Articles | Volume 19, issue 1
https://doi.org/10.5194/tc-19-325-2025
© 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-19-325-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
27 Jan 2025
Research article |
| 27 Jan 2025
| 27 Jan 2025
Snow depth estimation on leadless landfast ice using Cryo2Ice satellite observations
Monojit Saha
CORRESPONDING AUTHOR
Centre for Earth Observation Science, Department of Environment and Geography, University of Manitoba, Winnipeg, Canada
Julienne Stroeve
Centre for Earth Observation Science, Department of Environment and Geography, University of Manitoba, Winnipeg, Canada
Department of Earth Sciences, University College London, London, United Kingdom
Dustin Isleifson
Centre for Earth Observation Science, Department of Environment and Geography, University of Manitoba, Winnipeg, Canada
John Yackel
Department of Geography, University of Calgary, Calgary, Canada
Vishnu Nandan
Centre for Earth Observation Science, Department of Environment and Geography, University of Manitoba, Winnipeg, Canada
Department of Geography, University of Calgary, Calgary, Canada
Jack Christopher Landy
Centre for Integrated Remote Sensing and Forecasting for Arctic Operations (CIRFA), UiT The Arctic University of Norway, Tromsø, Norway
Hoi Ming Lam
Department of Geography, University of Calgary, Calgary, Canada
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Anton Komarov and Julienne Stroeve
EGUsphere, https://doi.org/10.5194/egusphere-2026-3873, https://doi.org/10.5194/egusphere-2026-3873, 2026
This preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).
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Warming climate and changing precipitation regimes in Arctic and boreal regions cause frequent rain-on-snow events when liquid water precipitate on the snow surface leading to water infiltration, heterogeneous flow, and the development of refrozen percolation features within the snowpack. These processes change the physical properties of the snow and may lead to liquid-water runoff. In this paper, we investigate how local factors affect these processes in a taiga environment.
Julienne Stroeve, Rosemary Willatt, Madeleine Downie, Monojit Saha, Carmen Nab, Alicia Fallows, Clement Soriot, Robbie Mallett, Anton Komarov, Vishnu Nandan, Thomas Newman, Jennifer Lukovich, and John Yackel
The Cryosphere, 20, 4367–4399, https://doi.org/10.5194/tc-20-4367-2026, https://doi.org/10.5194/tc-20-4367-2026, 2026
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We evaluate polarimetry for snow depth retrieval on Arctic winter transport routes. Over landfast ice and tundra, traditional dual-frequency (Ku/Ka) methods often fail. We demonstrate that cross-polarization (VH) provides a more reliable marker for snow/ice and snow/ground interfaces. For lakes, we successfully resolve air, snow, and ice interfaces to retrieve snow and ice thickness simultaneously. These results establish a baseline for future polarimetric satellite missions.
Patrick C. Taylor, Armin Sorooshian, Rei Ueyama, Sebastian Schmidt, Ihab Abboud, Quincy Allison, Kevin Barry, Sebastian Becker, Holly A. Bender, Joseph R. Bennett, James B. Blair, Niklas Bohn, Linette Boisvert, Matthew D. Brown, Roelof Bruintjes, Anthony Bucholtz, Megan Buzanowicz, Brian Cairns, Filippo Calì Quaglia, Eduard Chemyakin, Bo Chen, Gao Chen, Hong Chen, Yu-Wen Chen, Zezhen Cheng, Swarup China, Dan Chirica, Yonghoon Choi, Peter Colarco, Brian Collister, Ewan Crosbie, Maurice J. Cross, Janet Daniels, Paul DeMott, Joshua P. DiGangi, Alcide Giorgio di Sarra, Glenn S. Diskin, Erica K. Dolinar, Eva-Lou Edwards, Samuel Ephraim, Nikolaos Evangeliou, Romanos Foskinis, Francesca Gallo, Lan Gao, José Luis Gómez-Amo, Daisy Gonzalez, Christine Groot Zwaaftink, Pawan Gupta, Ivan Heckman, Michael Hendrickson, Miguel Ricardo A. Hilario, Ken Hirata, Michelle Hofton, Andrew L. Holen, Ulas Im, Alia L. Khan, Ralph Kahn, Alexei V. Korolev, Sonia Kreidenweis, Thomas Krumpen, Nathan Kurtz, Leslie Lait, Bradley Lamkin, Jack Landy, Nurun Nahar Lata, Paul Lawson, Samuel LeBlanc, Sean