Articles | Volume 17, issue 9
https://doi.org/10.5194/essd-17-4253-2025
© 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/essd-17-4253-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description article
| 
01 Sep 2025
Data description article |
| 01 Sep 2025
| 01 Sep 2025
GCL-Mascon2024: a novel satellite gravimetry mascon solution using the short-arc approach
Zhengwen Yan
Department of Earth and Space Sciences, Southern University of Science and Technology, Shenzhen, 518055, China
Key Laboratory of Intraplate Volcanoes and Earthquakes (China University of Geosciences, Beijing), Ministry of Education, Beijing, 100083, China
Key Laboratory of Polar Environment Monitoring and Public Governance (Wuhan University), Ministry of Education, Wuhan, 430072, China
Jiangjun Ran
CORRESPONDING AUTHOR
Department of Earth and Space Sciences, Southern University of Science and Technology, Shenzhen, 518055, China
Pavel Ditmar
Department of Geoscience and Remote Sensing, Delft University of Technology, Delft, 2628 CN, the Netherlands
C. K. Shum
Division of Geodetic Science, School of Earth Sciences, The Ohio State University, Columbus, Ohio 43210, USA
Roland Klees
Department of Geoscience and Remote Sensing, Delft University of Technology, Delft, 2628 CN, the Netherlands
Patrick Smith
Division of Geodetic Science, School of Earth Sciences, The Ohio State University, Columbus, Ohio 43210, USA
Xavier Fettweis
Department of Geography, University of Liège, Liège, 4000, Belgium
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María Santolaria-Otín, Charles Amory, Martin Ménégoz, Fanny Brun, Xavier Faïn, Xavier Fettweis, Mondher Chekki, Patrick Wagnon, Dibas Shrestha, and Arbindra Khadka
EGUsphere, https://doi.org/10.5194/egusphere-2026-4572, https://doi.org/10.5194/egusphere-2026-4572, 2026
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
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High Mountain Asia contains the largest concentration of glacier ice outside the polar regions and supplies water to hundreds of millions of people, yet its climate remains poorly understood because of its complex terrain and limited observations. We produced a high-resolution climate dataset for the Pamir and Central Himalaya covering 1950–2025. It captures seasonal climate and snow changes and will support studies of water resources, glaciers, and natural hazards.
Bjorn Backeberg, Jemma Johnson, Natalia Aleksandrova, Cornelis Slobbe, Fabio Mangini, Marcello Passaro, Sanne Muis, Pavel Ditmar, Antonio Bonaduce, Gundula Winter, and Michael Hart-Davis
EGUsphere, https://doi.org/10.5194/egusphere-2026-3916, https://doi.org/10.5194/egusphere-2026-3916, 2026
This preprint is open for discussion and under review for Natural Hazards and Earth System Sciences (NHESS).
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Coastal cities face growing flood risk from rising seas and storms. Scientists estimate dangerous water levels using satellite measurements of sea level and computer models of ocean behaviour, but the two are often combined inconsistently. We reviewed this research and found the real challenge is not merging the data, but making sure both methods measure the same thing, the same way. Solving this could lead to more reliable, consistent flood-risk estimates for coastal communities worldwide.
Christian Torres, Deniz Bozkurt, Vincent Favier, Victoire Buffet, Claudio Bravo, Xavier Fettweis, Thomas Dethinne, Antoine Rabatel, Maximiliano Viale, Sang-Jong Park, and Jorge Arigony-Neto
EGUsphere, https://doi.org/10.5194/egusphere-2026-3508, https://doi.org/10.5194/egusphere-2026-3508, 2026
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We investigated periods when unusually warm conditions in Patagonia occurred at the same time as precipitation events on the Antarctic Peninsula. By combining observations and simulations, we identified 127 such events between 1980 and 2022. These events increased ice melt in Patagonia while enhancing accumulation on the Antarctic Peninsula, highlighting how large-scale weather patterns can simultaneously affect ice-covered regions in different ways.
Marco Tedesco, Racheet Matai, and Xavier Fettweis
The Cryosphere, 20, 4235–4253, https://doi.org/10.5194/tc-20-4235-2026, https://doi.org/10.5194/tc-20-4235-2026, 2026
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We developed a machine learning emulator of a climate model simulating melting over Greenland that performs as well as the original model but it is much faster. We show that this emulator can be used as powerful tools to complement regional climate models by enabling computationally efficient ensemble simulations and physically interpretable attribution of past and future Greenland surface melt. Development of regional climate models should go hand in hand with ML-based tools.
