Articles | Volume 20, issue 9
https://doi.org/10.5194/tc-20-5247-2026
© Author(s) 2026. 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-20-5247-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
21 Sep 2026
Research article |
| 21 Sep 2026
| 21 Sep 2026
Temporal evolution of the Petermann Ice Shelf estuary constrained by satellite remote sensing observations
Michela Savignano
CORRESPONDING AUTHOR
Department of Geography, University of Colorado Boulder, Boulder, 80309, USA
Cooperative Institute for Research in Environmental Sciences (CIRES), University of Colorado Boulder, Boulder, 80309, USA
Alison F. Banwell
Cooperative Institute for Research in Environmental Sciences (CIRES), University of Colorado Boulder, Boulder, 80309, USA
Centre for Polar Observation and Modelling (CPOM), School of Geography and Natural Sciences, Northumbria University, Newcastle Upon Tyne, UK
Waleed Abdalati
Department of Geography, University of Colorado Boulder, Boulder, 80309, USA
Cooperative Institute for Research in Environmental Sciences (CIRES), University of Colorado Boulder, Boulder, 80309, USA
Robin E. Bell
Lamont Doherty Earth Observatory (LDEO) of Columbia University, Palisades, 10964, USA
Alexandra Boghosian
Lamont Doherty Earth Observatory (LDEO) of Columbia University, Palisades, 10964, USA
W. Roger Buck
Lamont Doherty Earth Observatory (LDEO) of Columbia University, Palisades, 10964, USA
Department of Earth and Environmental Sciences, Columbia University, New York, NY 10025, USA
Sarah E. Esenther
Department of Earth, Planetary, and Environmental Sciences and Institute at Brown for Environment and Society, Brown University, Providence RI 02912
Emily Glazer
Lamont Doherty Earth Observatory (LDEO) of Columbia University, Palisades, 10964, USA
Department of Earth and Environmental Sciences, Columbia University, New York, NY 10025, USA
Adam L. LeWinter
US Army Corps of Engineers Cold Regions Research and Engineering Laboratory, Hanover, NH 03755 USA
Laurence C. Smith
Department of Earth, Planetary, and Environmental Sciences and Institute at Brown for Environment and Society, Brown University, Providence RI 02912
Leigh A. Stearns
Department of Earth and Environmental Science, University of Pennsylvania, Philadelphia, PA 19104 USA
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Emily C. Glazer and Kirsty J. Tinto
The Cryosphere, 20, 5131–5156, https://doi.org/10.5194/tc-20-5131-2026, https://doi.org/10.5194/tc-20-5131-2026, 2026
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Surface meltwater ponds on Antarctic ice shelves can trigger ice break-up. Using satellite records of observed ponds along with temperatures, snowfall rates, and melt rates from climate models, we show that ponding occurs more widely than theory predicts. Our calibrated method identifies vulnerable areas more accurately and suggests pond coverage could be over double what standard methods predict by 2100, highlighting the need for careful evaluation of climate thresholds used to predict ponding.
Seebany Datta-Barua, Alison F. Banwell, Jonah Wilkes, Alec Weedman, Roohollah Parvizi, Christian Allen, Aiden Verdin, Hiroki Kawai, Logan Garcia, and Kristine M. Larson
EGUsphere, https://doi.org/10.5194/egusphere-2026-5057, https://doi.org/10.5194/egusphere-2026-5057, 2026
This preprint is open for discussion and under review for Geoscientific Instrumentation, Methods and Data Systems (GI).
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We tested reflected Global Navigation Satellite System (GNSS) signals as a way to monitor glacier surfaces using the Antarctic ice shelf near McMurdo Station during the 2023–24 austral summer. We collected GNSS, lidar, and camera data from: snow-covered ice near Phoenix airfield, and a mixed surface of bare ice and snow-covered ice at the former Pegasus airfield. The directly-reflected GNSS signal was too weak to extract surface conditions. GNSS interferometry data do differ between the sites.
Emily Glen, Alison F. Banwell, Katie E. Miles, Amber A. Leeson, Rebecca L. Dell, Malcolm McMillan, and Jennifer Maddalena
The Cryosphere, 20, 4345–4365, https://doi.org/10.5194/tc-20-4345-2026, https://doi.org/10.5194/tc-20-4345-2026, 2026
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Using satellite imagery and machine learning, we created the first Greenland-wide dataset of slush (waterlogged snow) from 2016 to 2024. Slush was widespread and varied strongly between years and across Greenland, becoming most extensive during high melt seasons. It was most common where melting was greater and snow had less capacity to store water. These findings show that slush should be included in models of future melting and sea-level rise.
