Articles | Volume 14, issue 11
https://doi.org/10.5194/tc-14-3785-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-14-3785-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
06 Nov 2020
Research article |
| 06 Nov 2020
| 06 Nov 2020
The firn meltwater Retention Model Intercomparison Project (RetMIP): evaluation of nine firn models at four weather station sites on the Greenland ice sheet
Geological Survey of Denmark and Greenland, Copenhagen, Denmark
Department of Civil Engineering, Technical University of Denmark,
Kgs. Lyngby, Denmark
Ruth Mottram
Danish Meteorological Institute, Copenhagen, Denmark
Peter L. Langen
Department of Environmental Science, iClimate, Aarhus University, Roskilde, Denmark
Danish Meteorological Institute, Copenhagen, Denmark
Robert S. Fausto
Geological Survey of Denmark and Greenland, Copenhagen, Denmark
Martin Olesen
Danish Meteorological Institute, Copenhagen, Denmark
C. Max Stevens
Department of Earth and Space Sciences, University of Washington, Seattle, WA,
USA
Vincent Verjans
Lancaster Environment Centre, Lancaster University, Lancaster, UK
Amber Leeson
Lancaster Environment Centre, Lancaster University, Lancaster, UK
Stefan Ligtenberg
Institute for Marine and Atmospheric research, Utrecht University, Utrecht, the Netherlands
Weather Impact, Amersfoort, the Netherlands
Peter Kuipers Munneke
Institute for Marine and Atmospheric research, Utrecht University, Utrecht, the Netherlands
Sergey Marchenko
Department of Earth Sciences, Uppsala University, Uppsala, Sweden
Ward van Pelt
Department of Earth Sciences, Uppsala University, Uppsala, Sweden
Colin R. Meyer
Thayer School of Engineering, Dartmouth College, Hanover, NH, USA
Sebastian B. Simonsen
National Space Institute, Technical University of Denmark, Kgs.
Lyngby, Denmark
Achim Heilig
Department of Earth and Environmental Sciences, Ludwig Maximilian University, Munich, Germany
Samira Samimi
Department of Geography, University of Calgary, Calgary, AB, Canada
Shawn Marshall
Department of Geography, University of Calgary, Calgary, AB, Canada
Horst Machguth
Department of Geosciences, University of Fribourg, Fribourg, Switzerland
Michael MacFerrin
Cooperative Institute for Research in Environmental Sciences,
University of Colorado, Boulder, CO, USA
Masashi Niwano
Meteorological Research Institute, Japan Meteorological Agency,
Tsukuba, 305-0052 Japan
Olivia Miller
US Geological Survey, Utah Water Science Center, Salt Lake City,
UT, USA
Clifford I. Voss
US Geological Survey, Menlo Park, CA, USA
Jason E. Box
Geological Survey of Denmark and Greenland, Copenhagen, Denmark
Related authors
Josephine Yolanda Lindsey-Clark, Aslak Grinsted, Baptiste Vandecrux, and Christine Schøtt Hvidberg
EGUsphere, https://doi.org/10.5194/egusphere-2025-2516, https://doi.org/10.5194/egusphere-2025-2516, 2025
This preprint is open for discussion and under review for The Cryosphere (TC).
Short summary
Short summary
We present a new method to improve estimates of snowfall across Greenland, a crucial factor in predicting sea-level rise. Current climate models often misrepresent snowfall patterns, resulting in significant long-term errors. By using two million observations, our method corrects model errors and produces more accurate snowfall maps. The improved maps can help to reduce uncertainty in sea-level rise projections and enhance understanding of Greenland’s proximity to critical melting thresholds.
Alamgir Hossan, Andreas Colliander, Baptiste Vandecrux, Nicole-Jeanne Schlegel, Joel Harper, Shawn Marshall, and Julie Z. Miller
EGUsphere, https://doi.org/10.5194/egusphere-2024-2563, https://doi.org/10.5194/egusphere-2024-2563, 2024
Short summary
Short summary
We used L-band observations from the SMAP mission to quantify the surface and subsurface liquid water amounts (LWA) in the percolation zone of the Greenland ice sheet. The algorithm is described, and the validation results are provided. The results demonstrate the potential for creating an LWA data product across GrIS, which will advance our understanding of ice sheet physical processes for better projection of Greenland’s contribution to global sea level rise.
Anja Rutishauser, Kirk M. Scanlan, Baptiste Vandecrux, Nanna B. Karlsson, Nicolas Jullien, Andreas P. Ahlstrøm, Robert S. Fausto, and Penelope How
The Cryosphere, 18, 2455–2472, https://doi.org/10.5194/tc-18-2455-2024, https://doi.org/10.5194/tc-18-2455-2024, 2024
Short summary
Short summary
The Greenland Ice Sheet interior is covered by a layer of firn, which is important for surface meltwater runoff and contributions to global sea-level rise. Here, we combine airborne radar sounding and laser altimetry measurements to delineate vertically homogeneous and heterogeneous firn. Our results reveal changes in firn between 2011–2019, aligning well with known climatic events. This approach can be used to outline firn areas primed for significantly changing future meltwater runoff.
Baptiste Vandecrux, Robert S. Fausto, Jason E. Box, Federico Covi, Regine Hock, Åsa K. Rennermalm, Achim Heilig, Jakob Abermann, Dirk van As, Elisa Bjerre, Xavier Fettweis, Paul C. J. P. Smeets, Peter Kuipers Munneke, Michiel R. van den Broeke, Max Brils, Peter L. Langen, Ruth Mottram, and Andreas P. Ahlstrøm
The Cryosphere, 18, 609–631, https://doi.org/10.5194/tc-18-609-2024, https://doi.org/10.5194/tc-18-609-2024, 2024
Short summary
Short summary
How fast is the Greenland ice sheet warming? In this study, we compiled 4500+ temperature measurements at 10 m below the ice sheet surface (T10m) from 1912 to 2022. We trained a machine learning model on these data and reconstructed T10m for the ice sheet during 1950–2022. After a slight cooling during 1950–1985, the ice sheet warmed at a rate of 0.7 °C per decade until 2022. Climate models showed mixed results compared to our observations and underestimated the warming in key regions.
Baptiste Vandecrux, Jason E. Box, Andreas P. Ahlstrøm, Signe B. Andersen, Nicolas Bayou, William T. Colgan, Nicolas J. Cullen, Robert S. Fausto, Dominik Haas-Artho, Achim Heilig, Derek A. Houtz, Penelope How, Ionut Iosifescu Enescu, Nanna B. Karlsson, Rebecca Kurup Buchholz, Kenneth D. Mankoff, Daniel McGrath, Noah P. Molotch, Bianca Perren, Maiken K. Revheim, Anja Rutishauser, Kevin Sampson, Martin Schneebeli, Sandy Starkweather, Simon Steffen, Jeff Weber, Patrick J. Wright, Henry Jay Zwally, and Konrad Steffen
Earth Syst. Sci. Data, 15, 5467–5489, https://doi.org/10.5194/essd-15-5467-2023, https://doi.org/10.5194/essd-15-5467-2023, 2023
Short summary
Short summary
The Greenland Climate Network (GC-Net) comprises stations that have been monitoring the weather on the Greenland Ice Sheet for over 30 years. These stations are being replaced by newer ones maintained by the Geological Survey of Denmark and Greenland (GEUS). The historical data were reprocessed to improve their quality, and key information about the weather stations has been compiled. This augmented dataset is available at https://doi.org/10.22008/FK2/VVXGUT (Steffen et al., 2022).
Michael J. MacFerrin, C. Max Stevens, Baptiste Vandecrux, Edwin D. Waddington, and Waleed Abdalati
Earth Syst. Sci. Data, 14, 955–971, https://doi.org/10.5194/essd-14-955-2022, https://doi.org/10.5194/essd-14-955-2022, 2022
Short summary
Short summary
The vast majority of the Greenland ice sheet's surface is covered by pluriannual snow, also called firn, that accumulates year after year and is compressed into glacial ice. The thickness of the firn layer changes through time and responds to the surface climate. We present continuous measurement of the firn compaction at various depths for eight sites. The dataset will help to evaluate firn models, interpret ice cores, and convert remotely sensed ice sheet surface height change to mass loss.
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
Short summary
Short summary
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.
Robert S. Fausto, Dirk van As, Kenneth D. Mankoff, Baptiste Vandecrux, Michele Citterio, Andreas P. Ahlstrøm, Signe B. Andersen, William Colgan, Nanna B. Karlsson, Kristian K. Kjeldsen, Niels J. Korsgaard, Signe H. Larsen, Søren Nielsen, Allan Ø. Pedersen, Christopher L. Shields, Anne M. Solgaard, and Jason E. Box
Earth Syst. Sci. Data, 13, 3819–3845, https://doi.org/10.5194/essd-13-3819-2021, https://doi.org/10.5194/essd-13-3819-2021, 2021
Short summary
Short summary
The Programme for Monitoring of the Greenland Ice Sheet (PROMICE) has been measuring climate and ice sheet properties since 2007. Here, we present our data product from weather and ice sheet measurements from a network of automatic weather stations mainly located in the melt area of the ice sheet. Currently the PROMICE automatic weather station network includes 25 instrumented sites in Greenland.
Heiko Goelzer, Constantijn J. Berends, Fredrik Boberg, Gael Durand, Tamsin Edwards, Xavier Fettweis, Fabien Gillet-Chaulet, Quentin Glaude, Philippe Huybrechts, Sébastien Le clec'h, Ruth Mottram, Brice Noël, Martin Olesen, Charlotte Rahlves, Jeremy Rohmer, Michiel van den Broeke, and Roderik S. W. van de Wal
EGUsphere, https://doi.org/10.5194/egusphere-2025-3098, https://doi.org/10.5194/egusphere-2025-3098, 2025
This preprint is open for discussion and under review for The Cryosphere (TC).
Short summary
Short summary
We present an ensemble of ice sheet model projections for the Greenland ice sheet. The focus is on providing projections that improve our understanding of the range future sea-level rise and the inherent uncertainties over the next 100 to 300 years. Compared to earlier work we more fully account for some of the uncertainties in sea-level projections. We include a wider range of climate model output, more climate change scenarios and we extend projections schematically up to year 2300.
Marcus Gastaldello, Enrico Mattea, Martin Hoelzle, and Horst Machguth
The Cryosphere, 19, 2983–3008, https://doi.org/10.5194/tc-19-2983-2025, https://doi.org/10.5194/tc-19-2983-2025, 2025
Short summary
Short summary
Inside the highest glaciers of the Alps lies an invaluable archive of data revealing the Earth's historic climate. However, as the atmosphere warms due to climate change, so does the glaciers' internal temperature, threatening the future longevity of these records. Using our customised Python model, validated by on-site measurements, we show how a doubling in surface melt has caused a warming of 1.5 °C in the past 21 years and explore the challenges of modelling in complex mountainous terrain.
Anna Puggaard, Nicolaj Hansen, Ruth Mottram, Thomas Nagler, Stefan Scheiblauer, Sebastian B. Simonsen, Louise S. Sørensen, Jan Wuite, and Anne M. Solgaard
The Cryosphere, 19, 2963–2981, https://doi.org/10.5194/tc-19-2963-2025, https://doi.org/10.5194/tc-19-2963-2025, 2025
Short summary
Short summary
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.
Valeria Di Biase, Peter Kuipers Munneke, Bert Wouters, Michiel R. van den Broeke, and Maurice van Tiggelen
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).
Short summary
Short summary
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.
