Articles | Volume 20, issue 5
https://doi.org/10.5194/tc-20-2871-2026
© 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-20-2871-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
21 May 2026
Research article |
| 21 May 2026
| 21 May 2026
Estimating the thermodynamic contribution of post-industrial warming to recent Greenland ice sheet surface mass loss
Jonathon R. Preece
CORRESPONDING AUTHOR
Department of Geography, University of Georgia, Athens, 30602, USA
Patrick Alexander
Lamont-Doherty Earth Observatory, Columbia University, Palisades, 10964, USA
NASA Goddard Institute for Space Studies, New York, 10025, USA
Thomas L. Mote
Department of Geography, University of Georgia, Athens, 30602, USA
Gabriel J. Kooperman
Department of Geography, University of Georgia, Athens, 30602, USA
Xavier Fettweis
Laboratory of Climatology, Department of Geography, SPHERES research unit, University of Liège, Liège, Belgium
Marco Tedesco
Lamont-Doherty Earth Observatory, Columbia University, Palisades, 10964, USA
NASA Goddard Institute for Space Studies, New York, 10025, USA
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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.
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.
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.
Raf Antwerpen, Marco Tedesco, Pierre Gentine, Willem Jan van de Berg, and Xavier Fettweis
EGUsphere, https://doi.org/10.5194/egusphere-2025-6143, https://doi.org/10.5194/egusphere-2025-6143, 2026
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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.
Marco Tedesco, Racheet Matai, and Xavier Fettweis
EGUsphere, https://doi.org/10.5194/egusphere-2026-490, https://doi.org/10.5194/egusphere-2026-490, 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.
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.
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.
Zhengwen Yan, Jiangjun Ran, Pavel Ditmar, C. K. Shum, Roland Klees, Patrick Smith, and Xavier Fettweis
Earth Syst. Sci. Data, 17, 4253–4275, https://doi.org/10.5194/essd-17-4253-2025, https://doi.org/10.5194/essd-17-4253-2025, 2025
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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.
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
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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.
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.
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.
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.
Wenwen Li, Chia-Yu Hsu, and Marco Tedesco
EGUsphere, https://doi.org/10.5194/egusphere-2023-2831, https://doi.org/10.5194/egusphere-2023-2831, 2024
Preprint withdrawn
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This review paper fills a knowledge gap in comprehensive literature review at the junction of AI-Arctic sea ice research. We provide a fine-grained review of AI applications in a variety of sea ice research domains. Based on these analyses, we point out exciting opportunities where the Arctic sea ice community can continue benefiting from cutting-edge AI. These future research directions will foster the continuous growth of the Arctic sea ice–AI research community.
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.
Benjamin James Washington, Lynne Seymour, and Thomas L. Mote
Adv. Stat. Clim. Meteorol. Oceanogr., 9, 1–28, https://doi.org/10.5194/ascmo-9-1-2023, https://doi.org/10.5194/ascmo-9-1-2023, 2023
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We develop new methodology to statistically model known bias in general atmospheric circulation models. We focus on Puerto Rico specifically because of other important ongoing and long-term ecological and environmental research taking place there. Our methods work even in the presence of Puerto Rico's broken climate record. With our methods, we find that climate change will not only favor a warmer and wetter climate in Puerto Rico, but also increase the frequency of extreme rainfall events.
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.
Kenneth D. Mankoff, Xavier Fettweis, Peter L. Langen, Martin Stendel, Kristian K. Kjeldsen, Nanna B. Karlsson, Brice Noël, Michiel R. van den Broeke, Anne Solgaard, William Colgan, Jason E. Box, Sebastian B. Simonsen, Michalea D. King, Andreas P. Ahlstrøm, Signe Bech Andersen, and Robert S. Fausto
Earth Syst. Sci. Data, 13, 5001–5025, https://doi.org/10.5194/essd-13-5001-2021, https://doi.org/10.5194/essd-13-5001-2021, 2021
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We estimate the daily mass balance and its components (surface, marine, and basal mass balance) for the Greenland ice sheet. Our time series begins in 1840 and has annual resolution through 1985 and then daily from 1986 through next week. Results are operational (updated daily) and provided for the entire ice sheet or by commonly used regions or sectors. This is the first input–output mass balance estimate to include the basal mass balance.
Ruth Mottram, Nicolaj Hansen, Christoph Kittel, J. Melchior van Wessem, Cécile Agosta, Charles Amory, Fredrik Boberg, Willem Jan van de Berg, Xavier Fettweis, Alexandra Gossart, Nicole P. M. van Lipzig, Erik van Meijgaard, Andrew Orr, Tony Phillips, Stuart Webster, Sebastian B. Simonsen, and Niels Souverijns
The Cryosphere, 15, 3751–3784, https://doi.org/10.5194/tc-15-3751-2021, https://doi.org/10.5194/tc-15-3751-2021, 2021
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We compare the calculated surface mass budget (SMB) of Antarctica in five different regional climate models. On average ~ 2000 Gt of snow accumulates annually, but different models vary by ~ 10 %, a difference equivalent to ± 0.5 mm of global sea level rise. All models reproduce observed weather, but there are large differences in regional patterns of snowfall, especially in areas with very few observations, giving greater uncertainty in Antarctic mass budget than previously identified.
Louis Le Toumelin, Charles Amory, Vincent Favier, Christoph Kittel, Stefan Hofer, Xavier Fettweis, Hubert Gallée, and Vinay Kayetha
The Cryosphere, 15, 3595–3614, https://doi.org/10.5194/tc-15-3595-2021, https://doi.org/10.5194/tc-15-3595-2021, 2021
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Snow is frequently eroded from the surface by the wind in Adelie Land (Antarctica) and suspended in the lower atmosphere. By performing model simulations, we show firstly that suspended snow layers interact with incoming radiation similarly to a near-surface cloud. Secondly, suspended snow modifies the atmosphere's thermodynamic structure and energy exchanges with the surface. Our results suggest snow transport by the wind should be taken into account in future model studies over the region.
Xavier Fettweis, Stefan Hofer, Roland Séférian, Charles Amory, Alison Delhasse, Sébastien Doutreloup, Christoph Kittel, Charlotte Lang, Joris Van Bever, Florent Veillon, and Peter Irvine
The Cryosphere, 15, 3013–3019, https://doi.org/10.5194/tc-15-3013-2021, https://doi.org/10.5194/tc-15-3013-2021, 2021
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Without any reduction in our greenhouse gas emissions, the Greenland ice sheet surface mass loss can be brought in line with a medium-mitigation emissions scenario by reducing the solar downward flux at the top of the atmosphere by 1.5 %. In addition to reducing global warming, these solar geoengineering measures also dampen the well-known positive melt–albedo feedback over the ice sheet by 6 %. However, only stronger reductions in solar radiation could maintain a stable ice sheet in 2100.
