Articles | Volume 13, issue 10
https://doi.org/10.5194/essd-13-5001-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/essd-13-5001-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Greenland ice sheet mass balance from 1840 through next week
Department of Glaciology and Climate, Geological Survey of Denmark and Greenland (GEUS), Copenhagen, Denmark
Xavier Fettweis
SPHERES research unit, Department of Geography, University of Liège, Liège, Belgium
Peter L. Langen
Department of Environmental Science, iClimate, Aarhus University, Roskilde, Denmark
Martin Stendel
Danish Meteorological Institute (DMI), Copenhagen, Denmark
Kristian K. Kjeldsen
Department of Glaciology and Climate, Geological Survey of Denmark and Greenland (GEUS), Copenhagen, Denmark
Nanna B. Karlsson
Department of Glaciology and Climate, Geological Survey of Denmark and Greenland (GEUS), Copenhagen, Denmark
Brice Noël
Institute for Marine and Atmospheric Research, Utrecht University, the Netherlands
Michiel R. van den Broeke
Institute for Marine and Atmospheric Research, Utrecht University, the Netherlands
Anne Solgaard
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
Jason E. Box
Department of Glaciology and Climate, Geological Survey of Denmark and Greenland (GEUS), Copenhagen, Denmark
Sebastian B. Simonsen
Geodesy and Earth Observation, DTU Space, Technical University of Denmark, Lyngby, Denmark
Michalea D. King
Polar Science Center, University of Washington, Seattle, WA, USA
Andreas P. Ahlstrøm
Department of Glaciology and Climate, Geological Survey of Denmark and Greenland (GEUS), Copenhagen, Denmark
Signe Bech Andersen
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
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The Cryosphere, 16, 2471–2491, https://doi.org/10.5194/tc-16-2471-2022, https://doi.org/10.5194/tc-16-2471-2022, 2022
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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
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This preprint is open for discussion and under review for The Cryosphere (TC).
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This preprint is open for discussion and under review for The Cryosphere (TC).
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The Cryosphere, 19, 2963–2981, https://doi.org/10.5194/tc-19-2963-2025, https://doi.org/10.5194/tc-19-2963-2025, 2025
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Regional climate models are currently the only source for assessing the melt volume of the Greenland Ice Sheet on a global scale. This study compares the modeled melt volume with observations from weather stations and melt extent observed from the Advanced SCATterometer (ASCAT) to assess the performance of the models. It highlights the importance of critically evaluating model outputs with high-quality satellite measurements to improve the understanding of variability among models.
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EGUsphere, https://doi.org/10.5194/egusphere-2025-2900, https://doi.org/10.5194/egusphere-2025-2900, 2025
This preprint is open for discussion and under review for The Cryosphere (TC).
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We produce annual maps of Antarctic surface melt volumes from 2012 to 2021 using satellite microwave data. We detect melting days from thresholds on the satellite signal and then use actual melt measurements from weather stations to convert those signals into water‑equivalent volumes. Our maps capture known melt hotspots and show slightly lower totals than climate models. This dataset supports climate and ice‑shelf studies.
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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
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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
This preprint is open for discussion and under review for The Cryosphere (TC).
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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.
Sofie Hedetoft, Olivia Bang Brinck, Ruth Mottram, Andrea M. U. Gierisch, Steffen Malskær Olsen, Martin Olesen, Nicolaj Hansen, Anders Anker Bjørk, Erik Loebel, Anne Solgaard, and Peter Thejll
EGUsphere, https://doi.org/10.5194/egusphere-2025-1907, https://doi.org/10.5194/egusphere-2025-1907, 2025
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Iceberg mélange is the jumble of icebergs in front of some glaciers that calve into the sea. Some studies suggest mélange might help to control the retreat of glaciers. We studied 3 glaciers in NW Greenland where we used GPS sensors and satellites to track ice movement. We found that glaciers push forward and calve all year, including when mélange and landfast sea ice are present, suggesting mélange is not important in supporting glaciers, but may influence the seasonal calving cycle.
Tanja Denager, Jesper Riis Christiansen, Raphael Johannes Maria Schneider, Peter L. Langen, Thea Quistgaard, and Simon Stisen
EGUsphere, https://doi.org/10.5194/egusphere-2025-2503, https://doi.org/10.5194/egusphere-2025-2503, 2025
This preprint is open for discussion and under review for Biogeosciences (BG).
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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
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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.
Maurice van Tiggelen, Paul C. J. P. Smeets, Carleen H. Reijmer, Peter Kuipers Munneke, and Michiel R. van den Broeke
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-88, https://doi.org/10.5194/essd-2025-88, 2025
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This paper describes the 154 station-years of in situ measurements from the 19 IMAU automatic weather stations that operated on the Antarctic ice sheet between 1995 and 2022. These stations also recorded all four components of net surface radiation and surface height change, which allows for the quantification of the surface energy-and-mass balance at hourly resolution. This data is invaluable for the evaluation of weather and climate models, and for the detection of climatological changes.
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
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Kirk M. Scanlan, Anja Rutishauser, and Sebastian B. Simonsen
The Cryosphere, 19, 1221–1239, https://doi.org/10.5194/tc-19-1221-2025, https://doi.org/10.5194/tc-19-1221-2025, 2025
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Ida Haven, Hans Christian Steen-Larsen, Laura J. Dietrich, Sonja Wahl, Jason E. Box, Michiel R. Van den Broeke, Alun Hubbard, Stephan T. Kral, Joachim Reuder, and Maurice Van Tiggelen
EGUsphere, https://doi.org/10.5194/egusphere-2025-711, https://doi.org/10.5194/egusphere-2025-711, 2025
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Three independent Eddy-Covariance measurement systems deployed on top of the Greenland Ice Sheet are compared. Using this dataset, we evaluate the reproducibility and quantify the differences between the systems. The fidelity of two regional climate models in capturing the seasonal variability in the latent and sensible heat flux between the snow surface and the atmosphere is assessed. We identify differences between observations and model simulations, especially during the winter period.
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
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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
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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
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Coastal areas face rising flood threats as storms intensifies with climate change. With an advanced model of the Scheldt Estuary-North Sea, we studied how detailed atmospheric data must be to predict storm surge peaks in estuaries. We found that high-resolution atmospheric data gives the best results, and coarser data with same resolution as current global climate models give poorer results. We show that investing in localized, high-resolution atmospheric data can significantly improve results.
Sindhu Vudayagiri, Bo Vinther, Johannes Freitag, Peter L. Langen, and Thomas Blunier
Clim. Past, 21, 517–528, https://doi.org/10.5194/cp-21-517-2025, https://doi.org/10.5194/cp-21-517-2025, 2025
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Air trapped in polar ice during snowfall reflects atmospheric pressure at the time of occlusion, serving as a proxy for elevation. However, melting, firn structure changes, and air pressure variability complicate this relationship. We measured total air content (TAC) in the RECAP ice core from Renland ice cap, eastern Greenland, spanning 121 000 years. Melt layers and short-term TAC variations, whose origins remain unclear, present challenges in interpreting elevation changes.
Jonathan Ortved Melcher, Sune Halkjær, Peter Ditlevsen, Peter L. Langen, Guido Vettoretti, and Sune Olander Rasmussen
Clim. Past, 21, 115–132, https://doi.org/10.5194/cp-21-115-2025, https://doi.org/10.5194/cp-21-115-2025, 2025
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We introduce a new model that simulates Dansgaard–Oeschger events, dramatic and irregular climate shifts within past ice ages. The model consists of simplified equations inspired by ocean current dynamics. We fine-tune this model to capture the Dansgaard–Oeschger events with unprecedented accuracy, providing deeper insights into past climate patterns. This helps us understand and predict complex climate changes, aiding future climate change resilience efforts.
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
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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.
Zhengwen Yan, Jiangjun Ran, Pavel Ditmar, C. K. Shum, Roland Klees, Patrick Smith, and Xavier Fettweis
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-512, https://doi.org/10.5194/essd-2024-512, 2025
Revised manuscript accepted for ESSD
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The Gravity Recovery And Climate Experiment (GRACE) mission has greatly improved our understanding of changes in Earth's gravity field over time. A novel mass concentration (mascon) dataset, GCL-Mascon2024, was determined by leveraging the short-arc approach, advanced spatial constraints, frequency-dependent noise processing strategy, and parameterization integrating natural boundaries, which aims to enhance accuracy for monitoring mass transportation on Earth.
Christiaan T. van Dalum, Willem Jan van de Berg, Michiel R. van den Broeke, and Maurice van Tiggelen
EGUsphere, https://doi.org/10.5194/egusphere-2024-3728, https://doi.org/10.5194/egusphere-2024-3728, 2025
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In this study, we present a new surface mass balance (SMB) and near-surface climate product for Antarctica with the regional climate model RACMO2.4p1. We assess the impact of major model updates on the climate of Antarctica. Locally, the SMB has changed substantially, but also agrees well with observations. In addition, we show that the SMB components, surface energy budget, albedo, pressure, temperature and wind speed compare well with in-situ and remote sensing observations.
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
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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.
Weiran Li, Stef Lhermitte, Bert Wouters, Cornelis Slobbe, Max Brils, and Xavier Fettweis
EGUsphere, https://doi.org/10.5194/egusphere-2024-3251, https://doi.org/10.5194/egusphere-2024-3251, 2024
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Due to the melt events in recent decades, the snow condition over Greenland has been 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 has a long-lasting impact on the volume scattering of Greenland firn. This impact cannot fully recover due to the recent and more frequent melt events.
Sylvie Charbit, Christophe Dumas, Fabienne Maignan, Catherine Ottlé, Nina Raoult, Xavier Fettweis, and Philippe Conesa
The Cryosphere, 18, 5067–5099, https://doi.org/10.5194/tc-18-5067-2024, https://doi.org/10.5194/tc-18-5067-2024, 2024
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The evolution of the Greenland ice sheet is highly dependent on surface melting and therefore on the processes operating at the snow–atmosphere interface and within the snow cover. Here we present new developments to apply a snow model to the Greenland ice sheet. The performance of this model is analysed in terms of its ability to simulate ablation processes. Our analysis shows that the model performs well when compared with the MAR regional polar atmospheric model.
Sanne B. M. Veldhuijsen, Willem Jan van de Berg, Peter Kuipers Munneke, Nicolaj Hansen, Fredrik Boberg, Christoph Kittel, Charles Amory, and Michiel R. van den Broeke
EGUsphere, https://doi.org/10.5194/egusphere-2024-2855, https://doi.org/10.5194/egusphere-2024-2855, 2024
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Perennial firn aquifers (PFAs), year-round bodies of liquid water within firn, can potentially impact ice-shelf and ice-sheet stability. We developed a fast XGBoost firn emulator to predict 21st-century distribution of PFAs in Antarctica for 12 climatic forcings datasets. Our findings suggest that under low emission scenarios, PFAs remain confined to the Antarctic Peninsula. However, under a high-emission scenario, PFAs are projected to expand to a region in West Antarctica and East Antarctica.
Robert G. Bingham, Julien A. Bodart, Marie G. P. Cavitte, Ailsa Chung, Rebecca J. Sanderson, Johannes C. R. Sutter, Olaf Eisen, Nanna B. Karlsson, Joseph A. MacGregor, Neil Ross, Duncan A. Young, David W. Ashmore, Andreas Born, Winnie Chu, Xiangbin Cui, Reinhard Drews, Steven Franke, Vikram Goel, John W. Goodge, A. Clara J. Henry, Antoine Hermant, Benjamin H. Hills, Nicholas Holschuh, Michelle R. Koutnik, Gwendolyn J.-M. C. Leysinger Vieli, Emma J. Mackie, Elisa Mantelli, Carlos Martín, Felix S. L. Ng, Falk M. Oraschewski, Felipe Napoleoni, Frédéric Parrenin, Sergey V. Popov, Therese Rieckh, Rebecca Schlegel, Dustin M. Schroeder, Martin J. Siegert, Xueyuan Tang, Thomas O. Teisberg, Kate Winter, Shuai Yan, Harry Davis, Christine F. Dow, Tyler J. Fudge, Tom A. Jordan, Bernd Kulessa, Kenichi Matsuoka, Clara J. Nyqvist, Maryam Rahnemoonfar, Matthew R. Siegfried, Shivangini Singh, Verjan Višnjević, Rodrigo Zamora, and Alexandra Zuhr
EGUsphere, https://doi.org/10.5194/egusphere-2024-2593, https://doi.org/10.5194/egusphere-2024-2593, 2024
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The ice sheets covering Antarctica have built up over millenia through successive snowfall events which become buried and preserved as internal surfaces of equal age detectable with ice-penetrating radar. This paper describes an international initiative to work together on this archival data to build a comprehensive 3-D picture of how old the ice is everywhere across Antarctica, and how this will be used to reconstruct past and predict future ice and climate behaviour.