Gregor Luetzenburg, Niels J. Korsgaard, Anna K. Deichmann, Tobias Socher, Karin Gleie, Thomas Scharffenberger, Rasmus P. Meyer, Dominik Fahrner, Eva B. Nielsen, Penelope How, Anders A. Bjørk, Kristian K. Kjeldsen, Andreas P. Ahlstrøm, and Robert S. Fausto
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-415, https://doi.org/10.5194/essd-2025-415, 2025
Preprint under review for ESSD
Short summary
Short summary
We mapped the edge of the Greenland Ice Sheet using recent satellite images to create a detailed outline of its extent in 2022. This helps track how the ice sheet is changing as the climate warms. By carefully combining satellite data and checking results by hand, we created one of the most accurate maps of the ice sheet to date. This map supports research on ice loss and improves predictions of future changes in Greenland’s ice and its effect on the planet.
Josephine Yolanda Lindsey-Clark, Aslak Grinsted, Baptiste Vandecrux, and Christine Schøtt Hvidberg
EGUsphere, https://doi.org/10.5194/egusphere-2025-2516, https://doi.org/10.5194/egusphere-2025-2516, 2025
This preprint is open for discussion and under review for The Cryosphere (TC).
Short summary
Short summary
We present a new method to improve estimates of snowfall across Greenland, a crucial factor in predicting sea-level rise. Current climate models often misrepresent snowfall patterns, resulting in significant long-term errors. By using two million observations, our method corrects model errors and produces more accurate snowfall maps. The improved maps can help to reduce uncertainty in sea-level rise projections and enhance understanding of Greenland’s proximity to critical melting thresholds.
Shfaqat A. Khan, Helene Seroussi, Mathieu Morlighem, William Colgan, Veit Helm, Gong Cheng, Danjal Berg, Valentina R. Barletta, Nicolaj K. Larsen, William Kochtitzky, Michiel van den Broeke, Kurt H. Kjær, Andy Aschwanden, Brice Noël, Jason E. Box, Joseph A. MacGregor, Robert S. Fausto, Kenneth D. Mankoff, Ian M. Howat, Kuba Oniszk, Dominik Fahrner, Anja Løkkegaard, Eigil Y. H. Lippert, Alicia Bråtner, and Javed Hassan
Earth Syst. Sci. Data, 17, 3047–3071, https://doi.org/10.5194/essd-17-3047-2025, https://doi.org/10.5194/essd-17-3047-2025, 2025
Short summary
Short summary
The surface elevation of the Greenland Ice Sheet is changing due to surface mass balance processes and ice dynamics, each exhibiting distinct spatiotemporal patterns. Here, we employ satellite and airborne altimetry data with fine spatial (1 km) and temporal (monthly) resolutions to document this spatiotemporal evolution from 2003 to 2023. This dataset of fine-resolution altimetry data in both space and time will support studies of ice mass loss and be useful for GIS ice sheet modeling.
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
Short summary
Short summary
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).
Short summary
Short summary
This study demonstrates that incorporating both temperature and temporal variability in water level in emission models significantly influences CO2 emission from peat soil. Especially the co-occurrence of elevated air temperature and low groundwater table significantly influence CO2 emissions under scenarios of rewetting and climate change.
Michael MacFerrin, Christopher Amante, Kelly Carignan, Matthew Love, and Elliot Lim
Earth Syst. Sci. Data, 17, 1835–1849, https://doi.org/10.5194/essd-17-1835-2025, https://doi.org/10.5194/essd-17-1835-2025, 2025
Short summary
Short summary
Here we present Earth TOPOgraphy (ETOPO) 2022, the latest iteration of NOAA's global seamless topographic–bathymetric dataset. ETOPO 2022 is a significant upgrade regarding resolution and accuracy from previous ETOPO releases and is freely available in multiple data formats and resolutions for all uses (public or private), excepting navigation.
Gavin A. Schmidt, Kenneth D. Mankoff, Jonathan L. Bamber, Dustin Carroll, David M. Chandler, Violaine Coulon, Benjamin J. Davison, Matthew H. England, Paul R. Holland, Nicolas C. Jourdain, Qian Li, Juliana M. Marson, Pierre Mathiot, Clive R. McMahon, Twila A. Moon, Ruth Mottram, Sophie Nowicki, Anne Olivé Abelló, Andrew G. Pauling, Thomas Rackow, and Damien Ringeisen
EGUsphere, https://doi.org/10.5194/egusphere-2025-1940, https://doi.org/10.5194/egusphere-2025-1940, 2025
Short summary
Short summary
The impact of increasing mass loss from the Greenland and Antarctic ice sheets has not so far been included in historical climate model simulations. This paper describes the protocols and data available for modeling groups to add this anomalous freshwater to their ocean modules to better represent the impacts of these fluxes on ocean circulation, sea ice, salinity and sea level.
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
Revised manuscript accepted for ESSD
Short summary
Short summary
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.
Tim van den Akker, Ward van Pelt, Rickard Petterson, and Veijo A. Pohjola
The Cryosphere, 19, 1513–1525, https://doi.org/10.5194/tc-19-1513-2025, https://doi.org/10.5194/tc-19-1513-2025, 2025
Short summary
Short summary
Liquid water can persist within old snow on glaciers and ice caps if it can percolate into the snow before it refreezes. Snow is a good insulator, and it is porous where the percolated water can be stored. If this happens, the water piles up and forms a groundwater-like system. Here, we show observations of such a groundwater-like system found in Svalbard. We demonstrate that it behaves like a groundwater system and use that to model the development of the water table from 1957 until the present day.
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
Short summary
Short summary
An ice sheet's surface modulates its response to climate change, and it is therefore critical to monitor how it evolves through time. Here, we investigate novel measurements of Greenland surface roughness based on the strength of reflected local airborne and pan-Greenland satellite radar signals. These measurements respond to roughness at scales typically larger than those considered in mass balance modelling while highlighting the scale dependency of surface roughness that is often overlooked.
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
Short summary
Short summary
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
Short summary
Short summary
We compare surface meltwater features from optical satellite imagery in the Russell–Leverett glacier catchment during high (2019) and low (2018) melt years. In the high melt year, features appear at higher elevations, meltwater systems are more connected, small lakes are more frequent, and slush is more widespread. These findings provide insights into how a warming climate, where high melt years become common, could alter meltwater distribution and dynamics on the Greenland Ice Sheet.
Penelope How, Dorthe Petersen, Kristian Kjellerup Kjeldsen, Katrine Raundrup, Nanna Bjørnholt Karlsson, Alexandra Messerli, Anja Rutishauser, Jonathan Lee Carrivick, James M. Lea, Robert Schjøtt Fausto, Andreas Peter Ahlstrøm, and Signe Bech Andersen
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-18, https://doi.org/10.5194/essd-2025-18, 2025
Revised manuscript under review for ESSD
Short summary
Short summary
Ice-marginal lakes around Greenland temporarily store glacial meltwater, affecting sea level rise, glacier dynamics and ecosystems. Our study presents an eight-year inventory (2016–2023) of 2918 lakes, mapping their size, abundance, and surface water temperature. This openly available dataset supports future research on sea level projections, lake-driven glacier melting, and sustainable resource planning, including hydropower development under Greenland's climate commitments.
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
Short summary
Short summary
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.
Ingalise Kindstedt, Dominic Winski, C. Max Stevens, Emma Skelton, Luke Copland, Karl Kreutz, Mikaila Mannello, Renée Clavette, Jacob Holmes, Mary Albert, and Scott N. Williamson
EGUsphere, https://doi.org/10.5194/egusphere-2024-3807, https://doi.org/10.5194/egusphere-2024-3807, 2025
Short summary
Short summary
Atmospheric warming over mountain glaciers is leading to increased warming and melting of snow as it compresses into glacier ice. This affects both regional hydrology and climate records contained in the ice. Here we use field observations and modeling to show that surface melting and percolation at Eclipse Icefield (Yukon, Canada) is increasing with an increase in extreme melt events, and that compressing snow at Eclipse is likely to continue warming even if air temperatures remain stable.
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
Short summary
Short summary
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.
Ward van Pelt and Thomas Frank
The Cryosphere, 19, 1–17, https://doi.org/10.5194/tc-19-1-2025, https://doi.org/10.5194/tc-19-1-2025, 2025
Short summary
Short summary
Accurate information on the ice thickness of Svalbard's glaciers is important for assessing the contribution to sea level rise in a present and a future climate. However, direct observations of the glacier bed are scarce. Here, we use an inverse approach and high-resolution surface observations to infer basal conditions. We present and analyse the new bed and thickness maps, quantify the ice volume (6800 km3), and compare these against radar data and previous studies.
Ryan Hossaini, David Sherry, Zihao Wang, Martyn P. Chipperfield, Wuhu Feng, David E. Oram, Karina E. Adcock, Stephen A. Montzka, Isobel J. Simpson, Andrea Mazzeo, Amber A. Leeson, Elliot Atlas, and Charles C.-K. Chou
Atmos. Chem. Phys., 24, 13457–13475, https://doi.org/10.5194/acp-24-13457-2024, https://doi.org/10.5194/acp-24-13457-2024, 2024
Short summary
Short summary
DCE (1,2-dichloroethane) is an industrial chemical used to produce PVC (polyvinyl chloride). We analysed DCE production data to estimate global DCE emissions (2002–2020). The emissions were included in an atmospheric model and evaluated by comparing simulated DCE to DCE measurements in the troposphere. We show that DCE contributes ozone-depleting Cl to the stratosphere and that this has increased with increasing DCE emissions. DCE’s impact on stratospheric O3 is currently small but non-zero.
Mai Winstrup, Heidi Ranndal, Signe Hillerup Larsen, Sebastian B. Simonsen, Kenneth D. Mankoff, Robert S. Fausto, and Louise Sandberg Sørensen
Earth Syst. Sci. Data, 16, 5405–5428, https://doi.org/10.5194/essd-16-5405-2024, https://doi.org/10.5194/essd-16-5405-2024, 2024
Short summary
Short summary
Surface topography across the marginal zone of the Greenland Ice Sheet is constantly evolving. Here we present an annual series (2019–2022) of summer digital elevation models (PRODEMs) for the Greenland Ice Sheet margin, covering all outlet glaciers from the ice sheet. The PRODEMs are based on fusion of CryoSat-2 radar altimetry and ICESat-2 laser altimetry. With their high spatial and temporal resolution, the PRODEMs will enable detailed studies of the changes in marginal ice sheet elevations.
Alamgir Hossan, Andreas Colliander, Baptiste Vandecrux, Nicole-Jeanne Schlegel, Joel Harper, Shawn Marshall, and Julie Z. Miller
EGUsphere, https://doi.org/10.5194/egusphere-2024-2563, https://doi.org/10.5194/egusphere-2024-2563, 2024
Short summary
Short summary
We used L-band observations from the SMAP mission to quantify the surface and subsurface liquid water amounts (LWA) in the percolation zone of the Greenland ice sheet. The algorithm is described, and the validation results are provided. The results demonstrate the potential for creating an LWA data product across GrIS, which will advance our understanding of ice sheet physical processes for better projection of Greenland’s contribution to global sea level rise.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
Due to increasing air temperatures, surface melt expands to higher elevations on the Greenland ice sheet. This is visible on satellite imagery in the form of rivers of meltwater running across the surface of the ice sheet. We compare model results of meltwater at high elevations on the ice sheet to satellite observations. We find that each of the models shows strengths and weaknesses. A detailed look into the model results reveals potential reasons for the differences between models.
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
Short summary
Short summary
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
Short summary
Short summary
The Greenland Ecosystem Monitoring programme has been running since 1995. In 2008, the Glaciological monitoring sub-program GlacioBasis was initiated at the Zackenberg site in northeast Greenland, with a transect of three weather stations on the A. P. Olsen Ice Cap. In 2022, the weather stations were replaced with a more standardized set up. Here, we provide the reprocessed and quality-checked data from 2008 to 2022, i.e., the first 15 years of continued monitoring.