Paolo Colosio, Marco Tedesco, Roberto Ranzi, and Xavier Fettweis
The Cryosphere, 15, 2623–2646, https://doi.org/10.5194/tc-15-2623-2021, https://doi.org/10.5194/tc-15-2623-2021, 2021
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We use a new satellite dataset to study the spatiotemporal evolution of surface melting over Greenland at an enhanced resolution of 3.125 km. Using meteorological data and the MAR model, we observe that a dynamic algorithm can best detect surface melting. We found that the melting season is elongating, the melt extent is increasing and that high-resolution data better describe the spatiotemporal evolution of the melting season, which is crucial to improve estimates of sea level rise.
Charles Amory, Christoph Kittel, Louis Le Toumelin, Cécile Agosta, Alison Delhasse, Vincent Favier, and Xavier Fettweis
Geosci. Model Dev., 14, 3487–3510, https://doi.org/10.5194/gmd-14-3487-2021, https://doi.org/10.5194/gmd-14-3487-2021, 2021
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This paper presents recent developments in the drifting-snow scheme of the regional climate model MAR and its application to simulate drifting snow and the surface mass balance of Adélie Land in East Antarctica. The model is extensively described and evaluated against a multi-year drifting-snow dataset and surface mass balance estimates available in the area. The model sensitivity to input parameters and improvements over a previously published version are also assessed.
Cited articles
Amory, C., Kittel, C., Le Toumelin, L., Agosta, C., Delhasse, A., Favier, V., and Fettweis, X.: Performance of MAR (v3.11) in simulating the drifting-snow climate and surface mass balance of Adélie Land, East Antarctica, Geosci. Model Dev., 14, 3487–3510, https://doi.org/10.5194/gmd-14-3487-2021, 2021.
Andersen, M. L., Nettles, M., Elosegui, P., Larsen, T. B., Hamilton, G. S., and Stearns, L. A.: Quantitative estimates of velocity sensitivity to surface melt variations at a large Greenland outlet glacier, J. Glaciol., 57, 609–620, https://doi.org/10.3189/002214311797409785, 2011.
Bailey, H. and Hubbard, A.: Snow Mass Recharge of the Greenland Ice Sheet Fueled by Intense Atmospheric River, Geophys. Res. Lett., 52, e2024GL110121, https://doi.org/10.1029/2024GL110121, 2025.
Ballinger, T. J., Hanna, E., Hall, R. J., Miller, J., Ribergaard, M. H., and Høyer, J. L.: Greenland coastal air temperatures linked to Baffin Bay and Greenland Sea ice conditions during autumn through regional blocking patterns, Clim. Dynam., 50, 83–100, https://doi.org/10.1007/s00382-017-3583-3, 2018.
Ballinger, T. J., Mote, T. L., Mattingly, K., Bliss, A. C., Hanna, E., van As, D., Prieto, M., Gharehchahi, S., Fettweis, X., Noël, B., Smeets, P. C. J. P., Reijmer, C. H., Ribergaard, M. H., and Cappelen, J.: Greenland Ice Sheet late-season melt: investigating multiscale drivers of K-transect events, The Cryosphere, 13, 2241–2257, https://doi.org/10.5194/tc-13-2241-2019, 2019.
Bennartz, R., Shupe, M. D., Turner, D. D., Walden, V. P., Steffen, K., Cox, C. J., Kulie, M. S., Miller, N. B., and Pettersen, C.: July 2012 Greenland melt extent enhanced by low-level liquid clouds, Nature, 496, 83–86, https://doi.org/10.1038/nature12002, 2013.
Bevis, M., Harig, C., Khan, S. A., Brown, A., Simons, F. J., Willis, M., Fettweis, X., Broeke, M. R. van den, Madsen, F. B., Kendrick, E., Caccamise, D. J., Dam, T. van, Knudsen, P., and Nylen, T.: Accelerating changes in ice mass within Greenland, and the ice sheet's sensitivity to atmospheric forcing, P. Natl. Acad. Sci. USA, 116, 1934–1939, https://doi.org/10.1073/pnas.1806562116, 2019.
Boers, N. and Rypdal, M.: Critical slowing down suggests that the western Greenland Ice Sheet is close to a tipping point, P. Natl. Acad. Sci. USA, 118, e2024192118, https://doi.org/10.1073/pnas.2024192118, 2021.
Bonsoms, J., González-Herrero, S., Fettweis, X., Lemus-Cánovas, M., Oliva, M., and López-Moreno, J. I.: Record-breaking Greenland ice sheet melt events under recent and future climate, Nat. Commun., 17, 3605, https://doi.org/10.1038/s41467-026-69543-5, 2026.
Box, J. E., Cressie, N., Bromwich, D. H., Jung, J.-H., van den Broeke, M., Van Angelen, J. H., Forster, R. R., Miège, C., Mosley-Thompson, E., Vinther, B., and McConnell, J. R.: Greenland Ice Sheet Mass Balance Reconstruction. Part I: Net Snow Accumulation (1600–2009), J. Climate, 26, 3919–3934, https://doi.org/10.1175/JCLI-D-12-00373.1, 2013.
Box, J. E., Wehrlé, A., van As, D., Fausto, R. S., Kjeldsen, K. K., Dachauer, A., Ahlstrøm, A. P., and Picard, G.: Greenland Ice Sheet Rainfall, Heat and Albedo Feedback Impacts From the Mid-August 2021 Atmospheric River, Geophys. Res. Lett., 49, e2021GL097356, https://doi.org/10.1029/2021GL097356, 2022.
Box, J. E., Nielsen, K. P., Yang, X., Niwano, M., Wehrlé, A., van As, D., Fettweis, X., Køltzow, M. A. Ø., Palmason, B., Fausto, R. S., van den Broeke, M. R., Huai, B., Ahlstrøm, A. P., Langley, K., Dachauer, A., and Noël, B.: Greenland ice sheet rainfall climatology, extremes and atmospheric river rapids, Meteorol. Appl., 30, e2134, https://doi.org/10.1002/met.2134, 2023.
Bromwich, D. H., Cullather, R. I., Chen, Q., and Csathó, B. M.: Evaluation of recent precipitation studies for Greenland Ice Sheet, J. Geophys. Res.-Atmos., 103, 26007–26024, https://doi.org/10.1029/98JD02278, 1998.
Brun, E., Martin, E., Simon, V., Gendre, C., and Coléou, C.: An Energy and Mass Model of Snow Cover Suitable for Operational Avalanche Forecasting, J. Glaciol., 35, 333, https://doi.org/10.1017/S0022143000009254, 1989.
Brun, E., David, P., Sudul, M., and Brunot, G.: A numerical model to simulate snow-cover stratigraphy for operational avalanche forecasting, J. Glaciol., 38, 13–22, https://doi.org/10.3189/S0022143000009552, 1992.
Caesar, L., Rahmstorf, S., Robinson, A., Feulner, G., and Saba, V.: Observed fingerprint of a weakening Atlantic Ocean overturning circulation, Nature, 556, 191–196, https://doi.org/10.1038/s41586-018-0006-5, 2018.
