Articles | Volume 14, issue 2
https://doi.org/10.5194/tc-14-461-2020
© Author(s) 2020. 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-14-461-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
05 Feb 2020
Research article |
| 05 Feb 2020
| 05 Feb 2020
Effects of decimetre-scale surface roughness on L-band brightness temperature of sea ice
Maciej Miernecki
CORRESPONDING AUTHOR
Centre d'Etudes Spatiales de la Biosphère (CESBIO), 18 avenue Edouard Belin bpi 2801, 31401 Toulouse CEDEX 9, France
Institute of Oceanography (IfM), University of Hamburg, Bundesstr. 53, 20146 Hamburg, Germany
Lars Kaleschke
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven, Bussestr. 24, 27570 Bremerhaven, Germany
Institute of Oceanography (IfM), University of Hamburg, Bundesstr. 53, 20146 Hamburg, Germany
Nina Maaß
Institute of Oceanography (IfM), University of Hamburg, Bundesstr. 53, 20146 Hamburg, Germany
Stefan Hendricks
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven, Bussestr. 24, 27570 Bremerhaven, Germany
Sten Schmidl Søbjærg
Technical University of Denmark, Ørsteds Plads, 2800 Kgs. Lyngby, Denmark
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Marion Bocquet, Robert Ricker, Torbjörn Kagel, Stefan Kern, Thomas Lavergne, Emily Down, and Stefan Hendricks
EGUsphere, https://doi.org/10.5194/egusphere-2026-4063, https://doi.org/10.5194/egusphere-2026-4063, 2026
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Antarctic sea ice has changed dramatically in recent years, highlighting the need for better information on ice and snow thickness. We combined measurements from several satellites with ice motion data to create a daily updated record spanning from 2018 to 2025. By considering the ice drift in the sea-ice thickness gridding process, we captured finer spatial detail and produced more consistent estimates. The results provide a stronger basis for monitoring ongoing changes in the Southern Ocean.
Luisa von Albedyll, Robert Ricker, Frank Kauker, Daniel Krogmann, and Stefan Hendricks
EGUsphere, https://doi.org/10.5194/egusphere-2026-3122, https://doi.org/10.5194/egusphere-2026-3122, 2026
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Using satellite observations and model simulations, we studied winter Arctic sea ice thickness change. Separating thickening from ridging and thinning from lead opening showed that dynamic processes contribute nearly as much to winter ice growth as freezing. Between 2002 and 2020, dynamic thickness change increased linked to stronger sea ice deformation. This is consistent with the idea that sea ice dynamics partly counteract thinning of Arctic sea ice during ongoing climate warming.
Ida Lundtorp Olsen, Henriette Skourup, Heidi Sallila, Stefan Hendricks, Renée Mie Fredensborg Hansen, Stefan Kern, Stephan Paul, Marion Bocquet, Sara Fleury, Dmitry Divine, and Eero Rinne
Earth Syst. Sci. Data, 18, 2469–2505, https://doi.org/10.5194/essd-18-2469-2026, https://doi.org/10.5194/essd-18-2469-2026, 2026
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Discover the latest advancements in sea ice research with our comprehensive Climate Change Initiative (CCI) sea ice thickness (SIT) Round Robin Data Package (RRDP). This pioneering collection contains reference measurements from 1960 to 2024 from airborne sensors, buoys, visual observations and sonar and covers the polar regions from 1993 to 2024, providing crucial reference measurements for validating satellite-derived sea ice thickness.
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.
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.
Robert Ricker, Thomas Lavergne, Stefan Hendricks, Stephan Paul, Emily Down, Mari Anne Killie, and Marion Bocquet
The Cryosphere, 19, 3785–3803, https://doi.org/10.5194/tc-19-3785-2025, https://doi.org/10.5194/tc-19-3785-2025, 2025
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We developed a new method to map Arctic sea ice thickness daily using satellite measurements. We address a problem similar to motion blur in photography. Traditional methods collect satellite data over 1 month to get a full picture of Arctic sea ice thickness. But in the same way as in photos of moving objects, long exposure leads to motion blur, making it difficult to identify certain features in the sea ice maps. Our method corrects for this motion blur, providing a sharper view of the evolving sea ice.
