Articles | Volume 19, issue 2
https://doi.org/10.5194/tc-19-597-2025
© Author(s) 2025. 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-19-597-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
11 Feb 2025
Research article |
| 11 Feb 2025
| 11 Feb 2025
Extreme precipitation associated with atmospheric rivers over West Antarctic ice shelves: insights from kilometre-scale regional climate modelling
British Antarctic Survey, Madingley Road, Cambridge, UK
Denis Pishniak
National Antarctic Science Centre of Ukraine, Kyiv, Ukraine
José Abraham Torres
Danish Meteorological Institute, Copenhagen, Denmark
Andrew Orr
British Antarctic Survey, Madingley Road, Cambridge, UK
Michelle Maclennan
Department of Atmospheric and Oceanic Sciences, University of Colorado Boulder, Boulder, CO, USA
British Antarctic Survey, Madingley Road, Cambridge, UK
Nander Wever
WSL Institute for Snow and Avalanche Research SLF, Davos, Switzerland
Kristiina Verro
Institute for Marine and Atmospheric Research, Utrecht University, Utrecht, the Netherlands
Danish Meteorological Institute, Copenhagen, Denmark
Related authors
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.
Ella Gilbert, Jhaswantsing Purseed, Yun Li, Martina Krämer, Beatrice Altamura, and Nicolas Bellouin
EGUsphere, https://doi.org/10.5194/egusphere-2024-821, https://doi.org/10.5194/egusphere-2024-821, 2024
Preprint withdrawn
Short summary
Short summary
We use a simple experiment to explore the non-CO2 impacts of aviation on climate, which are considerably larger than the impact of the sector’s carbon emissions alone. We show that the main effect of our experiments – which intend to mimic the effect of aircraft soot emissions reaching existing high-altitude cirrus clouds – is to extend cloud lifetime, thereby enhancing their effect on climate.
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.
Andrew O. Hoffman, Michelle L. Maclennan, Jan Lenaerts, Kristine M. Larson, and Knut Christianson
The Cryosphere, 19, 713–730, https://doi.org/10.5194/tc-19-713-2025, https://doi.org/10.5194/tc-19-713-2025, 2025
Short summary
Short summary
Traditionally, glaciologists use global navigation satellite systems (GNSSs) to measure the surface elevation and velocity of glaciers to understand processes associated with ice flow. Using the interference of GNSS signals that bounce off of the ice sheet surface, we measure the surface height change near GNSS receivers in the Amundsen Sea Embayment (ASE). From surface height change, we infer daily accumulation rates that we use to understand the drivers of extreme precipitation in the ASE.
Elizaveta Sharaborova, Michael Lehning, Nander Wever, Marcia Phillips, and Hendrik Huwald
EGUsphere, https://doi.org/10.5194/egusphere-2024-4174, https://doi.org/10.5194/egusphere-2024-4174, 2025
This preprint is open for discussion and under review for The Cryosphere (TC).
Short summary
Short summary
Global warming provokes permafrost to thaw, damaging landscapes and infrastructure. This study explores methods to slow this thawing at an alpine site. We investigate different methods based on passive and active cooling system. The best approach mixes both methods and manages heat flow, potentially allowing excess energy to be used locally.
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.
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
EGUsphere, https://doi.org/10.5194/egusphere-2024-2805, https://doi.org/10.5194/egusphere-2024-2805, 2024
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 Karakoram Himalaya (HKH). The approach leverages climate model and weather station data, along with statistical / machine learning techniques. Our results show this approach outperforms traditional methods, especially in remote, ungauged areas, suggesting it could be used to improve precipitation maps across much of the HKH, as well as other mountain regions.
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.
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.
Benjamin Bouchard, Daniel F. Nadeau, Florent Domine, Nander Wever, Adrien Michel, Michael Lehning, and Pierre-Erik Isabelle
The Cryosphere, 18, 2783–2807, https://doi.org/10.5194/tc-18-2783-2024, https://doi.org/10.5194/tc-18-2783-2024, 2024
Short summary
Short summary
Observations over several winters at two boreal sites in eastern Canada show that rain-on-snow (ROS) events lead to the formation of melt–freeze layers and that preferential flow is an important water transport mechanism in the sub-canopy snowpack. Simulations with SNOWPACK generally show good agreement with observations, except for the reproduction of melt–freeze layers. This was improved by simulating intercepted snow microstructure evolution, which also modulates ROS-induced runoff.
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
Short summary
Short summary
On the Antarctic Peninsula, there is a small bay that had sea ice fastened to the shoreline (
fast ice) for over a decade. The fast ice stabilized the glaciers that fed into the ocean. In January 2022, the fast ice broke away. Using satellite data we found that this was because of low sea ice concentrations and a high long-period ocean wave swell. We find that the glaciers have responded to this event by thinning, speeding up, and retreating by breaking off lots of icebergs at remarkable rates.
Ella Gilbert, Jhaswantsing Purseed, Yun Li, Martina Krämer, Beatrice Altamura, and Nicolas Bellouin
EGUsphere, https://doi.org/10.5194/egusphere-2024-821, https://doi.org/10.5194/egusphere-2024-821, 2024
Preprint withdrawn
Short summary
Short summary
We use a simple experiment to explore the non-CO2 impacts of aviation on climate, which are considerably larger than the impact of the sector’s carbon emissions alone. We show that the main effect of our experiments – which intend to mimic the effect of aircraft soot emissions reaching existing high-altitude cirrus clouds – is to extend cloud lifetime, thereby enhancing their effect on climate.
Eric Keenan, Nander Wever, Jan T. M. Lenaerts, and Brooke Medley
Geosci. Model Dev., 16, 3203–3219, https://doi.org/10.5194/gmd-16-3203-2023, https://doi.org/10.5194/gmd-16-3203-2023, 2023
Short summary
Short summary
Ice sheets gain mass via snowfall. However, snowfall is redistributed by the wind, resulting in accumulation differences of up to a factor of 5 over distances as short as 5 km. These differences complicate estimates of ice sheet contribution to sea level rise. For this reason, we have developed a new model for estimating wind-driven snow redistribution on ice sheets. We show that, over Pine Island Glacier in West Antarctica, the model improves estimates of snow accumulation variability.
Megan Thompson-Munson, Nander Wever, C. Max Stevens, Jan T. M. Lenaerts, and Brooke Medley
The Cryosphere, 17, 2185–2209, https://doi.org/10.5194/tc-17-2185-2023, https://doi.org/10.5194/tc-17-2185-2023, 2023
Short summary
Short summary
To better understand the Greenland Ice Sheet’s firn layer and its ability to buffer sea level rise by storing meltwater, we analyze firn density observations and output from two firn models. We find that both models, one physics-based and one semi-empirical, simulate realistic density and firn air content when compared to observations. The models differ in their representation of firn air content, highlighting the uncertainty in physical processes and the paucity of deep-firn measurements.
Michelle L. Maclennan, Jan T. M. Lenaerts, Christine A. Shields, Andrew O. Hoffman, Nander Wever, Megan Thompson-Munson, Andrew C. Winters, Erin C. Pettit, Theodore A. Scambos, and Jonathan D. Wille
The Cryosphere, 17, 865–881, https://doi.org/10.5194/tc-17-865-2023, https://doi.org/10.5194/tc-17-865-2023, 2023
Short summary
Short summary
Atmospheric rivers are air masses that transport large amounts of moisture and heat towards the poles. Here, we use a combination of weather observations and models to quantify the amount of snowfall caused by atmospheric rivers in West Antarctica which is about 10 % of the total snowfall each year. We then examine a unique event that occurred in early February 2020, when three atmospheric rivers made landfall over West Antarctica in rapid succession, leading to heavy snowfall and surface melt.
Nicole Clerx, Horst Machguth, Andrew Tedstone, Nicolas Jullien, Nander Wever, Rolf Weingartner, and Ole Roessler
The Cryosphere, 16, 4379–4401, https://doi.org/10.5194/tc-16-4379-2022, https://doi.org/10.5194/tc-16-4379-2022, 2022
Short summary
Short summary
Meltwater runoff is one of the main contributors to mass loss on the Greenland Ice Sheet that influences global sea level rise. However, it remains unclear where meltwater runs off and what processes cause this. We measured the velocity of meltwater flow through snow on the ice sheet, which ranged from 0.17–12.8 m h−1 for vertical percolation and from 1.3–15.1 m h−1 for lateral flow. This is an important step towards understanding where, when and why meltwater runoff occurs on the ice sheet.
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
Short summary
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.
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.
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.
Adrien Michel, Bettina Schaefli, Nander Wever, Harry Zekollari, Michael Lehning, and Hendrik Huwald
Hydrol. Earth Syst. Sci., 26, 1063–1087, https://doi.org/10.5194/hess-26-1063-2022, https://doi.org/10.5194/hess-26-1063-2022, 2022
Short summary
Short summary
This study presents an extensive study of climate change impacts on river temperature in Switzerland. Results show that, even for low-emission scenarios, water temperature increase will lead to adverse effects for both ecosystems and socio-economic sectors throughout the 21st century. For high-emission scenarios, the effect will worsen. This study also shows that water seasonal warming will be different between the Alpine regions and the lowlands. Finally, efficiency of models is assessed.
