Articles | Volume 16, issue 10
https://doi.org/10.5194/tc-16-4553-2022
© Author(s) 2022. 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-16-4553-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Surface melt on the Shackleton Ice Shelf, East Antarctica (2003–2021)
Dominic Saunderson
CORRESPONDING AUTHOR
Securing Antarctica's Environmental Future, School of Earth,
Atmosphere and Environment, Monash University, Clayton, VIC 3800,
Australia
Andrew Mackintosh
Securing Antarctica's Environmental Future, School of Earth,
Atmosphere and Environment, Monash University, Clayton, VIC 3800,
Australia
Felicity McCormack
Securing Antarctica's Environmental Future, School of Earth,
Atmosphere and Environment, Monash University, Clayton, VIC 3800,
Australia
Richard Selwyn Jones
Securing Antarctica's Environmental Future, School of Earth,
Atmosphere and Environment, Monash University, Clayton, VIC 3800,
Australia
Ghislain Picard
Institut des Géosciences de l'Environnement (IGE), UMR 5001, Université Grenoble Alpes, CNRS, Grenoble, France
Geological Survey of Denmark and Greenland (GEUS), 1350
Copenhagen, Denmark
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Lawrence A. Bird, Vitaliy Ogarko, Laurent Ailleres, Lachlan Grose, Jérémie Giraud, Felicity S. McCormack, David E. Gwyther, Jason L. Roberts, Richard S. Jones, and Andrew N. Mackintosh
The Cryosphere, 19, 3355–3380, https://doi.org/10.5194/tc-19-3355-2025, https://doi.org/10.5194/tc-19-3355-2025, 2025
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The terrain of the seafloor has important controls on the access of warm water below floating ice shelves around Antarctica. Here, we present an open-source method to infer what the seafloor looks like around the Antarctic continent and within these ice shelf cavities, using measurements of the Earth's gravitational field. We present an improved seafloor map for the Vincennes Bay region in East Antarctica and assess its impact on ice melt rates.
Adrien Ooms, Mathieu Casado, Ghislain Picard, Laurent Arnaud, Maria Hörhold, Andrea Spolaor, Rita Traversi, Joel Savarino, Patrick Ginot, Pete Akers, Birthe Twarloh, and Valérie Masson-Delmotte
EGUsphere, https://doi.org/10.5194/egusphere-2025-3259, https://doi.org/10.5194/egusphere-2025-3259, 2025
This preprint is open for discussion and under review for The Cryosphere (TC).
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This work presents a new approach to the estimation of accumulation rates at Concordia Station, East-Antarctica, for the last 20 years, from a new data set of chemical tracers and snow micro-scale properties measured in a snow trench. Multi-annual and meter to decameter scale variability of accumulation rates are compared again in-situ measurements of surface laser scanner and stake farm, with very good agreement. This further constrains SMB estimation for Antarctica at high temporal resolution.
Levan G. Tielidze, Andrew N. Mackintosh, and Weilin Yang
The Cryosphere, 19, 2677–2694, https://doi.org/10.5194/tc-19-2677-2025, https://doi.org/10.5194/tc-19-2677-2025, 2025
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Heard Island is a UNESCO World Heritage site due to its outstanding physical and biological features which are being affected by significant ongoing climatic changes. As one of the only sub-Antarctic islands mostly free of introduced species, its largely undisturbed ecosystems are at risk from the impact of glacier retreat. This glacier inventory will help in designing effective conservation strategies and managing protected areas to ensure the preservation of the biodiversity they support.
Janina Güntzel, Juliane Müller, Ralf Tiedemann, Gesine Mollenhauer, Lester Lembke-Jene, Estella Weigelt, Lasse Schopen, Niklas Wesch, Laura Kattein, Andrew N. Mackintosh, and Johann P. Klages
EGUsphere, https://doi.org/10.5194/egusphere-2025-2515, https://doi.org/10.5194/egusphere-2025-2515, 2025
This preprint is open for discussion and under review for The Cryosphere (TC).
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Combined multi-proxy sediment core analyses reveal the deglaciation along the Mac. Robertson Shelf, a yet insufficiently studied sector of the East Antarctic margin. Grounding line extent towards the continental shelf break prior to ~12.5 cal. ka BP and subsequent episodic mid-shelf retreat towards the early Holocene prevented Antarctic Bottom Water formation in its current form, hence suggesting either its absence or an alternative pre-Holocene formation mechanism.
Titouan Tcheng, Elise Fourré, Christophe Leroy-Dos-Santos, Frédéric Parrenin, Emmanuel Le Meur, Frédéric Prié, Olivier Jossoud, Roxanne Jacob, Bénédicte Minster, Olivier Magand, Cécile Agosta, Niels Dutrievoz, Vincent Favier, Léa Baubant, Coralie Lassalle-Bernard, Mathieu Casado, Martin Werner, Alexandre Cauquoin, Laurent Arnaud, Bruno Jourdain, Ghislain Picard, Marie Bouchet, and Amaëlle Landais
EGUsphere, https://doi.org/10.5194/egusphere-2025-2863, https://doi.org/10.5194/egusphere-2025-2863, 2025
This preprint is open for discussion and under review for The Cryosphere (TC).
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Studying Antarctic ice cores is crucial to assess past climate changes, as they hold historical climate data. This study examines multiple ice cores from three sites in coastal Adélie Land to see if combining cores improves data interpretability. It does at two sites, but at a third, wind-driven snow layer mixing limited benefits. We show that using multiple ice cores from one location can better uncover climate history, especially in areas with less wind disturbance.
Jessica M. A. Macha, Andrew N. Mackintosh, Felicity S. McCormack, Benjamin J. Henley, Helen V. McGregor, Christiaan T. van Dalum, and Ariaan Purich
The Cryosphere, 19, 1915–1935, https://doi.org/10.5194/tc-19-1915-2025, https://doi.org/10.5194/tc-19-1915-2025, 2025
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Extreme El Niño–Southern Oscillation (ENSO) events have global impacts, but their Antarctic impacts are poorly understood. Examining Antarctic snow accumulation anomalies of past observed extreme ENSO events, we show that accumulation changes differ between events and are insignificant during most events. Significant changes occur during 2015/16 and in Enderby Land during all extreme El Niños. Historical data limit conclusions, but future greater extremes could cause Antarctic accumulation changes.
Florent Domine, Mireille Quémener, Ludovick Bégin, Benjamin Bouchard, Valérie Dionne, Sébastien Jerczynski, Raphaël Larouche, Félix Lévesque-Desrosiers, Simon-Olivier Philibert, Marc-André Vigneault, Ghislain Picard, and Daniel C. Côté
The Cryosphere, 19, 1757–1774, https://doi.org/10.5194/tc-19-1757-2025, https://doi.org/10.5194/tc-19-1757-2025, 2025
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Shrubs buried in snow absorb solar radiation and reduce irradiance in the snowpack. This decreases photochemical reaction rates and emissions to the atmosphere. By monitoring irradiance in snowpacks with and without shrubs, we conclude that shrubs absorb solar radiation as much as 140 ppb of soot and reduce irradiance by a factor of 2. Shrub expansion in the Arctic may therefore affect tropospheric composition during the snow season with climatic effects.
Léa Elise Bonnefoy, Catherine Prigent, Ghislain Picard, Clément Soriot, Alice Le Gall, Lise Kilic, and Carlos Jimenez
EGUsphere, https://doi.org/10.5194/egusphere-2024-3972, https://doi.org/10.5194/egusphere-2024-3972, 2025
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Microwave radiometry senses the thermal emission from a target, whereas its active counterpart, radar, sends a signal to the target and measures the signal reflected back. We simultaneously model radar and radiometry over the East Antarctic ice sheet, which we propose as an analog for icy moons: we can reproduce most data with a unique model. Saturn's moons' radar brightness cannot be reproduced and must be caused by processes unaccounted for in the model and less active in the Antarctic.
Marion Leduc-Leballeur, Ghislain Picard, Pierre Zeiger, and Giovanni Macelloni
EGUsphere, https://doi.org/10.5194/egusphere-2025-732, https://doi.org/10.5194/egusphere-2025-732, 2025
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This study presents a quantitative and synthetic classification of the snowpack in 10 dry-wet status by aggregating separate binary indicators derived from satellite observations. The classification follows the expected evolution of the melt season: night refreezing is frequent at the onset, sustained melting is observed during the summer peak, and remnant liquid water at depth occurs at the end. This dataset improves the knowledge of melt processes using passive microwave remote sensing.
