Articles | Volume 16, issue 20
https://doi.org/10.5194/gmd-16-5803-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-16-5803-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
19 Oct 2023
Model description paper |
| 19 Oct 2023
| 19 Oct 2023
A new model for supraglacial hydrology evolution and drainage for the Greenland Ice Sheet (SHED v1.0)
Prateek Gantayat
Lancaster Environment Centre, Lancaster University, Lancaster, UK
Alison F. Banwell
Cooperative Institute for Research in Environmental Sciences (CIRES), University of Colorado Boulder, Boulder, USA
Lancaster Environment Centre, Lancaster University, Lancaster, UK
Data Science Institute, Lancaster University, Lancaster, UK
James M. Lea
School of Environmental Sciences, University of Liverpool, Liverpool, UK
Dorthe Petersen
Asiaq Greenland Survey, Nuuk, Greenland
Noel Gourmelen
Department of Geoscience, University of Edinburgh, Edinburgh, UK
Xavier Fettweis
Unit of Physical geography and Quaternary period, University of Liege, Liege, Belgium
Related authors
No articles found.
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
Short summary
Short summary
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.
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
Short summary
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.
Heiko Goelzer, Constantijn J. Berends, Fredrik Boberg, Gael Durand, Tamsin Edwards, Xavier Fettweis, Fabien Gillet-Chaulet, Quentin Glaude, Philippe Huybrechts, Sébastien Le clec'h, Ruth Mottram, Brice Noël, Martin Olesen, Charlotte Rahlves, Jeremy Rohmer, Michiel van den Broeke, and Roderik S. W. van de Wal
EGUsphere, https://doi.org/10.5194/egusphere-2025-3098, https://doi.org/10.5194/egusphere-2025-3098, 2025
This preprint is open for discussion and under review for The Cryosphere (TC).
Short summary
Short summary
We present an ensemble of ice sheet model projections for the Greenland ice sheet. The focus is on providing projections that improve our understanding of the range future sea-level rise and the inherent uncertainties over the next 100 to 300 years. Compared to earlier work we more fully account for some of the uncertainties in sea-level projections. We include a wider range of climate model output, more climate change scenarios and we extend projections schematically up to year 2300.
Audrey Goutard, Marion Réveillet, Fanny Brun, Delphine Six, Kevin Fourteau, Charles Amory, Xavier Fettweis, Mathieu Fructus, Arbindra Khadka, and Matthieu Lafaysse
EGUsphere, https://doi.org/10.5194/egusphere-2025-2947, https://doi.org/10.5194/egusphere-2025-2947, 2025
This preprint is open for discussion and under review for The Cryosphere (TC).
Short summary
Short summary
A new scheme has been developed in the SURFEX/ISBA-Crocus model, 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.
Chloë Marie Paice, Xavier Fettweis, and Philippe Huybrechts
EGUsphere, https://doi.org/10.5194/egusphere-2025-2465, https://doi.org/10.5194/egusphere-2025-2465, 2025
Short summary
Short summary
To study the interactions between the Greenland ice sheet and the atmosphere, we coupled an ice sheet model to a regional climate model and performed simulations of differing coupling complexity over 1000 years. They reveal that at first melt at the ice sheet margin is reduced by changing wind patterns. But over time, as the ice sheet surface lowers, precipitation patterns and cloudiness also change and amplify ice mass loss over the entire ice sheet.
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
EGUsphere, https://doi.org/10.5194/egusphere-2025-386, https://doi.org/10.5194/egusphere-2025-386, 2025
Short summary
Short summary
A realistic representation of Antarctic sea ice is crucial for accurate climate and ocean model predictions. We assessed how different models capture the sunlight reflectivity, snow cover, and ice thickness. Most performed well under mild weather conditions, but overestimated snow/ice reflectivity during cold, with patchy/thin snow conditions. High-resolution satellite imagery revealed spatial albedo variability that models failed to replicate.
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
Short summary
Short summary
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.
Emily Glen, Amber Leeson, Alison F. Banwell, Jennifer Maddalena, Diarmuid Corr, Olivia Atkins, Brice Noël, and Malcolm McMillan
The Cryosphere, 19, 1047–1066, https://doi.org/10.5194/tc-19-1047-2025, https://doi.org/10.5194/tc-19-1047-2025, 2025
Short summary
Short summary
We compare surface meltwater features from optical satellite imagery in the Russell–Leverett glacier catchment during high (2019) and low (2018) melt years. In the high melt year, features appear at higher elevations, meltwater systems are more connected, small lakes are more frequent, and slush is more widespread. These findings provide insights into how a warming climate, where high melt years become common, could alter meltwater distribution and dynamics on the Greenland Ice Sheet.
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
Short summary
Short summary
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.
Katie Lowery, Pierre Dutrieux, Paul R. Holland, Anna E. Hogg, Noel Gourmelen, and Benjamin J. Wallis
EGUsphere, https://doi.org/10.5194/egusphere-2025-267, https://doi.org/10.5194/egusphere-2025-267, 2025
Short summary
Short summary
We use CryoSat-2 to observe monthly changes in Pine Island Glacier's ice shelf (PIG) surface at 250 m resolution. We show that melt is focused on the western walls of basal channels and highlight the role of channels in grounding pinning points. PIG’s main channel geometry is inherited from the ice-bed interface upstream of the grounding line. These results highlight the importance of channels on ice shelf stability and how this can change over time.
Ryan Hossaini, David Sherry, Zihao Wang, Martyn P. Chipperfield, Wuhu Feng, David E. Oram, Karina E. Adcock, Stephen A. Montzka, Isobel J. Simpson, Andrea Mazzeo, Amber A. Leeson, Elliot Atlas, and Charles C.-K. Chou
Atmos. Chem. Phys., 24, 13457–13475, https://doi.org/10.5194/acp-24-13457-2024, https://doi.org/10.5194/acp-24-13457-2024, 2024
Short summary
Short summary
DCE (1,2-dichloroethane) is an industrial chemical used to produce PVC (polyvinyl chloride). We analysed DCE production data to estimate global DCE emissions (2002–2020). The emissions were included in an atmospheric model and evaluated by comparing simulated DCE to DCE measurements in the troposphere. We show that DCE contributes ozone-depleting Cl to the stratosphere and that this has increased with increasing DCE emissions. DCE’s impact on stratospheric O3 is currently small but non-zero.
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
Short summary
Short summary
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.