Guillaume Timmermans, Brice Noël, Christoph Kittel, Thomas Dethinne, Nicolas Ghilain, and Xavier Fettweis
EGUsphere, https://doi.org/10.5194/egusphere-2026-2341, https://doi.org/10.5194/egusphere-2026-2341, 2026
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We assess how well a regional climate model reproduces changes in the mass of the Greenland Ice Sheet due to surface processes, an important driver of sea level rise. By comparing model results with observations, we show that high-resolution simulations closely match reality. Coarser simulations are less detailed near the edges but remain reliable overall. A resolution of 10 kilometers provides a good balance between accuracy and computing cost for long-term projections.
Ian Simpson, Edward Hanna, Ryan S. Williams, Linh Luu, Andrew Orr, Julie Jones, Xavier Fettweis, Jose Abraham Torres Alavez, Ole Bøssing Christensen, Ella Gilbert, Sid Gumber, Christoph Kittel, Sihan Li, Damien Maure, Ruth Mottram, Tony Phillips, Willem Jan van de Berg, and Kristiina Verro
EGUsphere, https://doi.org/10.5194/egusphere-2026-2270, https://doi.org/10.5194/egusphere-2026-2270, 2026
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The warming trend in global temperatures has potential to result in accelerated break up of the Antarctic ice shelves, which would contribute to rising sea levels. Here we present a novel database of Antarctic extreme weather events over a selection of the Antarctic ice shelves. We examine air temperature, precipitation, wind and surface pressure. In addition, we examine trends in the frequency of extreme events and the links with weather patterns around Antarctica.
Raf Antwerpen, Marco Tedesco, Pierre Gentine, Willem Jan van de Berg, and Xavier Fettweis
The Cryosphere, 20, 3131–3149, https://doi.org/10.5194/tc-20-3131-2026, https://doi.org/10.5194/tc-20-3131-2026, 2026
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We study why Greenland ice melts faster by improving how ice brightness is represented. This is important because it controls how much sunlight is absorbed by the ice. Using satellite data and a new transparent machine learning method trained with climate model information, we capture how the shape of the ice sheet, temperature, and meltwater change ice brightness. Our approach outperforms existing climate models and can reduce uncertainty in future sea level rise projections.
Jonathon R. Preece, Patrick Alexander, Thomas L. Mote, Gabriel J. Kooperman, Xavier Fettweis, and Marco Tedesco
The Cryosphere, 20, 2871–2894, https://doi.org/10.5194/tc-20-2871-2026, https://doi.org/10.5194/tc-20-2871-2026, 2026
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Surface melt of the Greenland Ice Sheet has increased dramatically since the turn of the century, aided by an increase in persistent atmospheric circulation patterns that promote anomalously warm conditions. Through modeling experiments, this study shows that surface mass loss would have been reduced by 62% relative to historical conditions if this shift in atmospheric circulation would have occurred under the lower average temperatures of a preindustrial climate.
Ian Castellanos, Martin Ménégoz, Juliette Blanchet, Julien Beaumet, Hubert Gallée, Eduardo Moreno-Chamarro, Chantal Staquet, and Xavier Fettweis
Earth Syst. Dynam., 17, 581–605, https://doi.org/10.5194/esd-17-581-2026, https://doi.org/10.5194/esd-17-581-2026, 2026
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The Alps host glaciers, distinct ecosystems, socio-economic interests and water resources that are being impacted by climate change. In this study, we aim at understanding how warming occurs in the Alps in projected scenarios and what physical processes drive it. We find under these scenarios that elevations around the snowline will warm faster than elsewhere, because snow retreats to higher elevations. Indeed, snow slows down warming due to its high albedo and the energy consumed to melt it.
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
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An ensemble of regional climate model simulations is used to estimate the 21st century change in precipitation on the Greenland ice sheet. For the end of the century, the change is in the range 40 to 170 Gt per year, depending on the emission scenario. Using annual values of 2 m air temperature and precipitation, we estimate an increase in precipitation of 35 Gt per year for every degree of warming.
