Articles | Volume 17, issue 1
https://doi.org/10.5194/tc-17-175-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-17-175-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
16 Jan 2023
Research article |
| 16 Jan 2023
| 16 Jan 2023
Snow stratigraphy observations from Operation IceBridge surveys in Alaska using S and C band airborne ultra-wideband FMCW (frequency-modulated continuous wave) radar
The Center for Remote Sensing and Integrated Systems (CReSIS),
University of Kansas, Lawrence, KS 66045, USA
Fernando Rodriguez-Morales
The Center for Remote Sensing and Integrated Systems (CReSIS),
University of Kansas, Lawrence, KS 66045, USA
Xavier Fettweis
Department of Geography, SPHERES research unit, University of Liège, Liège, Belgium
Oluwanisola Ibikunle
The Center for Remote Sensing and Integrated Systems (CReSIS),
University of Kansas, Lawrence, KS 66045, USA
Carl Leuschen
The Center for Remote Sensing and Integrated Systems (CReSIS),
University of Kansas, Lawrence, KS 66045, USA
John Paden
The Center for Remote Sensing and Integrated Systems (CReSIS),
University of Kansas, Lawrence, KS 66045, USA
Daniel Gomez-Garcia
The Center for Remote Sensing and Integrated Systems (CReSIS),
University of Kansas, Lawrence, KS 66045, USA
Emily Arnold
The Center for Remote Sensing and Integrated Systems (CReSIS),
University of Kansas, Lawrence, KS 66045, USA
Related authors
Renée Mie Fredensborg Hansen, Henriette Skourup, Eero Rinne, Arttu Jutila, Isobel R. Lawrence, Andrew Shepherd, Knut Vilhelm Høyland, Jilu Li, Fernando Rodriguez-Morales, Sebastian Bjerregaaard Simonsen, Jeremy Wilkinson, Gaelle Veyssiere, Donghui Yi, René Forsberg, and Taniâ Gil Duarte Casal
The Cryosphere, 19, 4167–4192, https://doi.org/10.5194/tc-19-4167-2025, https://doi.org/10.5194/tc-19-4167-2025, 2025
Short summary
Short summary
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 snow penetration. Ka-band and Ku-band had limited penetration with significant contributions from the air–snow interface, contradicting traditional assumptions with discrepancies between commonly used C/S-band "snow-radar" methodologies, all challenging comparisons of airborne and spaceborne estimates.
Renée Mie Fredensborg Hansen, Henriette Skourup, Eero Rinne, Arttu Jutila, Isobel R. Lawrence, Andrew Shepherd, Knut Vilhelm Høyland, Jilu Li, Fernando Rodriguez-Morales, Sebastian Bjerregaaard Simonsen, Jeremy Wilkinson, Gaelle Veyssiere, Donghui Yi, René Forsberg, and Taniâ Gil Duarte Casal
The Cryosphere, 19, 4193–4209, https://doi.org/10.5194/tc-19-4193-2025, https://doi.org/10.5194/tc-19-4193-2025, 2025
Short summary
Short summary
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 snow penetration. Ka-band and Ku-band had limited penetration with significant contributions from the air–snow interface, contradicting traditional assumptions with discrepancies between commonly used C/S-band "snow-radar" methodologies, all challenging comparisons of airborne and spaceborne estimates.
Joseph A. MacGregor, Mark A. Fahnestock, John D. Paden, Jilu Li, Jeremy P. Harbeck, and Andy Aschwanden
Earth Syst. Sci. Data, 17, 2911–2931, https://doi.org/10.5194/essd-17-2911-2025, https://doi.org/10.5194/essd-17-2911-2025, 2025
Short summary
Short summary
This paper describes the second version of a deep radiostratigraphic database for the Greenland Ice Sheet. It includes numerous improvements to the original database from 2015 and includes newer high-quality radar sounding data from 2014–2019. It represents a unique and widespread constraint on the history of the ice sheet that could be helpful to initialize and interpret ice-sheet models.
Isobel Rowell, Carlos Martin, Robert Mulvaney, Helena Pryer, Dieter Tetzner, Emily Doyle, Hara Madhav Talasila, Jilu Li, and Eric Wolff
Clim. Past, 19, 1699–1714, https://doi.org/10.5194/cp-19-1699-2023, https://doi.org/10.5194/cp-19-1699-2023, 2023
Short summary
Short summary
We present an age scale for a new type of ice core from a vulnerable region in West Antarctic, which is lacking in longer-term (greater than a few centuries) ice core records. The Sherman Island core extends to greater than 1 kyr. We provide modelling evidence for the potential of a 10 kyr long core. We show that this new type of ice core can be robustly dated and that climate records from this core will be a significant addition to existing regional climate records.
Kristiina Verro, Cecilia Äijälä, Roberta Pirazzini, Ruzica Dadic, Damien Maure, Willem Jan van de Berg, Giacomo Traversa, Christiaan T. van Dalum, Petteri Uotila, Xavier Fettweis, Biagio Di Mauro, and Milla Johansson
The Cryosphere, 19, 4409–4436, https://doi.org/10.5194/tc-19-4409-2025, https://doi.org/10.5194/tc-19-4409-2025, 2025
Short summary
Short summary
Accurately representing Antarctic sea ice is essential for reliable climate and ocean model predictions. We evaluated how different models simulate the sea ice's sunlight reflectivity (called albedo) using field and satellite data. Models with simple albedo schemes performed well in limited cases but missed key processes. The advanced scheme in the MetROMS-UHel ocean model provided the most accurate results, including observed day–night albedo changes observed during a field campaign.
Ella Gilbert, José Abraham Torres-Alavez, Marte G. Hofsteenge, Willem Jan van de Berg, Fredrik Boberg, Ole Bøssing Christensen, Christiaan Timo van Dalum, Xavier Fettweis, Siddharth Gumber, Nicolaj Hansen, Christoph Kittel, Clara Lambin, Damien Maure, Ruth Mottram, Martin Olesen, Andrew Orr, Tony Phillips, Maurice van Tiggelen, Kristiina Verro, and Priscilla A. Mooney
EGUsphere, https://doi.org/10.5194/egusphere-2025-4214, https://doi.org/10.5194/egusphere-2025-4214, 2025
This preprint is open for discussion and under review for The Cryosphere (TC).
Short summary
Short summary
Here we present a new dataset – the PolarRES ensemble – of four state-of-the-art regional climate models, which capture the full complexity of Antarctica's climate. The ensemble out-performs other available tools, advancing our ability to explore Antarctic climate. While it still has limitations, the PolarRES ensemble offers a novel and exciting way of evaluating climate processes and features, and we encourage researchers to use the data, which are freely available.
Jonathon R. Preece, Patrick Alexander, Thomas L. Mote, Gabriel J. Kooperman, Xavier Fettweis, and Marco Tedesco
EGUsphere, https://doi.org/10.5194/egusphere-2025-4140, https://doi.org/10.5194/egusphere-2025-4140, 2025
This preprint is open for discussion and under review for The Cryosphere (TC).
