Articles | Volume 17, issue 10
https://doi.org/10.5194/tc-17-4267-2023
© 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-17-4267-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
06 Oct 2023
Research article |
| 06 Oct 2023
| 06 Oct 2023
Sensitivity of the MAR regional climate model snowpack to the parameterization of the assimilation of satellite-derived wet-snow masks on the Antarctic Peninsula
SPHERES research unit, Laboratory of Climatology, University of Liège, Liège, Belgium
SPHERES research unit, Earth Observation and Ecosystem Monitoring laboratory, University of Liège, , Liège, Belgium
Quentin Glaude
SPHERES research unit, Laboratory of Climatology, University of Liège, Liège, Belgium
Centre Spatial de Liège, Signal Processing Laboratory, University of Liège, Liège, Belgium
Ghislain Picard
Institut des Géosciences de l'Environnement (IGE), Université Grenoble Alpes/CNRS/UMR 5001, Grenoble, France
Christoph Kittel
Institut des Géosciences de l'Environnement (IGE), Université Grenoble Alpes/CNRS/IRD/G-INP, Grenoble, France
Patrick Alexander
Lamont-Doherty Earth Observatory, Columbia University, Palisades, NY, USA
NASA Goddard Institute for Space Studies, New York, NY, USA
Anne Orban
Centre Spatial de Liège, Signal Processing Laboratory, University of Liège, Liège, Belgium
Xavier Fettweis
SPHERES research unit, Laboratory of Climatology, University of Liège, Liège, Belgium
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Weiran Li, Stef Lhermitte, Bert Wouters, Cornelis Slobbe, Max Brils, and Xavier Fettweis
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Sylvie Charbit, Christophe Dumas, Fabienne Maignan, Catherine Ottlé, Nina Raoult, Xavier Fettweis, and Philippe Conesa
The Cryosphere, 18, 5067–5099, https://doi.org/10.5194/tc-18-5067-2024, https://doi.org/10.5194/tc-18-5067-2024, 2024
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Sanne B. M. Veldhuijsen, Willem Jan van de Berg, Peter Kuipers Munneke, Nicolaj Hansen, Fredrik Boberg, Christoph Kittel, Charles Amory, and Michiel R. van den Broeke
EGUsphere, https://doi.org/10.5194/egusphere-2024-2855, https://doi.org/10.5194/egusphere-2024-2855, 2024
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Perennial firn aquifers (PFAs), year-round bodies of liquid water within firn, can potentially impact ice-shelf and ice-sheet stability. We developed a fast XGBoost firn emulator to predict 21st-century distribution of PFAs in Antarctica for 12 climatic forcings datasets. Our findings suggest that under low emission scenarios, PFAs remain confined to the Antarctic Peninsula. However, under a high-emission scenario, PFAs are projected to expand to a region in West Antarctica and East Antarctica.
Horst Machguth, Andrew Tedstone, Peter Kuipers Munneke, Max Brils, Brice Noël, Nicole Clerx, Nicolas Jullien, Xavier Fettweis, and Michiel van den Broeke
EGUsphere, https://doi.org/10.5194/egusphere-2024-2750, https://doi.org/10.5194/egusphere-2024-2750, 2024
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Due to increasing air temperatures, surface melt expands to higher elevations on the Greenland ice sheet. This is visible on satellite imagery in the form of rivers of meltwater running across the surface of the ice sheet. We compare model results of meltwater at high elevations on the ice sheet to satellite observations. We find that each of the models shows strengths and weaknesses. A detailed look into the model results reveals potential reasons for the differences between models.
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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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.
Cécile Davrinche, Anaïs Orsi, Cécile Agosta, Charles Amory, and Christoph Kittel
The Cryosphere, 18, 2239–2256, https://doi.org/10.5194/tc-18-2239-2024, https://doi.org/10.5194/tc-18-2239-2024, 2024
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Coastal surface winds in Antarctica are amongst the strongest winds on Earth. They are either driven by the cooling of the surface air mass by the ice sheet (katabatic) or by large-scale pressure systems. Here we compute the relative contribution of these drivers. We find that seasonal variations in the wind speed come from the katabatic acceleration, but, at a 3-hourly timescale, none of the large-scale or katabatic accelerations can be considered as the main driver.
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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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.
Alison Delhasse, Johanna Beckmann, Christoph Kittel, and Xavier Fettweis
The Cryosphere, 18, 633–651, https://doi.org/10.5194/tc-18-633-2024, https://doi.org/10.5194/tc-18-633-2024, 2024
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Aiming to study the long-term influence of an extremely warm climate in the Greenland Ice Sheet contribution to sea level rise, a new regional atmosphere–ice sheet model setup was established. The coupling, explicitly considering the melt–elevation feedback, is compared to an offline method to consider this feedback. We highlight mitigation of the feedback due to local changes in atmospheric circulation with changes in surface topography, making the offline correction invalid on the margins.
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.
Baptiste Vandecrux, Robert S. Fausto, Jason E. Box, Federico Covi, Regine Hock, Åsa K. Rennermalm, Achim Heilig, Jakob Abermann, Dirk van As, Elisa Bjerre, Xavier Fettweis, Paul C. J. P. Smeets, Peter Kuipers Munneke, Michiel R. van den Broeke, Max Brils, Peter L. Langen, Ruth Mottram, and Andreas P. Ahlstrøm
The Cryosphere, 18, 609–631, https://doi.org/10.5194/tc-18-609-2024, https://doi.org/10.5194/tc-18-609-2024, 2024
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How fast is the Greenland ice sheet warming? In this study, we compiled 4500+ temperature measurements at 10 m below the ice sheet surface (T10m) from 1912 to 2022. We trained a machine learning model on these data and reconstructed T10m for the ice sheet during 1950–2022. After a slight cooling during 1950–1985, the ice sheet warmed at a rate of 0.7 °C per decade until 2022. Climate models showed mixed results compared to our observations and underestimated the warming in key regions.
Violaine Coulon, Ann Kristin Klose, Christoph Kittel, Tamsin Edwards, Fiona Turner, Ricarda Winkelmann, and Frank Pattyn
The Cryosphere, 18, 653–681, https://doi.org/10.5194/tc-18-653-2024, https://doi.org/10.5194/tc-18-653-2024, 2024
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We present new projections of the evolution of the Antarctic ice sheet until the end of the millennium, calibrated with observations. We show that the ocean will be the main trigger of future ice loss. As temperatures continue to rise, the atmosphere's role may shift from mitigating to amplifying Antarctic mass loss already by the end of the century. For high-emission scenarios, this may lead to substantial sea-level rise. Adopting sustainable practices would however reduce the rate of ice loss.