Karen E. Alley, Christian T. Wild, Adrian Luckman, Ted A. Scambos, Martin Truffer, Erin C. Pettit, Atsuhiro Muto, Bruce Wallin, Marin Klinger, Tyler Sutterley, Sarah F. Child, Cyrus Hulen, Jan T. M. Lenaerts, Michelle Maclennan, Eric Keenan, and Devon Dunmire
The Cryosphere, 15, 5187–5203, https://doi.org/10.5194/tc-15-5187-2021, https://doi.org/10.5194/tc-15-5187-2021, 2021
Short summary
Short summary
We present a 20-year, satellite-based record of velocity and thickness change on the Thwaites Eastern Ice Shelf (TEIS), the largest remaining floating extension of Thwaites Glacier (TG). TG holds the single greatest control on sea-level rise over the next few centuries, so it is important to understand changes on the TEIS, which controls much of TG's flow into the ocean. Our results suggest that the TEIS is progressively destabilizing and is likely to disintegrate over the next few decades.
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.
Devon Dunmire, Alison F. Banwell, Nander Wever, Jan T. M. Lenaerts, and Rajashree Tri Datta
The Cryosphere, 15, 2983–3005, https://doi.org/10.5194/tc-15-2983-2021, https://doi.org/10.5194/tc-15-2983-2021, 2021
Short summary
Short summary
Here, we automatically detect buried lakes (meltwater lakes buried below layers of snow) across the Greenland Ice Sheet, providing insight into a poorly studied meltwater feature. For 2018 and 2019, we compare areal extent of buried lakes. We find greater buried lake extent in 2019, especially in northern Greenland, which we attribute to late-summer surface melt and high autumn temperatures. We also provide evidence that buried lakes form via different processes across Greenland.
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.
Eric Keenan, Nander Wever, Marissa Dattler, Jan T. M. Lenaerts, Brooke Medley, Peter Kuipers Munneke, and Carleen Reijmer
The Cryosphere, 15, 1065–1085, https://doi.org/10.5194/tc-15-1065-2021, https://doi.org/10.5194/tc-15-1065-2021, 2021
Short summary
Short summary
Snow density is required to convert observed changes in ice sheet volume into mass, which ultimately drives ice sheet contribution to sea level rise. However, snow properties respond dynamically to wind-driven redistribution. Here we include a new wind-driven snow density scheme into an existing snow model. Our results demonstrate an improved representation of snow density when compared to observations and can therefore be used to improve retrievals of ice sheet mass balance.
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.
Richard Essery, Hyungjun Kim, Libo Wang, Paul Bartlett, Aaron Boone, Claire Brutel-Vuilmet, Eleanor Burke, Matthias Cuntz, Bertrand Decharme, Emanuel Dutra, Xing Fang, Yeugeniy Gusev, Stefan Hagemann, Vanessa Haverd, Anna Kontu, Gerhard Krinner, Matthieu Lafaysse, Yves Lejeune, Thomas Marke, Danny Marks, Christoph Marty, Cecile B. Menard, Olga Nasonova, Tomoko Nitta, John Pomeroy, Gerd Schädler, Vladimir Semenov, Tatiana Smirnova, Sean Swenson, Dmitry Turkov, Nander Wever, and Hua Yuan
The Cryosphere, 14, 4687–4698, https://doi.org/10.5194/tc-14-4687-2020, https://doi.org/10.5194/tc-14-4687-2020, 2020
Short summary
Short summary
Climate models are uncertain in predicting how warming changes snow cover. This paper compares 22 snow models with the same meteorological inputs. Predicted trends agree with observations at four snow research sites: winter snow cover does not start later, but snow now melts earlier in spring than in the 1980s at two of the sites. Cold regions where snow can last until late summer are predicted to be particularly sensitive to warming because the snow then melts faster at warmer times of year.
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.
Louis Quéno, Charles Fierz, Alec van Herwijnen, Dylan Longridge, and Nander Wever
The Cryosphere, 14, 3449–3464, https://doi.org/10.5194/tc-14-3449-2020, https://doi.org/10.5194/tc-14-3449-2020, 2020
Short summary
Short summary
Deep ice layers may form in the snowpack due to preferential water flow with impacts on the snowpack mechanical, hydrological and thermodynamical properties. We studied their formation and evolution at a high-altitude alpine site, combining a comprehensive observation dataset at a daily frequency (with traditional snowpack observations, penetration resistance and radar measurements) and detailed snowpack modeling, including a new parameterization of ice formation in the 1-D SNOWPACK model.
Thore Kausch, Stef Lhermitte, Jan T. M. Lenaerts, Nander Wever, Mana Inoue, Frank Pattyn, Sainan Sun, Sarah Wauthy, Jean-Louis Tison, and Willem Jan van de Berg
The Cryosphere, 14, 3367–3380, https://doi.org/10.5194/tc-14-3367-2020, https://doi.org/10.5194/tc-14-3367-2020, 2020
Short summary
Short summary
Ice rises are elevated parts of the otherwise flat ice shelf. Here we study the impact of an Antarctic ice rise on the surrounding snow accumulation by combining field data and modeling. Our results show a clear difference in average yearly snow accumulation between the windward side, the leeward side and the peak of the ice rise due to differences in snowfall and wind erosion. This is relevant for the interpretation of ice core records, which are often drilled on the peak of an ice rise.
Rebecca Dell, Neil Arnold, Ian Willis, Alison Banwell, Andrew Williamson, Hamish Pritchard, and Andrew Orr
The Cryosphere, 14, 2313–2330, https://doi.org/10.5194/tc-14-2313-2020, https://doi.org/10.5194/tc-14-2313-2020, 2020
Short summary
Short summary
A semi-automated method is developed from pre-existing work to track surface water bodies across Antarctic ice shelves over time, using data from Sentinel-2 and Landsat 8. This method is applied to the Nivlisen Ice Shelf for the 2016–2017 melt season. The results reveal two large linear meltwater systems, which hold 63 % of the peak total surface meltwater volume on 26 January 2017. These meltwater systems migrate towards the ice shelf front as the melt season progresses.
Nander Wever, Leonard Rossmann, Nina Maaß, Katherine C. Leonard, Lars Kaleschke, Marcel Nicolaus, and Michael Lehning
Geosci. Model Dev., 13, 99–119, https://doi.org/10.5194/gmd-13-99-2020, https://doi.org/10.5194/gmd-13-99-2020, 2020
Short summary
Short summary
Sea ice is an important component of the global climate system. The presence of a snow layer covering sea ice can impact ice mass and energy budgets. The detailed, physics-based, multi-layer snow model SNOWPACK was modified to simulate the snow–sea-ice system, providing simulations of the snow microstructure, water percolation and flooding, and superimposed ice formation. The model is applied to in situ measurements from snow and ice mass-balance buoys installed in the Antarctic Weddell Sea.
Cécile B. Ménard, Richard Essery, Alan Barr, Paul Bartlett, Jeff Derry, Marie Dumont, Charles Fierz, Hyungjun Kim, Anna Kontu, Yves Lejeune, Danny Marks, Masashi Niwano, Mark Raleigh, Libo Wang, and Nander Wever
Earth Syst. Sci. Data, 11, 865–880, https://doi.org/10.5194/essd-11-865-2019, https://doi.org/10.5194/essd-11-865-2019, 2019
Short summary
Short summary
This paper describes long-term meteorological and evaluation datasets from 10 reference sites for use in snow modelling. We demonstrate how data sharing is crucial to the identification of errors and how the publication of these datasets contributes to good practice, consistency, and reproducibility in geosciences. The ease of use, availability, and quality of the datasets will help model developers quantify and reduce model uncertainties and errors.
Gerhard Krinner, Chris Derksen, Richard Essery, Mark Flanner, Stefan Hagemann, Martyn Clark, Alex Hall, Helmut Rott, Claire Brutel-Vuilmet, Hyungjun Kim, Cécile B. Ménard, Lawrence Mudryk, Chad Thackeray, Libo Wang, Gabriele Arduini, Gianpaolo Balsamo, Paul Bartlett, Julia Boike, Aaron Boone, Frédérique Chéruy, Jeanne Colin, Matthias Cuntz, Yongjiu Dai, Bertrand Decharme, Jeff Derry, Agnès Ducharne, Emanuel Dutra, Xing Fang, Charles Fierz, Josephine Ghattas, Yeugeniy Gusev, Vanessa Haverd, Anna Kontu, Matthieu Lafaysse, Rachel Law, Dave Lawrence, Weiping Li, Thomas Marke, Danny Marks, Martin Ménégoz, Olga Nasonova, Tomoko Nitta, Masashi Niwano, John Pomeroy, Mark S. Raleigh, Gerd Schaedler, Vladimir Semenov, Tanya G. Smirnova, Tobias Stacke, Ulrich Strasser, Sean Svenson, Dmitry Turkov, Tao Wang, Nander Wever, Hua Yuan, Wenyan Zhou, and Dan Zhu
Geosci. Model Dev., 11, 5027–5049, https://doi.org/10.5194/gmd-11-5027-2018, https://doi.org/10.5194/gmd-11-5027-2018, 2018
Short summary
Short summary
This paper provides an overview of a coordinated international experiment to determine the strengths and weaknesses in how climate models treat snow. The models will be assessed at point locations using high-quality reference measurements and globally using satellite-derived datasets. How well climate models simulate snow-related processes is important because changing snow cover is an important part of the global climate system and provides an important freshwater resource for human use.