Lawrence A. Bird, Felicity S. McCormack, Johanna Beckmann, Richard S. Jones, and Andrew N. Mackintosh
The Cryosphere, 19, 955–973, https://doi.org/10.5194/tc-19-955-2025, https://doi.org/10.5194/tc-19-955-2025, 2025
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Vanderford Glacier is the fastest-retreating glacier in East Antarctica and may have important implications for future ice loss from the Aurora Subglacial Basin. Our ice sheet model simulations suggest that grounding line retreat is driven by sub-ice-shelf basal melting, in which warm ocean waters melt ice close to the grounding line. We show that current estimates of basal melt are likely too low, highlighting the need for improved estimates and direct measurements of basal melt in the region.
Inès Ollivier, Hans Christian Steen-Larsen, Barbara Stenni, Laurent Arnaud, Mathieu Casado, Alexandre Cauquoin, Giuliano Dreossi, Christophe Genthon, Bénédicte Minster, Ghislain Picard, Martin Werner, and Amaëlle Landais
The Cryosphere, 19, 173–200, https://doi.org/10.5194/tc-19-173-2025, https://doi.org/10.5194/tc-19-173-2025, 2025
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The role of post-depositional processes taking place at the ice sheet's surface on the water stable isotope signal measured in polar ice cores is not fully understood. Using field observations and modelling results, we show that the original precipitation isotopic signal at Dome C, East Antarctica, is modified by post-depositional processes and provide the first quantitative estimation of their mean impact on the isotopic signal observed in the snow.
Ghislain Picard and Quentin Libois
Geosci. Model Dev., 17, 8927–8953, https://doi.org/10.5194/gmd-17-8927-2024, https://doi.org/10.5194/gmd-17-8927-2024, 2024
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The Two-streAm Radiative TransfEr in Snow (TARTES) is a radiative transfer model to compute snow albedo in the solar domain and the profiles of light and energy absorption in a multi-layered snowpack whose physical properties are user defined. It uniquely considers snow grain shape flexibly, based on recent insights showing that snow does not behave as a collection of ice spheres but instead as a random medium. TARTES is user-friendly yet performs comparably to more complex models.
Cari Rand, Richard S. Jones, Andrew N. Mackintosh, Brent Goehring, and Kat Lilly
EGUsphere, https://doi.org/10.5194/egusphere-2024-2674, https://doi.org/10.5194/egusphere-2024-2674, 2024
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In this study, we determine how recently samples from a mountain in East Antarctica were last covered by the East Antarctic ice sheet. By examining concentrations of carbon-14 in rock samples, we determined that all but the summit of the mountain was buried under glacial ice within the last 15 thousand years. Other methods of estimating past ice thicknesses are not sensitive enough to capture ice cover this recent, so we were previously unaware that ice at this site was thicker at this time.
Melody Sandells, Nick Rutter, Kirsty Wivell, Richard Essery, Stuart Fox, Chawn Harlow, Ghislain Picard, Alexandre Roy, Alain Royer, and Peter Toose
The Cryosphere, 18, 3971–3990, https://doi.org/10.5194/tc-18-3971-2024, https://doi.org/10.5194/tc-18-3971-2024, 2024
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Satellite microwave observations are used for weather forecasting. In Arctic regions this is complicated by natural emission from snow. By simulating airborne observations from in situ measurements of snow, this study shows how snow properties affect the signal within the atmosphere. Fresh snowfall between flights changed airborne measurements. Good knowledge of snow layering and structure can be used to account for the effects of snow and could unlock these data to improve forecasts.
Sara Arioli, Ghislain Picard, Laurent Arnaud, Simon Gascoin, Esteban Alonso-González, Marine Poizat, and Mark Irvine
Earth Syst. Sci. Data, 16, 3913–3934, https://doi.org/10.5194/essd-16-3913-2024, https://doi.org/10.5194/essd-16-3913-2024, 2024
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High-accuracy precision maps of the surface temperature of snow were acquired with an uncooled thermal-infrared camera during winter 2021–2022 and spring 2023. The accuracy – i.e., mean absolute error – improved from 1.28 K to 0.67 K between the seasons thanks to an improved camera setup and temperature stabilization. The dataset represents a major advance in the validation of satellite measurements and physical snow models over a complex topography.
Romilly Harris Stuart, Amaëlle Landais, Laurent Arnaud, Christo Buizert, Emilie Capron, Marie Dumont, Quentin Libois, Robert Mulvaney, Anaïs Orsi, Ghislain Picard, Frédéric Prié, Jeffrey Severinghaus, Barbara Stenni, and Patricia Martinerie
The Cryosphere, 18, 3741–3763, https://doi.org/10.5194/tc-18-3741-2024, https://doi.org/10.5194/tc-18-3741-2024, 2024
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Ice core δO2/N2 records are useful dating tools due to their local insolation pacing. A precise understanding of the physical mechanism driving this relationship, however, remain ambiguous. By compiling data from 15 polar sites, we find a strong dependence of mean δO2/N2 on accumulation rate and temperature in addition to the well-documented insolation dependence. Snowpack modelling is used to investigate which physical properties drive the mechanistic dependence on these local parameters.
Julien Meloche, Melody Sandells, Henning Löwe, Nick Rutter, Richard Essery, Ghislain Picard, Randall K. Scharien, Alexandre Langlois, Matthias Jaggi, Josh King, Peter Toose, Jérôme Bouffard, Alessandro Di Bella, and Michele Scagliola
EGUsphere, https://doi.org/10.5194/egusphere-2024-1583, https://doi.org/10.5194/egusphere-2024-1583, 2024
Preprint archived
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Sea ice thickness is essential for climate studies. Radar altimetry has provided sea ice thickness measurement, but uncertainty arises from interaction of the signal with the snow cover. Therefore, modelling the signal interaction with the snow is necessary to improve retrieval. A radar model was used to simulate the radar signal from the snow-covered sea ice. This work paved the way to improved physical algorithm to retrieve snow depth and sea ice thickness for radar altimeter missions.
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.
Justin Murfitt, Claude Duguay, Ghislain Picard, and Juha Lemmetyinen
The Cryosphere, 18, 869–888, https://doi.org/10.5194/tc-18-869-2024, https://doi.org/10.5194/tc-18-869-2024, 2024
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This research focuses on the interaction between microwave signals and lake ice under wet conditions. Field data collected for Lake Oulujärvi in Finland were used to model backscatter under different conditions. The results of the modelling likely indicate that a combination of increased water content and roughness of different interfaces caused backscatter to increase. These results could help to identify areas where lake ice is unsafe for winter transportation.
Claudio Stefanini, Giovanni Macelloni, Marion Leduc-Leballeur, Vincent Favier, Benjamin Pohl, and Ghislain Picard
The Cryosphere, 18, 593–608, https://doi.org/10.5194/tc-18-593-2024, https://doi.org/10.5194/tc-18-593-2024, 2024
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Local and large-scale meteorological conditions have been considered in order to explain some peculiar changes of snow grains on the East Antarctic Plateau from 2000 to 2022, by using remote sensing observations and reanalysis. We identified some extreme grain size events on the highest ice divide, resulting from a combination of conditions of low wind speed and low temperature. Moreover, the beginning of seasonal grain growth has been linked to the occurrence of atmospheric rivers.
Jean Emmanuel Sicart, Victor Ramseyer, Ghislain Picard, Laurent Arnaud, Catherine Coulaud, Guilhem Freche, Damien Soubeyrand, Yves Lejeune, Marie Dumont, Isabelle Gouttevin, Erwan Le Gac, Frédéric Berger, Jean-Matthieu Monnet, Laurent Borgniet, Éric Mermin, Nick Rutter, Clare Webster, and Richard Essery
Earth Syst. Sci. Data, 15, 5121–5133, https://doi.org/10.5194/essd-15-5121-2023, https://doi.org/10.5194/essd-15-5121-2023, 2023
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Forests strongly modify the accumulation, metamorphism and melting of snow in midlatitude and high-latitude regions. Two field campaigns during the winters 2016–17 and 2017–18 were conducted in a coniferous forest in the French Alps to study interactions between snow and vegetation. This paper presents the field site, instrumentation and collection methods. The observations include forest characteristics, meteorology, snow cover and snow interception by the canopy during precipitation events.
Koi McArthur, Felicity S. McCormack, and Christine F. Dow
The Cryosphere, 17, 4705–4727, https://doi.org/10.5194/tc-17-4705-2023, https://doi.org/10.5194/tc-17-4705-2023, 2023
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Using subglacial hydrology model outputs for Denman Glacier, East Antarctica, we investigated the effects of various friction laws and effective pressure inputs on ice dynamics modeling over the same glacier. The Schoof friction law outperformed the Budd friction law, and effective pressure outputs from the hydrology model outperformed a typically prescribed effective pressure. We propose an empirical prescription of effective pressure to be used in the absence of hydrology model outputs.