Idunn Aamnes Mostue, Stefan Hofer, Trude Storelvmo, and Xavier Fettweis
The Cryosphere, 18, 475–488, https://doi.org/10.5194/tc-18-475-2024, https://doi.org/10.5194/tc-18-475-2024, 2024
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The latest generation of climate models (Coupled Model Intercomparison Project Phase 6 – CMIP6) warm more over Greenland and the Arctic and thus also project a larger mass loss from the Greenland Ice Sheet (GrIS) compared to the previous generation of climate models (CMIP5). Our work suggests for the first time that part of the greater mass loss in CMIP6 over the GrIS is driven by a difference in the surface mass balance sensitivity from a change in cloud representation in the CMIP6 models.
Laura J. Dietrich, Hans Christian Steen-Larsen, Sonja Wahl, Anne-Katrine Faber, and Xavier Fettweis
The Cryosphere, 18, 289–305, https://doi.org/10.5194/tc-18-289-2024, https://doi.org/10.5194/tc-18-289-2024, 2024
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The contribution of the humidity flux to the surface mass balance in the accumulation zone of the Greenland Ice Sheet is uncertain. Here, we evaluate the regional climate model MAR using a multi-annual dataset of eddy covariance measurements and bulk estimates of the humidity flux. The humidity flux largely contributes to the summer surface mass balance (SMB) in the accumulation zone, indicating its potential importance for the annual SMB in a warming climate.
Aymeric P. M. Servettaz, Cécile Agosta, Christoph Kittel, and Anaïs J. Orsi
The Cryosphere, 17, 5373–5389, https://doi.org/10.5194/tc-17-5373-2023, https://doi.org/10.5194/tc-17-5373-2023, 2023
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It has been previously observed in polar regions that the atmospheric temperature is warmer during precipitation events. Here, we use a regional atmospheric model to quantify the temperature changes associated with snowfall events across Antarctica. We show that more intense snowfall is statistically associated with a warmer temperature anomaly compared to the seasonal average, with the largest anomalies seen in winter. This bias may affect water isotopes in ice cores deposited during snowfall.
Marco Tedesco, Paolo Colosio, Xavier Fettweis, and Guido Cervone
The Cryosphere, 17, 5061–5074, https://doi.org/10.5194/tc-17-5061-2023, https://doi.org/10.5194/tc-17-5061-2023, 2023
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We developed a technique to improve the outputs of a model that calculates the gain and loss of Greenland and consequently its contribution to sea level rise. Our technique generates “sharper” images of the maps generated by the model to better understand and quantify where losses occur. This has implications for improving models, understanding what drives the contributions of Greenland to sea level rise, and more.
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.
Thorsten Seehaus, Christian Sommer, Thomas Dethinne, and Philipp Malz
The Cryosphere, 17, 4629–4644, https://doi.org/10.5194/tc-17-4629-2023, https://doi.org/10.5194/tc-17-4629-2023, 2023
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Existing mass budget estimates for the northern Antarctic Peninsula (>70° S) are affected by considerable limitations. We carried out the first region-wide analysis of geodetic mass balances throughout this region (coverage of 96.4 %) for the period 2013–2017 based on repeat pass bi-static TanDEM-X acquisitions. A total mass budget of −24.1±2.8 Gt/a is revealed. Imbalanced high ice discharge, particularly at former ice shelf tributaries, is the main driver of overall ice loss.
Damien Maure, Christoph Kittel, Clara Lambin, Alison Delhasse, and Xavier Fettweis
The Cryosphere, 17, 4645–4659, https://doi.org/10.5194/tc-17-4645-2023, https://doi.org/10.5194/tc-17-4645-2023, 2023
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The Arctic is warming faster than the rest of the Earth. Studies have already shown that Greenland and the Canadian Arctic are experiencing a record increase in melting rates, while Svalbard has been relatively less impacted. Looking at those regions but also extending the study to Iceland and the Russian Arctic archipelagoes, we see a heterogeneity in the melting-rate response to the Arctic warming, with the Russian archipelagoes experiencing lower melting rates than other regions.
Prateek Gantayat, Alison F. Banwell, Amber A. Leeson, James M. Lea, Dorthe Petersen, Noel Gourmelen, and Xavier Fettweis
Geosci. Model Dev., 16, 5803–5823, https://doi.org/10.5194/gmd-16-5803-2023, https://doi.org/10.5194/gmd-16-5803-2023, 2023
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We developed a new supraglacial hydrology model for the Greenland Ice Sheet. This model simulates surface meltwater routing, meltwater drainage, supraglacial lake (SGL) overflow, and formation of lake ice. The model was able to reproduce 80 % of observed lake locations and provides a good match between the observed and modelled temporal evolution of SGLs.
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.
Inès N. Otosaka, Andrew Shepherd, Erik R. Ivins, Nicole-Jeanne Schlegel, Charles Amory, Michiel R. van den Broeke, Martin Horwath, Ian Joughin, Michalea D. King, Gerhard Krinner, Sophie Nowicki, Anthony J. Payne, Eric Rignot, Ted Scambos, Karen M. Simon, Benjamin E. Smith, Louise S. Sørensen, Isabella Velicogna, Pippa L. Whitehouse, Geruo A, Cécile Agosta, Andreas P. Ahlstrøm, Alejandro Blazquez, William Colgan, Marcus E. Engdahl, Xavier Fettweis, Rene Forsberg, Hubert Gallée, Alex Gardner, Lin Gilbert, Noel Gourmelen, Andreas Groh, Brian C. Gunter, Christopher Harig, Veit Helm, Shfaqat Abbas Khan, Christoph Kittel, Hannes Konrad, Peter L. Langen, Benoit S. Lecavalier, Chia-Chun Liang, Bryant D. Loomis, Malcolm McMillan, Daniele Melini, Sebastian H. Mernild, Ruth Mottram, Jeremie Mouginot, Johan Nilsson, Brice Noël, Mark E. Pattle, William R. Peltier, Nadege Pie, Mònica Roca, Ingo Sasgen, Himanshu V. Save, Ki-Weon Seo, Bernd Scheuchl, Ernst J. O. Schrama, Ludwig Schröder, Sebastian B. Simonsen, Thomas Slater, Giorgio Spada, Tyler C. Sutterley, Bramha Dutt Vishwakarma, Jan Melchior van Wessem, David Wiese, Wouter van der Wal, and Bert Wouters
Earth Syst. Sci. Data, 15, 1597–1616, https://doi.org/10.5194/essd-15-1597-2023, https://doi.org/10.5194/essd-15-1597-2023, 2023
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By measuring changes in the volume, gravitational attraction, and ice flow of Greenland and Antarctica from space, we can monitor their mass gain and loss over time. Here, we present a new record of the Earth’s polar ice sheet mass balance produced by aggregating 50 satellite-based estimates of ice sheet mass change. This new assessment shows that the ice sheets have lost (7.5 x 1012) t of ice between 1992 and 2020, contributing 21 mm to sea level rise.