Short summary
Short summary
Surface melt of the Greenland Ice Sheet has increased dramatically since the turn of the century, aided by an increase in persistent atmospheric circulation patterns that promote anomalously warm conditions. Through modeling experiments, this study shows that surface mass loss would have been reduced by 62% relative to historical conditions if this shift in atmospheric circulation would have occurred in a preindustrial climate, highlighting the important contribution of anthropogenic warming.
Renée Mie Fredensborg Hansen, Henriette Skourup, Eero Rinne, Arttu Jutila, Isobel R. Lawrence, Andrew Shepherd, Knut Vilhelm Høyland, Jilu Li, Fernando Rodriguez-Morales, Sebastian Bjerregaaard Simonsen, Jeremy Wilkinson, Gaelle Veyssiere, Donghui Yi, René Forsberg, and Taniâ Gil Duarte Casal
The Cryosphere, 19, 4167–4192, https://doi.org/10.5194/tc-19-4167-2025, https://doi.org/10.5194/tc-19-4167-2025, 2025
Short summary
Short summary
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 snow penetration. Ka-band and Ku-band had limited penetration with significant contributions from the air–snow interface, contradicting traditional assumptions with discrepancies between commonly used C/S-band "snow-radar" methodologies, all challenging comparisons of airborne and spaceborne estimates.
Renée Mie Fredensborg Hansen, Henriette Skourup, Eero Rinne, Arttu Jutila, Isobel R. Lawrence, Andrew Shepherd, Knut Vilhelm Høyland, Jilu Li, Fernando Rodriguez-Morales, Sebastian Bjerregaaard Simonsen, Jeremy Wilkinson, Gaelle Veyssiere, Donghui Yi, René Forsberg, and Taniâ Gil Duarte Casal
The Cryosphere, 19, 4193–4209, https://doi.org/10.5194/tc-19-4193-2025, https://doi.org/10.5194/tc-19-4193-2025, 2025
Short summary
Short summary
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 snow penetration. Ka-band and Ku-band had limited penetration with significant contributions from the air–snow interface, contradicting traditional assumptions with discrepancies between commonly used C/S-band "snow-radar" methodologies, all challenging comparisons of airborne and spaceborne estimates.
Weiran Li, Stef Lhermitte, Bert Wouters, Cornelis Slobbe, Max Brils, and Xavier Fettweis
The Cryosphere, 19, 3419–3442, https://doi.org/10.5194/tc-19-3419-2025, https://doi.org/10.5194/tc-19-3419-2025, 2025
Short summary
Short summary
Due to recurrent melt and refreezing events in recent decades, the snow conditions over Greenland have changed. To observe this, we use a parameter (leading edge width; LeW) derived from satellite altimetry and analyse its spatial and temporal variations. By comparing the LeW variations with modelled firn parameters, we concluded that the 2012 melt event and the recent and increasingly frequent melt events have a long-lasting impact on the volume scattering of Greenland firn.
Zhengwen Yan, Jiangjun Ran, Pavel Ditmar, C. K. Shum, Roland Klees, Patrick Smith, and Xavier Fettweis
Earth Syst. Sci. Data, 17, 4253–4275, https://doi.org/10.5194/essd-17-4253-2025, https://doi.org/10.5194/essd-17-4253-2025, 2025
Short summary
Short summary
The Gravity Recovery And Climate Experiment (GRACE) mission has greatly improved our understanding of changes in Earth's gravity field over time. A novel mass concentration (mascon) dataset, GCL-Mascon2024, was determined by leveraging the short-arc approach, advanced spatial constraints, a frequency-dependent noise processing strategy, and parameterization-integrating natural boundaries, aiming to enhance accuracy for monitoring mass transportation on Earth.
Heiko Goelzer, Constantijn J. Berends, Fredrik Boberg, Gael Durand, Tamsin Edwards, Xavier Fettweis, Fabien Gillet-Chaulet, Quentin Glaude, Philippe Huybrechts, Sébastien Le clec'h, Ruth Mottram, Brice Noël, Martin Olesen, Charlotte Rahlves, Jeremy Rohmer, Michiel van den Broeke, and Roderik S. W. van de Wal
EGUsphere, https://doi.org/10.5194/egusphere-2025-3098, https://doi.org/10.5194/egusphere-2025-3098, 2025
Short summary
Short summary
We present an ensemble of ice sheet model projections for the Greenland ice sheet. The focus is on providing projections that improve our understanding of the range future sea-level rise and the inherent uncertainties over the next 100 to 300 years. Compared to earlier work we more fully account for some of the uncertainties in sea-level projections. We include a wider range of climate model output, more climate change scenarios and we extend projections schematically up to year 2300.
Audrey Goutard, Marion Réveillet, Fanny Brun, Delphine Six, Kevin Fourteau, Charles Amory, Xavier Fettweis, Mathieu Fructus, Arbindra Khadka, and Matthieu Lafaysse
EGUsphere, https://doi.org/10.5194/egusphere-2025-2947, https://doi.org/10.5194/egusphere-2025-2947, 2025
Short summary
Short summary
A new scheme has been developed in the SURFEX/ISBA-Crocus model, to consider the impact of liquid water dynamics on bare ice, including albedo feedback and refreezing. When applied to the Mera Glacier in Nepal, the model reveals strong seasonal effects on the energy and mass balance, with increased melting in dry seasons and significant refreezing during the monsoon. This development improves mass balance modeling under increasing rainfall and bare ice exposure due to climate warming.
Chloë Marie Paice, Xavier Fettweis, and Philippe Huybrechts
EGUsphere, https://doi.org/10.5194/egusphere-2025-2465, https://doi.org/10.5194/egusphere-2025-2465, 2025
Short summary
Short summary
To study the interactions between the Greenland ice sheet and the atmosphere, we coupled an ice sheet model to a regional climate model and performed simulations of differing coupling complexity over 1000 years. They reveal that at first melt at the ice sheet margin is reduced by changing wind patterns. But over time, as the ice sheet surface lowers, precipitation patterns and cloudiness also change and amplify ice mass loss over the entire ice sheet.
Joseph A. MacGregor, Mark A. Fahnestock, John D. Paden, Jilu Li, Jeremy P. Harbeck, and Andy Aschwanden
Earth Syst. Sci. Data, 17, 2911–2931, https://doi.org/10.5194/essd-17-2911-2025, https://doi.org/10.5194/essd-17-2911-2025, 2025
Short summary
Short summary
This paper describes the second version of a deep radiostratigraphic database for the Greenland Ice Sheet. It includes numerous improvements to the original database from 2015 and includes newer high-quality radar sounding data from 2014–2019. It represents a unique and widespread constraint on the history of the ice sheet that could be helpful to initialize and interpret ice-sheet models.
Charlotte M. Carter, Steven Franke, Daniela Jansen, Chris R. Stokes, Veit Helm, John Paden, and Olaf Eisen
EGUsphere, https://doi.org/10.5194/egusphere-2025-1743, https://doi.org/10.5194/egusphere-2025-1743, 2025
Short summary
Short summary
The landscapes beneath actively fast-flowing ice in Greenland have not been explored in detail, as digital elevation models do not have a high enough resolution to see these subglacial features. We use swath radar imaging to visualise these landforms at a high resolution, revealing a landscape that would usually be assumed to be indicative of faster ice flow than the current velocities. Interpretation of the landscape also gives an indication of the properties of the bed beneath the ice stream.