Maria T. Kappelsberger, Martin Horwath, Eric Buchta, Matthias O. Willen, Ludwig Schröder, Sanne B. M. Veldhuijsen, Peter Kuipers Munneke, and Michiel R. van den Broeke
The Cryosphere, 18, 4355–4378, https://doi.org/10.5194/tc-18-4355-2024, https://doi.org/10.5194/tc-18-4355-2024, 2024
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The interannual variations in the height of the Antarctic Ice Sheet (AIS) are mainly due to natural variations in snowfall. Precise knowledge of these variations is important for the detection of any long-term climatic trends in AIS surface elevation. We present a new product that spatially resolves these height variations over the period 1992–2017. The product combines the strengths of atmospheric modeling results and satellite altimetry measurements.
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
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Due to increasing air temperatures, surface melt expands to higher elevations on the Greenland ice sheet. This is visible on satellite imagery in the form of rivers of meltwater running across the surface of the ice sheet. We compare model results of meltwater at high elevations on the ice sheet to satellite observations. We find that each of the models shows strengths and weaknesses. A detailed look into the model results reveals potential reasons for the differences between models.
Renée M. Fredensborg Hansen, Henriette Skourup, Eero Rinne, Arttu Jutila, Isobel R. Lawrence, Andrew Shepherd, Knut V. Høyland, Jilu Li, Fernando Rodriguez-Morales, Sebastian B. Simonsen, Jeremy Wilkinson, Gaelle Veyssiere, Donghui Yi, René Forsberg, and Taniâ G. D. Casal
EGUsphere, https://doi.org/10.5194/egusphere-2024-2854, https://doi.org/10.5194/egusphere-2024-2854, 2024
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In December 2022, an airborne campaign collected unprecedented coincident multi-frequency radar and lidar data over sea ice along a CryoSat-2 and ICESat-2 (CRYO2ICE) orbit in the Weddell Sea useful for evaluating microwave penetration. We found limited snow penetration at Ka- and Ku-bands, with significant contributions from the air-snow interface, contradicting traditional assumptions. These findings challenge current methods for comparing air- and spaceborne altimeter estimates of sea ice.
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
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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.
Christiaan T. van Dalum, Willem Jan van de Berg, Srinidhi N. Gadde, Maurice van Tiggelen, Tijmen van der Drift, Erik van Meijgaard, Lambertus H. van Ulft, and Michiel R. van den Broeke
The Cryosphere, 18, 4065–4088, https://doi.org/10.5194/tc-18-4065-2024, https://doi.org/10.5194/tc-18-4065-2024, 2024
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We present a new version of the polar Regional Atmospheric Climate Model (RACMO), version 2.4p1, and show first results for Greenland, Antarctica and the Arctic. We provide an overview of all changes and investigate the impact that they have on the climate of polar regions. By comparing the results with observations and the output from the previous model version, we show that the model performs well regarding the surface mass balance of the ice sheets and near-surface climate.
Mikkel Langgaard Lauritzen, Anne Munck Solgaard, Nicholas Mossor Rathmann, Bo Møllesøe Vinther, Aslak Grindsted, Brice Noël, Guðfinna Aðalgeirsdóttir, and Christine Schøtt Hvidberg
EGUsphere, https://doi.org/10.5194/egusphere-2024-2223, https://doi.org/10.5194/egusphere-2024-2223, 2024
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We study the Holocene period, which started about 11,700 years ago, through 841 computer simulations to better understand the history of the Greenland Ice Sheet. We accurately match historical surface elevation records, verifying our model. The simulations show that an ice bridge that used to connect the Greenland ice sheet to Canada collapsed around 4,900 years ago and still influences the ice sheet. Over the past 500 years, the Greenland ice sheet has contributed 12 millimeters to sea levels.
Nanna B. Karlsson, Dustin M. Schroeder, Louise Sandberg Sørensen, Winnie Chu, Jørgen Dall, Natalia H. Andersen, Reese Dobson, Emma J. Mackie, Simon J. Köhn, Jillian E. Steinmetz, Angelo S. Tarzona, Thomas O. Teisberg, and Niels Skou
Earth Syst. Sci. Data, 16, 3333–3344, https://doi.org/10.5194/essd-16-3333-2024, https://doi.org/10.5194/essd-16-3333-2024, 2024
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In the 1970s, more than 177 000 km of observations were acquired from airborne radar over the Greenland ice sheet. The radar data contain information on not only the thickness of the ice, but also the properties of the ice itself. This information was recorded on film rolls and subsequently stored. In this study, we document the digitization of these film rolls that shed new and unprecedented detailed light on the Greenland ice sheet 50 years ago.
Nicolaj Hansen, Andrew Orr, Xun Zou, Fredrik Boberg, Thomas J. Bracegirdle, Ella Gilbert, Peter L. Langen, Matthew A. Lazzara, Ruth Mottram, Tony Phillips, Ruth Price, Sebastian B. Simonsen, and Stuart Webster
The Cryosphere, 18, 2897–2916, https://doi.org/10.5194/tc-18-2897-2024, https://doi.org/10.5194/tc-18-2897-2024, 2024
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We investigated a melt event over the Ross Ice Shelf. We use regional climate models and a firn model to simulate the melt and compare the results with satellite data. We find that the firn model aligned well with observed melt days in certain parts of the ice shelf. The firn model had challenges accurately simulating the melt extent in the western sector. We identified potential reasons for these discrepancies, pointing to limitations in the models related to representing the cloud properties.
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
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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
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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.
Xiaofeng Wang, Lu An, Peter L. Langen, and Rongxing Li
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-1-2024, 691–696, https://doi.org/10.5194/isprs-archives-XLVIII-1-2024-691-2024, https://doi.org/10.5194/isprs-archives-XLVIII-1-2024-691-2024, 2024
Sanne B. M. Veldhuijsen, Willem Jan van de Berg, Peter Kuipers Munneke, and Michiel R. van den Broeke
The Cryosphere, 18, 1983–1999, https://doi.org/10.5194/tc-18-1983-2024, https://doi.org/10.5194/tc-18-1983-2024, 2024
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We use the IMAU firn densification model to simulate the 21st-century evolution of Antarctic firn air content. Ice shelves on the Antarctic Peninsula and the Roi Baudouin Ice Shelf in Dronning Maud Land are particularly vulnerable to total firn air content (FAC) depletion. Our results also underline the potentially large vulnerability of low-accumulation ice shelves to firn air depletion through ice slab formation.
Aslak Grinsted, Nicholas Mossor Rathmann, Ruth Mottram, Anne Munck Solgaard, Joachim Mathiesen, and Christine Schøtt Hvidberg
The Cryosphere, 18, 1947–1957, https://doi.org/10.5194/tc-18-1947-2024, https://doi.org/10.5194/tc-18-1947-2024, 2024
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Ice fracture can cause glacier crevassing and calving. These natural hazards can also modulate the flow and evolution of ice sheets. In a new study, we use a new high-resolution dataset to determine a new failure criterion for glacier ice. Surprisingly, the strength of ice depends on the mode of deformation, and this has potential implications for the currently used flow law of ice.
Alison Delhasse, Johanna Beckmann, Christoph Kittel, and Xavier Fettweis
The Cryosphere, 18, 633–651, https://doi.org/10.5194/tc-18-633-2024, https://doi.org/10.5194/tc-18-633-2024, 2024
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Aiming to study the long-term influence of an extremely warm climate in the Greenland Ice Sheet contribution to sea level rise, a new regional atmosphere–ice sheet model setup was established. The coupling, explicitly considering the melt–elevation feedback, is compared to an offline method to consider this feedback. We highlight mitigation of the feedback due to local changes in atmospheric circulation with changes in surface topography, making the offline correction invalid on the margins.
Baptiste Vandecrux, Robert S. Fausto, Jason E. Box, Federico Covi, Regine Hock, Åsa K. Rennermalm, Achim Heilig, Jakob Abermann, Dirk van As, Elisa Bjerre, Xavier Fettweis, Paul C. J. P. Smeets, Peter Kuipers Munneke, Michiel R. van den Broeke, Max Brils, Peter L. Langen, Ruth Mottram, and Andreas P. Ahlstrøm
The Cryosphere, 18, 609–631, https://doi.org/10.5194/tc-18-609-2024, https://doi.org/10.5194/tc-18-609-2024, 2024
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How fast is the Greenland ice sheet warming? In this study, we compiled 4500+ temperature measurements at 10 m below the ice sheet surface (T10m) from 1912 to 2022. We trained a machine learning model on these data and reconstructed T10m for the ice sheet during 1950–2022. After a slight cooling during 1950–1985, the ice sheet warmed at a rate of 0.7 °C per decade until 2022. Climate models showed mixed results compared to our observations and underestimated the warming in key regions.
Louise Sandberg Sørensen, Rasmus Bahbah, Sebastian B. Simonsen, Natalia Havelund Andersen, Jade Bowling, Noel Gourmelen, Alex Horton, Nanna B. Karlsson, Amber Leeson, Jennifer Maddalena, Malcolm McMillan, Anne Solgaard, and Birgit Wessel
The Cryosphere, 18, 505–523, https://doi.org/10.5194/tc-18-505-2024, https://doi.org/10.5194/tc-18-505-2024, 2024
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Under the right topographic and hydrological conditions, lakes may form beneath the large ice sheets. Some of these subglacial lakes are active, meaning that they periodically drain and refill. When a subglacial lake drains rapidly, it may cause the ice surface above to collapse, and here we investigate how to improve the monitoring of active subglacial lakes in Greenland by monitoring how their associated collapse basins change over time.
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
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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
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The latest generation of climate models (Coupled Model Intercomparison Project Phase 6 – CMIP6) warm more over Greenland and the Arctic and thus also project a larger mass loss from the Greenland Ice Sheet (GrIS) compared to the previous generation of climate models (CMIP5). Our work suggests for the first time that part of the greater mass loss in CMIP6 over the GrIS is driven by a difference in the surface mass balance sensitivity from a change in cloud representation in the CMIP6 models.
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
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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
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The contribution of the humidity flux to the surface mass balance in the accumulation zone of the Greenland Ice Sheet is uncertain. Here, we evaluate the regional climate model MAR using a multi-annual dataset of eddy covariance measurements and bulk estimates of the humidity flux. The humidity flux largely contributes to the summer surface mass balance (SMB) in the accumulation zone, indicating its potential importance for the annual SMB in a warming climate.
Dominik Fahrner, Donald Slater, Aman KC, Claudia Cenedese, David A. Sutherland, Ellyn Enderlin, Femke de Jong, Kristian K. Kjeldsen, Michael Wood, Peter Nienow, Sophie Nowicki, and Till Wagner
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-411, https://doi.org/10.5194/essd-2023-411, 2023
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Marine-terminating glaciers can lose mass through frontal ablation, which comprises submarine and surface melting, and iceberg calving. We estimate frontal ablation for 49 marine-terminating glaciers in Greenland by combining existing, satellite derived data and calculating volume change near the glacier front over time. The dataset offers exciting opportunities to study the influence of climate forcings on marine-terminating glaciers in Greenland over multi-decadal timescales.
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
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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
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We developed a technique to improve the outputs of a model that calculates the gain and loss of Greenland and consequently its contribution to sea level rise. Our technique generates “sharper” images of the maps generated by the model to better understand and quantify where losses occur. This has implications for improving models, understanding what drives the contributions of Greenland to sea level rise, and more.