Leavor, Jing Li, Thorsten Markus, Hal Maring, Andreas H. Massling, Camille Mavis, Flynn McGinnity, Kerry Meyer, Gabriel Mojica, Richard H. Moore, Parker Morris, Giovanni Muscari, Vikas Nataraja, Amin R. Nehrir, Athanasios Nenes, Edward P. Nowottnick, Matteo Ottaviani, Chelsea Parker, Ryan Patnaude, Michael Perez, Russell J. Perkins, Colten Peterson, Alek Petty, Stevie Phothisane, Chris Polashenski, Kerri A. Pratt, Kayla M. Preisler, John Prytherch, David Rabine, Jens Redemann, Ju-Mee Ryoo, Joseph S. Schlosser, Vanessa Selimovic, Michael A. Shook, Morgan Silverman, Henrik Skov, Alexander Smirnov, Cassidy Soloff, Amy Solomon, Snorre Stamnes, Azusa Takeishi, David R. Thompson, K. Lee Thornhill, Rachel Tilling, Michael Tjernström, Monica Tosco, Pedro C. Valdelomar, David Van Gilst, Jian Wang, Zhien Wang, Andrzej Wasilewski, Manfred Wendisch, Brent Wilder, Edward L. Winstead, Albert Wu, Peng Xian, Lauren M. Zamora, Jiaoshi Zhang, Lei Zhang, Lu Zhang, Luke Ziemba, and Paquita Zuidema
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2026-241, https://doi.org/10.5194/essd-2026-241, 2026
Preprint under review for ESSD
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This article summarizes the data sets collected during the Arctic Radiation Cloud aerosol Sea ice Interaction eXperiment (ARCSIX), NASA's most comprehensive Arctic field campaign to date. The overarching goal was to quantify the contributions of surface, clouds, aerosol particles, and precipitation to summer sea ice melt. This paper describes the ARCSIX implementation including the flight strategy, instruments, complementary data sets, access, and usage details.
Elie René-Bazin, Michel Tsamados, Sabrina Sofea Binti Aliff Raziuddin, Joel Perez Ferrer, Tudor Suciu, Carmen Nab, Chamkaur Ghag, Harry Heorton, Rosemary Willatt, Jack Landy, Matthew Fox, and Thomas Bodin
The Cryosphere, 20, 3913–3932, https://doi.org/10.5194/tc-20-3913-2026, https://doi.org/10.5194/tc-20-3913-2026, 2026
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This paper introduces a new statistical approach to retrieve ice and snow depth over the Arctic Ocean, using satellite altimeters measurements. We demonstrate the ability of this method to compute efficiently the sea ice thickness and the snow depth over the Arctic, without major assumptions on the snow. In addition to the ice and snow depth, this approach is efficient to study the penetration of radar and laser pulses, paving the way for further research in satellite altimetry.
Mehran Dadjoo and Dustin Isleifson
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., XI-3-2026, 403–409, https://doi.org/10.5194/isprs-annals-XI-3-2026-403-2026, https://doi.org/10.5194/isprs-annals-XI-3-2026-403-2026, 2026
Lanqing Huang, Julienne Stroeve, Thomas Newman, Robbie Mallett, Rosemary Willatt, Lu Zhou, Malin Johansson, Carmen Nab, and Alicia Fallows
The Cryosphere, 20, 2825–2849, https://doi.org/10.5194/tc-20-2825-2026, https://doi.org/10.5194/tc-20-2825-2026, 2026
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Understanding snow depth on sea ice is key for measuring ice thickness, studying ecosystems, and modelling climate. Using snow and ice thickness measurements from Arctic and Antarctic campaigns, this study examines sub-kilometre-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 parameterisations in snow models and remote sensing algorithms.
Catherine Taelman, Jack Landy, Robbie Mallett, and Polona Itkin
EGUsphere, https://doi.org/10.5194/egusphere-2026-1662, https://doi.org/10.5194/egusphere-2026-1662, 2026
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Arctic sea ice thickness is commonly estimated using radar measurements from satellites. This technique assumes that the snow on sea ice is 'invisible' to the radar signals. We studied if this assumption is valid and found that the radar measurements work well in cold conditions, when air temperatures are below –10 °C. However, the radar measurements can overestimate ice thickness during warmer periods, especially if there is new snowfall and if the snow contains salt.