Marissa E. Dattler, Brooke Medley, and C. Max Stevens
The Cryosphere, 18, 3613–3631, https://doi.org/10.5194/tc-18-3613-2024, https://doi.org/10.5194/tc-18-3613-2024, 2024
Short summary
Short summary
We developed an algorithm based on combining models and satellite observations to identify the presence of surface melt on the Antarctic Ice Sheet. We find that this method works similarly to previous methods by assessing 13 sites and the Larsen C ice shelf. Unlike previous methods, this algorithm is based on physical parameters, and updates to this method could allow the meltwater present on the Antarctic Ice Sheet to be quantified instead of simply detected.
Jeremy Carter, Erick A. Chacón-Montalván, and Amber Leeson
Geosci. Model Dev., 17, 5733–5757, https://doi.org/10.5194/gmd-17-5733-2024, https://doi.org/10.5194/gmd-17-5733-2024, 2024
Short summary
Short summary
Climate models are essential tools in the study of climate change and its wide-ranging impacts on life on Earth. However, the output is often afflicted with some bias. In this paper, a novel model is developed to predict and correct bias in the output of climate models. The model captures uncertainty in the correction and explicitly models underlying spatial correlation between points. These features are of key importance for climate change impact assessments and resulting decision-making.
Annie L. Putman, Patrick C. Longley, Morgan C. McDonnell, James Reddy, Michelle Katoski, Olivia L. Miller, and J. Renée Brooks
Hydrol. Earth Syst. Sci., 28, 2895–2918, https://doi.org/10.5194/hess-28-2895-2024, https://doi.org/10.5194/hess-28-2895-2024, 2024
Short summary
Short summary
Accuracy of streamflow estimates where water management and use are prevalent, such as the western US, reflect hydrologic modeling decisions. To evaluate process inclusion decisions, we equipped a hydrologic model with tracers and compared estimates to observations. The tracer-equipped model performed well, and differences between the model and observations suggest that the inclusion of water from irrigation may improve model performance in this region.
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
Short summary
Short summary
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.
Anja Rutishauser, Kirk M. Scanlan, Baptiste Vandecrux, Nanna B. Karlsson, Nicolas Jullien, Andreas P. Ahlstrøm, Robert S. Fausto, and Penelope How
The Cryosphere, 18, 2455–2472, https://doi.org/10.5194/tc-18-2455-2024, https://doi.org/10.5194/tc-18-2455-2024, 2024
Short summary
Short summary
The Greenland Ice Sheet interior is covered by a layer of firn, which is important for surface meltwater runoff and contributions to global sea-level rise. Here, we combine airborne radar sounding and laser altimetry measurements to delineate vertically homogeneous and heterogeneous firn. Our results reveal changes in firn between 2011–2019, aligning well with known climatic events. This approach can be used to outline firn areas primed for significantly changing future meltwater runoff.
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
Short summary
Short summary
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
Short summary
Short summary
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.
Horst Machguth, Anja Eichler, Margit Schwikowski, Sabina Brütsch, Enrico Mattea, Stanislav Kutuzov, Martin Heule, Ryskul Usubaliev, Sultan Belekov, Vladimir N. Mikhalenko, Martin Hoelzle, and Marlene Kronenberg
The Cryosphere, 18, 1633–1646, https://doi.org/10.5194/tc-18-1633-2024, https://doi.org/10.5194/tc-18-1633-2024, 2024
Short summary
Short summary
In 2018 we drilled an 18 m ice core on the summit of Grigoriev ice cap, located in the Tien Shan mountains of Kyrgyzstan. The core analysis reveals strong melting since the early 2000s. Regardless of this, we find that the structure and temperature of the ice have changed little since the 1980s. The probable cause of this apparent stability is (i) an increase in snowfall and (ii) the fact that meltwater nowadays leaves the glacier and thereby removes so-called latent heat.
Baptiste Vandecrux, Robert S. Fausto, Jason E. Box, Federico Covi, Regine Hock, Åsa K. Rennermalm, Achim Heilig, Jakob Abermann, Dirk van As, Elisa Bjerre, Xavier Fettweis, Paul C. J. P. Smeets, Peter Kuipers Munneke, Michiel R. van den Broeke, Max Brils, Peter L. Langen, Ruth Mottram, and Andreas P. Ahlstrøm
The Cryosphere, 18, 609–631, https://doi.org/10.5194/tc-18-609-2024, https://doi.org/10.5194/tc-18-609-2024, 2024
Short summary
Short summary
How fast is the Greenland ice sheet warming? In this study, we compiled 4500+ temperature measurements at 10 m below the ice sheet surface (T10m) from 1912 to 2022. We trained a machine learning model on these data and reconstructed T10m for the ice sheet during 1950–2022. After a slight cooling during 1950–1985, the ice sheet warmed at a rate of 0.7 °C per decade until 2022. Climate models showed mixed results compared to our observations and underestimated the warming in key regions.
Laura Melling, Amber Leeson, Malcolm McMillan, Jennifer Maddalena, Jade Bowling, Emily Glen, Louise Sandberg Sørensen, Mai Winstrup, and Rasmus Lørup Arildsen
The Cryosphere, 18, 543–558, https://doi.org/10.5194/tc-18-543-2024, https://doi.org/10.5194/tc-18-543-2024, 2024
Short summary
Short summary
Lakes on glaciers hold large volumes of water which can drain through the ice, influencing estimates of sea level rise. To estimate water volume, we must calculate lake depth. We assessed the accuracy of three satellite-based depth detection methods on a study area in western Greenland and considered the implications for quantifying the volume of water within lakes. We found that the most popular method of detecting depth on the ice sheet scale has higher uncertainty than previously assumed.
Louise Sandberg Sørensen, Rasmus Bahbah, Sebastian B. Simonsen, Natalia Havelund Andersen, Jade Bowling, Noel Gourmelen, Alex Horton, Nanna B. Karlsson, Amber Leeson, Jennifer Maddalena, Malcolm McMillan, Anne Solgaard, and Birgit Wessel
The Cryosphere, 18, 505–523, https://doi.org/10.5194/tc-18-505-2024, https://doi.org/10.5194/tc-18-505-2024, 2024
Short summary
Short summary
Under the right topographic and hydrological conditions, lakes may form beneath the large ice sheets. Some of these subglacial lakes are active, meaning that they periodically drain and refill. When a subglacial lake drains rapidly, it may cause the ice surface above to collapse, and here we investigate how to improve the monitoring of active subglacial lakes in Greenland by monitoring how their associated collapse basins change over time.
Hélène Seroussi, Vincent Verjans, Sophie Nowicki, Antony J. Payne, Heiko Goelzer, William H. Lipscomb, Ayako Abe-Ouchi, Cécile Agosta, Torsten Albrecht, Xylar Asay-Davis, Alice Barthel, Reinhard Calov, Richard Cullather, Christophe Dumas, Benjamin K. Galton-Fenzi, Rupert Gladstone, Nicholas R. Golledge, Jonathan M. Gregory, Ralf Greve, Tore Hattermann, Matthew J. Hoffman, Angelika Humbert, Philippe Huybrechts, Nicolas C. Jourdain, Thomas Kleiner, Eric Larour, Gunter R. Leguy, Daniel P. Lowry, Chistopher M. Little, Mathieu Morlighem, Frank Pattyn, Tyler Pelle, Stephen F. Price, Aurélien Quiquet, Ronja Reese, Nicole-Jeanne Schlegel, Andrew Shepherd, Erika Simon, Robin S. Smith, Fiammetta Straneo, Sainan Sun, Luke D. Trusel, Jonas Van Breedam, Peter Van Katwyk, Roderik S. W. van de Wal, Ricarda Winkelmann, Chen Zhao, Tong Zhang, and Thomas Zwinger
The Cryosphere, 17, 5197–5217, https://doi.org/10.5194/tc-17-5197-2023, https://doi.org/10.5194/tc-17-5197-2023, 2023
Short summary
Short summary
Mass loss from Antarctica is a key contributor to sea level rise over the 21st century, and the associated uncertainty dominates sea level projections. We highlight here the Antarctic glaciers showing the largest changes and quantify the main sources of uncertainty in their future evolution using an ensemble of ice flow models. We show that on top of Pine Island and Thwaites glaciers, Totten and Moscow University glaciers show rapid changes and a strong sensitivity to warmer ocean conditions.
Baptiste Vandecrux, Jason E. Box, Andreas P. Ahlstrøm, Signe B. Andersen, Nicolas Bayou, William T. Colgan, Nicolas J. Cullen, Robert S. Fausto, Dominik Haas-Artho, Achim Heilig, Derek A. Houtz, Penelope How, Ionut Iosifescu Enescu, Nanna B. Karlsson, Rebecca Kurup Buchholz, Kenneth D. Mankoff, Daniel McGrath, Noah P. Molotch, Bianca Perren, Maiken K. Revheim, Anja Rutishauser, Kevin Sampson, Martin Schneebeli, Sandy Starkweather, Simon Steffen, Jeff Weber, Patrick J. Wright, Henry Jay Zwally, and Konrad Steffen
Earth Syst. Sci. Data, 15, 5467–5489, https://doi.org/10.5194/essd-15-5467-2023, https://doi.org/10.5194/essd-15-5467-2023, 2023
Short summary
Short summary
The Greenland Climate Network (GC-Net) comprises stations that have been monitoring the weather on the Greenland Ice Sheet for over 30 years. These stations are being replaced by newer ones maintained by the Geological Survey of Denmark and Greenland (GEUS). The historical data were reprocessed to improve their quality, and key information about the weather stations has been compiled. This augmented dataset is available at https://doi.org/10.22008/FK2/VVXGUT (Steffen et al., 2022).
Motoshi Nishimura, Teruo Aoki, Masashi Niwano, Sumito Matoba, Tomonori Tanikawa, Tetsuhide Yamasaki, Satoru Yamaguchi, and Koji Fujita
Earth Syst. Sci. Data, 15, 5207–5226, https://doi.org/10.5194/essd-15-5207-2023, https://doi.org/10.5194/essd-15-5207-2023, 2023
Short summary
Short summary
We presented the method of data quality checks and the dataset for two ground weather observations in northwest Greenland. We found that the warm and clear weather conditions in the 2015, 2019, and 2020 summers caused the snowmelt and the decline in surface reflectance of solar radiation at a low-elevated site (SIGMA-B; 944 m), but those were not seen at the high-elevated site (SIGMA-A; 1490 m). We hope that our data management method and findings will help climate scientists.
Prateek Gantayat, Alison F. Banwell, Amber A. Leeson, James M. Lea, Dorthe Petersen, Noel Gourmelen, and Xavier Fettweis
Geosci. Model Dev., 16, 5803–5823, https://doi.org/10.5194/gmd-16-5803-2023, https://doi.org/10.5194/gmd-16-5803-2023, 2023
Short summary
Short summary
We developed a new supraglacial hydrology model for the Greenland Ice Sheet. This model simulates surface meltwater routing, meltwater drainage, supraglacial lake (SGL) overflow, and formation of lake ice. The model was able to reproduce 80 % of observed lake locations and provides a good match between the observed and modelled temporal evolution of SGLs.
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
Preprint archived
Short summary
Short summary
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.
Thomas Frank, Ward J. J. van Pelt, and Jack Kohler
The Cryosphere, 17, 4021–4045, https://doi.org/10.5194/tc-17-4021-2023, https://doi.org/10.5194/tc-17-4021-2023, 2023
Short summary
Short summary
Since the ice thickness of most glaciers worldwide is unknown, and since it is not feasible to visit every glacier and observe their thickness directly, inverse modelling techniques are needed that can calculate ice thickness from abundant surface observations. Here, we present a new method for doing that. Our methodology relies on modelling the rate of surface elevation change for a given glacier, compare this with observations of the same quantity and change the bed until the two are in line.