Jean-François Grailet, Robin J. Hogan, Nicolas Ghilain, David Bolsée, Xavier Fettweis, and Marilaure Grégoire
Geosci. Model Dev., 18, 1965–1988, https://doi.org/10.5194/gmd-18-1965-2025, https://doi.org/10.5194/gmd-18-1965-2025, 2025
Short summary
Short summary
The MAR (Modèle Régional Atmosphérique) is a regional climate model used for weather forecasting and studying the climate over various regions. This paper presents an update of MAR thanks to which it can precisely decompose solar radiation, in particular in the UV (ultraviolet) and photosynthesis ranges, both being critical to human health and ecosystems. As a first application of this new capability, this paper presents a method for predicting UV indices with MAR.
Ny Riana Randresihaja, Olivier Gourgue, Lauranne Alaerts, Xavier Fettweis, Jonathan Lambrechts, Miguel De Le Court, Marilaure Grégoire, and Emmanuel Hanert
EGUsphere, https://doi.org/10.5194/egusphere-2025-634, https://doi.org/10.5194/egusphere-2025-634, 2025
Preprint archived
Short summary
Short summary
Coastal areas face rising flood threats as storms intensifies with climate change. With an advanced model of the Scheldt Estuary-North Sea, we studied how detailed atmospheric data must be to predict storm surge peaks in estuaries. We found that high-resolution atmospheric data gives the best results, and coarser data with same resolution as current global climate models give poorer results. We show that investing in localized, high-resolution atmospheric data can significantly improve results.
Sylvie Charbit, Christophe Dumas, Fabienne Maignan, Catherine Ottlé, Nina Raoult, Xavier Fettweis, and Philippe Conesa
The Cryosphere, 18, 5067–5099, https://doi.org/10.5194/tc-18-5067-2024, https://doi.org/10.5194/tc-18-5067-2024, 2024
Short summary
Short summary
The evolution of the Greenland ice sheet is highly dependent on surface melting and therefore on the processes operating at the snow–atmosphere interface and within the snow cover. Here we present new developments to apply a snow model to the Greenland ice sheet. The performance of this model is analysed in terms of its ability to simulate ablation processes. Our analysis shows that the model performs well when compared with the MAR regional polar atmospheric model.
Horst Machguth, Andrew Tedstone, Peter Kuipers Munneke, Max Brils, Brice Noël, Nicole Clerx, Nicolas Jullien, Xavier Fettweis, and Michiel van den Broeke
EGUsphere, https://doi.org/10.5194/egusphere-2024-2750, https://doi.org/10.5194/egusphere-2024-2750, 2024
Short summary
Short summary
Due to increasing air temperatures, surface melt expands to higher elevations on the Greenland ice sheet. This is visible on satellite imagery in the form of rivers of meltwater running across the surface of the ice sheet. We compare model results of meltwater at high elevations on the ice sheet to satellite observations. We find that each of the models shows strengths and weaknesses. A detailed look into the model results reveals potential reasons for the differences between models.
Alison Delhasse, Johanna Beckmann, Christoph Kittel, and Xavier Fettweis
The Cryosphere, 18, 633–651, https://doi.org/10.5194/tc-18-633-2024, https://doi.org/10.5194/tc-18-633-2024, 2024
Short summary
Short summary
Aiming to study the long-term influence of an extremely warm climate in the Greenland Ice Sheet contribution to sea level rise, a new regional atmosphere–ice sheet model setup was established. The coupling, explicitly considering the melt–elevation feedback, is compared to an offline method to consider this feedback. We highlight mitigation of the feedback due to local changes in atmospheric circulation with changes in surface topography, making the offline correction invalid on the margins.
Baptiste Vandecrux, Robert S. Fausto, Jason E. Box, Federico Covi, Regine Hock, Åsa K. Rennermalm, Achim Heilig, Jakob Abermann, Dirk van As, Elisa Bjerre, Xavier Fettweis, Paul C. J. P. Smeets, Peter Kuipers Munneke, Michiel R. van den Broeke, Max Brils, Peter L. Langen, Ruth Mottram, and Andreas P. Ahlstrøm
The Cryosphere, 18, 609–631, https://doi.org/10.5194/tc-18-609-2024, https://doi.org/10.5194/tc-18-609-2024, 2024
Short summary
Short summary
How fast is the Greenland ice sheet warming? In this study, we compiled 4500+ temperature measurements at 10 m below the ice sheet surface (T10m) from 1912 to 2022. We trained a machine learning model on these data and reconstructed T10m for the ice sheet during 1950–2022. After a slight cooling during 1950–1985, the ice sheet warmed at a rate of 0.7 °C per decade until 2022. Climate models showed mixed results compared to our observations and underestimated the warming in key regions.
Idunn Aamnes Mostue, Stefan Hofer, Trude Storelvmo, and Xavier Fettweis
The Cryosphere, 18, 475–488, https://doi.org/10.5194/tc-18-475-2024, https://doi.org/10.5194/tc-18-475-2024, 2024
Short summary
Short summary
The latest generation of climate models (Coupled Model Intercomparison Project Phase 6 – CMIP6) warm more over Greenland and the Arctic and thus also project a larger mass loss from the Greenland Ice Sheet (GrIS) compared to the previous generation of climate models (CMIP5). Our work suggests for the first time that part of the greater mass loss in CMIP6 over the GrIS is driven by a difference in the surface mass balance sensitivity from a change in cloud representation in the CMIP6 models.
Laura J. Dietrich, Hans Christian Steen-Larsen, Sonja Wahl, Anne-Katrine Faber, and Xavier Fettweis
The Cryosphere, 18, 289–305, https://doi.org/10.5194/tc-18-289-2024, https://doi.org/10.5194/tc-18-289-2024, 2024
Short summary
Short summary
The contribution of the humidity flux to the surface mass balance in the accumulation zone of the Greenland Ice Sheet is uncertain. Here, we evaluate the regional climate model MAR using a multi-annual dataset of eddy covariance measurements and bulk estimates of the humidity flux. The humidity flux largely contributes to the summer surface mass balance (SMB) in the accumulation zone, indicating its potential importance for the annual SMB in a warming climate.
Marco Tedesco, Paolo Colosio, Xavier Fettweis, and Guido Cervone
The Cryosphere, 17, 5061–5074, https://doi.org/10.5194/tc-17-5061-2023, https://doi.org/10.5194/tc-17-5061-2023, 2023
Short summary
Short summary
We developed a technique to improve the outputs of a model that calculates the gain and loss of Greenland and consequently its contribution to sea level rise. Our technique generates “sharper” images of the maps generated by the model to better understand and quantify where losses occur. This has implications for improving models, understanding what drives the contributions of Greenland to sea level rise, and more.
Damien Maure, Christoph Kittel, Clara Lambin, Alison Delhasse, and Xavier Fettweis
The Cryosphere, 17, 4645–4659, https://doi.org/10.5194/tc-17-4645-2023, https://doi.org/10.5194/tc-17-4645-2023, 2023
Short summary
Short summary
The Arctic is warming faster than the rest of the Earth. Studies have already shown that Greenland and the Canadian Arctic are experiencing a record increase in melting rates, while Svalbard has been relatively less impacted. Looking at those regions but also extending the study to Iceland and the Russian Arctic archipelagoes, we see a heterogeneity in the melting-rate response to the Arctic warming, with the Russian archipelagoes experiencing lower melting rates than other regions.
