compare the calculated surface mass budget (SMB) of Antarctica in five different regional climate models. On average ~ 2000 Gt of snow accumulates annually, but different models vary by ~ 10 %, a difference equivalent to ± 0.5 mm of global sea level rise. All models reproduce observed weather, but there are large differences in regional patterns of snowfall, especially in areas with very few observations, giving greater uncertainty in Antarctic mass budget than previously identified.
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Short summary
We developed a new statistical approach to track monthly changes in the surface height of the Greenland Ice Sheet using radar data from the CryoSat-2 satellite (2011–2025). The method lets seasonal and long-term variations emerge directly from the data, creating a consistent record of elevation change that helps reveal how Greenland responds to ongoing climate change.
We developed a new statistical approach to track monthly changes in the surface height of the...