Kevin Shionalyn, Ginny Catania, Daniel T. Trugman, Michael G. Shahin, Leigh A. Stearns, and Denis Felikson
The Cryosphere, 20, 1725–1744, https://doi.org/10.5194/tc-20-1725-2026, https://doi.org/10.5194/tc-20-1725-2026, 2026
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The ocean-facing front of a glacier changes with the seasons. We know this cycle is controlled by the shape and speed of the glacier as well as by the climate, but we do not have a full understanding of these processes. Our study uses 20 years of data and a machine learning model to predict this pattern and identifies which factors matter most. We find that while several factors influence the seasonal cycle, the shape of the glacier plays a key role in how much a glacier changes annually.
Emily Glen, Amber Leeson, Alison F. Banwell, Jennifer Maddalena, Diarmuid Corr, Olivia Atkins, Brice Noël, and Malcolm McMillan
The Cryosphere, 19, 1047–1066, https://doi.org/10.5194/tc-19-1047-2025, https://doi.org/10.5194/tc-19-1047-2025, 2025
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We compare surface meltwater features from optical satellite imagery in the Russell–Leverett glacier catchment during high (2019) and low (2018) melt years. In the high melt year, features appear at higher elevations, meltwater systems are more connected, small lakes are more frequent, and slush is more widespread. These findings provide insights into how a warming climate, where high melt years become common, could alter meltwater distribution and dynamics on the Greenland Ice Sheet.
Derek J. Pickell, Robert L. Hawley, and Adam LeWinter
The Cryosphere, 19, 1013–1029, https://doi.org/10.5194/tc-19-1013-2025, https://doi.org/10.5194/tc-19-1013-2025, 2025
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We use a low-cost, low-power GNSS network to measure surface accumulation in Greenland's interior using the interferometric reflectometry technique. Additionally, we extend this method to also estimate centimeter- to meter-scale surface roughness. Our results closely align with a validation record and highlight a period of unusually high accumulation from late 2022 to 2023, along with seasonal variations in surface roughness.
Sonam F. Sherpa, Laurence C. Smith, Bo Wang, and Cassie Stuurman
EGUsphere, https://doi.org/10.5194/egusphere-2025-133, https://doi.org/10.5194/egusphere-2025-133, 2025
Preprint archived
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As the climate warms, glaciers in the Himalayas are melting and retreating, creating new lakes that are often held back by ice or loose rock. These lakes can suddenly burst, causing devastating floods. On August 16, 2024, such a flood occurred unexpectedly in Nepal's Bhotekoshi River Valley, near Mount Everest. We highlight how modern technologies can play a crucial role in detecting potential dangers and helping communities prepare for risks in a changing climate.
W. Roger Buck
The Cryosphere, 18, 4165–4176, https://doi.org/10.5194/tc-18-4165-2024, https://doi.org/10.5194/tc-18-4165-2024, 2024
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Standard theory predicts that the edge of an ice shelf should bend downward. Satellite observations show that the edges of many ice shelves bend upward. A new theory for ice shelf bending is developed that, for the first time, includes the kind of vertical variations in ice flow properties expected for ice shelves. Upward bending of shelf edges is predicted as long as the ice surface is very cold and the ice flow properties depend strongly on temperature.
Naomi E. Ochwat, Ted A. Scambos, Alison F. Banwell, Robert S. Anderson, Michelle L. Maclennan, Ghislain Picard, Julia A. Shates, Sebastian Marinsek, Liliana Margonari, Martin Truffer, and Erin C. Pettit
The Cryosphere, 18, 1709–1731, https://doi.org/10.5194/tc-18-1709-2024, https://doi.org/10.5194/tc-18-1709-2024, 2024
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On the Antarctic Peninsula, there is a small bay that had sea ice fastened to the shoreline (
fast ice) for over a decade. The fast ice stabilized the glaciers that fed into the ocean. In January 2022, the fast ice broke away. Using satellite data we found that this was because of low sea ice concentrations and a high long-period ocean wave swell. We find that the glaciers have responded to this event by thinning, speeding up, and retreating by breaking off lots of icebergs at remarkable rates.