Benjamin E. Smith, Brooke Medley, Xavier Fettweis, Tyler Sutterley, Patrick Alexander, David Porter, and Marco Tedesco
The Cryosphere, 17, 789–808, https://doi.org/10.5194/tc-17-789-2023, https://doi.org/10.5194/tc-17-789-2023, 2023
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We use repeated satellite measurements of the height of the Greenland ice sheet to learn about how three computational models of snowfall, melt, and snow compaction represent actual changes in the ice sheet. We find that the models do a good job of estimating how the parts of the ice sheet near the coast have changed but that two of the models have trouble representing surface melt for the highest part of the ice sheet. This work provides suggestions for how to better model snowmelt.
Jilu Li, Fernando Rodriguez-Morales, Xavier Fettweis, Oluwanisola Ibikunle, Carl Leuschen, John Paden, Daniel Gomez-Garcia, and Emily Arnold
The Cryosphere, 17, 175–193, https://doi.org/10.5194/tc-17-175-2023, https://doi.org/10.5194/tc-17-175-2023, 2023
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Alaskan glaciers' loss of ice mass contributes significantly to ocean surface rise. It is important to know how deeply and how much snow accumulates on these glaciers to comprehend and analyze the glacial mass loss process. We reported the observed seasonal snow depth distribution from our radar data taken in Alaska in 2018 and 2021, developed a method to estimate the annual snow accumulation rate at Mt. Wrangell caldera, and identified transition zones from wet-snow zones to ablation zones.
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.
Dominic Saunderson, Andrew Mackintosh, Felicity McCormack, Richard Selwyn Jones, and Ghislain Picard
The Cryosphere, 16, 4553–4569, https://doi.org/10.5194/tc-16-4553-2022, https://doi.org/10.5194/tc-16-4553-2022, 2022
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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.
Raf M. Antwerpen, Marco Tedesco, Xavier Fettweis, Patrick Alexander, and Willem Jan van de Berg
The Cryosphere, 16, 4185–4199, https://doi.org/10.5194/tc-16-4185-2022, https://doi.org/10.5194/tc-16-4185-2022, 2022
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The ice on Greenland has been melting more rapidly over the last few years. Most of this melt comes from the exposure of ice when the overlying snow melts. This ice is darker than snow and absorbs more sunlight, leading to more melt. It remains challenging to accurately simulate the brightness of the ice. We show that the color of ice simulated by Modèle Atmosphérique Régional (MAR) is too bright. We then show that this means that MAR may underestimate how fast the Greenland ice is melting.
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.
Jeremy Carter, Amber Leeson, Andrew Orr, Christoph Kittel, and J. Melchior van Wessem
The Cryosphere, 16, 3815–3841, https://doi.org/10.5194/tc-16-3815-2022, https://doi.org/10.5194/tc-16-3815-2022, 2022
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Climate models provide valuable information for studying processes such as the collapse of ice shelves over Antarctica which impact estimates of sea level rise. This paper examines variability across climate simulations over Antarctica for fields including snowfall, temperature and melt. Significant systematic differences between outputs are found, occurring at both large and fine spatial scales across Antarctica. Results are important for future impact assessments and model development.
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.
Christoph Kittel, Charles Amory, Stefan Hofer, Cécile Agosta, Nicolas C. Jourdain, Ella Gilbert, Louis Le Toumelin, Étienne Vignon, Hubert Gallée, and Xavier Fettweis
The Cryosphere, 16, 2655–2669, https://doi.org/10.5194/tc-16-2655-2022, https://doi.org/10.5194/tc-16-2655-2022, 2022
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Model projections suggest large differences in future Antarctic surface melting even for similar greenhouse gas scenarios and warming rates. We show that clouds containing a larger amount of liquid water lead to stronger melt. As surface melt can trigger the collapse of the ice shelves (the safety band of the Antarctic Ice Sheet), clouds could be a major source of uncertainties in projections of sea level rise.
Sébastien Doutreloup, Xavier Fettweis, Ramin Rahif, Essam Elnagar, Mohsen S. Pourkiaei, Deepak Amaripadath, and Shady Attia
Earth Syst. Sci. Data, 14, 3039–3051, https://doi.org/10.5194/essd-14-3039-2022, https://doi.org/10.5194/essd-14-3039-2022, 2022
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This data set provides historical (1980–2014) and future (2015–2100) weather data for 12 cities in Belgium. This data set is intended for architects or building or energy designers. In particular, it makes available to all users hourly open-access weather data according to certain standards to recreate a Typical and an Extreme Meteorological Year. In addition, it provides hourly data on heatwaves from 1980 to 2100. Weather data were produced from the outputs of the MAR model simulations.
Nicolaj Hansen, Sebastian B. Simonsen, Fredrik Boberg, Christoph Kittel, Andrew Orr, Niels Souverijns, J. Melchior van Wessem, and Ruth Mottram
The Cryosphere, 16, 711–718, https://doi.org/10.5194/tc-16-711-2022, https://doi.org/10.5194/tc-16-711-2022, 2022
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We investigate the impact of different ice masks when modelling surface mass balance over Antarctica. We used ice masks and data from five of the most used regional climate models and a common mask. We see large disagreement between the ice masks, which has a large impact on the surface mass balance, especially around the Antarctic Peninsula and some of the largest glaciers. We suggest a solution for creating a new, up-to-date, high-resolution ice mask that can be used in Antarctic modelling.
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.
Charles Pelletier, Thierry Fichefet, Hugues Goosse, Konstanze Haubner, Samuel Helsen, Pierre-Vincent Huot, Christoph Kittel, François Klein, Sébastien Le clec'h, Nicole P. M. van Lipzig, Sylvain Marchi, François Massonnet, Pierre Mathiot, Ehsan Moravveji, Eduardo Moreno-Chamarro, Pablo Ortega, Frank Pattyn, Niels Souverijns, Guillian Van Achter, Sam Vanden Broucke, Alexander Vanhulle, Deborah Verfaillie, and Lars Zipf
Geosci. Model Dev., 15, 553–594, https://doi.org/10.5194/gmd-15-553-2022, https://doi.org/10.5194/gmd-15-553-2022, 2022
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We present PARASO, a circumpolar model for simulating the Antarctic climate. PARASO features five distinct models, each covering different Earth system subcomponents (ice sheet, atmosphere, land, sea ice, ocean). In this technical article, we describe how this tool has been developed, with a focus on the
coupling interfacesrepresenting the feedbacks between the distinct models used for contribution. PARASO is stable and ready to use but is still characterized by significant biases.
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.
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
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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.