Anja Løkkegaard, Kenneth D. Mankoff, Christian Zdanowicz, Gary D. Clow, Martin P. Lüthi, Samuel H. Doyle, Henrik H. Thomsen, David Fisher, Joel Harper, Andy Aschwanden, Bo M. Vinther, Dorthe Dahl-Jensen, Harry Zekollari, Toby Meierbachtol, Ian McDowell, Neil Humphrey, Anne Solgaard, Nanna B. Karlsson, Shfaqat A. Khan, Benjamin Hills, Robert Law, Bryn Hubbard, Poul Christoffersen, Mylène Jacquemart, Julien Seguinot, Robert S. Fausto, and William T. Colgan
The Cryosphere, 17, 3829–3845, https://doi.org/10.5194/tc-17-3829-2023, https://doi.org/10.5194/tc-17-3829-2023, 2023
Short summary
Short summary
This study presents a database compiling 95 ice temperature profiles from the Greenland ice sheet and peripheral ice caps. Ice viscosity and hence ice flow are highly sensitive to ice temperature. To highlight the value of the database in evaluating ice flow simulations, profiles from the Greenland ice sheet are compared to a modeled temperature field. Reoccurring discrepancies between modeled and observed temperatures provide insight on the difficulties faced when simulating ice temperatures.
Yukihiko Onuma, Koji Fujita, Nozomu Takeuchi, Masashi Niwano, and Teruo Aoki
The Cryosphere, 17, 3309–3328, https://doi.org/10.5194/tc-17-3309-2023, https://doi.org/10.5194/tc-17-3309-2023, 2023
Short summary
Short summary
We established a novel model that simulates the temporal changes in cryoconite hole (CH) depth using heat budgets calculated independently at the ice surface and CH bottom based on hole shape geometry. The simulations suggest that CH depth is governed by the balance between the intensity of the diffuse component of downward shortwave radiation and the wind speed. The meteorological conditions may be important factors contributing to the recent ice surface darkening via the redistribution of CHs.
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
Short summary
Short summary
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.
Megan Thompson-Munson, Nander Wever, C. Max Stevens, Jan T. M. Lenaerts, and Brooke Medley
The Cryosphere, 17, 2185–2209, https://doi.org/10.5194/tc-17-2185-2023, https://doi.org/10.5194/tc-17-2185-2023, 2023
Short summary
Short summary
To better understand the Greenland Ice Sheet’s firn layer and its ability to buffer sea level rise by storing meltwater, we analyze firn density observations and output from two firn models. We find that both models, one physics-based and one semi-empirical, simulate realistic density and firn air content when compared to observations. The models differ in their representation of firn air content, highlighting the uncertainty in physical processes and the paucity of deep-firn measurements.
Inès N. Otosaka, Andrew Shepherd, Erik R. Ivins, Nicole-Jeanne Schlegel, Charles Amory, Michiel R. van den Broeke, Martin Horwath, Ian Joughin, Michalea D. King, Gerhard Krinner, Sophie Nowicki, Anthony J. Payne, Eric Rignot, Ted Scambos, Karen M. Simon, Benjamin E. Smith, Louise S. Sørensen, Isabella Velicogna, Pippa L. Whitehouse, Geruo A, Cécile Agosta, Andreas P. Ahlstrøm, Alejandro Blazquez, William Colgan, Marcus E. Engdahl, Xavier Fettweis, Rene Forsberg, Hubert Gallée, Alex Gardner, Lin Gilbert, Noel Gourmelen, Andreas Groh, Brian C. Gunter, Christopher Harig, Veit Helm, Shfaqat Abbas Khan, Christoph Kittel, Hannes Konrad, Peter L. Langen, Benoit S. Lecavalier, Chia-Chun Liang, Bryant D. Loomis, Malcolm McMillan, Daniele Melini, Sebastian H. Mernild, Ruth Mottram, Jeremie Mouginot, Johan Nilsson, Brice Noël, Mark E. Pattle, William R. Peltier, Nadege Pie, Mònica Roca, Ingo Sasgen, Himanshu V. Save, Ki-Weon Seo, Bernd Scheuchl, Ernst J. O. Schrama, Ludwig Schröder, Sebastian B. Simonsen, Thomas Slater, Giorgio Spada, Tyler C. Sutterley, Bramha Dutt Vishwakarma, Jan Melchior van Wessem, David Wiese, Wouter van der Wal, and Bert Wouters
Earth Syst. Sci. Data, 15, 1597–1616, https://doi.org/10.5194/essd-15-1597-2023, https://doi.org/10.5194/essd-15-1597-2023, 2023
Short summary
Short summary
By measuring changes in the volume, gravitational attraction, and ice flow of Greenland and Antarctica from space, we can monitor their mass gain and loss over time. Here, we present a new record of the Earth’s polar ice sheet mass balance produced by aggregating 50 satellite-based estimates of ice sheet mass change. This new assessment shows that the ice sheets have lost (7.5 x 1012) t of ice between 1992 and 2020, contributing 21 mm to sea level rise.
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
Short summary
Short summary
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.
Ikumi Oyabu, Kenji Kawamura, Shuji Fujita, Ryo Inoue, Hideaki Motoyama, Kotaro Fukui, Motohiro Hirabayashi, Yu Hoshina, Naoyuki Kurita, Fumio Nakazawa, Hiroshi Ohno, Konosuke Sugiura, Toshitaka Suzuki, Shun Tsutaki, Ayako Abe-Ouchi, Masashi Niwano, Frédéric Parrenin, Fuyuki Saito, and Masakazu Yoshimori
Clim. Past, 19, 293–321, https://doi.org/10.5194/cp-19-293-2023, https://doi.org/10.5194/cp-19-293-2023, 2023
Short summary
Short summary
We reconstructed accumulation rate around Dome Fuji, Antarctica, over the last 5000 years from 15 shallow ice cores and seven snow pits. We found a long-term decreasing trend in the preindustrial period, which may be associated with secular surface cooling and sea ice expansion. Centennial-scale variations were also found, which may partly be related to combinations of volcanic, solar and greenhouse gas forcings. The most rapid and intense increases of accumulation rate occurred since 1850 CE.
Marlene Kronenberg, Ward van Pelt, Horst Machguth, Joel Fiddes, Martin Hoelzle, and Felix Pertziger
The Cryosphere, 16, 5001–5022, https://doi.org/10.5194/tc-16-5001-2022, https://doi.org/10.5194/tc-16-5001-2022, 2022
Short summary
Short summary
The Pamir Alay is located at the edge of regions with anomalous glacier mass changes. Unique long-term in situ data are available for Abramov Glacier, located in the Pamir Alay. In this study, we use this extraordinary data set in combination with reanalysis data and a coupled surface energy balance–multilayer subsurface model to compute and analyse the distributed climatic mass balance and firn evolution from 1968 to 2020.
Vincent Verjans, Alexander A. Robel, Helene Seroussi, Lizz Ultee, and Andrew F. Thompson
Geosci. Model Dev., 15, 8269–8293, https://doi.org/10.5194/gmd-15-8269-2022, https://doi.org/10.5194/gmd-15-8269-2022, 2022
Short summary
Short summary
We describe the development of the first large-scale ice sheet model that accounts for stochasticity in a range of processes. Stochasticity allows the impacts of inherently uncertain processes on ice sheets to be represented. This includes climatic uncertainty, as the climate is inherently chaotic. Furthermore, stochastic capabilities also encompass poorly constrained glaciological processes that display strong variability at fine spatiotemporal scales. We present the model and test experiments.
Nicole Clerx, Horst Machguth, Andrew Tedstone, Nicolas Jullien, Nander Wever, Rolf Weingartner, and Ole Roessler
The Cryosphere, 16, 4379–4401, https://doi.org/10.5194/tc-16-4379-2022, https://doi.org/10.5194/tc-16-4379-2022, 2022
Short summary
Short summary
Meltwater runoff is one of the main contributors to mass loss on the Greenland Ice Sheet that influences global sea level rise. However, it remains unclear where meltwater runs off and what processes cause this. We measured the velocity of meltwater flow through snow on the ice sheet, which ranged from 0.17–12.8 m h−1 for vertical percolation and from 1.3–15.1 m h−1 for lateral flow. This is an important step towards understanding where, when and why meltwater runoff occurs on the ice sheet.
Brooke Medley, Thomas A. Neumann, H. Jay Zwally, Benjamin E. Smith, and C. Max Stevens
The Cryosphere, 16, 3971–4011, https://doi.org/10.5194/tc-16-3971-2022, https://doi.org/10.5194/tc-16-3971-2022, 2022
Short summary
Short summary
Satellite altimeters measure the height or volume change over Earth's ice sheets, but in order to understand how that change translates into ice mass, we must account for various processes at the surface. Specifically, snowfall events generate large, transient increases in surface height, yet snow fall has a relatively low density, which means much of that height change is composed of air. This air signal must be removed from the observed height changes before we can assess ice mass change.
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
Short summary
Short summary
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.
Jeremy Carter, Amber Leeson, Andrew Orr, Christoph Kittel, and J. Melchior van Wessem
The Cryosphere, 16, 3815–3841, https://doi.org/10.5194/tc-16-3815-2022, https://doi.org/10.5194/tc-16-3815-2022, 2022
Short summary
Short summary
Climate models provide valuable information for studying processes such as the collapse of ice shelves over Antarctica which impact estimates of sea level rise. This paper examines variability across climate simulations over Antarctica for fields including snowfall, temperature and melt. Significant systematic differences between outputs are found, occurring at both large and fine spatial scales across Antarctica. Results are important for future impact assessments and model development.
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
Short summary
Short summary
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.
Ioanna Karagali, Magnus Barfod Suhr, Ruth Mottram, Pia Nielsen-Englyst, Gorm Dybkjær, Darren Ghent, and Jacob L. Høyer
The Cryosphere, 16, 3703–3721, https://doi.org/10.5194/tc-16-3703-2022, https://doi.org/10.5194/tc-16-3703-2022, 2022
Short summary
Short summary
Ice surface temperature (IST) products were used to develop the first multi-sensor, gap-free Level 4 (L4) IST product of the Greenland Ice Sheet (GIS) for 2012, when a significant melt event occurred. For the melt season, mean IST was −15 to −1 °C, and almost the entire GIS experienced at least 1 to 5 melt days. Inclusion of the L4 IST to a surface mass budget (SMB) model improved simulated surface temperatures during the key onset of the melt season, where biases are typically large.
William Colgan, Agnes Wansing, Kenneth Mankoff, Mareen Lösing, John Hopper, Keith Louden, Jörg Ebbing, Flemming G. Christiansen, Thomas Ingeman-Nielsen, Lillemor Claesson Liljedahl, Joseph A. MacGregor, Árni Hjartarson, Stefan Bernstein, Nanna B. Karlsson, Sven Fuchs, Juha Hartikainen, Johan Liakka, Robert S. Fausto, Dorthe Dahl-Jensen, Anders Bjørk, Jens-Ove Naslund, Finn Mørk, Yasmina Martos, Niels Balling, Thomas Funck, Kristian K. Kjeldsen, Dorthe Petersen, Ulrik Gregersen, Gregers Dam, Tove Nielsen, Shfaqat A. Khan, and Anja Løkkegaard
Earth Syst. Sci. Data, 14, 2209–2238, https://doi.org/10.5194/essd-14-2209-2022, https://doi.org/10.5194/essd-14-2209-2022, 2022
Short summary
Short summary
We assemble all available geothermal heat flow measurements collected in and around Greenland into a new database. We use this database of point measurements, in combination with other geophysical datasets, to model geothermal heat flow in and around Greenland. Our geothermal heat flow model is generally cooler than previous models of Greenland, especially in southern Greenland. It does not suggest any high geothermal heat flows resulting from Icelandic plume activity over 50 million years ago.
Daniel Clarkson, Emma Eastoe, and Amber Leeson
The Cryosphere, 16, 1597–1607, https://doi.org/10.5194/tc-16-1597-2022, https://doi.org/10.5194/tc-16-1597-2022, 2022
Short summary
Short summary
The Greenland ice sheet has seen large amounts of melt in recent years, and accurately modelling temperatures is vital to understand how much of the ice sheet is melting. We estimate the probability of melt from ice surface temperature data to identify which areas of the ice sheet have experienced melt and estimate temperature quantiles. Our results suggest that for large areas of the ice sheet, melt has become more likely over the past 2 decades and high temperatures are also becoming warmer.
