Articles | Volume 14, issue 7
https://doi.org/10.5194/tc-14-2173-2020
© 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-14-2173-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
The MOSAiC ice floe: sediment-laden survivor from the Siberian shelf
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine
Research, Am Handelshafen 12, 27570 Bremerhaven, Germany
Florent Birrien
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine
Research, Am Handelshafen 12, 27570 Bremerhaven, Germany
Frank Kauker
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine
Research, Am Handelshafen 12, 27570 Bremerhaven, Germany
Thomas Rackow
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine
Research, Am Handelshafen 12, 27570 Bremerhaven, Germany
Luisa von Albedyll
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine
Research, Am Handelshafen 12, 27570 Bremerhaven, Germany
Michael Angelopoulos
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine
Research, Am Handelshafen 12, 27570 Bremerhaven, Germany
H. Jakob Belter
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine
Research, Am Handelshafen 12, 27570 Bremerhaven, Germany
Vladimir Bessonov
Arctic and Antarctic Research Institute, Ulitsa Beringa, 38, Saint
Petersburg, 199397, Russia
Ellen Damm
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine
Research, Am Handelshafen 12, 27570 Bremerhaven, Germany
Klaus Dethloff
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine
Research, Am Handelshafen 12, 27570 Bremerhaven, Germany
Jari Haapala
Finnish Meteorological Institute, Marine Research, P.O. Box 503,
00101 Helsinki, Finland
Christian Haas
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine
Research, Am Handelshafen 12, 27570 Bremerhaven, Germany
Carolynn Harris
Dartmouth College, Department of Earth Science, 6105 Fairchild
Hall, Hanover, NH 03755, USA
Stefan Hendricks
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine
Research, Am Handelshafen 12, 27570 Bremerhaven, Germany
Jens Hoelemann
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine
Research, Am Handelshafen 12, 27570 Bremerhaven, Germany
Mario Hoppmann
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine
Research, Am Handelshafen 12, 27570 Bremerhaven, Germany
Lars Kaleschke
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine
Research, Am Handelshafen 12, 27570 Bremerhaven, Germany
Michael Karcher
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine
Research, Am Handelshafen 12, 27570 Bremerhaven, Germany
Nikolai Kolabutin
Arctic and Antarctic Research Institute, Ulitsa Beringa, 38, Saint
Petersburg, 199397, Russia
Ruibo Lei
Polar Research Institute of China, MNR Key Laboratory for Polar
Science, 451 Jinqiao Road, Pudong, Shanghai 200136, China
Josefine Lenz
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine
Research, Am Handelshafen 12, 27570 Bremerhaven, Germany
Association of Polar Early Career Scientists, Alfred Wegener Institute
for Polar and Marine Research, Telegrafenberg A45, 14473 Potsdam, Germany
Anne Morgenstern
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine
Research, Am Handelshafen 12, 27570 Bremerhaven, Germany
Marcel Nicolaus
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine
Research, Am Handelshafen 12, 27570 Bremerhaven, Germany
Uwe Nixdorf
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine
Research, Am Handelshafen 12, 27570 Bremerhaven, Germany
Tomash Petrovsky
Arctic and Antarctic Research Institute, Ulitsa Beringa, 38, Saint
Petersburg, 199397, Russia
Benjamin Rabe
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine
Research, Am Handelshafen 12, 27570 Bremerhaven, Germany
Lasse Rabenstein
Drift & Noise Polar Services, Stavendamm 17, 28195 Bremen, Germany
Markus Rex
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine
Research, Am Handelshafen 12, 27570 Bremerhaven, Germany
Robert Ricker
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine
Research, Am Handelshafen 12, 27570 Bremerhaven, Germany
Jan Rohde
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine
Research, Am Handelshafen 12, 27570 Bremerhaven, Germany
Egor Shimanchuk
Arctic and Antarctic Research Institute, Ulitsa Beringa, 38, Saint
Petersburg, 199397, Russia
Suman Singha
German Aerospace Center, Remote Sensing Technology Institute, SAR
Signal Processing, Am Fallturm 9, 28359 Bremen, Germany
Vasily Smolyanitsky
Arctic and Antarctic Research Institute, Ulitsa Beringa, 38, Saint
Petersburg, 199397, Russia
Vladimir Sokolov
Arctic and Antarctic Research Institute, Ulitsa Beringa, 38, Saint
Petersburg, 199397, Russia
Tim Stanton
Naval Postgraduate School, Oceanography Department, 833 Dyer Road,
Building 232, Monterey, CA 93943, USA
Anna Timofeeva
Arctic and Antarctic Research Institute, Ulitsa Beringa, 38, Saint
Petersburg, 199397, Russia
Michel Tsamados
Centre for Polar Observation and Modelling, University College
London, Dept. of Earth Science, 5 Gower Place, London WC1E 6BS, UK
Daniel Watkins
College of Earth, Ocean, and Atmospheric Science, Oregon State
University, Corvallis, OR, USA
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Steven Franke, Daniel Steinhage, Veit Helm, Tobias Binder, Uwe Nixdorf, Heinrich Miller, Angelika Humbert, Daniela Jansen, Graeme Eagles, Hannes Eisermann, Wilfried Jokat, Antonia Ruppel, Reinhard Drews, Alexandra Zuhr, Amelie Driemel, Andreas Walter, Peter Konopatzky, Robin Heß, Antonie Haas, Roland Koppe, Pascal H. Andreas, and Olaf Eisen
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Chengyan Liu, Zhaomin Wang, Dake Chen, Xianxian Han, Hengling Leng, Xi Liang, Liangjun Yan, Xiang Li, Craig Stevens, Andrew McC. Hogg, Kazuya Kusahara, Kaihe Yamazaki, Kay I. Ohshima, Meng Zhou, Xiao Cheng, Dongxiao Wang, Changming Dong, Jiping Liu, Qinghua Yang, Xichen Li, Ruibo Lei, Minghu Ding, Zhaoru Zhang, Dujuan Kang, Di Qi, Tongya Liu, Jihai Dong, Lu An, Ru Chen, Tong Zhang, Xiaoming Hu, Bo Han, Haibo Bi, Qi Shu, Longjiang Mu, Shiming Xu, Hu Yang, Hailong Liu, Tingfeng Dou, Zhixuan Feng, Lei Zheng, Xueyuan Tang, Guitao Shi, Yongqing Cai, Bingrui Li, Yang Wu, Xia Lin, Wenjin Sun, Yu Liu, Kai Yu, Yu Zhang, Weizeng Shao, Xiaoyu Wang, Shaojun Zheng, Chengyi Yuan, Chunxia Zhou, Jian Liu, Yang Liu, Yue Xia, Xiaoyu Pan, Jiabao Zeng, Kechen Liu, Jiahao Fan, Chen Cheng, and Qi Li
Geosci. Model Dev., 19, 2985–3033, https://doi.org/10.5194/gmd-19-2985-2026, https://doi.org/10.5194/gmd-19-2985-2026, 2026
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Alistair Duffey, Walker Lee, Lauren Wheeler, Peter Irvine, Benjamin Wagman, Matthew Henry, Daniele Visioni, Michel Tsamados, and Douglas MacMartin
Earth Syst. Dynam., 17, 353–385, https://doi.org/10.5194/esd-17-353-2026, https://doi.org/10.5194/esd-17-353-2026, 2026
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Adding a layer of reflective particles high in the atmosphere is one suggested way of cooling the planet and reducing the impacts of climate change. This technique might be less logistically difficult in the high latitudes, because the material could be released at lower altitude there. Here, we use new simulations in three earth system models to assess how this form of intervention, High-Latitude Low-Altitude Stratospheric Aerosol Injection (HiLLA-SAI), would impact the global climate.