Cattiaux, J., Peings, Y., Saint-Martin, D., Trou-Kechout, N., and Vavrus, S. J.: Sinuosity of midlatitude atmospheric flow in a warming world, Geophys. Res. Lett., 43, 8259–8268, https://doi.org/10.1002/2016GL070309, 2016.
Cazenave, A., Palanisamy, H., and Ablain, M.: Contemporary sea level changes from satellite altimetry: What have we learned? What are the new challenges?, Adv. Space Res., 62, 1639–1653, https://doi.org/10.1016/j.asr.2018.07.017, 2018.
Chu, V. W.: Greenland ice sheet hydrology: A review, Prog. Phys. Geogr.: Earth and Environment, 38, 19–54, https://doi.org/10.1177/0309133313507075, 2014.
Chung, E., Ha, K., Timmermann, A., Stuecker, M. F., Bodai, T., and Lee, S.: Cold-Season Arctic Amplification Driven by Arctic Ocean-Mediated Seasonal Energy Transfer, Earth's Future, 9, https://doi.org/10.1029/2020ef001898, 2021.
Clausen, H. B., Gundestrup, N. S., Johnsen, S. J., Bindschadler, R., and Zwally, J.: Glaciological Investigations in the Crête Area, Central Greenland: A Search for a new Deep-Drilling Site, Ann. Glaciol., 10, 10–15, https://doi.org/10.3189/S0260305500004080, 1988.
Cohen, J., Screen, J. A., Furtado, J. C., Barlow, M., Whittleston, D., Coumou, D., Francis, J., Dethloff, K., Entekhabi, D., Overland, J., and Jones, J.: Recent Arctic amplification and extreme mid-latitude weather, Nat. Geosci., 7, 627–637, https://doi.org/10.1038/ngeo2234, 2014.
Copernicus Climate Change Service: ERA5 hourly data on pressure levels from 1940 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set], https://doi.org/10.24381/CDS.BD0915C6, 2018.
Coumou, D., Lehmann, J., and Beckmann, J.: The weakening summer circulation in the Northern Hemisphere mid-latitudes, Science, 348, 324–327, https://doi.org/10.1126/science.1261768, 2015.
Coumou, D., Di Capua, G., Vavrus, S., Wang, L., and Wang, S.: The influence of Arctic amplification on mid-latitude summer circulation, Nat. Commun., 9, 2959, https://doi.org/10.1038/s41467-018-05256-8, 2018.
Cullather, R. I., Andrews, L. C., Croteau, M. J., Digirolamo, N. E., Hall, D. K., Lim, Y.-K., Loomis, B. D., Shuman, C. A., and Nowicki, S. M. J.: Anomalous Circulation in July 2019 Resulting in Mass Loss on the Greenland Ice Sheet, Geophys. Res. Lett., 47, e2020GL087263, https://doi.org/10.1029/2020GL087263, 2020.
Davini, P. and D'Andrea, F.: From CMIP3 to CMIP6: Northern Hemisphere Atmospheric Blocking Simulation in Present and Future Climate, J. Climate, 33, 10021–10038, https://doi.org/10.1175/JCLI-D-19-0862.1, 2020.
Delhasse, A., Fettweis, X., Kittel, C., Amory, C., and Agosta, C.: Brief communication: Impact of the recent atmospheric circulation change in summer on the future surface mass balance of the Greenland Ice Sheet, The Cryosphere, 12, 3409–3418, https://doi.org/10.5194/tc-12-3409-2018, 2018.
Delhasse, A., Hanna, E., Kittel, C., and Fettweis, X.: Brief communication: CMIP6 does not suggest any atmospheric blocking increase in summer over Greenland by 2100, Int. J. Climatol., 41, 2589–2596, https://doi.org/10.1002/joc.6977, 2021.
Di Capua, G. and Coumou, D.: Changes in meandering of the Northern Hemisphere circulation, Environ. Res. Lett., 11, 094028, https://doi.org/10.1088/1748-9326/11/9/094028, 2016.
Fausto, R. S., van As, D., Box, J. E., Colgan, W., and Langen, P. L.: Quantifying the Surface Energy Fluxes in South Greenland during the 2012 High Melt Episodes Using In-situ Observations, Front. Earth Sci., 4, https://doi.org/10.3389/feart.2016.00082, 2016a.
Fausto, R. S., van As, D., Box, J. E., Colgan, W., Langen, P. L., and Mottram, R. H.: The implication of nonradiative energy fluxes dominating Greenland ice sheet exceptional ablation area surface melt in 2012, Geophys. Res. Lett., 43, 2649–2658, https://doi.org/10.1002/2016GL067720, 2016b.
Fettweis, X., Gallée, H., Lefebre, F., and van Ypersele, J.-P.: Greenland surface mass balance simulated by a regional climate model and comparison with satellite-derived data in 1990–1991, Clim. Dynam., 24, 623–640, https://doi.org/10.1007/s00382-005-0010-y, 2005.
Fettweis, X., Hanna, E., Lang, C., Belleflamme, A., Erpicum, M., and Gallée, H.: Brief communication “Important role of the mid-tropospheric atmospheric circulation in the recent surface melt increase over the Greenland ice sheet”, The Cryosphere, 7, 241–248, https://doi.org/10.5194/tc-7-241-2013, 2013.
Fettweis, X., Box, J. E., Agosta, C., Amory, C., Kittel, C., Lang, C., van As, D., Machguth, H., and Gallée, H.: Reconstructions of the 1900–2015 Greenland ice sheet surface mass balance using the regional climate MAR model, The Cryosphere, 11, 1015–1033, https://doi.org/10.5194/tc-11-1015-2017, 2017.
Fettweis, X., Hofer, S., Krebs-Kanzow, U., Amory, C., Aoki, T., Berends, C. J., Born, A., Box, J. E., Delhasse, A., Fujita, K., Gierz, P., Goelzer, H., Hanna, E., Hashimoto, A., Huybrechts, P., Kapsch, M.-L., King, M. D., Kittel, C., Lang, C., Langen, P. L., Lenaerts, J. T. M., Liston, G. E., Lohmann, G., Mernild, S. H., Mikolajewicz, U., Modali, K., Mottram, R. H., Niwano, M., Noël, B., Ryan, J. C., Smith, A., Streffing, J., Tedesco, M., van de Berg, W. J., van den Broeke, M., van de Wal, R. S. W., van Kampenhout, L., Wilton, D., Wouters, B., Ziemen, F., and Zolles, T.: GrSMBMIP: intercomparison of the modelled 1980–2012 surface mass balance over the Greenland Ice Sheet, The Cryosphere, 14, 3935–3958, https://doi.org/10.5194/tc-14-3935-2020, 2020.
Francis, J. A. and Vavrus, S. J.: Evidence linking Arctic amplification to extreme weather in mid-latitudes: ARCTIC LINKS TO MID-LATITUDE WEATHER, Geophys. Res. Lett., 39, L06801, https://doi.org/10.1029/2012GL051000, 2012.