Damien Maure, Christoph Kittel, Clara Lambin, Alison Delhasse, and Xavier Fettweis
The Cryosphere, 17, 4645–4659, https://doi.org/10.5194/tc-17-4645-2023, https://doi.org/10.5194/tc-17-4645-2023, 2023
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The Arctic is warming faster than the rest of the Earth. Studies have already shown that Greenland and the Canadian Arctic are experiencing a record increase in melting rates, while Svalbard has been relatively less impacted. Looking at those regions but also extending the study to Iceland and the Russian Arctic archipelagoes, we see a heterogeneity in the melting-rate response to the Arctic warming, with the Russian archipelagoes experiencing lower melting rates than other regions.
Prateek Gantayat, Alison F. Banwell, Amber A. Leeson, James M. Lea, Dorthe Petersen, Noel Gourmelen, and Xavier Fettweis
Geosci. Model Dev., 16, 5803–5823, https://doi.org/10.5194/gmd-16-5803-2023, https://doi.org/10.5194/gmd-16-5803-2023, 2023
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We developed a new supraglacial hydrology model for the Greenland Ice Sheet. This model simulates surface meltwater routing, meltwater drainage, supraglacial lake (SGL) overflow, and formation of lake ice. The model was able to reproduce 80 % of observed lake locations and provides a good match between the observed and modelled temporal evolution of SGLs.
Thomas Dethinne, Quentin Glaude, Ghislain Picard, Christoph Kittel, Patrick Alexander, Anne Orban, and Xavier Fettweis
The Cryosphere, 17, 4267–4288, https://doi.org/10.5194/tc-17-4267-2023, https://doi.org/10.5194/tc-17-4267-2023, 2023
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We investigate the sensitivity of the regional climate model
Modèle Atmosphérique Régional(MAR) to the assimilation of wet-snow occurrence estimated by remote sensing datasets. The assimilation is performed by nudging the MAR snowpack temperature. The data assimilation is performed over the Antarctic Peninsula for the 2019–2021 period. The results show an increase in the melt production (+66.7 %) and a decrease in surface mass balance (−4.5 %) of the model for the 2019–2020 melt season.
Lena G. Buth, Valeria Di Biase, Peter Kuipers Munneke, Stef Lhermitte, Sanne B. M. Veldhuijsen, Sophie de Roda Husman, Michiel R. van den Broeke, and Bert Wouters
EGUsphere, https://doi.org/10.5194/egusphere-2023-2000, https://doi.org/10.5194/egusphere-2023-2000, 2023
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Liquid meltwater which is stored in air bubbles in the compacted snow near the surface of Antarctica can affect ice shelf stability. In order to detect the presence of such firn aquifers over large scales, satellite remote sensing is needed. In this paper, we present our new detection method using radar satellite data as well as the results for the whole Antarctic Peninsula. Firn aquifers are found in the north and northwest of the peninsula, in agreement with locations predicted by models.
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
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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.
Sarah A. Woodroffe, Leanne M. Wake, Kristian K. Kjeldsen, Natasha L. M. Barlow, Antony J. Long, and Kurt H. Kjær
Clim. Past, 19, 1585–1606, https://doi.org/10.5194/cp-19-1585-2023, https://doi.org/10.5194/cp-19-1585-2023, 2023
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Salt marsh in SE Greenland records sea level changes over the past 300 years in sediments and microfossils. The pattern is rising sea level until ~ 1880 CE and sea level fall since. This disagrees with modelled sea level, which overpredicts sea level fall by at least 0.5 m. This is the same even when reducing the overall amount of Greenland ice sheet melt and allowing for more time. Fitting the model to the data leaves ~ 3 mm yr−1 of unexplained sea level rise in SE Greenland since ~ 1880 CE.
Nicolaj Hansen, Louise Sandberg Sørensen, Giorgio Spada, Daniele Melini, Rene Forsberg, Ruth Mottram, and Sebastian B. Simonsen
The Cryosphere Discuss., https://doi.org/10.5194/tc-2023-104, https://doi.org/10.5194/tc-2023-104, 2023
Preprint withdrawn
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We use ICESat-2 to estimate the surface elevation change over Greenland and Antarctica in the period of 2018 to 2021. Numerical models have been used the compute the firn compaction and the vertical bedrock movement so non-mass-related elevation changes can be taken into account. We have made a parameterization of the surface density so we can convert the volume change to mass change. We find that Antarctica has lost 135.7±27.3 Gt per year, and the Greenland ice sheet 237.5±14.0 Gt per year.
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
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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 %.
Elin Andrée, Jian Su, Morten Andreas Dahl Larsen, Martin Drews, Martin Stendel, and Kristine Skovgaard Madsen
Nat. Hazards Earth Syst. Sci., 23, 1817–1834, https://doi.org/10.5194/nhess-23-1817-2023, https://doi.org/10.5194/nhess-23-1817-2023, 2023
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When natural processes interact, they may compound each other. The combined effect can amplify extreme sea levels, such as when a storm occurs at a time when the water level is already higher than usual. We used numerical modelling of a record-breaking storm surge in 1872 to show that other prior sea-level conditions could have further worsened the outcome. Our research highlights the need to consider the physical context of extreme sea levels in measures to reduce coastal flood risk.
Inès N. Otosaka, Andrew Shepherd, Erik R. Ivins, Nicole-Jeanne Schlegel, Charles Amory, Michiel R. van den Broeke, Martin Horwath, Ian Joughin, Michalea D. King, Gerhard Krinner, Sophie Nowicki, Anthony J. Payne, Eric Rignot, Ted Scambos, Karen M. Simon, Benjamin E. Smith, Louise S. Sørensen, Isabella Velicogna, Pippa L. Whitehouse, Geruo A, Cécile Agosta, Andreas P. Ahlstrøm, Alejandro Blazquez, William Colgan, Marcus E. Engdahl, Xavier Fettweis, Rene Forsberg, Hubert Gallée, Alex Gardner, Lin Gilbert, Noel Gourmelen, Andreas Groh, Brian C. Gunter, Christopher Harig, Veit Helm, Shfaqat Abbas Khan, Christoph Kittel, Hannes Konrad, Peter L. Langen, Benoit S. Lecavalier, Chia-Chun Liang, Bryant D. Loomis, Malcolm McMillan, Daniele Melini, Sebastian H. Mernild, Ruth Mottram, Jeremie Mouginot, Johan Nilsson, Brice Noël, Mark E. Pattle, William R. Peltier, Nadege Pie, Mònica Roca, Ingo Sasgen, Himanshu V. Save, Ki-Weon Seo, Bernd Scheuchl, Ernst J. O. Schrama, Ludwig Schröder, Sebastian B. Simonsen, Thomas Slater, Giorgio Spada, Tyler C. Sutterley, Bramha Dutt Vishwakarma, Jan Melchior van Wessem, David Wiese, Wouter van der Wal, and Bert Wouters
Earth Syst. Sci. Data, 15, 1597–1616, https://doi.org/10.5194/essd-15-1597-2023, https://doi.org/10.5194/essd-15-1597-2023, 2023
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By measuring changes in the volume, gravitational attraction, and ice flow of Greenland and Antarctica from space, we can monitor their mass gain and loss over time. Here, we present a new record of the Earth’s polar ice sheet mass balance produced by aggregating 50 satellite-based estimates of ice sheet mass change. This new assessment shows that the ice sheets have lost (7.5 x 1012) t of ice between 1992 and 2020, contributing 21 mm to sea level rise.
Sanne B. M. Veldhuijsen, Willem Jan van de Berg, Max Brils, Peter Kuipers Munneke, and Michiel R. van den Broeke
The Cryosphere, 17, 1675–1696, https://doi.org/10.5194/tc-17-1675-2023, https://doi.org/10.5194/tc-17-1675-2023, 2023
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Firn is the transition of snow to glacier ice and covers 99 % of the Antarctic ice sheet. Knowledge about the firn layer and its variability is important, as it impacts satellite-based estimates of ice sheet mass change. Also, firn contains pores in which nearly all of the surface melt is retained. Here, we improve a semi-empirical firn model and simulate the firn characteristics for the period 1979–2020. We evaluate the performance with field and satellite measures and test its sensitivity.
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
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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.
Mads Dømgaard, Kristian K. Kjeldsen, Flora Huiban, Jonathan L. Carrivick, Shfaqat A. Khan, and Anders A. Bjørk
The Cryosphere, 17, 1373–1387, https://doi.org/10.5194/tc-17-1373-2023, https://doi.org/10.5194/tc-17-1373-2023, 2023
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Sudden releases of meltwater from glacier-dammed lakes can influence ice flow, cause flooding hazards and landscape changes. This study presents a record of 14 drainages from 2007–2021 from a lake in west Greenland. The time series reveals how the lake fluctuates between releasing large and small amounts of drainage water which is caused by a weakening of the damming glacier following the large events. We also find a shift in the water drainage route which increases the risk of flooding hazards.
Benjamin E. Smith, Brooke Medley, Xavier Fettweis, Tyler Sutterley, Patrick Alexander, David Porter, and Marco Tedesco
The Cryosphere, 17, 789–808, https://doi.org/10.5194/tc-17-789-2023, https://doi.org/10.5194/tc-17-789-2023, 2023
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We use repeated satellite measurements of the height of the Greenland ice sheet to learn about how three computational models of snowfall, melt, and snow compaction represent actual changes in the ice sheet. We find that the models do a good job of estimating how the parts of the ice sheet near the coast have changed but that two of the models have trouble representing surface melt for the highest part of the ice sheet. This work provides suggestions for how to better model snowmelt.
Jilu Li, Fernando Rodriguez-Morales, Xavier Fettweis, Oluwanisola Ibikunle, Carl Leuschen, John Paden, Daniel Gomez-Garcia, and Emily Arnold
The Cryosphere, 17, 175–193, https://doi.org/10.5194/tc-17-175-2023, https://doi.org/10.5194/tc-17-175-2023, 2023
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Alaskan glaciers' loss of ice mass contributes significantly to ocean surface rise. It is important to know how deeply and how much snow accumulates on these glaciers to comprehend and analyze the glacial mass loss process. We reported the observed seasonal snow depth distribution from our radar data taken in Alaska in 2018 and 2021, developed a method to estimate the annual snow accumulation rate at Mt. Wrangell caldera, and identified transition zones from wet-snow zones to ablation zones.
Marte G. Hofsteenge, Nicolas J. Cullen, Carleen H. Reijmer, Michiel van den Broeke, Marwan Katurji, and John F. Orwin
The Cryosphere, 16, 5041–5059, https://doi.org/10.5194/tc-16-5041-2022, https://doi.org/10.5194/tc-16-5041-2022, 2022
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In the McMurdo Dry Valleys (MDV), foehn winds can impact glacial meltwater production and the fragile ecosystem that depends on it. We study these dry and warm winds at Joyce Glacier and show they are caused by a different mechanism than that found for nearby valleys, demonstrating the complex interaction of large-scale winds with the mountains in the MDV. We find that foehn winds increase sublimation of ice, increase heating from the atmosphere, and increase the occurrence and rates of melt.
Raf M. Antwerpen, Marco Tedesco, Xavier Fettweis, Patrick Alexander, and Willem Jan van de Berg
The Cryosphere, 16, 4185–4199, https://doi.org/10.5194/tc-16-4185-2022, https://doi.org/10.5194/tc-16-4185-2022, 2022
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The ice on Greenland has been melting more rapidly over the last few years. Most of this melt comes from the exposure of ice when the overlying snow melts. This ice is darker than snow and absorbs more sunlight, leading to more melt. It remains challenging to accurately simulate the brightness of the ice. We show that the color of ice simulated by Modèle Atmosphérique Régional (MAR) is too bright. We then show that this means that MAR may underestimate how fast the Greenland ice is melting.
