Articles | Volume 19, issue 11
https://doi.org/10.5194/tc-19-5403-2025
© 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-19-5403-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
06 Nov 2025
Research article |
| 06 Nov 2025
| 06 Nov 2025
Modelling the impacts of historical and future extreme precipitation days on seasonal surface mass balance in the Eastern Canadian Arctic and Greenland
Department of Environment & Geography and Centre for Earth Observation Science, University of Manitoba, Winnipeg, MB, Canada
Alex Crawford
Department of Environment & Geography and Centre for Earth Observation Science, University of Manitoba, Winnipeg, MB, Canada
Brice Noël
Laboratory of Climatology, Department of Geography, SPHERES research unit, University of Liège, Liège, Belgium
Julienne Stroeve
Department of Environment & Geography and Centre for Earth Observation Science, University of Manitoba, Winnipeg, MB, Canada
Department of Earth Sciences, University College London, London, United Kingdom
National Snow and Ice Data Center, Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Boulder, CO, United States
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Understanding snow depth on sea ice is key for measuring ice thickness, studying ecosystems, and modeling climate. Using snow and ice thickness measurements from Arctic and Antarctic campaigns, this study examines sub-kilometer-scale (<1 km²) snow depth variations and identifies the most suitable statistical models for different ice ages, thicknesses, and weather conditions. These results can improve sub-grid snow parameterizations in snow models and remote sensing algorithms.
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This study examines how changing weather is affecting sea ice near the Arctic community of Tuktoyaktuk in Canada. Using satellite images and weather records, we found that stronger winds from certain directions are causing the sea ice to break more often in winter. These changes pose risks for local people who depend on stable ice for travel and hunting. Our findings help understand how climate change is making Arctic ice less reliable and more dangerous.
Shfaqat A. Khan, Helene Seroussi, Mathieu Morlighem, William Colgan, Veit Helm, Gong Cheng, Danjal Berg, Valentina R. Barletta, Nicolaj K. Larsen, William Kochtitzky, Michiel van den Broeke, Kurt H. Kjær, Andy Aschwanden, Brice Noël, Jason E. Box, Joseph A. MacGregor, Robert S. Fausto, Kenneth D. Mankoff, Ian M. Howat, Kuba Oniszk, Dominik Fahrner, Anja Løkkegaard, Eigil Y. H. Lippert, Alicia Bråtner, and Javed Hassan
Earth Syst. Sci. Data, 17, 3047–3071, https://doi.org/10.5194/essd-17-3047-2025, https://doi.org/10.5194/essd-17-3047-2025, 2025
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Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLVIII-M-6-2025, 393–397, https://doi.org/10.5194/isprs-archives-XLVIII-M-6-2025-393-2025, https://doi.org/10.5194/isprs-archives-XLVIII-M-6-2025-393-2025, 2025
Emily Glen, Amber Leeson, Alison F. Banwell, Jennifer Maddalena, Diarmuid Corr, Olivia Atkins, Brice Noël, and Malcolm McMillan
The Cryosphere, 19, 1047–1066, https://doi.org/10.5194/tc-19-1047-2025, https://doi.org/10.5194/tc-19-1047-2025, 2025
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We compare surface meltwater features from optical satellite imagery in the Russell–Leverett glacier catchment during high (2019) and low (2018) melt years. In the high melt year, features appear at higher elevations, meltwater systems are more connected, small lakes are more frequent, and slush is more widespread. These findings provide insights into how a warming climate, where high melt years become common, could alter meltwater distribution and dynamics on the Greenland Ice Sheet.
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The Cryosphere, 19, 325–346, https://doi.org/10.5194/tc-19-325-2025, https://doi.org/10.5194/tc-19-325-2025, 2025
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Xueyu Zhang, Lin Liu, Brice Noël, and Zhicai Luo
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This study indicates that the overall characteristics of the upper firn density in the percolation zone could be captured by the choice of appropriate model configurations and climatic forcing, which is necessary for understanding the current mass balance of the GrIS and predicting its future. The modelled firn density in this study generally aligns well with observations from 16 cores, with the relative bias in density ranging from 0.36 % to 6 % at Dye-2 and being within ±5 % at KAN_U.
Wiebke Margitta Kolbe, Rasmus T. Tonboe, and Julienne Stroeve
Earth Syst. Sci. Data, 16, 1247–1264, https://doi.org/10.5194/essd-16-1247-2024, https://doi.org/10.5194/essd-16-1247-2024, 2024
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Current satellite-based sea-ice climate data records (CDRs) usually begin in October 1978 with the first multichannel microwave radiometer data. Here, we present a sea ice dataset based on the single-channel Electrical Scanning Microwave Radiometer (ESMR) that operated from 1972-1977 onboard NASA’s Nimbus 5 satellite. The data were processed using modern methods and include uncertainty estimations in order to provide an important, easy-to-use reference period of good quality for current CDRs.
Xueyu Zhang, Lin Liu, Brice Noël, and Zhicai Luo
EGUsphere, https://doi.org/10.5194/egusphere-2024-122, https://doi.org/10.5194/egusphere-2024-122, 2024
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In this study, an improved firn densification model is developed by integrating the Bucket scheme and Darcy’s law to assess the capillary retention, refreezing, and runoff of liquid water within the firn layer. This model captures high-density peaks (~917 kg · m-3) or the features of high-density layers caused by the refreezing of liquid water. In general, the modelled firn depth-density profiles at KAN_U and Dye-2 agree well with the in situ measurements.
Alistair Duffey, Robbie Mallett, Peter J. Irvine, Michel Tsamados, and Julienne Stroeve
Earth Syst. Dynam., 14, 1165–1169, https://doi.org/10.5194/esd-14-1165-2023, https://doi.org/10.5194/esd-14-1165-2023, 2023
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The Arctic is warming several times faster than the rest of the planet. Here, we use climate model projections to quantify for the first time how this faster warming in the Arctic impacts the timing of crossing the 1.5 °C and 2 °C thresholds defined in the Paris Agreement. We show that under plausible emissions scenarios that fail to meet the Paris 1.5 °C target, a hypothetical world without faster warming in the Arctic would breach that 1.5 °C target around 5 years later.