Michael J. MacFerrin, C. Max Stevens, Baptiste Vandecrux, Edwin D. Waddington, and Waleed Abdalati
Earth Syst. Sci. Data, 14, 955–971, https://doi.org/10.5194/essd-14-955-2022, https://doi.org/10.5194/essd-14-955-2022, 2022
Short summary
Short summary
The vast majority of the Greenland ice sheet's surface is covered by pluriannual snow, also called firn, that accumulates year after year and is compressed into glacial ice. The thickness of the firn layer changes through time and responds to the surface climate. We present continuous measurement of the firn compaction at various depths for eight sites. The dataset will help to evaluate firn models, interpret ice cores, and convert remotely sensed ice sheet surface height change to mass loss.
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
Short summary
Short summary
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
Short summary
Short summary
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.
Diarmuid Corr, Amber Leeson, Malcolm McMillan, Ce Zhang, and Thomas Barnes
Earth Syst. Sci. Data, 14, 209–228, https://doi.org/10.5194/essd-14-209-2022, https://doi.org/10.5194/essd-14-209-2022, 2022
Short summary
Short summary
We identify 119 km2 of meltwater area over West Antarctica in January 2017. In combination with Stokes et al., 2019, this forms the first continent-wide assessment helping to quantify the mass balance of Antarctica and its contribution to global sea level rise. We apply thresholds for meltwater classification to satellite images, mapping the extent and manually post-processing to remove false positives. Our study provides a high-fidelity dataset to train and validate machine learning methods.
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
Short summary
Short summary
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
Short summary
Short summary
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.
Kenneth D. Mankoff, Xavier Fettweis, Peter L. Langen, Martin Stendel, Kristian K. Kjeldsen, Nanna B. Karlsson, Brice Noël, Michiel R. van den Broeke, Anne Solgaard, William Colgan, Jason E. Box, Sebastian B. Simonsen, Michalea D. King, Andreas P. Ahlstrøm, Signe Bech Andersen, and Robert S. Fausto
Earth Syst. Sci. Data, 13, 5001–5025, https://doi.org/10.5194/essd-13-5001-2021, https://doi.org/10.5194/essd-13-5001-2021, 2021
Short summary
Short summary
We estimate the daily mass balance and its components (surface, marine, and basal mass balance) for the Greenland ice sheet. Our time series begins in 1840 and has annual resolution through 1985 and then daily from 1986 through next week. Results are operational (updated daily) and provided for the entire ice sheet or by commonly used regions or sectors. This is the first input–output mass balance estimate to include the basal mass balance.
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
Short summary
Short summary
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
Short summary
Short summary
We compare the calculated surface mass budget (SMB) of Antarctica in five different regional climate models. On average ~ 2000 Gt of snow accumulates annually, but different models vary by ~ 10 %, a difference equivalent to ± 0.5 mm of global sea level rise. All models reproduce observed weather, but there are large differences in regional patterns of snowfall, especially in areas with very few observations, giving greater uncertainty in Antarctic mass budget than previously identified.
Amy Solomon, Céline Heuzé, Benjamin Rabe, Sheldon Bacon, Laurent Bertino, Patrick Heimbach, Jun Inoue, Doroteaciro Iovino, Ruth Mottram, Xiangdong Zhang, Yevgeny Aksenov, Ronan McAdam, An Nguyen, Roshin P. Raj, and Han Tang
Ocean Sci., 17, 1081–1102, https://doi.org/10.5194/os-17-1081-2021, https://doi.org/10.5194/os-17-1081-2021, 2021
Short summary
Short summary
Freshwater in the Arctic Ocean plays a critical role in the global climate system by impacting ocean circulations, stratification, mixing, and emergent regimes. In this review paper we assess how Arctic Ocean freshwater changed in the 2010s relative to the 2000s. Estimates from observations and reanalyses show a qualitative stabilization in the 2010s due to a compensation between a freshening of the Beaufort Gyre and a reduction in freshwater in the Amerasian and Eurasian basins.
Robert S. Fausto, Dirk van As, Kenneth D. Mankoff, Baptiste Vandecrux, Michele Citterio, Andreas P. Ahlstrøm, Signe B. Andersen, William Colgan, Nanna B. Karlsson, Kristian K. Kjeldsen, Niels J. Korsgaard, Signe H. Larsen, Søren Nielsen, Allan Ø. Pedersen, Christopher L. Shields, Anne M. Solgaard, and Jason E. Box
Earth Syst. Sci. Data, 13, 3819–3845, https://doi.org/10.5194/essd-13-3819-2021, https://doi.org/10.5194/essd-13-3819-2021, 2021
Short summary
Short summary
The Programme for Monitoring of the Greenland Ice Sheet (PROMICE) has been measuring climate and ice sheet properties since 2007. Here, we present our data product from weather and ice sheet measurements from a network of automatic weather stations mainly located in the melt area of the ice sheet. Currently the PROMICE automatic weather station network includes 25 instrumented sites in Greenland.
Thomas James Barnes, Amber Alexandra Leeson, Malcolm McMillan, Vincent Verjans, Jeremy Carter, and Christoph Kittel
The Cryosphere Discuss., https://doi.org/10.5194/tc-2021-214, https://doi.org/10.5194/tc-2021-214, 2021
Revised manuscript not accepted
Short summary
Short summary
We find that the area covered by lakes on George VI ice shelf in 2020 is similar to that seen in other years such as 1989. However, the climate conditions are much more in favour of lakes forming. We find that it is likely that snowfall, and the build up of a surface snow layer limits the development of lakes on the surface of George VI ice shelf in 2020. We also find that in future, snowfall is predicted to decrease, and therefore this limiting effect may be reduced in future.
Anne Solgaard, Anders Kusk, John Peter Merryman Boncori, Jørgen Dall, Kenneth D. Mankoff, Andreas P. Ahlstrøm, Signe B. Andersen, Michele Citterio, Nanna B. Karlsson, Kristian K. Kjeldsen, Niels J. Korsgaard, Signe H. Larsen, and Robert S. Fausto
Earth Syst. Sci. Data, 13, 3491–3512, https://doi.org/10.5194/essd-13-3491-2021, https://doi.org/10.5194/essd-13-3491-2021, 2021
Short summary
Short summary
The PROMICE Ice Velocity product is a time series of Greenland Ice Sheet ice velocity mosaics spanning September 2016 to present. It is derived from Sentinel-1 SAR data and has a spatial resolution of 500 m. Each mosaic spans 24 d (two Sentinel-1 cycles), and a new one is posted every 12 d (every Sentinel-1A cycle). The spatial comprehensiveness and temporal consistency make the product ideal for monitoring and studying ice-sheet-wide ice discharge and dynamics of glaciers.
Enrico Mattea, Horst Machguth, Marlene Kronenberg, Ward van Pelt, Manuela Bassi, and Martin Hoelzle
The Cryosphere, 15, 3181–3205, https://doi.org/10.5194/tc-15-3181-2021, https://doi.org/10.5194/tc-15-3181-2021, 2021
Short summary
Short summary
In our study we find that climate change is affecting the high-alpine Colle Gnifetti glacier (Swiss–Italian Alps) with an increase in melt amounts and ice temperatures.
In the near future this trend could threaten the viability of the oldest ice core record in the Alps.
To reach our conclusions, for the first time we used the meteorological data of the highest permanent weather station in Europe (Capanna Margherita, 4560 m), together with an advanced numeric simulation of the glacier.
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
Short summary
Short summary
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.
Naomi E. Ochwat, Shawn J. Marshall, Brian J. Moorman, Alison S. Criscitiello, and Luke Copland
The Cryosphere, 15, 2021–2040, https://doi.org/10.5194/tc-15-2021-2021, https://doi.org/10.5194/tc-15-2021-2021, 2021
Short summary
Short summary
In May 2018 we drilled into Kaskawulsh Glacier to study how it is being affected by climate warming and used models to investigate the evolution of the firn since the 1960s. We found that the accumulation zone has experienced increased melting that has refrozen as ice layers and has formed a perennial firn aquifer. These results better inform climate-induced changes on northern glaciers and variables to take into account when estimating glacier mass change using remote-sensing methods.
Chris M. DeBeer, Howard S. Wheater, John W. Pomeroy, Alan G. Barr, Jennifer L. Baltzer, Jill F. Johnstone, Merritt R. Turetsky, Ronald E. Stewart, Masaki Hayashi, Garth van der Kamp, Shawn Marshall, Elizabeth Campbell, Philip Marsh, Sean K. Carey, William L. Quinton, Yanping Li, Saman Razavi, Aaron Berg, Jeffrey J. McDonnell, Christopher Spence, Warren D. Helgason, Andrew M. Ireson, T. Andrew Black, Mohamed Elshamy, Fuad Yassin, Bruce Davison, Allan Howard, Julie M. Thériault, Kevin Shook, Michael N. Demuth, and Alain Pietroniro
Hydrol. Earth Syst. Sci., 25, 1849–1882, https://doi.org/10.5194/hess-25-1849-2021, https://doi.org/10.5194/hess-25-1849-2021, 2021
Short summary
Short summary
This article examines future changes in land cover and hydrological cycling across the interior of western Canada under climate conditions projected for the 21st century. Key insights into the mechanisms and interactions of Earth system and hydrological process responses are presented, and this understanding is used together with model application to provide a synthesis of future change. This has allowed more scientifically informed projections than have hitherto been available.
Christian Zdanowicz, Jean-Charles Gallet, Mats P. Björkman, Catherine Larose, Thomas Schuler, Bartłomiej Luks, Krystyna Koziol, Andrea Spolaor, Elena Barbaro, Tõnu Martma, Ward van Pelt, Ulla Wideqvist, and Johan Ström
Atmos. Chem. Phys., 21, 3035–3057, https://doi.org/10.5194/acp-21-3035-2021, https://doi.org/10.5194/acp-21-3035-2021, 2021
Short summary
Short summary
Black carbon (BC) aerosols are soot-like particles which, when transported to the Arctic, darken snow surfaces, thus indirectly affecting climate. Information on BC in Arctic snow is needed to measure their impact and monitor the efficacy of pollution-reduction policies. This paper presents a large new set of BC measurements in snow in Svalbard collected between 2007 and 2018. It describes how BC in snow varies across the archipelago and explores some factors controlling these variations.
Eric Keenan, Nander Wever, Marissa Dattler, Jan T. M. Lenaerts, Brooke Medley, Peter Kuipers Munneke, and Carleen Reijmer
The Cryosphere, 15, 1065–1085, https://doi.org/10.5194/tc-15-1065-2021, https://doi.org/10.5194/tc-15-1065-2021, 2021
Short summary
Short summary
Snow density is required to convert observed changes in ice sheet volume into mass, which ultimately drives ice sheet contribution to sea level rise. However, snow properties respond dynamically to wind-driven redistribution. Here we include a new wind-driven snow density scheme into an existing snow model. Our results demonstrate an improved representation of snow density when compared to observations and can therefore be used to improve retrievals of ice sheet mass balance.
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
Manuscript not accepted for further review
Short summary
Short summary
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
Manuscript not accepted for further review
Short summary
Short summary
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).
Jenny V. Turton, Amélie Kirchgaessner, Andrew N. Ross, John C. King, and Peter Kuipers Munneke
The Cryosphere, 14, 4165–4180, https://doi.org/10.5194/tc-14-4165-2020, https://doi.org/10.5194/tc-14-4165-2020, 2020
Short summary
Short summary
Föhn winds are warm and dry downslope winds in the lee of a mountain range, such as the Antarctic Peninsula. Föhn winds heat the ice of the Larsen C Ice Shelf at the base of the mountains and promote more melting than during non-föhn periods in spring, summer and autumn in both model output and observations. Especially in spring, when they are most frequent, föhn winds can extend the melt season by over a month and cause a similar magnitude of melting to that observed in summer.