Francisco J. Doblas-Reyes, Jenni Kontkanen, Irina Sandu, Mario Acosta, Mohammed Hussam Al Turjmam, Ivan Alsina-Ferrer, Miguel Andrés-Martínez, Costanza Anerdi, Leo Arriola, Marvin Axness, Marc Batlle Martín, Peter Bauer, Tobias Becker, Daniel Beltrán, Sebastian Beyer, Hendryk Bockelmann, Pierre-Antoine Bretonnière, Sebastien Cabaniols, Silvia Caprioli, Miguel Castrillo, Aparna Chandrasekar, Suvarchal Cheedela, Victor Correal, Emanuele Danovaro, Paolo Davini, Jussi Enkovaara, Claudia Frauen, Barbara Früh, Aina Gaya Àvila, Paolo Ghinassi, Rohit Ghosh, Supriyo Ghosh, Iker González, Katherine Grayson, Matthew Griffith, Ioan Hadade, Christopher Haine, Carl Hartick, Utz-Uwe Haus, Shane Hearne, Heikki Järvinen, Bernat Jiménez, Amal John, Marlin Juchem, Thomas Jung, Jessica Kegel, Matthias Kelbling, Kai Keller, Bruno Kinoshita, Theresa Kiszler, Daniel Klocke, Lukas Kluft, Nikolay Koldunov, Tobias Kölling, Joonas Kolstela, Luis Kornblueh, Sergey Kosukhin, Aleksander Lacima-Nadolnik, Jeisson Javier Leal Rojas, Jonni Lehtiranta, Tuomas Lunttila, Anna Luoma, Pekka Manninen, Alexey Medvedev, Sebastian Milinski, Ali Mohammed, Sebastian Müller, Devaraju Naryanappa, Natalia Nazarova, Sami Niemelä, Bimochan Niraula, Henrik Nortamo, Aleksi Nummelin, Matteo Nurisso, Pablo Ortega, Stella Paronuzzi, Xabier Pedruzo-Bagazgoitia, Charles Pelletier, Carlos Peña, Suraj Polade, Himansu Kesari Pradhan, Rommel Quintanilla, Tiago Quintino, Thomas Rackow, Jouni Räisänen, Maqsood Mubarak Rajput, René Redler, Balthasar Reuter, Nuno Rocha Monteiro, Francesc Roura-Adserias, Silva Ruppert, Susan Sayed, Reiner Schnur, Tanvi Sharma, Dmitry Sidorenko, Outi Sievi-Korte, Albert Soret, Christian Steger, Bjorn Stevens, Jan Streffing, Jaleena Sunny, Luiggi Tenorio, Stephan Thober, Ulf Tigerstedt, Oriol Tinto, Juha Tonttila, Heikki Tuomenvirta, Lauri Tuppi, Ginka Van Thielen, Emanuele Vitali, Jost von Hardenberg, Ingo Wagner, Nils Wedi, Jan Wehner, Sven Willner, Xavier Yepes-Arbós, Florian Ziemen, and Janos Zimmermann
Geosci. Model Dev., 19, 2821–2848, https://doi.org/10.5194/gmd-19-2821-2026, https://doi.org/10.5194/gmd-19-2821-2026, 2026
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The Climate Change Adaptation Digital Twin (Climate DT) pioneers the operationalisation of global climate projections. It produces global simulations with local granularity for adaptation decision-making. Applications are embedded to generate tailored indicators. A unified workflow orchestrates all components in several supercomputers. Data management ensures consistency and streaming enables real-time use. It is a complementary innovation to initiatives like CMIP, CORDEX, and climate services.
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.
Niklas Neckel, Niels Fuchs, Jonathan Kolar, Thomas Kordes, and Christian Haas
EGUsphere, https://doi.org/10.5194/egusphere-2026-714, https://doi.org/10.5194/egusphere-2026-714, 2026
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This study summarizes challenges of operating consumer-grade UAVs over high-latitude Arctic pack ice. High ice-floe drift and the lack of commercial grid-mission solutions north of 85° N hinder the generation of void-free orthomosaics and DEMs. We present an autonomous high-latitude grid-flight approach with pre- and post-flight drift correction, applied during ArcWatch-2 (Aug/Sep 2024), enabling ice thickness, surface type and pond depth retrievals.
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.
Alejandra Quintanilla-Zurita, Benjamin Rabe, Claudia Wekerle, Torsten Kanzow, Ivan Kuznetsov, Sinhue Torres-Valdes, Enric Pallàs-Sanz, and Ying-Chih Fang
Ocean Sci., 22, 305–328, https://doi.org/10.5194/os-22-305-2026, https://doi.org/10.5194/os-22-305-2026, 2026
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During a year-long Arctic expedition, we discovered nine underwater eddies beneath the sea ice in the central Arctic Ocean. These hidden structures form within a layered part of the ocean just below the surface and may reshape water layers and transport heat, freshwater, and nutrients. Using drifting ice platforms, we measured their size, depth, and motion to understand how they form.
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.
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.
Amanda Sellmaier, Ellen Damm, Torsten Sachs, Benjamin Kirbus, Inge Wiekenkamp, Annette Rinke, Falk Pätzold, Daiki Nomura, Astrid Lampert, and Markus Rex
Atmos. Chem. Phys., 25, 17685–17700, https://doi.org/10.5194/acp-25-17685-2025, https://doi.org/10.5194/acp-25-17685-2025, 2025
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This study presents continuous ship-borne measurements of methane (CH4) concentration and isotopic composition monitored during an ice drift expedition in 2020. Using trajectory analysis, we linked atmospheric CH4 variabilities to air mass pathways transported over open water or sea-ice. The study highlights the potential of ship-borne observations to fill significant data gaps in the high Arctic.
Yi-Jie Yang, Suman Singha, Ron Goldman, and Florian Schütte
Earth Syst. Sci. Data, 17, 6807–6837, https://doi.org/10.5194/essd-17-6807-2025, https://doi.org/10.5194/essd-17-6807-2025, 2025
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This data descriptor presents a dataset containing oil slicks, look-alikes, and other remarkable ocean phenomena in synthetic aperture radar (SAR) data, which can be used for training oil spill detection methods. It explains the formation of various oceanic phenomena, supported by examples and supporting materials. These insights can help researchers from diverse backgrounds, such as remote sensing, oceanography, and machine learning, to better understand the sources of the signatures.
Lena G. Buth, Thomas Krumpen, Niklas Neckel, Melinda A. Webster, Gerit Birnbaum, Niels Fuchs, Philipp Heuser, Ole Johannsen, and Christian Haas
The Cryosphere, 19, 6527–6545, https://doi.org/10.5194/tc-19-6527-2025, https://doi.org/10.5194/tc-19-6527-2025, 2025
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Arctic sea ice is becoming smoother, raising the question of how these changes affect melt pond coverage and thereby surface albedo. Using airborne imagery and laser altimeter data, we investigated how pressure ridges influence melt ponds. The presence of ridges does not directly control pond fraction, but it does influence pond size distribution and pond geometry. Small ponds have a more complex shape on rough ice than on smooth ice, while the opposite is true for large ponds.