Lena G. Buth, Bert Wouters, Sanne B. M. Veldhuijsen, Stef Lhermitte, Peter Kuipers Munneke, and Michiel R. van den Broeke
The Cryosphere Discuss., https://doi.org/10.5194/tc-2022-127, https://doi.org/10.5194/tc-2022-127, 2022
Manuscript not accepted for further review
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Liquid meltwater which is stored in air bubbles in the compacted snow near the surface of Antarctica can affect ice shelf stability. In order to detect the presence of such firn aquifers over large scales, satellite remote sensing is needed. In this paper, we present our new detection method using radar satellite data as well as the results for the whole Antarctic Peninsula. Firn aquifers are found in the north and northwest of the peninsula, in agreement with locations predicted by models.
Max Brils, Peter Kuipers Munneke, Willem Jan van de Berg, and Michiel van den Broeke
Geosci. Model Dev., 15, 7121–7138, https://doi.org/10.5194/gmd-15-7121-2022, https://doi.org/10.5194/gmd-15-7121-2022, 2022
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Firn covers the Greenland ice sheet (GrIS) and can temporarily prevent mass loss. Here, we present the latest version of our firn model, IMAU-FDM, with an application to the GrIS. We improved the density of fallen snow, the firn densification rate and the firn's thermal conductivity. This leads to a higher air content and 10 m temperatures. Furthermore we investigate three case studies and find that the updated model shows greater variability and an increased sensitivity in surface elevation.
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
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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.
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
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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
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Model projections suggest large differences in future Antarctic surface melting even for similar greenhouse gas scenarios and warming rates. We show that clouds containing a larger amount of liquid water lead to stronger melt. As surface melt can trigger the collapse of the ice shelves (the safety band of the Antarctic Ice Sheet), clouds could be a major source of uncertainties in projections of sea level rise.
Sébastien Doutreloup, Xavier Fettweis, Ramin Rahif, Essam Elnagar, Mohsen S. Pourkiaei, Deepak Amaripadath, and Shady Attia
Earth Syst. Sci. Data, 14, 3039–3051, https://doi.org/10.5194/essd-14-3039-2022, https://doi.org/10.5194/essd-14-3039-2022, 2022
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This data set provides historical (1980–2014) and future (2015–2100) weather data for 12 cities in Belgium. This data set is intended for architects or building or energy designers. In particular, it makes available to all users hourly open-access weather data according to certain standards to recreate a Typical and an Extreme Meteorological Year. In addition, it provides hourly data on heatwaves from 1980 to 2100. Weather data were produced from the outputs of the MAR model simulations.
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
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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
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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.
Christiaan T. van Dalum, Willem Jan van de Berg, and Michiel R. van den Broeke
The Cryosphere, 16, 1071–1089, https://doi.org/10.5194/tc-16-1071-2022, https://doi.org/10.5194/tc-16-1071-2022, 2022
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In this study, we improve the regional climate model RACMO2 and investigate the climate of Antarctica. We have implemented a new radiative transfer and snow albedo scheme and do several sensitivity experiments. When fully tuned, the results compare well with observations and snow temperature profiles improve. Moreover, small changes in the albedo and the investigated processes can lead to a strong overestimation of melt, locally leading to runoff and a reduced surface mass balance.
H. E. Markus Meier, Madline Kniebusch, Christian Dieterich, Matthias Gröger, Eduardo Zorita, Ragnar Elmgren, Kai Myrberg, Markus P. Ahola, Alena Bartosova, Erik Bonsdorff, Florian Börgel, Rene Capell, Ida Carlén, Thomas Carlund, Jacob Carstensen, Ole B. Christensen, Volker Dierschke, Claudia Frauen, Morten Frederiksen, Elie Gaget, Anders Galatius, Jari J. Haapala, Antti Halkka, Gustaf Hugelius, Birgit Hünicke, Jaak Jaagus, Mart Jüssi, Jukka Käyhkö, Nina Kirchner, Erik Kjellström, Karol Kulinski, Andreas Lehmann, Göran Lindström, Wilhelm May, Paul A. Miller, Volker Mohrholz, Bärbel Müller-Karulis, Diego Pavón-Jordán, Markus Quante, Marcus Reckermann, Anna Rutgersson, Oleg P. Savchuk, Martin Stendel, Laura Tuomi, Markku Viitasalo, Ralf Weisse, and Wenyan Zhang
Earth Syst. Dynam., 13, 457–593, https://doi.org/10.5194/esd-13-457-2022, https://doi.org/10.5194/esd-13-457-2022, 2022
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Based on the Baltic Earth Assessment Reports of this thematic issue in Earth System Dynamics and recent peer-reviewed literature, current knowledge about the effects of global warming on past and future changes in the climate of the Baltic Sea region is summarised and assessed. The study is an update of the Second Assessment of Climate Change (BACC II) published in 2015 and focuses on the atmosphere, land, cryosphere, ocean, sediments, and the terrestrial and marine biosphere.
Nicolaj Hansen, Sebastian B. Simonsen, Fredrik Boberg, Christoph Kittel, Andrew Orr, Niels Souverijns, J. Melchior van Wessem, and Ruth Mottram
The Cryosphere, 16, 711–718, https://doi.org/10.5194/tc-16-711-2022, https://doi.org/10.5194/tc-16-711-2022, 2022
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We investigate the impact of different ice masks when modelling surface mass balance over Antarctica. We used ice masks and data from five of the most used regional climate models and a common mask. We see large disagreement between the ice masks, which has a large impact on the surface mass balance, especially around the Antarctic Peninsula and some of the largest glaciers. We suggest a solution for creating a new, up-to-date, high-resolution ice mask that can be used in Antarctic modelling.
Martin Horwath, Benjamin D. Gutknecht, Anny Cazenave, Hindumathi Kulaiappan Palanisamy, Florence Marti, Ben Marzeion, Frank Paul, Raymond Le Bris, Anna E. Hogg, Inès Otosaka, Andrew Shepherd, Petra Döll, Denise Cáceres, Hannes Müller Schmied, Johnny A. Johannessen, Jan Even Øie Nilsen, Roshin P. Raj, René Forsberg, Louise Sandberg Sørensen, Valentina R. Barletta, Sebastian B. Simonsen, Per Knudsen, Ole Baltazar Andersen, Heidi Ranndal, Stine K. Rose, Christopher J. Merchant, Claire R. Macintosh, Karina von Schuckmann, Kristin Novotny, Andreas Groh, Marco Restano, and Jérôme Benveniste
Earth Syst. Sci. Data, 14, 411–447, https://doi.org/10.5194/essd-14-411-2022, https://doi.org/10.5194/essd-14-411-2022, 2022
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Global mean sea-level change observed from 1993 to 2016 (mean rate of 3.05 mm yr−1) matches the combined effect of changes in water density (thermal expansion) and ocean mass. Ocean-mass change has been assessed through the contributions from glaciers, ice sheets, and land water storage or directly from satellite data since 2003. Our budget assessments of linear trends and monthly anomalies utilise new datasets and uncertainty characterisations developed within ESA's Climate Change Initiative.
Anna Rutgersson, Erik Kjellström, Jari Haapala, Martin Stendel, Irina Danilovich, Martin Drews, Kirsti Jylhä, Pentti Kujala, Xiaoli Guo Larsén, Kirsten Halsnæs, Ilari Lehtonen, Anna Luomaranta, Erik Nilsson, Taru Olsson, Jani Särkkä, Laura Tuomi, and Norbert Wasmund
Earth Syst. Dynam., 13, 251–301, https://doi.org/10.5194/esd-13-251-2022, https://doi.org/10.5194/esd-13-251-2022, 2022
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A natural hazard is a naturally occurring extreme event with a negative effect on people, society, or the environment; major events in the study area include wind storms, extreme waves, high and low sea level, ice ridging, heavy precipitation, sea-effect snowfall, river floods, heat waves, ice seasons, and drought. In the future, an increase in sea level, extreme precipitation, heat waves, and phytoplankton blooms is expected, and a decrease in cold spells and severe ice winters is anticipated.
Fredrik Boberg, Ruth Mottram, Nicolaj Hansen, Shuting Yang, and Peter L. Langen
The Cryosphere, 16, 17–33, https://doi.org/10.5194/tc-16-17-2022, https://doi.org/10.5194/tc-16-17-2022, 2022
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Using the regional climate model HIRHAM5, we compare two versions (v2 and v3) of the global climate model EC-Earth for the Greenland and Antarctica ice sheets. We are interested in the surface mass balance of the ice sheets due to its importance when making estimates of future sea level rise. We find that the end-of-century change in the surface mass balance for Antarctica is 420 Gt yr−1 (v2) and 80 Gt yr−1 (v3), and for Greenland it is −290 Gt yr−1 (v2) and −1640 Gt yr−1 (v3).
Zhongyang Hu, Peter Kuipers Munneke, Stef Lhermitte, Maaike Izeboud, and Michiel van den Broeke
The Cryosphere, 15, 5639–5658, https://doi.org/10.5194/tc-15-5639-2021, https://doi.org/10.5194/tc-15-5639-2021, 2021
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Antarctica is shrinking, and part of the mass loss is caused by higher temperatures leading to more snowmelt. We use computer models to estimate the amount of melt, but this can be inaccurate – specifically in the areas with the most melt. This is because the model cannot account for small, darker areas like rocks or darker ice. Thus, we trained a computer using artificial intelligence and satellite images that showed these darker areas. The model computed an improved estimate of melt.
Nicolaj Hansen, Peter L. Langen, Fredrik Boberg, Rene Forsberg, Sebastian B. Simonsen, Peter Thejll, Baptiste Vandecrux, and Ruth Mottram
The Cryosphere, 15, 4315–4333, https://doi.org/10.5194/tc-15-4315-2021, https://doi.org/10.5194/tc-15-4315-2021, 2021
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We have used computer models to estimate the Antarctic surface mass balance (SMB) from 1980 to 2017. Our estimates lies between 2473.5 ± 114.4 Gt per year and 2564.8 ± 113.7 Gt per year. To evaluate our models, we compared the modelled snow temperatures and densities to in situ measurements. We also investigated the spatial distribution of the SMB. It is very important to have estimates of the Antarctic SMB because then it is easier to understand global sea level changes.
Ruth Mottram, Nicolaj Hansen, Christoph Kittel, J. Melchior van Wessem, Cécile Agosta, Charles Amory, Fredrik Boberg, Willem Jan van de Berg, Xavier Fettweis, Alexandra Gossart, Nicole P. M. van Lipzig, Erik van Meijgaard, Andrew Orr, Tony Phillips, Stuart Webster, Sebastian B. Simonsen, and Niels Souverijns
The Cryosphere, 15, 3751–3784, https://doi.org/10.5194/tc-15-3751-2021, https://doi.org/10.5194/tc-15-3751-2021, 2021
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We compare the calculated surface mass budget (SMB) of Antarctica in five different regional climate models. On average ~ 2000 Gt of snow accumulates annually, but different models vary by ~ 10 %, a difference equivalent to ± 0.5 mm of global sea level rise. All models reproduce observed weather, but there are large differences in regional patterns of snowfall, especially in areas with very few observations, giving greater uncertainty in Antarctic mass budget than previously identified.
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
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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
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Snow is frequently eroded from the surface by the wind in Adelie Land (Antarctica) and suspended in the lower atmosphere. By performing model simulations, we show firstly that suspended snow layers interact with incoming radiation similarly to a near-surface cloud. Secondly, suspended snow modifies the atmosphere's thermodynamic structure and energy exchanges with the surface. Our results suggest snow transport by the wind should be taken into account in future model studies over the region.
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
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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.
Ulas Im, Kostas Tsigaridis, Gregory Faluvegi, Peter L. Langen, Joshua P. French, Rashed Mahmood, Manu A. Thomas, Knut von Salzen, Daniel C. Thomas, Cynthia H. Whaley, Zbigniew Klimont, Henrik Skov, and Jørgen Brandt
Atmos. Chem. Phys., 21, 10413–10438, https://doi.org/10.5194/acp-21-10413-2021, https://doi.org/10.5194/acp-21-10413-2021, 2021
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Future (2015–2050) simulations of the aerosol burdens and their radiative forcing and climate impacts over the Arctic under various emission projections show that although the Arctic aerosol burdens are projected to decrease significantly by 10 to 60 %, regardless of the magnitude of aerosol reductions, surface air temperatures will continue to increase by 1.9–2.6 ℃, while sea-ice extent will continue to decrease, implying reductions of greenhouse gases are necessary to mitigate climate change.