Ethan Welty, Michael Zemp, Francisco Navarro, Matthias Huss, Johannes J. Fürst, Isabelle Gärtner-Roer, Johannes Landmann, Horst Machguth, Kathrin Naegeli, Liss M. Andreassen, Daniel Farinotti, Huilin Li, and GlaThiDa Contributors
Earth Syst. Sci. Data, 12, 3039–3055, https://doi.org/10.5194/essd-12-3039-2020, https://doi.org/10.5194/essd-12-3039-2020, 2020
Short summary
Short summary
Knowing the thickness of glacier ice is critical for predicting the rate of glacier loss and the myriad downstream impacts. To facilitate forecasts of future change, we have added 3 million measurements to our worldwide database of glacier thickness: 14 % of global glacier area is now within 1 km of a thickness measurement (up from 6 %). To make it easier to update and monitor the quality of our database, we have used automated tools to check and track changes to the data over time.
Jennifer F. Arthur, Chris R. Stokes, Stewart S. R. Jamieson, J. Rachel Carr, and Amber A. Leeson
The Cryosphere, 14, 4103–4120, https://doi.org/10.5194/tc-14-4103-2020, https://doi.org/10.5194/tc-14-4103-2020, 2020
Short summary
Short summary
Surface meltwater lakes can flex and fracture ice shelves, potentially leading to ice shelf break-up. A long-term record of lake evolution on Shackleton Ice Shelf is produced using optical satellite imagery and compared to surface air temperature and modelled surface melt. The results reveal that lake clustering on the ice shelf is linked to melt-enhancing feedbacks. Peaks in total lake area and volume closely correspond with intense snowmelt events rather than with warmer seasonal temperatures.
Kenneth D. Mankoff, Brice Noël, Xavier Fettweis, Andreas P. Ahlstrøm, William Colgan, Ken Kondo, Kirsty Langley, Shin Sugiyama, Dirk van As, and Robert S. Fausto
Earth Syst. Sci. Data, 12, 2811–2841, https://doi.org/10.5194/essd-12-2811-2020, https://doi.org/10.5194/essd-12-2811-2020, 2020
Short summary
Short summary
This work partitions regional climate model (RCM) runoff from the MAR and RACMO RCMs to hydrologic outlets at the ice margin and coast. Temporal resolution is daily from 1959 through 2019. Spatial grid is ~ 100 m, resolving individual streams. In addition to discharge at outlets, we also provide the streams, outlets, and basin geospatial data, as well as a script to query and access the geospatial or time series discharge data from the data files.
Xavier Fettweis, Stefan Hofer, Uta Krebs-Kanzow, Charles Amory, Teruo Aoki, Constantijn J. Berends, Andreas Born, Jason E. Box, Alison Delhasse, Koji Fujita, Paul Gierz, Heiko Goelzer, Edward Hanna, Akihiro Hashimoto, Philippe Huybrechts, Marie-Luise Kapsch, Michalea D. King, Christoph Kittel, Charlotte Lang, Peter L. Langen, Jan T. M. Lenaerts, Glen E. Liston, Gerrit Lohmann, Sebastian H. Mernild, Uwe Mikolajewicz, Kameswarrao Modali, Ruth H. Mottram, Masashi Niwano, Brice Noël, Jonathan C. Ryan, Amy Smith, Jan Streffing, Marco Tedesco, Willem Jan van de Berg, Michiel van den Broeke, Roderik S. W. van de Wal, Leo van Kampenhout, David Wilton, Bert Wouters, Florian Ziemen, and Tobias Zolles
The Cryosphere, 14, 3935–3958, https://doi.org/10.5194/tc-14-3935-2020, https://doi.org/10.5194/tc-14-3935-2020, 2020
Short summary
Short summary
We evaluated simulated Greenland Ice Sheet surface mass balance from 5 kinds of models. While the most complex (but expensive to compute) models remain the best, the faster/simpler models also compare reliably with observations and have biases of the same order as the regional models. Discrepancies in the trend over 2000–2012, however, suggest that large uncertainties remain in the modelled future SMB changes as they are highly impacted by the meltwater runoff biases over the current climate.
Shawn J. Marshall and Kristina Miller
The Cryosphere, 14, 3249–3267, https://doi.org/10.5194/tc-14-3249-2020, https://doi.org/10.5194/tc-14-3249-2020, 2020
Short summary
Short summary
Surface-albedo measurements from 2002 to 2017 from Haig Glacier in the Canadian Rockies provide no evidence of long-term trends (i.e., the glacier does not appear to be darkening), but there are large variations in albedo over the melt season and from year to year. The glacier ice is exceptionally dark in association with forest fire fallout but is effectively cleansed by meltwater or rainfall. Summer snowfall plays an important role in refreshing the glacier surface and reducing summer melt.
Ankit Pramanik, Jack Kohler, Katrin Lindbäck, Penelope How, Ward Van Pelt, Glen Liston, and Thomas V. Schuler
The Cryosphere Discuss., https://doi.org/10.5194/tc-2020-197, https://doi.org/10.5194/tc-2020-197, 2020
Revised manuscript not accepted
Short summary
Short summary
Freshwater discharge from tidewater glaciers influences fjord circulation and fjord ecosystem. Glacier hydrology plays crucial role in transporting water underneath glacier ice. We investigated hydrology beneath the tidewater glaciers of Kongsfjord basin in Northwest Svalbard and found that subglacial water flow differs substantially from surface flow of glacier ice. Furthermore, we derived freshwater discharge time-series from all the glaciers to the fjord.
C. Max Stevens, Vincent Verjans, Jessica M. D. Lundin, Emma C. Kahle, Annika N. Horlings, Brita I. Horlings, and Edwin D. Waddington
Geosci. Model Dev., 13, 4355–4377, https://doi.org/10.5194/gmd-13-4355-2020, https://doi.org/10.5194/gmd-13-4355-2020, 2020
Short summary
Short summary
Understanding processes in snow (firn), including compaction and airflow, is important for calculating how much mass the ice sheets are losing and for interpreting climate records from ice cores. We have developed the open-source Community Firn Model to simulate these processes. We used it to compare 13 different firn compaction equations and found that they do not agree within 10 %. We also show that including firn compaction in a firn-air model improves the match with data from ice cores.
Vincent Verjans, Amber A. Leeson, Christopher Nemeth, C. Max Stevens, Peter Kuipers Munneke, Brice Noël, and Jan Melchior van Wessem
The Cryosphere, 14, 3017–3032, https://doi.org/10.5194/tc-14-3017-2020, https://doi.org/10.5194/tc-14-3017-2020, 2020
Short summary
Short summary
Ice sheets are covered by a firn layer, which is the transition stage between fresh snow and ice. Accurate modelling of firn density properties is important in many glaciological aspects. Current models show disagreements, are mostly calibrated to match specific observations of firn density and lack thorough uncertainty analysis. We use a novel calibration method for firn models based on a Bayesian statistical framework, which results in improved model accuracy and in uncertainty evaluation.
Cited articles
Ahlstrøm, A. P., Gravesen, P., Andersen, S. B., van As, D., Citterio, M.,
Fausto, R. S., Nielsen, S., Jepsen, H. F., Kristensen, S. S., Christensen,
E. L., Stenseng, L., Forsberg, R., Hanson, S., and Petersen, D.: A new
programme for monitoring the mass loss of the Greenland ice sheet, Geol.
Surv. Denmark Greenl. Bull., 15, 61–64, https://doi.org/10.34194/geusb.v15.5045, 2008.
Albert, M. R. and Shultz, E. F.: Snow and firn properties and air–snow
transport processes at Summit, Greenland, Atmos. Environ.,
36, 2789–2797, https://doi.org/10.1016/S1352-2310(02)00119-X, 2002.
Alexander, P. M., Tedesco, M., Koenig, L., and Fettweis, X.: Evaluating a
Regional Climate Model Simulation of Greenland Ice Sheet Snow and Firn
Density for Improved Surface Mass Balance Estimates, Geophys. Res. Lett.,
46, 12073–12082, https://doi.org/10.1029/2019GL084101, 2019.
Anderson, E. A.: A point energy and mass balance model of a snow cover, NOAA
technical report NWS 19,
available at: https://repository.library.noaa.gov/view/noaa/6392/noaa_6392_ DS1.pdf (last access: 2 November 2020), 1976.
Arthern, R. J., Vaughan, D. G., Rankin, A. M., Mulvaney, R., and Thomas, E.
R.: In situ measurements of Antarctic snow compaction compared with
predictions of models, J. Geophys. Res.-Earth Surf., 115, 1–12,
https://doi.org/10.1029/2009JF001306, 2010.
Bear, J.: Dynamics of fluids in porous media, Dover, New York, 1988.
Benson, C. S.: Stratigraphic studies in the snow and firn of the Greenland
ice sheet, SIPRE Res. Rep., 70, 76–83, https://doi.org/10.21236/ada337542, 1962.
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.
Box, J. E. and Steffen, K.: Sublimation on the Greenland Ice Sheet from
automated weather station observations, J. Geophys. Res., 106, 33965–33981, https://doi.org/10.1029/2001JD900219, 2001.
Box, J. E., Cressie, N., Bromwich, D. H., Jung, J. H., Van Den Broeke, M.,
Van Angelen, J. H., Forster, R. R., Miège, C., Mosley-Thompson, E.,
Vinther, B., and Mcconnell, J. R.: Greenland ice sheet mass balance
reconstruction. Part I: Net snow accumulation (1600–2009), J. Climate, 26,
3919–3934, https://doi.org/10.1175/JCLI-D-12-00373.1, 2013.
Box, J. E., van As, D., Steffen, K., and the PROMICE team: Greenland,
Canadian and Icelandic land-ice albedo grids (2000–2016), Geological Survey
of Denmark and Greenland Bulletin, 38, 53–56, https://doi.org/10.34194/geusb.v38.4414, 2017.
Braithwaite, R. J., Laternser, M., and Pfeffer, W. T.: Variations of
near-surface firn density in the lower accumulation area of the Greenland
ice sheet, Pakitsoq, West Greenland, J. Glaciol., 40, 477–485,
https://doi.org/10.1017/S002214300001234X, 1994.
Calonne, N., Flin, F., Morin, S., Lesaffre, B., Du Roscoat, S. R., and
Geindreau, C.: Numerical and experimental investigations of the effective
thermal conductivity of snow, Geophys. Res. Lett., 38, 1–6,
https://doi.org/10.1029/2011GL049234, 2011.
Calonne, N., Geindreau, C., Flin, F., Morin, S., Lesaffre, B., Rolland du Roscoat, S., and Charrier, P.: 3-D image-based numerical computations of snow permeability: links to specific surface area, density, and microstructural anisotropy, The Cryosphere, 6, 939–951, https://doi.org/10.5194/tc-6-939-2012, 2012.
Calonne, N., Milliancourt, L., Burr, A., Philip, A., Martin, C. L., Flin,
F., and Geindreau, C.:. Thermal conductivity of snow, firn, and porous ice
from 3-D image-based computations. Geophys. Res. Lett., 46, 13079–13089,
https://doi.org/10.1029/2019GL085228, 2019.
Charalampidis, C., van As, D., Box, J. E., van den Broeke, M. R., Colgan, W. T., Doyle, S. H., Hubbard, A. L., MacFerrin, M., Machguth, H., and Smeets, C. J. P. P.: Changing surface–atmosphere energy exchange and refreezing capacity of the lower accumulation area, West Greenland, The Cryosphere, 9, 2163–2181, https://doi.org/10.5194/tc-9-2163-2015, 2015.