Felicity S. McCormack, Jason L. Roberts, Bernd Kulessa, Alan Aitken, Christine F. Dow, Lawrence Bird, Benjamin K. Galton-Fenzi, Katharina Hochmuth, Richard S. Jones, Andrew N. Mackintosh, and Koi McArthur
The Cryosphere, 17, 4549–4569, https://doi.org/10.5194/tc-17-4549-2023, https://doi.org/10.5194/tc-17-4549-2023, 2023
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Changes in Antarctic surface elevation can cause changes in ice and basal water flow, impacting how much ice enters the ocean. We find that ice and basal water flow could divert from the Totten to the Vanderford Glacier, East Antarctica, under only small changes in the surface elevation, with implications for estimates of ice loss from this region. Further studies are needed to determine when this could occur and if similar diversions could occur elsewhere in Antarctica due to climate change.
Thomas Dethinne, Quentin Glaude, Ghislain Picard, Christoph Kittel, Patrick Alexander, Anne Orban, and Xavier Fettweis
The Cryosphere, 17, 4267–4288, https://doi.org/10.5194/tc-17-4267-2023, https://doi.org/10.5194/tc-17-4267-2023, 2023
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We investigate the sensitivity of the regional climate model
Modèle Atmosphérique Régional(MAR) to the assimilation of wet-snow occurrence estimated by remote sensing datasets. The assimilation is performed by nudging the MAR snowpack temperature. The data assimilation is performed over the Antarctic Peninsula for the 2019–2021 period. The results show an increase in the melt production (+66.7 %) and a decrease in surface mass balance (−4.5 %) of the model for the 2019–2020 melt season.
Yaowen Zheng, Nicholas R. Golledge, Alexandra Gossart, Ghislain Picard, and Marion Leduc-Leballeur
The Cryosphere, 17, 3667–3694, https://doi.org/10.5194/tc-17-3667-2023, https://doi.org/10.5194/tc-17-3667-2023, 2023
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Positive degree-day (PDD) schemes are widely used in many Antarctic numerical ice sheet models. However, the PDD approach has not been systematically explored for its application in Antarctica. We have constructed a novel grid-cell-level spatially distributed PDD (dist-PDD) model and assessed its accuracy. We suggest that an appropriately parameterized dist-PDD model can be a valuable tool for exploring Antarctic surface melt beyond the satellite era.
Esteban Alonso-González, Simon Gascoin, Sara Arioli, and Ghislain Picard
The Cryosphere, 17, 3329–3342, https://doi.org/10.5194/tc-17-3329-2023, https://doi.org/10.5194/tc-17-3329-2023, 2023
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Data assimilation techniques are a promising approach to improve snowpack simulations in remote areas that are difficult to monitor. This paper studies the ability of satellite-observed land surface temperature to improve snowpack simulations through data assimilation. We show that it is possible to improve snowpack simulations, but the temporal resolution of the observations and the algorithm used are critical to obtain satisfactory results.
Sara Arioli, Ghislain Picard, Laurent Arnaud, and Vincent Favier
The Cryosphere, 17, 2323–2342, https://doi.org/10.5194/tc-17-2323-2023, https://doi.org/10.5194/tc-17-2323-2023, 2023
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To assess the drivers of the snow grain size evolution during snow drift, we exploit a 5-year time series of the snow grain size retrieved from spectral-albedo observations made with a new, autonomous, multi-band radiometer and compare it to observations of snow drift, snowfall and snowmelt at a windy location of coastal Antarctica. Our results highlight the complexity of the grain size evolution in the presence of snow drift and show an overall tendency of snow drift to limit its variations.
James A. Smith, Louise Callard, Michael J. Bentley, Stewart S. R. Jamieson, Maria Luisa Sánchez-Montes, Timothy P. Lane, Jeremy M. Lloyd, Erin L. McClymont, Christopher M. Darvill, Brice R. Rea, Colm O'Cofaigh, Pauline Gulliver, Werner Ehrmann, Richard S. Jones, and David H. Roberts
The Cryosphere, 17, 1247–1270, https://doi.org/10.5194/tc-17-1247-2023, https://doi.org/10.5194/tc-17-1247-2023, 2023
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The Greenland Ice Sheet is melting at an accelerating rate. To understand the significance of these changes we reconstruct the history of one of its fringing ice shelves, known as 79° N ice shelf. We show that the ice shelf disappeared 8500 years ago, following a period of enhanced warming. An important implication of our study is that 79° N ice shelf is susceptible to collapse when atmospheric and ocean temperatures are ~2°C warmer than present, which could occur by the middle of this century.
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.
Ghislain Picard, Henning Löwe, and Christian Mätzler
The Cryosphere, 16, 3861–3866, https://doi.org/10.5194/tc-16-3861-2022, https://doi.org/10.5194/tc-16-3861-2022, 2022
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Microwave satellite observations used to monitor the cryosphere require radiative transfer models for their interpretation. These models represent how microwaves are scattered by snow and ice. However no existing theory is suitable for all types of snow and ice found on Earth. We adapted a recently published generic scattering theory to snow and show how it may improve the representation of snows with intermediate densities (~500 kg/m3) and/or with coarse grains at high microwave frequencies.
Gauthier Vérin, Florent Domine, Marcel Babin, Ghislain Picard, and Laurent Arnaud
The Cryosphere, 16, 3431–3449, https://doi.org/10.5194/tc-16-3431-2022, https://doi.org/10.5194/tc-16-3431-2022, 2022
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Snow physical properties on Arctic sea ice are monitored during the melt season. As snow grains grow, and the snowpack thickness is reduced, the surface albedo decreases. The extra absorbed energy accelerates melting. Radiative transfer modeling shows that more radiation is then transmitted to the snow–sea-ice interface. A sharp increase in transmitted radiation takes place when the snowpack thins significantly, and this coincides with the initiation of the phytoplankton bloom in the seawater.
Zhiang Xie, Dietmar Dommenget, Felicity S. McCormack, and Andrew N. Mackintosh
Geosci. Model Dev., 15, 3691–3719, https://doi.org/10.5194/gmd-15-3691-2022, https://doi.org/10.5194/gmd-15-3691-2022, 2022
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Paleoclimate research requires better numerical model tools to explore interactions among the cryosphere, atmosphere, ocean and land surface. To explore those interactions, this study offers a tool, the GREB-ISM, which can be run for 2 million model years within 1 month on a personal computer. A series of experiments show that the GREB-ISM is able to reproduce the modern ice sheet distribution as well as classic climate oscillation features under paleoclimate conditions.
Alvaro Robledano, Ghislain Picard, Laurent Arnaud, Fanny Larue, and Inès Ollivier
The Cryosphere, 16, 559–579, https://doi.org/10.5194/tc-16-559-2022, https://doi.org/10.5194/tc-16-559-2022, 2022
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Topography controls the surface temperature of snow-covered, mountainous areas. We developed a modelling chain that uses ray-tracing methods to quantify the impact of a few topographic effects on snow surface temperature at high spatial resolution. Its large spatial and temporal variations are correctly simulated over a 50 km2 area in the French Alps, and our results show that excluding a single topographic effect results in cooling (or warming) effects on the order of 1 °C.
Jamey Stutz, Andrew Mackintosh, Kevin Norton, Ross Whitmore, Carlo Baroni, Stewart S. R. Jamieson, Richard S. Jones, Greg Balco, Maria Cristina Salvatore, Stefano Casale, Jae Il Lee, Yeong Bae Seong, Robert McKay, Lauren J. Vargo, Daniel Lowry, Perry Spector, Marcus Christl, Susan Ivy Ochs, Luigia Di Nicola, Maria Iarossi, Finlay Stuart, and Tom Woodruff
The Cryosphere, 15, 5447–5471, https://doi.org/10.5194/tc-15-5447-2021, https://doi.org/10.5194/tc-15-5447-2021, 2021
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Understanding the long-term behaviour of ice sheets is essential to projecting future changes due to climate change. In this study, we use rocks deposited along the margin of the David Glacier, one of the largest glacier systems in the world, to reveal a rapid thinning event initiated over 7000 years ago and endured for ~ 2000 years. Using physical models, we show that subglacial topography and ocean heat are important drivers for change along this sector of the Antarctic Ice Sheet.
