Articles | Volume 16, issue 9
https://doi.org/10.5194/tc-16-3815-2022
© 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-16-3815-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
23 Sep 2022
Research article |
| 23 Sep 2022
| 23 Sep 2022
Variability in Antarctic surface climatology across regional climate models and reanalysis datasets
Department of Mathematics and Statistics, Lancaster University, Lancaster, United Kingdom
Amber Leeson
Lancaster Environment Centre, Lancaster University, Lancaster, United Kingdom
Andrew Orr
British Antarctic Survey, High Cross, Madingley Road, Cambridge, United Kingdom
Christoph Kittel
Laboratory of Climatology, Department of Geography, SPHERES, University of Liège, Liège, Belgium
J. Melchior van Wessem
Institute for Marine and Atmospheric research Utrecht, Utrecht University, Utrecht, the Netherlands
Related authors
Jeremy Carter, Erick A. Chacón-Montalván, and Amber Leeson
Geosci. Model Dev., 17, 5733–5757, https://doi.org/10.5194/gmd-17-5733-2024, https://doi.org/10.5194/gmd-17-5733-2024, 2024
Short summary
Short summary
Climate models are essential tools in the study of climate change and its wide-ranging impacts on life on Earth. However, the output is often afflicted with some bias. In this paper, a novel model is developed to predict and correct bias in the output of climate models. The model captures uncertainty in the correction and explicitly models underlying spatial correlation between points. These features are of key importance for climate change impact assessments and resulting decision-making.
Hamish D. Pritchard, Edward C. King, David J. Goodger, Douglas Boyle, Daniel N. Goldberg, Beatriz Recinos, Andrew Orr, and Dhananjay Regmi
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-519, https://doi.org/10.5194/essd-2025-519, 2025
Preprint under review for ESSD
Short summary
Short summary
We present a new and uniquely extensive dataset of glacier thickness from the Khumbu Himal around Mount Everest that stretches for 119 km, doubling the extent of thickness measurements in High Mountain Asia. Such measurements are key inputs for models that estimate how much ice is stored on the whole mountain range scale and for models that predict how this ice reserve will change in future, and what impact this will have on water supply for the large populations living downstream.
Marc Girona-Mata, Andrew Orr, Martin Widmann, Daniel Bannister, Ghulam Hussain Dars, Scott Hosking, Jesse Norris, David Ocio, Tony Phillips, Jakob Steiner, and Richard E. Turner
Hydrol. Earth Syst. Sci., 29, 3073–3100, https://doi.org/10.5194/hess-29-3073-2025, https://doi.org/10.5194/hess-29-3073-2025, 2025
Short summary
Short summary
We introduce a novel method for improving daily precipitation maps in mountain regions and pilot it across three basins in the Hindu Kush Himalaya (HKH). The approach leverages climate model and weather station data, along with statistical or machine learning techniques. Our results show that this approach outperforms traditional methods, especially in remote ungauged areas, suggesting that it could be used to improve precipitation maps across much of the HKH, as well as other mountain regions.
Nicolas C. Jourdain, Charles Amory, Christoph Kittel, and Gaël Durand
The Cryosphere, 19, 1641–1674, https://doi.org/10.5194/tc-19-1641-2025, https://doi.org/10.5194/tc-19-1641-2025, 2025
Short summary
Short summary
A mixed statistical–physical approach is used to reproduce the behaviour of a regional climate model. From that, we estimate the contribution of snowfall and melting at the surface of the Antarctic Ice Sheet to changes in global mean sea level. We also investigate the impact of surface melting in a warmer climate on the stability of the Antarctic ice shelves that provide back stress on the ice flow to the ocean.
Cécile Davrinche, Anaïs Orsi, Charles Amory, Christoph Kittel, and Cécile Agosta
EGUsphere, https://doi.org/10.5194/egusphere-2025-1419, https://doi.org/10.5194/egusphere-2025-1419, 2025
Short summary
Short summary
We analyse 4 projections of winter surface winds in Antarctica. On the continent, projected changes in wind speed by 2100 reveal opposing trends depending on the area and model. Nevertheless, models agree on a strengthening of surface winds in Adélie Land for example and a weakening in some coastal areas. Lastly, we attribute strengthening of near-surface winds to changes in the large-sale atmospheric circulation and weakening of near-surface to changes in the structure of the lower atmosphere.
Alison Delhasse, Christoph Kittel, and Johanna Beckmann
EGUsphere, https://doi.org/10.5194/egusphere-2025-709, https://doi.org/10.5194/egusphere-2025-709, 2025
Short summary
Short summary
This study explores how the Greenland Ice Sheet (GrIS) responds to different levels of stabilized global warming, and if the climate cools back. Our findings show that global temperature increases beyond +2.3 °C mark a critical threshold. We also highlight the importance of limiting warming to avoid irreversible ice loss, as well as the potential for recovery after temporarily exceeding warming thresholds if action is taken quickly to lower global temperatures.
Emily Glen, Amber Leeson, Alison F. Banwell, Jennifer Maddalena, Diarmuid Corr, Olivia Atkins, Brice Noël, and Malcolm McMillan
The Cryosphere, 19, 1047–1066, https://doi.org/10.5194/tc-19-1047-2025, https://doi.org/10.5194/tc-19-1047-2025, 2025
Short summary
Short summary
We compare surface meltwater features from optical satellite imagery in the Russell–Leverett glacier catchment during high (2019) and low (2018) melt years. In the high melt year, features appear at higher elevations, meltwater systems are more connected, small lakes are more frequent, and slush is more widespread. These findings provide insights into how a warming climate, where high melt years become common, could alter meltwater distribution and dynamics on the Greenland Ice Sheet.
Justine Caillet, Nicolas C. Jourdain, Pierre Mathiot, Fabien Gillet-Chaulet, Benoit Urruty, Clara Burgard, Charles Amory, Mondher Chekki, and Christoph Kittel
Earth Syst. Dynam., 16, 293–315, https://doi.org/10.5194/esd-16-293-2025, https://doi.org/10.5194/esd-16-293-2025, 2025
Short summary
Short summary
Internal climate variability, resulting from processes intrinsic to the climate system, modulates the Antarctic response to climate change by delaying or offsetting its effects. Using climate and ice-sheet models, we highlight that irreducible internal climate variability significantly enlarges the likely range of Antarctic contribution to sea-level rise until 2100. Thus, we recommend considering internal climate variability as a source of uncertainty for future ice-sheet projections.
Ella Gilbert, Denis Pishniak, José Abraham Torres, Andrew Orr, Michelle Maclennan, Nander Wever, and Kristiina Verro
The Cryosphere, 19, 597–618, https://doi.org/10.5194/tc-19-597-2025, https://doi.org/10.5194/tc-19-597-2025, 2025
Short summary
Short summary
We use three sophisticated climate models to examine extreme precipitation in a critical region of West Antarctica. We found that rainfall probably occurred during the two cases we examined and that it was generated by the interaction of air with steep topography. Our results show that kilometre-scale models are useful tools for exploring extreme precipitation in this region and that more observations of rainfall are needed.
