Articles | Volume 12, issue 4
https://doi.org/10.5194/essd-12-2811-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-12-2811-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
14 Nov 2020
Data description paper |
| 14 Nov 2020
| 14 Nov 2020
Greenland liquid water discharge from 1958 through 2019
Department of Glaciology and Climate, Geological Survey of Denmark and Greenland (GEUS), Copenhagen, Denmark
Brice Noël
Institute for Marine and Atmospheric Research, Utrecht University, Utrecht, the Netherlands
Xavier Fettweis
SPHERES research unit, Department of Geography, University of Liège,
Liège, Belgium
Andreas P. Ahlstrøm
Department of Glaciology and Climate, Geological Survey of Denmark and Greenland (GEUS), Copenhagen, Denmark
William Colgan
Department of Glaciology and Climate, Geological Survey of Denmark and Greenland (GEUS), Copenhagen, Denmark
Ken Kondo
Institute of Low Temperature Science, Hokkaido University, Sapporo, Japan
Kirsty Langley
Asiaq – Greenland Survey, Nuuk, Greenland
Shin Sugiyama
Institute of Low Temperature Science, Hokkaido University, Sapporo, Japan
Dirk van As
Department of Glaciology and Climate, Geological Survey of Denmark and Greenland (GEUS), Copenhagen, Denmark
Robert S. Fausto
Department of Glaciology and Climate, Geological Survey of Denmark and Greenland (GEUS), Copenhagen, Denmark
Related authors
Shfaqat A. Khan, Helene Seroussi, Mathieu Morlighem, William Colgan, Veit Helm, Gong Cheng, Danjal Berg, Valentina R. Barletta, Nicolaj K. Larsen, William Kochtitzky, Michiel van den Broeke, Kurt H. Kjær, Andy Aschwanden, Brice Noël, Jason E. Box, Joseph A. MacGregor, Robert S. Fausto, Kenneth D. Mankoff, Ian M. Howat, Kuba Oniszk, Dominik Fahrner, Anja Løkkegaard, Eigil Y. H. Lippert, Alicia Bråtner, and Javed Hassan
Earth Syst. Sci. Data, 17, 3047–3071, https://doi.org/10.5194/essd-17-3047-2025, https://doi.org/10.5194/essd-17-3047-2025, 2025
Short summary
Short summary
The surface elevation of the Greenland Ice Sheet is changing due to surface mass balance processes and ice dynamics, each exhibiting distinct spatiotemporal patterns. Here, we employ satellite and airborne altimetry data with fine spatial (1 km) and temporal (monthly) resolutions to document this spatiotemporal evolution from 2003 to 2023. This dataset of fine-resolution altimetry data in both space and time will support studies of ice mass loss and be useful for GIS ice sheet modeling.
Gavin A. Schmidt, Kenneth D. Mankoff, Jonathan L. Bamber, Dustin Carroll, David M. Chandler, Violaine Coulon, Benjamin J. Davison, Matthew H. England, Paul R. Holland, Nicolas C. Jourdain, Qian Li, Juliana M. Marson, Pierre Mathiot, Clive R. McMahon, Twila A. Moon, Ruth Mottram, Sophie Nowicki, Anne Olivé Abelló, Andrew G. Pauling, Thomas Rackow, and Damien Ringeisen
EGUsphere, https://doi.org/10.5194/egusphere-2025-1940, https://doi.org/10.5194/egusphere-2025-1940, 2025
Short summary
Short summary
The impact of increasing mass loss from the Greenland and Antarctic ice sheets has not so far been included in historical climate model simulations. This paper describes the protocols and data available for modeling groups to add this anomalous freshwater to their ocean modules to better represent the impacts of these fluxes on ocean circulation, sea ice, salinity and sea level.
Mai Winstrup, Heidi Ranndal, Signe Hillerup Larsen, Sebastian B. Simonsen, Kenneth D. Mankoff, Robert S. Fausto, and Louise Sandberg Sørensen
Earth Syst. Sci. Data, 16, 5405–5428, https://doi.org/10.5194/essd-16-5405-2024, https://doi.org/10.5194/essd-16-5405-2024, 2024
Short summary
Short summary
Surface topography across the marginal zone of the Greenland Ice Sheet is constantly evolving. Here we present an annual series (2019–2022) of summer digital elevation models (PRODEMs) for the Greenland Ice Sheet margin, covering all outlet glaciers from the ice sheet. The PRODEMs are based on fusion of CryoSat-2 radar altimetry and ICESat-2 laser altimetry. With their high spatial and temporal resolution, the PRODEMs will enable detailed studies of the changes in marginal ice sheet elevations.
Anja Løkkegaard, Kenneth D. Mankoff, Christian Zdanowicz, Gary D. Clow, Martin P. Lüthi, Samuel H. Doyle, Henrik H. Thomsen, David Fisher, Joel Harper, Andy Aschwanden, Bo M. Vinther, Dorthe Dahl-Jensen, Harry Zekollari, Toby Meierbachtol, Ian McDowell, Neil Humphrey, Anne Solgaard, Nanna B. Karlsson, Shfaqat A. Khan, Benjamin Hills, Robert Law, Bryn Hubbard, Poul Christoffersen, Mylène Jacquemart, Julien Seguinot, Robert S. Fausto, and William T. Colgan
The Cryosphere, 17, 3829–3845, https://doi.org/10.5194/tc-17-3829-2023, https://doi.org/10.5194/tc-17-3829-2023, 2023
Short summary
Short summary
This study presents a database compiling 95 ice temperature profiles from the Greenland ice sheet and peripheral ice caps. Ice viscosity and hence ice flow are highly sensitive to ice temperature. To highlight the value of the database in evaluating ice flow simulations, profiles from the Greenland ice sheet are compared to a modeled temperature field. Reoccurring discrepancies between modeled and observed temperatures provide insight on the difficulties faced when simulating ice temperatures.
William Colgan, Christopher Shields, Pavel Talalay, Xiaopeng Fan, Austin P. Lines, Joshua Elliott, Harihar Rajaram, Kenneth Mankoff, Morten Jensen, Mira Backes, Yunchen Liu, Xianzhe Wei, Nanna B. Karlsson, Henrik Spanggård, and Allan Ø. Pedersen
Geosci. Instrum. Method. Data Syst., 12, 121–140, https://doi.org/10.5194/gi-12-121-2023, https://doi.org/10.5194/gi-12-121-2023, 2023
Short summary
Short summary
We describe a new drill for glaciers and ice sheets. Instead of drilling down into the ice, via mechanical action, our drill melts into the ice. Our goal is simply to pull a cable of temperature sensors on a one-way trip down to the ice–bed interface. Here, we describe the design and testing of our drill. Under laboratory conditions, our melt-tip drill has an efficiency of ∼ 35 % with a theoretical maximum penetration rate of ∼ 12 m h−1. Under field conditions, our efficiency is just ∼ 15 %.
Eva Friis Møller, Asbjørn Christensen, Janus Larsen, Kenneth D. Mankoff, Mads Hvid Ribergaard, Mikael Sejr, Philip Wallhead, and Marie Maar
Ocean Sci., 19, 403–420, https://doi.org/10.5194/os-19-403-2023, https://doi.org/10.5194/os-19-403-2023, 2023
Short summary
Short summary
Melt from the Greenland ice sheet and sea ice both influence light and nutrient availability in the Arctic coastal ocean. We use a 3D coupled hydrodynamic–biogeochemical model to evaluate the relative importance of these processes for timing, distribution, and magnitude of phytoplankton production in Disko Bay, west Greenland. Our study indicates that decreasing sea ice and more freshwater discharge can work synergistically and increase primary productivity of the coastal ocean around Greenland.
Mimmi Oksman, Anna Bang Kvorning, Signe Hillerup Larsen, Kristian Kjellerup Kjeldsen, Kenneth David Mankoff, William Colgan, Thorbjørn Joest Andersen, Niels Nørgaard-Pedersen, Marit-Solveig Seidenkrantz, Naja Mikkelsen, and Sofia Ribeiro
The Cryosphere, 16, 2471–2491, https://doi.org/10.5194/tc-16-2471-2022, https://doi.org/10.5194/tc-16-2471-2022, 2022
Short summary
Short summary
One of the questions facing the cryosphere community today is how increasing runoff from the Greenland Ice Sheet impacts marine ecosystems. To address this, long-term data are essential. Here, we present multi-site records of fjord productivity for SW Greenland back to the 19th century. We show a link between historical freshwater runoff and productivity, which is strongest in the inner fjord – influenced by marine-terminating glaciers – where productivity has increased since the late 1990s.