Xavier Fettweis, Stefan Hofer, Roland Séférian, Charles Amory, Alison Delhasse, Sébastien Doutreloup, Christoph Kittel, Charlotte Lang, Joris Van Bever, Florent Veillon, and Peter Irvine
The Cryosphere, 15, 3013–3019, https://doi.org/10.5194/tc-15-3013-2021, https://doi.org/10.5194/tc-15-3013-2021, 2021
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Without any reduction in our greenhouse gas emissions, the Greenland ice sheet surface mass loss can be brought in line with a medium-mitigation emissions scenario by reducing the solar downward flux at the top of the atmosphere by 1.5 %. In addition to reducing global warming, these solar geoengineering measures also dampen the well-known positive melt–albedo feedback over the ice sheet by 6 %. However, only stronger reductions in solar radiation could maintain a stable ice sheet in 2100.
Paolo Colosio, Marco Tedesco, Roberto Ranzi, and Xavier Fettweis
The Cryosphere, 15, 2623–2646, https://doi.org/10.5194/tc-15-2623-2021, https://doi.org/10.5194/tc-15-2623-2021, 2021
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We use a new satellite dataset to study the spatiotemporal evolution of surface melting over Greenland at an enhanced resolution of 3.125 km. Using meteorological data and the MAR model, we observe that a dynamic algorithm can best detect surface melting. We found that the melting season is elongating, the melt extent is increasing and that high-resolution data better describe the spatiotemporal evolution of the melting season, which is crucial to improve estimates of sea level rise.
Maurice van Tiggelen, Paul C. J. P. Smeets, Carleen H. Reijmer, Bert Wouters, Jakob F. Steiner, Emile J. Nieuwstraten, Walter W. Immerzeel, and Michiel R. van den Broeke
The Cryosphere, 15, 2601–2621, https://doi.org/10.5194/tc-15-2601-2021, https://doi.org/10.5194/tc-15-2601-2021, 2021
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We developed a method to estimate the aerodynamic properties of the Greenland Ice Sheet surface using either UAV or ICESat-2 elevation data. We show that this new method is able to reproduce the important spatiotemporal variability in surface aerodynamic roughness, measured by the field observations. The new maps of surface roughness can be used in atmospheric models to improve simulations of surface turbulent heat fluxes and therefore surface energy and mass balance over rough ice worldwide.
Charles Amory, Christoph Kittel, Louis Le Toumelin, Cécile Agosta, Alison Delhasse, Vincent Favier, and Xavier Fettweis
Geosci. Model Dev., 14, 3487–3510, https://doi.org/10.5194/gmd-14-3487-2021, https://doi.org/10.5194/gmd-14-3487-2021, 2021
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This paper presents recent developments in the drifting-snow scheme of the regional climate model MAR and its application to simulate drifting snow and the surface mass balance of Adélie Land in East Antarctica. The model is extensively described and evaluated against a multi-year drifting-snow dataset and surface mass balance estimates available in the area. The model sensitivity to input parameters and improvements over a previously published version are also assessed.
Christiaan T. van Dalum, Willem Jan van de Berg, and Michiel R. van den Broeke
The Cryosphere, 15, 1823–1844, https://doi.org/10.5194/tc-15-1823-2021, https://doi.org/10.5194/tc-15-1823-2021, 2021
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Absorption of solar radiation is often limited to the surface in regional climate models. Therefore, we have implemented a new radiative transfer scheme in the model RACMO2, which allows for internal heating and improves the surface reflectivity. Here, we evaluate its impact on the surface mass and energy budget and (sub)surface temperature, by using observations and the previous model version for the Greenland ice sheet. New results match better with observations and introduce subsurface melt.
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
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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).
J. Melchior van Wessem, Christian R. Steger, Nander Wever, and Michiel R. van den Broeke
The Cryosphere, 15, 695–714, https://doi.org/10.5194/tc-15-695-2021, https://doi.org/10.5194/tc-15-695-2021, 2021
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This study presents the first modelled estimates of perennial firn aquifers (PFAs) in Antarctica. PFAs are subsurface meltwater bodies that do not refreeze in winter due to the isolating effects of the snow they are buried underneath. They were first identified in Greenland, but conditions for their existence are also present in the Antarctic Peninsula. These PFAs can have important effects on meltwater retention, ice shelf stability, and, consequently, sea level rise.
Helle Astrid Kjær, Patrick Zens, Ross Edwards, Martin Olesen, Ruth Mottram, Gabriel Lewis, Christian Terkelsen Holme, Samuel Black, Kasper Holst Lund, Mikkel Schmidt, Dorthe Dahl-Jensen, Bo Vinther, Anders Svensson, Nanna Karlsson, Jason E. Box, Sepp Kipfstuhl, and Paul Vallelonga
The Cryosphere Discuss., https://doi.org/10.5194/tc-2020-337, https://doi.org/10.5194/tc-2020-337, 2021
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We have reconstructed accumulation in 6 firn cores and 8 snow cores in Northern Greenland and compared with a regional Climate model over Greenland. We find the model underestimate precipitation especially in north-eastern part of the ice cap- an important finding if aiming to reconstruct surface mass balance.
Temperatures at 10 meters depth at 6 sites in Greenland were also determined and show a significant warming since the 1990's of 0.9 to 2.5 °C.
Fredrik Boberg, Ruth Mottram, Nicolaj Hansen, Shuting Yang, and Peter L. Langen
The Cryosphere Discuss., https://doi.org/10.5194/tc-2020-331, https://doi.org/10.5194/tc-2020-331, 2020
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Using the regional climate model HIRHAM5, we compare two versions (v2 and v3) of the global climate model EC-Earth for the Greenland and Antarctica ice sheets. We are interested in the surface mass balance of the ice sheets due to its importance when making estimates of the future sea level rise. We find that the end-of-century change of the surface mass balance for Antarctica is +150 Gt yr−1 (v2) and −710 Gt yr−1 (v3) and for Greenland the numbers are −210 Gt yr−1 (v2) and −1150 Gt yr−1 (v3).
Kristian Svennevig, Trine Dahl-Jensen, Marie Keiding, John Peter Merryman Boncori, Tine B. Larsen, Sara Salehi, Anne Munck Solgaard, and Peter H. Voss
Earth Surf. Dynam., 8, 1021–1038, https://doi.org/10.5194/esurf-8-1021-2020, https://doi.org/10.5194/esurf-8-1021-2020, 2020
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The 17 June 2017 Karrat landslide in Greenland caused a tsunami that killed four people. We apply a multidisciplinary workflow to reconstruct a timeline of events and find that three historic landslides occurred in 2009, 2016, and 2017. We also find evidence of much older periods of landslide activity. Three newly discovered active slopes might pose a future hazard. We speculate that the trigger for the recent events is melting permafrost due to a warming climate.
Seyedhamidreza Mojtabavi, Frank Wilhelms, Eliza Cook, Siwan M. Davies, Giulia Sinnl, Mathias Skov Jensen, Dorthe Dahl-Jensen, Anders Svensson, Bo M. Vinther, Sepp Kipfstuhl, Gwydion Jones, Nanna B. Karlsson, Sergio Henrique Faria, Vasileios Gkinis, Helle Astrid Kjær, Tobias Erhardt, Sarah M. P. Berben, Kerim H. Nisancioglu, Iben Koldtoft, and Sune Olander Rasmussen
Clim. Past, 16, 2359–2380, https://doi.org/10.5194/cp-16-2359-2020, https://doi.org/10.5194/cp-16-2359-2020, 2020
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We present a first chronology for the East Greenland Ice-core Project (EGRIP) over the Holocene and last glacial termination. After field measurements and processing of the ice-core data, the GICC05 timescale is transferred from the NGRIP core to the EGRIP core by means of matching volcanic events and common patterns (381 match points) in the ECM and DEP records. The new timescale is named GICC05-EGRIP-1 and extends back to around 15 kyr b2k.
Baojuan Huai, Michiel R. van den Broeke, and Carleen H. Reijmer
The Cryosphere, 14, 4181–4199, https://doi.org/10.5194/tc-14-4181-2020, https://doi.org/10.5194/tc-14-4181-2020, 2020
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This study presents the surface energy balance (SEB) of the Greenland Ice Sheet (GrIS) using a SEB model forced with observations from automatic weather stations (AWSs). We correlate ERA5 with AWSs to show a significant positive correlation of GrIS summer surface temperature and melt with the Greenland Blocking Index and weaker and opposite correlations with the North Atlantic Oscillation. This analysis may help explain melting patterns in the GrIS with respect to circulation anomalies.
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
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The study investigates precipitation changes in the Alps, using observations and a 7 km resolution climate simulation over 1900–2010. An increase in mean precipitation is found in winter over the Alps, whereas a drying occurred in summer in the surrounding plains. A general increase in the daily annual maximum of precipitation is evidenced (20 to 40 % per century), suggesting an increase in extreme events that is significant only when considering long time series, typically 50 to 80 years.
Kenneth D. Mankoff, Brice Noël, Xavier Fettweis, Andreas P. Ahlstrøm, William Colgan, Ken Kondo, Kirsty Langley, Shin Sugiyama, Dirk van As, and Robert S. Fausto
Earth Syst. Sci. Data, 12, 2811–2841, https://doi.org/10.5194/essd-12-2811-2020, https://doi.org/10.5194/essd-12-2811-2020, 2020
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This work partitions regional climate model (RCM) runoff from the MAR and RACMO RCMs to hydrologic outlets at the ice margin and coast. Temporal resolution is daily from 1959 through 2019. Spatial grid is ~ 100 m, resolving individual streams. In addition to discharge at outlets, we also provide the streams, outlets, and basin geospatial data, as well as a script to query and access the geospatial or time series discharge data from the data files.
Xavier Fettweis, Stefan Hofer, Uta Krebs-Kanzow, Charles Amory, Teruo Aoki, Constantijn J. Berends, Andreas Born, Jason E. Box, Alison Delhasse, Koji Fujita, Paul Gierz, Heiko Goelzer, Edward Hanna, Akihiro Hashimoto, Philippe Huybrechts, Marie-Luise Kapsch, Michalea D. King, Christoph Kittel, Charlotte Lang, Peter L. Langen, Jan T. M. Lenaerts, Glen E. Liston, Gerrit Lohmann, Sebastian H. Mernild, Uwe Mikolajewicz, Kameswarrao Modali, Ruth H. Mottram, Masashi Niwano, Brice Noël, Jonathan C. Ryan, Amy Smith, Jan Streffing, Marco Tedesco, Willem Jan van de Berg, Michiel van den Broeke, Roderik S. W. van de Wal, Leo van Kampenhout, David Wilton, Bert Wouters, Florian Ziemen, and Tobias Zolles
The Cryosphere, 14, 3935–3958, https://doi.org/10.5194/tc-14-3935-2020, https://doi.org/10.5194/tc-14-3935-2020, 2020
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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
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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.
Christiaan T. van Dalum, Willem Jan van de Berg, Stef Lhermitte, and Michiel R. van den Broeke
The Cryosphere, 14, 3645–3662, https://doi.org/10.5194/tc-14-3645-2020, https://doi.org/10.5194/tc-14-3645-2020, 2020
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The reflectivity of sunlight, which is also known as albedo, is often inadequately modeled in regional climate models. Therefore, we have implemented a new snow and ice albedo scheme in the regional climate model RACMO2. In this study, we evaluate a new RACMO2 version for the Greenland ice sheet by using observations and the previous model version. RACMO2 output compares well with observations, and by including new processes we improve the ability of RACMO2 to make future climate projections.
Christine S. Hvidberg, Aslak Grinsted, Dorthe Dahl-Jensen, Shfaqat Abbas Khan, Anders Kusk, Jonas Kvist Andersen, Niklas Neckel, Anne Solgaard, Nanna B. Karlsson, Helle Astrid Kjær, and Paul Vallelonga
The Cryosphere, 14, 3487–3502, https://doi.org/10.5194/tc-14-3487-2020, https://doi.org/10.5194/tc-14-3487-2020, 2020
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The Northeast Greenland Ice Stream (NEGIS) extends around 600 km from its onset in the interior of Greenland to the coast. Several maps of surface velocity and topography in Greenland exist, but accuracy is limited due to the lack of validation data. Here we present results from a 5-year GPS survey in an interior section of NEGIS. We use the data to assess a list of satellite-derived ice velocity and surface elevation products and discuss the implications for the ice stream flow in the area.