Charalampidis, C., Van As, D., Colgan, W., Fausto, R., Macferrin, M., and
Machguth, H.: Thermal tracing of retained meltwater in the lower
accumulation area of the Southwestern Greenland ice sheet, Ann.
Glaciol., 57, 1–10, https://doi.org/10.1017/aog.2016.2, 2016.
Colbeck, S. C.: A theory for water flow through a layered snowpack, Water
Resour. Res., 11, 261–266, https://doi.org/10.1029/WR011i002p00261,
1975.
Coléou, C. and Lesaffre, B.: Irreducible water saturation in snow:
experimental results in a cold laboratory, Ann. Glaciol., 26, 64–68,
https://doi.org/10.3189/1998aog26-1-64-68, 1998.
de la Peña, S., Howat, I. M., Nienow, P. W., van den Broeke, M. R., Mosley-Thompson, E., Price, S. F., Mair, D., Noël, B., and Sole, A. J.: Changes in the firn structure of the western Greenland Ice Sheet caused by recent warming, The Cryosphere, 9, 1203–1211, https://doi.org/10.5194/tc-9-1203-2015, 2015.
Dibb, J. E. and Fahnestock, M.: Snow accumulation, surface height change,
and firn densification at Summit, Greenland: Insights from 2 years of in
situ observation, J. Geophys. Res.-Atmos., 109, D24113, https://doi.org/10.1029/2003JD004300,
2004.
Fausto, R. S., van As, D., Box, J. E., Colgan, W., Langen, P. L., and
Mottram, R. H.: The implication of nonradiative energy fluxes dominating
Greenland ice sheet exceptional ablation area surface melt in 2012, Geophys.
Res. Lett., 43, 2649–2658, https://doi.org/10.1002/2016GL067720, 2016.
Fausto, R. S., Box, J. E., Vandecrux, B., van As, D., Steffen, K.,MacFerrin,
M., Machguth H., Colgan W., Koenig L. S., Mc-Grath D., Charalampidis, C.,
and Braithwaite, R. J.: A Snow Density Dataset for Improving Surface
Boundary Conditions in Greenland Ice Sheet Firn Modeling, Front. Earth Sci.,
6, 51, https://doi.org/10.3389/feart.2018.00051, 2018.
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 Discuss., https://doi.org/10.5194/tc-2019-321, in review, 2020.
Forster, R. R., Box, J. E., van den Broeke, M. R., Miège, C., Burgess,
E. W., Angelen, J. H., Lenaerts, J. T. M., Koenig, L.
S., Paden, J., Lewis, C., Gogineni, S. P., Leuschen, C., and Mc-Connell, J.
R.: Extensive liquid meltwater storage in firn within the Greenland ice
sheet, Nat. Geosci., 7, 95–98, https://doi.org/10.1038/ngeo2043, 2014.
Gray, J. M. N. T.: Water movement in wet snow, Philos. T. R. Soc. A, 354,
465–500, https://doi.org/10.1098/rsta.1996.0017, 1996.
Gregory, S. A., Albert, M. R., and Baker, I.: Impact of physical properties and accumulation rate on pore close-off in layered firn, The Cryosphere, 8, 91–105, https://doi.org/10.5194/tc-8-91-2014, 2014.
Harper, J., Humphrey, N., Pfeffer, W. T., Brown, J., and Fettweis, X.:
Greenland ice-sheet contribution to sea-level rise buffered by meltwater
storage in firn, Nature, 491, 240–243, https://doi.org/10.1038/nature11566,
2012.
Heilig, A., Eisen, O., MacFerrin, M., Tedesco, M., and Fettweis, X.: Seasonal monitoring of melt and accumulation within the deep percolation zone of the Greenland Ice Sheet and comparison with simulations of regional climate modeling, The Cryosphere, 12, 1851–1866, https://doi.org/10.5194/tc-12-1851-2018, 2018.
Herron, M. M. and Langway, C. C.: Firn Densification: An Empirical Model, J.
Glaciol., 25, 373–385, https://doi.org/10.3189/s0022143000015239, 1980.
Hirashima, H., Yamaguchi, S., Sato, A., and Lehning, M.: Numerical modeling
of liquid water movement through layered snow based on new measurements of
the water retention curve, Cold Reg. Sci. Technol., 64, 94–103,
https://doi.org/10.1016/j.coldregions.2010.09.003, 2010.
Kameda, T., Narita, H., Shoji, H., Nishio, F., Fujii, Y., and Watanabe, O.:
Melt features in ice cores from Site J, southern Greenland: some
implications for summer climate since AD 1550, Ann. Glaciol., 21, 51–58,
https://doi.org/10.3189/s0260305500015597, 1995.
Koenig, L. S., Miège, C., Forster, R. R., and Brucker, L.: Initial in
situ measurements of perennial meltwater storage in the Greenland firn
aquifer, Geophys. Res. Lett., 41, 81–85,
https://doi.org/10.1002/2013GL058083, 2014.
Kuipers Munneke, P., Ligtenberg, M. S. R., Van den Broeke, M. R., Van Angelen,
J. H., and Forster, R. R: Explaining the presence of perennial liquid water
bodies in the firn of the Greenland Ice Sheet, Geophys. Res. Lett.,
41, 476–483, https://doi.org/10.1002/2013GL058389, 2014.
Kuipers Munneke, P., Ligtenberg, S. R. M., Noël, B. P. Y., Howat, I. M., Box, J. E., Mosley-Thompson, E., McConnell, J. R., Steffen, K., Harper, J. T., Das, S. B., and van den Broeke, M. R.: Elevation change of the Greenland Ice Sheet due to surface mass balance and firn processes, 1960–2014, The Cryosphere, 9, 2009–2025, https://doi.org/10.5194/tc-9-2009-2015, 2015.
Langen, P., Fausto, R. S., Vandecrux, B., Mottram, R., and Box, J.: 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.
Lefebre, F., Gallée, H., van Ypersele, J.-P., and Greuell, W.: 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.
Ligtenberg, S. R. M., Helsen, M. M., and van den Broeke, M. R.: An improved semi-empirical model for the densification of Antarctic firn, The Cryosphere, 5, 809–819, https://doi.org/10.5194/tc-5-809-2011, 2011.
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.
Lomonaco, R., Albert, M., and Baker, I.: Microstructural evolution of
fine-grained layers through the firn column at Summit, Greenland, J.
Glaciol., 57, 755–762, https://doi.org/10.3189/002214311797409730,
2011.
Lundin, J. M. D., Stevens, C. M., Arthern, R., Buizert, C., Orsi, A.,
Ligtenberg, S. R. M., Simonsen, S. B., Cummings, E., Essery, R., Leahy, W.,
Harris, P., Helsen, M. M., and Waddington, E. D.: Firn Model Intercomparison
Experiment (FirnMICE), J. Glaciol., 63, 401–422,
https://doi.org/10.1017/jog.2016.114, 2017.
MacFerrin, M., Machguth, H., As, D. van, Charalampidis, C., Stevens, C. M.,
Heilig, A., Vandecrux, B., Langen, P. L., Mottram, R., Fettweis, X., Van Den
Broeke, M. R., Pfeffer, W. T., Moussavi, M. S., and Abdalati, W.: Rapid
expansion of Greenland's low-permeability ice slabs, Nature, 573,
403–407, https://doi.org/10.1038/s41586-019-1550-3, 2019.
Machguth, H., Macferrin, M., Van As, D., Box, J. E., Charalampidis, C.,
Colgan, W., Fausto, R. S., Meijer, H. A. J., Mosley-Thompson, E., and Van De
Wal, R. S. W.: Greenland meltwater storage in firn limited by near-surface
ice formation, Nat. Clim. Chang., 6, 390–393,
https://doi.org/10.1038/nclimate2899, 2016.
Marchenko, S., Van Pelt, W. J. J., Claremar, B., Pohjola, V., Pettersson,
R., Machguth, H., and Reijmer, C.: Parameterizing deep water percolation
improves subsurface temperature simulations by a multilayer firn model,
Front. Earth Sci., 5, 16, https://doi.org/10.3389/feart.2017.00016, 2017.
Marchenko, S., Cheng, G., Lötstedt, P., Pohjola, V., Pettersson, R., van Pelt, W., and Reijmer, C.: Thermal conductivity of firn at Lomonosovfonna, Svalbard, derived from subsurface temperature measurements, The Cryosphere, 13, 1843–1859, https://doi.org/10.5194/tc-13-1843-2019, 2019.
Marsh, P. and Woo, M. K.: Wetting front advance and freezing of meltwater
within a snow cover: 1. Observations in the Canadian Arctic, Water Resour.
Res., 20, 1853–1864, https://doi.org/10.1029/WR020i012p01853, 1984.
Mayewski, P. and Whitlow, S.: Snow Pit Data from Greenland Summit, 1989 to
1993, NSF Arctic Data Center, https://doi.org/10.5065/D6NP22KX,
2016.
Meyer, C. R. and Hewitt, I. J.: A continuum model for meltwater flow through compacting snow, The Cryosphere, 11, 2799–2813, https://doi.org/10.5194/tc-11-2799-2017, 2017.
Miège, C., Forster, R. R., Brucker, L., Koenig, L. S., Solomon, D. K.,
Paden, J. D., Box, J. E., Burgess, E. W., Miller, J. Z., McNerney, L.,
Brautigam, N., Fausto, R. S., and Gogineni, S.: Spatial extent and temporal
variability of Greenland firn aquifers detected by ground and airborne
radars, J. Geophys. Res.-Earth Surf., 121, 2381–2398,
https://doi.org/10.1002/2016JF003869, 2016.
Mikkelsen, A. B., Hubbard, A., MacFerrin, M., Box, J. E., Doyle, S. H., Fitzpatrick, A., Hasholt, B., Bailey, H. L., Lindbäck, K., and Pettersson, R.: Extraordinary runoff from the Greenland ice sheet in 2012 amplified by hypsometry and depleted firn retention, The Cryosphere, 10, 1147–1159, https://doi.org/10.5194/tc-10-1147-2016, 2016.
Miller, O., Solomon, D. K., Miège, C., Koenig, L., Forster, R., Schmerr,
N., Ligtenberg, S. R., and Montgomery, L.: Direct evidence of meltwater flow
within a firn aquifer in southeast Greenland, Geophys. Res. Lett., 45, 207–215,
https://doi.org/10.1002/2017GL075707, 2018.
Miller, O., Solomon, D.K., Miège, C., Koenig, L., Forster, R., Schmerr,
N., Ligtenberg, S.R., Legchenko, A., Voss, C.I., Montgomery, L., and
McConnell, J.R., Hydrology of a perennial firn aquifer in Southeast
Greenland: an overview driven by field data, Water Resour. Res., 56, e2019WR026348, https://doi.org/10.1029/2019WR026348, 2019.
Montgomery, L., Koenig, L., and Alexander, P.: The SUMup dataset: compiled measurements of surface mass balance components over ice sheets and sea ice with analysis over Greenland, Earth Syst. Sci. Data, 10, 1959–1985, https://doi.org/10.5194/essd-10-1959-2018, 2018.
Mosley-Thompson, E., McConnell, J. R., Bales, R. C., Li, Z., Lin, P. N.,
Steffen, K., Thompson, L. G., Edwards, R., and Bathke, D.: Local to
regional-scale variability of annual net accumulation on the Greenland ice
sheet from PARCA cores, J. Geophys. Res.-Atmos., 106, 33839–33851,
https://doi.org/10.1029/2001JD900067, 2001.
Nghiem, S. V., Hall, D. K., Mote, T. L., Tedesco, M., Albert, M. R., Keegan,
K., Shuman, C. A., DiGirolamo, N. E., and Neumann, G.: The extreme melt
across the Greenland ice sheet in 2012, Geophys. Res. Lett., 39, L20502,
https://doi.org/10.1029/2012GL053611, 2012.