Horst Machguth, Andrew Tedstone, Peter Kuipers Munneke, Max Brils, Brice Noël, Nicole Clerx, Nicolas Jullien, Xavier Fettweis, and Michiel van den Broeke
EGUsphere, https://doi.org/10.5194/egusphere-2024-2750, https://doi.org/10.5194/egusphere-2024-2750, 2024
Short summary
Short summary
Due to increasing air temperatures, surface melt expands to higher elevations on the Greenland ice sheet. This is visible on satellite imagery in the form of rivers of meltwater running across the surface of the ice sheet. We compare model results of meltwater at high elevations on the ice sheet to satellite observations. We find that each of the models shows strengths and weaknesses. A detailed look into the model results reveals potential reasons for the differences between models.
Jeremy Carter, Erick A. Chacón-Montalván, and Amber Leeson
Geosci. Model Dev., 17, 5733–5757, https://doi.org/10.5194/gmd-17-5733-2024, https://doi.org/10.5194/gmd-17-5733-2024, 2024
Short summary
Short summary
Climate models are essential tools in the study of climate change and its wide-ranging impacts on life on Earth. However, the output is often afflicted with some bias. In this paper, a novel model is developed to predict and correct bias in the output of climate models. The model captures uncertainty in the correction and explicitly models underlying spatial correlation between points. These features are of key importance for climate change impact assessments and resulting decision-making.
Naomi E. Ochwat, Ted A. Scambos, Alison F. Banwell, Robert S. Anderson, Michelle L. Maclennan, Ghislain Picard, Julia A. Shates, Sebastian Marinsek, Liliana Margonari, Martin Truffer, and Erin C. Pettit
The Cryosphere, 18, 1709–1731, https://doi.org/10.5194/tc-18-1709-2024, https://doi.org/10.5194/tc-18-1709-2024, 2024
Short summary
Short summary
On the Antarctic Peninsula, there is a small bay that had sea ice fastened to the shoreline (
fast ice) for over a decade. The fast ice stabilized the glaciers that fed into the ocean. In January 2022, the fast ice broke away. Using satellite data we found that this was because of low sea ice concentrations and a high long-period ocean wave swell. We find that the glaciers have responded to this event by thinning, speeding up, and retreating by breaking off lots of icebergs at remarkable rates.
Trystan Surawy-Stepney, Anna E. Hogg, Stephen L. Cornford, Benjamin J. Wallis, Benjamin J. Davison, Heather L. Selley, Ross A. W. Slater, Elise K. Lie, Livia Jakob, Andrew Ridout, Noel Gourmelen, Bryony I. D. Freer, Sally F. Wilson, and Andrew Shepherd
The Cryosphere, 18, 977–993, https://doi.org/10.5194/tc-18-977-2024, https://doi.org/10.5194/tc-18-977-2024, 2024
Short summary
Short summary
Here, we use satellite observations and an ice flow model to quantify the impact of sea ice buttressing on ice streams on the Antarctic Peninsula. The evacuation of 11-year-old landfast sea ice in the Larsen B embayment on the East Antarctic Peninsula in January 2022 was closely followed by major changes in the calving behaviour and acceleration (30 %) of the ocean-terminating glaciers. Our results show that sea ice buttressing had a negligible direct role in the observed dynamic changes.
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
Short summary
Short summary
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
Short summary
Short summary
How fast is the Greenland ice sheet warming? In this study, we compiled 4500+ temperature measurements at 10 m below the ice sheet surface (T10m) from 1912 to 2022. We trained a machine learning model on these data and reconstructed T10m for the ice sheet during 1950–2022. After a slight cooling during 1950–1985, the ice sheet warmed at a rate of 0.7 °C per decade until 2022. Climate models showed mixed results compared to our observations and underestimated the warming in key regions.
Laura Melling, Amber Leeson, Malcolm McMillan, Jennifer Maddalena, Jade Bowling, Emily Glen, Louise Sandberg Sørensen, Mai Winstrup, and Rasmus Lørup Arildsen
The Cryosphere, 18, 543–558, https://doi.org/10.5194/tc-18-543-2024, https://doi.org/10.5194/tc-18-543-2024, 2024
Short summary
Short summary
Lakes on glaciers hold large volumes of water which can drain through the ice, influencing estimates of sea level rise. To estimate water volume, we must calculate lake depth. We assessed the accuracy of three satellite-based depth detection methods on a study area in western Greenland and considered the implications for quantifying the volume of water within lakes. We found that the most popular method of detecting depth on the ice sheet scale has higher uncertainty than previously assumed.
Louise Sandberg Sørensen, Rasmus Bahbah, Sebastian B. Simonsen, Natalia Havelund Andersen, Jade Bowling, Noel Gourmelen, Alex Horton, Nanna B. Karlsson, Amber Leeson, Jennifer Maddalena, Malcolm McMillan, Anne Solgaard, and Birgit Wessel
The Cryosphere, 18, 505–523, https://doi.org/10.5194/tc-18-505-2024, https://doi.org/10.5194/tc-18-505-2024, 2024
Short summary
Short summary
Under the right topographic and hydrological conditions, lakes may form beneath the large ice sheets. Some of these subglacial lakes are active, meaning that they periodically drain and refill. When a subglacial lake drains rapidly, it may cause the ice surface above to collapse, and here we investigate how to improve the monitoring of active subglacial lakes in Greenland by monitoring how their associated collapse basins change over time.
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
Timo Schmid, Valentina Radić, Andrew Tedstone, James M. Lea, Stephen Brough, and Mauro Hermann
The Cryosphere, 17, 3933–3954, https://doi.org/10.5194/tc-17-3933-2023, https://doi.org/10.5194/tc-17-3933-2023, 2023
Short summary
Short summary
The Greenland Ice Sheet contributes strongly to sea level rise in the warming climate. One process that can affect the ice sheet's mass balance is short-term ice speed-up events. These can be caused by high melting or rainfall as the water flows underneath the glacier and allows for faster sliding. In this study we found three main weather patterns that cause such ice speed-up events on the Russell Glacier in southwest Greenland and analyzed how they induce local melting and ice accelerations.