Maria Belke-Brea, Florent Domine, Ghislain Picard, Mathieu Barrere, and Laurent Arnaud
Biogeosciences, 18, 5851–5869, https://doi.org/10.5194/bg-18-5851-2021, https://doi.org/10.5194/bg-18-5851-2021, 2021
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Expanding shrubs in the Arctic change snowpacks into a mix of snow, impurities and buried branches. Snow is a translucent medium into which light penetrates and gets partly absorbed by branches or impurities. Measurements of light attenuation in snow in Northern Quebec, Canada, showed (1) black-carbon-dominated light attenuation in snowpacks without shrubs and (2) buried branches influence radiation attenuation in snow locally, leading to melting and pockets of large crystals close to branches.
Rachel K. Smedley, David Small, Richard S. Jones, Stephen Brough, Jennifer Bradley, and Geraint T. H. Jenkins
Geochronology, 3, 525–543, https://doi.org/10.5194/gchron-3-525-2021, https://doi.org/10.5194/gchron-3-525-2021, 2021
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We apply new rock luminescence techniques to a well-constrained scenario of the Beinn Alligin rock avalanche, NW Scotland. We measure accurate erosion rates consistent with independently derived rates and reveal a transient state of erosion over the last ~4000 years in the wet, temperate climate of NW Scotland. This study shows that the new luminescence erosion-meter has huge potential for inferring erosion rates on sub-millennial scales, which is currently impossible with existing techniques.
Martim Mas e Braga, Richard Selwyn Jones, Jennifer C. H. Newall, Irina Rogozhina, Jane L. Andersen, Nathaniel A. Lifton, and Arjen P. Stroeven
The Cryosphere, 15, 4929–4947, https://doi.org/10.5194/tc-15-4929-2021, https://doi.org/10.5194/tc-15-4929-2021, 2021
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Mountains higher than the ice surface are sampled to know when the ice reached the sampled elevation, which can be used to guide numerical models. This is important to understand how much ice will be lost by ice sheets in the future. We use a simple model to understand how ice flow around mountains affects the ice surface topography and show how much this influences results from field samples. We also show that models need a finer resolution over mountainous areas to better match field samples.
Lisa Craw, Adam Treverrow, Sheng Fan, Mark Peternell, Sue Cook, Felicity McCormack, and Jason Roberts
The Cryosphere, 15, 2235–2250, https://doi.org/10.5194/tc-15-2235-2021, https://doi.org/10.5194/tc-15-2235-2021, 2021
Short summary
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Ice sheet and ice shelf models rely on data from experiments to accurately represent the way ice moves. Performing experiments at the temperatures and stresses that are generally present in nature takes a long time, and so there are few of these datasets. Here, we test the method of speeding up an experiment by running it initially at a higher temperature, before dropping to a lower target temperature to generate the relevant data. We show that this method can reduce experiment time by 55 %.
Alison F. Banwell, Rajashree Tri Datta, Rebecca L. Dell, Mahsa Moussavi, Ludovic Brucker, Ghislain Picard, Christopher A. Shuman, and Laura A. Stevens
The Cryosphere, 15, 909–925, https://doi.org/10.5194/tc-15-909-2021, https://doi.org/10.5194/tc-15-909-2021, 2021
Short summary
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Ice shelves are thick floating layers of glacier ice extending from the glaciers on land that buttress much of the Antarctic Ice Sheet and help to protect it from losing ice to the ocean. However, the stability of ice shelves is vulnerable to meltwater lakes that form on their surfaces during the summer. This study focuses on the northern George VI Ice Shelf on the western side of the AP, which had an exceptionally long and extensive melt season in 2019/2020 compared to the previous 31 seasons.
François Tuzet, Marie Dumont, Ghislain Picard, Maxim Lamare, Didier Voisin, Pierre Nabat, Mathieu Lafaysse, Fanny Larue, Jesus Revuelto, and Laurent Arnaud
The Cryosphere, 14, 4553–4579, https://doi.org/10.5194/tc-14-4553-2020, https://doi.org/10.5194/tc-14-4553-2020, 2020
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This study presents a field dataset collected over 30 d from two snow seasons at a Col du Lautaret site (French Alps). The dataset compares different measurements or estimates of light-absorbing particle (LAP) concentrations in snow, highlighting a gap in the current understanding of the measurement of these quantities. An ensemble snowpack model is then evaluated for this dataset estimating that LAPs shorten each snow season by around 10 d despite contrasting meteorological conditions.
Maxim Lamare, Marie Dumont, Ghislain Picard, Fanny Larue, François Tuzet, Clément Delcourt, and Laurent Arnaud
The Cryosphere, 14, 3995–4020, https://doi.org/10.5194/tc-14-3995-2020, https://doi.org/10.5194/tc-14-3995-2020, 2020
Short summary
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Terrain features found in mountainous regions introduce large errors into the calculation of the physical properties of snow using optical satellite images. We present a new model performing rapid calculations of solar radiation over snow-covered rugged terrain that we tested over a site in the French Alps. The results of the study show that all the interactions between sunlight and the terrain should be accounted for over snow-covered surfaces to correctly estimate snow properties from space.
Syed Abdul Salam, Jason L. Roberts, Felicity S. McCormack, Richard Coleman, and Jacqueline A. Halpin
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2020-146, https://doi.org/10.5194/essd-2020-146, 2020
Publication in ESSD not foreseen
Short summary
Short summary
Accurate estimates of englacial temperature and geothermal heat flux are incredibly important
for constraining model simulations of ice dynamics (e.g. viscosity is temperature-dependent) and sliding. However, we currently have few direct measurements of vertical temperature (i.e. only at boreholes/ice domes) and geothermal heat flux in Antarctica. This method derives attenuation rates, that can then be mapped directly to englacial temperatures and geothermal heat flux.
Cited articles
Arthur, J. F., Stokes, C., Jamieson, S. S., Carr, J. R., and Leeson, A. A.: Recent Understanding of Antarctic Supraglacial Lakes Using Satellite Remote Sensing, Prog. Phys. Geogr.-Earth Environ., 44, 0309133320916114, https://doi.org/10.1177/0309133320916114, 2020a. a
Arthur, J. F., Stokes, C. R., Jamieson, S. S. R., Carr, J. R., and Leeson, A. A.: Distribution and seasonal evolution of supraglacial lakes on Shackleton Ice Shelf, East Antarctica, The Cryosphere, 14, 4103–4120, https://doi.org/10.5194/tc-14-4103-2020, 2020b. a, b
Bamber, J. L., Oppenheimer, M., Kopp, R. E., Aspinall, W. P., and Cooke, R. M.:
Ice Sheet Contributions to Future Sea-Level Rise from Structured Expert
Judgment, P. Natl. Acad. Sci., 116,
11195–11200, https://doi.org/10.1073/pnas.1817205116, 2019. a
Banwell, A. F., MacAyeal, D. R., and Sergienko, O. V.: Breakup of the Larsen
B Ice Shelf Triggered by Chain Reaction Drainage of Supraglacial Lakes,
Geophys. Res. Lett., 40, 5872–5876, https://doi.org/10.1002/2013GL057694,
2013. a
Banwell, A. F., Datta, R. T., Dell, R. L., Moussavi, M., Brucker, L., Picard, G., Shuman, C. A., and Stevens, L. A.: The 32-year record-high surface melt in 2019/2020 on the northern George VI Ice Shelf, Antarctic Peninsula, The Cryosphere, 15, 909–925, https://doi.org/10.5194/tc-15-909-2021, 2021. a, b
Bevan, S., Luckman, A., Hendon, H., and Wang, G.: The 2020 Larsen C Ice Shelf surface melt is a 40-year record high, The Cryosphere, 14, 3551–3564, https://doi.org/10.5194/tc-14-3551-2020, 2020. a
Bevan, S. L., Luckman, A. J., Kuipers Munneke, P., Hubbard, B., Kulessa, B.,
and Ashmore, D. W.: Decline in Surface Melt Duration on Larsen C Ice
Shelf Revealed by The Advanced Scatterometer (ASCAT), Earth
Space Sci., 5, 578–591, https://doi.org/10.1029/2018EA000421, 2018. a, b
Bindschadler, R., Vornberger, P., Fleming, A., Fox, A., Mullins, J., Binnie,
D., Paulsen, S., Granneman, B., and Gorodetzky, D.: The Landsat Image
Mosaic of Antarctica, Remote Sens. Environ., 112, 4214–4226,
https://doi.org/10.1016/j.rse.2008.07.006, 2008. a, b
Bindschadler, R., Choi, H., Wichlacz, A., Bingham, R., Bohlander, J., Brunt, K., Corr, H., Drews, R., Fricker, H., Hall, M., Hindmarsh, R., Kohler, J., Padman, L., Rack, W., Rotschky, G., Urbini, S., Vornberger, P., and Young, N.: Getting around Antarctica: new high-resolution mappings of the grounded and freely-floating boundaries of the Antarctic ice sheet created for the International Polar Year, The Cryosphere, 5, 569–588, https://doi.org/10.5194/tc-5-569-2011, 2011. a
Brancato, V., Rignot, E., Milillo, P., Morlighem, M., Mouginot, J., An, L.,
Scheuchl, B., Jeong, S., Rizzoli, P., Bueso Bello, J. L., and Prats-Iraola,
P.: Grounding Line Retreat of Denman Glacier, East Antarctica,
Measured With COSMO-SkyMed Radar Interferometry Data, Geophys.