Prateek Gantayat, Alison F. Banwell, Amber A. Leeson, James M. Lea, Dorthe Petersen, Noel Gourmelen, and Xavier Fettweis
Geosci. Model Dev., 16, 5803–5823, https://doi.org/10.5194/gmd-16-5803-2023, https://doi.org/10.5194/gmd-16-5803-2023, 2023
Short summary
Short summary
We developed a new supraglacial hydrology model for the Greenland Ice Sheet. This model simulates surface meltwater routing, meltwater drainage, supraglacial lake (SGL) overflow, and formation of lake ice. The model was able to reproduce 80 % of observed lake locations and provides a good match between the observed and modelled temporal evolution of SGLs.
Thomas Dethinne, Quentin Glaude, Ghislain Picard, Christoph Kittel, Patrick Alexander, Anne Orban, and Xavier Fettweis
The Cryosphere, 17, 4267–4288, https://doi.org/10.5194/tc-17-4267-2023, https://doi.org/10.5194/tc-17-4267-2023, 2023
Short summary
Short summary
We investigate the sensitivity of the regional climate model
Modèle Atmosphérique Régional(MAR) to the assimilation of wet-snow occurrence estimated by remote sensing datasets. The assimilation is performed by nudging the MAR snowpack temperature. The data assimilation is performed over the Antarctic Peninsula for the 2019–2021 period. The results show an increase in the melt production (+66.7 %) and a decrease in surface mass balance (−4.5 %) of the model for the 2019–2020 melt season.
Isobel Rowell, Carlos Martin, Robert Mulvaney, Helena Pryer, Dieter Tetzner, Emily Doyle, Hara Madhav Talasila, Jilu Li, and Eric Wolff
Clim. Past, 19, 1699–1714, https://doi.org/10.5194/cp-19-1699-2023, https://doi.org/10.5194/cp-19-1699-2023, 2023
Short summary
Short summary
We present an age scale for a new type of ice core from a vulnerable region in West Antarctic, which is lacking in longer-term (greater than a few centuries) ice core records. The Sherman Island core extends to greater than 1 kyr. We provide modelling evidence for the potential of a 10 kyr long core. We show that this new type of ice core can be robustly dated and that climate records from this core will be a significant addition to existing regional climate records.
Alice C. Frémand, Peter Fretwell, Julien A. Bodart, Hamish D. Pritchard, Alan Aitken, Jonathan L. Bamber, Robin Bell, Cesidio Bianchi, Robert G. Bingham, Donald D. Blankenship, Gino Casassa, Ginny Catania, Knut Christianson, Howard Conway, Hugh F. J. Corr, Xiangbin Cui, Detlef Damaske, Volkmar Damm, Reinhard Drews, Graeme Eagles, Olaf Eisen, Hannes Eisermann, Fausto Ferraccioli, Elena Field, René Forsberg, Steven Franke, Shuji Fujita, Yonggyu Gim, Vikram Goel, Siva Prasad Gogineni, Jamin Greenbaum, Benjamin Hills, Richard C. A. Hindmarsh, Andrew O. Hoffman, Per Holmlund, Nicholas Holschuh, John W. Holt, Annika N. Horlings, Angelika Humbert, Robert W. Jacobel, Daniela Jansen, Adrian Jenkins, Wilfried Jokat, Tom Jordan, Edward King, Jack Kohler, William Krabill, Mette Kusk Gillespie, Kirsty Langley, Joohan Lee, German Leitchenkov, Carlton Leuschen, Bruce Luyendyk, Joseph MacGregor, Emma MacKie, Kenichi Matsuoka, Mathieu Morlighem, Jérémie Mouginot, Frank O. Nitsche, Yoshifumi Nogi, Ole A. Nost, John Paden, Frank Pattyn, Sergey V. Popov, Eric Rignot, David M. Rippin, Andrés Rivera, Jason Roberts, Neil Ross, Anotonia Ruppel, Dustin M. Schroeder, Martin J. Siegert, Andrew M. Smith, Daniel Steinhage, Michael Studinger, Bo Sun, Ignazio Tabacco, Kirsty Tinto, Stefano Urbini, David Vaughan, Brian C. Welch, Douglas S. Wilson, Duncan A. Young, and Achille Zirizzotti
Earth Syst. Sci. Data, 15, 2695–2710, https://doi.org/10.5194/essd-15-2695-2023, https://doi.org/10.5194/essd-15-2695-2023, 2023
Short summary
Short summary
This paper presents the release of over 60 years of ice thickness, bed elevation, and surface elevation data acquired over Antarctica by the international community. These data are a crucial component of the Antarctic Bedmap initiative which aims to produce a new map and datasets of Antarctic ice thickness and bed topography for the international glaciology and geophysical community.
Inès N. Otosaka, Andrew Shepherd, Erik R. Ivins, Nicole-Jeanne Schlegel, Charles Amory, Michiel R. van den Broeke, Martin Horwath, Ian Joughin, Michalea D. King, Gerhard Krinner, Sophie Nowicki, Anthony J. Payne, Eric Rignot, Ted Scambos, Karen M. Simon, Benjamin E. Smith, Louise S. Sørensen, Isabella Velicogna, Pippa L. Whitehouse, Geruo A, Cécile Agosta, Andreas P. Ahlstrøm, Alejandro Blazquez, William Colgan, Marcus E. Engdahl, Xavier Fettweis, Rene Forsberg, Hubert Gallée, Alex Gardner, Lin Gilbert, Noel Gourmelen, Andreas Groh, Brian C. Gunter, Christopher Harig, Veit Helm, Shfaqat Abbas Khan, Christoph Kittel, Hannes Konrad, Peter L. Langen, Benoit S. Lecavalier, Chia-Chun Liang, Bryant D. Loomis, Malcolm McMillan, Daniele Melini, Sebastian H. Mernild, Ruth Mottram, Jeremie Mouginot, Johan Nilsson, Brice Noël, Mark E. Pattle, William R. Peltier, Nadege Pie, Mònica Roca, Ingo Sasgen, Himanshu V. Save, Ki-Weon Seo, Bernd Scheuchl, Ernst J. O. Schrama, Ludwig Schröder, Sebastian B. Simonsen, Thomas Slater, Giorgio Spada, Tyler C. Sutterley, Bramha Dutt Vishwakarma, Jan Melchior van Wessem, David Wiese, Wouter van der Wal, and Bert Wouters
Earth Syst. Sci. Data, 15, 1597–1616, https://doi.org/10.5194/essd-15-1597-2023, https://doi.org/10.5194/essd-15-1597-2023, 2023
Short summary
Short summary
By measuring changes in the volume, gravitational attraction, and ice flow of Greenland and Antarctica from space, we can monitor their mass gain and loss over time. Here, we present a new record of the Earth’s polar ice sheet mass balance produced by aggregating 50 satellite-based estimates of ice sheet mass change. This new assessment shows that the ice sheets have lost (7.5 x 1012) t of ice between 1992 and 2020, contributing 21 mm to sea level rise.