William Colgan, Agnes Wansing, Kenneth Mankoff, Mareen Lösing, John Hopper, Keith Louden, Jörg Ebbing, Flemming G. Christiansen, Thomas Ingeman-Nielsen, Lillemor Claesson Liljedahl, Joseph A. MacGregor, Árni Hjartarson, Stefan Bernstein, Nanna B. Karlsson, Sven Fuchs, Juha Hartikainen, Johan Liakka, Robert S. Fausto, Dorthe Dahl-Jensen, Anders Bjørk, Jens-Ove Naslund, Finn Mørk, Yasmina Martos, Niels Balling, Thomas Funck, Kristian K. Kjeldsen, Dorthe Petersen, Ulrik Gregersen, Gregers Dam, Tove Nielsen, Shfaqat A. Khan, and Anja Løkkegaard
Earth Syst. Sci. Data, 14, 2209–2238, https://doi.org/10.5194/essd-14-2209-2022, https://doi.org/10.5194/essd-14-2209-2022, 2022
Short summary
Short summary
We assemble all available geothermal heat flow measurements collected in and around Greenland into a new database. We use this database of point measurements, in combination with other geophysical datasets, to model geothermal heat flow in and around Greenland. Our geothermal heat flow model is generally cooler than previous models of Greenland, especially in southern Greenland. It does not suggest any high geothermal heat flows resulting from Icelandic plume activity over 50 million years ago.
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.
Robert S. Fausto, Dirk van As, Kenneth D. Mankoff, Baptiste Vandecrux, Michele Citterio, Andreas P. Ahlstrøm, Signe B. Andersen, William Colgan, Nanna B. Karlsson, Kristian K. Kjeldsen, Niels J. Korsgaard, Signe H. Larsen, Søren Nielsen, Allan Ø. Pedersen, Christopher L. Shields, Anne M. Solgaard, and Jason E. Box
Earth Syst. Sci. Data, 13, 3819–3845, https://doi.org/10.5194/essd-13-3819-2021, https://doi.org/10.5194/essd-13-3819-2021, 2021
Short summary
Short summary
The Programme for Monitoring of the Greenland Ice Sheet (PROMICE) has been measuring climate and ice sheet properties since 2007. Here, we present our data product from weather and ice sheet measurements from a network of automatic weather stations mainly located in the melt area of the ice sheet. Currently the PROMICE automatic weather station network includes 25 instrumented sites in Greenland.
Anne Solgaard, Anders Kusk, John Peter Merryman Boncori, Jørgen Dall, Kenneth D. Mankoff, Andreas P. Ahlstrøm, Signe B. Andersen, Michele Citterio, Nanna B. Karlsson, Kristian K. Kjeldsen, Niels J. Korsgaard, Signe H. Larsen, and Robert S. Fausto
Earth Syst. Sci. Data, 13, 3491–3512, https://doi.org/10.5194/essd-13-3491-2021, https://doi.org/10.5194/essd-13-3491-2021, 2021
Short summary
Short summary
The PROMICE Ice Velocity product is a time series of Greenland Ice Sheet ice velocity mosaics spanning September 2016 to present. It is derived from Sentinel-1 SAR data and has a spatial resolution of 500 m. Each mosaic spans 24 d (two Sentinel-1 cycles), and a new one is posted every 12 d (every Sentinel-1A cycle). The spatial comprehensiveness and temporal consistency make the product ideal for monitoring and studying ice-sheet-wide ice discharge and dynamics of glaciers.
Mikkel Langgaard Lauritzen, Anne Solgaard, Nicholas Mossor Rathmann, Bo Møllesøe Vinther, Aslak Grindsted, Brice Noël, Guðfinna Aðalgeirsdóttir, and Christine Schøtt Hvidberg
The Cryosphere, 19, 3599–3622, https://doi.org/10.5194/tc-19-3599-2025, https://doi.org/10.5194/tc-19-3599-2025, 2025
Short summary
Short summary
We studied the Holocene (past 11 700 years) to understand how the Greenland Ice Sheet has changed. Using 841 computer simulations, we tested different scenarios and matched them to historical ice elevation data, confirming our model's accuracy. Results show that Greenland's melting has raised sea levels by about 5.3 m since the Holocene began and by around 12 mm in just the past 500 years.
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.
Gregor Luetzenburg, Niels J. Korsgaard, Anna K. Deichmann, Tobias Socher, Karin Gleie, Thomas Scharffenberger, Rasmus P. Meyer, Dominik Fahrner, Eva B. Nielsen, Penelope How, Anders A. Bjørk, Kristian K. Kjeldsen, Andreas P. Ahlstrøm, and Robert S. Fausto
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-415, https://doi.org/10.5194/essd-2025-415, 2025
Preprint under review for ESSD
Short summary
Short summary
We mapped the edge of the Greenland Ice Sheet using recent satellite images to create a detailed outline of its extent in 2022. This helps track how the ice sheet is changing as the climate warms. By carefully combining satellite data and checking results by hand, we created one of the most accurate maps of the ice sheet to date. This map supports research on ice loss and improves predictions of future changes in Greenland’s ice and its effect on the planet.
Shfaqat A. Khan, Helene Seroussi, Mathieu Morlighem, William Colgan, Veit Helm, Gong Cheng, Danjal Berg, Valentina R. Barletta, Nicolaj K. Larsen, William Kochtitzky, Michiel van den Broeke, Kurt H. Kjær, Andy Aschwanden, Brice Noël, Jason E. Box, Joseph A. MacGregor, Robert S. Fausto, Kenneth D. Mankoff, Ian M. Howat, Kuba Oniszk, Dominik Fahrner, Anja Løkkegaard, Eigil Y. H. Lippert, Alicia Bråtner, and Javed Hassan
Earth Syst. Sci. Data, 17, 3047–3071, https://doi.org/10.5194/essd-17-3047-2025, https://doi.org/10.5194/essd-17-3047-2025, 2025
Short summary
Short summary
The surface elevation of the Greenland Ice Sheet is changing due to surface mass balance processes and ice dynamics, each exhibiting distinct spatiotemporal patterns. Here, we employ satellite and airborne altimetry data with fine spatial (1 km) and temporal (monthly) resolutions to document this spatiotemporal evolution from 2003 to 2023. This dataset of fine-resolution altimetry data in both space and time will support studies of ice mass loss and be useful for GIS ice sheet modeling.
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.
Gavin A. Schmidt, Kenneth D. Mankoff, Jonathan L. Bamber, Dustin Carroll, David M. Chandler, Violaine Coulon, Benjamin J. Davison, Matthew H. England, Paul R. Holland, Nicolas C. Jourdain, Qian Li, Juliana M. Marson, Pierre Mathiot, Clive R. McMahon, Twila A. Moon, Ruth Mottram, Sophie Nowicki, Anne Olivé Abelló, Andrew G. Pauling, Thomas Rackow, and Damien Ringeisen
EGUsphere, https://doi.org/10.5194/egusphere-2025-1940, https://doi.org/10.5194/egusphere-2025-1940, 2025
Short summary
Short summary
The impact of increasing mass loss from the Greenland and Antarctic ice sheets has not so far been included in historical climate model simulations. This paper describes the protocols and data available for modeling groups to add this anomalous freshwater to their ocean modules to better represent the impacts of these fluxes on ocean circulation, sea ice, salinity and sea level.
Nicole A. Loeb, Alex Crawford, Brice Noël, and Julienne Stroeve
EGUsphere, https://doi.org/10.5194/egusphere-2025-995, https://doi.org/10.5194/egusphere-2025-995, 2025
Short summary
Short summary
This study examines how extreme precipitation days affect the seasonal mass balance (SMB) of land ice in Greenland and the Eastern Canadian Arctic in historical and future simulations. Past extreme precipitation led to higher SMB with snowfall. As temperatures rise, extreme precipitation may lead to the loss of ice mass as more extreme precipitation falls as rain rather than snow. Across the region, extreme precipitation becomes more important to seasonal SMB in the future, warmer climate.
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.
Penelope How, Dorthe Petersen, Kristian Kjellerup Kjeldsen, Katrine Raundrup, Nanna Bjørnholt Karlsson, Alexandra Messerli, Anja Rutishauser, Jonathan Lee Carrivick, James M. Lea, Robert Schjøtt Fausto, Andreas Peter Ahlstrøm, and Signe Bech Andersen
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-18, https://doi.org/10.5194/essd-2025-18, 2025
Revised manuscript under review for ESSD
Short summary
Short summary
Ice-marginal lakes around Greenland temporarily store glacial meltwater, affecting sea level rise, glacier dynamics and ecosystems. Our study presents an eight-year inventory (2016–2023) of 2918 lakes, mapping their size, abundance, and surface water temperature. This openly available dataset supports future research on sea level projections, lake-driven glacier melting, and sustainable resource planning, including hydropower development under Greenland's climate commitments.
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.
Shin Sugiyama, Shun Tsutaki, Daiki Sakakibara, Izumi Asaji, Ken Kondo, Yefan Wang, Evgeny Podolskiy, Guillaume Jouvet, and Martin Funk
The Cryosphere, 19, 525–540, https://doi.org/10.5194/tc-19-525-2025, https://doi.org/10.5194/tc-19-525-2025, 2025
Short summary
Short summary
We report flow speed variations near the front of a tidewater glacier in Greenland. Ice flow near the glacier front is crucial for the mass loss of the Greenland ice sheet, but in situ data are hard to obtain. Our unique in situ GPS data revealed fine details of short-term speed variations associated with melting, ocean tides, and rain. The results are important for understanding the response of tidewater glaciers to changing environments, such as warming, more frequent rain, and ice thinning.