Vishnu Nandan, Rosemary Willatt, Robbie Mallett, Julienne Stroeve, Torsten Geldsetzer, Randall Scharien, Rasmus Tonboe, John Yackel, Jack Landy, David Clemens-Sewall, Arttu Jutila, David N. Wagner, Daniela Krampe, Marcus Huntemann, Mallik Mahmud, David Jensen, Thomas Newman, Stefan Hendricks, Gunnar Spreen, Amy Macfarlane, Martin Schneebeli, James Mead, Robert Ricker, Michael Gallagher, Claude Duguay, Ian Raphael, Chris Polashenski, Michel Tsamados, Ilkka Matero, and Mario Hoppmann
The Cryosphere, 17, 2211–2229, https://doi.org/10.5194/tc-17-2211-2023, https://doi.org/10.5194/tc-17-2211-2023, 2023
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We show that wind redistributes snow on Arctic sea ice, and Ka- and Ku-band radar measurements detect both newly deposited snow and buried snow layers that can affect the accuracy of snow depth estimates on sea ice. Radar, laser, meteorological, and snow data were collected during the MOSAiC expedition. With frequent occurrence of storms in the Arctic, our results show that
wind-redistributed snow needs to be accounted for to improve snow depth estimates on sea ice from satellite radars.
Inès N. Otosaka, Andrew Shepherd, Erik R. Ivins, Nicole-Jeanne Schlegel, Charles Amory, Michiel R. van den Broeke, Martin Horwath, Ian Joughin, Michalea D. King, Gerhard Krinner, Sophie Nowicki, Anthony J. Payne, Eric Rignot, Ted Scambos, Karen M. Simon, Benjamin E. Smith, Louise S. Sørensen, Isabella Velicogna, Pippa L. Whitehouse, Geruo A, Cécile Agosta, Andreas P. Ahlstrøm, Alejandro Blazquez, William Colgan, Marcus E. Engdahl, Xavier Fettweis, Rene Forsberg, Hubert Gallée, Alex Gardner, Lin Gilbert, Noel Gourmelen, Andreas Groh, Brian C. Gunter, Christopher Harig, Veit Helm, Shfaqat Abbas Khan, Christoph Kittel, Hannes Konrad, Peter L. Langen, Benoit S. Lecavalier, Chia-Chun Liang, Bryant D. Loomis, Malcolm McMillan, Daniele Melini, Sebastian H. Mernild, Ruth Mottram, Jeremie Mouginot, Johan Nilsson, Brice Noël, Mark E. Pattle, William R. Peltier, Nadege Pie, Mònica Roca, Ingo Sasgen, Himanshu V. Save, Ki-Weon Seo, Bernd Scheuchl, Ernst J. O. Schrama, Ludwig Schröder, Sebastian B. Simonsen, Thomas Slater, Giorgio Spada, Tyler C. Sutterley, Bramha Dutt Vishwakarma, Jan Melchior van Wessem, David Wiese, Wouter van der Wal, and Bert Wouters
Earth Syst. Sci. Data, 15, 1597–1616, https://doi.org/10.5194/essd-15-1597-2023, https://doi.org/10.5194/essd-15-1597-2023, 2023
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By measuring changes in the volume, gravitational attraction, and ice flow of Greenland and Antarctica from space, we can monitor their mass gain and loss over time. Here, we present a new record of the Earth’s polar ice sheet mass balance produced by aggregating 50 satellite-based estimates of ice sheet mass change. This new assessment shows that the ice sheets have lost (7.5 x 1012) t of ice between 1992 and 2020, contributing 21 mm to sea level rise.
Younjoo J. Lee, Wieslaw Maslowski, John J. Cassano, Jaclyn Clement Kinney, Anthony P. Craig, Samy Kamal, Robert Osinski, Mark W. Seefeldt, Julienne Stroeve, and Hailong Wang
The Cryosphere, 17, 233–253, https://doi.org/10.5194/tc-17-233-2023, https://doi.org/10.5194/tc-17-233-2023, 2023
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During 1979–2020, four winter polynyas occurred in December 1986 and February 2011, 2017, and 2018 north of Greenland. Instead of ice melting due to the anomalous warm air intrusion, the extreme wind forcing resulted in greater ice transport offshore. Based on the two ensemble runs, representing a 1980s thicker ice vs. a 2010s thinner ice, a dominant cause of these winter polynyas stems from internal variability of atmospheric forcing rather than from the forced response to a warming climate.
Qianjie Chen, Jessica A. Mirrielees, Sham Thanekar, Nicole A. Loeb, Rachel M. Kirpes, Lucia M. Upchurch, Anna J. Barget, Nurun Nahar Lata, Angela R. W. Raso, Stephen M. McNamara, Swarup China, Patricia K. Quinn, Andrew P. Ault, Aaron Kennedy, Paul B. Shepson, Jose D. Fuentes, and Kerri A. Pratt
Atmos. Chem. Phys., 22, 15263–15285, https://doi.org/10.5194/acp-22-15263-2022, https://doi.org/10.5194/acp-22-15263-2022, 2022
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During a spring field campaign in the coastal Arctic, ultrafine particles were enhanced during high wind speeds, and coarse-mode particles were reduced during blowing snow. Calculated periods blowing snow were overpredicted compared to observations. Sea spray aerosols produced by sea ice leads affected the composition of aerosols and snowpack. An improved understanding of aerosol emissions from leads and blowing snow is critical for predicting the future climate of the rapidly warming Arctic.
Julienne Stroeve, Vishnu Nandan, Rosemary Willatt, Ruzica Dadic, Philip Rostosky, Michael Gallagher, Robbie Mallett, Andrew Barrett, Stefan Hendricks, Rasmus Tonboe, Michelle McCrystall, Mark Serreze, Linda Thielke, Gunnar Spreen, Thomas Newman, John Yackel, Robert Ricker, Michel Tsamados, Amy Macfarlane, Henna-Reetta Hannula, and Martin Schneebeli
The Cryosphere, 16, 4223–4250, https://doi.org/10.5194/tc-16-4223-2022, https://doi.org/10.5194/tc-16-4223-2022, 2022
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Impacts of rain on snow (ROS) on satellite-retrieved sea ice variables remain to be fully understood. This study evaluates the impacts of ROS over sea ice on active and passive microwave data collected during the 2019–20 MOSAiC expedition. Rainfall and subsequent refreezing of the snowpack significantly altered emitted and backscattered radar energy, laying important groundwork for understanding their impacts on operational satellite retrievals of various sea ice geophysical variables.