Benjamin E. Smith, Brooke Medley, Xavier Fettweis, Tyler Sutterley, Patrick Alexander, David Porter, and Marco Tedesco
The Cryosphere, 17, 789–808, https://doi.org/10.5194/tc-17-789-2023, https://doi.org/10.5194/tc-17-789-2023, 2023
Short summary
Short summary
We use repeated satellite measurements of the height of the Greenland ice sheet to learn about how three computational models of snowfall, melt, and snow compaction represent actual changes in the ice sheet. We find that the models do a good job of estimating how the parts of the ice sheet near the coast have changed but that two of the models have trouble representing surface melt for the highest part of the ice sheet. This work provides suggestions for how to better model snowmelt.
Raf M. Antwerpen, Marco Tedesco, Xavier Fettweis, Patrick Alexander, and Willem Jan van de Berg
The Cryosphere, 16, 4185–4199, https://doi.org/10.5194/tc-16-4185-2022, https://doi.org/10.5194/tc-16-4185-2022, 2022
Short summary
Short summary
The ice on Greenland has been melting more rapidly over the last few years. Most of this melt comes from the exposure of ice when the overlying snow melts. This ice is darker than snow and absorbs more sunlight, leading to more melt. It remains challenging to accurately simulate the brightness of the ice. We show that the color of ice simulated by Modèle Atmosphérique Régional (MAR) is too bright. We then show that this means that MAR may underestimate how fast the Greenland ice is melting.
Christoph Kittel, Charles Amory, Stefan Hofer, Cécile Agosta, Nicolas C. Jourdain, Ella Gilbert, Louis Le Toumelin, Étienne Vignon, Hubert Gallée, and Xavier Fettweis
The Cryosphere, 16, 2655–2669, https://doi.org/10.5194/tc-16-2655-2022, https://doi.org/10.5194/tc-16-2655-2022, 2022
Short summary
Short summary
Model projections suggest large differences in future Antarctic surface melting even for similar greenhouse gas scenarios and warming rates. We show that clouds containing a larger amount of liquid water lead to stronger melt. As surface melt can trigger the collapse of the ice shelves (the safety band of the Antarctic Ice Sheet), clouds could be a major source of uncertainties in projections of sea level rise.
Sébastien Doutreloup, Xavier Fettweis, Ramin Rahif, Essam Elnagar, Mohsen S. Pourkiaei, Deepak Amaripadath, and Shady Attia
Earth Syst. Sci. Data, 14, 3039–3051, https://doi.org/10.5194/essd-14-3039-2022, https://doi.org/10.5194/essd-14-3039-2022, 2022
Short summary
Short summary
This data set provides historical (1980–2014) and future (2015–2100) weather data for 12 cities in Belgium. This data set is intended for architects or building or energy designers. In particular, it makes available to all users hourly open-access weather data according to certain standards to recreate a Typical and an Extreme Meteorological Year. In addition, it provides hourly data on heatwaves from 1980 to 2100. Weather data were produced from the outputs of the MAR model simulations.
Steven Franke, Daniela Jansen, Tobias Binder, John D. Paden, Nils Dörr, Tamara A. Gerber, Heinrich Miller, Dorthe Dahl-Jensen, Veit Helm, Daniel Steinhage, Ilka Weikusat, Frank Wilhelms, and Olaf Eisen
Earth Syst. Sci. Data, 14, 763–779, https://doi.org/10.5194/essd-14-763-2022, https://doi.org/10.5194/essd-14-763-2022, 2022
Short summary
Short summary
The Northeast Greenland Ice Stream (NEGIS) is the largest ice stream in Greenland. In order to better understand the past and future dynamics of the NEGIS, we present a high-resolution airborne radar data set (EGRIP-NOR-2018) for the onset region of the NEGIS. The survey area is centered at the location of the drill site of the East Greenland Ice-Core Project (EastGRIP), and radar profiles cover both shear margins and are aligned parallel to several flow lines.
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.
Marie G. P. Cavitte, Duncan A. Young, Robert Mulvaney, Catherine Ritz, Jamin S. Greenbaum, Gregory Ng, Scott D. Kempf, Enrica Quartini, Gail R. Muldoon, John Paden, Massimo Frezzotti, Jason L. Roberts, Carly R. Tozer, Dustin M. Schroeder, and Donald D. Blankenship
Earth Syst. Sci. Data, 13, 4759–4777, https://doi.org/10.5194/essd-13-4759-2021, https://doi.org/10.5194/essd-13-4759-2021, 2021
Short summary
Short summary
We present a data set consisting of ice-penetrating-radar internal stratigraphy: 26 internal reflecting horizons that cover the greater Dome C area, East Antarctica, the most extensive IRH data set to date in the region. This data set uses radar surveys collected over the span of 10 years, starting with an airborne international collaboration in 2008 to explore the region, up to the detailed ground-based surveys in support of the European Beyond EPICA – Oldest Ice (BE-OI) project.
Ruth Mottram, Nicolaj Hansen, Christoph Kittel, J. Melchior van Wessem, Cécile Agosta, Charles Amory, Fredrik Boberg, Willem Jan van de Berg, Xavier Fettweis, Alexandra Gossart, Nicole P. M. van Lipzig, Erik van Meijgaard, Andrew Orr, Tony Phillips, Stuart Webster, Sebastian B. Simonsen, and Niels Souverijns
The Cryosphere, 15, 3751–3784, https://doi.org/10.5194/tc-15-3751-2021, https://doi.org/10.5194/tc-15-3751-2021, 2021
Short summary
Short summary
We compare the calculated surface mass budget (SMB) of Antarctica in five different regional climate models. On average ~ 2000 Gt of snow accumulates annually, but different models vary by ~ 10 %, a difference equivalent to ± 0.5 mm of global sea level rise. All models reproduce observed weather, but there are large differences in regional patterns of snowfall, especially in areas with very few observations, giving greater uncertainty in Antarctic mass budget than previously identified.
Louis Le Toumelin, Charles Amory, Vincent Favier, Christoph Kittel, Stefan Hofer, Xavier Fettweis, Hubert Gallée, and Vinay Kayetha
The Cryosphere, 15, 3595–3614, https://doi.org/10.5194/tc-15-3595-2021, https://doi.org/10.5194/tc-15-3595-2021, 2021
Short summary
Short summary
Snow is frequently eroded from the surface by the wind in Adelie Land (Antarctica) and suspended in the lower atmosphere. By performing model simulations, we show firstly that suspended snow layers interact with incoming radiation similarly to a near-surface cloud. Secondly, suspended snow modifies the atmosphere's thermodynamic structure and energy exchanges with the surface. Our results suggest snow transport by the wind should be taken into account in future model studies over the region.
Xavier Fettweis, Stefan Hofer, Roland Séférian, Charles Amory, Alison Delhasse, Sébastien Doutreloup, Christoph Kittel, Charlotte Lang, Joris Van Bever, Florent Veillon, and Peter Irvine
The Cryosphere, 15, 3013–3019, https://doi.org/10.5194/tc-15-3013-2021, https://doi.org/10.5194/tc-15-3013-2021, 2021
Short summary
Short summary
Without any reduction in our greenhouse gas emissions, the Greenland ice sheet surface mass loss can be brought in line with a medium-mitigation emissions scenario by reducing the solar downward flux at the top of the atmosphere by 1.5 %. In addition to reducing global warming, these solar geoengineering measures also dampen the well-known positive melt–albedo feedback over the ice sheet by 6 %. However, only stronger reductions in solar radiation could maintain a stable ice sheet in 2100.