Matias Uusinoka, Jari Haapala, Jan Åström, Mikko Lensu, and Arttu Polojärvi
The Cryosphere, 19, 6493–6506, https://doi.org/10.5194/tc-19-6493-2025, https://doi.org/10.5194/tc-19-6493-2025, 2025
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We tracked sea ice deformation over a nine-month period using high-resolution ship radar data and a state-of-the-art deep learning technique. We observe that the typically consistent scale-invariant pattern in sea ice deformation has a possible lower limit of about 102 meters in winter, but this behavior disappears during summer. Our findings provide important insights for considering current modeling assumptions and for connecting the scales of interest in sea ice dynamics.
Guokun Lyu, Longjiang Mu, Armin Koehl, Ruibo Lei, Xi Liang, and Chuanyu Liu
Geosci. Model Dev., 18, 9451–9468, https://doi.org/10.5194/gmd-18-9451-2025, https://doi.org/10.5194/gmd-18-9451-2025, 2025
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In the sea ice-ocean models, errors in the parameters and missing spatiotemporal variations contribute to the deviations between the simulations and the observations. We extended an adjoint method to optimize spatiotemporally varying parameters together with the atmosphere forcing and the initial conditions using satellite and in-situ observations. Seasonally, this scheme demonstrates a more prominent advantage in mid-autumn and show great potential for accurately reproducing the Arctic changes.
Pauline Walz, Oliver Fritz, Sabrina Marx, Marlin M. Mueller, Christian Thiel, Josefine Lenz, Soraya Kaiser, Roxanne Frappier, Alexander Zipf, and Moritz Langer
The Cryosphere, 19, 6355–6379, https://doi.org/10.5194/tc-19-6355-2025, https://doi.org/10.5194/tc-19-6355-2025, 2025
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We explored how citizen scientists can help map changes in Arctic landscapes. Using a web tool we created, more than 100 volunteers contributed the approximate center points of particular ground patterns called ice-wedge polygons in aerial images from Alaska and Canada. Our work shows that the data created by volunteers can be used to reconstruct ice-wedge polygon networks and provide valuable insights on the state of frozen ground in the Arctic.
Steven Franke, Mara Neudert, Veit Helm, Arttu Jutila, Océane Hames, Niklas Neckel, Stefanie Arndt, and Christian Haas
The Cryosphere, 19, 6319–6339, https://doi.org/10.5194/tc-19-6319-2025, https://doi.org/10.5194/tc-19-6319-2025, 2025
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Our research explored how icebergs affect the distribution of snow and flooding on Antarctic coastal sea ice. Using aircraft-based radar and laser scanning, we found that icebergs create thick snow drifts on their wind-facing sides and leave snow-free zones in their lee. The weight of these snow drifts often causes the ice below to flood, forming slush. These patterns, driven by wind and iceberg placement, are crucial for understanding sea ice changes and improving climate models.
Igor V. Polyakov, Andrey V. Pnyushkov, Eddy C. Carmack, Matthew Charette, Kyoung-Ho Cho, Steven Dykstra, Jari Haapala, Jinyoung Jung, Lauren Kipp, Eun Jin Yang, and Sergey Molodtsov
Ocean Sci., 21, 3105–3122, https://doi.org/10.5194/os-21-3105-2025, https://doi.org/10.5194/os-21-3105-2025, 2025
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The Siberian Arctic Ocean greatly influences the Arctic climate system. Moreover, the region is experiencing some of the most notable Arctic climate change. In the summer, strong near-inertial currents in the upper (<30m) ocean account for more than half of the current speed and shear. In the winter, upper ocean ventilation due to atlantification distributes wind energy to far deeper (>100m) layers. Understanding the implications for mixing and halocline weakening depends on these findings.
Gavin A. Schmidt, Kenneth D. Mankoff, Jonathan L. Bamber, Clara Burgard, Dustin Carroll, David M. Chandler, Violaine Coulon, Benjamin J. Davison, Matthew H. England, Paul R. Holland, Nicolas C. Jourdain, Qian Li, Juliana M. Marson, Pierre Mathiot, Clive R. McMahon, Twila A. Moon, Ruth Mottram, Sophie Nowicki, Anna Olivé Abelló, Andrew G. Pauling, Thomas Rackow, and Damien Ringeisen
Geosci. Model Dev., 18, 8333–8361, https://doi.org/10.5194/gmd-18-8333-2025, https://doi.org/10.5194/gmd-18-8333-2025, 2025
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The impact of increasing mass loss from the Greenland and Antarctic ice sheets has not so far been included in historical climate model simulations. This paper describes the protocols and data available for modeling groups to add this anomalous freshwater to their ocean modules to better represent the impacts of these fluxes on ocean circulation, sea ice, salinity and sea level.
Hans Segura, Xabier Pedruzo-Bagazgoitia, Philipp Weiss, Sebastian K. Müller, Thomas Rackow, Junhong Lee, Edgar Dolores-Tesillos, Imme Benedict, Matthias Aengenheyster, Razvan Aguridan, Gabriele Arduini, Alexander J. Baker, Jiawei Bao, Swantje Bastin, Eulàlia Baulenas, Tobias Becker, Sebastian Beyer, Hendryk Bockelmann, Nils Brüggemann, Lukas Brunner, Suvarchal K. Cheedela, Sushant Das, Jasper Denissen, Ian Dragaud, Piotr Dziekan, Madeleine Ekblom, Jan Frederik Engels, Monika Esch, Richard Forbes, Claudia Frauen, Lilli Freischem, Diego García-Maroto, Philipp Geier, Paul Gierz, Álvaro González-Cervera, Katherine Grayson, Matthew Griffith, Oliver Gutjahr, Helmuth Haak, Ioan Hadade, Kerstin Haslehner, Shabeh ul Hasson, Jan Hegewald, Lukas Kluft, Aleksei Koldunov, Nikolay Koldunov, Tobias Kölling, Shunya Koseki, Sergey Kosukhin, Josh Kousal, Peter Kuma, Arjun U. Kumar, Rumeng Li, Nicolas Maury, Maximilian Meindl, Sebastian Milinski, Kristian Mogensen, Bimochan Niraula, Jakub Nowak, Divya Sri Praturi, Ulrike Proske, Dian Putrasahan, René Redler, David Santuy, Domokos Sármány, Reiner Schnur, Patrick Scholz, Dmitry Sidorenko, Dorian Spät, Birgit Sützl, Daisuke Takasuka, Adrian Tompkins, Alejandro Uribe, Mirco Valentini, Menno Veerman, Aiko Voigt, Sarah Warnau, Fabian Wachsmann, Marta Wacławczyk, Nils Wedi, Karl-Hermann Wieners, Jonathan Wille, Marius Winkler, Yuting Wu, Florian Ziemen, Janos Zimmermann, Frida A.-M. Bender, Dragana Bojovic, Sandrine Bony, Simona Bordoni, Patrice Brehmer, Marcus Dengler, Emanuel Dutra, Saliou Faye, Erich Fischer, Chiel van Heerwaarden, Cathy Hohenegger, Heikki Järvinen, Markus Jochum, Thomas Jung, Johann H. Jungclaus, Noel S. Keenlyside, Daniel Klocke, Heike Konow, Martina Klose, Szymon Malinowski, Olivia Martius, Thorsten Mauritsen, Juan Pedro Mellado, Theresa Mieslinger, Elsa Mohino, Hanna Pawłowska, Karsten Peters-von Gehlen, Abdoulaye Sarré, Pajam Sobhani, Philip Stier, Lauri Tuppi, Pier Luigi Vidale, Irina Sandu, and Bjorn Stevens
Geosci. Model Dev., 18, 7735–7761, https://doi.org/10.5194/gmd-18-7735-2025, https://doi.org/10.5194/gmd-18-7735-2025, 2025
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The Next Generation of Earth Modeling Systems project (nextGEMS) developed two Earth system models that use horizontal grid spacing of 10 km and finer, giving more fidelity to the representation of local phenomena, globally. In its fourth cycle, nextGEMS simulated the Earth System climate over the 2020–2049 period under the SSP3-7.0 scenario. Here, we provide an overview of nextGEMS, insights into the model development, and the realism of multi-decadal, kilometer-scale simulations.