Christian Gabriel Sommer, Nander Wever, Charles Fierz, and Michael Lehning
The Cryosphere, 12, 2923–2939, https://doi.org/10.5194/tc-12-2923-2018, https://doi.org/10.5194/tc-12-2923-2018, 2018
Short summary
Short summary
Wind packing is how wind produces hard crusts at the surface of the snowpack. This is relevant for the local mass balance in polar regions. However, not much is known about this process and it is difficult to capture its high spatial and temporal variability. A wind-packing event was measured in Antarctica. It could be quantified how drifting snow leads to wind packing and generates barchan dunes. The documentation of these deposition dynamics is an important step in understanding polar snow.
Reinhold Spang, Lars Hoffmann, Rolf Müller, Jens-Uwe Grooß, Ines Tritscher, Michael Höpfner, Michael Pitts, Andrew Orr, and Martin Riese
Atmos. Chem. Phys., 18, 5089–5113, https://doi.org/10.5194/acp-18-5089-2018, https://doi.org/10.5194/acp-18-5089-2018, 2018
Short summary
Short summary
This paper represents an unprecedented pole-covering day- and nighttime climatology of the polar stratospheric clouds (PSCs) based on satellite measurements, their spatial distribution, and composition of different particle types. The climatology has a high potential for the validation and improvement of PSC schemes in chemical transport and chemistry–climate models, which is important for a better prediction of future polar ozone loss in a changing climate.
Sebastian Würzer, Nander Wever, Roman Juras, Michael Lehning, and Tobias Jonas
Hydrol. Earth Syst. Sci., 21, 1741–1756, https://doi.org/10.5194/hess-21-1741-2017, https://doi.org/10.5194/hess-21-1741-2017, 2017
Short summary
Short summary
We discuss a dual-domain water transport model in a physics-based snowpack model to account for preferential flow (PF) in addition to matrix flow. So far no operationally used snow model has explicitly accounted for PF. The new approach is compared to existing water transport models and validated against in situ data from sprinkling and natural rain-on-snow (ROS) events. Our work demonstrates the benefit of considering PF in modelling hourly snowpack runoff, especially during ROS conditions.
Lars Hoffmann, Reinhold Spang, Andrew Orr, M. Joan Alexander, Laura A. Holt, and Olaf Stein
Atmos. Chem. Phys., 17, 2901–2920, https://doi.org/10.5194/acp-17-2901-2017, https://doi.org/10.5194/acp-17-2901-2017, 2017
Short summary
Short summary
We introduce a 10-year record (2003–2012) of AIRS/Aqua observations of gravity waves in the polar lower stratosphere. The data set was optimized to study the impact of gravity waves on the formation of polar stratospheric clouds (PSCs). We discuss the temporal and spatial patterns of gravity wave activity, validate explicitly resolved small-scale temperature fluctuations in the ECMWF data, and present a survey of gravity-wave-induced PSC formation events using joint AIRS and MIPAS observations.
Reinhold Spang, Lars Hoffmann, Michael Höpfner, Sabine Griessbach, Rolf Müller, Michael C. Pitts, Andrew M. W. Orr, and Martin Riese
Atmos. Meas. Tech., 9, 3619–3639, https://doi.org/10.5194/amt-9-3619-2016, https://doi.org/10.5194/amt-9-3619-2016, 2016
Short summary
Short summary
We present a new classification approach for different polar stratospheric cloud types. The so-called Bayesian classifier estimates the most likely probability that one of the three PSC types (ice, NAT, or STS) dominates the characteristics of a measured infrared spectrum. The entire measurement period of the satellite instrument MIPAS from July 2002 to April 2013 is processed using the new classifier.
A. Orr, J. S. Hosking, L. Hoffmann, J. Keeble, S. M. Dean, H. K. Roscoe, N. L. Abraham, S. Vosper, and P. Braesicke
Atmos. Chem. Phys., 15, 1071–1086, https://doi.org/10.5194/acp-15-1071-2015, https://doi.org/10.5194/acp-15-1071-2015, 2015
Related subject area
Discipline: Snow | Subject: Antarctic
Surface processes and drivers of the snow water stable isotopic composition at Dome C, East Antarctica – a multi-dataset and modelling analysis
Dual-frequency radar observations of snowmelt processes on Antarctic perennial sea ice by CFOSCAT and ASCAT
How do extreme ENSO events affect Antarctic surface mass balance?
Contribution of blowing-snow sublimation to the surface mass balance of Antarctica
A decade (2008–2017) of water stable isotope composition of precipitation at Concordia Station, East Antarctica
Firn air content changes on Antarctic ice shelves under three future warming scenarios
Extreme events of snow grain size increase in East Antarctica and their relationship with meteorological conditions
Local spatial variability in the occurrence of summer precipitation in the Sør Rondane Mountains, Antarctica
Characteristics of the 1979–2020 Antarctic firn layer simulated with IMAU-FDM v1.2A
The sensitivity of satellite microwave observations to liquid water in the Antarctic snowpack
Spectral characterization, radiative forcing and pigment content of coastal Antarctic snow algae: approaches to spectrally discriminate red and green communities and their impact on snowmelt
Distinguishing the impacts of ozone and ozone-depleting substances on the recent increase in Antarctic surface mass balance
Representative surface snow density on the East Antarctic Plateau
Brief communication: Evaluating Antarctic precipitation in ERA5 and CMIP6 against CloudSat observations
Drifting-snow statistics from multiple-year autonomous measurements in Adélie Land, East Antarctica
Impact of exhaust emissions on chemical snowpack composition at Concordia Station, Antarctica
Observation of the process of snow accumulation on the Antarctic Plateau by time lapse laser scanning
Evaluation of CloudSat snowfall rate profiles by a comparison with in situ micro-rain radar observations in East Antarctica
Investigation of a wind-packing event in Queen Maud Land, Antarctica
Archival processes of the water stable isotope signal in East Antarctic ice cores
Inès Ollivier, Hans Christian Steen-Larsen, Barbara Stenni, Laurent Arnaud, Mathieu Casado, Alexandre Cauquoin, Giuliano Dreossi, Christophe Genthon, Bénédicte Minster, Ghislain Picard, Martin Werner, and Amaëlle Landais
The Cryosphere, 19, 173–200, https://doi.org/10.5194/tc-19-173-2025, https://doi.org/10.5194/tc-19-173-2025, 2025
Short summary
Short summary
The role of post-depositional processes taking place at the ice sheet's surface on the water stable isotope signal measured in polar ice cores is not fully understood. Using field observations and modelling results, we show that the original precipitation isotopic signal at Dome C, East Antarctica, is modified by post-depositional processes and provide the first quantitative estimation of their mean impact on the isotopic signal observed in the snow.
Rui Xu, Chaofang Zhao, Stefanie Arndt, and Christian Haas
The Cryosphere, 18, 5769–5788, https://doi.org/10.5194/tc-18-5769-2024, https://doi.org/10.5194/tc-18-5769-2024, 2024
Short summary
Short summary
The onset of snowmelt on Antarctic sea ice is an important indicator of sea ice change. In this study, we used two radar scatterometers to detect the onset of snowmelt on perennial Antarctic sea ice. Results show that since 2007, snowmelt onset has demonstrated strong interannual and regional variabilities. We also found that the difference in snowmelt onsets between the two scatterometers is closely related to snow metamorphism.
Jessica M. A. Macha, Andrew N. Mackintosh, Felicity S. Mccormack, Benjamin J. Henley, Helen V. McGregor, Christiaan T. van Dalum, and Ariaan Purich
EGUsphere, https://doi.org/10.5194/egusphere-2024-3425, https://doi.org/10.5194/egusphere-2024-3425, 2024
Short summary
Short summary
Extreme El Niño-Southern Oscillation (ENSO) events have global impacts but their Antarctic impacts are poorly understood. Examining Antarctic snow accumulation impacts of past observed extreme ENSO events, we show that accumulation changes differ between events & are unsignificant during most events. Remarkable changes occur during 2015/16 & in Enderby Land during all extreme El Niños. Historical data limits conclusions but future greater extremes could cause Antarctic accumulation changes.