Anneke Louise Vries, Willem Jan van de Berg, Brice Noël, Lorenz Meire, and Michiel R. van den Broeke
EGUsphere, https://doi.org/10.5194/egusphere-2024-3735, https://doi.org/10.5194/egusphere-2024-3735, 2025
Short summary
Short summary
Freshwater enters Greenland's fjords from various sources. Solid ice discharge dominates freshwater input into fjords in the southeast and northwest. In contrast, in the southwest, runoff from the ice sheet and tundra are most significant. Seasonally resolved data revealed that fjord precipitation and tundra runoff contribute up to 11 % and 35 % of the total freshwater influx, respectively. Our results provide valuable input for ocean models and for researchers studying fjord ecosystems.
Jorrit van der Schot, Jakob Abermann, Tiago Silva, Kerstin Rasmussen, Michael Winkler, Kirsty Langley, and Wolfgang Schöner
The Cryosphere, 18, 5803–5823, https://doi.org/10.5194/tc-18-5803-2024, https://doi.org/10.5194/tc-18-5803-2024, 2024
Short summary
Short summary
We present snow data from nine locations in coastal Greenland. We show that a reanalysis product (CARRA) simulates seasonal snow characteristics better than a regional climate model (RACMO). CARRA output matches particularly well with our reference dataset when we look at the maximum snow water equivalent and the snow cover end date. We show that seasonal snow in coastal Greenland has large spatial and temporal variability and find little evidence of trends in snow cover characteristics.
Mai Winstrup, Heidi Ranndal, Signe Hillerup Larsen, Sebastian B. Simonsen, Kenneth D. Mankoff, Robert S. Fausto, and Louise Sandberg Sørensen
Earth Syst. Sci. Data, 16, 5405–5428, https://doi.org/10.5194/essd-16-5405-2024, https://doi.org/10.5194/essd-16-5405-2024, 2024
Short summary
Short summary
Surface topography across the marginal zone of the Greenland Ice Sheet is constantly evolving. Here we present an annual series (2019–2022) of summer digital elevation models (PRODEMs) for the Greenland Ice Sheet margin, covering all outlet glaciers from the ice sheet. The PRODEMs are based on fusion of CryoSat-2 radar altimetry and ICESat-2 laser altimetry. With their high spatial and temporal resolution, the PRODEMs will enable detailed studies of the changes in marginal ice sheet elevations.
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.
Signe Hillerup Larsen, Daniel Binder, Anja Rutishauser, Bernhard Hynek, Robert Schjøtt Fausto, and Michele Citterio
Earth Syst. Sci. Data, 16, 4103–4118, https://doi.org/10.5194/essd-16-4103-2024, https://doi.org/10.5194/essd-16-4103-2024, 2024
Short summary
Short summary
The Greenland Ecosystem Monitoring programme has been running since 1995. In 2008, the Glaciological monitoring sub-program GlacioBasis was initiated at the Zackenberg site in northeast Greenland, with a transect of three weather stations on the A. P. Olsen Ice Cap. In 2022, the weather stations were replaced with a more standardized set up. Here, we provide the reprocessed and quality-checked data from 2008 to 2022, i.e., the first 15 years of continued monitoring.
Xueyu Zhang, Lin Liu, Brice Noël, and Zhicai Luo
EGUsphere, https://doi.org/10.5194/egusphere-2024-1726, https://doi.org/10.5194/egusphere-2024-1726, 2024
Preprint archived
Short summary
Short summary
This study indicates that the overall characteristics of the upper firn density in the percolation zone could be captured by the choice of appropriate model configurations and climatic forcing, which is necessary for understanding the current mass balance of the GrIS and predicting its future. The modelled firn density in this study generally aligns well with observations from 16 cores, with the relative bias in density ranging from 0.36 % to 6 % at Dye-2 and being within ±5 % at KAN_U.
Anja Rutishauser, Kirk M. Scanlan, Baptiste Vandecrux, Nanna B. Karlsson, Nicolas Jullien, Andreas P. Ahlstrøm, Robert S. Fausto, and Penelope How
The Cryosphere, 18, 2455–2472, https://doi.org/10.5194/tc-18-2455-2024, https://doi.org/10.5194/tc-18-2455-2024, 2024
Short summary
Short summary
The Greenland Ice Sheet interior is covered by a layer of firn, which is important for surface meltwater runoff and contributions to global sea-level rise. Here, we combine airborne radar sounding and laser altimetry measurements to delineate vertically homogeneous and heterogeneous firn. Our results reveal changes in firn between 2011–2019, aligning well with known climatic events. This approach can be used to outline firn areas primed for significantly changing future meltwater runoff.
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.
Xueyu Zhang, Lin Liu, Brice Noël, and Zhicai Luo
EGUsphere, https://doi.org/10.5194/egusphere-2024-122, https://doi.org/10.5194/egusphere-2024-122, 2024
Preprint archived
Short summary
Short summary
In this study, an improved firn densification model is developed by integrating the Bucket scheme and Darcy’s law to assess the capillary retention, refreezing, and runoff of liquid water within the firn layer. This model captures high-density peaks (~917 kg · m-3) or the features of high-density layers caused by the refreezing of liquid water. In general, the modelled firn depth-density profiles at KAN_U and Dye-2 agree well with the in situ measurements.
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.
Tong Zhang, William Colgan, Agnes Wansing, Anja Løkkegaard, Gunter Leguy, William H. Lipscomb, and Cunde Xiao
The Cryosphere, 18, 387–402, https://doi.org/10.5194/tc-18-387-2024, https://doi.org/10.5194/tc-18-387-2024, 2024
Short summary
Short summary
The geothermal heat flux determines how much heat enters from beneath the ice sheet, and thus impacts the temperature and the flow of the ice sheet. In this study we investigate how much geothermal heat flux impacts the initialization of the Greenland ice sheet. We use the Community Ice Sheet Model with two different initialization methods. We find a non-trivial influence of the choice of heat flow boundary conditions on the ice sheet initializations for further designs of ice sheet modeling.
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.
Baptiste Vandecrux, Jason E. Box, Andreas P. Ahlstrøm, Signe B. Andersen, Nicolas Bayou, William T. Colgan, Nicolas J. Cullen, Robert S. Fausto, Dominik Haas-Artho, Achim Heilig, Derek A. Houtz, Penelope How, Ionut Iosifescu Enescu, Nanna B. Karlsson, Rebecca Kurup Buchholz, Kenneth D. Mankoff, Daniel McGrath, Noah P. Molotch, Bianca Perren, Maiken K. Revheim, Anja Rutishauser, Kevin Sampson, Martin Schneebeli, Sandy Starkweather, Simon Steffen, Jeff Weber, Patrick J. Wright, Henry Jay Zwally, and Konrad Steffen
Earth Syst. Sci. Data, 15, 5467–5489, https://doi.org/10.5194/essd-15-5467-2023, https://doi.org/10.5194/essd-15-5467-2023, 2023
Short summary
Short summary
The Greenland Climate Network (GC-Net) comprises stations that have been monitoring the weather on the Greenland Ice Sheet for over 30 years. These stations are being replaced by newer ones maintained by the Geological Survey of Denmark and Greenland (GEUS). The historical data were reprocessed to improve their quality, and key information about the weather stations has been compiled. This augmented dataset is available at https://doi.org/10.22008/FK2/VVXGUT (Steffen et al., 2022).
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.
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
Short summary
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.
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.
Anja Løkkegaard, Kenneth D. Mankoff, Christian Zdanowicz, Gary D. Clow, Martin P. Lüthi, Samuel H. Doyle, Henrik H. Thomsen, David Fisher, Joel Harper, Andy Aschwanden, Bo M. Vinther, Dorthe Dahl-Jensen, Harry Zekollari, Toby Meierbachtol, Ian McDowell, Neil Humphrey, Anne Solgaard, Nanna B. Karlsson, Shfaqat A. Khan, Benjamin Hills, Robert Law, Bryn Hubbard, Poul Christoffersen, Mylène Jacquemart, Julien Seguinot, Robert S. Fausto, and William T. Colgan
The Cryosphere, 17, 3829–3845, https://doi.org/10.5194/tc-17-3829-2023, https://doi.org/10.5194/tc-17-3829-2023, 2023
Short summary
Short summary
This study presents a database compiling 95 ice temperature profiles from the Greenland ice sheet and peripheral ice caps. Ice viscosity and hence ice flow are highly sensitive to ice temperature. To highlight the value of the database in evaluating ice flow simulations, profiles from the Greenland ice sheet are compared to a modeled temperature field. Reoccurring discrepancies between modeled and observed temperatures provide insight on the difficulties faced when simulating ice temperatures.