Inès N. Otosaka, Andrew Shepherd, Erik R. Ivins, Nicole-Jeanne Schlegel, Charles Amory, Michiel R. van den Broeke, Martin Horwath, Ian Joughin, Michalea D. King, Gerhard Krinner, Sophie Nowicki, Anthony J. Payne, Eric Rignot, Ted Scambos, Karen M. Simon, Benjamin E. Smith, Louise S. Sørensen, Isabella Velicogna, Pippa L. Whitehouse, Geruo A, Cécile Agosta, Andreas P. Ahlstrøm, Alejandro Blazquez, William Colgan, Marcus E. Engdahl, Xavier Fettweis, Rene Forsberg, Hubert Gallée, Alex Gardner, Lin Gilbert, Noel Gourmelen, Andreas Groh, Brian C. Gunter, Christopher Harig, Veit Helm, Shfaqat Abbas Khan, Christoph Kittel, Hannes Konrad, Peter L. Langen, Benoit S. Lecavalier, Chia-Chun Liang, Bryant D. Loomis, Malcolm McMillan, Daniele Melini, Sebastian H. Mernild, Ruth Mottram, Jeremie Mouginot, Johan Nilsson, Brice Noël, Mark E. Pattle, William R. Peltier, Nadege Pie, Mònica Roca, Ingo Sasgen, Himanshu V. Save, Ki-Weon Seo, Bernd Scheuchl, Ernst J. O. Schrama, Ludwig Schröder, Sebastian B. Simonsen, Thomas Slater, Giorgio Spada, Tyler C. Sutterley, Bramha Dutt Vishwakarma, Jan Melchior van Wessem, David Wiese, Wouter van der Wal, and Bert Wouters
Earth Syst. Sci. Data, 15, 1597–1616, https://doi.org/10.5194/essd-15-1597-2023, https://doi.org/10.5194/essd-15-1597-2023, 2023
Short summary
Short summary
By measuring changes in the volume, gravitational attraction, and ice flow of Greenland and Antarctica from space, we can monitor their mass gain and loss over time. Here, we present a new record of the Earth’s polar ice sheet mass balance produced by aggregating 50 satellite-based estimates of ice sheet mass change. This new assessment shows that the ice sheets have lost (7.5 x 1012) t of ice between 1992 and 2020, contributing 21 mm to sea level rise.
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
Short summary
Short summary
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
Short summary
Short summary
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.
Connor J. Shiggins, James M. Lea, and Stephen Brough
The Cryosphere, 17, 15–32, https://doi.org/10.5194/tc-17-15-2023, https://doi.org/10.5194/tc-17-15-2023, 2023
Short summary
Short summary
Iceberg detection is spatially and temporally limited around the Greenland Ice Sheet. This study presents a new, accessible workflow to automatically detect icebergs from timestamped ArcticDEM strip data. The workflow successfully produces comparable output to manual digitisation, with results revealing new iceberg area-to-volume conversion equations that can be widely applied to datasets where only iceberg outlines can be extracted (e.g. optical and SAR imagery).
Ghislain Picard, Marion Leduc-Leballeur, Alison F. Banwell, Ludovic Brucker, and Giovanni Macelloni
The Cryosphere, 16, 5061–5083, https://doi.org/10.5194/tc-16-5061-2022, https://doi.org/10.5194/tc-16-5061-2022, 2022
Short summary
Short summary
Using a snowpack radiative transfer model, we investigate in which conditions meltwater can be detected from passive microwave satellite observations from 1.4 to 37 GHz. In particular, we determine the minimum detectable liquid water content, the maximum depth of detection of a buried wet snow layer and the risk of false alarm due to supraglacial lakes. These results provide information for the developers of new, more advanced satellite melt products and for the users of the existing products.
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
Short summary
Short summary
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.
Jeremy Carter, Amber Leeson, Andrew Orr, Christoph Kittel, and J. Melchior van Wessem
The Cryosphere, 16, 3815–3841, https://doi.org/10.5194/tc-16-3815-2022, https://doi.org/10.5194/tc-16-3815-2022, 2022
Short summary
Short summary
Climate models provide valuable information for studying processes such as the collapse of ice shelves over Antarctica which impact estimates of sea level rise. This paper examines variability across climate simulations over Antarctica for fields including snowfall, temperature and melt. Significant systematic differences between outputs are found, occurring at both large and fine spatial scales across Antarctica. Results are important for future impact assessments and model development.
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
Short summary
Short summary
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
Short summary
Short summary
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.
Daniel Clarkson, Emma Eastoe, and Amber Leeson
The Cryosphere, 16, 1597–1607, https://doi.org/10.5194/tc-16-1597-2022, https://doi.org/10.5194/tc-16-1597-2022, 2022
Short summary
Short summary
The Greenland ice sheet has seen large amounts of melt in recent years, and accurately modelling temperatures is vital to understand how much of the ice sheet is melting. We estimate the probability of melt from ice surface temperature data to identify which areas of the ice sheet have experienced melt and estimate temperature quantiles. Our results suggest that for large areas of the ice sheet, melt has become more likely over the past 2 decades and high temperatures are also becoming warmer.
Diarmuid Corr, Amber Leeson, Malcolm McMillan, Ce Zhang, and Thomas Barnes
Earth Syst. Sci. Data, 14, 209–228, https://doi.org/10.5194/essd-14-209-2022, https://doi.org/10.5194/essd-14-209-2022, 2022
Short summary
Short summary
We identify 119 km2 of meltwater area over West Antarctica in January 2017. In combination with Stokes et al., 2019, this forms the first continent-wide assessment helping to quantify the mass balance of Antarctica and its contribution to global sea level rise. We apply thresholds for meltwater classification to satellite images, mapping the extent and manually post-processing to remove false positives. Our study provides a high-fidelity dataset to train and validate machine learning methods.
Kenneth D. Mankoff, Xavier Fettweis, Peter L. Langen, Martin Stendel, Kristian K. Kjeldsen, Nanna B. Karlsson, Brice Noël, Michiel R. van den Broeke, Anne Solgaard, William Colgan, Jason E. Box, Sebastian B. Simonsen, Michalea D. King, Andreas P. Ahlstrøm, Signe Bech Andersen, and Robert S. Fausto
Earth Syst. Sci. Data, 13, 5001–5025, https://doi.org/10.5194/essd-13-5001-2021, https://doi.org/10.5194/essd-13-5001-2021, 2021
Short summary
Short summary
We estimate the daily mass balance and its components (surface, marine, and basal mass balance) for the Greenland ice sheet. Our time series begins in 1840 and has annual resolution through 1985 and then daily from 1986 through next week. Results are operational (updated daily) and provided for the entire ice sheet or by commonly used regions or sectors. This is the first input–output mass balance estimate to include the basal mass balance.