Karl Kortum, Suman Singha, and Gunnar Spreen
The Cryosphere, 19, 4701–4714, https://doi.org/10.5194/tc-19-4701-2025, https://doi.org/10.5194/tc-19-4701-2025, 2025
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Improved sea ice observations are essential to understanding the processes that lead to the strong warming effect currently being observed in the Arctic. In this work, we combine complementary satellite measurement techniques and find remarkable correlations between the two observations. This allows us to expand the coverage of ice topography measurements to a scope and resolution that could not previously be observed.
Hannah Niehaus, Gunnar Spreen, Larysa Istomina, and Marcel Nicolaus
The Cryosphere, 19, 3915–3938, https://doi.org/10.5194/tc-19-3915-2025, https://doi.org/10.5194/tc-19-3915-2025, 2025
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Melt ponds on Arctic sea ice affect how much solar energy is absorbed, impacting Arctic warming and global climate. In this study satellite data (2017–2023) is used to examine how these ponds vary across regions and seasons. The results show that the surface fraction of melt ponds is more stable in the Central Arctic, with air temperature and surface roughness playing key roles in their formation. Understanding these patterns can help to improve climate models and predictions for Arctic warming.
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.
Fanyi Zhang, Ruibo Lei, Meng Qu, Na Li, Ying Chen, and Xiaoping Pang
The Cryosphere, 19, 3065–3087, https://doi.org/10.5194/tc-19-3065-2025, https://doi.org/10.5194/tc-19-3065-2025, 2025
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We reconstructed sea ice drift trajectories and identified optimal deployment areas for Lagrangian observations in the central Arctic Ocean. The trajectories revealed a preference for ice advection towards the Transpolar Drift region over the Beaufort Gyre, with endpoints influenced by large-scale atmospheric circulation patterns. This study provides critical support for the planning and implementation of Lagrangian observations relying on ice floes in the central Arctic Ocean under changing environmental conditions.
Mehriban Aliyeva, Michael Angelopoulos, Julia Boike, Moritz Langer, Frederieke Miesner, Scott Dallimore, Dustin Whalen, Lukas U. Arenson, and Pier Paul Overduin
EGUsphere, https://doi.org/10.5194/egusphere-2025-2675, https://doi.org/10.5194/egusphere-2025-2675, 2025
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In this study, we investigate the ongoing transformation of terrestrial permafrost into subsea permafrost on a rapidly eroding Arctic island using electrical resistivity tomography and numerical modelling. We draw on 60 years of shoreline data to support our findings. This work is important for understanding permafrost loss in Arctic coastal areas and for guiding future efforts to protect vulnerable shorelines.
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
Simeon Lisovski, Alexandra Runge, Iuliia Shevtsova, Nele Landgraf, Anne Morgenstern, Ronald Reagan Okoth, Matthias Fuchs, Nikolay Lashchinskiy, Carl Stadie, Alison Beamish, Ulrike Herzschuh, Guido Grosse, and Birgit Heim
Earth Syst. Sci. Data, 17, 1707–1730, https://doi.org/10.5194/essd-17-1707-2025, https://doi.org/10.5194/essd-17-1707-2025, 2025
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The Lena Delta is the largest river delta in the Arctic and represents a biodiversity hotspot. Here, we describe multiple field datasets and a detailed habitat classification map for the Lena Delta. We present context and methods of these openly available datasets and show how they can improve our understanding of the rapidly changing Arctic tundra system.
Ephraim Erkens, Michael Angelopoulos, Jens Tronicke, Scott R. Dallimore, Dustin Whalen, Julia Boike, and Pier Paul Overduin
The Cryosphere, 19, 997–1012, https://doi.org/10.5194/tc-19-997-2025, https://doi.org/10.5194/tc-19-997-2025, 2025
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We investigate the depth of subsea permafrost formed by inundation of terrestrial permafrost due to marine transgression around the rapidly disappearing, permafrost-cored Tuktoyaktuk Island (Beaufort Sea, NWT, Canada). We use geoelectrical surveys with floating electrodes to identify the boundary between unfrozen and frozen sediment. Our findings indicate that permafrost thaw depths beneath the seabed can be explained by coastal erosion rates and landscape features before inundation.
Naoya Kanna, Kazutaka Tateyama, Takuji Waseda, Anna Timofeeva, Maria Papadimitraki, Laura Whitmore, Hajime Obata, Daiki Nomura, Hiroshi Ogawa, Youhei Yamashita, and Igor Polyakov
Biogeosciences, 22, 1057–1076, https://doi.org/10.5194/bg-22-1057-2025, https://doi.org/10.5194/bg-22-1057-2025, 2025
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This article presents data on iron and manganese, essential micronutrients for primary producers in the Arctic Laptev and East Siberian seas (LESS). There, observations were made through international cooperation with the Nansen and Amundsen Basin Observational System expedition during the late summer of 2021. The results from this study indicate that the major sources controlling the iron and manganese distributions on the LESS continental margins are river discharge and shelf sediment input.
Thomas Rackow, Xabier Pedruzo-Bagazgoitia, Tobias Becker, Sebastian Milinski, Irina Sandu, Razvan Aguridan, Peter Bechtold, Sebastian Beyer, Jean Bidlot, Souhail Boussetta, Willem Deconinck, Michail Diamantakis, Peter Dueben, Emanuel Dutra, Richard Forbes, Rohit Ghosh, Helge F. Goessling, Ioan Hadade, Jan Hegewald, Thomas Jung, Sarah Keeley, Lukas Kluft, Nikolay Koldunov, Aleksei Koldunov, Tobias Kölling, Josh Kousal, Christian Kühnlein, Pedro Maciel, Kristian Mogensen, Tiago Quintino, Inna Polichtchouk, Balthasar Reuter, Domokos Sármány, Patrick Scholz, Dmitry Sidorenko, Jan Streffing, Birgit Sützl, Daisuke Takasuka, Steffen Tietsche, Mirco Valentini, Benoît Vannière, Nils Wedi, Lorenzo Zampieri, and Florian Ziemen
Geosci. Model Dev., 18, 33–69, https://doi.org/10.5194/gmd-18-33-2025, https://doi.org/10.5194/gmd-18-33-2025, 2025
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Detailed global climate model simulations have been created based on a numerical weather prediction model, offering more accurate spatial detail down to the scale of individual cities ("kilometre-scale") and a better understanding of climate phenomena such as atmospheric storms, whirls in the ocean, and cracks in sea ice. The new model aims to provide globally consistent information on local climate change with greater precision, benefiting environmental planning and local impact modelling.