Gallagher, M. R., Shupe, M. D., and Miller, N. B.: Impact of Atmospheric Circulation on Temperature, Clouds, and Radiation at Summit Station, Greenland, with Self-Organizing Maps, J. Climate, 31, 8895–8915, https://doi.org/10.1175/JCLI-D-17-0893.1, 2018.
Glaude, Q., Noel, B., Olesen, M., van den Broeke, M., Van De Berg, W. J., Mottram, R., Hansen, N., Delhasse, A., Amory, C., Kittel, C., Goelzer, H., and Fettweis, X.: A Factor Two Difference in 21st-Century Greenland Ice Sheet Surface Mass Balance Projections From Three Regional Climate Models Under a Strong Warming Scenario (SSP5-8.5), Geophys. Res. Lett., 51, e2024GL111902, https://doi.org/10.1029/2024GL111902, 2024.
Gorter, W., van Angelen, J. H., Lenaerts, J. T. M., and van den Broeke, M. R.: Present and future near-surface wind climate of Greenland from high resolution regional climate modelling, Clim. Dynam., 42, 1595–1611, https://doi.org/10.1007/s00382-013-1861-2, 2014.
Gutmann, E. D., Rasmussen, R. M., Liu, C., Ikeda, K., Bruyere, C. L., Done, J. M., Garrè, L., Friis-Hansen, P., and Veldore, V.: Changes in Hurricanes from a 13-Yr Convection-Permitting Pseudo–Global Warming Simulation, J. Climate, 31, 3643–3657, https://doi.org/10.1175/JCLI-D-17-0391.1, 2018.
Hanna, E., Jónsson, T., Ólafsson, J., and Valdimarsson, H.: Icelandic Coastal Sea Surface Temperature Records Constructed: Putting the Pulse on Air–Sea–Climate Interactions in the Northern North Atlantic. Part I: Comparison with HadISST1 Open-Ocean Surface Temperatures and Preliminary Analysis of Long-Term Patterns and Anomalies of SSTs around Iceland, J. Climate, 19, 5652–5666, https://doi.org/10.1175/JCLI3933.1, 2006.
Hanna, E., Huybrechts, P., Steffen, K., Cappelen, J., Huff, R., Shuman, C., Irvine-Fynn, T., Wise, S., and Griffiths, M.: Increased Runoff from Melt from the Greenland Ice Sheet: A Response to Global Warming, J. Climate, 21, 331–341, https://doi.org/10.1175/2007JCLI1964.1, 2008.
Hanna, E., Cappelen, J., Fettweis, X., Huybrechts, P., Luckman, A., and Ribergaard, M. H.: Hydrologic response of the Greenland ice sheet: the role of oceanographic warming, Hydrol. Process., 23, 7–30, https://doi.org/10.1002/hyp.7090, 2009.
Hanna, E., Jones, J. M., Cappelen, J., Mernild, S. H., Wood, L., Steffen, K., and Huybrechts, P.: The influence of North Atlantic atmospheric and oceanic forcing effects on 1900-2010 Greenland summer climate and ice melt/runoff, Int. J. Climatol., 33, 862–880, https://doi.org/10.1002/joc.3475, 2013.
Hanna, E., Fettweis, X., Mernild, S. H., Cappelen, J., Ribergaard, M. H., Shuman, C. A., Steffen, K., Wood, L., and Mote, T. L.: Atmospheric and oceanic climate forcing of the exceptional Greenland ice sheet surface melt in summer 2012, Int. J. Climatol., 34, 1022–1037, https://doi.org/10.1002/joc.3743, 2014.
Hanna, E., Cropper, T. E., Jones, P. D., Scaife, A. A., and Allan, R.: Recent seasonal asymmetric changes in the NAO (a marked summer decline and increased winter variability) and associated changes in the AO and Greenland Blocking Index, Int. J. Climatol., 35, 2540–2554, https://doi.org/10.1002/joc.4157, 2015.
Hanna, E., Cropper, T. E., Hall, R. J., and Cappelen, J.: Greenland Blocking Index 1851-2015: a regional climate change signal: Greenland Blocking Index 1851-2015, Int. J. Climatol., 36, 4847–4861, https://doi.org/10.1002/joc.4673, 2016.
Hanna, E., Fettweis, X., and Hall, R. J.: Brief communication: Recent changes in summer Greenland blocking captured by none of the CMIP5 models, The Cryosphere, 12, 3287–3292, https://doi.org/10.5194/tc-12-3287-2018, 2018a.
Hanna, E., Hall, R. J., Cropper, T. E., Ballinger, T. J., Wake, L., Mote, T., and Cappelen, J.: Greenland blocking index daily series 1851–2015: Analysis of changes in extremes and links with North Atlantic and UK climate variability and change, Int. J. Climatol., 38, 3546–3564, https://doi.org/10.1002/joc.5516, 2018b.
Hanna, E., Cappelen, J., Fettweis, X., Mernild, S. H., Mote, T. L., Mottram, R., Steffen, K., Ballinger, T. J., and Hall, R. J.: Greenland surface air temperature changes from 1981 to 2019 and implications for ice-sheet melt and mass-balance change, Int. J. Climatol., 41, E1336–E1352, https://doi.org/10.1002/joc.6771, 2021.
Hanna, E., Cropper, T. E., Hall, R. J., Cornes, R. C., and Barriendos, M.: Extended North Atlantic Oscillation and Greenland Blocking Indices 1800–2020 from New Meteorological Reanalysis, Atmosphere, 13, 436, https://doi.org/10.3390/atmos13030436, 2022.
Hanna, E., Topál, D., Box, J. E., Buzzard, S., Christie, F. D. W., Hvidberg, C., Morlighem, M., De Santis, L., Silvano, A., Colleoni, F., Sasgen, I., Banwell, A. F., van den Broeke, M. R., DeConto, R., De Rydt, J., Goelzer, H., Gossart, A., Gudmundsson, G. H., Lindbäck, K., Miles, B., Mottram, R., Pattyn, F., Reese, R., Rignot, E., Srivastava, A., Sun, S., Toller, J., Tuckett, P. A., and Ultee, L.: Short- and long-term variability of the Antarctic and Greenland ice sheets, Nat. Rev. Earth Environ., 5, 193–210, https://doi.org/10.1038/s43017-023-00509-7, 2024.
Henderson, G. R., Barrett, B. S., Wachowicz, L. J., Mattingly, K. S., Preece, J. R., and Mote, T. L.: Local and Remote Atmospheric Circulation Drivers of Arctic Change: A Review, Front. Earth Sci., 9, https://doi.org/10.3389/feart.2021.709896, 2021.
Hermann, M., Papritz, L., and Wernli, H.: A Lagrangian analysis of the dynamical and thermodynamic drivers of large-scale Greenland melt events during 1979–2017, Weather Clim. Dynam., 1, 497–518, https://doi.org/10.5194/wcd-1-497-2020, 2020.