Rasmus Tage Tonboe, Vishnu Nandan, Marcus Huntemann, Julienne Stroeve, Randall Scharien, John Yackel, Lars Kaleschke, Hoyeon Shi, and Tânia Casal
EGUsphere, https://doi.org/10.5194/egusphere-2026-1440, https://doi.org/10.5194/egusphere-2026-1440, 2026
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Scattering and absorption from air bubbles, voids, and brine pockets significantly affect radar and microwave radiometer measurements of sea ice and light propagation through sea ice. Here, we used a high-resolution dataset, collected during the 2019–20 MOSAiC expedition, of thin ice slices of various Arctic sea ice types to estimate the autocorrelation length and density of the inclusions. The data can be used to initialize sea ice scattering models and for understanding satellite data.
Nicholas Williams, Nicholas Byrne, Daniel Feltham, Peter Jan Van Leeuwen, Ross Bannister, David Schroeder, Isobel Lawrence, Lars Nerger, Jack Landy, and Geoffrey Dawson
EGUsphere, https://doi.org/10.5194/egusphere-2026-742, https://doi.org/10.5194/egusphere-2026-742, 2026
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In this study we present three satellite era Arctic sea ice reanalyses, each assimilating different combinations of sea ice concentration and thickness observations. Results show that using year-round thickness observations substantially improves reanalysis compared to winter-only data. The best-performing reanalysis reveals a seasonally compensating bias cycle, suggesting errors in ice growth, leads, refreezing, marginal ice zone dynamics, redistribution, and melt timing mask model errors.
Wenxuan Liu, Ruibo Lei, Taoyong Jin, Heyang Sun, Michel Tsamados, Isolde A. Glissenaar, Jack Christopher Landy, and Yi Zhou
EGUsphere, https://doi.org/10.5194/egusphere-2026-766, https://doi.org/10.5194/egusphere-2026-766, 2026
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The thickness and surface shape of Arctic sea ice are difficult to measure accurately, especially in summer when melting occurs. We developed a new method that uses ICESat-2 photon data to map sea ice height throughout the year. By carefully filtering noise and using satellite images to help identify open water, we obtained more detailed and reliable ice heights and freeboards than existing products. The results better capture rough ice features and improve accuracy.
Ghislain Picard, Justin Murfitt, Elena Zakharova, Pierre Zeiger, Laurent Arnaud, Jeremie Aublanc, Jack C. Landy, Michele Scagliola, and Claude Duguay
EGUsphere, https://doi.org/10.5194/egusphere-2025-6056, https://doi.org/10.5194/egusphere-2025-6056, 2026
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Radar altimeters measure ice-sheet elevation and sea-ice thickness. To improve their accuracy, we developed a model that simulates altimeter waveforms based on the physical properties of snow and sea ice. It computes the power, time, and Doppler shift of radar echoes as waves travel to the surface, interact with snow and ice, and return to the satellite. The model was verified internally, validated against other models and applied in Antarctica using in-situ snow measurements.
Anne Braakmann-Folgmann, Jack C. Landy, Geoffrey Dawson, and Robert Ricker
The Cryosphere, 20, 905–929, https://doi.org/10.5194/tc-20-905-2026, https://doi.org/10.5194/tc-20-905-2026, 2026
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To calculate sea ice thickness from altimetry, returns from ice and leads need to be differentiated. During summer, melt ponds complicate this task, as they resemble leads. In this study, we improve a previously suggested neural network classifier by expanding the training dataset fivefold, tuning the network architecture and introducing an additional class for thinned floes. We show that this increases the accuracy from 77 ± 5 % to 84 ± 2 % and that more leads are found.