Res. Lett., 47, e2019GL086291, https://doi.org/10.1029/2019GL086291, 2020. a
Bromwich, D. H.: Satellite Analyses of Antarctic Katabatic Wind
Behavior, B. Am. Meteorol. Soc., 70, 738–749,
https://doi.org/10.1175/1520-0477(1989)070<0738:SAOAKW>2.0.CO;2, 1989. a
Burton-Johnson, A., Black, M., Fretwell, P. T., and Kaluza-Gilbert, J.: An automated methodology for differentiating rock from snow, clouds and sea in Antarctica from Landsat 8 imagery: a new rock outcrop map and area estimation for the entire Antarctic continent, The Cryosphere, 10, 1665–1677, https://doi.org/10.5194/tc-10-1665-2016, 2016. a
Cassano, J. J., Nigro, M. A., and Lazzara, M. A.: Characteristics of the
Near-Surface Atmosphere over the Ross Ice Shelf, Antarctica, J. Geophys. Res.-Atmos., 121, 3339–3362,
https://doi.org/10.1002/2015JD024383, 2016. a
Colhoun, E. A. and Adamson, D. A.: Former Glacial Lakes of the Bunger
Hills, Antarctica, Australian Geographer, 20, 125–135,
https://doi.org/10.1080/00049188908702984, 1989. a
Das, I., Bell, R. E., Scambos, T. A., Wolovick, M., Creyts, T. T., Studinger,
M., Frearson, N., Nicolas, J. P., Lenaerts, J. T. M., and van den Broeke,
M. R.: Influence of Persistent Wind Scour on the Surface Mass Balance of
Antarctica, Nature Geosci., 6, 367–371, https://doi.org/10.1038/ngeo1766, 2013. a
Dell, R. L., Banwell, A. F., Willis, I. C., Arnold, N. S., Halberstadt, A.
R. W., Chudley, T. R., and Pritchard, H. D.: Supervised Classification of
Slush and Ponded Water on Antarctic Ice Shelves Using Landsat 8
Imagery, J. Glaciol., 68, 401–414, https://doi.org/10.1017/jog.2021.114, 2021. a
Doran, P. T., McKay, C. P., Meyer, M. A., Andersen, D. T., Wharton, R. A., and
Hastings, J. T.: Climatology and Implications for Perennial Lake Ice
Occurrence at Bunger Hills Oasis, East Antarctica, Antarctic Sci.,
8, 289–296, https://doi.org/10.1017/S0954102096000429, 1996. a
Dupont, T. K. and Alley, R. B.: Assessment of the Importance of Ice-Shelf
Buttressing to Ice-Sheet Flow, Geophys. Res. Lett., 32, L04503,
https://doi.org/10.1029/2004GL022024, 2005. a
Elvidge, A. D., Kuipers Munneke, P., King, J. C., Renfrew, I. A., and Gilbert,
E.: Atmospheric Drivers of Melt on Larsen C Ice Shelf: Surface
Energy Budget Regimes and the Impact of Foehn, J.
Geophys. Res.-Atmos., 125, e2020JD032463,
https://doi.org/10.1029/2020JD032463, 2020. a
Fraser, A. D., Massom, R. A., Handcock, M. S., Reid, P., Ohshima, K. I., Raphael, M. N., Cartwright, J., Klekociuk, A. R., Wang, Z., and Porter-Smith, R.: Eighteen-year record of circum-Antarctic landfast-sea-ice distribution allows detailed baseline characterisation and reveals trends and variability, The Cryosphere, 15, 5061–5077, https://doi.org/10.5194/tc-15-5061-2021, 2021. a
Fürst, J. J., Durand, G., Gillet-Chaulet, F., Tavard, L., Rankl, M.,
Braun, M., and Gagliardini, O.: The Safety Band of Antarctic Ice Shelves,
Nat. Clim. Change, 6, 479–482, https://doi.org/10.1038/nclimate2912, 2016. a, b
Ghiz, M. L., Scott, R. C., Vogelmann, A. M., Lenaerts, J. T. M., Lazzara, M., and Lubin, D.: Energetics of surface melt in West Antarctica, The Cryosphere, 15, 3459–3494, https://doi.org/10.5194/tc-15-3459-2021, 2021. a, b
Gibson, P. B., Perkins-Kirkpatrick, S. E., Uotila, P., Pepler, A. S., and
Alexander, L. V.: On the Use of Self-Organizing Maps for Studying Climate
Extremes, J. Geophys. Res.-Atmos., 122, 3891–3903,
https://doi.org/10.1002/2016JD026256, 2017. a
Gilbert, E. and Kittel, C.: Surface Melt and Runoff on Antarctic Ice
Shelves at 1.5∘C, 2∘C, and 4∘C of
Future Warming, Geophys. Res. Lett., 48, e2020GL091733,
https://doi.org/10.1029/2020GL091733, 2021. a, b
Haseloff, M. and Sergienko, O. V.: The Effect of Buttressing on Grounding Line
Dynamics, J. Glaciol., 64, 417–431, https://doi.org/10.1017/jog.2018.30,
2018. a
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A.,
Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D.,
Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P.,
Biavati, G., Bidlot, J., Bonavita, M., Chiara, G. D., Dahlgren, P., Dee, D.,
Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer,
A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková, M.,
Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P.,
Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J.-N.: The ERA5
Global Reanalysis, Q. J. Roy. Meteorol. Soc.,
146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020. a
Hewitson, B. C. and Crane, R. G.: Self-Organizing Maps: Applications to
Synoptic Climatology, Climate Res., 22, 13–26, https://doi.org/10.3354/cr022013,
2002. a
Holland, P. R., Corr, H. F. J., Pritchard, H. D., Vaughan, D. G., Arthern,
R. J., Jenkins, A., and Tedesco, M.: The Air Content of Larsen Ice Shelf,
Geophys. Res. Lett., 38, L10503, https://doi.org/10.1029/2011GL047245, 2011. a
Howat, I. M., Porter, C., Smith, B. E., Noh, M.-J., and Morin, P.: The Reference Elevation Model of Antarctica, The Cryosphere, 13, 665–674, https://doi.org/10.5194/tc-13-665-2019, 2019. a, b, c
Hui, F., Ci, T., Cheng, X., Scambo, T. A., Liu, Y., Zhang, Y., Chi, Z., Huang,
H., Wang, X., Wang, F., Zhao, C., Jin, Z., and Wang, K.: Mapping Blue-Ice
Areas in Antarctica Using ETM+ and MODIS Data, Ann.