Sonika Shahi, Jakob Abermann, Tiago Silva, Kirsty Langley, Signe Hillerup Larsen, Mikhail Mastepanov, and Wolfgang Schöner
Weather Clim. Dynam., 4, 747–771, https://doi.org/10.5194/wcd-4-747-2023, https://doi.org/10.5194/wcd-4-747-2023, 2023
Short summary
Short summary
This study highlights how the sea ice variability in the Greenland Sea affects the terrestrial climate and the surface mass changes of peripheral glaciers of the Zackenberg region (ZR), Northeast Greenland, combining model output and observations. Our results show that the temporal evolution of sea ice influences the climate anomaly magnitude in the ZR. We also found that the changing temperature and precipitation patterns due to sea ice variability can affect the surface mass of the ice cap.
Alice C. Frémand, Peter Fretwell, Julien A. Bodart, Hamish D. Pritchard, Alan Aitken, Jonathan L. Bamber, Robin Bell, Cesidio Bianchi, Robert G. Bingham, Donald D. Blankenship, Gino Casassa, Ginny Catania, Knut Christianson, Howard Conway, Hugh F. J. Corr, Xiangbin Cui, Detlef Damaske, Volkmar Damm, Reinhard Drews, Graeme Eagles, Olaf Eisen, Hannes Eisermann, Fausto Ferraccioli, Elena Field, René Forsberg, Steven Franke, Shuji Fujita, Yonggyu Gim, Vikram Goel, Siva Prasad Gogineni, Jamin Greenbaum, Benjamin Hills, Richard C. A. Hindmarsh, Andrew O. Hoffman, Per Holmlund, Nicholas Holschuh, John W. Holt, Annika N. Horlings, Angelika Humbert, Robert W. Jacobel, Daniela Jansen, Adrian Jenkins, Wilfried Jokat, Tom Jordan, Edward King, Jack Kohler, William Krabill, Mette Kusk Gillespie, Kirsty Langley, Joohan Lee, German Leitchenkov, Carlton Leuschen, Bruce Luyendyk, Joseph MacGregor, Emma MacKie, Kenichi Matsuoka, Mathieu Morlighem, Jérémie Mouginot, Frank O. Nitsche, Yoshifumi Nogi, Ole A. Nost, John Paden, Frank Pattyn, Sergey V. Popov, Eric Rignot, David M. Rippin, Andrés Rivera, Jason Roberts, Neil Ross, Anotonia Ruppel, Dustin M. Schroeder, Martin J. Siegert, Andrew M. Smith, Daniel Steinhage, Michael Studinger, Bo Sun, Ignazio Tabacco, Kirsty Tinto, Stefano Urbini, David Vaughan, Brian C. Welch, Douglas S. Wilson, Duncan A. Young, and Achille Zirizzotti
Earth Syst. Sci. Data, 15, 2695–2710, https://doi.org/10.5194/essd-15-2695-2023, https://doi.org/10.5194/essd-15-2695-2023, 2023
Short summary
Short summary
This paper presents the release of over 60 years of ice thickness, bed elevation, and surface elevation data acquired over Antarctica by the international community. These data are a crucial component of the Antarctic Bedmap initiative which aims to produce a new map and datasets of Antarctic ice thickness and bed topography for the international glaciology and geophysical community.
William Colgan, Christopher Shields, Pavel Talalay, Xiaopeng Fan, Austin P. Lines, Joshua Elliott, Harihar Rajaram, Kenneth Mankoff, Morten Jensen, Mira Backes, Yunchen Liu, Xianzhe Wei, Nanna B. Karlsson, Henrik Spanggård, and Allan Ø. Pedersen
Geosci. Instrum. Method. Data Syst., 12, 121–140, https://doi.org/10.5194/gi-12-121-2023, https://doi.org/10.5194/gi-12-121-2023, 2023
Short summary
Short summary
We describe a new drill for glaciers and ice sheets. Instead of drilling down into the ice, via mechanical action, our drill melts into the ice. Our goal is simply to pull a cable of temperature sensors on a one-way trip down to the ice–bed interface. Here, we describe the design and testing of our drill. Under laboratory conditions, our melt-tip drill has an efficiency of ∼ 35 % with a theoretical maximum penetration rate of ∼ 12 m h−1. Under field conditions, our efficiency is just ∼ 15 %.
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.
Eva Friis Møller, Asbjørn Christensen, Janus Larsen, Kenneth D. Mankoff, Mads Hvid Ribergaard, Mikael Sejr, Philip Wallhead, and Marie Maar
Ocean Sci., 19, 403–420, https://doi.org/10.5194/os-19-403-2023, https://doi.org/10.5194/os-19-403-2023, 2023
Short summary
Short summary
Melt from the Greenland ice sheet and sea ice both influence light and nutrient availability in the Arctic coastal ocean. We use a 3D coupled hydrodynamic–biogeochemical model to evaluate the relative importance of these processes for timing, distribution, and magnitude of phytoplankton production in Disko Bay, west Greenland. Our study indicates that decreasing sea ice and more freshwater discharge can work synergistically and increase primary productivity of the coastal ocean around Greenland.
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.
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.
Tiago Silva, Jakob Abermann, Brice Noël, Sonika Shahi, Willem Jan van de Berg, and Wolfgang Schöner
The Cryosphere, 16, 3375–3391, https://doi.org/10.5194/tc-16-3375-2022, https://doi.org/10.5194/tc-16-3375-2022, 2022
Short summary
Short summary
To overcome internal climate variability, this study uses k-means clustering to combine NAO, GBI and IWV over the Greenland Ice Sheet (GrIS) and names the approach as the North Atlantic influence on Greenland (NAG). With the support of a polar-adapted RCM, spatio-temporal changes on SEB components within NAG phases are investigated. We report atmospheric warming and moistening across all NAG phases as well as large-scale and regional-scale contributions to GrIS mass loss and their interactions.
Jonathan P. Conway, Jakob Abermann, Liss M. Andreassen, Mohd Farooq Azam, Nicolas J. Cullen, Noel Fitzpatrick, Rianne H. Giesen, Kirsty Langley, Shelley MacDonell, Thomas Mölg, Valentina Radić, Carleen H. Reijmer, and Jean-Emmanuel Sicart
The Cryosphere, 16, 3331–3356, https://doi.org/10.5194/tc-16-3331-2022, https://doi.org/10.5194/tc-16-3331-2022, 2022
Short summary
Short summary
We used data from automatic weather stations on 16 glaciers to show how clouds influence glacier melt in different climates around the world. We found surface melt was always more frequent when it was cloudy but was not universally faster or slower than under clear-sky conditions. Also, air temperature was related to clouds in opposite ways in different climates – warmer with clouds in cold climates and vice versa. These results will help us improve how we model past and future glacier melt.
Joseph A. MacGregor, Winnie Chu, William T. Colgan, Mark A. Fahnestock, Denis Felikson, Nanna B. Karlsson, Sophie M. J. Nowicki, and Michael Studinger
The Cryosphere, 16, 3033–3049, https://doi.org/10.5194/tc-16-3033-2022, https://doi.org/10.5194/tc-16-3033-2022, 2022
Short summary
Short summary
Where the bottom of the Greenland Ice Sheet is frozen and where it is thawed is not well known, yet knowing this state is increasingly important to interpret modern changes in ice flow there. We produced a second synthesis of knowledge of the basal thermal state of the ice sheet using airborne and satellite observations and numerical models. About one-third of the ice sheet’s bed is likely thawed; two-fifths is likely frozen; and the remainder is too uncertain to specify.
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.
Mimmi Oksman, Anna Bang Kvorning, Signe Hillerup Larsen, Kristian Kjellerup Kjeldsen, Kenneth David Mankoff, William Colgan, Thorbjørn Joest Andersen, Niels Nørgaard-Pedersen, Marit-Solveig Seidenkrantz, Naja Mikkelsen, and Sofia Ribeiro
The Cryosphere, 16, 2471–2491, https://doi.org/10.5194/tc-16-2471-2022, https://doi.org/10.5194/tc-16-2471-2022, 2022
Short summary
Short summary
One of the questions facing the cryosphere community today is how increasing runoff from the Greenland Ice Sheet impacts marine ecosystems. To address this, long-term data are essential. Here, we present multi-site records of fjord productivity for SW Greenland back to the 19th century. We show a link between historical freshwater runoff and productivity, which is strongest in the inner fjord – influenced by marine-terminating glaciers – where productivity has increased since the late 1990s.
Rohi Muthyala, Åsa K. Rennermalm, Sasha Z. Leidman, Matthew G. Cooper, Sarah W. Cooley, Laurence C. Smith, and Dirk van As
The Cryosphere, 16, 2245–2263, https://doi.org/10.5194/tc-16-2245-2022, https://doi.org/10.5194/tc-16-2245-2022, 2022
Short summary
Short summary
In situ measurements of meltwater discharge through supraglacial stream networks are rare. The unprecedentedly long record of discharge captures diurnal and seasonal variability. Two major findings are (1) a change in the timing of peak discharge through the melt season that could impact meltwater delivery in the subglacial system and (2) though the primary driver of stream discharge is shortwave radiation, longwave radiation and turbulent heat fluxes play a major role during high-melt episodes.