Srinidhi Gadde and Willem Jan van de Berg
The Cryosphere, 18, 4933–4953, https://doi.org/10.5194/tc-18-4933-2024, https://doi.org/10.5194/tc-18-4933-2024, 2024
Short summary
Short summary
Blowing-snow sublimation is the major loss term in the mass balance of Antarctica. In this study we update the blowing-snow representation in the Regional Atmospheric Climate Model (RACMO). With the updates, results compare well with observations from East Antarctica. Also, the continent-wide variation of blowing snow compares well with satellite observations. Hence, the updates provide a clear step forward in producing a physically sound and reliable estimate of the mass balance of Antarctica.
Giuliano Dreossi, Mauro Masiol, Barbara Stenni, Daniele Zannoni, Claudio Scarchilli, Virginia Ciardini, Mathieu Casado, Amaëlle Landais, Martin Werner, Alexandre Cauquoin, Giampietro Casasanta, Massimo Del Guasta, Vittoria Posocco, and Carlo Barbante
The Cryosphere, 18, 3911–3931, https://doi.org/10.5194/tc-18-3911-2024, https://doi.org/10.5194/tc-18-3911-2024, 2024
Short summary
Short summary
Oxygen and hydrogen stable isotopes have been extensively used to reconstruct past temperatures, with precipitation representing the input signal of the isotopic records in ice cores. We present a 10-year record of stable isotopes in daily precipitation at Concordia Station: this is the longest record for inland Antarctica and represents a benchmark for quantifying post-depositional processes and improving the paleoclimate interpretation of ice cores.
Sanne B. M. Veldhuijsen, Willem Jan van de Berg, Peter Kuipers Munneke, and Michiel R. van den Broeke
The Cryosphere, 18, 1983–1999, https://doi.org/10.5194/tc-18-1983-2024, https://doi.org/10.5194/tc-18-1983-2024, 2024
Short summary
Short summary
We use the IMAU firn densification model to simulate the 21st-century evolution of Antarctic firn air content. Ice shelves on the Antarctic Peninsula and the Roi Baudouin Ice Shelf in Dronning Maud Land are particularly vulnerable to total firn air content (FAC) depletion. Our results also underline the potentially large vulnerability of low-accumulation ice shelves to firn air depletion through ice slab formation.
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
Short summary
Short summary
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.
Alfonso Ferrone, Étienne Vignon, Andrea Zonato, and Alexis Berne
The Cryosphere, 17, 4937–4956, https://doi.org/10.5194/tc-17-4937-2023, https://doi.org/10.5194/tc-17-4937-2023, 2023
Short summary
Short summary
In austral summer 2019/2020, three K-band Doppler profilers were deployed across the Sør Rondane Mountains, south of the Belgian base Princess Elisabeth Antarctica. Their measurements, along with atmospheric simulations and reanalyses, have been used to study the spatial variability in precipitation over the region, as well as investigate the interaction between the complex terrain and the typical flow associated with precipitating systems.
Sanne B. M. Veldhuijsen, Willem Jan van de Berg, Max Brils, Peter Kuipers Munneke, and Michiel R. van den Broeke
The Cryosphere, 17, 1675–1696, https://doi.org/10.5194/tc-17-1675-2023, https://doi.org/10.5194/tc-17-1675-2023, 2023
Short summary
Short summary
Firn is the transition of snow to glacier ice and covers 99 % of the Antarctic ice sheet. Knowledge about the firn layer and its variability is important, as it impacts satellite-based estimates of ice sheet mass change. Also, firn contains pores in which nearly all of the surface melt is retained. Here, we improve a semi-empirical firn model and simulate the firn characteristics for the period 1979–2020. We evaluate the performance with field and satellite measures and test its sensitivity.
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
Short summary
Short summary
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.
Alia L. Khan, Heidi M. Dierssen, Ted A. Scambos, Juan Höfer, and Raul R. Cordero
The Cryosphere, 15, 133–148, https://doi.org/10.5194/tc-15-133-2021, https://doi.org/10.5194/tc-15-133-2021, 2021
Short summary
Short summary
We present radiative forcing (RF) estimates by snow algae in the Antarctic Peninsula (AP) region from multi-year measurements of solar radiation and ground-based hyperspectral characterization of red and green snow algae collected during a brief field expedition in austral summer 2018. Mean daily RF was double for green (~26 W m−2) vs. red (~13 W m−2) snow algae during the peak growing season, which is on par with midlatitude dust attributions capable of advancing snowmelt.
Rei Chemke, Michael Previdi, Mark R. England, and Lorenzo M. Polvani
The Cryosphere, 14, 4135–4144, https://doi.org/10.5194/tc-14-4135-2020, https://doi.org/10.5194/tc-14-4135-2020, 2020
Short summary
Short summary
The increase in Antarctic surface mass balance (SMB, precipitation vs. evaporation/sublimation) is projected to mitigate sea-level rise. Here we show that nearly half of this increase over the 20th century is attributed to stratospheric ozone depletion and ozone-depleting substance (ODS) emissions. Our results suggest that the phaseout of ODS by the Montreal Protocol, and the recovery of stratospheric ozone, will act to decrease the SMB over the 21st century and the mitigation of sea-level rise.
Alexander H. Weinhart, Johannes Freitag, Maria Hörhold, Sepp Kipfstuhl, and Olaf Eisen
The Cryosphere, 14, 3663–3685, https://doi.org/10.5194/tc-14-3663-2020, https://doi.org/10.5194/tc-14-3663-2020, 2020
Short summary
Short summary
From 1 m snow profiles along a traverse on the East Antarctic Plateau, we calculated a representative surface snow density of 355 kg m−3 for this region with an error less than 1.5 %.
This density is 10 % higher and density fluctuations seem to happen on smaller scales than climate model outputs suggest. Our study can help improve the parameterization of surface snow density in climate models to reduce the error in future sea level predictions.
Marie-Laure Roussel, Florentin Lemonnier, Christophe Genthon, and Gerhard Krinner
The Cryosphere, 14, 2715–2727, https://doi.org/10.5194/tc-14-2715-2020, https://doi.org/10.5194/tc-14-2715-2020, 2020
Short summary
Short summary
The Antarctic precipitation is evaluated against space radar data in the most recent climate model intercomparison CMIP6 and reanalysis ERA5. The seasonal cycle is mostly well reproduced, but relative errors are higher in areas of complex topography, particularly in the higher-resolution models. At continental and regional scales all results are biased high, with no significant progress in the more recent models. Predicting Antarctic contribution to sea level still requires model improvements.
Charles Amory
The Cryosphere, 14, 1713–1725, https://doi.org/10.5194/tc-14-1713-2020, https://doi.org/10.5194/tc-14-1713-2020, 2020
Short summary
Short summary
This paper presents an assessment of drifting-snow occurrences and snow mass transport from up to 9 years (2010–2018) of half-hourly observational records collected at two remote locations in coastal Adelie Land (East Antarctica) using second-generation IAV Engineering acoustic FlowCapt sensors. The dataset is freely available to the scientific community and can be used to complement satellite products and evaluate snow-transport models close to the surface and at high temporal frequency.
Detlev Helmig, Daniel Liptzin, Jacques Hueber, and Joel Savarino
The Cryosphere, 14, 199–209, https://doi.org/10.5194/tc-14-199-2020, https://doi.org/10.5194/tc-14-199-2020, 2020
Short summary
Short summary
We present 15 months of trace gas observations from air withdrawn within the snowpack and from above the snow at Concordia Station in Antarctica. The data show occasional positive spikes, indicative of pollution from the station generator. The pollution signal can be seen in snowpack air shortly after it is observed above the snow surface, and lasting for up to several days, much longer than above the surface.
Ghislain Picard, Laurent Arnaud, Romain Caneill, Eric Lefebvre, and Maxim Lamare
The Cryosphere, 13, 1983–1999, https://doi.org/10.5194/tc-13-1983-2019, https://doi.org/10.5194/tc-13-1983-2019, 2019
Short summary
Short summary
To study how snow accumulates in Antarctica, we analyze daily surface elevation recorded by an automatic laser scanner. We show that new snow often accumulates in thick patches covering a small fraction of the surface. Most patches are removed by erosion within weeks, implying that only a few contribute to the snowpack. This explains the heterogeneity on the surface and in the snowpack. These findings are important for surface mass and energy balance, photochemistry, and ice core interpretation.
Florentin Lemonnier, Jean-Baptiste Madeleine, Chantal Claud, Christophe Genthon, Claudio Durán-Alarcón, Cyril Palerme, Alexis Berne, Niels Souverijns, Nicole van Lipzig, Irina V. Gorodetskaya, Tristan L'Ecuyer, and Norman Wood
The Cryosphere, 13, 943–954, https://doi.org/10.5194/tc-13-943-2019, https://doi.org/10.5194/tc-13-943-2019, 2019
Short summary
Short summary
Evaluation of the vertical precipitation rate profiles of CloudSat radar by comparison with two surface-based micro-rain radars (MRR) located at two antarctic stations gives a near-perfect correlation between both datasets, even though climatic and geographic conditions are different for the stations. A better understanding and reassessment of CloudSat uncertainties ranging from −13 % up to +22 % confirms the robustness of the CloudSat retrievals of snowfall over Antarctica.