Glaciol., 55, 129–137, https://doi.org/10.3189/2014AoG66A069, 2014. a
Jakobs, C. L., Reijmer, C. H., Kuipers Munneke, P., König-Langlo, G., and van den Broeke, M. R.: Quantifying the snowmelt–albedo feedback at Neumayer Station, East Antarctica, The Cryosphere, 13, 1473–1485, https://doi.org/10.5194/tc-13-1473-2019, 2019. a
Jakobs, C. L., Reijmer, C. H., Smeets, C. J. P. P., Trusel, L. D., van de
Berg, W. J., van den Broeke, M. R., and van Wessem, J. M.: A Benchmark
Dataset of in Situ Antarctic Surface Melt Rates and Energy Balance,
J. Glaciol., 66, 291–302, https://doi.org/10.1017/jog.2020.6, 2020. a
Johnson, A., Fahnestock, M., and Hock, R.: Evaluation of Passive Microwave Melt
Detection Methods on Antarctic Peninsula Ice Shelves Using Time Series of
Sentinel-1 SAR, Remote Sens. Environ., 250, 112044,
https://doi.org/10.1016/j.rse.2020.112044, 2020. a, b
Johnson, A., Hock, R., and Fahnestock, M.: Spatial Variability and Regional
Trends of Antarctic Ice Shelf Surface Melt Duration over 1979–2020 Derived from Passive Microwave Data, J. Glaciol., 68, 533–546,
https://doi.org/10.1017/jog.2021.112, 2021. a
King, J. C., Kirchgaessner, A., Bevan, S., Elvidge, A. D., Kuipers Munneke, P.,
Luckman, A., Orr, A., Renfrew, I. A., and van den Broeke, M. R.: The
Impact of Föhn Winds on Surface Energy Balance During the
2010–2011 Melt Season Over Larsen C Ice Shelf, Antarctica,
J. Geophys. Res.-Atmos., 122, 12062–12076,
https://doi.org/10.1002/2017JD026809, 2017. a
Kittel, C., Amory, C., Agosta, C., Jourdain, N. C., Hofer, S., Delhasse, A., Doutreloup, S., Huot, P.-V., Lang, C., Fichefet, T., and Fettweis, X.: Diverging future surface mass balance between the Antarctic ice shelves and grounded ice sheet, The Cryosphere, 15, 1215–1236, https://doi.org/10.5194/tc-15-1215-2021, 2021. a
Kohonen, T.: The Self-Organizing Map, Proceedings of the IEEE, 78, 1464–1480,
https://doi.org/10.1109/5.58325, 1990. a
Kohonen, T.: Self-Organizing Maps, 3rd ed., Springer Berlin, Heidelberg, 502 pp., https://doi.org/10.1007/978-3-642-56927-2, 2001. a
Konrad, H., Shepherd, A., Gilbert, L., Hogg, A. E., McMillan, M., Muir, A., and
Slater, T.: Net Retreat of Antarctic Glacier Grounding Lines, Nature
Geosci., 11, 258–262, https://doi.org/10.1038/s41561-018-0082-z, 2018. a, b
Kuipers Munneke, P., Ligtenberg, S. R., van den Broeke, M. R., and Vaughan,
D. G.: Firn Air Depletion as a Precursor of Antarctic Ice-Shelf Collapse,
J. Glaciol., 60, 205–214, https://doi.org/10.3189/2014JoG13J183, 2014. a
Kunz, L. and Long, D.: Melt Detection in Antarctic Ice Shelves Using
Scatterometers and Microwave Radiometers, IEEE T.
Geosci. Remote, 44, 2461–2469,
https://doi.org/10.1109/TGRS.2006.874138, 2006. a
Leduc-Leballeur, M., Picard, G., Macelloni, G., Mialon, A., and Kerr, Y. H.: Melt in Antarctica derived from Soil Moisture and Ocean Salinity (SMOS) observations at L band, The Cryosphere, 14, 539–548, https://doi.org/10.5194/tc-14-539-2020, 2020. a, b, c
Leeson, A. A., Forster, E., Rice, A., Gourmelen, N., and van Wessem, J. M.:
Evolution of Supraglacial Lakes on the Larsen B Ice Shelf in the
Decades Before It Collapsed, Geophys. Res. Lett., 47,
e2019GL085591, https://doi.org/10.1029/2019GL085591, 2020. a
Lenaerts, J. T. M., van den Broeke, M. R., Scarchilli, C., and Agosta, C.:
Impact of Model Resolution on Simulated Wind, Drifting Snow and Surface Mass
Balance in Terre Adélie, East Antarctica, J. Glaciol.,
58, 821–829, https://doi.org/10.3189/2012JoG12J020, 2012. a, b
Lenaerts, J. T. M., Lhermitte, S., Drews, R., Ligtenberg, S. R. M., Berger, S.,
Helm, V., Smeets, C. J. P. P., van den Broeke, M. R., van de Berg, W. J.,
van Meijgaard, E., Eijkelboom, M., Eisen, O., and Pattyn, F.: Meltwater
Produced by Wind-Albedo Interaction Stored in an East
Antarctic Ice Shelf, Nature Climate Change, 7, 58–62,
https://doi.org/10.1038/nclimate3180, 2017a. a, b
Lenaerts, J. T. M., van Tricht, K., Lhermitte, S., and L'Ecuyer, T. S.: Polar
Clouds and Radiation in Satellite Observations, Reanalyses, and Climate
Models, Geophys. Res. Lett., 44, 3355–3364,
https://doi.org/10.1002/2016GL072242, 2017b. a
Liang, D., Guo, H., Zhang, L., Cheng, Y., Zhu, Q., and Liu, X.: Time-Series
Snowmelt Detection over the Antarctic Using Sentinel-1 SAR Images on
Google Earth Engine, Remote Sens. Environ., 256, 112318,
https://doi.org/10.1016/j.rse.2021.112318, 2021. a
Liston, G. E. and Winther, J.-G.: Antarctic Surface and Subsurface Snow
and Ice Melt Fluxes, J. Climate, 18, 1469–1481,
https://doi.org/10.1175/JCLI3344.1, 2005. a
Liston, G. E., Winther, J.-G., Bruland, O., Elvehøy, H., and Sand, K.:
Below-Surface Ice Melt on the Coastal Antarctic Ice Sheet, J.
Glaciol., 45, 273–285, https://doi.org/10.3189/S0022143000001775, 1999. a
Liu, H., Wang, L., and Jezek, K. C.: Spatiotemporal Variations of Snowmelt in
Antarctica Derived from Satellite Scanning Multichannel Microwave
Radiometer and Special Sensor Microwave Imager Data (1978–2004), J. Geophys. Res.-Ea. Surf., 111, F01003,
https://doi.org/10.1029/2005JF000318, 2006. a, b, c
Luckman, A., Elvidge, A., Jansen, D., Kulessa, B., Kuipers Munneke, P., King,
J., and Barrand, N. E.: Surface Melt and Ponding on Larsen C Ice Shelf
and the Impact of Föhn Winds, Antarct. Sci., 26, 625–635,
https://doi.org/10.1017/S0954102014000339, 2014. a
MacAyeal, D. R., Scambos, T. A., Hulbe, C. L., and Fahnestock, M. A.:
Catastrophic Ice-Shelf Break-up by an Ice-Shelf-Fragment-Capsize Mechanism,
J. Glaciol., 49, 22–36, https://doi.org/10.3189/172756503781830863, 2003. a
Matsuoka, K., Skoglund, A., Roth, G., de Pomereu, J., Griffiths, H.,
Headland, R., Herried, B., Katsumata, K., Le Brocq, A., Licht, K., Morgan,
F., Neff, P. D., Ritz, C., Scheinert, M., Tamura, T., van de Putte, A.,
van den Broeke, M., von Deschwanden, A., Deschamps-Berger, C., van
Liefferinge, B., Tronstad, S., and Melvær, Y.: Quantarctica, an
Integrated Mapping Environment for Antarctica, the Southern Ocean,
and Sub-Antarctic Islands, Environ. Model. Softw., 140,
105015, https://doi.org/10.1016/j.envsoft.2021.105015, 2021. a, b
Meier, W. N., Markus, T., and Comiso, C.: AMSR-E/AMSR2 Unified L3 Daily
12.5 Km Brightness Temperatures, Sea Ice Concentration, Motion &
Snow Depth Polar Grids, Version 1, NASA National Snow and Ice Data Center Distributed Active Archive Center [data set], https://doi.org/10.5067/RA1MIJOYPK3P, 2018. a
Meier, W. N., Stewart, J., Wilcox, H., Scott, D., and Hardman, M.: DMSP
SSM/I-SSMIS Daily Polar Gridded Brightness Temperatures, Version
6, NASA National Snow and Ice Data Center Distributed Active Archive Center [data set], https://doi.org/10.5067/MXJL42WSXTS1, 2021. a
Miles, B. W. J., Jordan, J. R., Stokes, C. R., Jamieson, S. S. R., Gudmundsson, G. H., and Jenkins, A.: Recent acceleration of Denman Glacier (1972–2017), East Antarctica, driven by grounding line retreat and changes in ice tongue configuration, The Cryosphere, 15, 663–676, https://doi.org/10.5194/tc-15-663-2021, 2021. a, b