Bennet Juhls, Anne Morgenstern, Jens Hölemann, Antje Eulenburg, Birgit Heim, Frederieke Miesner, Hendrik Grotheer, Gesine Mollenhauer, Hanno Meyer, Ephraim Erkens, Felica Yara Gehde, Sofia Antonova, Sergey Chalov, Maria Tereshina, Oxana Erina, Evgeniya Fingert, Ekaterina Abramova, Tina Sanders, Liudmila Lebedeva, Nikolai Torgovkin, Georgii Maksimov, Vasily Povazhnyi, Rafael Gonçalves-Araujo, Urban Wünsch, Antonina Chetverova, Sophie Opfergelt, and Pier Paul Overduin
Earth Syst. Sci. Data, 17, 1–28, https://doi.org/10.5194/essd-17-1-2025, https://doi.org/10.5194/essd-17-1-2025, 2025
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The Siberian Arctic is warming fast: permafrost is thawing, river chemistry is changing, and coastal ecosystems are affected. We aimed to understand changes in the Lena River, a major Arctic river flowing to the Arctic Ocean, by collecting 4.5 years of detailed water data, including temperature and carbon and nutrient contents. This dataset records current conditions and helps us to detect future changes. Explore it at https://doi.org/10.1594/PANGAEA.913197 and https://lena-monitoring.awi.de/.
Rui Xu, Chaofang Zhao, Stefanie Arndt, and Christian Haas
The Cryosphere, 18, 5769–5788, https://doi.org/10.5194/tc-18-5769-2024, https://doi.org/10.5194/tc-18-5769-2024, 2024
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The onset of snowmelt on Antarctic sea ice is an important indicator of sea ice change. In this study, we used two radar scatterometers to detect the onset of snowmelt on perennial Antarctic sea ice. Results show that since 2007, snowmelt onset has demonstrated strong interannual and regional variabilities. We also found that the difference in snowmelt onsets between the two scatterometers is closely related to snow metamorphism.
Tore Wulf, Jørgen Buus-Hinkler, Suman Singha, Hoyeon Shi, and Matilde Brandt Kreiner
The Cryosphere, 18, 5277–5300, https://doi.org/10.5194/tc-18-5277-2024, https://doi.org/10.5194/tc-18-5277-2024, 2024
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Here, we present ASIP: a new and comprehensive deep-learning-based methodology to retrieve high-resolution sea ice concentration with accompanying well-calibrated uncertainties from satellite-based active and passive microwave observations at a pan-Arctic scale for all seasons. In a comparative study against pan-Arctic ice charts and well-established passive-microwave-based sea ice products, we show that ASIP generalizes well to the pan-Arctic region.
Lydia Stolpmann, Ingmar Nitze, Ingeborg Bussmann, Benjamin M. Jones, Josefine Lenz, Hanno Meyer, Juliane Wolter, and Guido Grosse
EGUsphere, https://doi.org/10.5194/egusphere-2024-2822, https://doi.org/10.5194/egusphere-2024-2822, 2024
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We combine hydrochemical and lake change data to show consequences of permafrost thaw induced lake changes on hydrochemistry, which are relevant for the global carbon cycle. We found higher methane concentrations in lakes that do not freeze to the ground and show that lagoons have lower methane concentrations than lakes. Our detailed lake sampling approach show higher concentrations in Dissolved Organic Carbon in areas of higher erosion rates, that might increase under the climate warming.
Yi Zhou, Xianwei Wang, Ruibo Lei, Arttu Jutila, Donald K. Perovich, Luisa von Albedyll, Dmitry V. Divine, Yu Zhang, and Christian Haas
EGUsphere, https://doi.org/10.5194/egusphere-2024-2821, https://doi.org/10.5194/egusphere-2024-2821, 2024
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This study examines how the bulk density of Arctic sea ice varies seasonally, a factor often overlooked in satellite measurements of sea ice thickness. From October to April, we found significant seasonal variations in sea ice bulk density at different spatial scales using direct observations as well as airborne and satellite data. New models were then developed to indirectly predict sea ice bulk density. This advance can improve our ability to monitor changes in Arctic sea ice.
Salar Karam, Céline Heuzé, Mario Hoppmann, and Laura de Steur
Ocean Sci., 20, 917–930, https://doi.org/10.5194/os-20-917-2024, https://doi.org/10.5194/os-20-917-2024, 2024
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A long-term mooring array in the Fram Strait allows for an evaluation of decadal trends in temperature in this major oceanic gateway into the Arctic. Since the 1980s, the deep waters of the Greenland Sea and the Eurasian Basin of the Arctic have warmed rapidly at a rate of 0.11°C and 0.05°C per decade, respectively, at a depth of 2500 m. We show that the temperatures of the two basins converged around 2017 and that the deep waters of the Greenland Sea are now a heat source for the Arctic Ocean.
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.
Gemma M. Brett, Greg H. Leonard, Wolfgang Rack, Christian Haas, Patricia J. Langhorne, Natalie J. Robinson, and Anne Irvin
The Cryosphere, 18, 3049–3066, https://doi.org/10.5194/tc-18-3049-2024, https://doi.org/10.5194/tc-18-3049-2024, 2024
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Glacial meltwater with ice crystals flows from beneath ice shelves, causing thicker sea ice with sub-ice platelet layers (SIPLs) beneath. Thicker sea ice and SIPL reveal where and how much meltwater is outflowing. We collected continuous measurements of sea ice and SIPL. In winter, we observed rapid SIPL growth with strong winds. In spring, SIPLs grew when tides caused offshore circulation. Wind-driven and tidal circulation influence glacial meltwater outflow from ice shelf cavities.
Niels Fuchs, Luisa von Albedyll, Gerit Birnbaum, Felix Linhardt, Natascha Oppelt, and Christian Haas
The Cryosphere, 18, 2991–3015, https://doi.org/10.5194/tc-18-2991-2024, https://doi.org/10.5194/tc-18-2991-2024, 2024
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Melt ponds are key components of the Arctic sea ice system, yet methods to derive comprehensive pond depth data are missing. We present a shallow-water bathymetry retrieval to derive this elementary pond property at high spatial resolution from aerial images. The retrieval method is presented in a user-friendly way to facilitate replication. Furthermore, we provide pond properties on the MOSAiC expedition floe, giving insights into the three-dimensional pond evolution before and after drainage.
Ivan Kuznetsov, Benjamin Rabe, Alexey Androsov, Ying-Chih Fang, Mario Hoppmann, Alejandra Quintanilla-Zurita, Sven Harig, Sandra Tippenhauer, Kirstin Schulz, Volker Mohrholz, Ilker Fer, Vera Fofonova, and Markus Janout
Ocean Sci., 20, 759–777, https://doi.org/10.5194/os-20-759-2024, https://doi.org/10.5194/os-20-759-2024, 2024
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Our research introduces a tool for dynamically mapping the Arctic Ocean using data from the MOSAiC experiment. Incorporating extensive data into a model clarifies the ocean's structure and movement. Our findings on temperature, salinity, and currents reveal how water layers mix and identify areas of intense water movement. This enhances understanding of Arctic Ocean dynamics and supports climate impact studies. Our work is vital for comprehending this key region in global climate science.
Jan Åström, Fredrik Robertsen, Jari Haapala, Arttu Polojärvi, Rivo Uiboupin, and Ilja Maljutenko
The Cryosphere, 18, 2429–2442, https://doi.org/10.5194/tc-18-2429-2024, https://doi.org/10.5194/tc-18-2429-2024, 2024
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The HiDEM code has been developed for analyzing the fracture and fragmentation of brittle materials and has been extensively applied to glacier calving. Here, we report on the adaptation of the code to sea-ice dynamics and breakup. The code demonstrates the capability to simulate sea-ice dynamics on a 100 km scale with an unprecedented resolution. We argue that codes of this type may become useful for improving forecasts of sea-ice dynamics.