Tiago Silva, Jakob Abermann, Brice Noël, Sonika Shahi, Willem Jan van de Berg, and Wolfgang Schöner
The Cryosphere, 16, 3375–3391, https://doi.org/10.5194/tc-16-3375-2022, https://doi.org/10.5194/tc-16-3375-2022, 2022
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To overcome internal climate variability, this study uses k-means clustering to combine NAO, GBI and IWV over the Greenland Ice Sheet (GrIS) and names the approach as the North Atlantic influence on Greenland (NAG). With the support of a polar-adapted RCM, spatio-temporal changes on SEB components within NAG phases are investigated. We report atmospheric warming and moistening across all NAG phases as well as large-scale and regional-scale contributions to GrIS mass loss and their interactions.
David N. Wagner, Matthew D. Shupe, Christopher Cox, Ola G. Persson, Taneil Uttal, Markus M. Frey, Amélie Kirchgaessner, Martin Schneebeli, Matthias Jaggi, Amy R. Macfarlane, Polona Itkin, Stefanie Arndt, Stefan Hendricks, Daniela Krampe, Marcel Nicolaus, Robert Ricker, Julia Regnery, Nikolai Kolabutin, Egor Shimanshuck, Marc Oggier, Ian Raphael, Julienne Stroeve, and Michael Lehning
The Cryosphere, 16, 2373–2402, https://doi.org/10.5194/tc-16-2373-2022, https://doi.org/10.5194/tc-16-2373-2022, 2022
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Based on measurements of the snow cover over sea ice and atmospheric measurements, we estimate snowfall and snow accumulation for the MOSAiC ice floe, between November 2019 and May 2020. For this period, we estimate 98–114 mm of precipitation. We suggest that about 34 mm of snow water equivalent accumulated until the end of April 2020 and that at least about 50 % of the precipitated snow was eroded or sublimated. Further, we suggest explanations for potential snowfall overestimation.
William Gregory, Julienne Stroeve, and Michel Tsamados
The Cryosphere, 16, 1653–1673, https://doi.org/10.5194/tc-16-1653-2022, https://doi.org/10.5194/tc-16-1653-2022, 2022
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This research was conducted to better understand how coupled climate models simulate one of the large-scale interactions between the atmosphere and Arctic sea ice that we see in observational data, the accurate representation of which is important for producing reliable forecasts of Arctic sea ice on seasonal to inter-annual timescales. With network theory, this work shows that models do not reflect this interaction well on average, which is likely due to regional biases in sea ice thickness.
Kenneth D. Mankoff, Xavier Fettweis, Peter L. Langen, Martin Stendel, Kristian K. Kjeldsen, Nanna B. Karlsson, Brice Noël, Michiel R. van den Broeke, Anne Solgaard, William Colgan, Jason E. Box, Sebastian B. Simonsen, Michalea D. King, Andreas P. Ahlstrøm, Signe Bech Andersen, and Robert S. Fausto
Earth Syst. Sci. Data, 13, 5001–5025, https://doi.org/10.5194/essd-13-5001-2021, https://doi.org/10.5194/essd-13-5001-2021, 2021
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We estimate the daily mass balance and its components (surface, marine, and basal mass balance) for the Greenland ice sheet. Our time series begins in 1840 and has annual resolution through 1985 and then daily from 1986 through next week. Results are operational (updated daily) and provided for the entire ice sheet or by commonly used regions or sectors. This is the first input–output mass balance estimate to include the basal mass balance.
Isolde A. Glissenaar, Jack C. Landy, Alek A. Petty, Nathan T. Kurtz, and Julienne C. Stroeve
The Cryosphere, 15, 4909–4927, https://doi.org/10.5194/tc-15-4909-2021, https://doi.org/10.5194/tc-15-4909-2021, 2021
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Scientists can estimate sea ice thickness using satellites that measure surface height. To determine the sea ice thickness, we also need to know the snow depth and density. This paper shows that the chosen snow depth product has a considerable impact on the findings of sea ice thickness state and trends in Baffin Bay, showing mean thinning with some snow depth products and mean thickening with others. This shows that it is important to better understand and monitor snow depth on sea ice.
Igor A. Dmitrenko, Denis L. Volkov, Tricia A. Stadnyk, Andrew Tefs, David G. Babb, Sergey A. Kirillov, Alex Crawford, Kevin Sydor, and David G. Barber
Ocean Sci., 17, 1367–1384, https://doi.org/10.5194/os-17-1367-2021, https://doi.org/10.5194/os-17-1367-2021, 2021
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Significant trends of sea ice in Hudson Bay have led to a considerable increase in shipping activity. Therefore, understanding sea level variability is an urgent issue crucial for safe navigation and coastal infrastructure. Using the sea level, atmospheric and river discharge data, we assess environmental factors impacting variability of sea level at Churchill. We find that it is dominated by wind forcing, with the seasonal cycle generated by the seasonal cycle in atmospheric circulation.
Marcel Kleinherenbrink, Anton Korosov, Thomas Newman, Andreas Theodosiou, Alexander S. Komarov, Yuanhao Li, Gert Mulder, Pierre Rampal, Julienne Stroeve, and Paco Lopez-Dekker
The Cryosphere, 15, 3101–3118, https://doi.org/10.5194/tc-15-3101-2021, https://doi.org/10.5194/tc-15-3101-2021, 2021
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Harmony is one of the Earth Explorer 10 candidates that has the chance of being selected for launch in 2028. The mission consists of two satellites that fly in formation with Sentinel-1D, which carries a side-looking radar system. By receiving Sentinel-1's signals reflected from the surface, Harmony is able to observe instantaneous elevation and two-dimensional velocity at the surface. As such, Harmony's data allow the retrieval of sea-ice drift and wave spectra in sea-ice-covered regions.
Robbie D. C. Mallett, Julienne C. Stroeve, Michel Tsamados, Jack C. Landy, Rosemary Willatt, Vishnu Nandan, and Glen E. Liston
The Cryosphere, 15, 2429–2450, https://doi.org/10.5194/tc-15-2429-2021, https://doi.org/10.5194/tc-15-2429-2021, 2021
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We re-estimate pan-Arctic sea ice thickness (SIT) values by combining data from the Envisat and CryoSat-2 missions with data from a new, reanalysis-driven snow model. Because a decreasing amount of ice is being hidden below the waterline by the weight of overlying snow, we argue that SIT may be declining faster than previously calculated in some regions. Because the snow product varies from year to year, our new SIT calculations also display much more year-to-year variability.