Camilla K. Crockart, Tessa R. Vance, Alexander D. Fraser, Nerilie J. Abram, Alison S. Criscitiello, Mark A. J. Curran, Vincent Favier, Ailie J. E. Gallant, Christoph Kittel, Helle A. Kjær, Andrew R. Klekociuk, Lenneke M. Jong, Andrew D. Moy, Christopher T. Plummer, Paul T. Vallelonga, Jonathan Wille, and Lingwei Zhang
Clim. Past, 17, 1795–1818, https://doi.org/10.5194/cp-17-1795-2021, https://doi.org/10.5194/cp-17-1795-2021, 2021
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We present preliminary analyses of the annual sea salt concentrations and snowfall accumulation in a new East Antarctic ice core, Mount Brown South. We compare this record with an updated Law Dome (Dome Summit South site) ice core record over the period 1975–2016. The Mount Brown South record preserves a stronger and inverse signal for the El Niño–Southern Oscillation (in austral winter and spring) compared to the Law Dome record (in summer).
Ruth Mottram, Nicolaj Hansen, Christoph Kittel, J. Melchior van Wessem, Cécile Agosta, Charles Amory, Fredrik Boberg, Willem Jan van de Berg, Xavier Fettweis, Alexandra Gossart, Nicole P. M. van Lipzig, Erik van Meijgaard, Andrew Orr, Tony Phillips, Stuart Webster, Sebastian B. Simonsen, and Niels Souverijns
The Cryosphere, 15, 3751–3784, https://doi.org/10.5194/tc-15-3751-2021, https://doi.org/10.5194/tc-15-3751-2021, 2021
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We compare the calculated surface mass budget (SMB) of Antarctica in five different regional climate models. On average ~ 2000 Gt of snow accumulates annually, but different models vary by ~ 10 %, a difference equivalent to ± 0.5 mm of global sea level rise. All models reproduce observed weather, but there are large differences in regional patterns of snowfall, especially in areas with very few observations, giving greater uncertainty in Antarctic mass budget than previously identified.
Louis Le Toumelin, Charles Amory, Vincent Favier, Christoph Kittel, Stefan Hofer, Xavier Fettweis, Hubert Gallée, and Vinay Kayetha
The Cryosphere, 15, 3595–3614, https://doi.org/10.5194/tc-15-3595-2021, https://doi.org/10.5194/tc-15-3595-2021, 2021
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Snow is frequently eroded from the surface by the wind in Adelie Land (Antarctica) and suspended in the lower atmosphere. By performing model simulations, we show firstly that suspended snow layers interact with incoming radiation similarly to a near-surface cloud. Secondly, suspended snow modifies the atmosphere's thermodynamic structure and energy exchanges with the surface. Our results suggest snow transport by the wind should be taken into account in future model studies over the region.
Thomas James Barnes, Amber Alexandra Leeson, Malcolm McMillan, Vincent Verjans, Jeremy Carter, and Christoph Kittel
The Cryosphere Discuss., https://doi.org/10.5194/tc-2021-214, https://doi.org/10.5194/tc-2021-214, 2021
Revised manuscript not accepted
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We find that the area covered by lakes on George VI ice shelf in 2020 is similar to that seen in other years such as 1989. However, the climate conditions are much more in favour of lakes forming. We find that it is likely that snowfall, and the build up of a surface snow layer limits the development of lakes on the surface of George VI ice shelf in 2020. We also find that in future, snowfall is predicted to decrease, and therefore this limiting effect may be reduced in future.
Xavier Fettweis, Stefan Hofer, Roland Séférian, Charles Amory, Alison Delhasse, Sébastien Doutreloup, Christoph Kittel, Charlotte Lang, Joris Van Bever, Florent Veillon, and Peter Irvine
The Cryosphere, 15, 3013–3019, https://doi.org/10.5194/tc-15-3013-2021, https://doi.org/10.5194/tc-15-3013-2021, 2021
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Without any reduction in our greenhouse gas emissions, the Greenland ice sheet surface mass loss can be brought in line with a medium-mitigation emissions scenario by reducing the solar downward flux at the top of the atmosphere by 1.5 %. In addition to reducing global warming, these solar geoengineering measures also dampen the well-known positive melt–albedo feedback over the ice sheet by 6 %. However, only stronger reductions in solar radiation could maintain a stable ice sheet in 2100.
Paolo Colosio, Marco Tedesco, Roberto Ranzi, and Xavier Fettweis
The Cryosphere, 15, 2623–2646, https://doi.org/10.5194/tc-15-2623-2021, https://doi.org/10.5194/tc-15-2623-2021, 2021
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We use a new satellite dataset to study the spatiotemporal evolution of surface melting over Greenland at an enhanced resolution of 3.125 km. Using meteorological data and the MAR model, we observe that a dynamic algorithm can best detect surface melting. We found that the melting season is elongating, the melt extent is increasing and that high-resolution data better describe the spatiotemporal evolution of the melting season, which is crucial to improve estimates of sea level rise.
Charles Amory, Christoph Kittel, Louis Le Toumelin, Cécile Agosta, Alison Delhasse, Vincent Favier, and Xavier Fettweis
Geosci. Model Dev., 14, 3487–3510, https://doi.org/10.5194/gmd-14-3487-2021, https://doi.org/10.5194/gmd-14-3487-2021, 2021
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This paper presents recent developments in the drifting-snow scheme of the regional climate model MAR and its application to simulate drifting snow and the surface mass balance of Adélie Land in East Antarctica. The model is extensively described and evaluated against a multi-year drifting-snow dataset and surface mass balance estimates available in the area. The model sensitivity to input parameters and improvements over a previously published version are also assessed.
Christoph Kittel, Charles Amory, Cécile Agosta, Nicolas C. Jourdain, Stefan Hofer, Alison Delhasse, Sébastien Doutreloup, Pierre-Vincent Huot, Charlotte Lang, Thierry Fichefet, and Xavier Fettweis
The Cryosphere, 15, 1215–1236, https://doi.org/10.5194/tc-15-1215-2021, https://doi.org/10.5194/tc-15-1215-2021, 2021
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The future surface mass balance (SMB) of the Antarctic ice sheet (AIS) will influence the ice dynamics and the contribution of the ice sheet to the sea level rise. We investigate the AIS sensitivity to different warmings using physical and statistical downscaling of CMIP5 and CMIP6 models. Our results highlight a contrasting effect between the grounded ice sheet (where the SMB is projected to increase) and ice shelves (where the future SMB depends on the emission scenario).
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
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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.