Yi Zhou, Xianwei Wang, Ruibo Lei, Luisa von Albedyll, Donald K. Perovich, Yu Zhang, and Christian Haas
EGUsphere, https://doi.org/10.5194/egusphere-2024-1240, https://doi.org/10.5194/egusphere-2024-1240, 2024
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This study examines how the density of Arctic sea ice varies seasonally, a factor often overlooked in satellite measurements of sea ice thickness. From October to April, using direct observations and satellite data, we found that sea ice density decreases significantly until mid-January due to increased porosity as the ice ages, and then stabilizes until April. We then developed new models to estimate sea ice density. This advance can improve our ability to monitor changes in Arctic sea ice.
Karl Kortum, Suman Singha, Gunnar Spreen, Nils Hutter, Arttu Jutila, and Christian Haas
The Cryosphere, 18, 2207–2222, https://doi.org/10.5194/tc-18-2207-2024, https://doi.org/10.5194/tc-18-2207-2024, 2024
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A dataset of 20 radar satellite acquisitions and near-simultaneous helicopter-based surveys of the ice topography during the MOSAiC expedition is constructed and used to train a variety of deep learning algorithms. The results give realistic insights into the accuracy of retrieval of measured ice classes using modern deep learning models. The models able to learn from the spatial distribution of the measured sea ice classes are shown to have a clear advantage over those that cannot.
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.
Lars Ackermann, Thomas Rackow, Kai Himstedt, Paul Gierz, Gregor Knorr, and Gerrit Lohmann
Geosci. Model Dev., 17, 3279–3301, https://doi.org/10.5194/gmd-17-3279-2024, https://doi.org/10.5194/gmd-17-3279-2024, 2024
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We present long-term simulations with interactive icebergs in the Southern Ocean. By melting, icebergs reduce the temperature and salinity of the surrounding ocean. In our simulations, we find that this cooling effect of iceberg melting is not limited to the surface ocean but also reaches the deep ocean and propagates northward into all ocean basins. Additionally, the formation of deep-water masses in the Southern Ocean is enhanced.
Katrin Müller, Peter von der Gathen, and Markus Rex
Atmos. Chem. Phys., 24, 4693–4716, https://doi.org/10.5194/acp-24-4693-2024, https://doi.org/10.5194/acp-24-4693-2024, 2024
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The transport history of tropospheric air masses above the tropical western Pacific is studied by local ozone and relative humidity profile measurements from Palau. A prominent anti-correlation between both tracers separates air masses of different origin and genesis. Back trajectories confirm a local convective origin of the year-round humid ozone-poor background. Anomalously dry ozone-rich air is generated in tropical Asia by pollution and dehydrated during transport via radiative cooling.
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.
Evelyn Jäkel, Sebastian Becker, Tim R. Sperzel, Hannah Niehaus, Gunnar Spreen, Ran Tao, Marcel Nicolaus, Wolfgang Dorn, Annette Rinke, Jörg Brauchle, and Manfred Wendisch
The Cryosphere, 18, 1185–1205, https://doi.org/10.5194/tc-18-1185-2024, https://doi.org/10.5194/tc-18-1185-2024, 2024
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The results of the surface albedo scheme of a coupled regional climate model were evaluated against airborne and ground-based measurements conducted in the European Arctic in different seasons between 2017 and 2022. We found a seasonally dependent bias between measured and modeled surface albedo for cloudless and cloudy situations. The strongest effects of the albedo model bias on the net irradiance were most apparent in the presence of optically thin clouds.
Hannah Niehaus, Larysa Istomina, Marcel Nicolaus, Ran Tao, Aleksey Malinka, Eleonora Zege, and Gunnar Spreen
The Cryosphere, 18, 933–956, https://doi.org/10.5194/tc-18-933-2024, https://doi.org/10.5194/tc-18-933-2024, 2024
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Melt ponds are puddles of meltwater which form on Arctic sea ice in the summer period. They are darker than the ice cover and lead to increased absorption of solar energy. Global climate models need information about the Earth's energy budget. Thus satellite observations are used to monitor the surface fractions of melt ponds, ocean, and sea ice in the entire Arctic. We present a new physically based algorithm that can separate these three surface types with uncertainty below 10 %.
Katrin Müller, Jordis S. Tradowsky, Peter von der Gathen, Christoph Ritter, Sharon Patris, Justus Notholt, and Markus Rex
Atmos. Chem. Phys., 24, 2169–2193, https://doi.org/10.5194/acp-24-2169-2024, https://doi.org/10.5194/acp-24-2169-2024, 2024
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The Palau Atmospheric Observatory is introduced as an ideal site to detect changes in atmospheric composition and dynamics above the remote tropical western Pacific. We focus on the ozone sounding program from 2016–2021, including El Niño 2016. The year-round high convective activity is reflected in dominant low tropospheric ozone and high relative humidity. Their seasonal distributions are unique compared to other tropical sites and are modulated by the Intertropical Convergence Zone.
Nathan Beech, Thomas Rackow, Tido Semmler, and Thomas Jung
Geosci. Model Dev., 17, 529–543, https://doi.org/10.5194/gmd-17-529-2024, https://doi.org/10.5194/gmd-17-529-2024, 2024
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Cost-reducing modeling strategies are applied to high-resolution simulations of the Southern Ocean in a changing climate. They are evaluated with respect to observations and traditional, lower-resolution modeling methods. The simulations effectively reproduce small-scale ocean flows seen in satellite data and are largely consistent with traditional model simulations after 4 °C of warming. Small-scale flows are found to intensify near bathymetric features and to become more variable.
Miao Yu, Peng Lu, Matti Leppäranta, Bin Cheng, Ruibo Lei, Bingrui Li, Qingkai Wang, and Zhijun Li
The Cryosphere, 18, 273–288, https://doi.org/10.5194/tc-18-273-2024, https://doi.org/10.5194/tc-18-273-2024, 2024
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Variations in Arctic sea ice are related not only to its macroscale properties but also to its microstructure. Arctic ice cores in the summers of 2008 to 2016 were used to analyze variations in the ice inherent optical properties related to changes in the ice microstructure. The results reveal changing ice microstructure greatly increased the amount of solar radiation transmitted to the upper ocean even when a constant ice thickness was assumed, especially in marginal ice zones.
Céline Heuzé, Oliver Huhn, Maren Walter, Natalia Sukhikh, Salar Karam, Wiebke Körtke, Myriel Vredenborg, Klaus Bulsiewicz, Jürgen Sültenfuß, Ying-Chih Fang, Christian Mertens, Benjamin Rabe, Sandra Tippenhauer, Jacob Allerholt, Hailun He, David Kuhlmey, Ivan Kuznetsov, and Maria Mallet
Earth Syst. Sci. Data, 15, 5517–5534, https://doi.org/10.5194/essd-15-5517-2023, https://doi.org/10.5194/essd-15-5517-2023, 2023
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Gases dissolved in the ocean water not used by the ecosystem (or "passive tracers") are invaluable to track water over long distances and investigate the processes that modify its properties. Unfortunately, especially so in the ice-covered Arctic Ocean, such gas measurements are sparse. We here present a data set of several passive tracers (anthropogenic gases, noble gases and their isotopes) collected over the full ocean depth, weekly, during the 1-year drift in the Arctic during MOSAiC.
Pablo Saavedra Garfias, Heike Kalesse-Los, Luisa von Albedyll, Hannes Griesche, and Gunnar Spreen
Atmos. Chem. Phys., 23, 14521–14546, https://doi.org/10.5194/acp-23-14521-2023, https://doi.org/10.5194/acp-23-14521-2023, 2023
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An important Arctic climate process is the release of heat fluxes from sea ice openings to the atmosphere that influence the clouds. The characterization of this process is the objective of this study. Using synergistic observations from the MOSAiC expedition, we found that single-layer cloud properties show significant differences when clouds are coupled or decoupled to the water vapour transport which is used as physical link between the upwind sea ice openings and the cloud under observation.