Rasmus T. Tonboe, Vishnu Nandan, John Yackel, Stefan Kern, Leif Toudal Pedersen, and Julienne Stroeve
The Cryosphere, 15, 1811–1822, https://doi.org/10.5194/tc-15-1811-2021, https://doi.org/10.5194/tc-15-1811-2021, 2021
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A relationship between the Ku-band radar scattering horizon and snow depth is found using a radar scattering model. This relationship has implications for (1) the use of snow climatology in the conversion of satellite radar freeboard into sea ice thickness and (2) the impact of variability in measured snow depth on the derived ice thickness. For both 1 and 2, the impact of using a snow climatology versus the actual snow depth is relatively small.
Lu Zhou, Julienne Stroeve, Shiming Xu, Alek Petty, Rachel Tilling, Mai Winstrup, Philip Rostosky, Isobel R. Lawrence, Glen E. Liston, Andy Ridout, Michel Tsamados, and Vishnu Nandan
The Cryosphere, 15, 345–367, https://doi.org/10.5194/tc-15-345-2021, https://doi.org/10.5194/tc-15-345-2021, 2021
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Snow on sea ice plays an important role in the Arctic climate system. Large spatial and temporal discrepancies among the eight snow depth products are analyzed together with their seasonal variability and long-term trends. These snow products are further compared against various ground-truth observations. More analyses on representation error of sea ice parameters are needed for systematic comparison and fusion of airborne, in situ and remote sensing observations.
Masa Kageyama, Louise C. Sime, Marie Sicard, Maria-Vittoria Guarino, Anne de Vernal, Ruediger Stein, David Schroeder, Irene Malmierca-Vallet, Ayako Abe-Ouchi, Cecilia Bitz, Pascale Braconnot, Esther C. Brady, Jian Cao, Matthew A. Chamberlain, Danny Feltham, Chuncheng Guo, Allegra N. LeGrande, Gerrit Lohmann, Katrin J. Meissner, Laurie Menviel, Polina Morozova, Kerim H. Nisancioglu, Bette L. Otto-Bliesner, Ryouta O'ishi, Silvana Ramos Buarque, David Salas y Melia, Sam Sherriff-Tadano, Julienne Stroeve, Xiaoxu Shi, Bo Sun, Robert A. Tomas, Evgeny Volodin, Nicholas K. H. Yeung, Qiong Zhang, Zhongshi Zhang, Weipeng Zheng, and Tilo Ziehn
Clim. Past, 17, 37–62, https://doi.org/10.5194/cp-17-37-2021, https://doi.org/10.5194/cp-17-37-2021, 2021
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The Last interglacial (ca. 127 000 years ago) is a period with increased summer insolation at high northern latitudes, resulting in a strong reduction in Arctic sea ice. The latest PMIP4-CMIP6 models all simulate this decrease, consistent with reconstructions. However, neither the models nor the reconstructions agree on the possibility of a seasonally ice-free Arctic. Work to clarify the reasons for this model divergence and the conflicting interpretations of the records will thus be needed.
Julienne Stroeve, Vishnu Nandan, Rosemary Willatt, Rasmus Tonboe, Stefan Hendricks, Robert Ricker, James Mead, Robbie Mallett, Marcus Huntemann, Polona Itkin, Martin Schneebeli, Daniela Krampe, Gunnar Spreen, Jeremy Wilkinson, Ilkka Matero, Mario Hoppmann, and Michel Tsamados
The Cryosphere, 14, 4405–4426, https://doi.org/10.5194/tc-14-4405-2020, https://doi.org/10.5194/tc-14-4405-2020, 2020
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This study provides a first look at the data collected by a new dual-frequency Ka- and Ku-band in situ radar over winter sea ice in the Arctic Ocean. The instrument shows potential for using both bands to retrieve snow depth over sea ice, as well as sensitivity of the measurements to changing snow and atmospheric conditions.
Kenneth D. Mankoff, Brice Noël, Xavier Fettweis, Andreas P. Ahlstrøm, William Colgan, Ken Kondo, Kirsty Langley, Shin Sugiyama, Dirk van As, and Robert S. Fausto
Earth Syst. Sci. Data, 12, 2811–2841, https://doi.org/10.5194/essd-12-2811-2020, https://doi.org/10.5194/essd-12-2811-2020, 2020
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This work partitions regional climate model (RCM) runoff from the MAR and RACMO RCMs to hydrologic outlets at the ice margin and coast. Temporal resolution is daily from 1959 through 2019. Spatial grid is ~ 100 m, resolving individual streams. In addition to discharge at outlets, we also provide the streams, outlets, and basin geospatial data, as well as a script to query and access the geospatial or time series discharge data from the data files.
Xavier Fettweis, Stefan Hofer, Uta Krebs-Kanzow, Charles Amory, Teruo Aoki, Constantijn J. Berends, Andreas Born, Jason E. Box, Alison Delhasse, Koji Fujita, Paul Gierz, Heiko Goelzer, Edward Hanna, Akihiro Hashimoto, Philippe Huybrechts, Marie-Luise Kapsch, Michalea D. King, Christoph Kittel, Charlotte Lang, Peter L. Langen, Jan T. M. Lenaerts, Glen E. Liston, Gerrit Lohmann, Sebastian H. Mernild, Uwe Mikolajewicz, Kameswarrao Modali, Ruth H. Mottram, Masashi Niwano, Brice Noël, Jonathan C. Ryan, Amy Smith, Jan Streffing, Marco Tedesco, Willem Jan van de Berg, Michiel van den Broeke, Roderik S. W. van de Wal, Leo van Kampenhout, David Wilton, Bert Wouters, Florian Ziemen, and Tobias Zolles
The Cryosphere, 14, 3935–3958, https://doi.org/10.5194/tc-14-3935-2020, https://doi.org/10.5194/tc-14-3935-2020, 2020
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We evaluated simulated Greenland Ice Sheet surface mass balance from 5 kinds of models. While the most complex (but expensive to compute) models remain the best, the faster/simpler models also compare reliably with observations and have biases of the same order as the regional models. Discrepancies in the trend over 2000–2012, however, suggest that large uncertainties remain in the modelled future SMB changes as they are highly impacted by the meltwater runoff biases over the current climate.
Cited articles
Ali, S. M. A. and Tandon, N. F.: Influence of Horizontal Model Resolution on the Horizontal Scale of Extreme Precipitation Events, Journal of Geophysical Research: Atmospheres, 129, e2023JD040146, https://doi.org/10.1029/2023JD040146, 2024.