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
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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
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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
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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.
Shujie Wang, Marco Tedesco, Patrick Alexander, Min Xu, and Xavier Fettweis
The Cryosphere, 14, 2687–2713, https://doi.org/10.5194/tc-14-2687-2020, https://doi.org/10.5194/tc-14-2687-2020, 2020
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Glacial algal blooms play a significant role in darkening the Greenland Ice Sheet during summertime. The dark pigments generated by glacial algae could substantially reduce the bare ice albedo and thereby enhance surface melt. We used satellite data to map the spatial distribution of glacial algae and characterized the seasonal growth pattern and interannual trends of glacial algae in southwestern Greenland. Our study is important for bridging microbial activities with ice sheet mass balance.
Cited articles
Allen, L., Scott, J., Brand, A., Hlava, M., and Altman, M.: Publishing: Credit where credit is due, Nature, 508, 312–313, https://doi.org/10.1038/508312a, 2014. a, b
Allen, L., O'Connell, A., and Kiermer, V.: How can we ensure visibility and diversity in research contributions? How the Contributor Role Taxonomy (CRediT) is helping the shift from authorship to contributorship, Learn. Publ., 32, 71–74, https://doi.org/10.1002/leap.1210, 2019. a, b
Amory, C., Kittel, C., Le Toumelin, L., Agosta, C., Delhasse, A., Favier, V., and Fettweis, X.: Performance of MAR (v3.11) in simulating the drifting-snow climate and surface mass balance of Adélie Land, East Antarctica, Geosci. Model Dev., 14, 3487–3510, https://doi.org/10.5194/gmd-14-3487-2021, 2021. a
Andresen, C. S., Straneo, F., Ribergaard, M. H., Bjørk, A. A., Andersen, T. J., Kuijpers, A., Nørgaard-Pedersen, N., Kjær, K. H., Schjøth, F., Weckström, K., and Ahlstrøm, A. P.: Rapid response of Helheim Glacier in Greenland to climate variability over the past century, Nat. Geosci., 5, 37–41, https://doi.org/10.1038/NGEO1349, 2012. a
Anonymous: RC1: Comment on essd-2021-131, https://doi.org/10.5194/essd-2021-131-rc1, 2021a. a
Anonymous: RC2: Comment on essd-2021-131, https://doi.org/10.5194/essd-2021-131-rc2, 2021b. a
Barletta, V. R., Sørensen, L. S., and Forsberg, R.: Scatter of mass changes estimates at basin scale for Greenland and Antarctica, The Cryosphere, 7, 1411–1432, https://doi.org/10.5194/tc-7-1411-2013, 2013. a, b, c
Barletta, V. R., Sørensen, L. S., Simonsen, S. B., and Forsberg, R.: Gravitational mass balance of Greenland 2003 to present v2.1, DTU Data [data set], https://doi.org/10.11583/DTU.12866579.v1, 2020. a
Bengtsson, L., Andrae, U., Aspelien, T., Batrak, Y., Calvo, J., de Rooy, W., Gleeson, E., Hansen-Sass, B., Homleid, M., Hortal, M., Ivarsson, K.-I., Lenderink, G., Niemelä, S., Nielsen, K. P., Onvlee, J., Rontu, L., Samuelsson, P., Muñoz, D. S., Subias, A., Tijm, S., Toll, V., Yang, X., and Køltzow, M. Ø.: The HARMONIE–AROME Model Configuration in the ALADIN–HIRLAM NWP System, Mon. Weather Rev., 145, 1919–1935, https://doi.org/10.1175/mwr-d-16-0417.1, 2017. a
Bjørk, A. A., Kjær, K. H., Korsgaard, N. J., Khan, S. A., Kjeldsen, K. K., Andresen, C. S., Box, J. E., Larsen, N. K., and Funder, S.: An aerial view of 80 years of climate-related glacier fluctuations in southeast Greenland, Nat. Geosci., 5, 427–432, https://doi.org/10.1038/NGEO1481, 2012. a
Boers, N. and Rypdal, M.: Critical slowing down suggests that the western Greenland Ice Sheet is close to a tipping point, P. Natl. Acad. Sci. USA, 118, e2024192118, https://doi.org/10.1073/pnas.2024192118, 2021. a
Bolch, T., Sørensen, L. S., Simonsen, S. B., Mölg, N., Machguth, H., Rastner, P., and Paul, F.: Mass loss of Greenland's glaciers and ice caps 2003–2008 revealed from ICESat data, Geophys. Res. Lett., 40, 875–881, https://doi.org/10.1002/grl.50270, 2013. a, b
Box, J. E.: Greenland ice sheet mass balance reconstruction. Part II: surface mass balance (1840–2010), J. Climate, 26, 6974–6989, https://doi.org/10.1175/JCLI-D-12-00518.1, 2013. a, b
Box, J. E. and Colgan, W.: Greenland ice sheet mass balance reconstruction. Part III: marine ice loss and total mass balance (1840–2010), J. Climate, 26, 6990–7002, https://doi.org/10.1175/JCLI-D-12-00546.1, 2013. a, b, c
Box, J. E., Cressie, N., Bromwich, D. H., Jung, J.-H., van den Broeke, M. R., van Angelen, J. H., Forster, R. R., Miège, C., Mosley-Thompson, E., Vinther, B., and McConnell, J. R.: Greenland ice sheet mass balance reconstruction. Part I: Net snow accumulation (1600–2009), J. Climate, 26, 3919–3934, https://doi.org/10.1175/JCLI-D-12-00373.1, 2013. a, b
Brand, A., Allen, L., Altman, M., Hlava, M., and Scott, J.: Beyond authorship: attribution, contribution, collaboration, and credit, Learn. Publ., 28, 151–155, https://doi.org/10.1087/20150211, 2015. a, b
Cappelen, J.: The observed climate of Greenland, 1958–99-with climatological
standard normals, 1961–90, Danish Meteorological Institute, Copenhagen, Denmark,
2001. a
Cappelen, J., Laursen, E. V., Jørgensen, P. V., and Kern-Hansen, C.: DMI Monthly Climate Data Collection 1768–2005: Denmark, The Faroe Islands and Greenland, DMI, Copenhagen, Denmark, 2006. a
Cappelen, J., Laursen, E., Jørgensen, P., and Kern-Hansen, C.: DMI monthly climate data collection 1768–2010, Denmark, the Faroe Islands and Greenland, Tech. rep., DMI Technical Report 11-05, Copenhagen, 2011. a
Christensen, O. B., Drews, M., Hesselbjerg Christensen, J., Dethloff, K., Ketelsen, K., Hebestadt, I., and Rinke, A.: The HIRHAM Regional Climate Model. Version 5 (beta), no. 06-17 in Denmark, Danish Meteorological Institute, Technical Report, Danish Climate Centre, Danish Meteorological Institute, Copenhagen, Denmark, 2007. a
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
Colgan, W.: Greenland ice sheet mass balance assessment (1995–2019), GEUS
Dataverse [data set], https://doi.org/10.22008/FK2/XOTO3K, 2021. a
Colgan, W., Abdalati, W., Citterio, M., Csatho, B., Fettweis, X., Luthcke, S., Moholdt, G., Simonsen, S. B., and Stober, M.: Hybrid glacier Inventory, Gravimetry and Altimetry (HIGA) mass balance product for Greenland and the Canadian Arctic, Remote Sens. Environ., 168, 24–39, https://doi.org/10.1016/j.rse.2015.06.016, 2015. a
Colgan, W., Mankoff, K. D., Kjeldsen, K. K., Bjørk, A. A., Box, J. E., Simonsen, S. B., Sørensen, L. S., Khan, S. A., Solgaard, A. M., Forsberg, R., Skourup, H., Stenseng, L., Kristensen, S. S., Hvidegaard, S. M., Citterio, M., Karlsson, N., Fettweis, X., Ahlstrøm, A. P., Andersen, S. B., van As, D., and Fausto, R. S.: Greenland ice sheet mass balance assessed by PROMICE (1995–2015), Geol. Surv. Den. Greenl., 43, e2019430201, https://doi.org/10.34194/GEUSB-201943-02-01, 2019. a, b, c, d, e, f, g, h, i, j, k, l, m, n, o, p, q, r, s, t, u, v, w, x
Cuffey, K. M. and Paterson, W. S. B.: The physics of glaciers, 4th edn., Academic Press, Burlington, MA USA, 2010. a
Dask Development Team: Dask: Library for dynamic task scheduling, available
at: https://dask.org (last access: 26 October 2021), 2016. a
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A. C. M., van de Berg, I., Biblot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Greer, A. J., Haimberger, L., Healy, S. B., Hersbach, H., Holm, E. V., Isaksen, L., Kallberg, P., Kohler, M., Matricardi, M., McNally, A. P., Mong-Sanz, B. M., Morcette, J.-J., Park, B.-K., Peubey, C., de Rosnay, P., Tavolato, C., Thepaut, J. N., and Vitart, F.: The ERA-Interim reanalysis: configuration and performance of the data assimilation system, Q. J. Roy. Meteor. Soc., 137, 553–597, https://doi.org/10.1002/qj.828, 2011. a, b
Eerola, K.: About the performance of HIRLAM version 7.0, Hirlam Newsletter, 51, 93–102, 2006. a
Enderlin, E. M., Howat, I. M., Jeong, S., Noh, M.-J., van Angelen, J. H., and van den Broeke, M. R.: An improved mass budget for the Greenland Ice Sheet, Geophys. Res. Lett., 41, 866–872, https://doi.org/10.1002/2013GL059010, 2014. a
Ettema, J., van den Broeke, M. R., van Meijgaard, E., van de Berg, W. J., Box, J. E., and Steffen, K.: Climate of the Greenland ice sheet using a high-resolution climate model – Part 1: Evaluation, The Cryosphere, 4, 511–527, https://doi.org/10.5194/tc-4-511-2010, 2010. a, b
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, c, d, e, f, g, h, i
Fox Maule, C., Purucker, M. E., and Olsen, N.: Inferring magnetic crustal
thickness and geothermal heat flux from crustal magnetic field models, Danish Climate Centre Report, Copenhagen, Denmark, 2009. a
Gallée, H. and Schayes, G.: Development of a Three-Dimensional Meso-γ Primitive Equation Model: Katabatic Winds Simulation in the Area of Terra Nova Bay, Antarctica, Mon. Weather Rev., 122, 671–685, https://doi.org/10.1175/1520-0493(1994)122<0671:doatdm>2.0.co;2, 1994. a
Gallée, H., Guyomarc'h, G., and Brun, E.: Impact Of Snow Drift On The Antarctic Ice Sheet Surface Mass Balance: Possible Sensitivity To Snow-Surface Properties, Bound.-Lay. Meteorol., 99, 1–19, https://doi.org/10.1023/a:1018776422809, 2001. a
Gardner, A. S., Moholdt, G., Cogley, J. G., Wouters, B., Arendt, A. A., Wahr, J., Berthier, E., Hock, R., Pfeffer, W. T., Kaser, G., Ligtenberg, S. R. M., Bolch, T., Sharp, M. J., Hagen, J. O., Van Den Broeke, M. R., and Paul, F.: A Reconciled Estimate of Glacier Contributions to Sea Level Rise: 2003 to 2009, Science, 340, 852–857, https://doi.org/10.1126/science.1234532, 2013. a
GDAL/OGR contributors: GDAL/OGR Geospatial Data Abstraction software Library,
Open Source Geospatial Foundation, available at: https://gdal.org (last access: 26 October 2021), 2020. a
Gillet-Chaulet, F., Gagliardini, O., Seddik, H., Nodet, M., Durand, G., Ritz, C., Zwinger, T., Greve, R., and Vaughan, D. G.: Greenland ice sheet contribution to sea-level rise from a new-generation ice-sheet model, The Cryosphere, 6, 1561–1576, https://doi.org/10.5194/tc-6-1561-2012, 2012. a