Paolo Colosio, Marco Tedesco, Roberto Ranzi, and Xavier Fettweis
The Cryosphere, 15, 2623–2646, https://doi.org/10.5194/tc-15-2623-2021, https://doi.org/10.5194/tc-15-2623-2021, 2021
Short summary
Short summary
We use a new satellite dataset to study the spatiotemporal evolution of surface melting over Greenland at an enhanced resolution of 3.125 km. Using meteorological data and the MAR model, we observe that a dynamic algorithm can best detect surface melting. We found that the melting season is elongating, the melt extent is increasing and that high-resolution data better describe the spatiotemporal evolution of the melting season, which is crucial to improve estimates of sea level rise.
Charles Amory, Christoph Kittel, Louis Le Toumelin, Cécile Agosta, Alison Delhasse, Vincent Favier, and Xavier Fettweis
Geosci. Model Dev., 14, 3487–3510, https://doi.org/10.5194/gmd-14-3487-2021, https://doi.org/10.5194/gmd-14-3487-2021, 2021
Short summary
Short summary
This paper presents recent developments in the drifting-snow scheme of the regional climate model MAR and its application to simulate drifting snow and the surface mass balance of Adélie Land in East Antarctica. The model is extensively described and evaluated against a multi-year drifting-snow dataset and surface mass balance estimates available in the area. The model sensitivity to input parameters and improvements over a previously published version are also assessed.
Joseph A. MacGregor, Michael Studinger, Emily Arnold, Carlton J. Leuschen, Fernando Rodríguez-Morales, and John D. Paden
The Cryosphere, 15, 2569–2574, https://doi.org/10.5194/tc-15-2569-2021, https://doi.org/10.5194/tc-15-2569-2021, 2021
Short summary
Short summary
We combine multiple recent global glacier datasets and extend one of them (GlaThiDa) to evaluate past performance of radar-sounding surveys of the thickness of Earth's temperate glaciers. An empirical envelope for radar performance as a function of center frequency is determined, its limitations are discussed and its relevance to future radar-sounder survey and system designs is considered.
Christoph Kittel, Charles Amory, Cécile Agosta, Nicolas C. Jourdain, Stefan Hofer, Alison Delhasse, Sébastien Doutreloup, Pierre-Vincent Huot, Charlotte Lang, Thierry Fichefet, and Xavier Fettweis
The Cryosphere, 15, 1215–1236, https://doi.org/10.5194/tc-15-1215-2021, https://doi.org/10.5194/tc-15-1215-2021, 2021
Short summary
Short summary
The future surface mass balance (SMB) of the Antarctic ice sheet (AIS) will influence the ice dynamics and the contribution of the ice sheet to the sea level rise. We investigate the AIS sensitivity to different warmings using physical and statistical downscaling of CMIP5 and CMIP6 models. Our results highlight a contrasting effect between the grounded ice sheet (where the SMB is projected to increase) and ice shelves (where the future SMB depends on the emission scenario).
Martin Ménégoz, Evgenia Valla, Nicolas C. Jourdain, Juliette Blanchet, Julien Beaumet, Bruno Wilhelm, Hubert Gallée, Xavier Fettweis, Samuel Morin, and Sandrine Anquetin
Hydrol. Earth Syst. Sci., 24, 5355–5377, https://doi.org/10.5194/hess-24-5355-2020, https://doi.org/10.5194/hess-24-5355-2020, 2020
Short summary
Short summary
The study investigates precipitation changes in the Alps, using observations and a 7 km resolution climate simulation over 1900–2010. An increase in mean precipitation is found in winter over the Alps, whereas a drying occurred in summer in the surrounding plains. A general increase in the daily annual maximum of precipitation is evidenced (20 to 40 % per century), suggesting an increase in extreme events that is significant only when considering long time series, typically 50 to 80 years.
Kenneth D. Mankoff, Brice Noël, Xavier Fettweis, Andreas P. Ahlstrøm, William Colgan, Ken Kondo, Kirsty Langley, Shin Sugiyama, Dirk van As, and Robert S. Fausto
Earth Syst. Sci. Data, 12, 2811–2841, https://doi.org/10.5194/essd-12-2811-2020, https://doi.org/10.5194/essd-12-2811-2020, 2020
Short summary
Short summary
This work partitions regional climate model (RCM) runoff from the MAR and RACMO RCMs to hydrologic outlets at the ice margin and coast. Temporal resolution is daily from 1959 through 2019. Spatial grid is ~ 100 m, resolving individual streams. In addition to discharge at outlets, we also provide the streams, outlets, and basin geospatial data, as well as a script to query and access the geospatial or time series discharge data from the data files.
Xavier Fettweis, Stefan Hofer, Uta Krebs-Kanzow, Charles Amory, Teruo Aoki, Constantijn J. Berends, Andreas Born, Jason E. Box, Alison Delhasse, Koji Fujita, Paul Gierz, Heiko Goelzer, Edward Hanna, Akihiro Hashimoto, Philippe Huybrechts, Marie-Luise Kapsch, Michalea D. King, Christoph Kittel, Charlotte Lang, Peter L. Langen, Jan T. M. Lenaerts, Glen E. Liston, Gerrit Lohmann, Sebastian H. Mernild, Uwe Mikolajewicz, Kameswarrao Modali, Ruth H. Mottram, Masashi Niwano, Brice Noël, Jonathan C. Ryan, Amy Smith, Jan Streffing, Marco Tedesco, Willem Jan van de Berg, Michiel van den Broeke, Roderik S. W. van de Wal, Leo van Kampenhout, David Wilton, Bert Wouters, Florian Ziemen, and Tobias Zolles
The Cryosphere, 14, 3935–3958, https://doi.org/10.5194/tc-14-3935-2020, https://doi.org/10.5194/tc-14-3935-2020, 2020
Short summary
Short summary
We evaluated simulated Greenland Ice Sheet surface mass balance from 5 kinds of models. While the most complex (but expensive to compute) models remain the best, the faster/simpler models also compare reliably with observations and have biases of the same order as the regional models. Discrepancies in the trend over 2000–2012, however, suggest that large uncertainties remain in the modelled future SMB changes as they are highly impacted by the meltwater runoff biases over the current climate.
Cited articles
Amory, C., Kittel, C., Le Toumelin, L., Agosta, C., Delhasse, A., Favier, V., and Fettweis, X.: Performance of MAR (v3.11) in simulating the drifting-snow climate and surface mass balance of Adélie Land, East Antarctica, Geosci. Model Dev., 14, 3487–3510, https://doi.org/10.5194/gmd-14-3487-2021, 2021.
Arcone, S. A.: Airborne-radar stratigraphy and electrical structure of
temperate firn: Bagley Ice Field, Alaska, U.S.A., J. Glaciol., 48, 317–334, https://doi.org/10.3189/172756502781831412, 2002.