William Colgan, Agnes Wansing, Kenneth Mankoff, Mareen Lösing, John Hopper, Keith Louden, Jörg Ebbing, Flemming G. Christiansen, Thomas Ingeman-Nielsen, Lillemor Claesson Liljedahl, Joseph A. MacGregor, Árni Hjartarson, Stefan Bernstein, Nanna B. Karlsson, Sven Fuchs, Juha Hartikainen, Johan Liakka, Robert S. Fausto, Dorthe Dahl-Jensen, Anders Bjørk, Jens-Ove Naslund, Finn Mørk, Yasmina Martos, Niels Balling, Thomas Funck, Kristian K. Kjeldsen, Dorthe Petersen, Ulrik Gregersen, Gregers Dam, Tove Nielsen, Shfaqat A. Khan, and Anja Løkkegaard
Earth Syst. Sci. Data, 14, 2209–2238, https://doi.org/10.5194/essd-14-2209-2022, https://doi.org/10.5194/essd-14-2209-2022, 2022
Short summary
Short summary
We assemble all available geothermal heat flow measurements collected in and around Greenland into a new database. We use this database of point measurements, in combination with other geophysical datasets, to model geothermal heat flow in and around Greenland. Our geothermal heat flow model is generally cooler than previous models of Greenland, especially in southern Greenland. It does not suggest any high geothermal heat flows resulting from Icelandic plume activity over 50 million years ago.
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.
Robert S. Fausto, Dirk van As, Kenneth D. Mankoff, Baptiste Vandecrux, Michele Citterio, Andreas P. Ahlstrøm, Signe B. Andersen, William Colgan, Nanna B. Karlsson, Kristian K. Kjeldsen, Niels J. Korsgaard, Signe H. Larsen, Søren Nielsen, Allan Ø. Pedersen, Christopher L. Shields, Anne M. Solgaard, and Jason E. Box
Earth Syst. Sci. Data, 13, 3819–3845, https://doi.org/10.5194/essd-13-3819-2021, https://doi.org/10.5194/essd-13-3819-2021, 2021
Short summary
Short summary
The Programme for Monitoring of the Greenland Ice Sheet (PROMICE) has been measuring climate and ice sheet properties since 2007. Here, we present our data product from weather and ice sheet measurements from a network of automatic weather stations mainly located in the melt area of the ice sheet. Currently the PROMICE automatic weather station network includes 25 instrumented sites in Greenland.
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.
Anne Solgaard, Anders Kusk, John Peter Merryman Boncori, Jørgen Dall, Kenneth D. Mankoff, Andreas P. Ahlstrøm, Signe B. Andersen, Michele Citterio, Nanna B. Karlsson, Kristian K. Kjeldsen, Niels J. Korsgaard, Signe H. Larsen, and Robert S. Fausto
Earth Syst. Sci. Data, 13, 3491–3512, https://doi.org/10.5194/essd-13-3491-2021, https://doi.org/10.5194/essd-13-3491-2021, 2021
Short summary
Short summary
The PROMICE Ice Velocity product is a time series of Greenland Ice Sheet ice velocity mosaics spanning September 2016 to present. It is derived from Sentinel-1 SAR data and has a spatial resolution of 500 m. Each mosaic spans 24 d (two Sentinel-1 cycles), and a new one is posted every 12 d (every Sentinel-1A cycle). The spatial comprehensiveness and temporal consistency make the product ideal for monitoring and studying ice-sheet-wide ice discharge and dynamics of glaciers.
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.
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.
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).
Eef C. H. van Dongen, Guillaume Jouvet, Shin Sugiyama, Evgeny A. Podolskiy, Martin Funk, Douglas I. Benn, Fabian Lindner, Andreas Bauder, Julien Seguinot, Silvan Leinss, and Fabian Walter
The Cryosphere, 15, 485–500, https://doi.org/10.5194/tc-15-485-2021, https://doi.org/10.5194/tc-15-485-2021, 2021
Short summary
Short summary
The dynamic mass loss of tidewater glaciers is strongly linked to glacier calving. We study calving mechanisms under a thinning regime, based on 5 years of field and remote-sensing data of Bowdoin Glacier. Our data suggest that Bowdoin Glacier ungrounded recently, and its calving behaviour changed from calving due to surface crevasses to buoyancy-induced calving resulting from basal crevasses. This change may be a precursor to glacier retreat.
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.
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
Ahlstrøm, A. P., Bøggild, C. E., Mohr, J. J., Reeh, N., Christensen, E. L.,
Olesen, O. B. and Keller, K.: Mapping of a hydrological ice-sheet drainage
basin on the West Greenland ice-sheet margin from ERS-1/-2 SAR
interferometry, ice-radar measurement and modelling, Ann. Glaciol.,
34, 309–314, https://doi.org/10.3189/172756402781817860, 2002. a
Ahlstrøm, A. P., Petersen, D., Langen, P. L., Citterio, M., and Box, J. E.:
Abrupt shift in the observed runoff from the southwestern Greenland ice
sheet, Sci. Adv., 3, e1701169, https://doi.org/10.1126/sciadv.1701169, 2017. a
Altman, D. G. and Bland, J. M.: Measurement in Medicine: The Analysis of Method
Comparison Studies, Statistician, 32, 307, https://doi.org/10.2307/2987937, 1983. a, b
An, S.-I., Kim, H., and Kim, B.-M.: Impact of freshwater discharge from the
Greenland ice sheet on North Atlantic climate variability, Theor. Appl. Climatol., 112, 29–43, https://doi.org/10.1007/s00704-012-0699-6, 2012. a
Anonymous: Interactive comment on “Greenland liquid waterrunoff from 1979 through 2017” by Kenneth D. Mankoff et al., Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2020-47-rc1, 2020a. a
Anonymous: Interactive comment on “Greenland liquid waterrunoff from 1979 through 2017” by Kenneth D. Mankoff et al., Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2020-47-rc2,
2020b. a
Balmonte, J. P., Hasler-Sheetal, H., Glud, R. N., Andersen, T. J., Sejr,
M. K., Middelboe, M., Teske, A., and Arnosti, C.: Sharp contrasts between
freshwater and marine microbial enzymatic capabilities, community
composition, and DOM pools in a NE Greenland fjord, Limnol.
Oceanogr., 65, 77–95,
https://doi.org/10.1002/lno.11253, 2019. a, b
Bamber, J. L., Griggs, J. A., Hurkmans, R. T. W. L., Dowdeswell, J. A., Gogineni, S. P., Howat, I., Mouginot, J., Paden, J., Palmer, S., Rignot, E., and Steinhage, D.: A new bed elevation dataset for Greenland, The Cryosphere, 7, 499–510, https://doi.org/10.5194/tc-7-499-2013, 2013. a
Bamber, J. L., Tedstone, A. J., King, M. D., Howat, I. M., Enderlin, E. M.,
van den Broeke, M. R., and Noel, B.: Land Ice Freshwater Budget of the
Arctic and North Atlantic Oceans: 1. Data, Methods, and Results,
J. Geophys. Rese.-Oceans, 123, 1827–1837,
https://doi.org/10.1002/2017jc013605, 2018. a, b, c, d, e, f, g, h, i
Beckmann, J., Perrette, M., Beyer, S., Calov, R., Willeit, M., and Ganopolski, A.: Modeling the response of Greenland outlet glaciers to global warming using a coupled flow line–plume model, The Cryosphere, 13, 2281–2301, https://doi.org/10.5194/tc-13-2281-2019, 2019. a
Bendtsen, J., Mortensen, J., Lennert, K., and Rysgaard, S.: Heat sources for
glacial ice melt in a West Greenland tidewater outlet glacier fjord: The
role of subglacial freshwater discharge, Geophys. Res. Lett., 65, 1535–1546,
https://doi.org/10.1002/2015GL063846, 2015. a
Brewer, C. A.: ColorBrewer.org Website,
http://www.ColorBrewer.org, last access: 2 June 2020. a
Catania, G. A., Stearns, L. A., Moon, T. A., Enderlin, E. M., and Jackson, R. H.: Future
Evolution of Greenland's Marine-Terminating Outlet Glaciers, J.
Geophys. Res.-Earth, 125, e2018JF004873, https://doi.org/10.1029/2018jf004873, 2020. a, b
Chu, W., Creyts, T. T., and Bell, R. E.: Rerouting of subglacial water flow
between neighboring glaciers in West Greenland, J.