Ella Gilbert, José Abraham Torres-Alavez, Marte G. Hofsteenge, Willem Jan van de Berg, Fredrik Boberg, Ole Bøssing Christensen, Christiaan Timo van Dalum, Xavier Fettweis, Siddharth Gumber, Nicolaj Hansen, Christoph Kittel, Clara Lambin, Damien Maure, Ruth Mottram, Martin Olesen, Andrew Orr, Tony Phillips, Maurice van Tiggelen, Kristiina Verro, and Priscilla A. Mooney
The Cryosphere, 20, 2629–2658, https://doi.org/10.5194/tc-20-2629-2026, https://doi.org/10.5194/tc-20-2629-2026, 2026
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Here we present a new dataset – the PolarRES ensemble – of four state-of-the-art regional climate models, which capture the full complexity of Antarctica's climate. The ensemble out-performs other available tools, advancing our ability to explore Antarctic climate. While it still has limitations, the PolarRES ensemble offers a novel and exciting way of evaluating climate processes and features, and we encourage researchers to use the data, which are freely available.
Audrey Goutard, Marion Réveillet, Fanny Brun, Delphine Six, Kevin Fourteau, Charles Amory, Xavier Fettweis, Mathieu Fructus, Arbindra Khadka, and Matthieu Lafaysse
The Cryosphere, 20, 2393–2416, https://doi.org/10.5194/tc-20-2393-2026, https://doi.org/10.5194/tc-20-2393-2026, 2026
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A new scheme has been developed in a snowpack model (SURFEX/ISBA-Crocus), to consider the impact of liquid water dynamics on bare ice, including albedo feedback and refreezing. When applied to the Mera Glacier in Nepal, the model reveals strong seasonal effects on the energy and mass balance, with increased melting in dry seasons and significant refreezing during the monsoon. This development improves mass balance modeling under increasing rainfall and bare ice exposure due to climate warming.
Fan Gao, Qiang Shen, Hansheng Wang, Tong Zhang, Liming Jiang, Yan Liu, C. K. Shum, Yan An, and Xu Zhang
The Cryosphere, 20, 1947–1965, https://doi.org/10.5194/tc-20-1947-2026, https://doi.org/10.5194/tc-20-1947-2026, 2026
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Basal ice-shelf melting critically impacts Antarctic ice sheet evolution. Our testing of two melting schemes showed starkly diverging projections despite near-identical initial states, especially for West Antarctica. By 2100, the predicted sea-level contributions differed by 57%. Initial setup changes hidden sub-ice properties (e.g., friction, temperature), modifying ice flow. Accurately representing melt and refining setup are thus essential to reduce projections uncertainty.
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
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We studied how the Antarctic ice sheet surface mass balance may change by 2100 using three high-resolution climate models forced by the same future climate scenario. While the models agree for present-day conditions, they project very different futures, especially over floating ice shelves. These differences mainly come from how melting, refreezing, and temperature are represented. Our results show that future sea level projections strongly depend on how well models simulate today’s climate.
Horst Machguth, Andrew Tedstone, Peter Kuipers Munneke, Max Brils, Brice Noël, Nicole Clerx, Nicolas Jullien, Xavier Fettweis, and Michiel van den Broeke
The Cryosphere, 20, 427–452, https://doi.org/10.5194/tc-20-427-2026, https://doi.org/10.5194/tc-20-427-2026, 2026
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Due to increasing air temperatures, surface melt expands to higher elevations on the Greenland ice sheet. This is visible on satellite imagery in the form of rivers of meltwater running across the surface of the ice sheet. We compare model results of meltwater at high elevations on the ice sheet to satellite observations. We find that each of the models shows strengths and weaknesses. A detailed look into the model results reveals potential reasons for the differences between models.
Chloë Marie Paice, Xavier Fettweis, and Philippe Huybrechts
The Cryosphere, 20, 309–332, https://doi.org/10.5194/tc-20-309-2026, https://doi.org/10.5194/tc-20-309-2026, 2026
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To study Greenland ice sheet–atmosphere interactions, we coupled an ice sheet model to a regional climate model and performed simulations of differing coupling complexity over 1000 years under a high-warming climate scenario. They reveal that at first melt at the ice sheet margin is reduced by changing wind patterns. But over time, as the ice sheet melts and its surface lowers, precipitation patterns and cloudiness also change and amplify ice mass loss over the entire ice sheet.