Christian Gabriel Sommer, Nander Wever, Charles Fierz, and Michael Lehning
The Cryosphere, 12, 2923–2939, https://doi.org/10.5194/tc-12-2923-2018, https://doi.org/10.5194/tc-12-2923-2018, 2018
Short summary
Short summary
Wind packing is how wind produces hard crusts at the surface of the snowpack. This is relevant for the local mass balance in polar regions. However, not much is known about this process and it is difficult to capture its high spatial and temporal variability. A wind-packing event was measured in Antarctica. It could be quantified how drifting snow leads to wind packing and generates barchan dunes. The documentation of these deposition dynamics is an important step in understanding polar snow.
Mathieu Casado, Amaelle Landais, Ghislain Picard, Thomas Münch, Thomas Laepple, Barbara Stenni, Giuliano Dreossi, Alexey Ekaykin, Laurent Arnaud, Christophe Genthon, Alexandra Touzeau, Valerie Masson-Delmotte, and Jean Jouzel
The Cryosphere, 12, 1745–1766, https://doi.org/10.5194/tc-12-1745-2018, https://doi.org/10.5194/tc-12-1745-2018, 2018
Short summary
Short summary
Ice core isotopic records rely on the knowledge of the processes involved in the archival processes of the snow. In the East Antarctic Plateau, post-deposition processes strongly affect the signal found in the surface and buried snow compared to the initial climatic signal. We evaluate the different contributions to the surface snow isotopic composition between the precipitation and the exchanges with the atmosphere and the variability of the isotopic signal found in profiles from snow pits.
Cited articles
Abel, S. J., Boutle, I. A., Waite, K., Fox, S., Brown, P. R. A., Cotton, R., Lloyd, G., Choularton, T. W., and Bower, K. N.: The role of precipitation in controlling the transition from stratocumulus to cumulus clouds in a Northern Hemisphere cold-air outbreak, J. Atmos. Sci., 74, 2293–2314, https://doi.org/10.1175/JAS-D-16-0362.1, 2017.
Adusumilli, S., Fish, M. A., Fricker, H. A., and Medley, B.: Atmospheric river precipitation contributed to rapid increases in surface height of the west Antarctic ice sheet in 2019, Geophys. Res. Lett., 48, e2020GL091076, https://doi.org/10.1029/2020GL091076, 2021.
Alley, K., Scambos, T., Siegfried, M., and Fricker, H. A.: Impacts of warm water on Antarctic ice shelf stability through basal channel formation, Nat. Geosci., 9, 290–293, https://doi.org/10.1038/ngeo2675, 2016.
Alley, K. E., Wild, C. T., Luckman, A., Scambos, T. A., Truffer, M., Pettit, E. C., Muto, A., Wallin, B., Klinger, M., Sutterley, T., Child, S. F., Hulen, C., Lenaerts, J. T. M., Maclennan, M., Keenan, E., and Dunmire, D.: Two decades of dynamic change and progressive destabilization on the Thwaites Eastern Ice Shelf, The Cryosphere, 15, 5187–5203, https://doi.org/10.5194/tc-15-5187-2021, 2021.
Baiman, R., Winters, A. C., Pohl, B., Favier, V., Wille, J. D., and Clem, K. R.: Synoptic and planetary-scale dynamics modulate Antarctic atmospheric river precipitation intensity, Commun. Earth Environ., 5, 127, https://doi.org/10.1038/s43247-024-01307-9, 2024.
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.
Bechtold, P., Cuijpers, J. W. M., Mascart, P., and Trouilhet, P.: Modeling of Trade Wind Cumuli with a Low-Order Turbulence Model: Toward a Unified Description of Cu and Se Clouds in Meteorological Models, J. Atmos. Sci., 52, 455–463, https://doi.org/10.1175/1520-0469(1995)052<0455:MOTWCW>2.0.CO;2, 1995.
Bengtsson, L., Andrae, U., Aspelien, T., Batrak, Y., Calvo, J., de Rooy, W., Gleeson, E., Hansen-Sass, B., Homleid, M., Hortal, M., Ivarsson, K.-I., Lenderink, G., Niemelä, S., Nielsen, K. P., Onvlee, J., Rontu, L., Samuelsson, P., Muñoz, D. S., Subias, A., Tijm, S., Toll, V., Yang, X., and Køltzow, M. Ø.: The HARMONIE–AROME Model Configuration in the ALADIN–HIRLAM NWP System, Mon. Weather Rev., 145, 1919–1935, https://doi.org/10.1175/MWR-D-16-0417.1, 2017.
Belušić, D., de Vries, H., Dobler, A., Landgren, O., Lind, P., Lindstedt, D., Pedersen, R. A., Sánchez-Perrino, J. C., Toivonen, E., van Ulft, B., Wang, F., Andrae, U., Batrak, Y., Kjellström, E., Lenderink, G., Nikulin, G., Pietikäinen, J.-P., Rodríguez-Camino, E., Samuelsson, P., van Meijgaard, E., and Wu, M.: HCLIM38: a flexible regional climate model applicable for different climate zones from coarse to convection-permitting scales, Geosci. Model Dev., 13, 1311–1333, https://doi.org/10.5194/gmd-13-1311-2020, 2020.
Bodas-Salcedo, A., Hill, P. G., Furtado, K., Williams, K. D., Field, P. R., Manners, J. C., Hyder, P., and Kato, S.: Large contribution of supercooled liquid clouds to the solar radiation budget of the Southern Ocean, J. Climate, 29, 4213–4228, https://doi.org/10.1175/JCLI-D-15-0564.1, 2016.
Box, J. E., Wehrlé, A., van As, D., Fausto, R. S., Kjeldsen, K. K., Dachauer, A., Ahlstrøm, A. P., and Picard, G.: Greenland ice sheet rainfall, heat and albedo feedback impacts from the mid-August 2021 atmospheric river, Geophys. Res. Lett., 49, e2021GL097356, https://doi.org/10.1029/2021GL097356, 2022.
Box, J. E., Nielsen, K. P., Yang, X., Niwano, M., Wehrlé, A., van As, D., Fettweis, X., Køltzow, M. A., Palmason, B., Fausto, R. S., and Noël, B.: Greenland ice sheet rainfall climatology, extremes and atmospheric river rapids, Met. Apps., 30, e2134, https://doi.org/10.1002/met.2134, 2023.
Bozkurt, D., Rondanelli, R., Marín, J. C., and Garreaud, R.: Foehn event triggered by an atmospheric river underlies record-setting temperature along continental Antarctica, J. Geophys. Res.-Atmos., 123, 3871–3892, https://doi.org/10.1002/2017JD027796, 2018.
Bozkurt, D., Carrasco, J., Cordero, R., Fernandoy, F., Gómez, A., Carrillo, B., and Guan, B.: Atmospheric river brings warmth and rainfall to the northern Antarctic Peninsula during the mid-austral winter of 2023, Geophys. Res. Lett., 51, e2024GL108391, https://doi.org/10.1029/2024GL108391, 2024.
Bromwich, D. H., Otieno, F. O., Hines, K. M., Manning, K. W., and Shilo, E.: Comprehensive evaluation of polar weather research and forecasting model performance in the Antarctic, J. Geophys. Res.-Atmos., 118, 274–292, https://doi.org/10.1029/2012JD018139, 2013.
Bromwich, D. H., Gorodetskaya, I. V., Carpentier, S., Alexander, S., Bazile, E., Heinrich, V. J., Massonnet, F., Powers, J. G., Carrasco, J. F., Cayette, A., and Zou, X.: Winter Targeted Observing Periods during the Year of Polar Prediction in the Southern Hemisphere (YOPP-SH), B. Am. Meteorol. Soc., 105, E1662–E1684, https://doi.org/10.1175/BAMS-D-22-0249.1, 2024.
Bush, M., Boutle, I., Edwards, J., Finnenkoetter, A., Franklin, C., Hanley, K., Jayakumar, A., Lewis, H., Lock, A., Mittermaier, M., Mohandas, S., North, R., Porson, A., Roux, B., Webster, S., and Weeks, M.: The second Met Office Unified Model–JULES Regional Atmosphere and Land configuration, RAL2, Geosci. Model Dev., 16, 1713–1734, https://doi.org/10.5194/gmd-16-1713-2023, 2023.
Chemke, R.: The future poleward shift of Southern Hemisphere summer mid-latitude storm tracks stems from ocean coupling, Nat. Commun., 13, 1730, https://doi.org/10.1038/s41467-022-29392-4, 2022.
Clapeyron, B. P. E.: Memoir sur la puissance motrice de la chaleur, Journal de l’École royale polytechnique 23, 153–190, 1834.