Ryan Hossaini, David Sherry, Zihao Wang, Martyn P. Chipperfield, Wuhu Feng, David E. Oram, Karina E. Adcock, Stephen A. Montzka, Isobel J. Simpson, Andrea Mazzeo, Amber A. Leeson, Elliot Atlas, and Charles C.-K. Chou
Atmos. Chem. Phys., 24, 13457–13475, https://doi.org/10.5194/acp-24-13457-2024, https://doi.org/10.5194/acp-24-13457-2024, 2024
Short summary
Short summary
DCE (1,2-dichloroethane) is an industrial chemical used to produce PVC (polyvinyl chloride). We analysed DCE production data to estimate global DCE emissions (2002–2020). The emissions were included in an atmospheric model and evaluated by comparing simulated DCE to DCE measurements in the troposphere. We show that DCE contributes ozone-depleting Cl to the stratosphere and that this has increased with increasing DCE emissions. DCE’s impact on stratospheric O3 is currently small but non-zero.
Kenza Tazi, Andrew Orr, Javier Hernandez-González, Scott Hosking, and Richard E. Turner
Hydrol. Earth Syst. Sci., 28, 4903–4925, https://doi.org/10.5194/hess-28-4903-2024, https://doi.org/10.5194/hess-28-4903-2024, 2024
Short summary
Short summary
This work aims to improve the understanding of precipitation patterns in High-mountain Asia, a crucial water source for around 1.9 billion people. Through a novel machine learning method, we generate high-resolution precipitation predictions, including the likelihoods of floods and droughts. Compared to state-of-the-art methods, our method is simpler to implement and more suitable for small datasets. The method also shows accuracy comparable to or better than existing benchmark datasets.
Sanne B. M. Veldhuijsen, Willem Jan van de Berg, Peter Kuipers Munneke, Nicolaj Hansen, Fredrik Boberg, Christoph Kittel, Charles Amory, and Michiel R. van den Broeke
EGUsphere, https://doi.org/10.5194/egusphere-2024-2855, https://doi.org/10.5194/egusphere-2024-2855, 2024
Short summary
Short summary
Perennial firn aquifers (PFAs), year-round bodies of liquid water within firn, can potentially impact ice-shelf and ice-sheet stability. We developed a fast XGBoost firn emulator to predict 21st-century distribution of PFAs in Antarctica for 12 climatic forcings datasets. Our findings suggest that under low emission scenarios, PFAs remain confined to the Antarctic Peninsula. However, under a high-emission scenario, PFAs are projected to expand to a region in West Antarctica and East Antarctica.
Xavier J. Levine, Ryan S. Williams, Gareth Marshall, Andrew Orr, Lise Seland Graff, Dörthe Handorf, Alexey Karpechko, Raphael Köhler, René R. Wijngaard, Nadine Johnston, Hanna Lee, Lars Nieradzik, and Priscilla A. Mooney
Earth Syst. Dynam., 15, 1161–1177, https://doi.org/10.5194/esd-15-1161-2024, https://doi.org/10.5194/esd-15-1161-2024, 2024
Short summary
Short summary
While the most recent climate projections agree that the Arctic is warming, differences remain in how much and in other climate variables such as precipitation. This presents a challenge for stakeholders who need to develop mitigation and adaptation strategies. We tackle this problem by using the storyline approach to generate four plausible and actionable realisations of end-of-century climate change for the Arctic, spanning its most likely range of variability.
Jeremy Carter, Erick A. Chacón-Montalván, and Amber Leeson
Geosci. Model Dev., 17, 5733–5757, https://doi.org/10.5194/gmd-17-5733-2024, https://doi.org/10.5194/gmd-17-5733-2024, 2024
Short summary
Short summary
Climate models are essential tools in the study of climate change and its wide-ranging impacts on life on Earth. However, the output is often afflicted with some bias. In this paper, a novel model is developed to predict and correct bias in the output of climate models. The model captures uncertainty in the correction and explicitly models underlying spatial correlation between points. These features are of key importance for climate change impact assessments and resulting decision-making.
Nicolaj Hansen, Andrew Orr, Xun Zou, Fredrik Boberg, Thomas J. Bracegirdle, Ella Gilbert, Peter L. Langen, Matthew A. Lazzara, Ruth Mottram, Tony Phillips, Ruth Price, Sebastian B. Simonsen, and Stuart Webster
The Cryosphere, 18, 2897–2916, https://doi.org/10.5194/tc-18-2897-2024, https://doi.org/10.5194/tc-18-2897-2024, 2024
Short summary
Short summary
We investigated a melt event over the Ross Ice Shelf. We use regional climate models and a firn model to simulate the melt and compare the results with satellite data. We find that the firn model aligned well with observed melt days in certain parts of the ice shelf. The firn model had challenges accurately simulating the melt extent in the western sector. We identified potential reasons for these discrepancies, pointing to limitations in the models related to representing the cloud properties.
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
Short summary
Short summary
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.
Alison Delhasse, Johanna Beckmann, Christoph Kittel, and Xavier Fettweis
The Cryosphere, 18, 633–651, https://doi.org/10.5194/tc-18-633-2024, https://doi.org/10.5194/tc-18-633-2024, 2024
Short summary
Short summary
Aiming to study the long-term influence of an extremely warm climate in the Greenland Ice Sheet contribution to sea level rise, a new regional atmosphere–ice sheet model setup was established. The coupling, explicitly considering the melt–elevation feedback, is compared to an offline method to consider this feedback. We highlight mitigation of the feedback due to local changes in atmospheric circulation with changes in surface topography, making the offline correction invalid on the margins.
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
Short summary
Short summary
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.
Laura Melling, Amber Leeson, Malcolm McMillan, Jennifer Maddalena, Jade Bowling, Emily Glen, Louise Sandberg Sørensen, Mai Winstrup, and Rasmus Lørup Arildsen
The Cryosphere, 18, 543–558, https://doi.org/10.5194/tc-18-543-2024, https://doi.org/10.5194/tc-18-543-2024, 2024
Short summary
Short summary
Lakes on glaciers hold large volumes of water which can drain through the ice, influencing estimates of sea level rise. To estimate water volume, we must calculate lake depth. We assessed the accuracy of three satellite-based depth detection methods on a study area in western Greenland and considered the implications for quantifying the volume of water within lakes. We found that the most popular method of detecting depth on the ice sheet scale has higher uncertainty than previously assumed.