Marion Donat-Magnin, Nicolas C. Jourdain, Christoph Kittel, Cécile Agosta, Charles Amory, Hubert Gallée, Gerhard Krinner, and Mondher Chekki
The Cryosphere, 15, 571–593, https://doi.org/10.5194/tc-15-571-2021, https://doi.org/10.5194/tc-15-571-2021, 2021
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We simulate the West Antarctic climate in 2100 under increasing greenhouse gases. Future accumulation over the ice sheet increases, which reduces sea level changing rate. Surface ice-shelf melt rates increase until 2100. Some ice shelves experience a lot of liquid water at their surface, which indicates potential ice-shelf collapse. In contrast, no liquid water is found over other ice shelves due to huge amounts of snowfall that bury liquid water, favouring refreezing and ice-shelf stability.
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.
Martin Ménégoz, Evgenia Valla, Nicolas C. Jourdain, Juliette Blanchet, Julien Beaumet, Bruno Wilhelm, Hubert Gallée, Xavier Fettweis, Samuel Morin, and Sandrine Anquetin
Hydrol. Earth Syst. Sci., 24, 5355–5377, https://doi.org/10.5194/hess-24-5355-2020, https://doi.org/10.5194/hess-24-5355-2020, 2020
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The study investigates precipitation changes in the Alps, using observations and a 7 km resolution climate simulation over 1900–2010. An increase in mean precipitation is found in winter over the Alps, whereas a drying occurred in summer in the surrounding plains. A general increase in the daily annual maximum of precipitation is evidenced (20 to 40 % per century), suggesting an increase in extreme events that is significant only when considering long time series, typically 50 to 80 years.
Kenneth D. Mankoff, Brice Noël, Xavier Fettweis, Andreas P. Ahlstrøm, William Colgan, Ken Kondo, Kirsty Langley, Shin Sugiyama, Dirk van As, and Robert S. Fausto
Earth Syst. Sci. Data, 12, 2811–2841, https://doi.org/10.5194/essd-12-2811-2020, https://doi.org/10.5194/essd-12-2811-2020, 2020
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This work partitions regional climate model (RCM) runoff from the MAR and RACMO RCMs to hydrologic outlets at the ice margin and coast. Temporal resolution is daily from 1959 through 2019. Spatial grid is ~ 100 m, resolving individual streams. In addition to discharge at outlets, we also provide the streams, outlets, and basin geospatial data, as well as a script to query and access the geospatial or time series discharge data from the data files.
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
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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.
Xavier Fettweis, Stefan Hofer, Uta Krebs-Kanzow, Charles Amory, Teruo Aoki, Constantijn J. Berends, Andreas Born, Jason E. Box, Alison Delhasse, Koji Fujita, Paul Gierz, Heiko Goelzer, Edward Hanna, Akihiro Hashimoto, Philippe Huybrechts, Marie-Luise Kapsch, Michalea D. King, Christoph Kittel, Charlotte Lang, Peter L. Langen, Jan T. M. Lenaerts, Glen E. Liston, Gerrit Lohmann, Sebastian H. Mernild, Uwe Mikolajewicz, Kameswarrao Modali, Ruth H. Mottram, Masashi Niwano, Brice Noël, Jonathan C. Ryan, Amy Smith, Jan Streffing, Marco Tedesco, Willem Jan van de Berg, Michiel van den Broeke, Roderik S. W. van de Wal, Leo van Kampenhout, David Wilton, Bert Wouters, Florian Ziemen, and Tobias Zolles
The Cryosphere, 14, 3935–3958, https://doi.org/10.5194/tc-14-3935-2020, https://doi.org/10.5194/tc-14-3935-2020, 2020
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We evaluated simulated Greenland Ice Sheet surface mass balance from 5 kinds of models. While the most complex (but expensive to compute) models remain the best, the faster/simpler models also compare reliably with observations and have biases of the same order as the regional models. Discrepancies in the trend over 2000–2012, however, suggest that large uncertainties remain in the modelled future SMB changes as they are highly impacted by the meltwater runoff biases over the current climate.
Kang Yang, Aleah Sommers, Lauren C. Andrews, Laurence C. Smith, Xin Lu, Xavier Fettweis, and Manchun Li
The Cryosphere, 14, 3349–3365, https://doi.org/10.5194/tc-14-3349-2020, https://doi.org/10.5194/tc-14-3349-2020, 2020
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This study compares hourly supraglacial moulin discharge simulations from three surface meltwater routing models. Results show that these models are superior to simply using regional climate model runoff without routing, but different routing models, different-spatial-resolution DEMs, and parameterized seasonal evolution of supraglacial stream and river networks induce significant variability in diurnal moulin discharges and corresponding subglacial effective pressures.
Heiko Goelzer, Sophie Nowicki, Anthony Payne, Eric Larour, Helene Seroussi, William H. Lipscomb, Jonathan Gregory, Ayako Abe-Ouchi, Andrew Shepherd, Erika Simon, Cécile Agosta, Patrick Alexander, Andy Aschwanden, Alice Barthel, Reinhard Calov, Christopher Chambers, Youngmin Choi, Joshua Cuzzone, Christophe Dumas, Tamsin Edwards, Denis Felikson, Xavier Fettweis, Nicholas R. Golledge, Ralf Greve, Angelika Humbert, Philippe Huybrechts, Sebastien Le clec'h, Victoria Lee, Gunter Leguy, Chris Little, Daniel P. Lowry, Mathieu Morlighem, Isabel Nias, Aurelien Quiquet, Martin Rückamp, Nicole-Jeanne Schlegel, Donald A. Slater, Robin S. Smith, Fiamma Straneo, Lev Tarasov, Roderik van de Wal, and Michiel van den Broeke
The Cryosphere, 14, 3071–3096, https://doi.org/10.5194/tc-14-3071-2020, https://doi.org/10.5194/tc-14-3071-2020, 2020
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In this paper we use a large ensemble of Greenland ice sheet models forced by six different global climate models to project ice sheet changes and sea-level rise contributions over the 21st century.
The results for two different greenhouse gas concentration scenarios indicate that the Greenland ice sheet will continue to lose mass until 2100, with contributions to sea-level rise of 90 ± 50 mm and 32 ± 17 mm for the high (RCP8.5) and low (RCP2.6) scenario, respectively.
Shujie Wang, Marco Tedesco, Patrick Alexander, Min Xu, and Xavier Fettweis
The Cryosphere, 14, 2687–2713, https://doi.org/10.5194/tc-14-2687-2020, https://doi.org/10.5194/tc-14-2687-2020, 2020
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Glacial algal blooms play a significant role in darkening the Greenland Ice Sheet during summertime. The dark pigments generated by glacial algae could substantially reduce the bare ice albedo and thereby enhance surface melt. We used satellite data to map the spatial distribution of glacial algae and characterized the seasonal growth pattern and interannual trends of glacial algae in southwestern Greenland. Our study is important for bridging microbial activities with ice sheet mass balance.