Heiko Goelzer, Constantijn J. Berends, Fredrik Boberg, Gael Durand, Tamsin L. Edwards, Xavier Fettweis, Fabien Gillet-Chaulet, Quentin Glaude, Philippe Huybrechts, Sébastien Le clec'h, Ruth Mottram, Brice Noël, Martin Olesen, Charlotte Rahlves, Jeremy Rohmer, Michiel van den Broeke, and Roderik S. W. van de Wal
The Cryosphere, 19, 6887–6906, https://doi.org/10.5194/tc-19-6887-2025, https://doi.org/10.5194/tc-19-6887-2025, 2025
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We present an ensemble of ice sheet model projections for the Greenland ice sheet. The focus is on providing projections that improve our understanding of the range future sea-level rise and the inherent uncertainties over the next 100 to 300 years. Compared to earlier work we more fully account for some of the uncertainties in sea-level projections. We include a wider range of climate model output, more climate change scenarios and we extend projections schematically up to year 2300.
Shengdao Wang, C. K. Shum, Michael Bevis, Xiaoxing He, Yu Zhang, Yihang Ding, Chaoyang Zhang, and Jean-Philippe Montillet
Earth Syst. Sci. Data, 17, 7055–7077, https://doi.org/10.5194/essd-17-7055-2025, https://doi.org/10.5194/essd-17-7055-2025, 2025
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Sea level rise is a major consequence of climate change, affecting the well-being of humankind. We combined long-term tide gauge records and satellite data to create a new global sea level record from 1950 to 2022. Our results reveal how natural climate patterns, including El Niño, La Niña, and the Pacific Decadal Oscillation, influence rapid present-day sea level change. The data product enhances understanding of climate–sea level interactions.
Thomas Dethinne, Nicolas Ghilain, Christoph Kittel, Benjamin Lecart, Xavier Fettweis, and François Jonard
EGUsphere, https://doi.org/10.5194/egusphere-2025-3907, https://doi.org/10.5194/egusphere-2025-3907, 2025
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This study replace standard vegetation input of a regional climate model with a satellite-based vegetation dataset to assess how vegetation influences climate during extreme events and to test the sensitivity of the model. The results show a non-linear sensitivity to vegetation, and using an observation-based vegetation input allows for a better representation of the extreme events, highlight the need for an advanced representation of vegetation in climate model to improve climate predictions.
Kristiina Verro, Cecilia Äijälä, Roberta Pirazzini, Ruzica Dadic, Damien Maure, Willem Jan van de Berg, Giacomo Traversa, Christiaan T. van Dalum, Petteri Uotila, Xavier Fettweis, Biagio Di Mauro, and Milla Johansson
The Cryosphere, 19, 4409–4436, https://doi.org/10.5194/tc-19-4409-2025, https://doi.org/10.5194/tc-19-4409-2025, 2025
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Accurately representing Antarctic sea ice is essential for reliable climate and ocean model predictions. We evaluated how different models simulate the sea ice's sunlight reflectivity (called albedo) using field and satellite data. Models with simple albedo schemes performed well in limited cases but missed key processes. The advanced scheme in the MetROMS-UHel ocean model provided the most accurate results, including observed day–night albedo changes observed during a field campaign.
Weiran Li, Stef Lhermitte, Bert Wouters, Cornelis Slobbe, Max Brils, and Xavier Fettweis
The Cryosphere, 19, 3419–3442, https://doi.org/10.5194/tc-19-3419-2025, https://doi.org/10.5194/tc-19-3419-2025, 2025
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Due to recurrent melt and refreezing events in recent decades, the snow conditions over Greenland have changed. To observe this, we use a parameter (leading edge width; LeW) derived from satellite altimetry and analyse its spatial and temporal variations. By comparing the LeW variations with modelled firn parameters, we concluded that the 2012 melt event and the recent and increasingly frequent melt events have a long-lasting impact on the volume scattering of Greenland firn.
Jean-François Grailet, Robin J. Hogan, Nicolas Ghilain, David Bolsée, Xavier Fettweis, and Marilaure Grégoire
Geosci. Model Dev., 18, 1965–1988, https://doi.org/10.5194/gmd-18-1965-2025, https://doi.org/10.5194/gmd-18-1965-2025, 2025
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The MAR (Modèle Régional Atmosphérique) is a regional climate model used for weather forecasting and studying the climate over various regions. This paper presents an update of MAR thanks to which it can precisely decompose solar radiation, in particular in the UV (ultraviolet) and photosynthesis ranges, both being critical to human health and ecosystems. As a first application of this new capability, this paper presents a method for predicting UV indices with MAR.