Ruth Mottram, Nicolaj Hansen, Christoph Kittel, J. Melchior van Wessem, Cécile Agosta, Charles Amory, Fredrik Boberg, Willem Jan van de Berg, Xavier Fettweis, Alexandra Gossart, Nicole P. M. van Lipzig, Erik van Meijgaard, Andrew Orr, Tony Phillips, Stuart Webster, Sebastian B. Simonsen, and Niels Souverijns
The Cryosphere, 15, 3751–3784, https://doi.org/10.5194/tc-15-3751-2021, https://doi.org/10.5194/tc-15-3751-2021, 2021
Short summary
Short summary
We compare the calculated surface mass budget (SMB) of Antarctica in five different regional climate models. On average ~ 2000 Gt of snow accumulates annually, but different models vary by ~ 10 %, a difference equivalent to ± 0.5 mm of global sea level rise. All models reproduce observed weather, but there are large differences in regional patterns of snowfall, especially in areas with very few observations, giving greater uncertainty in Antarctic mass budget than previously identified.
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
Short summary
Short summary
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.
Thomas James Barnes, Amber Alexandra Leeson, Malcolm McMillan, Vincent Verjans, Jeremy Carter, and Christoph Kittel
The Cryosphere Discuss., https://doi.org/10.5194/tc-2021-214, https://doi.org/10.5194/tc-2021-214, 2021
Revised manuscript not accepted
Short summary
Short summary
We find that the area covered by lakes on George VI ice shelf in 2020 is similar to that seen in other years such as 1989. However, the climate conditions are much more in favour of lakes forming. We find that it is likely that snowfall, and the build up of a surface snow layer limits the development of lakes on the surface of George VI ice shelf in 2020. We also find that in future, snowfall is predicted to decrease, and therefore this limiting effect may be reduced in future.
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
Short summary
Short summary
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.
Devon Dunmire, Alison F. Banwell, Nander Wever, Jan T. M. Lenaerts, and Rajashree Tri Datta
The Cryosphere, 15, 2983–3005, https://doi.org/10.5194/tc-15-2983-2021, https://doi.org/10.5194/tc-15-2983-2021, 2021
Short summary
Short summary
Here, we automatically detect buried lakes (meltwater lakes buried below layers of snow) across the Greenland Ice Sheet, providing insight into a poorly studied meltwater feature. For 2018 and 2019, we compare areal extent of buried lakes. We find greater buried lake extent in 2019, especially in northern Greenland, which we attribute to late-summer surface melt and high autumn temperatures. We also provide evidence that buried lakes form via different processes across Greenland.
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
Short summary
Short summary
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
Short summary
Short summary
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.
Livia Jakob, Noel Gourmelen, Martin Ewart, and Stephen Plummer
The Cryosphere, 15, 1845–1862, https://doi.org/10.5194/tc-15-1845-2021, https://doi.org/10.5194/tc-15-1845-2021, 2021
Short summary
Short summary
Glaciers and ice caps are currently the largest contributor to sea level rise. Global monitoring of these regions is a challenging task, and significant differences remain between current estimates. This study looks at glacier changes in High Mountain Asia and the Gulf of Alaska using a new technique, which for the first time makes the use of satellite radar altimetry for mapping ice mass loss over mountain glacier regions possible.
Christoph Kittel, Charles Amory, Cécile Agosta, Nicolas C. Jourdain, Stefan Hofer, Alison Delhasse, Sébastien Doutreloup, Pierre-Vincent Huot, Charlotte Lang, Thierry Fichefet, and Xavier Fettweis
The Cryosphere, 15, 1215–1236, https://doi.org/10.5194/tc-15-1215-2021, https://doi.org/10.5194/tc-15-1215-2021, 2021
Short summary
Short summary
The future surface mass balance (SMB) of the Antarctic ice sheet (AIS) will influence the ice dynamics and the contribution of the ice sheet to the sea level rise. We investigate the AIS sensitivity to different warmings using physical and statistical downscaling of CMIP5 and CMIP6 models. Our results highlight a contrasting effect between the grounded ice sheet (where the SMB is projected to increase) and ice shelves (where the future SMB depends on the emission scenario).
Alison F. Banwell, Rajashree Tri Datta, Rebecca L. Dell, Mahsa Moussavi, Ludovic Brucker, Ghislain Picard, Christopher A. Shuman, and Laura A. Stevens
The Cryosphere, 15, 909–925, https://doi.org/10.5194/tc-15-909-2021, https://doi.org/10.5194/tc-15-909-2021, 2021
Short summary
Short summary
Ice shelves are thick floating layers of glacier ice extending from the glaciers on land that buttress much of the Antarctic Ice Sheet and help to protect it from losing ice to the ocean. However, the stability of ice shelves is vulnerable to meltwater lakes that form on their surfaces during the summer. This study focuses on the northern George VI Ice Shelf on the western side of the AP, which had an exceptionally long and extensive melt season in 2019/2020 compared to the previous 31 seasons.
Thomas Slater, Isobel R. Lawrence, Inès N. Otosaka, Andrew Shepherd, Noel Gourmelen, Livia Jakob, Paul Tepes, Lin Gilbert, and Peter Nienow
The Cryosphere, 15, 233–246, https://doi.org/10.5194/tc-15-233-2021, https://doi.org/10.5194/tc-15-233-2021, 2021
Short summary
Short summary
Satellite observations are the best method for tracking ice loss, because the cryosphere is vast and remote. Using these, and some numerical models, we show that Earth has lost 28 trillion tonnes (Tt) of ice since 1994 from Arctic sea ice (7.6 Tt), ice shelves (6.5 Tt), mountain glaciers (6.1 Tt), the Greenland (3.8 Tt) and Antarctic ice sheets (2.5 Tt), and Antarctic sea ice (0.9 Tt). It has taken just 3.2 % of the excess energy Earth has absorbed due to climate warming to cause this ice loss.