Clausius, R.: Ueber die bewegende Kraft der Wärme und die Gesetze, welche sich daraus für die Wärmelehre selbst ableiten lassen, Ann. Phys., 155, 368–397, https://doi.org/10.1002/andp.18501550306, 1850.
Cullen, M. J. P.: The unified forecast/climate model, Meteorol. Mag., 122, 81–94, 1993.
Davison, B. J., Hogg, A. E., Rigby, R., Veldhuijsen, S., van Wessem, J. M., van den Broeke, M. R., Holland, P. R., Selley, H. L., and Dutrieux, P.: Sea level rise from West Antarctic mass loss significantly modified by large snowfall anomalies, Nat. Commun., 14, 1479, https://doi.org/10.1038/s41467-023-36990-3, 2023.
de Rooy, W. C. and Siebesma, A. P.: A Simple Parameterization for Detrainment in Shallow Cumulus, Mon. Weather Rev., 136, 560–576, https://doi.org/10.1175/2007MWR2201.1, 2008.
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.
Doyle, S. H., Hubbard, A., Van De Wal, R. S., Box, J. E., Van As, D., Scharrer, K., Meierbachtol, T. W., Smeets, P. C., Harper, J. T., Johansson, E., and Mottram, R. H.: Amplified melt and flow of the Greenland ice sheet driven by late-summer cyclonic rainfall, Nat. Geosci., 8, 647–653, https://doi.org/10.1038/ngeo2482, 2015.
ECMWF: Part IV: Physical Processes, in: IFS Documentation CY41R2, IFS Documentation, ECMWF, https://doi.org/10.21957/tr5rv27xu, 2016.
Elvidge, A. D. and Renfrew, I. A.: The causes of foehn warming in the lee of mountains, B. Am. Meteorol. Soc., 97, 455–466, https://doi.org/10.1175/BAMS-D-14-00194.1, 2016.
Fernández-González, S., Valero, F., Sánchez, J. L., Gascón, E., López, L., García-Ortega, E., and Merino, A.: Analysis of a seeder-feeder and freezing drizzle event, J. Geophys. Res.-Atmos., 120, 3984–3999, https://doi.org/10.1002/2014JD022916, 2015.
Field, P. R., Heymsfield, A. J., and Bansemer, A.: Snow Size Distribution Parameterization for Midlatitude and Tropical Ice Clouds, J. Atmos. Sci., 64, 4346–4365, https://doi.org/10.1175/2007JAS2344.1, 2007.
Finlon, J. A., Rauber, R. M., Wu, W., Zaremba, T. J., McFarquhar, G. M., Nesbitt, S. W., Schnaiter, M., Järvinen, E., Waitz, F., Hill, T. C., and DeMott, P. J.: Structure of an atmospheric river over Australia and the Southern Ocean: II. Microphysical evolution, J. Geophys. Res.-Atmos., 125, e2020JD032514, https://doi.org/10.1029/2020JD032513, 2020.
Francis, D., Fonseca, R., Mattingly, K. S., Lhermitte, S., and Walker, C.: Foehn winds at Pine Island Glacier and their role in ice changes, The Cryosphere, 17, 3041–3062, https://doi.org/10.5194/tc-17-3041-2023, 2023.
Gehring, J., Vignon, É., Billault-Roux, A. C., Ferrone, A., Protat, A., Alexander, S. P., and Berne, A.: Orographic flow influence on precipitation during an atmospheric river event at Davis, Antarctica, J. Geophys. Res.-Atmos., 127, e2021JD035210, https://doi.org/10.1029/2021JD035210, 2022.
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.
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., Orr, A., King, J. C., Renfrew, I. A., and Lachlan-Cope, T.: A 20-Year Study of Melt Processes Over Larsen C Ice Shelf Using a High-Resolution Regional Atmospheric Model: 1. Model Configuration and Validation, J. Geophys. Res.-Atmos., 127, e2021JD034766, https://doi.org/10.1029/2021JD034766, 2022.
Gilbert, E., Pishniak, D., and Torres, J. A.: Kilometre-scale regional climate model simulations of two atmospheric river case studies in West Antarctica, Zenodo [data set], https://doi.org/10.5281/zenodo.12697647, 2024.
Gorodetskaya, I. V., Durán-Alarcón, C., González-Herrero, S., Clem, K. R., Zou, X., Rowe, P., Rodriguez Imazio, P., Campos, D., Leroy-Dos Santos, C., Dutrievoz, N., and Wille, J. D.: Record-high Antarctic Peninsula temperatures and surface melt in February 2022: a compound event with an intense atmospheric river, npj Clim. Atmos. Sci., 6, 202, https://doi.org/10.1038/s41612-023-00529-6, 2023.
Harper, J., Saito, J., and Humphrey, N.: Cold season rain event has impact on Greenland's firn layer comparable to entire summer melt season, Geophys. Res. Lett., 50, e2023GL103654, https://doi.org/10.1029/2023GL103654, 2023.
He, Y., Yi, F., Liu, F., Yin, Z., Yi, Y., Zhou, J., Yu, C., and Zhang, Y.: Natural seeder-feeder process originating from mixed-phase clouds observed with polarization lidar and radiosonde at a mid-latitude plain site, J. Geophys. Res.-Atmos., 127, e2021JD036094, https://doi.org/10.1029/2021JD036094, 2022.
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., and Simmons, A.: The ERA5 global reanalysis, Q. J. Roy. Meteor. Soc., 146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020.
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 single levels from 1940 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set], https://doi.org/10.24381/cds.adbb2d47, 2023.
Hines, K. M., Bromwich, D. H., Wang, S.-H., Silber, I., Verlinde, J., and Lubin, D.: Microphysics of summer clouds in central West Antarctica simulated by the Polar Weather Research and Forecasting Model (WRF) and the Antarctic Mesoscale Prediction System (AMPS), Atmos. Chem. Phys., 19, 12431–12454, https://doi.org/10.5194/acp-19-12431-2019, 2019.
Howat, I. M., Porter, C., Smith, B. E., Noh, M.-J., and Morin, P.: The Reference Elevation Model of Antarctica, The Cryosphere, 13, 665–674, https://doi.org/10.5194/tc-13-665-2019, 2019.
Huffman, G. J., Stocker, E. F., Bolvin, D. T., Nelkin, E. J., and Tan, J.: GPM IMERG Final Precipitation L3 Half Hourly 0.1 degree x 0.1 degree V07, Greenbelt, MD, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set], https://doi.org/10.5067/GPM/IMERG/3B-HH/07, 2023.
Hyder, P., Edwards, J. M., Allan, R. P., Hewitt, H. T., Bracegirdle, T. J., Gregory, J. M., Wood, R. A., Meijers, A. J., Mulcahy, J., Field, P., and Furtado, K.: Critical Southern Ocean climate model biases traced to atmospheric model cloud errors, Nat. Commun. 9, 3625, https://doi.org/10.1038/s41467-018-05634-2, 2018.
IPCC: IPCC Special Report on the Ocean and Cryosphere in a Changing Climate, edited by: Pörtner, H.-O., Roberts, D. C., Masson-Delmotte, V., Zhai, P., Tignor, M., Poloczanska, E., Mintenbeck, K., Alegría, A., Nicolai, M., Okem, A., Petzold, J., Rama, B., and Weyer, N. M., Cambridge University Press, Cambridge, UK and New York, NY, USA, 755 pp., https://doi.org/10.1017/9781009157964, 2019.
Kain, J. S.: The Kain–Fritsch Convective Parameterization: An Update, J. Appl. Meteor. Clim., 43, 170–181, https://doi.org/10.1175/1520-0450(2004)043<0170:TKCPAU>2.0.CO;2, 2004.
Keenan, E., Wever, N., Dattler, M., Lenaerts, J. T. M., Medley, B., Kuipers Munneke, P., and Reijmer, C.: Physics-based SNOWPACK model improves representation of near-surface Antarctic snow and firn density, The Cryosphere, 15, 1065–1085, https://doi.org/10.5194/tc-15-1065-2021, 2021.
Kittel, C., Amory, C., Hofer, S., Agosta, C., Jourdain, N. C., Gilbert, E., Le Toumelin, L., Vignon, É., Gallée, H., and Fettweis, X.: Clouds drive differences in future surface melt over the Antarctic ice shelves, The Cryosphere, 16, 2655–2669, https://doi.org/10.5194/tc-16-2655-2022, 2022.
Lascaux, F., Richard, E., and Pinty, J.-P.: Numerical simulations of three different MAP IOPs and the associated microphysical processes, Q. J. Roy. Meteor. Soc., 132, 1907–1926, https://doi.org/10.1256/qj.05.197, 2006.
Lean, H. W. and Clark, P. A.: High resolution modelling of orographic rainfall, American Meteorological Society 10th Conference on Mesoscale Processes, Paper 6.7, http://ams.confex.com/ams/10Meso/techprogram/paper_62549.htm (last access: 3 February 2025), 2003.