Ny Riana Randresihaja, Olivier Gourgue, Lauranne Alaerts, Xavier Fettweis, Jonathan Lambrechts, Miguel De Le Court, Marilaure Grégoire, and Emmanuel Hanert
EGUsphere, https://doi.org/10.5194/egusphere-2025-634, https://doi.org/10.5194/egusphere-2025-634, 2025
Preprint archived
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Coastal areas face rising flood threats as storms intensifies with climate change. With an advanced model of the Scheldt Estuary-North Sea, we studied how detailed atmospheric data must be to predict storm surge peaks in estuaries. We found that high-resolution atmospheric data gives the best results, and coarser data with same resolution as current global climate models give poorer results. We show that investing in localized, high-resolution atmospheric data can significantly improve results.
Sylvie Charbit, Christophe Dumas, Fabienne Maignan, Catherine Ottlé, Nina Raoult, Xavier Fettweis, and Philippe Conesa
The Cryosphere, 18, 5067–5099, https://doi.org/10.5194/tc-18-5067-2024, https://doi.org/10.5194/tc-18-5067-2024, 2024
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The evolution of the Greenland ice sheet is highly dependent on surface melting and therefore on the processes operating at the snow–atmosphere interface and within the snow cover. Here we present new developments to apply a snow model to the Greenland ice sheet. The performance of this model is analysed in terms of its ability to simulate ablation processes. Our analysis shows that the model performs well when compared with the MAR regional polar atmospheric model.
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.
Alison Delhasse, Johanna Beckmann, Christoph Kittel, and Xavier Fettweis
The Cryosphere, 18, 633–651, https://doi.org/10.5194/tc-18-633-2024, https://doi.org/10.5194/tc-18-633-2024, 2024
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Aiming to study the long-term influence of an extremely warm climate in the Greenland Ice Sheet contribution to sea level rise, a new regional atmosphere–ice sheet model setup was established. The coupling, explicitly considering the melt–elevation feedback, is compared to an offline method to consider this feedback. We highlight mitigation of the feedback due to local changes in atmospheric circulation with changes in surface topography, making the offline correction invalid on the margins.
Idunn Aamnes Mostue, Stefan Hofer, Trude Storelvmo, and Xavier Fettweis
The Cryosphere, 18, 475–488, https://doi.org/10.5194/tc-18-475-2024, https://doi.org/10.5194/tc-18-475-2024, 2024
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The latest generation of climate models (Coupled Model Intercomparison Project Phase 6 – CMIP6) warm more over Greenland and the Arctic and thus also project a larger mass loss from the Greenland Ice Sheet (GrIS) compared to the previous generation of climate models (CMIP5). Our work suggests for the first time that part of the greater mass loss in CMIP6 over the GrIS is driven by a difference in the surface mass balance sensitivity from a change in cloud representation in the CMIP6 models.
Laura J. Dietrich, Hans Christian Steen-Larsen, Sonja Wahl, Anne-Katrine Faber, and Xavier Fettweis
The Cryosphere, 18, 289–305, https://doi.org/10.5194/tc-18-289-2024, https://doi.org/10.5194/tc-18-289-2024, 2024
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The contribution of the humidity flux to the surface mass balance in the accumulation zone of the Greenland Ice Sheet is uncertain. Here, we evaluate the regional climate model MAR using a multi-annual dataset of eddy covariance measurements and bulk estimates of the humidity flux. The humidity flux largely contributes to the summer surface mass balance (SMB) in the accumulation zone, indicating its potential importance for the annual SMB in a warming climate.
Marco Tedesco, Paolo Colosio, Xavier Fettweis, and Guido Cervone
The Cryosphere, 17, 5061–5074, https://doi.org/10.5194/tc-17-5061-2023, https://doi.org/10.5194/tc-17-5061-2023, 2023
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We developed a technique to improve the outputs of a model that calculates the gain and loss of Greenland and consequently its contribution to sea level rise. Our technique generates “sharper” images of the maps generated by the model to better understand and quantify where losses occur. This has implications for improving models, understanding what drives the contributions of Greenland to sea level rise, and more.