Louise Sandberg Sørensen, Rasmus Bahbah, Sebastian B. Simonsen, Natalia Havelund Andersen, Jade Bowling, Noel Gourmelen, Alex Horton, Nanna B. Karlsson, Amber Leeson, Jennifer Maddalena, Malcolm McMillan, Anne Solgaard, and Birgit Wessel
The Cryosphere, 18, 505–523, https://doi.org/10.5194/tc-18-505-2024, https://doi.org/10.5194/tc-18-505-2024, 2024
Short summary
Short summary
Under the right topographic and hydrological conditions, lakes may form beneath the large ice sheets. Some of these subglacial lakes are active, meaning that they periodically drain and refill. When a subglacial lake drains rapidly, it may cause the ice surface above to collapse, and here we investigate how to improve the monitoring of active subglacial lakes in Greenland by monitoring how their associated collapse basins change over time.
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
Short summary
Short summary
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.
Damien Maure, Christoph Kittel, Clara Lambin, Alison Delhasse, and Xavier Fettweis
The Cryosphere, 17, 4645–4659, https://doi.org/10.5194/tc-17-4645-2023, https://doi.org/10.5194/tc-17-4645-2023, 2023
Short summary
Short summary
The Arctic is warming faster than the rest of the Earth. Studies have already shown that Greenland and the Canadian Arctic are experiencing a record increase in melting rates, while Svalbard has been relatively less impacted. Looking at those regions but also extending the study to Iceland and the Russian Arctic archipelagoes, we see a heterogeneity in the melting-rate response to the Arctic warming, with the Russian archipelagoes experiencing lower melting rates than other regions.
Prateek Gantayat, Alison F. Banwell, Amber A. Leeson, James M. Lea, Dorthe Petersen, Noel Gourmelen, and Xavier Fettweis
Geosci. Model Dev., 16, 5803–5823, https://doi.org/10.5194/gmd-16-5803-2023, https://doi.org/10.5194/gmd-16-5803-2023, 2023
Short summary
Short summary
We developed a new supraglacial hydrology model for the Greenland Ice Sheet. This model simulates surface meltwater routing, meltwater drainage, supraglacial lake (SGL) overflow, and formation of lake ice. The model was able to reproduce 80 % of observed lake locations and provides a good match between the observed and modelled temporal evolution of SGLs.
Thomas Dethinne, Quentin Glaude, Ghislain Picard, Christoph Kittel, Patrick Alexander, Anne Orban, and Xavier Fettweis
The Cryosphere, 17, 4267–4288, https://doi.org/10.5194/tc-17-4267-2023, https://doi.org/10.5194/tc-17-4267-2023, 2023
Short summary
Short summary
We investigate the sensitivity of the regional climate model
Modèle Atmosphérique Régional(MAR) to the assimilation of wet-snow occurrence estimated by remote sensing datasets. The assimilation is performed by nudging the MAR snowpack temperature. The data assimilation is performed over the Antarctic Peninsula for the 2019–2021 period. The results show an increase in the melt production (+66.7 %) and a decrease in surface mass balance (−4.5 %) of the model for the 2019–2020 melt season.
Inès N. Otosaka, Andrew Shepherd, Erik R. Ivins, Nicole-Jeanne Schlegel, Charles Amory, Michiel R. van den Broeke, Martin Horwath, Ian Joughin, Michalea D. King, Gerhard Krinner, Sophie Nowicki, Anthony J. Payne, Eric Rignot, Ted Scambos, Karen M. Simon, Benjamin E. Smith, Louise S. Sørensen, Isabella Velicogna, Pippa L. Whitehouse, Geruo A, Cécile Agosta, Andreas P. Ahlstrøm, Alejandro Blazquez, William Colgan, Marcus E. Engdahl, Xavier Fettweis, Rene Forsberg, Hubert Gallée, Alex Gardner, Lin Gilbert, Noel Gourmelen, Andreas Groh, Brian C. Gunter, Christopher Harig, Veit Helm, Shfaqat Abbas Khan, Christoph Kittel, Hannes Konrad, Peter L. Langen, Benoit S. Lecavalier, Chia-Chun Liang, Bryant D. Loomis, Malcolm McMillan, Daniele Melini, Sebastian H. Mernild, Ruth Mottram, Jeremie Mouginot, Johan Nilsson, Brice Noël, Mark E. Pattle, William R. Peltier, Nadege Pie, Mònica Roca, Ingo Sasgen, Himanshu V. Save, Ki-Weon Seo, Bernd Scheuchl, Ernst J. O. Schrama, Ludwig Schröder, Sebastian B. Simonsen, Thomas Slater, Giorgio Spada, Tyler C. Sutterley, Bramha Dutt Vishwakarma, Jan Melchior van Wessem, David Wiese, Wouter van der Wal, and Bert Wouters
Earth Syst. Sci. Data, 15, 1597–1616, https://doi.org/10.5194/essd-15-1597-2023, https://doi.org/10.5194/essd-15-1597-2023, 2023
Short summary
Short summary
By measuring changes in the volume, gravitational attraction, and ice flow of Greenland and Antarctica from space, we can monitor their mass gain and loss over time. Here, we present a new record of the Earth’s polar ice sheet mass balance produced by aggregating 50 satellite-based estimates of ice sheet mass change. This new assessment shows that the ice sheets have lost (7.5 x 1012) t of ice between 1992 and 2020, contributing 21 mm to sea level rise.
Christoph Kittel, Charles Amory, Stefan Hofer, Cécile Agosta, Nicolas C. Jourdain, Ella Gilbert, Louis Le Toumelin, Étienne Vignon, Hubert Gallée, and Xavier Fettweis
The Cryosphere, 16, 2655–2669, https://doi.org/10.5194/tc-16-2655-2022, https://doi.org/10.5194/tc-16-2655-2022, 2022
Short summary
Short summary
Model projections suggest large differences in future Antarctic surface melting even for similar greenhouse gas scenarios and warming rates. We show that clouds containing a larger amount of liquid water lead to stronger melt. As surface melt can trigger the collapse of the ice shelves (the safety band of the Antarctic Ice Sheet), clouds could be a major source of uncertainties in projections of sea level rise.
Daniel Clarkson, Emma Eastoe, and Amber Leeson
The Cryosphere, 16, 1597–1607, https://doi.org/10.5194/tc-16-1597-2022, https://doi.org/10.5194/tc-16-1597-2022, 2022
Short summary
Short summary
The Greenland ice sheet has seen large amounts of melt in recent years, and accurately modelling temperatures is vital to understand how much of the ice sheet is melting. We estimate the probability of melt from ice surface temperature data to identify which areas of the ice sheet have experienced melt and estimate temperature quantiles. Our results suggest that for large areas of the ice sheet, melt has become more likely over the past 2 decades and high temperatures are also becoming warmer.
Matthew K. Laffin, Charles S. Zender, Melchior van Wessem, and Sebastián Marinsek
The Cryosphere, 16, 1369–1381, https://doi.org/10.5194/tc-16-1369-2022, https://doi.org/10.5194/tc-16-1369-2022, 2022
Short summary
Short summary
The collapses of the Larsen A and B ice shelves on the Antarctic Peninsula (AP) occurred while the ice shelves were covered with large melt lakes, and ocean waves damaged the ice shelf fronts, triggering collapse. Observations show föhn winds were present on both ice shelves and increased surface melt and drove sea ice away from the ice front. Collapsed ice shelves experienced enhanced surface melt driven by föhn winds, whereas extant ice shelves are affected less by föhn-wind-induced melt.