Nowicki, S. M. J., Payne, A., Larour, E., Seroussi, H., Goelzer, H., Lipscomb, W., Gregory, J., Abe-Ouchi, A., and Shepherd, A.: Ice Sheet Model Intercomparison Project (ISMIP6) contribution to CMIP6, Geosci. Model Dev., 9, 4521–4545, https://doi.org/10.5194/gmd-9-4521-2016, 2016.
Pfeffer, W. T. and Humphrey, N. F.: Determination of timing and location of
water movement and ice-layer formation by temperature measurements in
sub-freezing snow, J. Glaciol., 42,
292–304, https://doi.org/10.3189/S0022143000004159, 1996.
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.
Polashenski, C., Courville, Z., Benson, C., Wagner, A., Chen, J., Wong, G.,
Hawley, R., and Hall, D.: Observations of pronounced Greenland ice sheet firn
warming and implications for runoff production, Geophys. Res. Lett., 41,
4238–4246, https://doi.org/10.1002/2014GL059806, 2014.
Reijmer, C. H., van den Broeke, M. R., Fettweis, X., Ettema, J., and Stap, L. B.: Refreezing on the Greenland ice sheet: a comparison of parameterizations, The Cryosphere, 6, 743–762, https://doi.org/10.5194/tc-6-743-2012, 2012.
Retain Project: Firn Water Retention Intercomparison Project (RetMIP) Protocol, available at: http://retain.geus.dk/index.php/retmip/ (last access: 2 November 2020), 2018.
Samimi, S., Marshall, S. J., and MacFerrin, M.: Meltwater
penetration through temperate ice layers in the percolation zone at DYE-2,
Greenland Ice Sheet, Geophys. Res. Lett., 47, e2020GL089211,
https://doi.org/10.1029/2020GL089211, 2020.
Schneider, T. and Jansson, P.: Internal accumulation in firn and its
significance for the mass balance of Storglaciären, Sweden, J. Glaciol.,
50, 25–34, https://doi.org/10.3189/172756504781830277, 2004.
Schwander, J., Barnola, J.-M., Andrié, C., Leuenberger, M., Ludin, A.,
Raynaud, D., and Stauffer, B.: The age of the air in the firn and the ice at
Summit, Greenland, J. Geophys. Res., 98, 2831–2838, https://doi.org/10.1029/92JD02383, 1993.
Schwander, J., Sowers, T., Barnola, J.M., Blunier, T., Fuchs, A., and
Malaizé, B.: Age scale of the air in the Summit ice:
implication for glacial–interglacial temperature change, J. Geophys. Res.,
102, 19483–19493, https://doi.org/10.1029/97JD01309, 1997.
Simonsen, S. B., Stenseng, L., Adalgeirsdóttir, G., Fausto, R. S.,
Hvidberg, C. S., and Lucas-Picher, P.: Assessing a multilayered dynamic
firn-compaction model for Greenland with ASIRAS radar measurements, J.
Glaciol., 59, 545–558, https://doi.org/10.3189/2013JoG12J158, 2013.
Spencer, M. K., Alley, R. B., and Creyts, T. T.: Preliminary firn
densification model with 38-site dataset, J. Glaciol., 47, 671–676,
https://doi.org/10.3189/172756501781831765, 2001.
Steffen, C., Box, J., and Abdalati, W.: Greenland Climate Network: GC-Net.,
CRREL Special Report on Glaciers, Ice Sheets and Volcanoes, trib. to M.
Meier, 96, 98–103, 1996.
Steger, C. R., Reijmer, C. H., van den Broeke, M. R., Wever, N., Forster, R.
R., Koenig, L. S., Munneke, P. K., Lehning, M., Lhermitte, S., Ligtenberg,
S. R. M., Miège, C., and Noël, B. P. Y.: Firn meltwater retention on
the Greenland ice sheet: A model comparison, Front. Earth Sci., 5, 3,
https://doi.org/10.3389/feart.2017.00003, 2017.
Stevens, C. M., Verjans, V., Lundin, J. M. D., Kahle, E. C., Horlings, A. N., Horlings, B. I., and Waddington, E. D.: The Community Firn Model (CFM) v1.0, Geosci. Model Dev., 13, 4355–4377, https://doi.org/10.5194/gmd-13-4355-2020, 2020.
Sommers, A. N., Rajaram, H., Weber, E. P., MacFerrin, M. J., Colgan, W. T., and
Stevens, C. M.: Inferring firn permeability from pneumatic testing: a case
study on the Greenland ice sheet, Front. Earth Sci., 5, 20, https://doi.org/10.3389/feart.2017.00020, 2017.
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.
Stevens, C. M.: The Community Firn Model, available at: https://github.com/UWGlaciology/CommunityFirnModel, last access: 2 November 2020.
Sturm, M., Holmgren, J., König, M., and Morris, K.: The thermal
conductivity of seasonal snow, J. Glaciol., 43, 26–41,
https://doi.org/10.1017/S0022143000002781, 1997.
The IMBIE team: Mass balance of the Greenland Ice Sheet from 1992 to 2018,
Nature, 579, 233–239,
https://doi.org/10.1038/s41586-019-1855-2, 2020.
Van Angelen, J. H., Lenaerts, J. T. M., Van Den Broeke, M. R., Fettweis, X.,
and Van Meijgaard, E.: Rapid loss of firn pore space accelerates 21st
century Greenland mass loss, Geophys. Res. Lett., 40, 2109–2113,
https://doi.org/10.1002/grl.50490, 2013.
Van As, D., van den Broeke, M., Reijmer, C., and van de Wal, R.: The summer
surface energy balance of the high Antarctic plateau, Bound.-Lay.
Meteorol., 115, 289–317, https://doi.org/10.1007/s10546-004-4631-1,
2005.
Van As, D., Box, J. E., and Fausto, R. S.: Challenges of quantifying
meltwater retention in snow and firn: An expert elicitation, Front. Earth
Sci., 4, 1–5, https://doi.org/10.3389/feart.2016.00101, 2016.
Vandecrux, B.: The firn meltwater retention model intercomparison project
(RetMIP): forcing data, GEUS, https://doi.org/10.22008/FK2/GZ3CSN, 2020a.
Vandecrux, B.: RetMIP plotting scripts (Version v0), Zenodo, https://doi.org/10.5281/zenodo.4172094, 2020b.
Vandecrux, B.: GEUS surface energy balance and firn model (version 0.2), Zenodo, https://doi.org/10.5281/zenodo.4178986, 2020c.
Vandecrux, B., Fausto, R. S., Langen, P. L., van As, D., MacFerrin, M.,
Colgan, W. T., Ingeman-Nielsen, T., Steffen, K., Jensen, N. S., Møller,
M. T., and Box, J. E.: Drivers of Firn Density on the Greenland Ice Sheet
Revealed by Weather Station Observations and Modeling, J. Geophys. Res.-Earth Surf., 123, 2563–2576, https://doi.org/10.1029/2017JF004597,
2018.
Vandecrux, B., MacFerrin, M., Machguth, H., Colgan, W. T., van As, D., Heilig, A., Stevens, C. M., Charalampidis, C., Fausto, R. S., Morris, E. M., Mosley-Thompson, E., Koenig, L., Montgomery, L. N., Miège, C., Simonsen, S. B., Ingeman-Nielsen, T., and Box, J. E.: Firn data compilation reveals widespread decrease of firn air content in western Greenland, The Cryosphere, 13, 845–859, https://doi.org/10.5194/tc-13-845-2019, 2019.
Vandecrux, B., Fausto, R. S., van As, D., Colgan, W., Langen, P. L.,
Haubner, K., Ingeman-Nielsen, T., Heilig, A., Stevens, C. M., MacFerrin, M.,
Niwano, M., Steffen, K., and Box, J. E.: Firn cold content evolution at nine
sites on the Greenland ice sheet between 1998 and 2017, J.
Glaciol., 66, 591–602, https://doi.org/10.1017/jog.2020.30, 2020a.
Vandecrux, B., Langen, P.L., Kuipers Munneke, P. Simonsen, S., Verjans,
Stevens, C. M. V., Marchenko, S., Van Pelt, W., and Meyer, C.: The firn
meltwater retention model intercomparison project (RetMIP): model outputs,
GEUS, https://doi.org/10.22008/FK2/CVPUJL, 2020b.
van den Broeke, M. R., Enderlin, E. M., Howat, I. M., Kuipers Munneke, P., Noël, B. P. Y., van de Berg, W. J., van Meijgaard, E., and Wouters, B.: On the recent contribution of the Greenland ice sheet to sea level change, The Cryosphere, 10, 1933–1946, https://doi.org/10.5194/tc-10-1933-2016, 2016.
Van Genuchten, M. T.: Closed-Form Equation for Predicting the Hydraulic
Conductivity of Unsaturated Soils, Soil Sci. Soc. Am. J., 44, 892–898,
https://doi.org/10.2136/sssaj1980.03615995004400050002x, 1980.
van Pelt, W., Pohjola, V., Pettersson, R., Marchenko, S., Kohler, J., Luks, B., Hagen, J. O., Schuler, T. V., Dunse, T., Noël, B., and Reijmer, C.: A long-term dataset of climatic mass balance, snow conditions, and runoff in Svalbard (1957–2018), The Cryosphere, 13, 2259–2280, https://doi.org/10.5194/tc-13-2259-2019, 2019.
van Pelt, W. J. J., Oerlemans, J., Reijmer, C. H., Pohjola, V. A., Pettersson, R., and van Angelen, J. H.: Simulating melt, runoff and refreezing on Nordenskiöldbreen, Svalbard, using a coupled snow and energy balance model, The Cryosphere, 6, 641–659, https://doi.org/10.5194/tc-6-641-2012, 2012.
Verjans, V., Leeson, A. A., Stevens, C. M., MacFerrin, M., Noël, B., and van den Broeke, M. R.: Development of physically based liquid water schemes for Greenland firn-densification models, The Cryosphere, 13, 1819–1842, https://doi.org/10.5194/tc-13-1819-2019, 2019.
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.
Wever, N., Würzer, S., Fierz, C., and Lehning, M.: Simulating ice layer formation under the presence of preferential flow in layered snowpacks, The Cryosphere, 10, 2731–2744, https://doi.org/10.5194/tc-10-2731-2016, 2016.
Yamaguchi, S., Watanabe, K., Katsushima, T., Sato, A., and Kumakura, T.:
Dependence of the water retention curve of snow on snow characteristics.
Ann. Glaciol., 53, 6–12, https://doi.org/10.3189/2012AoG61A001,
2012.
Yen, Y.-C.: Review of thermal properties of snow, ice and sea ice, CRREL Report
81-10, 1–27, available at:
https://usace.contentdm.oclc.org/digital/api/collection/p266001coll1/id/7366/download (last access: 2 November 2020),
1981.
Zuo, Z. and Oerlemans, J.: Modelling albedo and specific balance of the
Greenland ice sheet: Calculations for the Søndre Strømfjord transect,
J. Glaciol., 42, 305–316, https://doi.org/10.3189/s0022143000004160,
1996.
Zwally, H. J., Li, J., Brenner, A. C., Beckley, M., Cornejo, H. G.,
DiMarzio, J., Giovinetto, M. B., Neumann, T., Robbins, J., Saba, J. L., Yi,
D., and Wang, W.: Greenland ice sheet mass balance: distribution of
increased mass loss with climate warming; 2003–07 versus 1992–2002, J.
Glaciol., 57, 88–102, https://doi.org/10.3189/002214311795306682, 2011.
Short summary
In the vast interior of the Greenland ice sheet, snow accumulates into a thick and porous layer called firn. Each summer, the firn retains part of the meltwater generated at the surface and buffers sea-level rise. In this study, we compare nine firn models traditionally used to quantify this retention at four sites and evaluate their performance against a set of in situ observations. We highlight limitations of certain model designs and give perspectives for future model development.
In the vast interior of the Greenland ice sheet, snow accumulates into a thick and porous layer...