Bailey, H. and Hubbard, A.: Snow Mass Recharge of the Greenland Ice Sheet Fueled by Intense Atmospheric River, Geophysical Research Letters, 52, e2024GL110121, https://doi.org/10.1029/2024GL110121, 2025.
Bamber, J. L., Westaway, R. M., Marzeion, B., and Wouters, B.: The land ice contribution to sea level during the satellite era, Environ. Res. Lett., 13, 063008, https://doi.org/10.1088/1748-9326/aac2f0, 2018.
Bao, J.-W., Michelson, S. A., Neiman, P. J., Ralph, F. M., and Wilczak, J. M.: Interpretation of Enhanced Integrated Water Vapor Bands Associated with Extratropical Cyclones: Their Formation and Connection to Tropical Moisture, Monthly Weather Review, 134, 1063–1080, https://doi.org/10.1175/MWR3123.1, 2006.
Bengtsson, L., Hodges, K. I., Koumoutsaris, S., Zahn, M., and Keenlyside, N.: The changing atmospheric water cycle in Polar Regions in a warmer climate, Tellus A: Dynamic Meteorology and Oceanography, 63, 907–920, https://doi.org/10.1111/j.1600-0870.2011.00534.x, 2011.
Bintanja, R. and Selten, F. M.: Future increases in Arctic precipitation linked to local evaporation and sea-ice retreat, Nature, 509, 479–482, https://doi.org/10.1038/nature13259, 2014.
Bolch, T., Sandberg Sørensen, L., Simonsen, S. B., Mölg, N., Machguth, H., Rastner, P., and Paul, F.: Mass loss of Greenland's glaciers and ice caps 2003–2008 revealed from ICESat laser altimetry data, Geophysical Research Letters, 40, 875–881, https://doi.org/10.1002/grl.50270, 2013.
Box, J. E.: Greenland Ice Sheet Mass Balance Reconstruction. Part II: Surface Mass Balance (1840–2010), Journal of Climate, 26, 6974–6989, https://doi.org/10.1175/JCLI-D-12-00518.1, 2013.
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, Geophysical Research Letters, 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. Ø., Palmason, B., Fausto, R. S., van den Broeke, M. R., Huai, B., Ahlstrøm, A. P., Langley, K., Dachauer, A., and Noël, B.: Greenland ice sheet rainfall climatology, extremes and atmospheric river rapids, Meteorological Applications, 30, e2134, https://doi.org/10.1002/met.2134, 2023.
Browning, K. A. and Pardoe, C. W.: Structure of low-level jet streams ahead of mid-latitude cold fronts, Quarterly Journal of the Royal Meteorological Society, 99, 619–638, https://doi.org/10.1002/qj.49709942204, 1973.
Cai, L., Alexeev, V. A., Arp, C. D., Jones, B. M., Liljedahl, A. K., and Gädeke, A.: The Polar WRF Downscaled Historical and Projected Twenty-First Century Climate for the Coast and Foothills of Arctic Alaska, Front. Earth Sci., 5, https://doi.org/10.3389/feart.2017.00111, 2018.
Cogley, J. G.: Greenland accumulation: An error model, Journal of Geophysical Research: Atmospheres, 109, https://doi.org/10.1029/2003JD004449, 2004.
Cogley, J. G., Hock, R., Rasmussen, L. A., Arendt, A. A., Bauder, A., Braithwaite, R. J., Jansson, P., Kaser, G., Möller, M., Nicholson, L., and Zemp, M.: Glossary of Glacier Mass Balance and Related Terms, UNESCO-IHP, Paris, France, https://wgms.ch/downloads/Cogley_etal_2011.pdf (last access: 6 May 2022), 2011.
Constable, A., Harper, S., Dawson, J., Mustonen, T., Piepenburg, D., Rost, B., Bokhorst, S., Boike, J., Cunsolo, A., Derksen, C., Feodoroff, P., Ford, J., Howell, S., Katny, A., MacDonald, J. P., Pedersen, Å. Ø., Robinson, S., Dorough, D. S., Shadrin, V., Skern-Mauritzen, M., Smith, S., Streletskiy, D., Tsujimoto, M., and Dam, B. V.: Cross-Chapter Paper 6: Polar Regions, in: Climate Change 2022: Impacts, Adaptation, and Vulnerability, edited by: Pörtner, H.-O., Roberts, D. C., Tignor, M., Poloczanska, E. S., Mintenbeck, K., Alegría, A., Craig, M., Langsdorf, S., Löschke, S., Möller, V., Okem, A., and Rama, B., Intergovernmental Panel on Climate Change, CCP6-1–66, https://doi.org/10.1017/9781009325844.023, 2022.
Crawford, A. D., McCrystall, M. R., Lukovich, J. V., and Stroeve, J. C.: The Response of Extratropical Cyclone Propagation in the Northern Hemisphere to Global Warming, Journal of Climate, 36, 7123–7142, https://doi.org/10.1175/JCLI-D-23-0082.1, 2023.
Danabasoglu, G., Lamarque, J.-F., Bacmeister, J., Bailey, D. A., DuVivier, A. K., Edwards, J., Emmons, L. K., Fasullo, J., Garcia, R., Gettelman, A., Hannay, C., Holland, M. M., Large, W. G., Lauritzen, P. H., Lawrence, D. M., Lenaerts, J. T. M., Lindsay, K., Lipscomb, W. H., Mills, M. J., Neale, R., Oleson, K. W., Otto-Bliesner, B., Phillips, A. S., Sacks, W., Tilmes, S., van Kampenhout, L., Vertenstein, M., Bertini, A., Dennis, J., Deser, C., Fischer, C., Fox-Kemper, B., Kay, J. E., Kinnison, D., Kushner, P. J., Larson, V. E., Long, M. C., Mickelson, S., Moore, J. K., Nienhouse, E., Polvani, L., Rasch, P. J., and Strand, W. G.: The Community Earth System Model Version 2 (CESM2), Journal of Advances in Modeling Earth Systems, 12, e2019MS001916, https://doi.org/10.1029/2019MS001916, 2020.
Doyle, S. H., Hubbard, A., van de Wal, R. S. W., Box, J. E., van As, D., Scharrer, K., Meierbachtol, T. W., Smeets, P. C. J. P., Harper, J. T., Johansson, E., Mottram, R. H., Mikkelsen, A. B., Wilhelms, F., Patton, H., Christoffersen, P., and Hubbard, B.: Amplified melt and flow of the Greenland ice sheet driven by late-summer cyclonic rainfall, Nature Geoscience, 8, 647–653, https://doi.org/10.1038/ngeo2482, 2015.