Nicolaj Hansen, Sebastian B. Simonsen, Fredrik Boberg, Christoph Kittel, Andrew Orr, Niels Souverijns, J. Melchior van Wessem, and Ruth Mottram
The Cryosphere, 16, 711–718, https://doi.org/10.5194/tc-16-711-2022, https://doi.org/10.5194/tc-16-711-2022, 2022
Short summary
Short summary
We investigate the impact of different ice masks when modelling surface mass balance over Antarctica. We used ice masks and data from five of the most used regional climate models and a common mask. We see large disagreement between the ice masks, which has a large impact on the surface mass balance, especially around the Antarctic Peninsula and some of the largest glaciers. We suggest a solution for creating a new, up-to-date, high-resolution ice mask that can be used in Antarctic modelling.
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
Short summary
Short summary
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.
Diarmuid Corr, Amber Leeson, Malcolm McMillan, Ce Zhang, and Thomas Barnes
Earth Syst. Sci. Data, 14, 209–228, https://doi.org/10.5194/essd-14-209-2022, https://doi.org/10.5194/essd-14-209-2022, 2022
Short summary
Short summary
We identify 119 km2 of meltwater area over West Antarctica in January 2017. In combination with Stokes et al., 2019, this forms the first continent-wide assessment helping to quantify the mass balance of Antarctica and its contribution to global sea level rise. We apply thresholds for meltwater classification to satellite images, mapping the extent and manually post-processing to remove false positives. Our study provides a high-fidelity dataset to train and validate machine learning methods.
Peter A. Tuckett, Jeremy C. Ely, Andrew J. Sole, James M. Lea, Stephen J. Livingstone, Julie M. Jones, and J. Melchior van Wessem
The Cryosphere, 15, 5785–5804, https://doi.org/10.5194/tc-15-5785-2021, https://doi.org/10.5194/tc-15-5785-2021, 2021
Short summary
Short summary
Lakes form on the surface of the Antarctic Ice Sheet during the summer. These lakes can generate further melt, break up floating ice shelves and alter ice dynamics. Here, we describe a new automated method for mapping surface lakes and apply our technique to the Amery Ice Shelf between 2005 and 2020. Lake area is highly variable between years, driven by large-scale climate patterns. This technique will help us understand the role of Antarctic surface lakes in our warming world.
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
Short summary
Short summary
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
Short summary
Short summary
We compare the calculated surface mass budget (SMB) of Antarctica in five different regional climate models. On average ~ 2000 Gt of snow accumulates annually, but different models vary by ~ 10 %, a difference equivalent to ± 0.5 mm of global sea level rise. All models reproduce observed weather, but there are large differences in regional patterns of snowfall, especially in areas with very few observations, giving greater uncertainty in Antarctic mass budget than previously identified.
Louis Le Toumelin, Charles Amory, Vincent Favier, Christoph Kittel, Stefan Hofer, Xavier Fettweis, Hubert Gallée, and Vinay Kayetha
The Cryosphere, 15, 3595–3614, https://doi.org/10.5194/tc-15-3595-2021, https://doi.org/10.5194/tc-15-3595-2021, 2021
Short summary
Short summary
Snow is frequently eroded from the surface by the wind in Adelie Land (Antarctica) and suspended in the lower atmosphere. By performing model simulations, we show firstly that suspended snow layers interact with incoming radiation similarly to a near-surface cloud. Secondly, suspended snow modifies the atmosphere's thermodynamic structure and energy exchanges with the surface. Our results suggest snow transport by the wind should be taken into account in future model studies over the region.
Thomas James Barnes, Amber Alexandra Leeson, Malcolm McMillan, Vincent Verjans, Jeremy Carter, and Christoph Kittel
The Cryosphere Discuss., https://doi.org/10.5194/tc-2021-214, https://doi.org/10.5194/tc-2021-214, 2021
Revised manuscript not accepted
Short summary
Short summary
We find that the area covered by lakes on George VI ice shelf in 2020 is similar to that seen in other years such as 1989. However, the climate conditions are much more in favour of lakes forming. We find that it is likely that snowfall, and the build up of a surface snow layer limits the development of lakes on the surface of George VI ice shelf in 2020. We also find that in future, snowfall is predicted to decrease, and therefore this limiting effect may be reduced in future.
Xavier Fettweis, Stefan Hofer, Roland Séférian, Charles Amory, Alison Delhasse, Sébastien Doutreloup, Christoph Kittel, Charlotte Lang, Joris Van Bever, Florent Veillon, and Peter Irvine
The Cryosphere, 15, 3013–3019, https://doi.org/10.5194/tc-15-3013-2021, https://doi.org/10.5194/tc-15-3013-2021, 2021
Short summary
Short summary
Without any reduction in our greenhouse gas emissions, the Greenland ice sheet surface mass loss can be brought in line with a medium-mitigation emissions scenario by reducing the solar downward flux at the top of the atmosphere by 1.5 %. In addition to reducing global warming, these solar geoengineering measures also dampen the well-known positive melt–albedo feedback over the ice sheet by 6 %. However, only stronger reductions in solar radiation could maintain a stable ice sheet in 2100.
Charles Amory, Christoph Kittel, Louis Le Toumelin, Cécile Agosta, Alison Delhasse, Vincent Favier, and Xavier Fettweis
Geosci. Model Dev., 14, 3487–3510, https://doi.org/10.5194/gmd-14-3487-2021, https://doi.org/10.5194/gmd-14-3487-2021, 2021
Short summary
Short summary
This paper presents recent developments in the drifting-snow scheme of the regional climate model MAR and its application to simulate drifting snow and the surface mass balance of Adélie Land in East Antarctica. The model is extensively described and evaluated against a multi-year drifting-snow dataset and surface mass balance estimates available in the area. The model sensitivity to input parameters and improvements over a previously published version are also assessed.
Andrew Orr, Hua Lu, Patrick Martineau, Edwin P. Gerber, Gareth J. Marshall, and Thomas J. Bracegirdle
Atmos. Chem. Phys., 21, 7451–7472, https://doi.org/10.5194/acp-21-7451-2021, https://doi.org/10.5194/acp-21-7451-2021, 2021
Short summary
Short summary
Reanalysis datasets combine observations and weather forecast simulations to create our best estimate of the state of the atmosphere and are important for climate monitoring. Differences in the technical details of these products mean that they may give different results. This study therefore examined how changes associated with the so-called Antarctic ozone hole are represented, which is one of the most important climate changes in recent decades, and showed that they were broadly consistent.