Cited articles
Adusumilli, S., Fricker, H. A., Medley, B., Padman, L., and Siegfried, M. R.:
Interannual variations in meltwater input to the Southern Ocean from
Antarctic ice shelves, Nat. Geosci., 13, 616–620,
https://doi.org/10.1038/s41561-020-0616-z, 2020. a
Amante, C. and Eakins, B. W.: ETOPO1 arc-minute global relief model:
procedures, data sources and analysis, NOAA technical memorandum NESDIS
NGDC-24, https://repository.library.noaa.gov/view/noaa/1163 (last access: 20 October 2022), 2009. a
Ashcraft, I. S. and Long, D. G.: Comparison of methods for melt detection over
Greenland using active and passive microwave measurements, Int.
J. Remote Sens., 27, 2469–2488, https://doi.org/10.1080/01431160500534465,
2006. 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
Barrand, N. E., Vaughan, D. G., Steiner, N., Tedesco, M., Kuipers Munneke, P.,
van den Broeke, M. R., and Hosking, J. S.: Trends in Antarctic Peninsula
surface melting conditions from observations and regional climate modeling,
J. Geophys. Res.-Earth Surf., 118, 315–330,
https://doi.org/10.1029/2012JF002559, 2013. a
Bell, R. E., Banwell, A. F., Trusel, L. D., and Kingslake, J.: Antarctic
surface hydrology and impacts on ice-sheet mass balance, Nat. Clim.
Change, 8, 1044–1052, https://doi.org/10.1038/s41558-018-0326-3, 2018. a, b
Brun, E., David, P., Sudul, M., and Brunot, G.: A numerical model to simulate
snow-cover stratigraphy for operational avalanche forecasting, J. Glaciol., 38, 13–22, https://doi.org/10.3189/s0022143000009552, 1992. a
Church, J., Clark, P., Cazenave, A., Gregory, J., Jevrejeva, S., Levermann, A.,
Merrifield, M., Milne, G., Nerem, R., Nunn, P., Payne, A., Pfeffer, W.,
Stammer, D., and Unnikrishnan, A.: Sea Level Change, in: Climate Change 2013:
The Physical Science Basis. Contribution of Working Group I to the Fifth
Assessment Report of the Intergovernmental Panel on Climate Change, edited by:
Stocker, T., Qin, D., Plattner, G.-K., Tignor, M., Allen, S., Boschung, J.,
Nauels, A., Xia, Y., Bex, V., and Midgley, P., Cambridge University Press,
Cambridge, United Kingdom and New York, NY, USA, https://www.ipcc.ch/site/assets/uploads/2018/02/WG1AR5_Chapter13_FINAL.pdf (last access: 6 October 2023), 2013. a
Chuter, S. J., Zammit-Mangion, A., Rougier, J., Dawson, G., and Bamber, J. L.: Mass evolution of the Antarctic Peninsula over the last 2 decades from a joint Bayesian inversion, The Cryosphere, 16, 1349–1367, https://doi.org/10.5194/tc-16-1349-2022, 2022. a, b
Coléou, C. and Lesaffre, B.: Irreducible water saturation in snow:
Experimental results in a cold laboratory, Ann. Glaciol., 26, 64–68,
https://doi.org/10.1017/S0260305500014579, 1998. a
Colosio, P., Tedesco, M., Ranzi, R., and Fettweis, X.: Surface melting over the Greenland ice sheet derived from enhanced resolution passive microwave brightness temperatures (1979–2019), The Cryosphere, 15, 2623–2646, https://doi.org/10.5194/tc-15-2623-2021, 2021. a, b
Datta, R. T., Tedesco, M., Agosta, C., Fettweis, X., Kuipers Munneke, P., and van den Broeke, M. R.: Melting over the northeast Antarctic Peninsula (1999–2009): evaluation of a high-resolution regional climate model, The Cryosphere, 12, 2901–2922, https://doi.org/10.5194/tc-12-2901-2018, 2018. a, b
Datta, R. T., Tedesco, M., Fettweis, X., Agosta, C., Lhermitte, S., Lenaerts,
J. T. M., and Wever, N.: The Effect of Foehn-Induced Surface Melt on Firn
Evolution Over the Northeast Antarctic Peninsula, Geophys. Res. Lett., 46, 3822–3831, https://doi.org/10.1029/2018GL080845, 2019. a
Delhasse, A., Kittel, C., Amory, C., Hofer, S., van As, D., S. Fausto, R., and Fettweis, X.: Brief communication: Evaluation of the near-surface climate in ERA5 over the Greenland Ice Sheet, The Cryosphere, 14, 957–965, https://doi.org/10.5194/tc-14-957-2020, 2020. a, b
Dethinne, T.: MAR RS assimilation, Zenodo [code], https://doi.org/10.5281/zenodo.8391577, 2023. a
Donat-Magnin, M., Jourdain, N. C., Kittel, C., Agosta, C., Amory, C., Gallée, H., Krinner, G., and Chekki, M.: Future surface mass balance and surface melt in the Amundsen sector of the West Antarctic Ice Sheet, The Cryosphere, 15, 571–593, https://doi.org/10.5194/tc-15-571-2021, 2021. a
Elachi, C. and van Zyl, J.: Nature and Properties of Electromagnetic Waves, in:
Introduction to the Physics and Techniques of Remote Sensing, Chap. 2,
23–50, John Wiley and Sons, Ltd, https://doi.org/10.1002/0471783390.ch2, 2006. a, b
ESA: The Sentinel-1 Toolbox,
https://sentinel.esa.int/web/sentinel/toolboxes/sentinel-1 (last access: 19 October 2022), 2022. a
ESA: Sentinel-1,
https://sentinel.esa.int/web/sentinel/missions/sentinel-1 (last access: 24 May 2023), 2023. a
Evensen, G.: Data assimilation: The ensemble kalman filter, Springer Berlin,
Heidelberg, https://doi.org/10.1007/978-3-642-03711-5, 2009. a
Fahnestock, M. A., Abdalati, W., and Shuman, C. A.: Long melt seasons on ice
shelves of the Antarctic Peninsula: an analysis using satellite-based
microwave emission measurements, Ann. Glaciol., 34, 127–133,
https://doi.org/10.3189/172756402781817798, 2002. a
Favier, L. and Pattyn, F.: Antarctic ice rise formation, evolution, and
stability, Geophys. Res. Lett., 42, 4456–4463,
https://doi.org/10.1002/2015GL064195, 2015. a, b