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.
Fausto, R. S., van As, D., Box, J. E., Colgan, W., and Langen, P. L.: Quantifying the Surface Energy Fluxes in South Greenland during the 2012 High Melt Episodes Using In-situ Observations, Front. Earth Sci., 4, https://doi.org/10.3389/feart.2016.00082, 2016a.
Fausto, R. S., van As, D., Box, J. E., Colgan, W., Langen, P. L., and Mottram, R. H.: The implication of nonradiative energy fluxes dominating Greenland ice sheet exceptional ablation area surface melt in 2012, Geophysical Research Letters, 43, 2649–2658, https://doi.org/10.1002/2016GL067720, 2016b.
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.
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.
Fischer, E. M. and Knutti, R.: Observed heavy precipitation increase confirms theory and early models, Nat. Clim. Change, 6, 986–991, https://doi.org/10.1038/nclimate3110, 2016.
Flanner, M. G. and Zender, C. S.: Linking snowpack microphysics and albedo evolution, Journal of Geophysical Research: Atmospheres, 111, https://doi.org/10.1029/2005JD006834, 2006.
Forster, R. R., Box, J. E., van den Broeke, M. R., Miège, C., Burgess, E. W., van Angelen, J. H., Lenaerts, J. T. M., Koenig, L. S., Paden, J., Lewis, C., Gogineni, S. P., Leuschen, C., and McConnell, J. R.: Extensive liquid meltwater storage in firn within the Greenland ice sheet, Nat. Geosci., 7, 95–98, https://doi.org/10.1038/ngeo2043, 2014.
Frederikse, T., Landerer, F., Caron, L., Adhikari, S., Parkes, D., Humphrey, V. W., Dangendorf, S., Hogarth, P., Zanna, L., Cheng, L., and Wu, Y.-H.: The causes of sea-level rise since 1900, Nature, 584, 393–397, https://doi.org/10.1038/s41586-020-2591-3, 2020.
Glaude, Q., Noel, B., Olesen, M., Van den Broeke, M., van de Berg, W. J., Mottram, R., Hansen, N., Delhasse, A., Amory, C., Kittel, C., Goelzer, H., and Fettweis, X.: A Factor Two Difference in 21st-Century Greenland Ice Sheet Surface Mass Balance Projections From Three Regional Climate Models Under a Strong Warming Scenario (SSP5-8.5), Geophysical Research Letters, 51, e2024GL111902, https://doi.org/10.1029/2024GL111902, 2024.
Harper, J., Saito, J., and Humphrey, N.: Cold Season Rain Event Has Impact on Greenland's Firn Layer Comparable to Entire Summer Melt Season, Geophysical Research Letters, 50, e2023GL103654, https://doi.org/10.1029/2023GL103654, 2023.
Hartmuth, K., Papritz, L., Boettcher, M., and Wernli, H.: Arctic Seasonal Variability and Extremes, and the Role of Weather Systems in a Changing Climate, Geophysical Research Letters, 50, e2022GL102349, https://doi.org/10.1029/2022GL102349, 2023.
Herrington, A. R., Lauritzen, P. H., Lofverstrom, M., Lipscomb, W. H., Gettelman, A., and Taylor, M. A.: Impact of grids and dynamical cores in CESM2.2 on the surface mass balance of the Greenland Ice Sheet, Journal of Advances in Modeling Earth Systems, e2022MS003192, https://doi.org/10.1029/2022MS003192, 2022.
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. de, Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J.-N.: The ERA5 global reanalysis, Quarterly Journal of the Royal Meteorological Society, 146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020.
Hofer, S., Lang, C., Amory, C., Kittel, C., Delhasse, A., Tedstone, A., and Fettweis, X.: Greater Greenland Ice Sheet contribution to global sea level rise in CMIP6, Nature Communications, 11, 6289, https://doi.org/10.1038/s41467-020-20011-8, 2020.
Hugonnet, R., McNabb, R., Berthier, E., Menounos, B., Nuth, C., Girod, L., Farinotti, D., Huss, M., Dussaillant, I., Brun, F., and Kääb, A.: Accelerated global glacier mass loss in the early twenty-first century, Nature, 592, 726–731, https://doi.org/10.1038/s41586-021-03436-z, 2021.
Hurrell, J. W., Hack, J. J., Shea, D., Caron, J. M., and Rosinski, J.: A New Sea Surface Temperature and Sea Ice Boundary Dataset for the Community Atmosphere Model, Journal of Climate, 21, 5145–5153, https://doi.org/10.1175/2008JCLI2292.1, 2008.
Jacob, T., Wahr, J., Pfeffer, W. T., and Swenson, S.: Recent contributions of glaciers and ice caps to sea level rise, Nature, 482, 514–518, https://doi.org/10.1038/nature10847, 2012.
Koerner, R. M.: Mass balance of glaciers in the Queen Elizabeth Islands, Nunavut, Canada, Ann. of Glaciol., 42, 417–-423, https://doi.org/10.3189/172756405781813122, 2005.
Kopec, B. G., Feng, X., Michel, F. A., and Posmentier, E. S.: Influence of sea ice on Arctic precipitation, P. Natl. Acad. Sci. USA, 113, 46–51, https://doi.org/10.1073/pnas.1504633113, 2016.
Kuipers Munneke, P., van den Broeke, M. R., Lenaerts, J. T. M., Flanner, M. G., Gardner, A. S., and van de Berg, W. J.: A new albedo parameterization for use in climate models over the Antarctic ice sheet, J. Geophys. Res., 116, D05114, https://doi.org/10.1029/2010JD015113, 2011.
Lawrence, D. M., Fisher, R. A., Koven, C. D., Oleson, K. W., Swenson, S. C., Bonan, G., Collier, N., Ghimire, B., van Kampenhout, L., Kennedy, D., Kluzek, E., Lawrence, P. J., Li, F., Li, H., Lombardozzi, D., Riley, W. J., Sacks, W. J., Shi, M., Vertenstein, M., Wieder, W. R., Xu, C., Ali, A. A., Badger, A. M., Bisht, G., van den Broeke, M., Brunke, M. A., Burns, S. P., Buzan, J., Clark, M., Craig, A., Dahlin, K., Drewniak, B., Fisher, J. B., Flanner, M., Fox, A. M., Gentine, P., Hoffman, F., Keppel-Aleks, G., Knox, R., Kumar, S., Lenaerts, J., Leung, L. R., Lipscomb, W. H., Lu, Y., Pandey, A., Pelletier, J. D., Perket, J., Randerson, J. T., Ricciuto, D. M., Sanderson, B. M., Slater, A., Subin, Z. M., Tang, J., Thomas, R. Q., Val Martin, M., and Zeng, X.: The Community Land Model Version 5: Description of New Features, Benchmarking, and Impact of Forcing Uncertainty, Journal of Advances in Modeling Earth Systems, 11, 4245–4287, https://doi.org/10.1029/2018MS001583, 2019.