Greene, C. A., Gardner, A. S., and Andrews, L. C.: Detecting seasonal ice dynamics in satellite images, The Cryosphere, 14, 4365–4378, https://doi.org/10.5194/tc-14-4365-2020, 2020. a
Groh, A., Horwath, M., Horvath, A., Meister, R., Sørensen, L. S., Barletta, V. R., Forsberg, R., Wouters, B., Ditmar, P., Ran, J., Klees, R., Su, X., Shang, K., Guo, J., Shum, C. K., Schrama, E., and Shepherd, A.: Evaluating GRACE Mass Change Time Series for the Antarctic and Greenland Ice Sheet – Methods and Results, Geosciences, 9, 415, https://doi.org/10.3390/geosciences9100415, 2019. a
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., Chiara, G. D., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J.: The ERA5 global reanalysis, Q. J. Roy. Meteor. Soc., 146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020. a
Howat, I. M., Negrete, A., and Smith, B. E.: The Greenland Ice Mapping Project (GIMP) land classification and surface elevation data sets, The Cryosphere, 8, 1509–1518, https://doi.org/10.5194/tc-8-1509-2014, 2014. a, b
Hoyer, S. and Hamman, J. J.: xarray: N-D labeled Arrays and Datasets in Python, Journal of Open Research Software, 5, 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
Joughin, I., Smith, B. E., and Howat, I.: Greenland Ice Mapping Project: ice flow velocity variation at sub-monthly to decadal timescales, The Cryosphere, 12, 2211–2227, https://doi.org/10.5194/tc-12-2211-2018, 2018. a
Karlsson, N. B.: Greenland Ice Sheet Basal Melt, GEUS Dataverse [data set], https://doi.org/10.22008/FK2/PLNUEO, 2021. a, b, c
Karlsson, N. B., Solgaard, A. M., Mankoff, K. D., Gillet-Chaulet, F., MacGregor, J. A., Box, J. E., Citterio, M., Colgan, W. T., Larsen, S. H., Kjeldsen, K. K., Korsgaard, N. J., Benn, D. I., Hewitt, I., and Fausto, R. S.: A first constraint on basal melt-water production of the Greenland ice sheet, Nat. Commun., 12, 3461, https://doi.org/10.1038/s41467-021-23739-z, 2021. a, b, c, d, e, f, g, h, i, j
Khan, S. A.: Greenland Ice Sheet Surface Elevation Change, GEUS Data Center [data set], http://promice.org/PromiceDataPortal/api/download/90fb4cbf-e88e-4e26-af95-a47d19a9cf10, 2017. a
Khan, S. A., Aschwanden, A., Bjørk, A. A., Wahr, J., Kjeldsen, K. K., and Kjær, K. H.: Greenland ice sheet mass balance: a review, Rep. Prog. Phys., 78, 046801, https://doi.org/10.1088/0034-4885/78/4/046801, 2015. a, b
Khan, S. A., Sasgen, I., Bevis, M., van Dam, T., Bamber, J. L., Wahr, J., Willis, M., Kjær, K. H., Wouters, B., Helm, V., Csatho, B., Fleming, K., Bjørk, A. A., Aschwanden, A., Knudsen, P., and Munneke, P. K.: Geodetic measurements reveal similarities between post-Last Glacial Maximum and present-day mass loss from the Greenland ice sheet, Science Advances, 2, e1600931, https://doi.org/10.1126/sciadv.1600931, 2016. a, b
Khan, S. A., Bjørk, A. A., Bamber, J. L., Morlighem, M., Bevis, M., Kjær, K. H., Mouginot, J., Løkkegaard, A., Holland, D. M., Aschwanden, A., Zhang, B., Helm, V., Korsgaard, N. J., Colgan, W., Larsen, N. K., Lui, L., Hansen, K., Barletta, V., Dahl-Jensen, T. S., Søndergaard, A. S., Csatho, B. M., Sasgen, I., Box, J., and Schenk, T.: Centennial response of Greenland's three largest outlet glaciers, Nat. Commun., 11, 5718, https://doi.org/10.1038/s41467-020-19580-5, 2020. a
King, M. D., Howat, I. M., Jeong, S., Noh, M. J., Wouters, B., Noël, B., and van den Broeke, M. R.: Seasonal to decadal variability in ice discharge from the Greenland Ice Sheet, The Cryosphere, 12, 3813–3825, https://doi.org/10.5194/tc-12-3813-2018, 2018. a, b
King, M. D., Howat, I. M., Candela, S. G., Noh, M. J., Jeong, S., Noël, B. P. Y., van den Broeke, M. R., Wouters, B., and Negrete, A.: Dynamic ice loss from the Greenland Ice Sheet driven by sustained glacier retreat, Communications Earth and Environment, 1, 1, https://doi.org/10.1038/s43247-020-0001-2, 2020. a, b
Kjeldsen, K. K., Korsgaard, N. J., Bjørk, A. A., Khan, S. A., Box, J. E., Funder, S., Larsen, N. K., Bamber, J. L., Colgan, W., Broeke, M. v. d., Siggaard-Andersen, M.-L., Nuth, C., Schomacker, A., Andresen, C. S., Willerslev, E., and Kjær, K. H.: Spatial and temporal distribution of mass loss from the Greenland Ice Sheet since AD 1900, Nature, 528, 396–400, https://doi.org/10.1038/nature16183, 2015. a, b, c, d, e, f, g, h, i, j, k, l, m, n, o, p, q, r, s, t, u, v, w, x, y, z
Kjeldsen, K. K., Khan, S. A., Colgan, W. T., MacGregor, J. A., and Fausto, R. S.: Time-Varying Ice Sheet Mask: Implications on Ice-Sheet Mass Balance and Crustal Uplift, J. Geophys. Res.-Earth, 125, e2020JF005775, https://doi.org/10.1029/2020jf005775, 2020. a
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
Langen, P. L., Fausto, R. S., Vandecrux, B., Mottram, R. H., and Box, J. E.: Liquid Water Flow and Retention on the Greenland Ice Sheet in the Regional Climate Model HIRHAM5: Local and Large-Scale Impacts, Front. Earth Sci., 4, 110, https://doi.org/10.3389/feart.2016.00110, 2017. a, b, c, d
Laprise, R.: The Euler Equations of Motion with Hydrostatic Pressure as an Independent Variable, Mon. Weather Rev., 120, 197–207, https://doi.org/10.1175/1520-0493(1992)120<0197:teeomw>2.0.co;2, 1992. a
Lefebre, F.: Modeling of snow and ice melt at ETH Camp (West Greenland): A study of surface albedo, J. Geophys. Res., 108, 4231, https://doi.org/10.1029/2001jd001160, 2003. a
Lenaerts, J. T. M., van den Broeke, M. R., van Angelen, J. H., van Meijgaard, E., and Déry, S. J.: Drifting snow climate of the Greenland ice sheet: a study with a regional climate model, The Cryosphere, 6, 891–899, https://doi.org/10.5194/tc-6-891-2012, 2012. a
Lewis, G., Osterberg, E., Hawley, R., Whitmore, B., Marshall, H. P., and Box, J.: Regional Greenland accumulation variability from Operation IceBridge airborne accumulation radar, The Cryosphere, 11, 773–788, https://doi.org/10.5194/tc-11-773-2017, 2017. a
Lewis, G., Osterberg, E., Hawley, R., Marshall, H. P., Meehan, T., Graeter, K., McCarthy, F., Overly, T., Thundercloud, Z., and Ferris, D.: Recent precipitation decrease across the western Greenland ice sheet percolation zone, The Cryosphere, 13, 2797–2815, https://doi.org/10.5194/tc-13-2797-2019, 2019. a
Ligtenberg, S. R. M., Kuipers Munneke, P., Noël, B. P. Y., and van den Broeke, M. R.: Brief communication: Improved simulation of the present-day Greenland firn layer (1960–2016), The Cryosphere, 12, 1643–1649, https://doi.org/10.5194/tc-12-1643-2018, 2018. a
Lucas-Picher, P., Wulff-Nielsen, M., Christensen, J. H., Aðalgeirsdóttir, G., Mottram, R., and Simonsen, S. B.: Very high resolution regional climate model simulations over Greenland: Identifying added value, J. Geophys. Res.-Atmos., 117, D02108, https://doi.org/10.1029/2011jd016267, 2012. a
MacGregor, J. A., Fahnestock, M. A., Catania, G. A., Aschwanden, A., Clow, G. D., Colgan, W. T., Gogineni, P. S., Morlighem, M., Nowicki, S. M. J., Paden, J. D., Price, S. F., and Seroussi, H.: A synthesis of the basal thermal state of the Greenland Ice Sheet, J. Geophys. Res.-Earth, 121, 1328–1350, https://doi.org/10.1002/2015JF003803, 2016. a, b
Maier, N., Humphrey, N., Harper, J., and Meierbachtol, T.: Sliding dominates slow-flowing margin regions, Greenland Ice Sheet, Science Advances, 5, eaaw5406, https://doi.org/10.1126/sciadv.aaw5406, 2019. a
Maier, N., Gimbert, F., Gillet-Chaulet, F., and Gilbert, A.: Basal traction mainly dictated by hard-bed physics over grounded regions of Greenland, The Cryosphere, 15, 1435–1451, https://doi.org/10.5194/tc-15-1435-2021, 2021. a
Mankoff, K.: Greenland Ice Sheet solid ice discharge from 1986 through last month: Gates, GEUS Dataverse [data set], https://doi.org/10.22008/promice/data/ice_discharge/gates/v02, 2020. a, b
Mankoff, K. and Solgaard, A.: Ice Discharge, GEUS Dataverse [data set], https://doi.org/10.22008/promice/data/ice_discharge, 2020. a, b, c
Mankoff, K., Fettweis, X., Solgaard, A., Langen, P., Stendel, M., Noël, B., van den Broeke, M. R., Karlsson, N., Box, J. E., and Kjeldsen, K.: Greenland ice sheet mass balance from from 1840 through next week, GEUS Dataverse [data set], https://doi.org/10.22008/FK2/OHI23Z, 2021. 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, b, c
Mankoff, K. D., Noël, B., Fettweis, X., Ahlstrøm, A. P., Colgan, W., Kondo, K., Langley, K., Sugiyama, S., van As, D., and Fausto, R. S.: Greenland liquid water discharge from 1958 through 2019, Earth Syst. Sci. Data, 12, 2811–2841, https://doi.org/10.5194/essd-12-2811-2020, 2020a. a
Mankoff, K. D., van As, D., Lines, A., Bording, T., Elliott, J., Kraghede, R., Cantalloube, H., Oriot, H., Dubois-Fernandez, P., Ruault du Plessis, O., Vest Christiansen, A., Auken, E., Hansen, K., Colgan, W., and Karlsson, N. B.: Search and recovery of aircraft parts in ice-sheet crevasse fields using airborne and in situ geophysical sensors, J. Glaciol., 66, 496–508, https://doi.org/10.1017/jog.2020.26, 2020c. a
Martos, Y. M., Jordan, T. A., Catalán, M., Jordan, T. M., Bamber, J. L., and Vaughan, D. G.: Geothermal Heat Flux Reveals the Iceland Hotspot Track Underneath Greenland, Geophys. Res. Lett., 45, 8214–8222, https://doi.org/10.1029/2018gl078289, 2018. a
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, https://doi.org/10.25080/Majora-92bf1922-00a,
2010. a
Millan, R., Rignot, E., Mouginot, J., Wood, M., Bjørk, A. A., and Morlighem, M.: Vulnerability of Southeast Greenland glaciers to warm Atlantic Water from Operation IceBridge and Ocean Melting Greenland data, Geophys. Res. Lett., 45, 2688–2696, https://doi.org/10.1002/2017gl076561, 2018. 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, 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 4, all subsets used, NASA National Snow and Ice Data Center Distributed Active Archive Center [data set], Boulder, Colorado, USA, https://doi.org/10.5067/VLJ5YXKCNGXO, 2021. a, b