Fettweis, X., Tedesco, M., van den Broeke, M., and Ettema, J.: Melting trends over the Greenland ice sheet (1958–2009) from spaceborne microwave data and regional climate models, The Cryosphere, 5, 359–375, https://doi.org/10.5194/tc-5-359-2011, 2011. a
Fettweis, X., Hofer, S., Séférian, R., Amory, C., Delhasse, A., Doutreloup, S., Kittel, C., Lang, C., Van Bever, J., Veillon, F., and Irvine, P.: Brief communication: Reduction in the future Greenland ice sheet surface melt with the help of solar geoengineering, The Cryosphere, 15, 3013–3019, https://doi.org/10.5194/tc-15-3013-2021, 2021. a
Fretwell, P., Pritchard, H. D., Vaughan, D. G., Bamber, J. L., Barrand, N. E., Bell, R., Bianchi, C., Bingham, R. G., Blankenship, D. D., Casassa, G., Catania, G., Callens, D., Conway, H., Cook, A. J., Corr, H. F. J., Damaske, D., Damm, V., Ferraccioli, F., Forsberg, R., Fujita, S., Gim, Y., Gogineni, P., Griggs, J. A., Hindmarsh, R. C. A., Holmlund, P., Holt, J. W., Jacobel, R. W., Jenkins, A., Jokat, W., Jordan, T., King, E. C., Kohler, J., Krabill, W., Riger-Kusk, M., Langley, K. A., Leitchenkov, G., Leuschen, C., Luyendyk, B. P., Matsuoka, K., Mouginot, J., Nitsche, F. O., Nogi, Y., Nost, O. A., Popov, S. V., Rignot, E., Rippin, D. M., Rivera, A., Roberts, J., Ross, N., Siegert, M. J., Smith, A. M., Steinhage, D., Studinger, M., Sun, B., Tinto, B. K., Welch, B. C., Wilson, D., Young, D. A., Xiangbin, C., and Zirizzotti, A.: Bedmap2: improved ice bed, surface and thickness datasets for Antarctica, The Cryosphere, 7, 375–393, https://doi.org/10.5194/tc-7-375-2013, 2013. a
Fricker, H. A., Arndt, P., Brunt, K. M., Datta, R. T., Fair, Z., Jasinski,
M. F., Kingslake, J., Magruder, L. A., Moussavi, M., Pope, A., Spergel,
J. J., Stoll, J. D., and Wouters, B.: ICESat-2 Meltwater Depth Estimates:
Application to Surface Melt on Amery Ice Shelf, East Antarctica, Geophys. Res. Lett., 48, e2020GL090550, https://doi.org/10.1029/2020GL090550, 2021. a, b
Gallée, H. and Schayes, G.: Development of a Three-Dimensional Meso-γ
Primitive Equation Model: Katabatic Winds Simulation in the Area of Terra
Nova Bay, Antarctica, Mon. Weather Rev., 122, 671–685,
https://doi.org/10.1175/1520-0493(1994)122<0671:DOATDM>2.0.CO;2, 1994. a
GEE: Sentinel-1 Algorithms,
https://developers.google.com/earth-engine/guides/sentinel1 (last access: 19 October 2022), 2022. 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,
9, https://doi.org/10.1029/2020GL091733, 2021. a, b
Glaude, Q., Amory, C., Berger, S., Derauw, D., Pattyn, F., Barbier, C., and
Orban, A.: Empirical Removal of Tides and Inverse Barometer Effect on DInSAR
From Double DInSAR and a Regional Climate Model, IEEE J. Sel.
Top. Appl. Earth Obs., 13, 4085–4094,
https://doi.org/10.1109/JSTARS.2020.3008497, 2020. a
Gorelick, N., Hancher, M., Dixon, M., Ilyushchenko, S., Thau, D., and Moore,
R.: Google Earth Engine: Planetary-scale geospatial analysis for everyone,
Remote Sens. Environ., 202, 18–27, https://doi.org/10.1016/j.rse.2017.06.031, 2017. 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., De Chiara, G., 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. Meteor. Soc., 146,
1999–2049, https://doi.org/10.1002/qj.3803, 2020. a, b, c
Husman, S. D. R., Zhongyang, H., Wouters, B., Munneke, P. K., Veldhuijsen, S.,
and Lhermitte, S.: Remote Sensing of Surface Melt on Antarctica:
Opportunities and Challenges, J. Sel. Top. Appl. Earth
Obs., 16, 2462–2480, https://doi.org/10.1109/JSTARS.2022.3216953, 2022. a
Jakobs, C. L., Reijmer, C. H., Smeets, C. J., Trusel, L. D., Berg, W. J. V. D.,
Broeke, M. R. V. D., and Wessem, J. M. V.: 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, dataset, 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, 2022. a
Kittel, C.: Present and future sensitivity of the Antarctic surface mass
balance to oceanic and atmospheric forcings: insights with the regional
climate model MAR, PhD thesis, ULiège – Université de Liège,
https://hdl.handle.net/2268/258491 (last access: 28 September 2023), 2021. 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, b
Kittel, C., Fettweis, X., Picard, G., and Gourmelen, N.: Assimilation of
satellite-derived melt extent increases melt simulated by MAR over the
Amundsen sector (West Antarctica), Bulletin de la Société Géographique de
Liège, 78, 87–99, https://doi.org/10.25518/0770-7576.6616, 2022. a, b, c
Koskinen, J., Pulliainen, J., and Hallikainen, M.: The use of ERS-1 SAR data in
snow melt monitoring, IEEE T. Geosci. Remote, 35,
601–610, https://doi.org/10.1109/36.581975, 1997. a
Kuipers Munneke, P., Luckman, A. J., Bevan, S. L., Smeets, C. J. P. P.,
Gilbert, E., van den Broeke, M. R., Wang, W., Zender, C., Hubbard, B.,
Ashmore, D., Orr, A., King, J. C., and Kulessa, B.: Intense Winter Surface
Melt on an Antarctic Ice Shelf, Geophys. Res. Lett., 45, 7615–7623,
https://doi.org/10.1029/2018GL077899, 2018. a
Lai, C.-Y., Kingslake, J., Wearing, M. G., Chen, P.-H. C., Gentine, P., Li, H.,
Spergel, J. J., and van Wessem, J. M.: Vulnerability of Antarctica’s ice
shelves to meltwater-driven fracture, Nature, 584, 574–578,
https://doi.org/10.1038/s41586-020-2627-8, 2020. a
Lambin, C., Fettweis, X., Kittel, C., Fonder, M., and Ernst, D.: Assessment of
future wind speed and wind power changes over South Greenland using the
Modèle Atmosphérique Régional regional climate model, Int.