Damien Maure, Christoph Kittel, Clara Lambin, Alison Delhasse, and Xavier Fettweis
The Cryosphere, 17, 4645–4659, https://doi.org/10.5194/tc-17-4645-2023, https://doi.org/10.5194/tc-17-4645-2023, 2023
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The Arctic is warming faster than the rest of the Earth. Studies have already shown that Greenland and the Canadian Arctic are experiencing a record increase in melting rates, while Svalbard has been relatively less impacted. Looking at those regions but also extending the study to Iceland and the Russian Arctic archipelagoes, we see a heterogeneity in the melting-rate response to the Arctic warming, with the Russian archipelagoes experiencing lower melting rates than other regions.
Prateek Gantayat, Alison F. Banwell, Amber A. Leeson, James M. Lea, Dorthe Petersen, Noel Gourmelen, and Xavier Fettweis
Geosci. Model Dev., 16, 5803–5823, https://doi.org/10.5194/gmd-16-5803-2023, https://doi.org/10.5194/gmd-16-5803-2023, 2023
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We developed a new supraglacial hydrology model for the Greenland Ice Sheet. This model simulates surface meltwater routing, meltwater drainage, supraglacial lake (SGL) overflow, and formation of lake ice. The model was able to reproduce 80 % of observed lake locations and provides a good match between the observed and modelled temporal evolution of SGLs.
Thomas Dethinne, Quentin Glaude, Ghislain Picard, Christoph Kittel, Patrick Alexander, Anne Orban, and Xavier Fettweis
The Cryosphere, 17, 4267–4288, https://doi.org/10.5194/tc-17-4267-2023, https://doi.org/10.5194/tc-17-4267-2023, 2023
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We investigate the sensitivity of the regional climate model
Modèle Atmosphérique Régional(MAR) to the assimilation of wet-snow occurrence estimated by remote sensing datasets. The assimilation is performed by nudging the MAR snowpack temperature. The data assimilation is performed over the Antarctic Peninsula for the 2019–2021 period. The results show an increase in the melt production (+66.7 %) and a decrease in surface mass balance (−4.5 %) of the model for the 2019–2020 melt season.
Inès N. Otosaka, Andrew Shepherd, Erik R. Ivins, Nicole-Jeanne Schlegel, Charles Amory, Michiel R. van den Broeke, Martin Horwath, Ian Joughin, Michalea D. King, Gerhard Krinner, Sophie Nowicki, Anthony J. Payne, Eric Rignot, Ted Scambos, Karen M. Simon, Benjamin E. Smith, Louise S. Sørensen, Isabella Velicogna, Pippa L. Whitehouse, Geruo A, Cécile Agosta, Andreas P. Ahlstrøm, Alejandro Blazquez, William Colgan, Marcus E. Engdahl, Xavier Fettweis, Rene Forsberg, Hubert Gallée, Alex Gardner, Lin Gilbert, Noel Gourmelen, Andreas Groh, Brian C. Gunter, Christopher Harig, Veit Helm, Shfaqat Abbas Khan, Christoph Kittel, Hannes Konrad, Peter L. Langen, Benoit S. Lecavalier, Chia-Chun Liang, Bryant D. Loomis, Malcolm McMillan, Daniele Melini, Sebastian H. Mernild, Ruth Mottram, Jeremie Mouginot, Johan Nilsson, Brice Noël, Mark E. Pattle, William R. Peltier, Nadege Pie, Mònica Roca, Ingo Sasgen, Himanshu V. Save, Ki-Weon Seo, Bernd Scheuchl, Ernst J. O. Schrama, Ludwig Schröder, Sebastian B. Simonsen, Thomas Slater, Giorgio Spada, Tyler C. Sutterley, Bramha Dutt Vishwakarma, Jan Melchior van Wessem, David Wiese, Wouter van der Wal, and Bert Wouters
Earth Syst. Sci. Data, 15, 1597–1616, https://doi.org/10.5194/essd-15-1597-2023, https://doi.org/10.5194/essd-15-1597-2023, 2023
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By measuring changes in the volume, gravitational attraction, and ice flow of Greenland and Antarctica from space, we can monitor their mass gain and loss over time. Here, we present a new record of the Earth’s polar ice sheet mass balance produced by aggregating 50 satellite-based estimates of ice sheet mass change. This new assessment shows that the ice sheets have lost (7.5 x 1012) t of ice between 1992 and 2020, contributing 21 mm to sea level rise.