Ole Zeising, Tore Hattermann, Lars Kaleschke, Sophie Berger, Olaf Boebel, Reinhard Drews, M. Reza Ershadi, Tanja Fromm, Frank Pattyn, Daniel Steinhage, and Olaf Eisen
The Cryosphere, 19, 2837–2854, https://doi.org/10.5194/tc-19-2837-2025, https://doi.org/10.5194/tc-19-2837-2025, 2025
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Basal melting of ice shelves impacts the mass loss of the Antarctic Ice Sheet. This study focuses on the Ekström Ice Shelf in East Antarctica, using multiyear data from an autonomous radar system. Results show a surprising seasonal pattern of high melt rates in winter and spring. The seasonalities of sea-ice growth and ocean density indicate that, in winter, dense water enhances plume activity and melt rates. Understanding these dynamics is crucial for improving future mass balance projections.
Lena Happ, Sonali Patil, Stefan Hendricks, Riccardo Fellegara, Lars Kaleschke, and Andreas Gerndt
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., X-G-2025, 333–340, https://doi.org/10.5194/isprs-annals-X-G-2025-333-2025, https://doi.org/10.5194/isprs-annals-X-G-2025-333-2025, 2025
Guisella Gacitúa, Jacob Lorentsen Høyer, Sten Schmidl Søbjærg, Hoyeon Shi, Sotirios Skarpalezos, Ioanna Karagali, Emy Alerskans, and Craig Donlon
Geosci. Instrum. Method. Data Syst., 13, 373–391, https://doi.org/10.5194/gi-13-373-2024, https://doi.org/10.5194/gi-13-373-2024, 2024
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In spring 2021, a study compared sea surface temperature (SST) measurements from thermal infrared (IR) and passive microwave (PMW) radiometers on a ferry between Denmark and Iceland. The goal was to reduce atmospheric effects and directly compare IR and PMW measurements. A method was developed to convert PMW data to match IR data, with uncertainties analysed in the process. The findings provide insights to improve SST inter-comparisons and enhance the synergy between IR and PMW observations.
Lars Kaleschke, Xiangshan Tian-Kunze, Stefan Hendricks, and Robert Ricker
Earth Syst. Sci. Data, 16, 3149–3170, https://doi.org/10.5194/essd-16-3149-2024, https://doi.org/10.5194/essd-16-3149-2024, 2024
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We describe a sea ice thickness dataset based on SMOS satellite measurements, initially designed for the Arctic but adapted for Antarctica. We validated it using limited Antarctic measurements. Our findings show promising results, with a small difference in thickness estimation and a strong correlation with validation data within the valid thickness range. However, improvements and synergies with other sensors are needed, especially for sea ice thicker than 1 m.
Stefanie Arndt, Nina Maaß, Leonard Rossmann, and Marcel Nicolaus
The Cryosphere, 18, 2001–2015, https://doi.org/10.5194/tc-18-2001-2024, https://doi.org/10.5194/tc-18-2001-2024, 2024
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Antarctic sea ice maintains year-round snow cover, crucial for its energy and mass budgets. Despite its significance, snow depth remains poorly understood. Over the last decades, Snow Buoys have been deployed extensively on the sea ice to measure snow accumulation but not actual depth due to snow transformation into meteoric ice. Therefore, in this study we utilize sea ice and snow models to estimate meteoric ice fractions in order to calculate actual snow depth in the Weddell Sea.
Luisa von Albedyll, Stefan Hendricks, Nils Hutter, Dmitrii Murashkin, Lars Kaleschke, Sascha Willmes, Linda Thielke, Xiangshan Tian-Kunze, Gunnar Spreen, and Christian Haas
The Cryosphere, 18, 1259–1285, https://doi.org/10.5194/tc-18-1259-2024, https://doi.org/10.5194/tc-18-1259-2024, 2024
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Leads (openings in sea ice cover) are created by sea ice dynamics. Because they are important for many processes in the Arctic winter climate, we aim to detect them with satellites. We present two new techniques to detect lead widths of a few hundred meters at high spatial resolution (700 m) and independent of clouds or sun illumination. We use the MOSAiC drift 2019–2020 in the Arctic for our case study and compare our new products to other existing lead products.