Geophys. Res.-Earth, 121, 925–938, https://doi.org/10.1002/2015JF003705, 2016. a, b, c
Citterio, M. and Ahlstrøm, A. P.: Brief communication “The aerophotogrammetric map of Greenland ice masses”, The Cryosphere, 7, 445–449, https://doi.org/10.5194/tc-7-445-2013, 2013. a, b
Citterio, M., Sejr, M. K., Langen, P. L., Mottram, R. H., Abermann, J.,
Hillerup Larsen, S., Skov, K., and Lund, M.: Towards quantifying the
glacial runoff signal in the freshwater input to Tyrolerfjord–Young
Sound, NE Greenland, Ambio., 46, 146–159,
https://doi.org/10.1007/s13280-016-0876-4, 2017. a
Colgan, W., Rajaram, H., Anderson, R., Steffen, K., Phillips, T., Joughin,
I. R., Zwally, H. J., and Abdalati, W.: The annual glaciohydrology cycle in
the ablation zone of the Greenland ice sheet: Part 1. Hydrology model,
J. Glaciol., 57, 697–709, 2011. a
Cowton, T. R., Slater, D., Sole, A., Goldberg, D., and Nienow, P.: Modeling the
impact of glacial runoff on fjord circulation and submarine melt rate using a
new subgrid-scale parameterization for glacial plumes, J. Geophys.
Res.-Oceans, 120, 796–812, https://doi.org/10.1002/2014JC010324, 2015. a
Cowton, T. R., Todd, J. A., and Benn, D. I.: Sensitivity of tidewater glaciers
to submarine melting governed by plume locations, Geophys. Res.
Lett., 46, 11219–11227, https://doi.org/10.1029/2019gl084215, 2019. a
Crozier, J., Karlstrom, L., and Yang, K.: Basal control of supraglacial meltwater catchments on the Greenland Ice Sheet, The Cryosphere, 12, 3383–3407, https://doi.org/10.5194/tc-12-3383-2018, 2018. a
Dask Development Team: Dask: Library for dynamic task scheduling,
available at: https://dask.org (last access: 11 November 2020), 2016. a
Delhasse, A., Kittel, C., Amory, C., Hofer, S., van As, D., S. Fausto, R., and Fettweis, X.: Brief communication: Evaluation of the near-surface climate in ERA5 over the Greenland Ice Sheet, The Cryosphere, 14, 957–965, https://doi.org/10.5194/tc-14-957-2020, 2020. a
Echelmeyer, K. and Harrison, W. D.: Jakobshavns IsbrÆ, West Greenland:
Seasonal Variations in Velocity – or Lack Thereof, J. Glaciol., 36,
82–88, https://doi.org/10.3189/s0022143000005591, 1990. a
Enderlin, E. M., Hamilton, G. S., Straneo, F., and Sutherland, D. A.: Iceberg
meltwater fluxes dominate the freshwater budget in Greenland's
iceberg-congested glacial fjords, Geophys. Res. Lett., 43, 11287–11294,
https://doi.org/10.1002/2016gl070718, 2016. a
Fahnestock, M., Abdalati, W., Joughin, I. R., Brozena, J., and Gogineni, P. S.:
High geothermal heat flow, basal melt, and the origin of rapid ice flow in
central Greenland, Science, 294, 2338–2342, https://doi.org/10.1126/science.1065370,
2001. a
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. a
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. a, b
Fried, M., Carroll, D., Catania, G., Sutherland, D., Stearns, L., Shroyer, E.,
and Nash, J.: Distinct frontal ablation processes drive heterogeneous
submarine terminus morphology, Geophys. Res. Lett., 46, 12083–12091,
https://doi.org/10.1029/2019gl083980, 2019. a
GDAL/OGR contributors: GDAL/OGR Geospatial Data Abstraction software
Library, Open Source Geospatial Foundation, available at: https://gdal.org, last access: 11 November
2020. a
Gillard, L. C., Hu, X., Myers, P. G., and Bamber, J. L.: Meltwater pathways
from marine terminating glaciers of the Greenland ice sheet, Geophys.
Res. Lett., 43, 10873–10882, https://doi.org/10.1002/2016gl070969, 2016. a
GRASS Development Team: Geographic Resources Analysis Support System (GRASS
GIS) Software, Open Source Geospatial Foundation, USA,
available at: https://grass.osgeo.org (last access: 13 August 2020), 2018. a
Hawkings, J., Wadham, J., Tranter, M., Lawson, E., Sole, A., Cowton, T.,
Tedstone, A., Bartholomew, I., Nienow, P., Chandler, D., and Telling, J.: The
effect of warming climate on nutrient and solute export from the Greenland Ice Sheet, Geochemical Perspectives Letters, 1, 94–104,
https://doi.org/10.7185/geochemlet.1510, 2015. a
Hawkings, J., Wadham, J., Telling, J., Bagshaw, E., Beaton, A., Chandler, D.,
and Dubnick, A.: Proglacial discharge measurements, Kiattuut Sermiat
glacier, south Greenland (near Narsarsuaq), Zenodo, https://doi.org/10.5281/zenodo.3685976, 2016a. a
Hawkings, J., Wadham, J., Tranter, M., Telling, J., Bagshaw, E., Beaton, A.,
Simmons, S.-L., Chandler, D., Tedstone, A., and Nienow, P.: The Greenland
Ice Sheet as a hot spot of phosphorus weathering and export in the
Arctic, Global Biogeochem., Cy., 30, 191–210,
https://doi.org/10.1002/2015gb005237, 2016b. a
Howat, I.: MEaSUREs Greenland Ice Mapping Project (GIMP) Land Ice
and Ocean Classification Mask, Version 1, NASA National Snow and Ice Data Center Distributed Active Archive Center, https://doi.org/10.5067/B8X58MQBFUPA (last access: 21 March 2019), 2017b. a, b
Hoyer, S. and Hamman, J. J.: xarray: N-D labeled Arrays and Datasets in
Python, Journal of Open Research Software, 5, 10, https://doi.org/10.5334/jors.148, 2017. a
Hunter, J. D.: Matplotlib: A 2D graphics environment, Comput. Sci.
Eng., 9, 90–95, 2007. a
Jasiewicz, J. and Metz, M.: A new GRASS GIS toolkit for Hortonian analysis of
drainage networks, Comput. Geosci., 37, 1162–1173,
https://doi.org/10.1016/j.cageo.2011.03.003, 2011. a, b
Jordahl, K., den Bossche, J. V., Wasserman, J., McBride, J., Fleischmann, M.,
Gerard, J., Tratner, J., Perry, M., Farmer, C., Hjelle, G. A., Gillies, S.,
Cochran, M., Bartos, M., Culbertson, L., Eubank, N., Bilogur, A., and
maxalbert: geopandas/geopandas: v0.7.0, Zenodo, https://doi.org/10.5281/zenodo.3669853, 2020. a
Jóhannesson, T., Pálmason, B., Hjartarson, Á., Jarosch, A., Magnússon, E., Belart, J., and Gudmundsson, M.: Non-surface mass balance of
glaciers in Iceland, J. Glaciol., 66, 685–697,
https://doi.org/10.1017/jog.2020.37, 2020. a
Kamenos, N. A., Hoey, T. B., Nienow, P. W., Fallick, A. E., and Claverle, T.:
Reconstructing Greenland ice sheet runoff using coralline algae, Geology,
40, 1095–1098, https://doi.org/10.1130/G33405.1, 2012. a
Kanna, N., Sugiyama, S., Ohashi, Y., Sakakibara, D., Fukamachi, Y., and Nomura,
D.: Upwelling of Macronutrients and Dissolved Inorganic Carbon by a
Subglacial Freshwater Driven Plume in Bowdoin Fjord, Northwestern
Greenland, J. Geophys. Res.-Biogeo., 123,
1666–1682, https://doi.org/10.1029/2017jg004248, 2018. a, b
Kluyver, T., Ragan-Kelley, B., Pérez, F., Granger, B., Bussonnier, M.,
Frederic, J., Kelley, K., Hamrick, J., Grout, J., Corlay, S., Ivanov, P.,
Avila, D., Abdalla, S., and Willing, C.: Jupyter Notebooks – a
publishing format for reproducible computational workflows, https://doi.org/10.3233/978-1-61499-649-1-87, 2016. a
Kondo, K. and Sugiyama, S.: Discharge measurement at the outlet stream of
Qaanaaq Glacier in the summer 2017–2019, GEUS Data Center,
https://doi.org/10.22008/hokkaido/data/meltwater_discharge/qaanaaq,
2020. a
Lampkin, D. J. and VanderBerg, J.: A preliminary investigation of the influence
of basal and surface topography on supraglacial lake distribution near
Jakobshavn Isbrae, western Greenland, Hydrol. Process., 25,
3347–3355, https://doi.org/10.1002/hyp.8170, 2011. a
Langen, P. L., Mottram, R. H., Christensen, J. H., Boberg, F., Rodehacke,
C. B., Stendel, M., van As, D., Ahlstrøm, A. P., Mortensen, J., Rysgaard,
S., Petersen, D., Svendsen, K. H., Aḥalgeirsdóttir, G., and
Cappelen, J.: Quantifying energy and mass fluxes controlling
Godthåbsfjord freshwater input in a 5 km simulation (1991–2012),
J. Climate, 28, 3694–3713, https://doi.org/10.1175/JCLI-D-14-00271.1, 2015. a
Lewis, S. M. and Smith, L. C.: Hydrologic drainage of the Greenland ice
sheet, Hydrol. Process., 23, 2004–2011, https://doi.org/10.1002/hyp.7343, 2009. a, b
Lindbäck, K., Pettersson, R., Doyle, S. H., Helanow, C., Jansson, P., Kristensen, S. S., Stenseng, L., Forsberg, R., and Hubbard, A. L.: High-resolution ice thickness and bed topography of a land-terminating section of the Greenland Ice Sheet, Earth Syst. Sci. Data, 6, 331–338, https://doi.org/10.5194/essd-6-331-2014, 2014. a, b, c
Lindbäck, K., Pettersson, R., Hubbard, A. L., Doyle, S. H., van As, D.,
Mikkelsen, A. B., and Fitzpatrick, A. A.: Subglacial water drainage, storage,
and piracy beneath the Greenland Ice Sheet, Geophys. Res.