Lenaerts, J. T. M., Angelen, J. H. van, Broeke, M. R. van den, Gardner, A. S., Wouters, B., and Meijgaard, E. van: Irreversible mass loss of Canadian Arctic Archipelago glaciers, Geophysical Research Letters, 40, 870–874, https://doi.org/10.1002/grl.50214, 2013.
Li, Z. and Ding, Q.: A global poleward shift of atmospheric rivers, Science Advances, 10, eadq0604, https://doi.org/10.1126/sciadv.adq0604, 2024.
Loeb, N. A., Crawford, A., Stroeve, J. C., and Hanesiak, J.: Extreme Precipitation in the Eastern Canadian Arctic and Greenland: An Evaluation of Atmospheric Reanalyses, Frontiers in Environmental Science, 10, https://doi.org/10.3389/fenvs.2022.866929, 2022.
Loeb, N. A., Crawford, A., Herrington, A., McCrystall, M., Stroeve, J., and Hanesiak, J.: Projections and Physical Drivers of Extreme Precipitation in Greenland & Baffin Bay, Journal of Geophysical Research: Atmospheres, 129, e2024JD041375, https://doi.org/10.1029/2024JD041375, 2024.
Loeb, N., Crawford, A., and Stroeve, J.: Extreme precipitation days and their impact on surface mass balance in Greenland and the Baffin Bay region, CanWIN [data set], https://canwin-datahub.ad.umanitoba.ca/data/dataset/extreme-precipitation-smb-greenland (last access: 2 September 2025), 2025.
MacFerrin, M., Machguth, H., van As, D., Charalampidis, C., Stevens, C. M., Heilig, A., Vandecrux, B., Langen, P. L., Mottram, R., Fettweis, X., van den Broeke, M. R., Pfeffer, W. T., Moussavi, M. S., and Abdalati, W.: Rapid expansion of Greenland's low-permeability ice slabs, Nature, 573, 403–407, https://doi.org/10.1038/s41586-019-1550-3, 2019.
Machguth, H., MacFerrin, M., van As, D., Box, J. E., Charalampidis, C., Colgan, W., Fausto, R. S., Meijer, H. A. J., Mosley-Thompson, E., and van de Wal, R. S. W.: Greenland meltwater storage in firn limited by near-surface ice formation, Nat. Clim. Change, 6, 390–393, https://doi.org/10.1038/nclimate2899, 2016.
Mattingly, K. S., Mote, T. L., and Fettweis, X.: Atmospheric River Impacts on Greenland Ice Sheet Surface Mass Balance, Journal of Geophysical Research: Atmospheres, 123, 8538–8560, https://doi.org/10.1029/2018JD028714, 2018.
Meehl, G. A., Arblaster, J. M., Bates, S., Richter, J. H., Tebaldi, C., Gettelman, A., Medeiros, B., Bacmeister, J., DeRepentigny, P., Rosenbloom, N., Shields, C., Hu, A., Teng, H., Mills, M. J., and Strand, G.: Characteristics of Future Warmer Base States in CESM2, Earth and Space Science, 7, e2020EA001296, https://doi.org/10.1029/2020EA001296, 2020.
Myhre, G., Alterskjær, K., Stjern, C. W., Hodnebrog, Ø., Marelle, L., Samset, B. H., Sillmann, J., Schaller, N., Fischer, E., Schulz, M., and Stohl, A.: Frequency of extreme precipitation increases extensively with event rareness under global warming, Sci. Rep., 9, 16063, https://doi.org/10.1038/s41598-019-52277-4, 2019.
Noël, B., van de Berg, W. J., van Meijgaard, E., Kuipers Munneke, P., van de Wal, R. S. W., and van den Broeke, M. R.: Evaluation of the updated regional climate model RACMO2.3: summer snowfall impact on the Greenland Ice Sheet, The Cryosphere, 9, 1831–1844, https://doi.org/10.5194/tc-9-1831-2015, 2015.
Noël, B., van de Berg, W. J., Machguth, H., Lhermitte, S., Howat, I., Fettweis, X., and van den Broeke, M. R.: A daily, 1 km resolution data set of downscaled Greenland ice sheet surface mass balance (1958–2015), The Cryosphere, 10, 2361–2377, https://doi.org/10.5194/tc-10-2361-2016, 2016.
Noël, B., van de Berg, W. J., Lhermitte, S., Wouters, B., Machguth, H., Howat, I., Citterio, M., Moholdt, G., Lenaerts, J. T. M., and van den Broeke, M. R.: A tipping point in refreezing accelerates mass loss of Greenland's glaciers and ice caps, Nat. Commun., 8, 14730, https://doi.org/10.1038/ncomms14730, 2017.
Noël, B., van de Berg, W. J., van Wessem, J. M., van Meijgaard, E., van As, D., Lenaerts, J. T. M., Lhermitte, S., Kuipers Munneke, P., Smeets, C. J. P. P., van Ulft, L. H., van de Wal, R. S. W., and van den Broeke, M. R.: Modelling the climate and surface mass balance of polar ice sheets using RACMO2 – Part 1: Greenland (1958–2016), The Cryosphere, 12, 811–831, https://doi.org/10.5194/tc-12-811-2018, 2018a.
Noël, B., van de Berg, W. J., Lhermitte, S., Wouters, B., Schaffer, N., and van den Broeke, M. R.: Six Decades of Glacial Mass Loss in the Canadian Arctic Archipelago, Journal of Geophysical Research: Earth Surface, 123, 1430–1449, https://doi.org/10.1029/2017JF004304, 2018b.
Noël, B., van Kampenhout, L., van de Berg, W. J., Lenaerts, J. T. M., Wouters, B., and van den Broeke, M. R.: Brief communication: CESM2 climate forcing (1950–2014) yields realistic Greenland ice sheet surface mass balance, The Cryosphere, 14, 1425–1435, https://doi.org/10.5194/tc-14-1425-2020, 2020.