Valentin Ludwig, Caroline Ribere, Sara Fleury, Christian Haas, Michel Tsamados, Mahmoud El Hajj, Jerome Bouffard, Michele Scagliola, Marion Bocquet, Eric de Boisseson, Vincent Boulenger, Guillaume Boutin, Laurence Connor, Léo Edel, Stefan Hendricks, Ferran Hernández Macià, Marcus Huntemann, Lars Kaleschke, Frank Kauker, Jack Landy, Tom Megain, Alek Petty, Till Soya Rasmussen, Mads Hvid Ribergaard, Robert Ricker, Axel Schweiger, Hoyeon Shi, Xiangshan Tian-Kunze, Donghui Yi, and Alessandro Di Bella
EGUsphere, https://doi.org/10.5194/egusphere-2025-6201, https://doi.org/10.5194/egusphere-2025-6201, 2026
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Our paper compares Arctic sea-ice thickness datasets from models, reanalyses, satellite-only, and multi-product sources. We validate them against Beaufort Sea reference data, compare large-scale products, and analyse time series. Cross-product biases range from 0.2–0.4 m, RMSDs from 0.4–0.9 m, and correlations from 0.5–0.8. We find no 2010–2023 trend, but 1995–2023 thinning of ~ 0.5 m in November and ~ 0.3 m in March.
Jack C. Landy, Claude de Rijke-Thomas, Carmen Nab, Isobel Lawrence, Isolde A. Glissenaar, Robbie D. C. Mallett, Renée M. Fredensborg Hansen, Alek Petty, Michel Tsamados, Amy R. Macfarlane, and Anne Braakmann-Folgmann
The Cryosphere, 20, 183–208, https://doi.org/10.5194/tc-20-183-2026, https://doi.org/10.5194/tc-20-183-2026, 2026
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In this study, we use three satellites to test the planned remote sensing approach of the upcoming mission Copernicus Polar Ice and Snow Topography Altimeter (CRISTAL) over sea ice and that its dual radars will accurately measure the heights of the top and base of snow sitting atop floating sea ice floes. Our results suggest that CRISTAL's dual radars will not necessarily measure the snow top and base under all conditions. We find that accurate height measurements depend more on surface roughness than on snow properties, as is commonly assumed.
Stephen E. L. Howell, Alex Cabaj, David G. Babb, Jack C. Landy, Jackie Dawson, Mallik Mahmud, and Mike Brady
The Cryosphere, 19, 6711–6725, https://doi.org/10.5194/tc-19-6711-2025, https://doi.org/10.5194/tc-19-6711-2025, 2025
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The Northwest Passage provides a shorter transit route connecting the Atlantic Ocean to the Pacific Ocean but ever-present sea ice has prevented its practical navigation. Sea ice area in the northern route of the Northwest Passage on September 30, 2024 fell to a minimum of 4×103 km2 or ~3% of its total area, the lowest ice area observed since 1960. This paper describes the unique processes that contributed to the record low sea ice area in the northern route of the Northwest Passage in 2024.
Nicole A. Loeb, Alex Crawford, Brice Noël, and Julienne Stroeve
The Cryosphere, 19, 5403–5422, https://doi.org/10.5194/tc-19-5403-2025, https://doi.org/10.5194/tc-19-5403-2025, 2025
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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.
Siqi Liu, Shiming Xu, Wenkai Guo, Yanfei Fan, Lu Zhou, Jack Landy, Malin Johansson, Weixin Zhu, and Alek Petty
The Cryosphere, 19, 5175–5199, https://doi.org/10.5194/tc-19-5175-2025, https://doi.org/10.5194/tc-19-5175-2025, 2025
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In this study, we explore the potential of using synthetic aperture radars (SAR) to predict the sea ice height measurements by the airborne campaign of Operation IceBridge. In particular, we predict the meter-scale sea ice height with the statistical relationship between the two, overcoming the resolution limitation of SAR images from Sentinel-1 satellites. The prediction and ice drift correction algorithms can be applied to the extrapolation of ICESat-2 measurements in the Arctic region.
Vaishali Chaudhary, Julienne Stroeve, Vishnu Nandan, and Dustin Isleifson
EGUsphere, https://doi.org/10.5194/egusphere-2025-2851, https://doi.org/10.5194/egusphere-2025-2851, 2025
Preprint archived
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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.
Franck Eitel Kemgang Ghomsi, Muharrem Hilmi Erkoç, Roshin P. Raj, Atinç Pirti, Antonio Bonaduce, Babatunde J. Abiodun, and Julienne Stroeve
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
Evgenii Salganik, Odile Crabeck, Niels Fuchs, Nils Hutter, Philipp Anhaus, and Jack Christopher Landy
The Cryosphere, 19, 1259–1278, https://doi.org/10.5194/tc-19-1259-2025, https://doi.org/10.5194/tc-19-1259-2025, 2025
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To measure Arctic ice thickness, we often check how much ice sticks out of the water. This method depends on knowing the ice's density, which drops significantly in summer. Our study, validated with sonar and laser data, shows that these seasonal changes in density can complicate melt measurements. We stress the importance of considering these density changes for more accurate ice thickness readings.