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.
Fanyi Zhang, Ruibo Lei, Mengxi Zhai, Xiaoping Pang, and Na Li
The Cryosphere, 17, 4609–4628, https://doi.org/10.5194/tc-17-4609-2023, https://doi.org/10.5194/tc-17-4609-2023, 2023
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Atmospheric circulation anomalies lead to high Arctic sea ice outflow in winter 2020, causing heavy ice conditions in the Barents–Greenland seas, subsequently impeding the sea surface temperature warming. This suggests that the winter–spring Arctic sea ice outflow can be considered a predictor of changes in sea ice and other marine environmental conditions in the Barents–Greenland seas, which could help to improve our understanding of the physical connections between them.
Alexandra M. Zuhr, Erik Loebel, Marek Muchow, Donovan Dennis, Luisa von Albedyll, Frigga Kruse, Heidemarie Kassens, Johanna Grabow, Dieter Piepenburg, Sören Brandt, Rainer Lehmann, Marlene Jessen, Friederike Krüger, Monika Kallfelz, Andreas Preußer, Matthias Braun, Thorsten Seehaus, Frank Lisker, Daniela Röhnert, and Mirko Scheinert
Polarforschung, 91, 73–80, https://doi.org/10.5194/polf-91-73-2023, https://doi.org/10.5194/polf-91-73-2023, 2023
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Polar research is an interdisciplinary and multi-faceted field of research. Its diversity ranges from history to geology and geophysics to social sciences and education. This article provides insights into the different areas of German polar research. This was made possible by a seminar series, POLARSTUNDE, established in the summer of 2020 and organized by the German Society of Polar Research and the German National Committee of the Association of Polar Early Career Scientists (APECS Germany).
Alexander Mchedlishvili, Christof Lüpkes, Alek Petty, Michel Tsamados, and Gunnar Spreen
The Cryosphere, 17, 4103–4131, https://doi.org/10.5194/tc-17-4103-2023, https://doi.org/10.5194/tc-17-4103-2023, 2023
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In this study we looked at sea ice–atmosphere drag coefficients, quantities that help with characterizing the friction between the atmosphere and sea ice, and vice versa. Using ICESat-2, a laser altimeter that measures elevation differences by timing how long it takes for photons it sends out to return to itself, we could map the roughness, i.e., how uneven the surface is. From roughness we then estimate drag force, the frictional force between sea ice and the atmosphere, across the Arctic.
Damien Ringeisen, Nils Hutter, and Luisa von Albedyll
The Cryosphere, 17, 4047–4061, https://doi.org/10.5194/tc-17-4047-2023, https://doi.org/10.5194/tc-17-4047-2023, 2023
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When sea ice is put into motion by wind and ocean currents, it deforms following narrow lines. Our two datasets at different locations and resolutions show that the intersection angle between these lines is often acute and rarely obtuse. We use the orientation of narrow lines to gain indications about the mechanical properties of sea ice and to constrain how to design sea-ice mechanical models for high-resolution simulation of the Arctic and improve regional predictions of sea-ice motion.
Ying Chen, Ruibo Lei, Xi Zhao, Shengli Wu, Yue Liu, Pei Fan, Qing Ji, Peng Zhang, and Xiaoping Pang
Earth Syst. Sci. Data, 15, 3223–3242, https://doi.org/10.5194/essd-15-3223-2023, https://doi.org/10.5194/essd-15-3223-2023, 2023
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The sea ice concentration product derived from the Microwave Radiation Image sensors on board the FengYun-3 satellites can reasonably and independently identify the seasonal and long-term changes of sea ice, as well as extreme cases of annual maximum and minimum sea ice extent in polar regions. It is comparable with other sea ice concentration products and applied to the studies of climate and marine environment.
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.
Sebastian Westermann, Thomas Ingeman-Nielsen, Johanna Scheer, Kristoffer Aalstad, Juditha Aga, Nitin Chaudhary, Bernd Etzelmüller, Simon Filhol, Andreas Kääb, Cas Renette, Louise Steffensen Schmidt, Thomas Vikhamar Schuler, Robin B. Zweigel, Léo Martin, Sarah Morard, Matan Ben-Asher, Michael Angelopoulos, Julia Boike, Brian Groenke, Frederieke Miesner, Jan Nitzbon, Paul Overduin, Simone M. Stuenzi, and Moritz Langer
Geosci. Model Dev., 16, 2607–2647, https://doi.org/10.5194/gmd-16-2607-2023, https://doi.org/10.5194/gmd-16-2607-2023, 2023
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The CryoGrid community model is a new tool for simulating ground temperatures and the water and ice balance in cold regions. It is a modular design, which makes it possible to test different schemes to simulate, for example, permafrost ground in an efficient way. The model contains tools to simulate frozen and unfrozen ground, snow, glaciers, and other massive ice bodies, as well as water bodies.
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.
Robert Ricker, Steven Fons, Arttu Jutila, Nils Hutter, Kyle Duncan, Sinead L. Farrell, Nathan T. Kurtz, and Renée Mie Fredensborg Hansen
The Cryosphere, 17, 1411–1429, https://doi.org/10.5194/tc-17-1411-2023, https://doi.org/10.5194/tc-17-1411-2023, 2023
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Information on sea ice surface topography is important for studies of sea ice as well as for ship navigation through ice. The ICESat-2 satellite senses the sea ice surface with six laser beams. To examine the accuracy of these measurements, we carried out a temporally coincident helicopter flight along the same ground track as the satellite and measured the sea ice surface topography with a laser scanner. This showed that ICESat-2 can see even bumps of only few meters in the sea ice cover.
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.
Na Li, Ruibo Lei, Petra Heil, Bin Cheng, Minghu Ding, Zhongxiang Tian, and Bingrui Li
The Cryosphere, 17, 917–937, https://doi.org/10.5194/tc-17-917-2023, https://doi.org/10.5194/tc-17-917-2023, 2023
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The observed annual maximum landfast ice (LFI) thickness off Zhongshan (Davis) was 1.59±0.17 m (1.64±0.08 m). Larger interannual and local spatial variabilities for the seasonality of LFI were identified at Zhongshan, with the dominant influencing factors of air temperature anomaly, snow atop, local topography and wind regime, and oceanic heat flux. The variability of LFI properties across the study domain prevailed at interannual timescales, over any trend during the recent decades.
Ruibo Lei, Mario Hoppmann, Bin Cheng, Marcel Nicolaus, Fanyi Zhang, Benjamin Rabe, Long Lin, Julia Regnery, and Donald K. Perovich
The Cryosphere Discuss., https://doi.org/10.5194/tc-2023-25, https://doi.org/10.5194/tc-2023-25, 2023
Manuscript not accepted for further review
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To characterize the freezing and melting of different types of sea ice, we deployed four IMBs during the MOSAiC second drift. The drifting pattern, together with a large snow accumulation, relatively warm air temperatures, and a rapid increase in oceanic heat close to Fram Strait, determined the seasonal evolution of the ice mass balance. The refreezing of ponded ice and voids within the unconsolidated ridges amplifies the anisotropy of the heat exchange between the ice and the atmosphere/ocean.
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.