Lehning, M., Bartelt, P., Brown, B., Russi, T., Stöckli, U., and Zimmerli, M.: Snowpack model calculations for avalanche warning based upon a new network of weather and snow stations, Cold Reg. Sci. Technol., 30, 145–157, https://doi.org/10.1016/S0165-232X(99)00022-1, 1999.
Lehning, M., Bartelt, P., Brown, B., and Fierz, C.: A physical SNOWPACK model for the Swiss avalanche warning: Part III: meteorological forcing, thin layer formation and evaluation, Cold Reg. Sci. Technol., 35, 169–184, https://doi.org/10.1016/S0165-232X(02)00072-1, 2002a.
Lehning, M., Bartelt, P., Brown, B., Fierz, C., and Satyawali, P.: A physical SNOWPACK model for the Swiss avalanche warning: Part II. Snow microstructure, Cold Reg. Sci. Technol., 35, 147–167, https://doi.org/10.1016/S0165-232X(02)00073-3, 2002b.
Lenaerts, J. T. M., Medley, B., van den Broeke, M. R. and Wouters, B.: Observing and Modeling Ice Sheet Surface Mass Balance, Rev. Geophys., 57, 376–420, https://doi.org/10.1029/2018RG000622, 2019.
Lhermitte, S., Sun, S., Shuman, C., Wouters, B., Pattyn, F., Wuite, J., Berthier, E., and Nagler, T.: Damage accelerates ice shelf instability and mass loss in Amundsen Sea Embayment, P. Natl. Acad. Sci. USA, 117, 24735–24741, https://doi.org/10.1073/pnas.1912890117, 2020.
Lu, H., Orr, A., King, J., Phillips, T., Gilbert, E., Colwell, S., and Bracegirdle, T. J.: Extreme warm events in the South Orkney Islands, Southern Ocean: Compounding influence of atmospheric rivers and föhn conditions, Q. J. Roy. Meteor. Soc., 149, 3645–3668, https://doi.org/10.1002/qj.4578, 2023.
Ma, W., Chen, G., and Guan, B.: Poleward shift of atmospheric rivers in the Southern Hemisphere in recent decades, Geophys. Res. Lett., 47, e2020GL089934, https://doi.org/10.1029/2020GL089934, 2020.
Maclennan, M. L., Lenaerts, J. T. M., Shields, C. A., Hoffman, A. O., Wever, N., Thompson-Munson, M., Winters, A. C., Pettit, E. C., Scambos, T. A., and Wille, J. D.: Climatology and surface impacts of atmospheric rivers on West Antarctica, The Cryosphere, 17, 865–881, https://doi.org/10.5194/tc-17-865-2023, 2023.
Marshall, H. P., Conway, H., and Rasmussen, L. A.: Snow densification during rain, Cold Reg. Sci. Technol., 30, 35–41, https://doi.org/10.1016/S0165-232X(99)00011-7, 1999.
McCrystall, M. R., Stroeve, J., Serreze, M., Forbes, B. C., and Screen, J. A.: New climate models reveal faster and larger increases in Arctic precipitation than previously projected, Nat. Commun., 12, 6765, https://doi.org/10.1038/s41467-021-27031-y, 2021.
Medley, B. and Thomas, E. R.: Increased snowfall over the Antarctic Ice Sheet mitigated twentieth-century sea-level rise, Nat. Clim Change, 9, 34–39, https://doi.org/10.1038/s41558-018-0356-x, 2019.
Morcrette, J.-J., Barker, H., Cole, J., Iacono, M., and Pincus, R.: Impact of a new radiation package, McRad, in the ECMWF Integrated Forecasting System, Mon. Weather Rev., 136, 4773–4798, https://doi.org/10.1175/2008MWR2363.1, 2008.
Morlighem, M.: MEaSUREs BedMachine Antarctica, Version 3, Boulder, Colorado USA, NASA National Snow and Ice Data Center Distributed Active Archive Center [data set], https://doi.org/10.5067/FPSU0V1MWUB6, 2022.
Morlighem, M., Rignot, E., Binder, T., Blankenship, D., Drews, R., Eagles, G., Eisen, O., Ferraccioli, F., Forsberg, R., Fretwell, P., and Goel, V.: Deep glacial troughs and stabilizing ridges unveiled beneath the margins of the Antarctic ice sheet, Nat. Geosci., 13, 132–137, https://doi.org/10.1038/s41561-019-0510-8, 2020.
Morrison, H., Thompson, G., and Tatarskii, V.: Impact of cloud microphysics on the development of trailing stratiform precipitation in a simulated squall line: Comparison of one- and two-moment schemes, Mon. Weather Rev., 137, 991–1007, https://doi.org/10.1175/2008MWR2556.1, 2008.
Morrison, H., van Lier-Walqui, M., Fridlind, A. M., Grabowski, W. W., Harrington, J. Y., Hoose, C., Korolev, A., Kumjian, M. R., Milbrandt, J. A., Pawlowska, H., and Posselt, D. J.: Confronting the challenge of modeling cloud and precipitation microphysics, J. Adv. Model. Earth Syst., 12, e2019MS001689, https://doi.org/10.1029/2019MS001689, 2020.
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.
Müller, M., Homleid, M., Ivarsson, K.-I., Køltzow, M. A. Ø., Lindskog, M., Midtbø, K. H., Andrae, U., Aspelien, T., Berggren, L., Bjørge, D., Dahlgren, P., Kristiansen, J., Randriamampianina, R., Ridal, M., and Vignes, O.: AROME-MetCoOp: A Nordic Convective-Scale Operational Weather Prediction Model, Weather Forecast., 32, 609–627, https://doi.org/10.1175/WAFD-16-0099.1, 2017.
Nicola, L., Notz, D., and Winkelmann, R.: Revisiting temperature sensitivity: how does Antarctic precipitation change with temperature?, The Cryosphere, 17, 2563–2583, https://doi.org/10.5194/tc-17-2563-2023, 2023.
Noël, B., Lenaerts, J. T., Lipscomb, W. H., Thayer-Calder, K., and van den Broeke, M. R.: Peak refreezing in the Greenland firn layer under future warming scenarios, Nat. Commun., 13, 6870, https://doi.org/10.1038/s41467-022-34524-x, 2022.
Pinty, J. P. and Jabouille, P. A.: mixed-phase cloud parameterization for use in mesoscale non-hydrostatic model: simulations of a squall line and of orographic precipitations, in: Conf. on cloud physics, Everett, WA: Amer. Meteor. Soc., 217–220, 1998.
Pritchard, H. D.: Global data gaps in our knowledge of the terrestrial cryosphere, Front. Clim., 3, 689823, https://doi.org/10.3389/fclim.2021.689823, 2021.
Ramelli, F., Henneberger, J., David, R. O., Bühl, J., Radenz, M., Seifert, P., Wieder, J., Lauber, A., Pasquier, J. T., Engelmann, R., Mignani, C., Hervo, M., and Lohmann, U.: Microphysical investigation of the seeder and feeder region of an Alpine mixed-phase cloud, Atmos. Chem. Phys., 21, 6681–6706, https://doi.org/10.5194/acp-21-6681-2021, 2021.
Rignot, E., Mouginot, J., Scheuchl, B., van den Broeke, M. R., van Wessem, M. J., and Morlighem, M.: Four decades of Antarctic Ice Sheet mass balance from 1979–2017, P. Natl. Acad. Sci. USA, 116, 1095–1105, https://doi.org/10.1073/pnas.1812883116, 2019.
Scambos, T.: Visala WXT520 weather station data at the Cavity and Channel AMIGOS-III sites, U.S. Antarctic Program (USAP) Data Center [data set], https://doi.org/10.15784/601549, 2022.
Scambos, T. A., Ross, R., Haran, T., Bauer, R., Ainley, D. G., Seo, K. W., De Keyser, M., Behar, A., and MacAyeal, D. R.: A camera and multisensor automated station design for polar physical and biological systems monitoring: AMIGOS, J. Glaciol., 59, 303–314, https://doi.org/10.3189/2013JoG12J170, 2013.
Scambos, T. A., Bell, R. E., Alley, R. B., Anandakrishnan, S., Bromwich, D. H., Brunt, K., Christianson, K., Creyts, T., Das, S. B., DeConto, R., and Dutrieux, P.: How much, how fast?: A science review and outlook for research on the instability of Antarctica's Thwaites Glacier in the 21st century, Global Planet. Change, 153, 16–34, https://doi.org/10.1016/j.gloplacha.2017.04.008, 2017.
Schmucki, E., Marty, C., Fierz, C., and Lehning, M.: Evaluation of modelled snow depth and snow water equivalent at three contrasting sites in Switzerland using SNOWPACK simulations driven by different meteorological data input, Cold Reg. Sci. Technol., 99, 27–37, https://doi.org/10.1016/J.COLDREGIONS.2013.12.004, 2014.
Scott, R. C., Nicolas, J. P., Bromwich, D. H., Norris, J. R., and Lubin, D.: Meteorological drivers and large-scale climate forcing of West Antarctic surface melt, J. Climate, 32, 665–684, https://doi.org/10.1175/JCLI-D-18-0233.1, 2019.
