Articles | Volume 20, issue 11
https://doi.org/10.5194/tc-20-6181-2026
© Author(s) 2026. 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-20-6181-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
30 Oct 2026
Research article |
| 30 Oct 2026
| 30 Oct 2026
Empirical evidence of overestimated Ku-band sea ice radar freeboards in satellite altimetry
Catherine Taelman
CORRESPONDING AUTHOR
Department of Physics and Technology, UiT The Arctic University of Norway, Tromsø, Norway
Jack C. Landy
Department of Physics and Technology, UiT The Arctic University of Norway, Tromsø, Norway
Robbie D. C. Mallett
Department of Physics and Technology, UiT The Arctic University of Norway, Tromsø, Norway
Polona Itkin
Norwegian Polar Institute, Tromsø, Norway
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Anne Braakmann Folgmann, Jack C. Landy, Stefan Hendricks, Clara Vydra, Robert Ricker, and Alessandro Di Bella
EGUsphere, https://doi.org/10.5194/egusphere-2026-5997, https://doi.org/10.5194/egusphere-2026-5997, 2026
This preprint is open for discussion and under review for The Cryosphere (TC).
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This study is the first to assess snow depth on Arctic sea ice year-round, i.e. including the more challenging summer melt season, which is the key season for marine operations and biological production. Our study shows that considerable snow remains in summer (May–Sep). A first test of altimetry-derived snow estimates year-round yields promising results, but higher snow north of Greenland could point at biases in the input altimetry data.
Øyvind Foss, Evgenii Salganik, Jack C. Landy, Samuel Brenner, Arild Sundfjord, Hiroshi Sumata, Sebastian Gerland, and Mats A. Granskog
EGUsphere, https://doi.org/10.5194/egusphere-2026-5407, https://doi.org/10.5194/egusphere-2026-5407, 2026
This preprint is open for discussion and under review for The Cryosphere (TC).
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Sea ice thickness is of key importance in the Arctic Ocean, but it is hard to measure. Using satellite observations and a 3-year record from moored instruments, this study examines sea ice in the northwestern Barents Sea. In 7 of 15 years examined, sea ice arrived from the north rather than forming locally. These irregular arrivals bring thicker and older ice grown while drifting across the Central Arctic Ocean, with consequences for the ocean, ecosystems, and human activity.
Ghislain Picard, Justin Murfitt, Elena Zakharova, Pierre Zeiger, Laurent Arnaud, Jeremie Aublanc, Jack C. Landy, Michele Scagliola, and Claude Duguay
Geosci. Model Dev., 19, 9103–9129, https://doi.org/10.5194/gmd-19-9103-2026, https://doi.org/10.5194/gmd-19-9103-2026, 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.
Ayush Prasad, Ioanna Merkouriadi, Aleksi Nummelin, Jack Landy, Arttu Jutila, and Glen E. Liston
EGUsphere, https://doi.org/10.5194/egusphere-2026-4727, https://doi.org/10.5194/egusphere-2026-4727, 2026
This preprint is open for discussion and under review for The Cryosphere (TC).
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Snow on Arctic sea ice is blown by wind into uneven drifts around ridges, which affects how well we can measure the thickness of the ice from satellites. Numerical models can capture this but are far too slow to run across the whole Arctic. We trained a machine-learning model on detailed simulations of small patches of ice, then applied it across the Arctic using satellite measurements of how rough the ice surface is.
Wenxuan Liu, Ruibo Lei, Taoyong Jin, Heyang Sun, Michel Tsamados, Isolde A. Glissenaar, Jack Christopher Landy, and Yi Zhou
The Cryosphere, 20, 4839–4876, https://doi.org/10.5194/tc-20-4839-2026, https://doi.org/10.5194/tc-20-4839-2026, 2026
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Arctic sea ice is thinning, but its height above the ocean is still hard to measure, especially in summer when melt ponds can look like open water from space. We developed a method that uses laser measurements from the Ice, Cloud, and land Elevation Satellite-2 and nearby satellite images to better separate ice from open water. It captures small ridges more clearly, improves lead detection, and provides year-round freeboard maps that can support better estimates of ice thickness.
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.
Céline Heuzé, Polona Itkin, Vladimir Ivanov, G. W. Kent Moore, Kazuki Nakata, Kay I. Ohshima, and Janna Rückert
EGUsphere, https://doi.org/10.5194/egusphere-2026-3855, https://doi.org/10.5194/egusphere-2026-3855, 2026
This preprint is open for discussion and under review for The Cryosphere (TC).