Haokui Xu, Brooke Medley, Leung Tsang, Joel T. Johnson, Kenneth C. Jezek, Marco Brogioni, and Lars Kaleschke
The Cryosphere, 17, 2793–2809, https://doi.org/10.5194/tc-17-2793-2023, https://doi.org/10.5194/tc-17-2793-2023, 2023
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The density profile of polar ice sheets is a major unknown in estimating the mass loss using lidar tomography methods. In this paper, we show that combing the active radar data and passive radiometer data can provide an estimation of density properties using the new model we implemented in this paper. The new model includes the short and long timescale variations in the firn and also the refrozen layers which are not included in the previous modeling work.
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.
Karina von Schuckmann, Audrey Minière, Flora Gues, Francisco José Cuesta-Valero, Gottfried Kirchengast, Susheel Adusumilli, Fiammetta Straneo, Michaël Ablain, Richard P. Allan, Paul M. Barker, Hugo Beltrami, Alejandro Blazquez, Tim Boyer, Lijing Cheng, John Church, Damien Desbruyeres, Han Dolman, Catia M. Domingues, Almudena García-García, Donata Giglio, John E. Gilson, Maximilian Gorfer, Leopold Haimberger, Maria Z. Hakuba, Stefan Hendricks, Shigeki Hosoda, Gregory C. Johnson, Rachel Killick, Brian King, Nicolas Kolodziejczyk, Anton Korosov, Gerhard Krinner, Mikael Kuusela, Felix W. Landerer, Moritz Langer, Thomas Lavergne, Isobel Lawrence, Yuehua Li, John Lyman, Florence Marti, Ben Marzeion, Michael Mayer, Andrew H. MacDougall, Trevor McDougall, Didier Paolo Monselesan, Jan Nitzbon, Inès Otosaka, Jian Peng, Sarah Purkey, Dean Roemmich, Kanako Sato, Katsunari Sato, Abhishek Savita, Axel Schweiger, Andrew Shepherd, Sonia I. Seneviratne, Leon Simons, Donald A. Slater, Thomas Slater, Andrea K. Steiner, Toshio Suga, Tanguy Szekely, Wim Thiery, Mary-Louise Timmermans, Inne Vanderkelen, Susan E. Wjiffels, Tonghua Wu, and Michael Zemp
Earth Syst. Sci. Data, 15, 1675–1709, https://doi.org/10.5194/essd-15-1675-2023, https://doi.org/10.5194/essd-15-1675-2023, 2023
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Earth's climate is out of energy balance, and this study quantifies how much heat has consequently accumulated over the past decades (ocean: 89 %, land: 6 %, cryosphere: 4 %, atmosphere: 1 %). Since 1971, this accumulated heat reached record values at an increasing pace. The Earth heat inventory provides a comprehensive view on the status and expectation of global warming, and we call for an implementation of this global climate indicator into the Paris Agreement’s Global Stocktake.
Felix L. Müller, Stephan Paul, Stefan Hendricks, and Denise Dettmering
The Cryosphere, 17, 809–825, https://doi.org/10.5194/tc-17-809-2023, https://doi.org/10.5194/tc-17-809-2023, 2023
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Thinning sea ice has significant impacts on the energy exchange between the atmosphere and the ocean. In this study we present visual and quantitative comparisons of thin-ice detections obtained from classified Cryosat-2 radar reflections and thin-ice-thickness estimates derived from MODIS thermal-infrared imagery. In addition to good comparability, the results of the study indicate the potential for a deeper understanding of sea ice in the polar seas and improved processing of altimeter data.