Jennifer F. Arthur, Chris R. Stokes, Stewart S. R. Jamieson, J. Rachel Carr, and Amber A. Leeson
The Cryosphere, 14, 4103–4120, https://doi.org/10.5194/tc-14-4103-2020, https://doi.org/10.5194/tc-14-4103-2020, 2020
Short summary
Short summary
Surface meltwater lakes can flex and fracture ice shelves, potentially leading to ice shelf break-up. A long-term record of lake evolution on Shackleton Ice Shelf is produced using optical satellite imagery and compared to surface air temperature and modelled surface melt. The results reveal that lake clustering on the ice shelf is linked to melt-enhancing feedbacks. Peaks in total lake area and volume closely correspond with intense snowmelt events rather than with warmer seasonal temperatures.
Martin Ménégoz, Evgenia Valla, Nicolas C. Jourdain, Juliette Blanchet, Julien Beaumet, Bruno Wilhelm, Hubert Gallée, Xavier Fettweis, Samuel Morin, and Sandrine Anquetin
Hydrol. Earth Syst. Sci., 24, 5355–5377, https://doi.org/10.5194/hess-24-5355-2020, https://doi.org/10.5194/hess-24-5355-2020, 2020
Short summary
Short summary
The study investigates precipitation changes in the Alps, using observations and a 7 km resolution climate simulation over 1900–2010. An increase in mean precipitation is found in winter over the Alps, whereas a drying occurred in summer in the surrounding plains. A general increase in the daily annual maximum of precipitation is evidenced (20 to 40 % per century), suggesting an increase in extreme events that is significant only when considering long time series, typically 50 to 80 years.
Kenneth D. Mankoff, Brice Noël, Xavier Fettweis, Andreas P. Ahlstrøm, William Colgan, Ken Kondo, Kirsty Langley, Shin Sugiyama, Dirk van As, and Robert S. Fausto
Earth Syst. Sci. Data, 12, 2811–2841, https://doi.org/10.5194/essd-12-2811-2020, https://doi.org/10.5194/essd-12-2811-2020, 2020
Short summary
Short summary
This work partitions regional climate model (RCM) runoff from the MAR and RACMO RCMs to hydrologic outlets at the ice margin and coast. Temporal resolution is daily from 1959 through 2019. Spatial grid is ~ 100 m, resolving individual streams. In addition to discharge at outlets, we also provide the streams, outlets, and basin geospatial data, as well as a script to query and access the geospatial or time series discharge data from the data files.
Xavier Fettweis, Stefan Hofer, Uta Krebs-Kanzow, Charles Amory, Teruo Aoki, Constantijn J. Berends, Andreas Born, Jason E. Box, Alison Delhasse, Koji Fujita, Paul Gierz, Heiko Goelzer, Edward Hanna, Akihiro Hashimoto, Philippe Huybrechts, Marie-Luise Kapsch, Michalea D. King, Christoph Kittel, Charlotte Lang, Peter L. Langen, Jan T. M. Lenaerts, Glen E. Liston, Gerrit Lohmann, Sebastian H. Mernild, Uwe Mikolajewicz, Kameswarrao Modali, Ruth H. Mottram, Masashi Niwano, Brice Noël, Jonathan C. Ryan, Amy Smith, Jan Streffing, Marco Tedesco, Willem Jan van de Berg, Michiel van den Broeke, Roderik S. W. van de Wal, Leo van Kampenhout, David Wilton, Bert Wouters, Florian Ziemen, and Tobias Zolles
The Cryosphere, 14, 3935–3958, https://doi.org/10.5194/tc-14-3935-2020, https://doi.org/10.5194/tc-14-3935-2020, 2020
Short summary
Short summary
We evaluated simulated Greenland Ice Sheet surface mass balance from 5 kinds of models. While the most complex (but expensive to compute) models remain the best, the faster/simpler models also compare reliably with observations and have biases of the same order as the regional models. Discrepancies in the trend over 2000–2012, however, suggest that large uncertainties remain in the modelled future SMB changes as they are highly impacted by the meltwater runoff biases over the current climate.
Baptiste Vandecrux, Ruth Mottram, Peter L. Langen, Robert S. Fausto, Martin Olesen, C. Max Stevens, Vincent Verjans, Amber Leeson, Stefan Ligtenberg, Peter Kuipers Munneke, Sergey Marchenko, Ward van Pelt, Colin R. Meyer, Sebastian B. Simonsen, Achim Heilig, Samira Samimi, Shawn Marshall, Horst Machguth, Michael MacFerrin, Masashi Niwano, Olivia Miller, Clifford I. Voss, and Jason E. Box
The Cryosphere, 14, 3785–3810, https://doi.org/10.5194/tc-14-3785-2020, https://doi.org/10.5194/tc-14-3785-2020, 2020
Short summary
Short summary
In the vast interior of the Greenland ice sheet, snow accumulates into a thick and porous layer called firn. Each summer, the firn retains part of the meltwater generated at the surface and buffers sea-level rise. In this study, we compare nine firn models traditionally used to quantify this retention at four sites and evaluate their performance against a set of in situ observations. We highlight limitations of certain model designs and give perspectives for future model development.
Kang Yang, Aleah Sommers, Lauren C. Andrews, Laurence C. Smith, Xin Lu, Xavier Fettweis, and Manchun Li
The Cryosphere, 14, 3349–3365, https://doi.org/10.5194/tc-14-3349-2020, https://doi.org/10.5194/tc-14-3349-2020, 2020
Short summary
Short summary
This study compares hourly supraglacial moulin discharge simulations from three surface meltwater routing models. Results show that these models are superior to simply using regional climate model runoff without routing, but different routing models, different-spatial-resolution DEMs, and parameterized seasonal evolution of supraglacial stream and river networks induce significant variability in diurnal moulin discharges and corresponding subglacial effective pressures.
Heiko Goelzer, Sophie Nowicki, Anthony Payne, Eric Larour, Helene Seroussi, William H. Lipscomb, Jonathan Gregory, Ayako Abe-Ouchi, Andrew Shepherd, Erika Simon, Cécile Agosta, Patrick Alexander, Andy Aschwanden, Alice Barthel, Reinhard Calov, Christopher Chambers, Youngmin Choi, Joshua Cuzzone, Christophe Dumas, Tamsin Edwards, Denis Felikson, Xavier Fettweis, Nicholas R. Golledge, Ralf Greve, Angelika Humbert, Philippe Huybrechts, Sebastien Le clec'h, Victoria Lee, Gunter Leguy, Chris Little, Daniel P. Lowry, Mathieu Morlighem, Isabel Nias, Aurelien Quiquet, Martin Rückamp, Nicole-Jeanne Schlegel, Donald A. Slater, Robin S. Smith, Fiamma Straneo, Lev Tarasov, Roderik van de Wal, and Michiel van den Broeke
The Cryosphere, 14, 3071–3096, https://doi.org/10.5194/tc-14-3071-2020, https://doi.org/10.5194/tc-14-3071-2020, 2020
Short summary
Short summary
In this paper we use a large ensemble of Greenland ice sheet models forced by six different global climate models to project ice sheet changes and sea-level rise contributions over the 21st century.