Hofer, S., Tedstone, A. J., Fettweis, X., and Bamber, J. L.: Decreasing cloud cover drives the recent mass loss on the Greenland Ice Sheet, Sci. Adv., 3, e1700584, https://doi.org/10.1126/sciadv.1700584, 2017.
Horwath, M., Gutknecht, B. D., Cazenave, A., Palanisamy, H. K., Marti, F., Marzeion, B., Paul, F., Le Bris, R., Hogg, A. E., Otosaka, I., Shepherd, A., Döll, P., Cáceres, D., Müller Schmied, H., Johannessen, J. A., Nilsen, J. E. Ø., Raj, R. P., Forsberg, R., Sandberg Sørensen, L., Barletta, V. R., Simonsen, S. B., Knudsen, P., Andersen, O. B., Ranndal, H., Rose, S. K., Merchant, C. J., Macintosh, C. R., von Schuckmann, K., Novotny, K., Groh, A., Restano, M., and Benveniste, J.: Global sea-level budget and ocean-mass budget, with a focus on advanced data products and uncertainty characterisation, Earth Syst. Sci. Data, 14, 411–447, https://doi.org/10.5194/essd-14-411-2022, 2022.
Hurrell, J. W., Hack, J. J., Shea, D., Caron, J. M., and Rosinski, J.: A New Sea Surface Temperature and Sea Ice Boundary Dataset for the Community Atmosphere Model, J. Climate, 21, 5145–5153, https://doi.org/10.1175/2008JCLI2292.1, 2008.
Hurrell, J. W., Phillips, A., and Shea, D.: Merged Hadley-OI sea surface temperature and sea ice concentration data set, Zenodo [data set], https://doi.org/10.5065/R33V-SV91, 2020.
Kawase, H., Yoshikane, T., Hara, M., Ailikun, B., Kimura, F., and Yasunari, T.: Downscaling of the Climatic Change in the Mei-yu Rainband in East Asia by a Pseudo Climate Simulation Method, SOLA, 4, 73–76, https://doi.org/10.2151/sola.2008-019, 2008.
Kay, J., Deser, C., Phillips, A., and Simpson, I.: CESM1 Large Ensemble Community Project, NSF National Center for Atmospheric Research [data set], https://doi.org/10.5065/D6J101D1, 2021.
Kay, J. E., Deser, C., Phillips, A., Mai, A., Hannay, C., Strand, G., Arblaster, J. M., Bates, S. C., Danabasoglu, G., Edwards, J., Holland, M., Kushner, P., Lamarque, J.-F., Lawrence, D., Lindsay, K., Middleton, A., Munoz, E., Neale, R., Oleson, K., Polvani, L., and Vertenstein, M.: The Community Earth System Model (CESM) Large Ensemble Project: A Community Resource for Studying Climate Change in the Presence of Internal Climate Variability, B. Am. Meteorol. Soc., 96, 1333–1349, https://doi.org/10.1175/BAMS-D-13-00255.1, 2015.
Khan, S. A., Aschwanden, A., Bjørk, A. A., Wahr, J., Kjeldsen, K. K., and Kjær, K. H.: Greenland ice sheet mass balance: a review, Rep. Prog. Phys., 78, 046801, https://doi.org/10.1088/0034-4885/78/4/046801, 2015.
Kimura, F. and Kitoh, A.: Downscaling by pseudo-global-warming method, in: The Final Report of the ICCAP, RIHN Project 1-1, 43–46, https://www.chikyu.ac.jp/iccap/ICCAP_Final_Report/2/4-climate_kimura.pdf (last access: 18 May 2026), 2007.
Kjeldsen, K. K., Korsgaard, N. J., Bjørk, A. A., Khan, S. A., Box, J. E., Funder, S., Larsen, N. K., Bamber, J. L., Colgan, W., van den Broeke, M., Siggaard-Andersen, M.-L., Nuth, C., Schomacker, A., Andresen, C. S., Willerslev, E., and Kjær, K. H.: Spatial and temporal distribution of mass loss from the Greenland Ice Sheet since AD 1900, Nature, 528, 396–400, https://doi.org/10.1038/nature16183, 2015.
Kornhuber, K. and Tamarin-Brodsky, T.: Future Changes in Northern Hemisphere Summer Weather Persistence Linked to Projected Arctic Warming, Geophys. Res. Lett., 48, e2020GL091603, https://doi.org/10.1029/2020GL091603, 2021.
Lackmann, G. M.: Hurricane Sandy before 1900 and after 2100, B. Am. Meteorol. Soc., 96, 547–560, https://doi.org/10.1175/BAMS-D-14-00123.1, 2015.
Lee, S. H. and Polvani, L. M.: Increasing Frequency and Persistence of the Summertime Greenland High Regime Not Captured by a Seasonal Prediction Model Very Large Ensemble, Geophys. Res. Lett., 53, e2025GL119421, https://doi.org/10.1029/2025GL119421, 2026.
Lefebre, F., Fettweis, X., Gallée, H., Van Ypersele, J.-P., Marbaix, P., Greuell, W., and Calanca, P.: Evaluation of a high-resolution regional climate simulation over Greenland, Clim. Dynam., 25, 99–116, https://doi.org/10.1007/s00382-005-0005-8, 2005.
Lenaerts, J. T. M., Medley, B., van den Broeke, M. R., and Wouters, B.: Observing and Modeling Ice Sheet Surface Mass Balance, Rev. Geophys., 57, 376–420, https://doi.org/10.1029/2018RG000622, 2019.
Liu, J., Chen, Z., Francis, J., Song, M., Mote, T., and Hu, Y.: Has Arctic Sea Ice Loss Contributed to Increased Surface Melting of the Greenland Ice Sheet?, J. Climate, 29, 3373–3386, https://doi.org/10.1175/JCLI-D-15-0391.1, 2016.
Lloyd, E. A. and Oreskes, N.: Climate Change Attribution: When Is It Appropriate to Accept New Methods?, Earth's Future, 6, 311–325, https://doi.org/10.1002/2017EF000665, 2018.
Luu, L. N., Hanna, E., de Alwis Pitts, D., Maddison, J., Screen, J. A., Catto, J. L., and Fettweis, X.: Greenland summer blocking characteristics: an evaluation of a high-resolution multi-model ensemble, Clim. Dynam., 62, 10503–10523, https://doi.org/10.1007/s00382-024-07453-2, 2024.
Mallard, M. S., Lackmann, G. M., Aiyyer, A., and Hill, K.: Atlantic Hurricanes and Climate Change. Part I: Experimental Design and Isolation of Thermodynamic Effects, J. Climate, 26, 4876–4893, https://doi.org/10.1175/JCLI-D-12-00182.1, 2013.
Mankoff, K. D., Colgan, W., Solgaard, A., Karlsson, N. B., Ahlstrøm, A. P., van As, D., Box, J. E., Khan, S. A., Kjeldsen, K. K., Mouginot, J., and Fausto, R. S.: Greenland Ice Sheet solid ice discharge from 1986 through 2017, Earth Syst. Sci. Data, 11, 769–786, https://doi.org/10.5194/essd-11-769-2019, 2019.