Christoph Kittel, Charles Amory, Cécile Agosta, Nicolas C. Jourdain, Stefan Hofer, Alison Delhasse, Sébastien Doutreloup, Pierre-Vincent Huot, Charlotte Lang, Thierry Fichefet, and Xavier Fettweis
The Cryosphere, 15, 1215–1236, https://doi.org/10.5194/tc-15-1215-2021, https://doi.org/10.5194/tc-15-1215-2021, 2021
Short summary
Short summary
The future surface mass balance (SMB) of the Antarctic ice sheet (AIS) will influence the ice dynamics and the contribution of the ice sheet to the sea level rise. We investigate the AIS sensitivity to different warmings using physical and statistical downscaling of CMIP5 and CMIP6 models. Our results highlight a contrasting effect between the grounded ice sheet (where the SMB is projected to increase) and ice shelves (where the future SMB depends on the emission scenario).
J. Melchior van Wessem, Christian R. Steger, Nander Wever, and Michiel R. van den Broeke
The Cryosphere, 15, 695–714, https://doi.org/10.5194/tc-15-695-2021, https://doi.org/10.5194/tc-15-695-2021, 2021
Short summary
Short summary
This study presents the first modelled estimates of perennial firn aquifers (PFAs) in Antarctica. PFAs are subsurface meltwater bodies that do not refreeze in winter due to the isolating effects of the snow they are buried underneath. They were first identified in Greenland, but conditions for their existence are also present in the Antarctic Peninsula. These PFAs can have important effects on meltwater retention, ice shelf stability, and, consequently, sea level rise.
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
Short summary
Short summary
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.
Jennifer F. Arthur, Chris R. Stokes, Stewart S. R. Jamieson, J. Rachel Carr, and Amber A. Leeson
The Cryosphere, 14, 4103–4120, https://doi.org/10.5194/tc-14-4103-2020, https://doi.org/10.5194/tc-14-4103-2020, 2020
Short summary
Short summary
Surface meltwater lakes can flex and fracture ice shelves, potentially leading to ice shelf break-up. A long-term record of lake evolution on Shackleton Ice Shelf is produced using optical satellite imagery and compared to surface air temperature and modelled surface melt. The results reveal that lake clustering on the ice shelf is linked to melt-enhancing feedbacks. Peaks in total lake area and volume closely correspond with intense snowmelt events rather than with warmer seasonal temperatures.
Xavier Fettweis, Stefan Hofer, Uta Krebs-Kanzow, Charles Amory, Teruo Aoki, Constantijn J. Berends, Andreas Born, Jason E. Box, Alison Delhasse, Koji Fujita, Paul Gierz, Heiko Goelzer, Edward Hanna, Akihiro Hashimoto, Philippe Huybrechts, Marie-Luise Kapsch, Michalea D. King, Christoph Kittel, Charlotte Lang, Peter L. Langen, Jan T. M. Lenaerts, Glen E. Liston, Gerrit Lohmann, Sebastian H. Mernild, Uwe Mikolajewicz, Kameswarrao Modali, Ruth H. Mottram, Masashi Niwano, Brice Noël, Jonathan C. Ryan, Amy Smith, Jan Streffing, Marco Tedesco, Willem Jan van de Berg, Michiel van den Broeke, Roderik S. W. van de Wal, Leo van Kampenhout, David Wilton, Bert Wouters, Florian Ziemen, and Tobias Zolles
The Cryosphere, 14, 3935–3958, https://doi.org/10.5194/tc-14-3935-2020, https://doi.org/10.5194/tc-14-3935-2020, 2020
Short summary
Short summary
We evaluated simulated Greenland Ice Sheet surface mass balance from 5 kinds of models. While the most complex (but expensive to compute) models remain the best, the faster/simpler models also compare reliably with observations and have biases of the same order as the regional models. Discrepancies in the trend over 2000–2012, however, suggest that large uncertainties remain in the modelled future SMB changes as they are highly impacted by the meltwater runoff biases over the current climate.
Baptiste Vandecrux, Ruth Mottram, Peter L. Langen, Robert S. Fausto, Martin Olesen, C. Max Stevens, Vincent Verjans, Amber Leeson, Stefan Ligtenberg, Peter Kuipers Munneke, Sergey Marchenko, Ward van Pelt, Colin R. Meyer, Sebastian B. Simonsen, Achim Heilig, Samira Samimi, Shawn Marshall, Horst Machguth, Michael MacFerrin, Masashi Niwano, Olivia Miller, Clifford I. Voss, and Jason E. Box
The Cryosphere, 14, 3785–3810, https://doi.org/10.5194/tc-14-3785-2020, https://doi.org/10.5194/tc-14-3785-2020, 2020
Short summary
Short summary
In the vast interior of the Greenland ice sheet, snow accumulates into a thick and porous layer called firn. Each summer, the firn retains part of the meltwater generated at the surface and buffers sea-level rise. In this study, we compare nine firn models traditionally used to quantify this retention at four sites and evaluate their performance against a set of in situ observations. We highlight limitations of certain model designs and give perspectives for future model development.
Andrew Orr, J. Scott Hosking, Aymeric Delon, Lars Hoffmann, Reinhold Spang, Tracy Moffat-Griffin, James Keeble, Nathan Luke Abraham, and Peter Braesicke
Atmos. Chem. Phys., 20, 12483–12497, https://doi.org/10.5194/acp-20-12483-2020, https://doi.org/10.5194/acp-20-12483-2020, 2020
Short summary
Short summary
Polar stratospheric clouds (PSCs) are clouds found in the Antarctic winter stratosphere and are implicated in the formation of the ozone hole. These clouds can sometimes be formed or enhanced by mountain waves, formed as air passes over hills or mountains. However, this important mechanism is missing in coarse-resolution climate models, limiting our ability to simulate ozone. This study examines an attempt to include the effects of mountain waves and their impact on PSCs and ozone.
Vincent Verjans, Amber A. Leeson, Christopher Nemeth, C. Max Stevens, Peter Kuipers Munneke, Brice Noël, and Jan Melchior van Wessem
The Cryosphere, 14, 3017–3032, https://doi.org/10.5194/tc-14-3017-2020, https://doi.org/10.5194/tc-14-3017-2020, 2020
Short summary
Short summary
Ice sheets are covered by a firn layer, which is the transition stage between fresh snow and ice. Accurate modelling of firn density properties is important in many glaciological aspects. Current models show disagreements, are mostly calibrated to match specific observations of firn density and lack thorough uncertainty analysis. We use a novel calibration method for firn models based on a Bayesian statistical framework, which results in improved model accuracy and in uncertainty evaluation.