The results for two different greenhouse gas concentration scenarios indicate that the Greenland ice sheet will continue to lose mass until 2100, with contributions to sea-level rise of 90 ± 50 mm and 32 ± 17 mm for the high (RCP8.5) and low (RCP2.6) scenario, respectively.
Vincent Verjans, Amber A. Leeson, Christopher Nemeth, C. Max Stevens, Peter Kuipers Munneke, Brice Noël, and Jan Melchior van Wessem
The Cryosphere, 14, 3017–3032, https://doi.org/10.5194/tc-14-3017-2020, https://doi.org/10.5194/tc-14-3017-2020, 2020
Short summary
Short summary
Ice sheets are covered by a firn layer, which is the transition stage between fresh snow and ice. Accurate modelling of firn density properties is important in many glaciological aspects. Current models show disagreements, are mostly calibrated to match specific observations of firn density and lack thorough uncertainty analysis. We use a novel calibration method for firn models based on a Bayesian statistical framework, which results in improved model accuracy and in uncertainty evaluation.
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.
Arnold, N., K. Richards, Willis, I., and Sharp, M.: Initial results from a distributed, physically based model of glacier hydrology, Hydrol. Processes, 12, 191–219, https://doi.org/10.1002/(SICI)1099-1085(199802)12:2<191::AIDHYP571>3.0.CO;2-C, 1998.
Arnold, N. S.: A new approach for dealing with depressions in digital elevation models when calculating flow accumulation values, Prog. Phys. Geogr., 34, 781–809, https://doi.org/10.1177/0309133310384542, 2010.
Banwell, A. F., Arnold, N., Willis, I., Tedesco, M., and Ahlstrom, A.: Modelling supraglacial water routing and lake filling on the Greenland Ice Sheet, J. Geophys. Res., 117, F04012, https://doi.org/10.1029/2012JF002393, 2012a.
Banwell, A. F., Willis, I. C., Arnold, N. S., Messerli, A., Rye, C. J., and Ahlstrøm, A. P.: Calibration and validation of a high resolution surface mass balance model for Paakitsoq, west Greenland, J. Glaciol., 58, 1047–1062, https://doi.org/10.3189/2012JoG12J034, 2012b.
Banwell, A. F., Willis, I., and Arnold, N.: Modelling subglacial water routing at Paakitsoq, W Greenland, J. Geophys. Res.-Earth, 118, 1282–1295, https://doi.org/10.1002/jgrf.20093, 2013.
Banwell, A., Caballero, M., Arnold, N., Glasser, N., Mac Cathles, L., and MacAyeal, D.: Supraglacial lakes on the Larsen B ice shelf, Antarctica, and at Paakitsoq, West Greenland: A comparative study, Ann. Glaciol., 55, 1–8, https://doi.org/10.3189/2014AoG66A049, 2014.
Banwell, A. F., Hewitt, I., Willis, I., and Arnold, N.: Moulin density controls drainage development beneath the Greenland ice sheet, J. Geophys. Res., 121, 2248–2269, https://doi.org/10.1002/2015JF003801, 2016.
Buzzard, S. C., Feltham, D. L., and Flocco, D.: A mathematical model of melt lake development on an ice shelf, J. Adv. Model. Earth Sy., 10, 262–283, https://doi.org/10.1002/2017MS001155, 2017.
Candela, S. G., Howat, I., Noh, M. J., Porter C. C., and Morin, P. J.: ArcticDEM validation and accuracy assessment, C51A Altimetry of the Polar Regions III, American Geophysical Union Fall Meeting, New Orleans, 2017AGUFM.C51A0951C, 2017.
Catania, G. A., Neumann, T. A., and Price, S. F.: Characterizing englacial drainage in the ablation zone of the Greenland ice sheet, J. Glaciol., 54, 567–578, https://doi.org/10.3189/002214308786570854, 2008.
Christoffersen, P., Bougamont, M., Hubbard, A., Doyle, S. H., Grigsby, S., and Pettersson, R.: Cascading lake drainage on the Greenland Ice Sheet triggered by tensile shock and fracture, Nat. Commun., 9, 1064, https://doi.org/10.1038/s41467-018-03420-8, 2018.
Clason, C., Mair, D. W. F., Burgess, D. O., and Nienow, P.: Modelling the delivery of supraglacial meltwater to the ice/bed interface: application to southwest Devon Ice Cap, Nunavut, Canada, J. Glaciol., 58, 208, https://doi.org/10.3189/2012JoG11J129, 2012.
Clason, C. C., Mair, D. W. F., Nienow, P. W., Bartholomew, I. D., Sole, A., Palmer, S., and Schwanghart, W.: Modelling the transfer of supraglacial meltwater to the bed of Leverett Glacier, Southwest Greenland, The Cryosphere, 9, 123–138, https://doi.org/10.5194/tc-9-123-2015, 2015.
Cooley, S. W. and, Christoffersen, P.: Observation bias correction reveals more rapidly draining lakes on the Greenland Ice Sheet, J. Geophys. Res.-Earth, 122, 1867–1881, https://doi.org/10.1002/2017JF004255, 2017.
Colbeck, S. C.: The physical aspects of water flow through snow, in Advances in Hydroscience, vol. 11, edited by: Chow, V. T., Academic, San Diego, Calif, 165–206, ISBN 9780120218110, 1978.
Colgan, W. and Steffen, K.: Modelling the spatial distribution of moulins near Jakobshavn, Greenland, IOP Conf. Ser.-Earth Environ. Sci., 6, 012022, https://doi.org/10.1088/1755-1307/6/1/012022, 2009.
Das, S. B., Joughin, I., Behn, M. D., Howat, I. M., King, M., Lizarralde, D., and Bhatia, M. P.: Fracture propagation to the base of the Greenland Ice Sheet during supraglacial lake drainage, Science, 320, 778–781, https://doi.org/10.1126/science.1153360, 2008.