Lett., 42, 7606–7614, https://doi.org/10.1002/2015GL065393, 2015. a, b, c, d
Liston, G. E. and Mernild, S. H.: Greenland freshwater runoff. Part I: A
runoff routing model for glaciated and nonglaciated landscapes
(HydroFlow), J. Climate, 25, 5997–6014,
https://doi.org/10.1175/JCLI-D-11-00591.1, 2012. a
Livingstone, S. J., Clark, C. D., Woodward, J., and Kingslake, J.: Potential subglacial lake locations and meltwater drainage pathways beneath the Antarctic and Greenland ice sheets, The Cryosphere, 7, 1721–1740, https://doi.org/10.5194/tc-7-1721-2013, 2013. a
Mankoff, K. D.: Freshwater runoff, GEUS Dataverse, https://doi.org/10.22008/promice/freshwater, 2020a. a, b
Mankoff, K. D. and Tulaczyk, S. M.: The past, present, and future viscous heat dissipation available for Greenland subglacial conduit formation, The Cryosphere, 11, 303–317, https://doi.org/10.5194/tc-11-303-2017, 2017. a
Mankoff, K. D., Straneo, F., Cenedese, C., Das, S. B., Richards, C. G., and
Singh, H.: Structure and dynamics of a subglacial discharge plume in a
Greelandic fjord, J. Geophys. Res.-Oceans, 121, 8670–8688,
https://doi.org/10.1002/2016JC011764, 2016. a, b
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. a
Martin Bland, J. and Altman, D. G.: Statistical methods for assessing agreement
between two methods of clinical measurement, Lancet, 327, 307–310,
https://doi.org/10.1016/s0140-6736(86)90837-8, 1986. a, b
McKinney, W.: Data Structures for Statistical Computing in Python, in:
Proceedings of the 9th Python in Science Conference, edited by: van der Walt, S. and Millman, J., 28 June–3 July, Austin, Texas, 51–56, 2010. a
Mernild, S. H. and Liston, G. E.: Greenland Freshwater Runoff. Part II:
Distribution and Trends, 1960-2010, J. Climate, 25, 6015–6035,
https://doi.org/10.1175/JCLI-D-11-00592.1, 2012. a
Mernild, S. H., Liston, G. E., Hiemstra, C. A., and Steffen, K.: Surface melt
area and water balance modeling on the Greenland ice sheet 1995-2005,
J. Hydrometeorol., 9, 1191–1211, https://doi.org/10.1175/2008JHM957.1, 2008. a
Mernild, S. H., Liston, G. E., Hiemstra, C. A., Steffen, K., Hanna, E., and
Christensen, J. H.: Greenland Ice Sheet surface mass-balance modelling and
freshwater flux for 2007, and in a 1995–2007 perspective, Hydrol.
Process., 23, 2470–2484, https://doi.org/10.1002/hyp.7354, 2009. a
Mernild, S. H., Howat, I. M., Ahn, Y., Liston, G. E., Steffen, K., Jakobsen, B. H., Hasholt, B., Fog, B., and van As, D.: Freshwater flux to Sermilik Fjord, SE Greenland, The Cryosphere, 4, 453–465, https://doi.org/10.5194/tc-4-453-2010, 2010a. a
Mernild, S. H., Liston, G. E., Steffen, K., van den Broeke, M., and Hasholt, B.: Runoff and mass-balance simulations from the Greenland Ice Sheet at Kangerlussuaq (Søndre Strømfjord) in a 30-year perspective, 1979–2008, The Cryosphere, 4, 231–242, https://doi.org/10.5194/tc-4-231-2010, 2010b. a
Mernild, S. H., Liston, G. E., van As, D., Hasholt, B., and Yde, J. C.:
High-resolution ice sheet surface mass-balance and spatiotemporal runoff
simulations: Kangerlussuaq, west Greenland, Arct. Antarct. Alp. Res., 50, S100008, https://doi.org/10.1080/15230430.2017.1415856, 2018. a, b
Monteban, D., Pedersen, J. O. P., and Nielsen, M. H.: Physical oceanographic
conditions and a sensitivity study on meltwater runoff in a West
Greenland fjord: Kangerlussuaq, Oceanologia, 62, 460–477,
https://doi.org/10.1016/j.oceano.2020.06.001, 2020. a
Moon, T., Sutherland, D. A., Carroll, D., Felikson, D., Kehrl, L., and Straneo,
F.: Subsurface iceberg melt key to Greenland fjord freshwater budget,
Nat. Geosci., 11, 49–54, https://doi.org/10.1038/s41561-017-0018-z, 2017. a
Morlighem, M., Williams, C., Rignot, E., An, L., Arndt, J. E., Bamber, J.,
Catania, G., Chauché, N., Dowdeswell, J. A., Dorschel, B., Fenty, I., Hogan,
K., Howat, I., Hubbard, A., Jakobsson, M., Jordan, T. M., Kjeldsen, K. K.,
Millan, R., Mayer, L., Mouginot, J., Noël, B., O'Cofaigh, C., Palmer, S. J.,
Rysgaard, S., Seroussi, H., Siegert, M. J., Slabon, P., Straneo, F., van den
Broeke, M. R., Weinrebe, W., Wood, M., and Zinglersen, K.: IceBridge
BedMachine Greenland, Version 3, https://doi.org/10.5067/2CIX82HUV88Y (last access: 28 October 2018), 2017a. a
Morlighem, M., Williams, C. N., Rignot, E., An, L., Arndt, J. E., Bamber,
J. L., Catania, G., Chauché, N., Dowdeswell, J. A., Dorschel, B., Fenty,
I., Hogan, K., Howat, I. M., Hubbard, A., Jakobsson, M., Jordan, T. M.,
Kjeldsen, K. K., Millan, R., Mayer, L., Mouginot, J., Noël, B. P. Y.,
Cofaigh, C. Ó., Palmer, S., Rysgaard, S., Seroussi, H., Siegert, M. J.,
Slabon, P., Straneo, F., van den Broeke, M. R., Weinrebe, W., Wood, M., and
Zinglersen, K. B.: BedMachine v3: Complete bed topography and ocean
bathymetry mapping of Greenland from multi-beam echo sounding combined with
mass conservation, Geophys. Res. Lett., 44, 11051–11061, https://doi.org/10.1002/2017gl074954,
2017b. a
Mortensen, J., Bendtsen, J., Motyka, R. J., Lennert, K., Truffer, M.,
Fahnestock, M., and Rysgaard, S.: On the seasonal freshwater stratification
in the proximity of fast-flowing tidewater outlet glaciers in a sub-Arctic
sill fjord, J. Geophys. Res.-Oceans, 118, 1382–1395,
https://doi.org/10.1002/jgrc.20134, 2013. a
Munneke, P. K., Ligtenberg, S. R. M., van den Broeke, M. R., van Angelen,
J. H., and Forster, R. R.: Explaining the presence of perennial liquid water
bodies in the firn of the Greenland Ice Sheet, Geophys. Res.