Beaumont, R. T.: Mt. Hood pressure pillow snow gage, J. Appl.
Meteorol., 4, 626–631, https://doi.org/10.1175/1520-0450(1965)004<0626:MHPPSG>2.0.CO;2, 1965.
Benson, C. S.: Glaciological studies on Mount Wrangell, Alaska, 1961,
Arctic, 21, 127–152, 1968.
Benson, C. S.: Ice core drilling on Mt. Wrangell, Alaska, 1982, CRREL Spec.
Rep. 84-34, 61–68, 1984.
Benson, C. S.: Stratigraphic studies in the snow and firn of the Greenland
ice sheet, SIPRE Res. Rep. 70, Revised edition of 1962 report, 1996.
Benson, C. S. and Motyka, R. J.: Glacier-volcano interactions on Mt.
Wrangell, Alaska, Annual Report, 1977–78, 1–25, Geophys. Inst., Univ. of
Alaska, Fairbanks, 1978.
Benson, C. S., Bingham, D. K., and Wharton, G. B.: Glaciological and
volcanological studies at the summit of Mt. Wrangell, Alaska, Int. Assoc.
Sci. Hydrol. Pubk, 104, 95–98, 1975.
Benson, C. S., Motyka, R. J., McNutt, S., Lüthi, M., and Truffer, M.:
Glacial–volcano interactions in the North Crater of Mt. Wrangell, Alaska,
Ann. Glaciol., 45, 48–57, https://doi.org/10.3189/172756407782282462, 2007.
Berger, V., Xu, M., Al-Ibadi, M., Chu, S., Crandall, D., Paden, J., and Fox,
G. C.: Automated ice-bottom tracking of 2D and 3D ice radar imagery using
Viterbi and TRW-S, IEEE J. Sel. Top. Appl., 12, 3272–3285, https://doi.org/10.1109/JSTARS.2019.2930920, 2019.
Bingham, D. K.: Ice motion and heat flow studies on Mt. Wrangell, Alaska,
MS thesis, Univ. of Alaska, Fairbanks, 1967.
CReSIS: Snow radar data, digital media, http://data.cresis.ku.edu/ (last access: 21 October 2022), 2021.
Dietz, A. J., Kuenzer, C., Gessner, U., and Dech, S.: Remote sensing of snow – a review of available methods, Int. J. Remote Sens., 33, 4094–4134, https://doi.org/10.1080/01431161.2011.640964, 2012.
Fettweis, X.: Reconstruction of the 1979–2006 Greenland ice sheet surface mass balance using the regional climate model MAR, The Cryosphere, 1, 21–40, https://doi.org/10.5194/tc-1-21-2007, 2007.
Fettweis, X.: MAR simulation of Alaskan glaciers, digital media, ftp://ftp.climato.be/fettweis/MARv3.12/Alaska/ (last access: 21 October 2022), 2021.
Fettweis, X., Hofer, S., Krebs-Kanzow, U., Amory, C., Aoki, T., Berends, C. J., Born, A., Box, J. E., Delhasse, A., Fujita, K., Gierz, P., Goelzer, H., Hanna, E., Hashimoto, A., Huybrechts, P., Kapsch, M.-L., King, M. D., Kittel, C., Lang, C., Langen, P. L., Lenaerts, J. T. M., Liston, G. E., Lohmann, G., Mernild, S. H., Mikolajewicz, U., Modali, K., Mottram, R. H., Niwano, M., Noël, B., Ryan, J. C., Smith, A., Streffing, J., Tedesco, M., van de Berg, W. J., van den Broeke, M., van de Wal, R. S. W., van Kampenhout, L., Wilton, D., Wouters, B., Ziemen, F., and Zolles, T.: GrSMBMIP: intercomparison of the modelled 1980–2012 surface mass balance over the Greenland Ice Sheet, The Cryosphere, 14, 3935–3958, https://doi.org/10.5194/tc-14-3935-2020, 2020.
Garry, K. C. C. and Guy, M. C.: Radar imaging of glaciovolcanic
stratigraphy, Mount Wrangell caldera, Alaska: interpretation model and
results, J. Geophys. Res., 94, 7237–7249, https://doi.org/10.1029/JB094iB06p07237, 1989.
Gusmeroli, A., Wolken, G. J., and Arendt, A. A.: Helicopter-borne radar
imaging of snow cover on and around glaciers in Alaska, Ann.
Glaciol., 55, 78–88, https://doi.org/10.3189/2014AoG67A029, 2014.
Hill, D. F., Bruhis, N., Calos, S. E., Arendt, A., and Beamer J.: Spatial
and temporal variability of freshwater discharge into the Gulf of Alaska, J.
Geophys. Res.-Oceans, 120, 634–646, https://doi.org/10.1002/2014JC010395, 2015.
Hugonnet, R., McNabb, R., Berthier, E., Menounos, B., Nuth, C., Girod, L.,
Farinotti, D., Huss, M., Dussaillant, I., Brun, F., and Kääb, A.:
Accelerated global glacier mass loss in the early twenty-first century,
Nature, 592, 726–731, https://doi.org/10.1038/s41586-021-03436-z, 2021.
Jeoung, H., Shi, S., and Liu, G.: A Novel approach to validate satellite snowfall retrievals by ground-based point measurements, Remote Sens., 14, 434, https://doi.org/10.3390/rs14030434, 2022.
Johnson, A. J., Larsen, C. F., Murphy, N., Arendt, A. A., and Zirnheld, S. L.: Mass
balance in the Glacier Bay Area of Alaska, USA,
and British Columbia, Canada, 1995–2011, using airborne laser altimetry,
J. Glaciol., 59, 216, https://doi.org/10.3189/2013JoG12J101, 2013.
Kanamori, S., Okura, Y., and Yoshikawa, K.: Snow pit studies and radio-echo
soundings on Mt. McKinley 2004, B. Glaciol. Res., 22,
89–97, 2005.
Kanamori, S., Benson, C. S., Truffer, M., and Matoba, S.: Seasonality of snow
accumulation at Mount Wrangell, Alaska, USA, J. Glaciol., 54, 273–278, https://doi.org/10.3189/002214308784886081, 2008.
Langley, K., Hamran, S. E., Høgda, K. A., Storvold, R., Brandt, O.,
Kohler, J., and Hagen., J. O.: From glacier facies to SAR backscatter zones
via GPR, IEEE TGRS, 46, 2506–2516, 2008.
Largeron, C., Dumont, M., Morin, S., Boone, A., Lafaysse, M., Metref, S.,
Cosme, E., Jonas, T., Winstral, A., and Margulis S. A.: Toward snow cover
estimation in mountainous areas using modern data assimilation methods: a
review, Front. Earth Sci. 8, 1–21, https://doi.org/10.3389/feart.2020.00325, 2020.
Li, J., Rodriguez-Morales, F., Arnold, E., Leuschen, C., Paden, J., Shang,
J., Gomez-Garcia, D., and Larsen, C.: Airborne snow measurements over Alaska
mountains and glaciers with a compact FMCW radar, Proc. IEEE Int. Geosci.
Remote Sens. Symp., Yokohama, Japan, 3966–3969, https://doi.org/10.1109/IGARSS.2019.8900034, 2019.