Mattingly, K. S., Ramseyer, C. A., Rosen, J. J., Mote, T. L., and Muthyala, R.: Increasing water vapor transport to the Greenland Ice Sheet revealed using self-organizing maps, Geophys. Res. Lett., 43, 9250–9258, https://doi.org/10.1002/2016GL070424, 2016.
Mattingly, K. S., Mote, T. L., and Fettweis, X.: Atmospheric River Impacts on Greenland Ice Sheet Surface Mass Balance, J. Geophys. Res.-Atmos., 123, 8538–8560, https://doi.org/10.1029/2018JD028714, 2018.
Meese, D. A., Gow, A. J., Grootes, P., Mayewski, P. A., Ram, M., Stuiver, M., Taylor, K. C., Waddington, E. D., and Zielinski, G. A.: The Accumulation Record from the GISP2 Core as an Indicator of Climate Change Throughout the Holocene, Science, 266, 1680–1682, 1994.
Mote, T. L.: Mid-tropospheric circulation and surface melt on the Greenland ice sheet. Part I: atmospheric teleconnections, Int. J. Climatol., 18, 111–129, https://doi.org/10.1002/(SICI)1097-0088(199802)18:2<111::AID-JOC227>3.0.CO;2-X, 1998.
Mote, T. L.: Greenland surface melt trends 1973–2007: Evidence of a large increase in 2007, Geophys. Res. Lett., 34, https://doi.org/10.1029/2007GL031976, 2007.
Mouginot, J., Rignot, E., Bjørk, A. A., van den Broeke, M. R., Millan, R., Morlighem, M., Noël, B., Scheuchl, B., and Wood, M.: Forty-six years of Greenland Ice Sheet mass balance from 1972 to 2018, P. Natl. Acad. Sci. USA, 116, 9239–9244, https://doi.org/10.1073/pnas.1904242116, 2019.
Neff, W., Compo, G. P., Martin Ralph, F., and Shupe, M. D.: Continental heat anomalies and the extreme melting of the Greenland ice surface in 2012 and 1889: Melting of Greenland in 1889 and 2012, J. Geophys. Res.-Atmos., 119, 6520–6536, https://doi.org/10.1002/2014JD021470, 2014.
Nghiem, S. V., Hall, D. K., Mote, T. L., Tedesco, M., Albert, M. R., Keegan, K., Shuman, C. A., DiGirolamo, N. E., and Neumann, G.: The extreme melt across the Greenland ice sheet in 2012, Geophys. Res. Lett., 39, https://doi.org/10.1029/2012GL053611, 2012.
Noël, B., Fettweis, X., van de Berg, W. J., van den Broeke, M. R., and Erpicum, M.: Sensitivity of Greenland Ice Sheet surface mass balance to perturbations in sea surface temperature and sea ice cover: a study with the regional climate model MAR, The Cryosphere, 8, 1871–1883, https://doi.org/10.5194/tc-8-1871-2014, 2014.
Noël, B., van de Berg, W. J., Lhermitte, S., Wouters, B., Machguth, H., Howat, I., Citterio, M., Moholdt, G., Lenaerts, J. T. M., and van den Broeke, M. R.: A tipping point in refreezing accelerates mass loss of Greenland's glaciers and ice caps, Nat. Commun., 8, 14730, https://doi.org/10.1038/ncomms14730, 2017.
Noël, B., Berg, W. J. van de, Lhermitte, S., and van den Broeke, M. R.: Rapid ablation zone expansion amplifies north Greenland mass loss, Sci. Adv., 5, eaaw0123, https://doi.org/10.1126/sciadv.aaw0123, 2019.
Noël, B., van Kampenhout, L., Lenaerts, J. T. M., van de Berg, W. J., and van den Broeke, M. R.: A 21st Century Warming Threshold for Sustained Greenland Ice Sheet Mass Loss, Geophys. Res. Lett., 48, e2020GL090471, https://doi.org/10.1029/2020GL090471, 2021.
Ogi, M. and Wallace, J. M.: Summer minimum Arctic sea ice extent and the associated summer atmospheric circulation, Geophys. Res. Lett., 34, https://doi.org/10.1029/2007GL029897, 2007.
Orsi, A. J., Kawamura, K., Masson-Delmotte, V., Fettweis, X., Box, J. E., Dahl-Jensen, D., Clow, G. D., Landais, A., and Severinghaus, J. P.: The recent warming trend in North Greenland, Geophys. Res. Lett., 44, 6235–6243, https://doi.org/10.1002/2016GL072212, 2017.
Otosaka, I. N., Shepherd, A., Ivins, E. R., Schlegel, N.-J., Amory, C., van den Broeke, M. R., Horwath, M., Joughin, I., King, M. D., Krinner, G., Nowicki, S., Payne, A. J., Rignot, E., Scambos, T., Simon, K. M., Smith, B. E., Sørensen, L. S., Velicogna, I., Whitehouse, P. L., A, G., Agosta, C., Ahlstrøm, A. P., Blazquez, A., Colgan, W., Engdahl, M. E., Fettweis, X., Forsberg, R., Gallée, H., Gardner, A., Gilbert, L., Gourmelen, N., Groh, A., Gunter, B. C., Harig, C., Helm, V., Khan, S. A., Kittel, C., Konrad, H., Langen, P. L., Lecavalier, B. S., Liang, C.-C., Loomis, B. D., McMillan, M., Melini, D., Mernild, S. H., Mottram, R., Mouginot, J., Nilsson, J., Noël, B., Pattle, M. E., Peltier, W. R., Pie, N., Roca, M., Sasgen, I., Save, H. V., Seo, K.-W., Scheuchl, B., Schrama, E. J. O., Schröder, L., Simonsen, S. B., Slater, T., Spada, G., Sutterley, T. C., Vishwakarma, B. D., van Wessem, J. M., Wiese, D., van der Wal, W., and Wouters, B.: Mass balance of the Greenland and Antarctic ice sheets from 1992 to 2020, Earth Syst. Sci. Data, 15, 1597–1616, https://doi.org/10.5194/essd-15-1597-2023, 2023.
Overland, J. E., Francis, J. A., Hanna, E., and Wang, M.: The recent shift in early summer Arctic atmospheric circulation, Geophys. Res. Lett., 39, L19804, https://doi.org/10.1029/2012GL053268, 2012.
Pedersen, R. A. and Christensen, J. H.: Attributing Greenland Warming Patterns to Regional Arctic Sea Ice Loss, Geophys. Res. Lett., 46, 10495–10503, https://doi.org/10.1029/2019GL083828, 2019.
Pithan, F. and Mauritsen, T.: Arctic amplification dominated by temperature feedbacks in contemporary climate models, Nat. Geosci., 7, 181–184, https://doi.org/10.1038/ngeo2071, 2014.