Cited articles
Agosta, C., Amory, C., Kittel, C., Orsi, A., Favier, V., Gallée, H., van den Broeke, M. R., Lenaerts, J. T. M., van Wessem, J. M., van de Berg, W. J., and Fettweis, X.: Estimation of the Antarctic surface mass balance using the regional climate model MAR (1979–2015) and identification of dominant processes, The Cryosphere, 13, 281–296, https://doi.org/10.5194/tc-13-281-2019, 2019. a, b, c, d, e, f, g, h
Balsamo, G., Beljaars, A., Scipal, K., Viterbo, P., v. d. Hurk, B., Hirschi,
M., and Betts, A. K.: A Revised Hydrology for the ECMWF Model:
Verification from Field Site to Terrestrial Water Storage and
Impact in the Integrated Forecast System, J. Hydrometeorol., 10, 623–643, https://doi.org/10.1175/2008JHM1068.1, 2009. a, b
Bamber, J. L., Gomez-Dans, J. L., and Griggs, J. A.: A new 1 km digital elevation model of the Antarctic derived from combined satellite radar and laser data – Part 1: Data and methods, The Cryosphere, 3, 101–111, https://doi.org/10.5194/tc-3-101-2009, 2009. a
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, Proc. 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
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
Best, M. J., Pryor, M., Clark, D. B., Rooney, G. G., Essery, R. L. H., Ménard, C. B., Edwards, J. M., Hendry, M. A., Porson, A., Gedney, N., Mercado, L. M., Sitch, S., Blyth, E., Boucher, O., Cox, P. M., Grimmond, C. S. B., and Harding, R. J.: The Joint UK Land Environment Simulator (JULES), model description – Part 1: Energy and water fluxes, Geosci. Model Dev., 4, 677–699, https://doi.org/10.5194/gmd-4-677-2011, 2011. a
Bromwich, D. H.: Satellite Analyses of Antarctic Katabatic Wind
Behavior, Bull. Am. Meteorol. Soc., 70, 738–749,
https://doi.org/10.1175/1520-0477(1989)070<0738:SAOAKW>2.0.CO;2, 1989. a
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/10.1017/s0022143000009552, 1992. a
Bulthuis, K., Arnst, M., Sun, S., and Pattyn, F.: Uncertainty quantification of the multi-centennial response of the Antarctic ice sheet to climate change, The Cryosphere, 13, 1349–1380, https://doi.org/10.5194/tc-13-1349-2019, 2019. a
Bush, M., Allen, T., Bain, C., Boutle, I., Edwards, J., Finnenkoetter, A., Franklin, C., Hanley, K., Lean, H., Lock, A., Manners, J., Mittermaier, M., Morcrette, C., North, R., Petch, J., Short, C., Vosper, S., Walters, D., Webster, S., Weeks, M., Wilkinson, J., Wood, N., and Zerroukat, M.: The first Met Office Unified Model–JULES Regional Atmosphere and Land configuration, RAL1, Geosci. Model Dev., 13, 1999–2029, https://doi.org/10.5194/gmd-13-1999-2020, 2020.
Cape, M. R., Vernet, M., Skvarca, P., Marinsek, S., Scambos, T., and Domack,
E.: Foehn winds link climate-driven warming to ice shelf evolution in
Antarctica, J. Geophys. Res.-Atmos., 120, 11037–11057, https://doi.org/10.1002/2015JD023465, 2015. a
Carter, J.: Jez-Carter/Antarctica_Climate_Variability: 0.1.0, Zenodo [code], https://doi.org/10.5281/zenodo.6375205, 2022. a
Carter, J., Leeson, A., Orr, A., Kittel, C., and van Wessem, M.: Variability in Antarctic Surface Climatology Across Regional Climate Models
and Reanalysis Datasets, Zenodo [data set], https://doi.org/10.5281/zenodo.6367850,
2022. a
Christensen, J. H., Boberg, F., Christensen, O. B., and Lucas-Picher, P.: On
the need for bias correction of regional climate change projections of
temperature and precipitation, Geophys. Res. Lett., 35, L20709, https://doi.org/10.1029/2008GL035694, 2008. a
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, b, c
DeConto, R., Pollard, D., Alley, R., Velicogna, I., Gasson, E., Gomez, N.,
Sadai, S., Condron, A., Gilford, D., Ashe, E., Kopp, R., Li, D., and Dutton, A.: The Paris Climate Agreement and future sea-level rise from
Antarctica, Nature, 593, 83–89, https://doi.org/10.1038/s41586-021-03427-0, 2021. a
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi,
S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P.,
Beljaars, A. C. M., v. d. Berg, L., Bidlot, J., Bormann, N., Delsol, C.,
Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B.,
Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P., Köhler, M.,
Matricardi, M., McNally, A. P., Monge‐Sanz, B. M., Morcrette, J.-J., Park,
B.-K., Peubey, C., Rosnay, P. d., Tavolato, C., Thépaut, J.-N., and Vitart,
F.: The ERA-Interim reanalysis: configuration and performance of the data assimilation system, Q. J. Roy. Meteor. Soc., 137, 553–597, https://doi.org/10.1002/qj.828, 2011. a
Depoorter, M. A., Bamber, J. L., Griggs, J., Lenaerts, J. T. M., Ligtenberg, S.