Lindsay, C., Zhu, J., Miller, A. E., Kirchner, P., and Wilson, T. L.:
Deriving snow cover metrics for Alaska from MODIS, Remote Sens., 7,
12961–12985, https://doi.org/10.3390/rs71012961, 2015.
Looyenga, H.: Dielectric constants of homogeneous mixture, Molec.
Phys., 9, 501–511, https://doi.org/10.1080/00268976500100671, 1965.
Matoba, S., Shimbori, K., and Shiraiwa, T.: Alpine ice-core drilling in the
North Pacific region, Ann. Glaciol., 55, 83–87, https://doi.org/10.3189/2014AoG68A020, 2014.
McGrath, D., Sass, L., O'Neel, S., Arendt, A., Wolken, G., Gusmeroli, A.,
Kienholz, C., and McNeil, C.: End-of-winter snow depth variability on
glaciers in Alaska, J. Geophys. Res.-Earth Surf., 120, 1530–1550, https://doi.org/10.1002/2015JF003539, 2015.
Motyka, R. J.: Increases and fluctuations in thermal activity at Mount
Wrangell, Alaska, PhD thesis, Univ. of Alaska, Fairbanks, 1983.
Neal, E. G., Hood, E., and Smikrud, K.: Contribution of glacier run-off
to freshwater discharge into the Gulf of Alaska, Geophys. Res. Lett., 37,
L06404, https://doi.org/10.1029/2010GL042385, 2010.
Paden, J., Li, J., Leuschen, C., Rodriguez-Morales, F., and Hale, R.: IceBridge Snow Radar L1B Geolocated Radar Echo Strength Profiles, Version 2, Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center [data set], https://doi.org/10.5067/FAZTWP500V70, 2014.
Panzer, B., Gomez-Garcia, D., Leuschen, C., Paden, J., Rodriguez-Morales,
F., Patel, A., Markus, T., Holt, B., and Gogineni, S.: An ultra-wideband,
microwave radar for measuring snow thickness on sea ice and mapping
near-surface internal layers in polar firn, J. Glaciol., 59,
244–254, https://doi.org/10.3189/2013JoG12J128, 2013.
Partington, K.: Discrimination of glacier facies using multi-temporal SAR
data, J. Glaciol., 44, 42–53, https://doi.org/10.3189/S0022143000002331, 1998.
Porter, S. E., Mosley-Thompson, E., and Thompson, L. G.: Ice core δ18O record linked to Western Arctic sea ice variability, J. Geophys. Res.-Atmos.,
124, 10784–10801, https://doi.org/10.1029/2019JD031023, 2019.
Ramage, J. M., Isacks, B. L., and Miller, M. M.: Radar glacier zones in
southeast Alaska, U.S.A.: field and satellite observations, J. Glaciol.,
46, 287–296, https://doi.org/10.3189/172756500781832828, 2000.
Robin, G. Q., Evans S., and Bailey, J. T.: Interpretation of radio echo sounding in polar ice sheets, Philos. T. R. Soc., Ser. A, 265, 437–505, 1969.
Rodríguez-Morales, F., Li, J., Gomez-García, D., Shang, J.,
Arnold, E., Leuschen, C., Larsen, C. F., Shepherd, A., Hvidegaard, S. M.,
and Forsber, R.: A compact, reconfigurable, multi-UWB radar for snow
thickness evaluation and altimetry: development and field trials, IEEE
JSTARS, 14, 6755–6765, https://doi.org/10.1109/JSTARS.2021.3092313, 2021a.
Rodriguez-Morales, F., Occhiogrosso, V., and Arnold, E.: Multichannel UWB
microwave radar front-end for fine-resolution measurements of terrestrial
snow cover, Proc. 2021 Int. Conf. Radar Ant. Microw Electron. Telecomm.,
120–124, https://doi.org/10.1109/ICRAMET53537.2021.9650490, 2021b.
Shanley, C. S., and Albert, D. M.: Climate change sensitivity index for
pacific salmon habitat in Southeast Alaska, PLoS ONE, 9, e104799, https://doi.org/10.1371/journal.pone.0104799,
2014.
Shiraiwa, T., Kanamori, S., Benson C. S., Solie D., and Muravyev, Y. D.: Shallow ice-core drilling at Mount Wrangell, Alaska, Bull.
Glaciol. Res., 21, 71–78, 2004.
Stuefer, S. L., Kane, D. L., and Dean, K. M.: Snow water equivalent
measurements in remote Arctic Alaska watersheds, Water Resour. Res.,
56, e2019WR025621, https://doi.org/10.1029/2019WR025621, 2020.
Tiuri, M., Sihvola, A., Nyfors, E., and Hallikaiken, M.: The complex
dielectric constant of snow at microwave frequencies, IEEE J.
Ocean. Eng., 9, 377–382, https://doi.org/10.1109/JOE.1984.1145645, 1984.
Urmann, D.: Decadal scale climate variability during the last millennium as
recorded by the Bona Churchill and Quelccaya Ice Cores, Dissertation, Ohio
State University, 2009.
WCRP Global Sea Level Budget Group: Global sea-level budget 1993–present, Earth Syst. Sci. Data, 10, 1551–1590, https://doi.org/10.5194/essd-10-1551-2018, 2018.
Winstral, A., Elder, K., and Davis, R. E.: Spatial snow modeling of
wind-redistributed snow using terrain-based parameters, J. Hydrometeorol.,
3, 524–538, https://doi.org/10.1175/1525-7541(2002)003<0524:SSMOWR>2.0.CO;2, 2002.
Yan, J. B., Gogineni, S., Rodriguez-Morales, F., Gomez-Garcia, D., Paden J.,
Li, J., Leuschen, C. J., Braaten, D., Richter-Menge, J., Farrell, S. L.,
Brozena, J., and Hale, R.: Airborne measurements of snow thickness: using
ultrawide-band frequency-modulated-continuous-wave radars, IEEE Geoscience
and Remote Sensing Magazine, 5, 57–76, https://doi.org/10.1109/MGRS.2017.2663325, 2017.
Yasunari, T. J., Shiraiwa, T., Kanamori, S., Fujii, Y., Igarashi, M.,
Yamazaki, K., Benson, C. S., and Hondoh, T.: Intra-annual variations in
atmospheric dust and tritium in the North Pacific region detected from an
ice core from Mount Wrangell, Alaska. J. Geophys. Res., 112, D10208, https://doi.org/10.1029/2006JD008121, 2007.
Zagorodnov, V., Thompson, L. G., Ginot, P., and Mikhalenko, V.: Intermediate-depth ice coring of high-altitude and polar glaciers with a lightweight drilling system, J. Glaciol., 51, 491–501, 2005.
Short summary
Alaskan glaciers' loss of ice mass contributes significantly to ocean surface rise. It is important to know how deeply and how much snow accumulates on these glaciers to comprehend and analyze the glacial mass loss process. We reported the observed seasonal snow depth distribution from our radar data taken in Alaska in 2018 and 2021, developed a method to estimate the annual snow accumulation rate at Mt. Wrangell caldera, and identified transition zones from wet-snow zones to ablation zones.
Alaskan glaciers' loss of ice mass contributes significantly to ocean surface rise. It is...