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Polynyas, openings in the sea ice, play a crucial role in the Arctic winter icescape, notably acting as breathing hole for the ecosystem, hunting ground for Indigenous communities, and comparatively safe navigation alternative. The Arctic being the region of the world changing fastest in response to climate change, we here review how polynyas and their impact on the climate have been changing too, and, for lack of adequate long-term observations or models, extrapolate their future.
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.
Rosalie McKay, Zoe Koenig, Polona Itkin, Rolf Gradinger, Christien Laber, Janina Osanen, Sanna Saur Heiland, and Karley Campbell
EGUsphere, https://doi.org/10.5194/egusphere-2026-4031, https://doi.org/10.5194/egusphere-2026-4031, 2026
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We investigate how sea-ice algal communities and photosynthesis are influenced by nutrients deeper in the water column north of Svalbard. A storm increased ocean mixing, bringing more nutrients and heat to the ice, which had competing effects of supporting photosynthesis and of accelerating ice melt. The storm also reduced light for algal growth by depositing more snow on the ice. Short-term physical forcing can strongly influence sea-ice algal production through multiple interacting processes.
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.
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.
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.
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.
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.
Polona Itkin, Evgenii Salganik, Dmitry V. Divine, Arttu Jutila, Christian Katlein, Mara Neudert, Ian A. Raphael, and Robert Ricker
EGUsphere, https://doi.org/10.5194/egusphere-2025-6081, https://doi.org/10.5194/egusphere-2025-6081, 2025
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We studied how Arctic ice ridges grow and change through winter and spring using a sensor that measures ice thickness without drilling. By comparing these measurements with data from aircraft, underwater surveys, and field work, we show that the sensor can detect both the full ridge thickness and its solid inner core. Our results reveal slow winter strengthening of ridges and highlight this method's value for understanding ice conditions and ecosystems.
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.
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.
Polona Itkin and Glen E. Liston
The Cryosphere, 19, 5111–5133, https://doi.org/10.5194/tc-19-5111-2025, https://doi.org/10.5194/tc-19-5111-2025, 2025
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A sea ice drifting observatory in 2019 and 2020 provided a year of observations of Arctic snow and sea ice, though some data were interrupted, especially during summer melt onset. We developed a data–model fusion system to produce continuous, high-resolution time series of snow and sea ice parameters. On all three analyzed ice types, snow redistribution correlated with sea ice deformation, and level ice thickness was governed by the thinnest fraction of snow cover.
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.
Polona Itkin
The Cryosphere, 19, 1135–1151, https://doi.org/10.5194/tc-19-1135-2025, https://doi.org/10.5194/tc-19-1135-2025, 2025
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Radar satellite images of sea ice were analyzed to understand how sea ice moves and deforms. These data are noisy, especially when looking at small details. A method was developed to filter out the noise. The filtered data were used to monitor how ice plates stretch and compress over time, revealing slow healing of ice fractures. Cohesive clusters of ice plates that move together were studied too. These methods provide climate-relevant insights into the dynamic nature of winter sea ice cover.
Monojit Saha, Julienne Stroeve, Dustin Isleifson, John Yackel, Vishnu Nandan, Jack Christopher Landy, and Hoi Ming Lam
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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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.
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.
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.
Wenkai Guo, Polona Itkin, Suman Singha, Anthony P. Doulgeris, Malin Johansson, and Gunnar Spreen
The Cryosphere, 17, 1279–1297, https://doi.org/10.5194/tc-17-1279-2023, https://doi.org/10.5194/tc-17-1279-2023, 2023
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Sea ice maps are produced to cover the MOSAiC Arctic expedition (2019–2020) and divide sea ice into scientifically meaningful classes. We use a high-resolution X-band synthetic aperture radar dataset and show how image brightness and texture systematically vary across the images. We use an algorithm that reliably corrects this effect and achieve good results, as evaluated by comparisons to ground observations and other studies. The sea ice maps are useful as a basis for future MOSAiC studies.
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.
Wenkai Guo, Polona Itkin, Johannes Lohse, Malin Johansson, and Anthony Paul Doulgeris
The Cryosphere, 16, 237–257, https://doi.org/10.5194/tc-16-237-2022, https://doi.org/10.5194/tc-16-237-2022, 2022
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This study uses radar satellite data categorized into different sea ice types to detect ice deformation, which is significant for climate science and ship navigation. For this, we examine radar signal differences of sea ice between two similar satellite sensors and show an optimal way to apply categorization methods across sensors, so more data can be used for this purpose. This study provides a basis for future reliable and constant detection of ice deformation remotely through satellite data.
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Short summary
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.
Arctic sea ice thickness is commonly estimated using radar measurements from satellites. This...
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