Benjamin E. Smith, Brooke Medley, Xavier Fettweis, Tyler Sutterley, Patrick Alexander, David Porter, and Marco Tedesco
The Cryosphere, 17, 789–808, https://doi.org/10.5194/tc-17-789-2023, https://doi.org/10.5194/tc-17-789-2023, 2023
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We use repeated satellite measurements of the height of the Greenland ice sheet to learn about how three computational models of snowfall, melt, and snow compaction represent actual changes in the ice sheet. We find that the models do a good job of estimating how the parts of the ice sheet near the coast have changed but that two of the models have trouble representing surface melt for the highest part of the ice sheet. This work provides suggestions for how to better model snowmelt.
Jilu Li, Fernando Rodriguez-Morales, Xavier Fettweis, Oluwanisola Ibikunle, Carl Leuschen, John Paden, Daniel Gomez-Garcia, and Emily Arnold
The Cryosphere, 17, 175–193, https://doi.org/10.5194/tc-17-175-2023, https://doi.org/10.5194/tc-17-175-2023, 2023
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Alaskan glaciers' loss of ice mass contributes significantly to ocean surface rise. It is important to know how deeply and how much snow accumulates on these glaciers to comprehend and analyze the glacial mass loss process. We reported the observed seasonal snow depth distribution from our radar data taken in Alaska in 2018 and 2021, developed a method to estimate the annual snow accumulation rate at Mt. Wrangell caldera, and identified transition zones from wet-snow zones to ablation zones.
Raf M. Antwerpen, Marco Tedesco, Xavier Fettweis, Patrick Alexander, and Willem Jan van de Berg
The Cryosphere, 16, 4185–4199, https://doi.org/10.5194/tc-16-4185-2022, https://doi.org/10.5194/tc-16-4185-2022, 2022
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The ice on Greenland has been melting more rapidly over the last few years. Most of this melt comes from the exposure of ice when the overlying snow melts. This ice is darker than snow and absorbs more sunlight, leading to more melt. It remains challenging to accurately simulate the brightness of the ice. We show that the color of ice simulated by Modèle Atmosphérique Régional (MAR) is too bright. We then show that this means that MAR may underestimate how fast the Greenland ice is melting.
Christoph Kittel, Charles Amory, Stefan Hofer, Cécile Agosta, Nicolas C. Jourdain, Ella Gilbert, Louis Le Toumelin, Étienne Vignon, Hubert Gallée, and Xavier Fettweis
The Cryosphere, 16, 2655–2669, https://doi.org/10.5194/tc-16-2655-2022, https://doi.org/10.5194/tc-16-2655-2022, 2022
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Model projections suggest large differences in future Antarctic surface melting even for similar greenhouse gas scenarios and warming rates. We show that clouds containing a larger amount of liquid water lead to stronger melt. As surface melt can trigger the collapse of the ice shelves (the safety band of the Antarctic Ice Sheet), clouds could be a major source of uncertainties in projections of sea level rise.
Sébastien Doutreloup, Xavier Fettweis, Ramin Rahif, Essam Elnagar, Mohsen S. Pourkiaei, Deepak Amaripadath, and Shady Attia
Earth Syst. Sci. Data, 14, 3039–3051, https://doi.org/10.5194/essd-14-3039-2022, https://doi.org/10.5194/essd-14-3039-2022, 2022
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This data set provides historical (1980–2014) and future (2015–2100) weather data for 12 cities in Belgium. This data set is intended for architects or building or energy designers. In particular, it makes available to all users hourly open-access weather data according to certain standards to recreate a Typical and an Extreme Meteorological Year. In addition, it provides hourly data on heatwaves from 1980 to 2100. Weather data were produced from the outputs of the MAR model simulations.
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Short summary
The Gravity Recovery And Climate Experiment (GRACE) mission has greatly improved our understanding of changes in Earth's gravity field over time. A novel mass concentration (mascon) dataset, GCL-Mascon2024, was determined by leveraging the short-arc approach, advanced spatial constraints, a frequency-dependent noise processing strategy, and parameterization-integrating natural boundaries, aiming to enhance accuracy for monitoring mass transportation on Earth.
The Gravity Recovery And Climate Experiment (GRACE) mission has greatly improved our...
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