Noël, B., Kampenhout, L. van, Lenaerts, J. T. M., van de Berg, W. J., and van den Broeke, M. R.: A 21st Century Warming Threshold for Sustained Greenland Ice Sheet Mass Loss, Geophysical Research Letters, 48, e2020GL090471, https://doi.org/10.1029/2020GL090471, 2021.
Noël, B., Lenaerts, J. T. M., 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.
Norris, J., Chen, G., and Neelin, J. D.: Thermodynamic versus Dynamic Controls on Extreme Precipitation in a Warming Climate from the Community Earth System Model Large Ensemble, Journal of Climate, 32, 1025–1045, https://doi.org/10.1175/JCLI-D-18-0302.1, 2019.
Oerlemans, J. and Klok, E. J. L.: Effect of summer snowfall on glacier mass balance, Annals of Glaciology, 38, 97–100, https://doi.org/10.3189/172756404781815158, 2004.
Pendergrass, A. G., Knutti, R., Lehner, F., Deser, C., and Sanderson, B. M.: Precipitation variability increases in a warmer climate, Sci. Rep., 7, 17966, https://doi.org/10.1038/s41598-017-17966-y, 2017.
Priestley, M. D. K. and Catto, J. L.: Future changes in the extratropical storm tracks and cyclone intensity, wind speed, and structure, Weather and Climate Dynamics, 3, 337–360, https://doi.org/10.5194/wcd-3-337-2022, 2022.
Rantanen, M., Karpechko, A. Y., Lipponen, A., Nordling, K., Hyvärinen, O., Ruosteenoja, K., Vihma, T., and Laaksonen, A.: The Arctic has warmed nearly four times faster than the globe since 1979, Commun. Earth Environ., 3, 1–10, https://doi.org/10.1038/s43247-022-00498-3, 2022.
Rignot, E. and Mouginot, J.: Ice flow in Greenland for the International Polar Year 2008–-2009, Geophys. Res. Lett., 39, https://doi.org/10.1029/2012GL051634, 2012.
Rignot, E., Velicogna, I., van den Broeke, M. R., Monaghan, A., and Lenaerts, J. T. M.: Acceleration of the contribution of the Greenland and Antarctic ice sheets to sea level rise, Geophys. Res. Lett., 38, https://doi.org/10.1029/2011GL046583, 2011.
Ryan, J. C., Medley, B., Stevens, C. M., Sutterley, T. C., and Siegfried, M. R.: Role of Snowfall Versus Air Temperatures for Greenland Ice Sheet Melt-Albedo Feedbacks, Earth and Space Science, 10, e2023EA003158, https://doi.org/10.1029/2023EA003158, 2023.
Skific, N., Francis, J. A., and Cassano, J. J.: Attribution of Seasonal and Regional Changes in Arctic Moisture Convergence, Journal of Climate, 22, 5115–5134, https://doi.org/10.1175/2009JCLI2829.1, 2009.
Van As, D., Andersen, M. L., Petersen, D., Fettweis, X., Angelen, J. H. V., Lenaerts, J. T. M., Broeke, M. R. V. D., Lea, J. M., Bøggild, C. E., Ahlstrøm, A. P., and Steffen, K.: Increasing meltwater discharge from the Nuuk region of the Greenland ice sheet and implications for mass balance (1960–-2012), Journal of Glaciology, 60, 314–-322, https://doi.org/10.3189/2014JoG13J065, 2014.
van Dalum, C. T., van de Berg, W. J., and van den Broeke, M. R.: Sensitivity of Antarctic surface climate to a new spectral snow albedo and radiative transfer scheme in RACMO2.3p3, The Cryosphere, 16, 1071–-1089, https://doi.org/10.5194/tc-16-1071-2022, 2022.
van den Broeke, M. R., Enderlin, E. M., Howat, I. M., Kuipers Munneke, P., Noël, B. P. Y., van de Berg, W. J., van Meijgaard, E., and Wouters, B.: On the recent contribution of the Greenland ice sheet to sea level change, The Cryosphere, 10, 1933–1946, https://doi.org/10.5194/tc-10-1933-2016, 2016.
van Kampenhout, L., Lenaerts, J. T. M., Lipscomb, W. H., Sacks, W. J., Lawrence, D. M., Slater, A. G., and van den Broeke, M. R.: Improving the Representation of Polar Snow and Firn in the Community Earth System Model, Journal of Advances in Modeling Earth Systems, 9, 2583–2600, https://doi.org/10.1002/2017MS000988, 2017.
van Kampenhout, L., Rhoades, A. M., Herrington, A. R., Zarzycki, C. M., Lenaerts, J. T. M., Sacks, W. J., and van den Broeke, M. R.: Regional grid refinement in an Earth system model: impacts on the simulated Greenland surface mass balance, The Cryosphere, 13, 1547–1564, https://doi.org/10.5194/tc-13-1547-2019, 2019.
van Kampenhout, L., Lenaerts, J. T. M., Lipscomb, W. H., Lhermitte, S., Noël, B., Vizcaíno, M., Sacks, W. J., and van den Broeke, M. R.: Present-Day Greenland Ice Sheet Climate and Surface Mass Balance in CESM2, Journal of Geophysical Research: Earth Surface, 125, e2019JF005318, https://doi.org/10.1029/2019JF005318, 2020.
van Meijgaard, E., van Ulft, L. H., van den Hurk, B. J. J. M., Lenderink, G., and Siebesma, A. P.: The KNMI regional atmospheric climate model RACMO, version 2, De Bilt, https://cdn.knmi.nl/knmi/pdf/bibliotheek/knmipubTR/TR302.pdf (last access: 3 September 2021), 2008.
van Pelt, W. and Kohler, J.: Modelling the long-term mass balance and firn evolution of glaciers around Kongsfjorden, Svalbard, Journal of Glaciology, 61, 731–744, https://doi.org/10.3189/2015JoG14J223, 2015.
Short summary
We examine how extreme precipitation days affect the seasonal mass balance (SMB) of land ice in Greenland and the Eastern Canadian Arctic in historical and future simulations. Past extreme precipitation led to higher SMB with snowfall. Future extreme precipitation may lead to the loss of ice mass as more falls as rain rather than snow in some regions, such as southwestern Greenland. Across the region, extreme precipitation becomes more important to seasonal SMB in the future, warmer climate.
We examine how extreme precipitation days affect the seasonal mass balance (SMB) of land ice in...