Marco Brogioni, Mark J. Andrews, Stefano Urbini, Kenneth C. Jezek, Joel T. Johnson, Marion Leduc-Leballeur, Giovanni Macelloni, Stephen F. Ackley, Alexandra Bringer, Ludovic Brucker, Oguz Demir, Giacomo Fontanelli, Caglar Yardim, Lars Kaleschke, Francesco Montomoli, Leung Tsang, Silvia Becagli, and Massimo Frezzotti
The Cryosphere, 17, 255–278, https://doi.org/10.5194/tc-17-255-2023, https://doi.org/10.5194/tc-17-255-2023, 2023
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In 2018 the first Antarctic campaign of UWBRAD was carried out. UWBRAD is a new radiometer able to collect microwave spectral signatures over 0.5–2 GHz, thus outperforming existing similar sensors. It allows us to probe thicker sea ice and ice sheet down to the bedrock. In this work we tried to assess the UWBRAD potentials for sea ice, glaciers, ice shelves and buried lakes. We also highlighted the wider range of information the spectral signature can provide to glaciological studies.
Jinfei Wang, Chao Min, Robert Ricker, Qian Shi, Bo Han, Stefan Hendricks, Renhao Wu, and Qinghua Yang
The Cryosphere, 16, 4473–4490, https://doi.org/10.5194/tc-16-4473-2022, https://doi.org/10.5194/tc-16-4473-2022, 2022
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The differences between Envisat and ICESat sea ice thickness (SIT) reveal significant temporal and spatial variations. Our findings suggest that both overestimation of Envisat sea ice freeboard, potentially caused by radar backscatter originating from inside the snow layer, and the AMSR-E snow depth biases and sea ice density uncertainties can possibly account for the differences between Envisat and ICESat SIT.
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.
Klaus Dethloff, Wieslaw Maslowski, Stefan Hendricks, Younjoo J. Lee, Helge F. Goessling, Thomas Krumpen, Christian Haas, Dörthe Handorf, Robert Ricker, Vladimir Bessonov, John J. Cassano, Jaclyn Clement Kinney, Robert Osinski, Markus Rex, Annette Rinke, Julia Sokolova, and Anja Sommerfeld
The Cryosphere, 16, 981–1005, https://doi.org/10.5194/tc-16-981-2022, https://doi.org/10.5194/tc-16-981-2022, 2022
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Sea ice thickness anomalies during the MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) winter in January, February and March 2020 were simulated with the coupled Regional Arctic climate System Model (RASM) and compared with CryoSat-2/SMOS satellite data. Hindcast and ensemble simulations indicate that the sea ice anomalies are driven by nonlinear interactions between ice growth processes and wind-driven sea-ice transports, with dynamics playing a dominant role.
Arttu Jutila, Stefan Hendricks, Robert Ricker, Luisa von Albedyll, Thomas Krumpen, and Christian Haas
The Cryosphere, 16, 259–275, https://doi.org/10.5194/tc-16-259-2022, https://doi.org/10.5194/tc-16-259-2022, 2022
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Sea-ice thickness retrieval from satellite altimeters relies on assumed sea-ice density values because density cannot be measured from space. We derived bulk densities for different ice types using airborne laser, radar, and electromagnetic induction sounding measurements. Compared to previous studies, we found high bulk density values due to ice deformation and younger ice cover. Using sea-ice freeboard, we derived a sea-ice bulk density parameterisation that can be applied to satellite data.
Marek Muchow, Amelie U. Schmitt, and Lars Kaleschke
The Cryosphere, 15, 4527–4537, https://doi.org/10.5194/tc-15-4527-2021, https://doi.org/10.5194/tc-15-4527-2021, 2021
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Linear-like openings in sea ice, also called leads, occur with widths from meters to kilometers. We use satellite images from Sentinel-2 with a resolution of 10 m to identify leads and measure their widths. With that we investigate the frequency of lead widths using two different statistical methods, since other studies have shown a dependency of heat exchange on the lead width. We are the first to address the sea-ice lead-width distribution in the Weddell Sea, Antarctica.
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