R. M., van den Broeke, M. R., and Moholdt, G.: Antarctic masks (ice-shelves, ice-sheet, and islands), link to shape file, In supplement to: Depoorter et al. (2013): Calving fluxes and basal melt rates of Antarctic ice shelves,
Nature, 502, 89–92, https://doi.org/10.1038/nature12567, 2013. a, b
ECMWF: Part IV: Physical Processes, in: IFS Documentation CY33R1, IFS Documentation, ECMWF, https://doi.org/10.21957/8o7vwlbdr, 2009. a
ECMWF: The ERA-Interim reanalysis dataset, Copernicus Climate Change Service (C3S), ECMWF [data set], https://www.ecmwf.int/en/forecasts/datasets/archive-datasets/reanalysis-datasets/era-interim (last access: 22 August 2022), 2011. a
ECMWF: Part IV: Physical Processes, in: IFS Documentation CY41R2, IFS Documentation, ECMWF, https://doi.org/10.21957/tr5rv27xu, 2016. a
Ehret, U., Zehe, E., Wulfmeyer, V., Warrach-Sagi, K., and Liebert, J.: HESS Opinions “Should we apply bias correction to global and regional climate model data?”, Hydrol. Earth Syst. Sci., 16, 3391–3404, https://doi.org/10.5194/hess-16-3391-2012, 2012. a, b
GLOBE: The Global Land One-kilometer Base Elevation (GLOBE) Digital Elevation Model, Version 1.0, National Oceanic and Atmospheric Administration, edited by: Hastings, D. A., Dunbar, P. K., Elphingstone, G. M., Bootz, M., Murakami, H., Maruyama, H., Masaharu, H., Holland, P., Payne, J., Bryant, N. A., Logan, T. L., Muller, J.-P., Schreier, G., and MacDonald, J. S., National Geophysical Data Center, 325 Broadway, Boulder, 80305-3328 Colorado, USA, http://www.ngdc.noaa.gov/mgg/topo/globe.html (last access: 12 September 2022), 1999. 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
Ettema, J., van den Broeke, M. R., van Meijgaard, E., van de Berg, W. J., Box, J. E., and Steffen, K.: Climate of the Greenland ice sheet using a high-resolution climate model – Part 1: Evaluation, The Cryosphere, 4, 511–527, https://doi.org/10.5194/tc-4-511-2010, 2010. a, b
Fettweis, X., Franco, B., Tedesco, M., van Angelen, J. H., Lenaerts, J. T. M., van den Broeke, M. R., and Gallée, H.: Estimating the Greenland ice sheet surface mass balance contribution to future sea level rise using the regional atmospheric climate model MAR, The Cryosphere, 7, 469–489, https://doi.org/10.5194/tc-7-469-2013, 2013. a, b
Fettweis, X., Box, J. E., Agosta, C., Amory, C., Kittel, C., Lang, C., van As, D., Machguth, H., and Gallée, H.: Reconstructions of the 1900–2015 Greenland ice sheet surface mass balance using the regional climate MAR model, The Cryosphere, 11, 1015–1033, https://doi.org/10.5194/tc-11-1015-2017, 2017. a
Franco, B., Fettweis, X., Lang, C., and Erpicum, M.: Impact of spatial resolution on the modelling of the Greenland ice sheet surface mass balance between 1990–2010, using the regional climate model MAR, The Cryosphere, 6, 695–711, https://doi.org/10.5194/tc-6-695-2012, 2012. 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, b
Gallée, H.: Simulation of the Mesocyclonic Activity in the Ross Sea,
Antarctica, Mon. Weather Rev., 123, 2051–2069,
https://doi.org/10.1175/1520-0493(1995)123<2051:SOTMAI>2.0.CO;2, 1995. a
Gallée, H. and Gorodetskaya, I. V.: Validation of a limited area model over
Dome C, Antarctic Plateau, during winter, Clim. Dynam., 34, 61,
https://doi.org/10.1007/s00382-008-0499-y, 2008. a
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
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
Gilbert, E., Orr, A., King, J. C., Renfrew, I. A., Lachlan‐Cope, T., Field,
P. F., and Boutle, I. A.: Summertime cloud phase strongly influences surface
melting on the Larsen C ice shelf, Antarctica, Q. J. Roy. Meteor. Soc., 146, 1575–1589, https://doi.org/10.1002/qj.3753, 2020.
Gilbert, E. M. K., Orr, A., King, J. C., Renfrew, I., and Lachlan-Cope, T. A.:
A 20-year study of melt processes over Larsen C Ice Shelf using a
high-resolution regional atmospheric model: Part 1, Model configuration
and validation, https://doi.org/10.1002/essoar.10506250.1, 2021. a
Giorgi, F.: Thirty Years of Regional Climate Modeling: Where Are
We and Where Are We Going next?, J. Geophys. Res.-Atmos., 124, 5696–5723, https://doi.org/10.1029/2018JD030094, 2019. a
Hansen, N., Langen, P. L., Boberg, F., Forsberg, R., Simonsen, S. B., Thejll, P., Vandecrux, B., and Mottram, R.: Downscaled surface mass balance in Antarctica: impacts of subsurface processes and large-scale atmospheric circulation, The Cryosphere, 15, 4315–4333, https://doi.org/10.5194/tc-15-4315-2021, 2021. a
Hansen, N., Simonsen, S. B., Boberg, F., Kittel, C., Orr, A., Souverijns, N., van Wessem, J. M., and Mottram, R.: Brief communication: Impact of common ice mask in surface mass balance estimates over the Antarctic ice sheet, The Cryosphere, 16, 711–718, https://doi.org/10.5194/tc-16-711-2022, 2022. a
Harris, C. R., Millman, K. J., van der Walt, S. J., Gommers, R., Virtanen, P.,
Cournapeau, D., Wieser, E., Taylor, J., Berg, S., Smith, N. J., Kern, R.,
Picus, M., Hoyer, S., van Kerkwijk, M. H., Brett, M., Haldane, A., del Río,
J. F., Wiebe, M., Peterson, P., Gérard-Marchant, P., Sheppard, K., Reddy,
T., Weckesser, W., Abbasi, H., Gohlke, C., and Oliphant, T. E.: Array
programming with NumPy, Nature, 585, 357–362,
https://doi.org/10.1038/s41586-020-2649-2, 2020. a
Heinemann, G. and Zentek, R.: A Model-Based Climatology of Low-Level
Jets in the Weddell Sea Region of the Antarctic, Atmosphere, 12,
1635, https://doi.org/10.3390/atmos12121635, 2021. a
Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A.,
Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers,
D., Simmons, A., Soci, C., Dee, D., and Thépaut, J.-N.: ERA5 hourly data
on pressure levels from 1979 to present, Copernicus Climate Change
Service (C3S) Climate Data Store (CDS), Copernicus [data set],
https://doi.org/10.24381/cds.bd0915c6, 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., Rosnay, P. d.,
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
Hunter, J. D.: Matplotlib: A 2D Graphics Environment, Computing in
Science Engineering, 9, 90–95, https://doi.org/10.1109/MCSE.2007.55, 2007. 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
Kopp, R. E., DeConto, R. M., Bader, D. A., Hay, C. C., Horton, R. M., Kulp, S.,
Oppenheimer, M., Pollard, D., and Strauss, B. H.: Evolving Understanding of
Antarctic Ice-Sheet Physics and Ambiguity in Probabilistic
Sea-Level Projections, Earth's Future, 5, 1217–1233,
https://doi.org/10.1002/2017EF000663, 2017. a
Kuipers Munneke, P., Ligtenberg, S. R. M., 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, b
Lenaerts, J. T. M., van den Broeke, M. R., Déry, S. J., König-Langlo, G., Ettema, J., and Munneke, P. K.: Modelling snowdrift sublimation on an Antarctic ice shelf, The Cryosphere, 4, 179–190, https://doi.org/10.5194/tc-4-179-2010, 2010. a