Preece, J., Alexander, P., Mote, T., Kooperman, G., Fettweis, X., and Tedesco, M.: Modèle Atmosphérique Régional (MAR) version 3.12 regional climate model pseudo-global warming experiment output, 2000-2019, Greenland domain, 20 kilometer (km) horizontal resolution, Arctic Data Center [data set], https://doi.org/10.18739/A2TT4FV6W, 2023a.
Preece, J. R., Wachowicz, L. J., Mote, T. L., Tedesco, M., and Fettweis, X.: Summer Greenland Blocking Diversity and Its Impact on the Surface Mass Balance of the Greenland Ice Sheet, J. Geophys. Res.-Atmos., 127, e2021JD035489, https://doi.org/10.1029/2021JD035489, 2022.
Preece, J. R., Mote, T. L., Cohen, J., Wachowicz, L. J., Knox, J. A., Tedesco, M., and Kooperman, G. J.: Summer atmospheric circulation over Greenland in response to Arctic amplification and diminished spring snow cover, Nat. Commun., 14, 3759, https://doi.org/10.1038/s41467-023-39466-6, 2023b.
Rantanen, M., Karpechko, A. Y., Lipponen, A., Nordling, K., Hyvärinen, O., Ruosteenoja, K., Vihma, T., and Laaksonen, A.: The Arctic has warmed nearly four times faster than the globe since 1979, Commun. Earth Environ., 3, 1–10, https://doi.org/10.1038/s43247-022-00498-3, 2022.
Rasmussen, K. L., Prein, A. F., Rasmussen, R. M., Ikeda, K., and Liu, C.: Changes in the convective population and thermodynamic environments in convection-permitting regional climate simulations over the United States, Clim. Dynam., 55, 383–408, https://doi.org/10.1007/s00382-017-4000-7, 2020.
Rasmussen, R., Liu, C., Ikeda, K., Gochis, D., Yates, D., Chen, F., Tewari, M., Barlage, M., Dudhia, J., Yu, W., Miller, K., Arsenault, K., Grubišić, V., Thompson, G., and Gutmann, E.: High-Resolution Coupled Climate Runoff Simulations of Seasonal Snowfall over Colorado: A Process Study of Current and Warmer Climate, J. Climate, 24, 3015–3048, https://doi.org/10.1175/2010JCLI3985.1, 2011.
Rennermalm, A. K., Smith, L. C., Stroeve, J. C., and Chu, V. W.: Does sea ice influence Greenland ice sheet surface-melt?, Environ. Res. Lett., 4, 024011, https://doi.org/10.1088/1748-9326/4/2/024011, 2009.
Rogers, J. C., Bathke, D. J., Mosley-Thompson, E., and Wang, S.-H.: Atmospheric circulation and cyclone frequency variations linked to the primary modes of Greenland snow accumulation, Geophys. Res. Lett., 31, https://doi.org/10.1029/2004GL021048, 2004.
Schär, C., Frei, C., Lüthi, D., and Davies, H. C.: Surrogate climate-change scenarios for regional climate models, Geophys. Res. Lett., 23, 669–672, https://doi.org/10.1029/96GL00265, 1996.
Schoof, C.: Ice-sheet acceleration driven by melt supply variability, Nature, 468, 803–806, https://doi.org/10.1038/nature09618, 2010.
Schuenemann, K. C., Cassano, J. J., and Finnis, J.: Synoptic Forcing of Precipitation over Greenland: Climatology for 1961–99, J. Hydrometeorol., 10, 60–78, https://doi.org/10.1175/2008JHM1014.1, 2009.
Screen, J. A.: Influence of Arctic sea ice on European summer precipitation, Environ. Res. Lett., 8, 044015, https://doi.org/10.1088/1748-9326/8/4/044015, 2013.
Screen, J. A.: Far-flung effects of Arctic warming, Nat. Geosci., 10, 253–254, https://doi.org/10.1038/ngeo2924, 2017.
Screen, J. A. and Simmonds, I.: The central role of diminishing sea ice in recent Arctic temperature amplification, Nature, 464, 1334–1337, https://doi.org/10.1038/nature09051, 2010.
Sellevold, R., Lenaerts, J. T. M., and Vizcaino, M.: Influence of Arctic sea-ice loss on the Greenland ice sheet climate, Clim. Dynam., 58, 179–193, https://doi.org/10.1007/s00382-021-05897-4, 2022.
Serreze, M. C. and Barry, R. G.: Processes and impacts of Arctic amplification: A research synthesis, Glob. Planet. Change, 77, 85–96, https://doi.org/10.1016/j.gloplacha.2011.03.004, 2011.
Shea, D., Hurrell, J., and Phillips, A.: Merged Hadley-OI sea surface temperature and sea ice concentration data set, Zenodo [data set], https://doi.org/10.5065/R33V-SV91, 2020.
Smith, B., Fricker, H. A., Gardner, A. S., Medley, B., Nilsson, J., Paolo, F. S., Holschuh, N., Adusumilli, S., Brunt, K., Csatho, B., Harbeck, K., Markus, T., Neumann, T., Siegfried, M. R., and Zwally, H. J.: Pervasive ice sheet mass loss reflects competing ocean and atmosphere processes, Science, 368, 1239–1242, https://doi.org/10.1126/science.aaz5845, 2020.
Stroeve, J. C., Mioduszewski, J. R., Rennermalm, A., Boisvert, L. N., Tedesco, M., and Robinson, D.: Investigating the local-scale influence of sea ice on Greenland surface melt, The Cryosphere, 11, 2363–2381, https://doi.org/10.5194/tc-11-2363-2017, 2017.
Tedesco, M. and Fettweis, X.: Unprecedented atmospheric conditions (1948–2019) drive the 2019 exceptional melting season over the Greenland ice sheet, The Cryosphere, 14, 1209–1223, https://doi.org/10.5194/tc-14-1209-2020, 2020.
Tedesco, M., Mote, T., Fettweis, X., Hanna, E., Jeyaratnam, J., Booth, J. F., Datta, R., and Briggs, K.: Arctic cut-off high drives the poleward shift of a new Greenland melting record, Nat. Commun., 7, 11723, https://doi.org/10.1038/ncomms11723, 2016.
The GlaMBIE Team, Zemp, M., Jakob, L., Dussaillant, I., Nussbaumer, S. U., Gourmelen, N., Dubber, S., A, G., Abdullahi, S., Andreassen, L. M., Berthier, E., Bhattacharya, A., Blazquez, A., Boehm Vock, L. F., Bolch, T., Box, J., Braun, M. H., Brun, F., Cicero, E., Colgan, W., Eckert, N., Farinotti, D., Florentine, C., Floricioiu, D., Gardner, A., Harig, C., Hassan, J., Hugonnet, R., Huss, M., Jóhannesson, T., Liang, C.-C. A., Ke, C.-Q., Khan, S. A., King, O., Kneib, M., Krieger, L., Maussion, F., Mattea, E., McNabb, R., Menounos, B., Miles, E., Moholdt, G., Nilsson, J., Pálsson, F., Pfeffer, J., Piermattei, L., Plummer, S., Richter, A., Sasgen, I., Schuster, L., Seehaus, T., Shen, X., Sommer, C., Sutterley, T., Treichler, D., Velicogna, I., Wouters, B., Zekollari, H., Zheng, W., and The GlaMBIE Team: Community estimate of global glacier mass changes from 2000 to 2023, Nature, 639, 382–388, https://doi.org/10.1038/s41586-024-08545-z, 2025.