Lett., 41, 476–483, https://doi.org/10.1002/2013GL058389, 2014. a
Neteler, M., Bowman, M. H., Landa, M., and Metz, M.: GRASS GIS: a
multi-purpose Open Source GIS, Environ. Modell. Softw., 31,
124–130, https://doi.org/10.1016/j.envsoft.2011.11.014, 2012. a, b
Noël, B., van de Berg, W. J., Machguth, H., Lhermitte, S., Howat, I., Fettweis, X., and van den Broeke, M. R.: A daily, 1 km resolution data set of downscaled Greenland ice sheet surface mass balance (1958–2015), The Cryosphere, 10, 2361–2377, https://doi.org/10.5194/tc-10-2361-2016, 2016. a
Noël, B., van de Berg, W. J., van Wessem, J. M., van Meijgaard, E., van As, D., Lenaerts, J. T. M., Lhermitte, S., Kuipers Munneke, P., Smeets, C. J. P. P., van Ulft, L. H., van de Wal, R. S. W., and van den Broeke, M. R.: Modelling the climate and surface mass balance of polar ice sheets using RACMO2 – Part 1: Greenland (1958–2016), The Cryosphere, 12, 811–831, https://doi.org/10.5194/tc-12-811-2018, 2018. a
Noël, B., van de Berg, W. J., 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. a, b, c
Oliphant, T. E.: A guide to NumPy, vol. 1, Trelgol Publishing, USA, 2006. a
Perner, K., Moros, M., Otterå, O. H., Blanz, T., Schneider, R. R., and Jansen,
E.: An oceanic perspective on Greenland's recent freshwater discharge
since 1850, Sci. Rep.-UK, 9, 17680, https://doi.org/10.1038/s41598-019-53723-z, 2019. a, b
Pitcher, L. H., Smith, L. C., Gleason, C. J., and Yang, K.: CryoSheds: a
GIS modeling framework for delineating land-ice watersheds for the
Greenland Ice Sheet, GISci. Remote Sens., 53, 707–722,
https://doi.org/10.1080/15481603.2016.1230084, 2016. a
Porter, C., Morin, P., Howat, I., Noh, M.-J., 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, Michael, J.,
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, https://doi.org/10.7910/DVN/OHHUKH (last access: 14 November 2019), 2018. a
PROJ contributors: PROJ coordinate transformation software library, Open
Source Geospatial Foundation, available at: https://proj4.org/ (last access: 13 August 2020), 2018. a
Rennermalm, A. K., Smith, L. C., Chu, V. W., Box, J. E., Forster, R. R., Van den Broeke, M. R., Van As, D., and Moustafa, S. E.: Evidence of meltwater retention within the Greenland ice sheet, The Cryosphere, 7, 1433–1445, https://doi.org/10.5194/tc-7-1433-2013, 2013. a, b
Rocklin, M.: Dask: Parallel Computation with Blocked algorithms and Task
Scheduling, in: Proceedings of the 14th Python in Science Conference, edited by: Huff, K. and Bergstra, J., 6–12 July 2015, Austin, Texas,
130–136, https://doi.org/10.25080/Majora-7b98e3ed-013, 2015. a
Sasgen, I., Wouters, B., Gardner, A. S., King, M. D., Tedesco, M., Landerer,
F. W., Dahle, C., Save, H., and Fettweis, X.: Return to rapid ice loss in
Greenland and record loss in 2019 detected by the GRACE-FO satellites,
Commun. Earth Environ., 1, 8, https://doi.org/10.1038/s43247-020-0010-1, 2020. a
Schulte, E., Davison, D., Dye, T., and Dominik, C.: A multi-language computing
environment for literate programming and reproducible research, J.
Stat. Softw., 46, 1–24, 2012. a
Schulzweida, U.: CDO User Guide, Zenodo, https://doi.org/10.5281/zenodo.3539275, 2019. a
Sergienko, O. V.: Glaciological twins: basally controlled subglacial and
supraglacial lakes, J. Glaciol., 59, 3–8,
https://doi.org/10.3189/2013JoG12J040, 2013. a
Shreve, R. L.: Movement of water in glaciers, J. Glaciol., 11,
205–214, 1972. a
Slater, D. A., Straneo, F., Felikson, D., Little, C. M., Goelzer, H., Fettweis, X., and Holte, J.: Estimating Greenland tidewater glacier retreat driven by submarine melting, The Cryosphere, 13, 2489–2509, https://doi.org/10.5194/tc-13-2489-2019, 2019. a
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. a
Stallman, R. M.: EMACS the extensible, customizable self-documenting display
editor, Proceedings of the ACM SIGPLAN SIGOA symposium on Text manipulation, 8–10 June 1981, Portland, Oregon, USA, 147–156,
https://doi.org/10.1145/800209.806466, 1981. a
Stevens, L. A., Hewitt, I. J., Das, S. B., and Behn, M. D.: Relationship
Between Greenland Ice Sheet Surface Speed and Modeled Effective Pressure,
J. Geophys. Res.-Earth, 123, 2258–2278,
https://doi.org/10.1029/2017jf004581, 2018. a
Straneo, F., Curry, R. G., Sutherland, D. A., Hamilton, G. S., Cenedese, C.,
Våge, K., and Stearns, L. A.: Impact of fjord dynamics and glacial runoff
on the circulation near Helheim Glacier, Nat. Geosci., 4, 322–327,
https://doi.org/10.1038/NGEO1109, 2011. a
Sugiyama, S., Sakakibara, D., Matsuno, S., Yamaguchi, S., Matoba, S., and Aoki,
T.: Initial field observations on Qaanaaq ice cap, northwestern
Greenland, Ann. Glaciol., 55, 25–33, https://doi.org/10.3189/2014aog66a102, 2014. a
Tange, O.: GNU Parallel – The Command-Line Power Tool, ;login: USENIX
Magazine, 36, 42–47, https://doi.org/10.5281/zenodo.16303, 2011. a
Tedstone, A., Bartholomew, I., Chandler, D., Cowton, C., Mair, D., Sole, A.,
Wadham, J., and Nienow, P.: Proglacial discharge measurements, Leverett
Glacier, south-west Greenland (2009–2012),
https://doi.org/10.5285/17c400f1-ed6d-4d5a-a51f-aad9ee61ce3d, 2017. a
Trusel, L. D., Das, S. B., Osman, M. B., Evans, M. J., Smith, B. E., Fettweis,
X., McConnell, J. R., Noël, B. P. Y., and van den Broeke, M. R.: Nonlinear
rise in Greenland runoff in response to post-industrial Arctic warming,
Nature, 564, 104–108, https://doi.org/10.1038/s41586-018-0752-4, 2018. a
van As, D., Hubbard, A. L., Hasholt, B., Mikkelsen, A. B., van den Broeke, M. R., and Fausto, R. S.: Large surface meltwater discharge from the Kangerlussuaq sector of the Greenland ice sheet during the record-warm year 2010 explained by detailed energy balance observations, The Cryosphere, 6, 199–209, https://doi.org/10.5194/tc-6-199-2012, 2012. a
van As, D., Bech Mikkelsen, A., Holtegaard Nielsen, M., Box, J. E., Claesson Liljedahl, L., Lindbäck, K., Pitcher, L., and Hasholt, B.: Hypsometric amplification and routing moderation of Greenland ice sheet meltwater release, The Cryosphere, 11, 1371–1386, https://doi.org/10.5194/tc-11-1371-2017, 2017. a, b, c, d, e, f
van As, D., Hasholt, B., Ahlstrøm, A. P., Box, J. E., Cappelen, J.,
Colgan, W., Fausto, R. S., Mernild, S. H., Mikkelsen, A. B., Noël, B.
P. Y., Petersen, D., and van den Broeke, M. R.: Reconstructing Greenland
Ice Sheet meltwater discharge through the Watson River (1949–2017),
Arct. Antarct. Alp. Res., 50, S100010. https://doi.org/10.1080/15230430.2018.1433799,
2018.
a, b, c, d, e, f, g, h, i
Van Rossum, G. and Drake Jr., F. L.: Python reference manual, Centrum voor
Wiskunde en Informatica Amsterdam, 1995. a
Vandecrux, B., MacFerrin, M., Machguth, H., Colgan, W. T., van As, D., Heilig, A., Stevens, C. M., Charalampidis, C., Fausto, R. S., Morris, E. M., Mosley-Thompson, E., Koenig, L., Montgomery, L. N., Miège, C., Simonsen, S. B., Ingeman-Nielsen, T., and Box, J. E.: Firn data compilation reveals widespread decrease of firn air content in western Greenland, The Cryosphere, 13, 845–859, https://doi.org/10.5194/tc-13-845-2019, 2019. a
Werder, M. A., Hewitt, I. J., Schoof, C. G., and Flowers, G. E.: Modeling
channelized and distributed subglacial drainage in two dimensions, J.
Geophys. Res., 118, 2140–2158, https://doi.org/10.1002/jgrf.20146, 2013. a
Yang, K. and Smith, L. C.: Internally drained catchments dominate supraglacial
hydrology of the southwest Greenland Ice Sheet, J. Geophys.
Res.-Earth, 121, 1891–1910, https://doi.org/10.1002/2016jf003927, 2016. a
Yang, K., Smith, L. C., Fettweis, X., Gleason, C. J., Lu, Y., and Li, M.:
Surface meltwater runoff on the Greenland ice sheet estimated from remotely sensed supraglacial lake infilling rate, Remote Sens. Environ., 234, 111459, https://doi.org/10.1016/j.rse.2019.111459, 2019. a, b
Zender, C. S.: Analysis of self-describing gridded geoscience data with
netCDF Operators (NCO), Environ. Modell. Softw., 23,
1338–1342, https://doi.org/10.1016/j.envsoft.2008.03.004, 2008. a
Zuo, Z. and Oerlemans, J.: Modelling albedo and specific balance of the
Greenland ice sheet: calculations for the SØndre StrØmfjord transect,
J. Glaciol., 42, 305–317, https://doi.org/10.3189/s0022143000004160, 1996. a, b
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.
This work partitions regional climate model (RCM) runoff from the MAR and RACMO RCMs to...
Altmetrics
Final-revised paper
Preprint