Morlighem, M., Rignot, E., Binder, T., Blankenship, D., Drews, R., Eagles, G.,
Eisen, O., Ferraccioli, F., Forsberg, R., Fretwell, P., Goel, V., Greenbaum,
J. S., Gudmundsson, H., Guo, J., Helm, V., Hofstede, C., Howat, I., Humbert,
A., Jokat, W., Karlsson, N. B., Lee, W. S., Matsuoka, K., Millan, R.,
Mouginot, J., Paden, J., Pattyn, F., Roberts, J., Rosier, S., Ruppel, A.,
Seroussi, H., Smith, E. C., Steinhage, D., Sun, B., van den Broeke, M. R.,
van Ommen, T. D., van Wessem, M., and Young, D. A.: Deep Glacial Troughs
and Stabilizing Ridges Unveiled beneath the Margins of the Antarctic Ice
Sheet, Nature Geosci., 13, 132–137, https://doi.org/10.1038/s41561-019-0510-8,
2020. a
Mouginot, J., Scheuchl, B., and Rignot, E.: MEaSUREs Antarctic Boundaries
for IPY 2007–2009 from Satellite Radar, Version 2, NASA National Snow and Ice Data Center Distributed Active Archive Center [data set],
https://doi.org/10.5067/AXE4121732AD, 2017. a, b, c, d
Nicolas, J. P., Vogelmann, A. M., Scott, R. C., Wilson, A. B., Cadeddu, M. P.,
Bromwich, D. H., Verlinde, J., Lubin, D., Russell, L. M., Jenkinson, C.,
Powers, H. H., Ryczek, M., Stone, G., and Wille, J. D.: January 2016
Extensive Summer Melt in West Antarctica Favoured by Strong El
Niño, Nat. Commun., 8, 15799, https://doi.org/10.1038/ncomms15799, 2017. a
Nihashi, S. and Ohshima, K. I.: Circumpolar Mapping of Antarctic Coastal
Polynyas and Landfast Sea Ice: Relationship and Variability,
J. Climate, 28, 3650–3670, https://doi.org/10.1175/JCLI-D-14-00369.1, 2015. a
Oppenheimer, M., Glavovic, B. C., Hinkel, J., van de Wal, R., Magnan, A. K.,
Abd-Elgawad, A., Cai, R., Cifuentes-Jara, M., Meyssignac, B., and
Sebesvari, Z.: Sea Level Rise and Implications for Low-Lying Islands, Coasts and Communities, in: IPCC Special Report on the Ocean and Cryosphere in a Changing Climate, edited by: Pörtner, H. O., Roberts, D. C., Masson-Delmotte, V., Zhai, P., Tignor, M., Poloczanska, E., Mintenbeck, K., Alegría, A., Nicolai, M., Okem, A., Petzold, J., Rama, B., and Weyer, N. M., Cambridge University Press, Cambridge, UK and New York, NY, USA, 321–445, https://doi.org/10.1017/9781009157964.006, 2019. a
Parish, T. R. and Bromwich, D. H.: Reexamination of the Near-Surface
Airflow over the Antarctic Continent and Implications on
Atmospheric Circulations at High Southern Latitudes, Mon. Weather
Rev., 135, 1961–1973, https://doi.org/10.1175/MWR3374.1, 2007. a
Pattyn, F. and Morlighem, M.: The Uncertain Future of the Antarctic Ice
Sheet, Science, 367, 1331–1335, https://doi.org/10.1126/science.aaz5487, 2020. a
Picard, G.: Snow status (wet/dry) in Antarctica from SMMR, SSM/I, AMSR-E and AMSR2 passive microwave radiometers, PerSCiDO [data set], https://doi.org/10.18709/perscido.2022.09.ds376, 2022. a
Picard, G., Fily, M., and Gallee, H.: Surface Melting Derived from Microwave
Radiometers: A Climatic Indicator in Antarctica, Ann. Glaciol.,
46, 29–34, https://doi.org/10.3189/172756407782871684, 2007. a
Polar Geospatial Center: University of Minnesota [data set], https://www.pgc.umn.edu/data/rema, last access: 12 October 2022. a
R Core Team: R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing [code], Vienna, Austria, https://www.R-project.org (last access: 12 October 2022), 2021. a
Rack, W. and Rott, H.: Pattern of Retreat and Disintegration of the Larsen
B Ice Shelf, Antarctic Peninsula, Ann. Glaciol., 39, 505–510,
https://doi.org/10.3189/172756404781814005, 2004. a
REMSS: https://www.remss.com/support/crossing-times, last access: 12 October 2022. a
Rignot, E., Casassa, G., Gogineni, P., Krabill, W., Rivera, A., and Thomas, R.:
Accelerated Ice Discharge from the Antarctic Peninsula Following the
Collapse of Larsen B Ice Shelf, Geophys. Res. Lett., 31, L18401,
https://doi.org/10.1029/2004GL020697, 2004. a
Rignot, E., Jacobs, S., Mouginot, J., and Scheuchl, B.: Ice-Shelf Melting
Around Antarctica, Science, 341, 266–270, https://doi.org/10.1126/science.1235798,
2013. a, b
Rignot, E., Mouginot, J., Scheuchl, B., van den Broeke, M. R., van Wessem,
M. J., and Morlighem, M.: Four Decades of Antarctic Ice Sheet Mass
Balance from 1979–2017, P. Natl. Acad.
Sci., 116, 1095–1103, https://doi.org/10.1073/pnas.1812883116, 2019. a
Robel, A. A. and Banwell, A. F.: A Speed Limit on Ice Shelf Collapse
Through Hydrofracture, Geophys. Res. Lett., 46, 12092–12100,
https://doi.org/10.1029/2019GL084397, 2019. a
Robel, A. A., Seroussi, H., and Roe, G. H.: Marine Ice Sheet Instability
Amplifies and Skews Uncertainty in Projections of Future Sea-Level Rise,
P. Natl. Acad. Sci., 116, 14887–14892,
https://doi.org/10.1073/pnas.1904822116, 2019. a
Rott, H., Rack, W., Skvarca, P., and Angelis, H. D.: Northern Larsen Ice
Shelf, Antarctica: Further Retreat after Collapse, Ann.
Glaciol., 34, 277–282, https://doi.org/10.3189/172756402781817716, 2002. a
Saunderson, D.: ShackletonSOM R Code used in Saunderson et al. (2022; The Cryosphere), Monash University [code], https://doi.org/10.26180/21132934.v1, 2022. a
Scambos, T. A., Hulbe, C., Fahnestock, M., and Bohlander, J.: The Link between
Climate Warming and Break-up of Ice Shelves in the Antarctic Peninsula,
J. Glaciol., 46, 516–530, https://doi.org/10.3189/172756500781833043, 2000. a
Scambos, T. A., Bohlander, J. A., Shuman, C. A., and Skvarca, P.: Glacier
Acceleration and Thinning after Ice Shelf Collapse in the Larsen B
Embayment, Antarctica, Geophys. Res. Lett., 31, L18402,
https://doi.org/10.1029/2004GL020670, 2004. a
Scott, R. C., Nicolas, J. P., Bromwich, D. H., Norris, J. R., and Lubin, D.:
Meteorological Drivers and Large-Scale Climate Forcing of West
Antarctic Surface Melt, J. Climate, 32, 665–684,
https://doi.org/10.1175/JCLI-D-18-0233.1, 2019. a, b
Sergienko, O. and MacAyeal, D. R.: Surface Melting on Larsen Ice Shelf,
Antarctica, Ann. Glaciol., 40, 215–218,
https://doi.org/10.3189/172756405781813474, 2005. a
Sheridan, S. C. and Lee, C. C.: The Self-Organizing Map in Synoptic
Climatological Research, Prog. Phys. Geogr.-Earth
Environ., 35, 109–119, https://doi.org/10.1177/0309133310397582, 2011. a
Stephenson, S. N. and Zwally, H. J.: Ice-Shelf Topography and Structure
Determined Using Satellite-Radar Altimetry and Landsat Imagery, Ann. Glaciol., 12, 162–169, https://doi.org/10.3189/S026030550000714X, 1989. a, b
Sun, S., Pattyn, F., Simon, E. G., Albrecht, T., Cornford, S., Calov, R.,
Dumas, C., Gillet-Chaulet, F., Goelzer, H., Golledge, N. R., Greve, R.,
Hoffman, M. J., Humbert, A., Kazmierczak, E., Kleiner, T., Leguy, G. R.,
Lipscomb, W. H., Martin, D., Morlighem, M., Nowicki, S., Pollard, D., Price,
S., Quiquet, A., Seroussi, H., Schlemm, T., Sutter, J., van de Wal, R.