Lenaerts, J. T. M., van den Broeke, M. R., Dery, S. J., van Meijgaard, E.,
van de Berg, W. J., Palm, S. P., and Rodrigo, J. S.: Modeling drifting snow
in Antarctica with a regional climate model: 1, Methods and model
evaluation, J. Geophys. Res.-Atmos., 117, D05108,
https://doi.org/10.1029/2011JD016145, 2012a. a
Lenaerts, J. T. M., van den Broeke, M. R., van de Berg, W. J., van Meijgaard,
E., and Munneke, P. K.: A new, high-resolution surface mass balance map of
Antarctica (1979–2010) based on regional atmospheric climate modeling,
Geophys. Res. Lett., 39, L04501, https://doi.org/10.1029/2011GL050713, 2012b. 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, Nat. Clim. Change, 7, 58, https://doi.org/10.1038/NCLIMATE3180, 2017. a, b
Luckman, A., Elvidge, A., Jansen, D., Kulessa, B., Munneke, P. K., King, J.,
and Barrand, N. E.: Surface melt and ponding on Larsen C Ice Shelf
and the impact of fohn winds, Antarctic Science, 26, 625–635,
https://doi.org/10.1017/S0954102014000339, 2014. a
Mann, S.: Cubic precision Clough-Tocher interpolation, Computer Aided
Geometric Design, 16, 85–88, https://doi.org/10.1016/S0167-8396(98)00038-7, 1999. 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
Met Office: Iris: A Python library for analysing and visualising
meteorological and oceanographic data sets, scitools, http://scitools.org.uk/ (last access: 12 September 2022), 2010. 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, b, c, d, e, f, g, h, i
Munneke, P. K., v. d. Broeke, M. R., Lenaerts, J. T. M., Flanner, M. G.,
Gardner, A. S., and v. d. Berg, W. J.: A new albedo parameterization for use
in climate models over the Antarctic ice sheet, J. Geophys. Res.-Atmos., 116, D05114, https://doi.org/10.1029/2010JD015113, 2011. a
Orr, A., Phillips, T., Webster, S., Elvidge, A., Weeks, M., Hosking, S., and
Turner, J.: Met Office Unified Model high-resolution simulations of a
strong wind event in Antarctica, Q. J. Roy. Meteor. Soc., 140, 2287–2297, https://doi.org/10.1002/qj.2296, 2014. a
Orr, A., Kirchgaessner, A., King, J., Phillips, T., Gilbert, E., Elvidge, A.,
Weeks, M., Gadian, A., Kuipers Munneke, P., van den Broeke, M., Webster, S.,
and McGrath, D.: Comparison of kilometre and sub-kilometre scale simulations
of a foehn wind event over the Larsen C Ice Shelf, Antarctic
Peninsula using the Met Office Unified Model (MetUM), Q. J. Roy. Meteor. Soc., 147, 3472–3492, https://doi.org/10.1002/qj.4138, 2021. a, b, c, d, e
Orr, A.: Antarctic CORDEX, Climate and Cryosphere [code], https://climate-cryosphere.org/antarctic-cordex/, last access: 1 March 2022. 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
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
Pollard, D., DeConto, R., and Alley, R.: Potential Antarctic Ice Sheet
retreat driven by hydrofracturing and ice cliff failure, Earth Planet. Sci. Lett., 412, 112–121, https://doi.org/10.1016/j.epsl.2014.12.035, 2015. a
Pritchard, H., Ligtenberg, S., Fricker, H., Vaughan, D., Van den Broeke, M.,
and Padman, L.: Antarctic ice-sheet loss driven by basal melting of ice
shelves, Nature, 484, 502–5, https://doi.org/10.1038/nature10968, 2012. 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
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
Slater, A. G., Lawrence, D. M., and Koven, C. D.: Process-level model evaluation: a snow and heat transfer metric, The Cryosphere, 11, 989–996, https://doi.org/10.5194/tc-11-989-2017, 2017. a
Tedesco, M., Doherty, S., Fettweis, X., Alexander, P., Jeyaratnam, J., and Stroeve, J.: The darkening of the Greenland ice sheet: trends, drivers, and projections (1981–2100), The Cryosphere, 10, 477–496, https://doi.org/10.5194/tc-10-477-2016, 2016. a
Trusel, L. D., Frey, K. E., Das, S. B., Karnauskas, K. B., Munneke, P. K., van
Meijgaard, E., and van den Broeke, M. R.: Divergent trajectories of
Antarctic surface melt under two twenty-first-century climate scenarios,
Nat. Geosci., 8, 927–U56, https://doi.org/10.1038/NGEO2563, 2015. a
Undén, P., Rontu, L., Järvinen, H., Lynch, P., Calvo-Sanchez, J., Cats, G.,
Cuxart, J., Eerola, K., Fortelius, C., and García-Moya, J.: HIRLAM-5
scientific documentation, 1 January 2002, https://www.researchgate.net/publication/278962772_HIRLAM-5_scientific_documentation, last access: 12 September 2022. a
van den Broeke, M.: Strong surface melting preceded collapse of Antarctic
Peninsula ice shelf, Geophys. Res. Lett., 32, L12815,
https://doi.org/10.1029/2005GL023247, 2005. a
Van Meijgaard, E., Van Ulft, L. H., Van de Berg, W. J., Bosvelt, F. C., Van den
Hurk, B., Lenderink, G., and Siebesma, A. P.: The KNMI regional atmospheric
model RACMO version 2.1, Tech. Note Tech. Rep, 302, 1–43, https://www.researchgate.net/publication/283432385_The_KNMI_regional_atmospheric_model_RACMO_version_21 (last access: 12 September 2022), 2008. a
van Wessem, J. M., Ligtenberg, S. R. M., Reijmer, C. H., van de Berg, W. J., van den Broeke, M. R., Barrand, N. E., Thomas, E. R., Turner, J., Wuite, J., Scambos, T. A., and van Meijgaard, E.: The modelled surface mass balance of the Antarctic Peninsula at 5.5 km horizontal resolution, The Cryosphere, 10, 271–285, https://doi.org/10.5194/tc-10-271-2016, 2016. 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, c, d, e
von Storch, H., Langenberg, H., and Feser, F.: A Spectral Nudging
Technique for Dynamical Downscaling Purposes, Mon. Weather Rev.,
128, 3664–3673, https://doi.org/10.1175/1520-0493(2000)128<3664:ASNTFD>2.0.CO;2, 2000. a
Walters, D., Boutle, I., Brooks, M., Melvin, T., Stratton, R., Vosper, S., Wells, H., Williams, K., Wood, N., Allen, T., Bushell, A., Copsey, D., Earnshaw, P., Edwards, J., Gross, M., Hardiman, S., Harris, C., Heming, J., Klingaman, N., Levine, R., Manners, J., Martin, G., Milton, S., Mittermaier, M., Morcrette, C., Riddick, T., Roberts, M., Sanchez, C., Selwood, P., Stirling, A., Smith, C., Suri, D., Tennant, W., Vidale, P. L., Wilkinson, J., Willett, M., Woolnough, S., and Xavier, P.: The Met Office Unified Model Global Atmosphere 6.0/6.1 and JULES Global Land 6.0/6.1 configurations, Geosci. Model Dev., 10, 1487–1520, https://doi.org/10.5194/gmd-10-1487-2017, 2017. a, b, c
Short summary
Climate models provide valuable information for studying processes such as the collapse of ice shelves over Antarctica which impact estimates of sea level rise. This paper examines variability across climate simulations over Antarctica for fields including snowfall, temperature and melt. Significant systematic differences between outputs are found, occurring at both large and fine spatial scales across Antarctica. Results are important for future impact assessments and model development.
Climate models provide valuable information for studying processes such as the collapse of ice...