Doyle, S. H., Hubbard, A. L., Fitzpatrick, A. A. W., Van As, D., Mikkelsen, A., Pettersson, R., and Hubbard, B. P.: Persistent flow acceleration within the interior of the Greenland Ice Sheet, Geophys. Res. Lett., 41, 899–905, https://doi.org/10.1002/2013GL058933, 2014.
Duguay, C. R., Flato, G. M., Jeffries, M. O., Menard, P., Morris, K., and Rouse, W. R.: Ice-cover variability on shallow lakes at high latitudes: model simulations and observations, Hydrol. Proccess., 17, 3465–3483, https://doi.org/10.1002/hyp.1394, 2003.
Ebert, E. and Curry, J.: An intermediate one-dimensional thermodynamic sea ice model for investigating ice-atmosphere interactions, J. Geophys. Res.-Oceans, 98, 10085–10109, 1993.
Fettweis, X., Hanna, E., Gallée, H., Huybrechts, P., and Erpicum, M.: Estimation of the Greenland ice sheet surface mass balance for the 20th and 21st centuries, The Cryosphere, 2, 117–129, https://doi.org/10.5194/tc-2-117-2008, 2008.
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.
Fischer, M. P., Alley, R. B., and Engelder, T.: Fracture toughness of ice and firn determined from the modified ring test, J. Glaciol., 41, 383–394, 1995.
Fitzpatrick, A. A. W., Hubbard, A. L., Box, J. E., Quincey, D. J., van As, D., Mikkelsen, A. P. B., Doyle, S. H., Dow, C. F., Hasholt, B., and Jones, G. A.: A decade (2002–2012) of supraglacial lake volume estimates across Russell Glacier, West Greenland, The Cryosphere, 8, 107–121, https://doi.org/10.5194/tc-8-107-2014, 2014.
Gantayat, P., Banwell, A., Leeson, A., Lea, J. M., Petersen, D., Gourmelen, N., and Fettweis, X.: A new hydrological model to simulate supraglacial lake evolution and meltwater drainage on the Greenland Ice Sheet (Version 1), Zenodo [code]. https://doi.org/10.5281/zenodo.7633220, 2022.
Gantayat, P., Banwell, A. F., Leeson, A. A., Lea, J. M., Petersen, D., Gourmelen, N., and Fettweis, X.: Model data for region 1. Zenodo [data set], https://zenodo.org/record/7652297, 2023a.
Gantayat, P., Banwell, A. F., Leeson, A. A., Lea, J. M., Petersen, D., Gourmelen, N., and Fettweis, X.: Data used for region 3, Zenodo [data set],https://zenodo.org/record/7652634, 2023b.
Georgiou, S., Shepherd, A., McMillan, M., and Nienow, P.: Seasonal evolution of supraglacial lake volume from ASTER imagery, Ann. Glaciol., 50, 95–100, https://doi.org/10.3189/172756409789624328, 2009.
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P. , Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu. C., Radnoti, G., de Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J.: The ERA5 global reanalysis, Q. J. Roy. Meteor. Soc., 146, 1999–2049, 2020.
Hill, T. and Dow, C. F.: Modelling the dynamics of supraglacial rivers and distributed meltwater flow with the Subaerial Drainage System (SaDS) model, J. Geophys. Res.-Earth, 126, e2021JF006309, https://doi.org/10.1029/2021JF006309, 2021.
Hoffman, M. J., Perego, M., Andrews, L. C., Price, S. F., Neumann, T. A., Johnson, J. V., and Lüthi, M. P.: Widespread moulin formation during supraglacial lake drainages in Greenland, Geophys. Res. Lett., 45, 778–788, https://doi.org/10.1002/2017GL075659, 2018.
Joughin, I., Smith, B., Howat, I., and Scambos, T.: MEaSUREs Greenland Ice Sheet Velocity Map from InSAR Data, Version 2, Boulder, Colorado USA, NASA National Snow and Ice Data Center Distributed Active Archive Center [data set], https://doi.org/10.5067/OC7B04ZM9G6Q, 2015.
Joughin, I., Smith, B., Howat, I., and Scambos, T.: MEaSUREs Greenland Ice Sheet Velocity Map from InSAR Data, Version 2, Boulder, Colorado USA, NASA National Snow and Ice Data Center Distributed Active Archive Center [data set], https://doi.org/10.5067/OC7B04ZM9G6Q, 2018.
Karlstrom, L. and Yang, K.: Fluvial supraglacial landscape evolution on the Greenland Ice Sheet, Geophys. Res. Lett., 43, 2683–2692, 2016.
Kingslake, J., Ng, F., and Sole, A.: Modelling channelized surface drainage of supraglacial lakes, J. Glaciol., 61, 225, https://doi.org/10.3189/2015JoG14J158, 2015.
Koenig, L. S., Lampkin, D. J., Montgomery, L. N., Hamilton, S. L., Turrin, J. B., Joseph, C. A., Moutsafa, S. E., Panzer, B., Casey, K. A., Paden, J. D., Leuschen, C., and Gogineni, P.: Wintertime storage of water in buried supraglacial lakes across the Greenland Ice Sheet, The Cryosphere, 9, 1333–1342, https://doi.org/10.5194/tc-9-1333-2015, 2015.
Koziol, C., Arnold, N., Pope, A., and Colgan, W.: Quantifying supraglacial meltwater pathways in the Paakitsoq region, West Greenland, J. Glaciol., 63, 464–476, 2017.
Krawczynski, M. J., Behn, M. D., Das, S. B., and Joughin, I.: Constraints on the lake volume required for hydro-fracture through ice sheets, Geophys. Res. Lett., 36, L10501, https://doi.org/10.1029/2008GL036765, 2009.
Law, R., Arnold, N., benedek, C., Tedesco, M., Banwell, A. F., and Willis, I.: Overwinter persistence of supraglacial lakes on the Greenland Ice Sheet: results and insights from a new model, J. Glaciol., 66, 362–372, https://doi.org/10.1017/jog.2020.7, 2020.
Lea, J. L.: Daily lake area delineated from MODIS using GEEDiT for the year 2019 (Version 1), Zenodo [data set], https://doi.org/10.5281/zenodo.7464796, 2022.
Leeson, A. A., Shepherd, A., Palmer, S., Sundal, A., and Fettweis, X.: Simulating the growth of supraglacial lakes at the western margin of the Greenland ice sheet, The Cryosphere, 6, 1077–1086, https://doi.org/10.5194/tc-6-1077-2012, 2012.