J. Climatol., 43, 558–574, https://doi.org/10.1002/joc.7795, 2022. 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, b
Lindsley, R. D. and Long, D. G.: Enhanced-Resolution Reconstruction of ASCAT
Backscatter Measurements, IEEE T. Geosci. Remote,
54, 2589–2601, https://doi.org/10.1109/TGRS.2015.2503762, 2016. a
MAR model: MAR, http://www.mar.cnrs.fr (last access:
10 November 2022), 2022. a
MAR Team: MARv3.12, MAR Team [code], https://gitlab.com/Mar-Group/ (last access: 16 November 2022), 2022. 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
Morcrette, J.-J.: Assessment of the ECMWF Model Cloudiness and Surface
Radiation Fields at the ARM SGP Site, Mon. Weather Rev., 130, 257–277, https://doi.org/10.1175/1520-0493(2002)130<0257:AOTEMC>2.0.CO;2, 2002. a
Moreira, A., Prats-Iraola, P., Younis, M., Krieger, G., Hajnsek, I., and
Papathanassiou, K. P.: A tutorial on synthetic aperture radar, IEEE
Geosci. Remote Sens. Mag., 1, 6–43,
https://doi.org/10.1109/MGRS.2013.2248301, 2013. a
Mottram, R., Hansen, N., Kittel, C., van Wessem, J. M., Agosta, C., Amory, C., Boberg, F., van de Berg, W. J., Fettweis, X., Gossart, A., van Lipzig, N. P. M., van Meijgaard, E., Orr, A., Phillips, T., Webster, S., Simonsen, S. B., and Souverijns, N.: What is the surface mass balance of Antarctica? An intercomparison of regional climate model estimates, The Cryosphere, 15, 3751–3784, https://doi.org/10.5194/tc-15-3751-2021, 2021. a
Mullissa, A., Vollrath, A., Odongo-Braun, C., Slagter, B., Balling, J., Gou,
Y., Gorelick, N., and Reiche, J.: Sentinel-1 SAR Backscatter Analysis Ready
Data Preparation in Google Earth Engine, Remote Sens., 13, 1954,
https://doi.org/10.3390/rs13101954, 2021. a
Mätzler, C.: Applications of the interaction of microwaves with the natural
snow cover, Remote Sens. Rev., 2, 259–387,
https://doi.org/10.1080/02757258709532086, 1987. a
Nagler, T. and Rott, H.: Retrieval of wet snow by means of multitemporal SAR
data, IEEE T. Geosci. Remote, 38, 754–765,
https://doi.org/10.1109/36.842004, 2000. a, b
Nagler, T., Rott, H., Ripper, E., Bippus, G., and Hetzenecker, M.: Advancements
for Snowmelt Monitoring by Means of Sentinel-1 SAR, Remote Sens., 8, 348,
https://doi.org/10.3390/rs8040348, 2016. a
Navari, M., Margulis, S. A., Tedesco, M., Fettweis, X., and Alexander, P. M.:
Improving Greenland Surface Mass Balance Estimates Through the Assimilation
of MODIS Albedo: A Case Study Along the K-Transect, Geophys. Res. Lett., 45, 6549–6556, https://doi.org/10.1029/2018GL078448, 2018. a
Noël, B., van de Berg, W. J., Lhermitte, S., Wouters, B., Machguth, H., Howat,
I., Citterio, M., Moholdt, G., Lenaerts, J. T. M., and van den Broeke, M. R.:
A tipping point in refreezing accelerates mass loss of Greenland’s glaciers
and ice caps, Nat. Commun., 8, 14730, https://doi.org/10.1038/ncomms14730,
2017. a
Paolo, F. S., Fricker, H. A., and Padman, L.: Volume loss from Antarctic ice
shelves is accelerating, Science, 348, 327–331,
https://doi.org/10.1126/science.aaa0940, 2015. a, b
Parkinson, C.: Satellite Passive Microwave Measurements of Sea Ice, in:
Encyclopedia of Ocean Sciences, edited by: Steele, J. H.,
Academic Press, Oxford, 2531–2539, https://doi.org/10.1006/rwos.2001.0336, 2001. a
Picard, G. and Fily, M.: Surface melting observations in Antarctica by
microwave radiometers: Correcting 26-year time series from changes in
acquisition hours, Remote Sens. Environ., 104, 325–336,
https://doi.org/10.1016/j.rse.2006.05.010, 2006. a, b
Ridder, K. D. and Gallée, H.: Land Surface-Induced Regional Climate Change
in Southern Israel, J. Appl. Meteorol., 37, 1470–1485,
https://doi.org/10.1175/1520-0450(1998)037<1470:LSIRCC>2.0.CO;2, 1998. a
Rignot, E., Mouginot, J., Scheuchl, B., van den Broeke, M., van Wessem, M. J.,
and Morlighem, M.: Four decades of Antarctic Ice Sheet mass balance from
1979–2013;2017, P. Natl. Acad. Sci. USA, 116,
1095–1103, https://doi.org/10.1073/pnas.1812883116, 2019. a, b
Scambos, T., Hulbe, C., and Fahnestock, M.: Climate-Induced Ice Shelf
Disintegration in the Antarctic Peninsula, in: Antarctic Peninsula Climate
Variability: Historical and Paleoenvironmental Perspectives,
American Geophysical Union, 79–92, https://doi.org/10.1029/AR079p0079, 2003. a
Slater, T., Shepherd, A., McMillan, M., Leeson, A., Gilbert, L., Muir, A.,
Munneke, P. K., Noël, B., Fettweis, X., van den Broeke, M., and Briggs, K.:
Increased variability in Greenland Ice Sheet runoff from satellite
observations, Nat. Commun., 12, 6069,
https://doi.org/10.1038/s41467-021-26229-4, 2021. a
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., Abdalati, W., and Zwally, H. J.: Persistent surface snowmelt over
Antarctica (1987–2006) from 19.35 GHz brightness temperatures, Geophys. Res. Lett., 34, 1–6, https://doi.org/10.1029/2007GL031199, 2007. a
The IMBIE Team: Mass balance of the Antarctic Ice Sheet from 1992 to 2017,
Nature, 558, 219–222, https://doi.org/10.1038/s41586-018-0179-y, 2018. a
Trusel, L. D., Frey, K. E., Das, S. B., Munneke, P. K., 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., Munneke, P. K.,
Meijgaard, E. V., and Broeke, M. R. V. D.: Divergent trajectories of
Antarctic surface melt under two twenty-first-century climate scenarios,
Nat. Geosci., 8, 927–932, https://doi.org/10.1038/ngeo2563, 2015. 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, Nat. Commun., 7, 10266, https://doi.org/10.1038/ncomms10266, 2016. a
Wille, J. D., Favier, V., Jourdain, N. C., Kittel, C., Turton, J. V., Agosta,
C., Gorodetskaya, I. V., Picard, G., Codron, F., Santos, C. L.-D., Amory, C.,
Fettweis, X., Blanchet, J., Jomelli, V., and Berchet, A.: Intense atmospheric
rivers can weaken ice shelf stability at the Antarctic Peninsula,
Commun. Earth Environ., 3, 90, https://doi.org/10.1038/s43247-022-00422-9,
2022. 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
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.
We investigate the sensitivity of the regional climate model
Modèle Atmosphérique Régional(MAR)...