Caroline R. Holmes, Thomas J. Bracegirdle, Paul R. Holland, Julienne Stroeve, and Jeremy Wilkinson
The Cryosphere, 18, 5641–5652, https://doi.org/10.5194/tc-18-5641-2024, https://doi.org/10.5194/tc-18-5641-2024, 2024
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Until recently, satellite data showed an increase in Antarctic sea ice area since 1979, but climate models simulated a decrease over this period. This mismatch was one reason for low confidence in model projections of 21st-century sea ice loss. We show that following low Antarctic sea ice in 2022 and 2023, we can no longer conclude that modelled and observed trends differ. However, differences in the manner of the decline mean that model sea ice projections should still be viewed with caution.
Lu Zhou, Julienne Stroeve, Vishnu Nandan, Rosemary Willatt, Shiming Xu, Weixin Zhu, Sahra Kacimi, Stefanie Arndt, and Zifan Yang
The Cryosphere, 18, 4399–4434, https://doi.org/10.5194/tc-18-4399-2024, https://doi.org/10.5194/tc-18-4399-2024, 2024
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Snow over Antarctic sea ice, influenced by highly variable meteorological conditions and heavy snowfall, has a complex stratigraphy and profound impact on the microwave signature. We employ advanced radiation transfer models to analyse the effects of complex snow properties on brightness temperatures over the sea ice in the Southern Ocean. Great potential lies in the understanding of snow processes and the application to satellite retrievals.
Stephen E. L. Howell, David G. Babb, Jack C. Landy, Isolde A. Glissenaar, Kaitlin McNeil, Benoit Montpetit, and Mike Brady
The Cryosphere, 18, 2321–2333, https://doi.org/10.5194/tc-18-2321-2024, https://doi.org/10.5194/tc-18-2321-2024, 2024
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The CAA serves as both a source and a sink for sea ice from the Arctic Ocean, while also exporting sea ice into Baffin Bay. It is also an important region with respect to navigating the Northwest Passage. Here, we quantify sea ice transport and replenishment across and within the CAA from 2016 to 2022. We also provide the first estimates of the ice area and volume flux within the CAA from the Queen Elizabeth Islands to Parry Channel, which spans the central region of the Northwest Passage.
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.
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.
Geoffrey J. Dawson and Jack C. Landy
The Cryosphere, 17, 4165–4178, https://doi.org/10.5194/tc-17-4165-2023, https://doi.org/10.5194/tc-17-4165-2023, 2023
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In this study, we compared measurements from CryoSat-2 and ICESat-2 over Arctic summer sea ice to understand any possible biases between the two satellites. We found that there is a difference when we measure elevation over summer sea ice using CryoSat-2 and ICESat-2, and this is likely due to surface melt ponds. The differences we found were in good agreement with theoretical predictions, and this work will be valuable for summer sea ice thickness measurements from both altimeters.
Isolde A. Glissenaar, Jack C. Landy, David G. Babb, Geoffrey J. Dawson, and Stephen E. L. Howell
The Cryosphere, 17, 3269–3289, https://doi.org/10.5194/tc-17-3269-2023, https://doi.org/10.5194/tc-17-3269-2023, 2023
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Observations of large-scale ice thickness have unfortunately only been available since 2003, a short record for researching trends and variability. We generated a proxy for sea ice thickness in the Canadian Arctic for 1996–2020. This is the longest available record for large-scale sea ice thickness available to date and the first record reliably covering the channels between the islands in northern Canada. The product shows that sea ice has thinned by 21 cm over the 25-year record in April.
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.
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.
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.
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.
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.
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Short summary
Snow on sea ice is vital for near-shore sea ice geophysical and biological processes. Past studies have measured snow depths using the satellite altimeters Cryosat-2 and ICESat-2 (Cryo2Ice), but estimating sea surface height from leadless landfast sea ice remains challenging. Snow depths from Cryo2Ice are compared to in situ data after adjusting for tides. Realistic snow depths are retrieved, but differences in roughness, satellite footprints, and snow geophysical properties are identified.
Snow on sea ice is vital for near-shore sea ice geophysical and biological processes. Past...