S. W., Winkelmann, R., and Zhang, T.: Antarctic Ice Sheet Response to Sudden
and Sustained Ice-Shelf Collapse (ABUMIP), J. Glaciol.,
66, 891–904, https://doi.org/10.1017/jog.2020.67, 2020. a
Tedesco, M. and Monaghan, A. J.: An Updated Antarctic Melt Record through
2009 and Its Linkages to High-Latitude and Tropical Climate Variability,
Geophys. Res. Lett., 36, L18502, https://doi.org/10.1029/2009GL039186, 2009. a
Tedesco, M., Abdalati, W., and Zwally, H. J.: Persistent Surface Snowmelt over
Antarctica (1987–2006) from 19.35 GHz Brightness
Temperatures, Geophys. Res. Lett., 34, L02504, https://doi.org/10.1029/2007GL031199,
2007. a, b
Torinesi, O., Fily, M., and Genthon, C.: Variability and Trends of the
Summer Melt Period of Antarctic Ice Margins since 1980 from
Microwave Sensors, J. Climate, 16, 1047–1060,
https://doi.org/10.1175/1520-0442(2003)016<1047:VATOTS>2.0.CO;2, 2003. a, b, c
Trusel, L. D., Frey, K. E., Das, S. B., Kuipers Munneke, P., and van den
Broeke, M. R.: Satellite-Based Estimates of Antarctic Surface Meltwater
Fluxes, Geophys. Res. Lett., 40, 6148–6153,
https://doi.org/10.1002/2013GL058138, 2013. a
Trusel, L. D., Frey, K. E., Das, S. B., Karnauskas, K. B., Kuipers Munneke, P.,
van Meijgaard, E., and van den Broeke, M. R.: Divergent Trajectories of
Antarctic Surface Melt under Two Twenty-First-Century Climate Scenarios,
Nature Geosci., 8, 927–932, https://doi.org/10.1038/ngeo2563, 2015. a, b
Turton, J. V., Kirchgaessner, A., Ross, A. N., King, J. C., and Kuipers Munneke, P.: The influence of föhn winds on annual and seasonal surface melt on the Larsen C Ice Shelf, Antarctica, The Cryosphere, 14, 4165–4180, https://doi.org/10.5194/tc-14-4165-2020, 2020. a
Udy, D. G., Vance, T. R., Kiem, A. S., Holbrook, N. J., and Curran, M. A. J.:
Links between Large-Scale Modes of Climate Variability and Synoptic
Weather Patterns in the Southern Indian Ocean, J. Climate, 34,
883–899, https://doi.org/10.1175/JCLI-D-20-0297.1, 2021. a
van Dalum, C. T., van de Berg, W., and van den Broeke, M. R.:
RACMO2.3p3 monthly SMB, SEB and t2m data for Antarctica (1979–2018), Zenodo [data set], https://doi.org/10.5281/zenodo.5512077,
2021. a, b, c
van Dalum, C. T., van de Berg, W. J., and van den Broeke, M. R.: Sensitivity of Antarctic surface climate to a new spectral snow albedo and radiative transfer scheme in RACMO2.3p3, The Cryosphere, 16, 1071–1089, https://doi.org/10.5194/tc-16-1071-2022, 2022. a, b
van den Broeke, M. R.: Strong Surface Melting Preceded Collapse of
Antarctic Peninsula Ice Shelf, Geophys. Res. Lett., 32, L12815,
https://doi.org/10.1029/2005GL023247, 2005. a
van den Broeke, M. R., Reijmer, C., As, D. V., and Boot, W.: Daily Cycle of
the Surface Energy Balance in Antarctica and the Influence of Clouds,
Int. J. Climatol., 26, 1587–1605, https://doi.org/10.1002/joc.1323,
2006. a
van den Broeke, M. R., König-Langlo, G., Picard, G., Kuipers Munneke,
P., and Lenaerts, J.: Surface Energy Balance, Melt and Sublimation at
Neumayer Station, East Antarctica, Antarct. Sci., 22, 87–96,
https://doi.org/10.1017/S0954102009990538, 2010. a
van der Veen, C. J.: Fracture Mechanics Approach to Penetration of Surface
Crevasses on Glaciers, Cold Reg. Sci. Technol., 27, 31–47,
https://doi.org/10.1016/S0165-232X(97)00022-0, 1998. a
van Tricht, K., Lhermitte, S., Lenaerts, J. T. M., Gorodetskaya, I. V.,
L'Ecuyer, T. S., Noël, B., van den Broeke, M. R., Turner, D. D., and
van Lipzig, N. P. M.: Clouds Enhance Greenland Ice Sheet Meltwater
Runoff, Nature Commun., 7, 10266, https://doi.org/10.1038/ncomms10266, 2016. a
van Wessem, J. M., Reijmer, C., Morlighem, M., Mouginot, J., Rignot, E.,
Medley, B., Joughin, I., Wouters, B., Depoorter, M., Bamber, J., Lenaerts,
J., van de Berg, W., van den Broeke, M., and van Meijgaard, E.:
Improved Representation of East Antarctic Surface Mass Balance in a
Regional Atmospheric Climate Model, J. Glaciol., 60, 761–770,
https://doi.org/10.3189/2014JoG14J051, 2014a. a
van Wessem, J. M., Reijmer, C. H., Lenaerts, J. T. M., van de Berg, W. J., van den Broeke, M. R., and van Meijgaard, E.: Updated cloud physics in a regional atmospheric climate model improves the modelled surface energy balance of Antarctica, The Cryosphere, 8, 125–135, https://doi.org/10.5194/tc-8-125-2014, 2014b. a
van Wessem, J. M., van de Berg, W. J., Noël, B. P. Y., van Meijgaard, E., Amory, C., Birnbaum, G., Jakobs, C. L., Krüger, K., Lenaerts, J. T. M., Lhermitte, S., Ligtenberg, S. R. M., Medley, B., Reijmer, C. H., van Tricht, K., Trusel, L. D., van Ulft, L. H., Wouters, B., Wuite, J., and van den Broeke, M. R.: Modelling the climate and surface mass balance of polar ice sheets using RACMO2 – Part 2: Antarctica (1979–2016), The Cryosphere, 12, 1479–1498, https://doi.org/10.5194/tc-12-1479-2018, 2018. a, b
Weertman, J.: Can a Water-Filled Crevasse Reach the Bottom Surface of a
Glacier?, International Association of Scientific Hydrology Publication, 95,
139–145, 1973. a
Weertman, J.: Stability of the Junction of an Ice Sheet and an Ice
Shelf, J. Glaciol., 13, 3–11, https://doi.org/10.3189/S0022143000023327,
1974. a
Wehrens, R. and Buydens, L. M. C.: Self- and Super-organizing Maps in
R: The Kohonen Package, J. Stat. Softw., 21,
1–19, https://doi.org/10.18637/jss.v021.i05, 2007. a
Wehrens, R. and Kruisselbrink, J.: Flexible Self-Organizing Maps in Kohonen
3.0, J. Stat. Softw., 87, 1–18, https://doi.org/10.18637/jss.v087.i07,
2018. a
Zheng, L. and Zhou, C.: Comparisons of Snowmelt Detected by Microwave Sensors
on the Shackleton Ice Shelf, East Antarctica, Int. J.
Remote Sens., 41, 1338–1348, https://doi.org/10.1080/01431161.2019.1666316, 2020. a, b, c, d
Zheng, L., Zhou, C., Liu, R., and Sun, Q.: Antarctic Snowmelt Detected by
Diurnal Variations of AMSR-E Brightness Temperature, Remote Sensing,
10, 1391, https://doi.org/10.3390/rs10091391, 2018. a
Zhou, C., Zheng, L., Sun, Q., and Liu, R.: Amery Ice Shelf Surface Snowmelt
Detected by ASCAT and Sentinel-1, Remote Sens. Lett., 10,
430–438, https://doi.org/10.1080/2150704X.2018.1553317, 2019. a, b
Zou, X., Bromwich, D. H., Nicolas, J. P., Montenegro, A., and Wang, S.-H.: West
Antarctic Surface Melt Event of January 2016 Facilitated by Föhn
Warming, Q. J. Roy. Meteorol. Soc., 145,
687–704, https://doi.org/10.1002/qj.3460, 2019.
a
Zwally, H. J. and Fiegles, S.: Extent and Duration of Antarctic Surface
Melting, J. Glaciol., 40, 463–475,
https://doi.org/10.3189/S0022143000012338, 1994. a, b, c, d
Short summary
We investigate the variability in surface melt on the Shackleton Ice Shelf in East Antarctica over the last 2 decades (2003–2021). Using daily satellite observations and the machine learning approach of a self-organising map, we identify nine distinct spatial patterns of melt. These patterns allow comparisons of melt within and across melt seasons and highlight the importance of both air temperatures and local controls such as topography, katabatic winds, and albedo in driving surface melt.
We investigate the variability in surface melt on the Shackleton Ice Shelf in East Antarctica...