Mouginot, J., Rignot, E., Bjørk, A. A., van den Broeke, M., Millan, R.,
Morlighem, M., Noël, B., Scheuchl, B., and Wood, M.: Forty-six years of
Greenland Ice Sheet mass balance from 1972 to 2018, P. Natl. Acad. Sci. USA, 116,
9239–9244, https://doi.org/10.1073/pnas.1904242116, 2019. a, b, c, d, e, f, g, h, i, j, k, l, m, n, o, p
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
Nilsson, J., Vallelonga, P., Simonsen, S. B., Sørensen, L. S., Forsberg, R., Dahl-Jensen, D., Hirabayashi, M., Goto-Azuma, K., Hvidberg, C. S., Kjær, H. A., and Satow, K.: Greenland 2012 melt event effects on CryoSat-2 radar altimetry, Geophys. Res. Lett., 42, 3919–3926, 2015. a
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, Science Advances, 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, United States, 2006. a
Pfeffer, W. T., Meier, M. F., and Illangasekare, T. H.: Retention of Greenland runoff by refreezing: Implications for projected future sea level change, J. Geophys. Res., 96, 22117, https://doi.org/10.1029/91jc02502, 1991. a
Rastner, P., Bolch, T., Mölg, N., Machguth, H., Le Bris, R., and Paul, F.: The first complete inventory of the local glaciers and ice caps on Greenland, The Cryosphere, 6, 1483–1495, https://doi.org/10.5194/tc-6-1483-2012, 2012. a
Rezvanbehbahani, S., Stearns, L. A., van der Veen, C. J., Oswald, G. K. A., and Greve, R.: Constraining the geothermal heat flux in Greenland at regions of radar-detected basal water, J. Glaciol., 65, 1023–1034, https://doi.org/10.1017/jog.2019.79, 2019. a
Rignot, E., Mouginot, J., Scheuchl, B., van den Broeke, M., van Wessem, M. J., and Morlighem, M.: Four decades of Antarctic Ice Sheet mass balance from 1979–2017, P. Natl. Acad. Sci. USA, 116, 1095–1103, https://doi.org/10.1073/pnas.1812883116, 2019. a
Rignot, E. J., Box, J. E., Burgess, E. W., and Hanna, E.: Mass balance of the Greenland ice sheet from 1958 to 2007, Geophys. Res. Lett., 35, L20502, https://doi.org/10.1029/2008GL035417, 2008. 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, Austin, TX, 130–136, 2015. a
Roeckner, E., Bäuml, G., Bonaventura, L., Brokopf, R., Esch, M.,
Giorgetta, M., Hagemann, S., Kirchner, I., Kornblueh, L., Manzini, E.,
Rhodin, A., Schlese, U., Schulzweida, U., and
Tompkins, A.: The atmospheric general
circulation model ECHAM 5. Part I: Model description, Report No. 349, Max-Planck-Institut für Meteorologie, 2003. a
Rogozhina, I., Hagedoorn, J. M., Martinec, Z., Fleming, K., Soucek, O., Greve, R., and Thomas, M.: Effects of uncertainties in the geothermal heat flux distribution on the Greenland Ice Sheet: An assessment of existing heat flow models, J. Geophys. Res.-Earth, 117, F02025, https://doi.org/10.1029/2011JF002098, 2012. a
Ryser, C., Lüthi, M. P., Andrews, L. C., Hoffman, M. J., Catania, G. A., Hawley, R. L., Neumann, T. A., and Kristensen, S. S.: Sustained high basal motion of the Greenland ice sheet revealed by borehole deformation, J. Glaciol., 60, 647–660, https://doi.org/10.3189/2014JoG13J196, 2014. a
Sasgen, I., Van Den Broeke, M., Bamber, J. L., Rignot, E., Sørensen, L. S., Wouters, B., Martinec, Z., Velicogna, I., and Simonsen, S. B.: Timing and origin of recent regional ice-mass loss in Greenland, Earth Planet. Sc. Lett., 333–334, 293–303, https://doi.org/10.1016/j.epsl.2012.03.033, 2012. 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, Communications Earth and Environment, 1, 293–303, 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 [code], https://doi.org/10.5281/zenodo.3539275, 2019. a
Shapiro, N. M. and Ritzwoller, M. H.: Inferring Surface Heat Flux Distributions Guided by a Global Seismic Model: Particular Application to Antarctica, Earth Planet. Sc. Lett., 223, 213–224, https://doi.org/10.1016/j.epsl.2004.04.011, 2004. a
Shreve, R. L.: Movement of water in glaciers, J. Glaciol., 11, 205–214, 1972. a
Simmons, A. J. and Burridge, D. M.: An Energy and Angular-Momentum Conserving Vertical Finite-Difference Scheme and Hybrid Vertical Coordinates, Mon. Weather Rev., 109, 758–766, https://doi.org/10.1175/1520-0493(1981)109<0758:aeaamc>2.0.co;2, 1981. a
Simonsen, S. B., Barletta, V. R., Colgan, W., and Sørensen, L. S.: Greenland Ice Sheet mass balance (1992–2020) from calibrated radar altimetry, DTU [data set], https://doi.org/10.11583/DTU.13353062.v1, 2021b. a
Smith, B., Fricker, H. A., Gardner, A. S., Medley, B., Nilsson, J.,
Paolo, F. S., Holschuh, N., Adusumilli, S., Brunt, K., Csatho, B.,
Harbeck, K., Markus, T.,
Neumann, T., Siegfried, M. R., and Zwally, J. H.: Pervasive ice sheet mass
loss reflects competing ocean and atmosphere processes, Science, 368, eaaz5845,
https://doi.org/10.1126/science.aaz5845, 2020. a
Solgaard, A., Kusk, A., Merryman Boncori, J. P., Dall, J., Mankoff, K. D., Ahlstrøm, A. P., Andersen, S. B., Citterio, M., Karlsson, N. B., Kjeldsen, K. K., Korsgaard, N. J., Larsen, S. H., and Fausto, R. S.: Greenland ice velocity maps from the PROMICE project, Earth Syst. Sci. Data, 13, 3491–3512, https://doi.org/10.5194/essd-13-3491-2021, 2021. a, b, c, d
Stallman, R. M.: EMACS the Extensible, Customizable Self-Documenting Display Editor, in: Proceedings of the ACM SIGPLAN SIGOA Symposium on Text Manipulation, Association for Computing Machinery, New York, NY, USA, 147–156, https://doi.org/10.1145/800209.806466, 1981. a
Sutterley, T. C., Velicogna, I., Rignot, E. J., Mouginot, J., Flament, T., van den Broeke, M. R., van Wessem, J. M., and Reijmer, C. H.: Mass loss of the Amundsen Sea Embayment of West Antarctica from four independent techniques, Geophys. Res. Lett., 41, 8421–8428, https://doi.org/10.1002/2014GL061940, 2014. a
Sørensen, L. S., Simonsen, S. B., Nielsen, K., Lucas-Picher, P., Spada, G., Adalgeirsdottir, G., Forsberg, R., and Hvidberg, C. S.: Mass balance of the Greenland ice sheet (2003–2008) from ICESat data – the impact of interpolation, sampling and firn density, The Cryosphere, 5, 173–186, https://doi.org/10.5194/tc-5-173-2011, 2011. a
Tange, O.: GNU Parallel – The Command-Line Power Tool, ;login: The USENIX
Magazine, 36, 42–47, available at:
http://www.gnu.org/s/parallel (last access: 24 October 2021), 2011. a
Tedesco, M. and Fettweis, X.: Unprecedented atmospheric conditions (1948–2019) drive the 2019 exceptional melting season over the Greenland ice sheet, The Cryosphere, 14, 1209–1223, https://doi.org/10.5194/tc-14-1209-2020, 2020. a
Uppala, S. M., Kållberg, P. W., Simmons, A. J., Andrae, U., Da Costa Bechtold, V., Fiorino, M., Gibson, J., Haseler, J., Hernandez, A., Kelly, G. A., Li, X., Onogi, K., Saarinen, S., Sokka, N., Allan, R. P., Anderson, E., Arpe, K., Balmaseda, M. A., Beljaars, A. C. M., Van De Berg, L., Bidlot, J., Bormann, N., Caires, S., Chevallier, F., Dethof, A., Dragosavac, M., Fisher, M., Fuentes, M., Hagemann, S., Hólm, E., Hoskins, B. J., Isaksen, L., Janssen, P. A. E. M., Jenne, R., Mcnally, A. P., Mahfouf, J.-F., Morcrette, J.-J., Rayner, N. A., Saunders, R. W., Simon, P., Sterl, A., Trenbreth, K. E., Untch, A., Vasiljevic, D., Viterbo, P., and Woollen, J.: The ERA-40 re-analysis, Q. J. Roy. Meteor. Soc., 131, 2961–3012, https://doi.org/10.1256/qj.04.176, 2005. a
van Angelen, J. H., Lenaerts, J. T. M., Lhermitte, S., Fettweis, X., Kuipers Munneke, P., van den Broeke, M. R., van Meijgaard, E., and Smeets, C. J. P. P.: Sensitivity of Greenland Ice Sheet surface mass balance to surface albedo parameterization: a study with a regional climate model, The Cryosphere, 6, 1175–1186, https://doi.org/10.5194/tc-6-1175-2012, 2012. a
van de Berg, W. J. and Medley, B.: Brief Communication: Upper-air relaxation in RACMO2 significantly improves modelled interannual surface mass balance variability in Antarctica, The Cryosphere, 10, 459–463, https://doi.org/10.5194/tc-10-459-2016, 2016.
a
Van Rossum, G. and Drake Jr., F. L.: Python reference manual, Centrum voor Wiskunde en Informatica Amsterdam, 1995. a
Velicogna, I., Mohajerani, Y., A, G., Landerer, F., Mouginot, J., Noel, B., Rignot, E., Sutterley, T., Broeke, M., Wessem, M., Rignot, E., Sutterley, T., van den Broeke, M., van Wessem, M., and Wieseand, D.: Continuity of Ice Sheet Mass Loss in Greenland and Antarctica From the GRACE and GRACE Follow-On Missions, Geophys. Res. Lett., 47, e2020GL087291, https://doi.org/10.1029/2020gl087291, 2020. a
Vinther, B. M., Andersen, K. K., Jones, P. D., Briffa, K. R., and Cappelen, J.: Extending Greenland temperature records into the late eighteenth century, J. Geophys. Res., 111, D11105, https://doi.org/10.1029/2005jd006810, 2006. a
Vionnet, V., Brun, E., Morin, S., Boone, A., Faroux, S., Le Moigne, P., Martin, E., and Willemet, J.-M.: The detailed snowpack scheme Crocus and its implementation in SURFEX v7.2, Geosci. Model Dev., 5, 773–791, https://doi.org/10.5194/gmd-5-773-2012, 2012. a
Wang, Z. Q. and Randriamampianina, R.: The Impact of Assimilating Satellite Radiance Observations in the Copernicus European Regional Reanalysis (CERRA), Remote Sens.-Basel, 13, 426, https://doi.org/10.3390/rs13030426, 2021. a
Yang, X., Palmason, B., Sattler, K., Thorsteinsson, S., Amstrup, B., Dahlbom, M., Hansen Sass, B., Pagh Nielsen, K., and Petersen, G. N.: IGB, the Upgrade to the Joint Operational HARMONIE by DMI and IMO in 2018, ALADIN-HIRLAM Newsletter, 93–96, 2018. a
Zemp, M., Huss, M., Eckert, N., Thibert, E., Paul, F., Nussbaumer, S. U., and Gärtner-Roer, I.: Brief communication: Ad hoc estimation of glacier contributions to sea-level rise from the latest glaciological observations, The Cryosphere, 14, 1043–1050, https://doi.org/10.5194/tc-14-1043-2020, 2020. a
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
Zwally, H. J. and Giovinetto, M. B.: Overview and Assessment of Antarctic Ice-Sheet Mass Balance Estimates: 1992–2009, Surv. Geophys., 32, 1–26, https://doi.org/10.1007/s10712-011-9123-5, 2011. a
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.
We estimate the daily mass balance and its components (surface, marine, and basal mass balance)...
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