Prateek Gantayat, Alison F. Banwell, Amber A. Leeson, James M. Lea, Dorthe Petersen, Noel Gourmelen, and Xavier Fettweis
Geosci. Model Dev., 16, 5803–5823, https://doi.org/10.5194/gmd-16-5803-2023, https://doi.org/10.5194/gmd-16-5803-2023, 2023
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We developed a new supraglacial hydrology model for the Greenland Ice Sheet. This model simulates surface meltwater routing, meltwater drainage, supraglacial lake (SGL) overflow, and formation of lake ice. The model was able to reproduce 80 % of observed lake locations and provides a good match between the observed and modelled temporal evolution of SGLs.
Sarah E. Esenther, Laurence C. Smith, Adam LeWinter, Lincoln H. Pitcher, Brandon T. Overstreet, Aaron Kehl, Cuyler Onclin, Seth Goldstein, and Jonathan C. Ryan
Geosci. Instrum. Method. Data Syst., 12, 215–230, https://doi.org/10.5194/gi-12-215-2023, https://doi.org/10.5194/gi-12-215-2023, 2023
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Meltwater runoff estimates from the Greenland ice sheet contain uncertainty. To better understand ice sheet hydrology, we installed a weather station and river stage sensors along three proglacial rivers in a cold-bedded area of NW Greenland without firn, crevasse, or moulin influence. The first 3 years (2019–2021) of observations have given us a first look at the seasonal and annual weather and hydrological patterns of this understudied region.
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
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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.
Ghislain Picard, Marion Leduc-Leballeur, Alison F. Banwell, Ludovic Brucker, and Giovanni Macelloni
The Cryosphere, 16, 5061–5083, https://doi.org/10.5194/tc-16-5061-2022, https://doi.org/10.5194/tc-16-5061-2022, 2022
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Using a snowpack radiative transfer model, we investigate in which conditions meltwater can be detected from passive microwave satellite observations from 1.4 to 37 GHz. In particular, we determine the minimum detectable liquid water content, the maximum depth of detection of a buried wet snow layer and the risk of false alarm due to supraglacial lakes. These results provide information for the developers of new, more advanced satellite melt products and for the users of the existing products.
Rohi Muthyala, Åsa K. Rennermalm, Sasha Z. Leidman, Matthew G. Cooper, Sarah W. Cooley, Laurence C. Smith, and Dirk van As
The Cryosphere, 16, 2245–2263, https://doi.org/10.5194/tc-16-2245-2022, https://doi.org/10.5194/tc-16-2245-2022, 2022
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In situ measurements of meltwater discharge through supraglacial stream networks are rare. The unprecedentedly long record of discharge captures diurnal and seasonal variability. Two major findings are (1) a change in the timing of peak discharge through the melt season that could impact meltwater delivery in the subglacial system and (2) though the primary driver of stream discharge is shortwave radiation, longwave radiation and turbulent heat fluxes play a major role during high-melt episodes.
Edward H. Bair, Jeff Dozier, Charles Stern, Adam LeWinter, Karl Rittger, Alexandria Savagian, Timbo Stillinger, and Robert E. Davis
The Cryosphere, 16, 1765–1778, https://doi.org/10.5194/tc-16-1765-2022, https://doi.org/10.5194/tc-16-1765-2022, 2022
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Understanding how snow and ice reflect solar radiation (albedo) is important for global climate. Using high-resolution topography, darkening from surface roughness (apparent albedo) is separated from darkening by the composition of the snow (intrinsic albedo). Intrinsic albedo is usually greater than apparent albedo, especially during melt. Such high-resolution topography is often not available; thus the use of a shade component when modeling mixtures is advised.
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
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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.
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Short summary
Surface rivers can transport meltwater from floating ice-shelves into the ocean, limiting ponding. However, if a river channel deepens to sea level, seawater can flow up into it and form an ice-shelf estuary. This adds load to the ice shelf and increases stresses that weaken the ice. Using high-resolution satellite imagery, we develop a new way to measure how quickly these rivers deepen, which we use to constrain the timing of Petermann Ice Shelf’s estuary formation over multiple melt seasons.
Surface rivers can transport meltwater from floating ice-shelves into the ocean, limiting...