The IMBIE team, Shepherd, A., Ivins, E., Rignot, E., Smith, B., van den Broeke, M., Velicogna, I., Whitehouse, P., Briggs, K., Joughin, I., Krinner, G., Nowicki, S., Payne, T., Scambos, T., Schlegel, N., A, G., Agosta, C., Ahlstrøm, A., Babonis, G., Barletta, V., Blazquez, A., Bonin, J., Csatho, B., Cullather, R., Felikson, D., Fettweis, X., Forsberg, R., Gallee, H., Gardner, A., Gilbert, L., Groh, A., Gunter, B., Hanna, E., Harig, C., Helm, V., Horvath, A., Horwath, M., Khan, S., Kjeldsen, K. K., Konrad, H., Langen, P., Lecavalier, B., Loomis, B., Luthcke, S., McMillan, M., Melini, D., Mernild, S., Mohajerani, Y., Moore, P., Mouginot, J., Moyano, G., Muir, A., Nagler, T., Nield, G., Nilsson, J., Noel, B., Otosaka, I., Pattle, M. E., Peltier, W. R., Pie, N., Rietbroek, R., Rott, H., Sandberg-Sørensen, L., Sasgen, I., Save, H., Scheuchl, B., Schrama, E., Schröder, L., Seo, K.-W., Simonsen, S., Slater, T., Spada, G., Sutterley, T., Talpe, M., Tarasov, L., van de Berg, W. J., van der Wal, W., van Wessem, M., Vishwakarma, B. D., Wiese, D., and Wouters, B.: Mass balance of the Antarctic Ice Sheet from 1992 to 2017, Nature, 558, 219–222, https://doi.org/10.1038/s41586-018-0179-y, 2018.
Topál, D., Ding, Q., Ballinger, T. J., Hanna, E., Fettweis, X., Li, Z., and Pieczka, I.: Discrepancies between observations and climate models of large-scale wind-driven Greenland melt influence sea-level rise projections, Nat. Commun., 13, https://doi.org/10.1038/s41467-022-34414-2, 2022.
Trenberth, K. E.: Changes in precipitation with climate change, Climate Res., 47, 123–138, 2011.
Trenberth, K. E., Fasullo, J. T., and Shepherd, T. G.: Attribution of climate extreme events, Nat. Clim. Change, 5, 725–730, https://doi.org/10.1038/nclimate2657, 2015.
van den Broeke, M. R., Bamber, J., Ettema, J., Rignot, E., Schrama, E., Berg, W. J. van de, Meijgaard, E. van, Velicogna, I., and Wouters, B.: Partitioning Recent Greenland Mass Loss, Science, 326, 984–986, https://doi.org/10.1126/science.1178176, 2009a.
van den Broeke, M. R., Smeets, P., and Ettema, J.: Surface layer climate and turbulent exchange in the ablation zone of the west Greenland ice sheet, Int. J. Climatol., 29, 2309–2323, https://doi.org/10.1002/joc.1815, 2009b.
van den Broeke, M. R., Enderlin, E. M., Howat, I. M., Kuipers Munneke, P., Noël, B. P. Y., van de Berg, W. J., van Meijgaard, E., and Wouters, B.: On the recent contribution of the Greenland ice sheet to sea level change, The Cryosphere, 10, 1933–1946, https://doi.org/10.5194/tc-10-1933-2016, 2016.
Vavrus, S. J., Wang, F., Martin, J. E., Francis, J. A., Peings, Y., and Cattiaux, J.: Changes in North American Atmospheric Circulation and Extreme Weather: Influence of Arctic Amplification and Northern Hemisphere Snow Cover, J. Climate, 30, 4317–4333, https://doi.org/10.1175/JCLI-D-16-0762.1, 2017.
Velicogna, I., Mohajerani, Y., A, G., Landerer, F., Mouginot, J., Noel, B., Rignot, E., Sutterley, T., van den Broeke, M., van Wessem, M., and Wiese, D.: Continuity of Ice Sheet Mass Loss in Greenland and Antarctica From the GRACE and GRACE Follow-On Missions, Geophys. Res. Lett., 47, e2020GL087291, https://doi.org/10.1029/2020GL087291, 2020.
Wang, S., Ma, X., Zhou, S., Wu, L., Wang, H., Tang, Z., Xu, G., Jing, Z., Chen, Z., and Gan, B.: Extreme atmospheric rivers in a warming climate, Nat. Commun., 14, 3219, https://doi.org/10.1038/s41467-023-38980-x, 2023.
Wang, W., Zender, C. S., and van As, D.: Temporal Characteristics of Cloud Radiative Effects on the Greenland Ice Sheet: Discoveries From Multiyear Automatic Weather Station Measurements, J. Geophys. Res.-Atmos., 123, 11,348-11,361, https://doi.org/10.1029/2018JD028540, 2018.
Wang, W., Zender, C. S., As, D. van, and Miller, N. B.: Spatial Distribution of Melt Season Cloud Radiative Effects Over Greenland: Evaluating Satellite Observations, Reanalyses, and Model Simulations Against In Situ Measurements, J. Geophys. Res.-Atmos., 124, 57–71, https://doi.org/10.1029/2018JD028919, 2019.
Wilcoxon, F.: Individual Comparisons by Ranking Methods, Biometrics Bulletin, 1, 80–83, https://doi.org/10.2307/3001968, 1945.
Woollings, T., Barriopedro, D., Methven, J., Son, S.-W., Martius, O., Harvey, B., Sillmann, J., Lupo, A. R., and Seneviratne, S.: Blocking and its Response to Climate Change, Curr. Clim. Change Rep., 4, 287–300, https://doi.org/10.1007/s40641-018-0108-z, 2018.
Wu, B., Zhang, R., D'Arrigo, R., and Su, J.: On the Relationship between Winter Sea Ice and Summer Atmospheric Circulation over Eurasia, J. Climate, 26, 5523–5536, https://doi.org/10.1175/JCLI-D-12-00524.1, 2013.
Yang, C., Leonelli, F. E., Marullo, S., Artale, V., Beggs, H., Nardelli, B. B., Chin, T. M., Toma, V. D., Good, S., Huang, B., Merchant, C. J., Sakurai, T., Santoleri, R., Vazquez-Cuervo, J., Zhang, H.-M., and Pisano, A.: Sea Surface Temperature Intercomparison in the Framework of the Copernicus Climate Change Service (C3S), J. Climate, 34, 5257–5283, https://doi.org/10.1175/JCLI-D-20-0793.1, 2021.
Short summary
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.
Surface melt of the Greenland Ice Sheet has increased dramatically since the turn of the...