Luthje, M., Pedersen, L., Reeh, N., and Greuell, W.: Modelling the evolution of supraglacial lakes on the West Greenland ice-sheet margin, J. Glaciol., 52, 608–618, 2006.
Manning, R.: On the flow of water in open channels and pipes, Transactions, Institution of Civil Engineers of Ireland, 20, 161–207, 1891.
McKay, C., Clow, G., Anderson, D., and Wharton Jr., R.: Light transmission and reflection in perennially ice-covered Lake Hoare, Antarctica, J. Geophys. Res.-Oceans, 99, 20427–20444, 1994.
Miles, K. E., Willis, I. C., Benedek, C. L., Williamson, A. G., and Tedesco, M.: Toward Monitoring Surface and Subsurface Lakes on the Greenland Ice Sheet Using Sentinel-1 SAR and Landsat-8 OLI Imagery, Front. Earth Sci., 5, 58, https://doi.org/10.3389/feart.2017.00058, 2017.
Mouginot, J., Rignot, E., Bjork, A. A., van den Broeke, M., Morlighem, M., Noel, 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.
Nicholson, L. and Benn, D. I.: Calculating ice melt beneath a debris layer using meteorological data, J. Glaciol., 52, 463–470, https://doi.org/10.3189/172756506781828584, 2006.
Petersen, D.: Measured discharge data for region 1 and region 2, Zenodo [data set], https://doi.org/10.997/zenodo.7655412, 2023.
Porter, Cl., Morin, P., Howat, I., Noh, M., Bates, B., Peterman, K., Keesey, S., Schlenk, M., Gardiner, J., Tomko, K., Willis, M., Kelleher, C., Cloutier, M., Husby, E., Foga, S., Nakamura, H., Platson, M., Wethington, M., Williamson, C., Bauer, G., Enos, J., Arnold, G., Kramer, W., Becker, P., Doshi, A., D'Souza, C., Cummens, P., Laurier, F., and Bojesen, M.: ArcticDEM, Harvard Dataverse v2.0 [data set], https://doi.org/10.7910/DVN/OHHUKH, 2018.
Rist, M. A., Sammonds, P. R., Murrel, S. A. F., Meredith, P. G., Doake, C. S. M., Oerter, H., and Matsuki, K.: Experimental fracture and mechanical properties of Antarctic ice: preliminary results, J. Geophys. Res., 104, 2973–2987, 1999.
Schoof, C.: Ice-sheet acceleration driven by melt supply variability, Nature, 468, 803–806, https://doi.org/10.1038/nature09618, 2010.
Selmes, N., Murray, T., and James, T. D.: Fast draining lakes of Greenland Ice Sheet, Geophys. Res. Lett., 38, L15501, https://doi.org/10.1029/2011GL047872, 2011.
Smith, B., Fricker, H. A., Gardner, A. S., Medley, B., Nilsson, J., Fernando, S. P., 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.
Smith, L. C., Chu, V. W., Yang, K., Gleason, C. J., Pitcher, L. H., Rennermalm, A. K., Legleiter, C. J., Behar, A. E., Overstreet, B. T., Moustafa, S. E., Tedesco, M., Forster, R. R., LeWinter, A. L., Finnegan, D. C., Sheng, Y., and Balog, J.: Efficient meltwater drainage through supraglacial streams and rivers on the southwest Greenland ice sheet, P. Natl. Acad. Sci. USA, 112, 1001–1006, https://doi.org/10.1073/pnas.1413024112, 2015.
Taylor, P. and Feltham, D.: A model of melt pond evolution on sea ice, J. Geophys. Res.-Oceans, 109, C12007, https://doi.org/10.1029/2004JC002361, 2004.
Tedesco, M., Willis, I. C., Hoffman, M. J., Banwell, A. F., Alexander, P., and Arnold, N. S.: Ice dynamic response to two modes of surface lake drainage on the Greenland ice sheet, Environ. Res. Lett., 8, 034007, https://doi.org/10.1088/1748-9326/8/3/034007, 2013.
The IMBIE Team: Mass balance of the Greenland Ice Sheet from 1992 to 2018, Nature, 579, 233–239 https://doi.org/10.1038/s41586-019-1855-2, 2020.
USGS (U.S. Geological Survey): EarthExplorer, https://earthexplorer.usgs.gov, last access: 10 October 2023.
van der Veen, C. J.: Fracture propagation as means of rapidly transferring surface meltwater to the base of glaciers, Geophys. Res. Lett., 34, L01501, https://doi.org/10.1029/2006GL028385, 2008.
Vaughan, D. G.: Relating the occurrence of crevasses to surface strain rates, J. Glaciol., 39, 255–266, 1993.
Williamson, A. G., Arnold, N. S., Banwell, A. F., and Willis, I. C.: A Fully Automated Supraglacial lake area and volume Tracking (“FAST”) algorithm: Development and application using MODIS imagery of West Greenland, Remote Sens. Environ., 196, 113–133, https://doi.org/10.1016/j.rse.2017.04.032, 2017.
Williamson, A. G., Banwell, A. F., Willis, I. C., and Arnold, N. S.: Dual-satellite (Sentinel-2 and Landsat 8) remote sensing of supraglacial lakes in Greenland, The Cryosphere, 12, 3045–3065, https://doi.org/10.5194/tc-12-3045-2018, 2018a.
Williamson, A. G., Willis, I. C., Arnold, N. S., and Banwell, A. F.: Controls on rapid supraglacial lake drainage in West Greenland: An Exploratory Data Analysis approach, J. Glaciol., 64, 208–226, https://doi.org/10.1017/jog.2018.8, 2018b.
Yang, K., Smith, L. C., Karlstrom, L., Cooper, M. G., Tedesco, M., van As, D., Cheng, X., Chen, Z., and Li, M.: A new surface meltwater routing model for use on the Greenland Ice Sheet surface, The Cryosphere, 12, 3791–3811, https://doi.org/10.5194/tc-12-3791-2018, 2018.
Zwally, H. J., Abdalati, W., herring, T., Larson, K., Saba, J., and Steffen, K.: Surface melt-induced acceleration of Greenland ice sheet flow, Science, 297, 218–222, https://doi.org/10.1126/science.1072708, 2002.
Short summary
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.
We developed a new supraglacial hydrology model for the Greenland Ice Sheet. This model...