Shields, C. A., Wille, J. D., Marquardt Collow, A. B., Maclennan, M., and Gorodetskaya, I. V.: Evaluating uncertainty and modes of variability for Antarctic atmospheric rivers, Geophys. Res. Lett., 49, e2022GL099577, https://doi.org/10.1029/2022GL099577, 2022.
Silber, I., Fridlind, A. M., Verlinde, J., Ackerman, A. S., Chen, Y. S., Bromwich, D. H., Wang, S. H., Cadeddu, M., and Eloranta, E. W.: Persistent supercooled drizzle at temperatures below −25 °C observed at McMurdo Station, Antarctica, J. Geophys. Res.-Atmos., 124, 10878–10895, https://doi.org/10.1029/2019JD030882, 2019.
Skamarock, W., Klemp, J., Dudhia, J., Gill, D. O., Liu, Z., Berner, J., Wang, W., Powers, J. G., Duda, M. G., Barker, D., and Huang, X.-Y.: A Description of the Advanced Research Polar-WRF Model Version 4.1 (No. NCAR/TN-556+STR), https://doi.org/10.5065/1dfh-6p97, 2019.
Smith, B., Fricker, H. A., Gardner, A. S., Medley, B., Nilsson, J., Paolo, F. S., Holschuh, N., Adusumilli, S., Brunt, K., Csatho, B., and Harbeck, K.: Pervasive ice sheet mass loss reflects competing ocean and atmosphere processes, Science, 368, 1239–1242, https://doi.org/10.1126/science.aaz5845, 2020.
Stroeve, J., Nandan, V., Willatt, R., Dadic, R., Rostosky, P., Gallagher, M., Mallett, R., Barrett, A., Hendricks, S., Tonboe, R., McCrystall, M., Serreze, M., Thielke, L., Spreen, G., Newman, T., Yackel, J., Ricker, R., Tsamados, M., Macfarlane, A., Hannula, H.-R., and Schneebeli, M.: Rain on snow (ROS) understudied in sea ice remote sensing: a multi-sensor analysis of ROS during MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate), The Cryosphere, 16, 4223–4250, https://doi.org/10.5194/tc-16-4223-2022, 2022.
Turner, J., Phillips, T., Thamban, M., Rahaman, W., Marshall, G. J., Wille, J. D., Favier, V., Winton, V. H. L., Thomas, E., Wang, Z., and van den Broeke, M.: The dominant role of extreme precipitation events in Antarctic snowfall variability, Geophys. Res. Lett., 46, 3502–3511, https://doi.org/10.1029/2018GL081517, 2019.
van Wessem, J. M., van den Broeke, M. R., Wouters, B., and Lhermitte, S.: Variable temperature thresholds of melt pond formation on Antarctic ice shelves, Nat. Clim. Change, 13, 161–166, https://doi.org/10.1038/s41558-022-01577-1, 2023.
Vergara-Temprado, J., Miltenberger, A. K., Furtado, K., Grosvenor, D. P., Shipway, B. J., Hill, A. A., Wilkinson, J. M., Field, P. R., Murray, B. J., and Carslaw, K. S.: Strong control of Southern Ocean cloud reflectivity by ice-nucleating particles, P. Natl. Acad. Sci. USA, 115, 2687–2692, https://doi.org/10.1073/pnas.1721627115, 2018.
Vignon, É., Roussel, M. L., Gorodetskaya, I. V., Genthon, C., and Berne, A.: Present and future of rainfall in Antarctica, Geophys. Res. Lett., 48, e2020GL092281, https://doi.org/10.1029/2020GL092281, 2021.
Walters, D., Baran, A. J., Boutle, I., Brooks, M., Earnshaw, P., Edwards, J., Furtado, K., Hill, P., Lock, A., Manners, J., Morcrette, C., Mulcahy, J., Sanchez, C., Smith, C., Stratton, R., Tennant, W., Tomassini, L., Van Weverberg, K., Vosper, S., Willett, M., Browse, J., Bushell, A., Carslaw, K., Dalvi, M., Essery, R., Gedney, N., Hardiman, S., Johnson, B., Johnson, C., Jones, A., Jones, C., Mann, G., Milton, S., Rumbold, H., Sellar, A., Ujiie, M., Whitall, M., Williams, K., and Zerroukat, M.: The Met Office Unified Model Global Atmosphere 7.0/7.1 and JULES Global Land 7.0 configurations, Geosci. Model Dev., 12, 1909–1963, https://doi.org/10.5194/gmd-12-1909-2019, 2019.
Wever, N.: SNOWPACK simulations for Thwaites Cavity and Channel AMIGOS sites in West Antarctica, Zenodo [data set], https://doi.org/10.5281/zenodo.7320237, 2022.
Wever, N., Schmid, L., Heilig, A., Eisen, O., Fierz, C., and Lehning, M.: Verification of the multi-layer SNOWPACK model with different water transport schemes, The Cryosphere, 9, 2271–2293, https://doi.org/10.5194/tc-9-2271-2015, 2015.
Wever, N., Keenan, E., Amory, C., Lehning, M., Sigmund, A., Huwald, H., and Lenaerts, J.: Observations and simulations of new snow density in the drifting snow-dominated environment of Antarctica, J. Glaciol., 69, 823–840, https://doi.org10.1017/jog.2022.102, 2023.
Wille, J. D., Favier, V., Dufour, A., Gorodetskaya, I. V., Turner, J., Agosta, C., and Codron, F.: West Antarctic surface melt triggered by atmospheric rivers, Nat. Geosci., 12, 911–916, https://doi.org/10.1038/s41561-019-0460-1, 2019.
Wille, J. D., Favier, V., Gorodetskaya, I. V., Agosta, C., Kittel, C., Beeman, J. C., Jourdain, N. C., Lenaerts, J. T., and Codron, F.: Antarctic atmospheric river climatology and precipitation impacts, J. Geophys. Res.-Atmos., 126, e2020JD033788, https://doi.org/10.1029/2020JD033788, 2021.
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., and Amory, C.: 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.
Wille, J. D., Alexander, S. P., Amory, C., Baiman, R., Barthélemy, L., Bergstrom, D. M., Berne, A., Binder, H., Blanchet, J., Bozkurt, D., Bracegirdle, T. J., Casado, M., Choi, T., Clem, K. R., Codron, F., Datta, R., Di Battista, S., Favier, V., Francis, D., Fraser, A. D., Fourré, E., Garreaud, R. D., Genthon, C., Gorodetskaya, I. V., González-Herrero, S., Heinrich, V. J., Hubert, G., Joos, H., Kim, S-J., John C. King, J. C., Kittel, C., Landais, A., Lazzara, M., Leonard, G. H., Lieser, J. L., Maclennan, M., Mikolajczyk, D., Neff, P., Ollivier, I., Picard, G., Pohl, B., Ralph, F. M., Rowe, P., Schlosser, E., Shields, C. A., Smith, I. J., Sprenger, M., Trusel, L., Udy, D., Vance, T., Vignon, E. Walker, C., Wever, N., and Zou, X.: The extraordinary March 2022 East Antarctica “heat” wave. Part II: impacts on the Antarctic ice sheet, J. Climate, 37, 779–799, https://doi.org/10.1175/JCLI-D-23-0176.1, 2024.
Wilson, A. B., Bromwich, D. H., and Hines, K. M.: Evaluation of Polar WRF forecasts on the Arctic System Reanalysis domain: Surface and upper air analysis, J. Geophys. Res., 116, D11112, https://doi.org/10.1029/2010JD015013, 2011.
Wilson, D. R. and Ballard, S. P.: A microphysically based precipitation scheme for the UK Meteorological Office Unified Model, Q. J. Roy. Meteor. Soc., 125, 1607–1636, https://doi.org/10.1002/qj.49712555707, 1999.
Xu, K. M. and Randall, D. A.: A semiempirical cloudiness parameterization for use in climate models, J. Atmos. Sci., 53, 3084–3102, https://doi.org/10.1175/1520-0469(1996)053<3084:ASCPFU>2.0.CO;2, 1996.
Xue, J., Xiao, Z., Bromwich, D. H., and Bai, L.: Polar Polar-WRF V4.1.1 simulation and evaluation for the Antarctic and Southern Ocean, Front. Earth Sci., 16, 1005–1024, https://doi.org/10.1007/s11707-022-0971-8, 2022.
Zou, X., Rowe, P. M., Gorodetskaya, I., Bromwich, D. H., Lazzara, M. A., Cordero, R. R., Zhang, Z., Kawzenuk, B., Cordeira, J. M., Wille, J. D., and Ralph, F. M.: Strong warming over the Antarctic Peninsula during combined atmospheric River and foehn events: Contribution of shortwave radiation and turbulence, J. Geophys. Res.-Atmos., 128, e2022JD038138, https://doi.org/10.1029/2022JD038138, 2023.
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.
We use three sophisticated climate models to examine extreme precipitation in a critical region...