Guillaume Boutin, Einar Ólason, Pierre Rampal, Heather Regan, Camille Lique, Claude Talandier, Laurent Brodeau, and Robert Ricker
The Cryosphere, 17, 617–638, https://doi.org/10.5194/tc-17-617-2023, https://doi.org/10.5194/tc-17-617-2023, 2023
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Sea ice cover in the Arctic is full of cracks, which we call leads. We suspect that these leads play a role for atmosphere–ocean interactions in polar regions, but their importance remains challenging to estimate. We use a new ocean–sea ice model with an original way of representing sea ice dynamics to estimate their impact on winter sea ice production. This model successfully represents sea ice evolution from 2000 to 2018, and we find that about 30 % of ice production takes place in leads.
Marc de Vos, Panagiotis Kountouris, Lasse Rabenstein, John Shears, Mira Suhrhoff, and Christian Katlein
Hist. Geo Space. Sci., 14, 1–13, https://doi.org/10.5194/hgss-14-1-2023, https://doi.org/10.5194/hgss-14-1-2023, 2023
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Poor visibility on the 3 d prior to the sinking of Sir Ernest Shackleton’s vessel, Endurance, during November 1915, hampered navigator Frank Worsley’s attempts to record its position. Thus, whilst the wreck was located in the Weddell Sea in March 2022, the drift path of Endurance during its final 3 d at the surface remained unknown. We used data from a modern meteorological model to reconstruct possible trajectories for this unknown portion of Endurance’s journey.
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.
Francesca Doglioni, Robert Ricker, Benjamin Rabe, Alexander Barth, Charles Troupin, and Torsten Kanzow
Earth Syst. Sci. Data, 15, 225–263, https://doi.org/10.5194/essd-15-225-2023, https://doi.org/10.5194/essd-15-225-2023, 2023
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This paper presents a new satellite-derived gridded dataset, including 10 years of sea surface height and geostrophic velocity at monthly resolution, over the Arctic ice-covered and ice-free regions, up to 88° N. We assess the dataset by comparison to independent satellite and mooring data. Results correlate well with independent satellite data at monthly timescales, and the geostrophic velocity fields can resolve seasonal to interannual variability of boundary currents wider than about 50 km.
Long Lin, Ruibo Lei, Mario Hoppmann, Donald K. Perovich, and Hailun He
The Cryosphere, 16, 4779–4796, https://doi.org/10.5194/tc-16-4779-2022, https://doi.org/10.5194/tc-16-4779-2022, 2022
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Ice mass balance observations indicated that average basal melt onset was comparable in the central Arctic Ocean and approximately 17 d earlier than surface melt in the Beaufort Gyre. The average onset of basal growth lagged behind the surface of the pan-Arctic Ocean for almost 3 months. In the Beaufort Gyre, both drifting-buoy observations and fixed-point observations exhibit a trend towards earlier basal melt onset, which can be ascribed to the earlier warming of the surface ocean.
Julian Gutt, Stefanie Arndt, David Keith Alan Barnes, Horst Bornemann, Thomas Brey, Olaf Eisen, Hauke Flores, Huw Griffiths, Christian Haas, Stefan Hain, Tore Hattermann, Christoph Held, Mario Hoppema, Enrique Isla, Markus Janout, Céline Le Bohec, Heike Link, Felix Christopher Mark, Sebastien Moreau, Scarlett Trimborn, Ilse van Opzeeland, Hans-Otto Pörtner, Fokje Schaafsma, Katharina Teschke, Sandra Tippenhauer, Anton Van de Putte, Mia Wege, Daniel Zitterbart, and Dieter Piepenburg
Biogeosciences, 19, 5313–5342, https://doi.org/10.5194/bg-19-5313-2022, https://doi.org/10.5194/bg-19-5313-2022, 2022
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Long-term ecological observations are key to assess, understand and predict impacts of environmental change on biotas. We present a multidisciplinary framework for such largely lacking investigations in the East Antarctic Southern Ocean, combined with case studies, experimental and modelling work. As climate change is still minor here but is projected to start soon, the timely implementation of this framework provides the unique opportunity to document its ecological impacts from the very onset.
Mario Hoppmann, Ivan Kuznetsov, Ying-Chih Fang, and Benjamin Rabe
Earth Syst. Sci. Data, 14, 4901–4921, https://doi.org/10.5194/essd-14-4901-2022, https://doi.org/10.5194/essd-14-4901-2022, 2022
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The role of eddies and fronts in the oceans is a hot topic in climate research, but there are still many related knowledge gaps, particularly in the ice-covered Arctic Ocean. Here we present a unique dataset of ocean observations collected by a set of drifting buoys installed on ice floes as part of the 2019/2020 MOSAiC campaign. The buoys recorded temperature and salinity data for 10 months, providing extraordinary insights into the properties and processes of the ocean along their drift.
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.
Mauricio Arboleda-Zapata, Michael Angelopoulos, Pier Paul Overduin, Guido Grosse, Benjamin M. Jones, and Jens Tronicke
The Cryosphere, 16, 4423–4445, https://doi.org/10.5194/tc-16-4423-2022, https://doi.org/10.5194/tc-16-4423-2022, 2022
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We demonstrate how we can reliably estimate the thawed–frozen permafrost interface with its associated uncertainties in subsea permafrost environments using 2D electrical resistivity tomography (ERT) data. In addition, we show how further analyses considering 1D inversion and sensitivity assessments can help quantify and better understand 2D ERT inversion results. Our results illustrate the capabilities of the ERT method to get insights into the development of the subsea permafrost.
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.
Jan Streffing, Dmitry Sidorenko, Tido Semmler, Lorenzo Zampieri, Patrick Scholz, Miguel Andrés-Martínez, Nikolay Koldunov, Thomas Rackow, Joakim Kjellsson, Helge Goessling, Marylou Athanase, Qiang Wang, Jan Hegewald, Dmitry V. Sein, Longjiang Mu, Uwe Fladrich, Dirk Barbi, Paul Gierz, Sergey Danilov, Stephan Juricke, Gerrit Lohmann, and Thomas Jung
Geosci. Model Dev., 15, 6399–6427, https://doi.org/10.5194/gmd-15-6399-2022, https://doi.org/10.5194/gmd-15-6399-2022, 2022
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We developed a new atmosphere–ocean coupled climate model, AWI-CM3. Our model is significantly more computationally efficient than its predecessors AWI-CM1 and AWI-CM2. We show that the model, although cheaper to run, provides results of similar quality when modeling the historic period from 1850 to 2014. We identify the remaining weaknesses to outline future work. Finally we preview an improved simulation where the reduction in computational cost has to be invested in higher model resolution.
Erik Loebel, Luisa von Albedyll, Rey Mourot, and Lena Nicola
Polarforschung, 90, 29–32, https://doi.org/10.5194/polf-90-29-2022, https://doi.org/10.5194/polf-90-29-2022, 2022
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On the occasion of Polar Week in March 2021 and with the motto
let’s talk fieldwork, APECS Germany hosted an online polar fieldwork panel discussion. Joined by a group of six early-career polar scientists and an audience of over 140 participants, the event provided an informal environment for debating experiences, issues and ideas. This contribution summarizes the event, sharing practical knowledge about polar fieldwork and fieldwork opportunities for early-career scientists.
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.
Fengguan Gu, Qinghua Yang, Frank Kauker, Changwei Liu, Guanghua Hao, Chao-Yuan Yang, Jiping Liu, Petra Heil, Xuewei Li, and Bo Han
The Cryosphere, 16, 1873–1887, https://doi.org/10.5194/tc-16-1873-2022, https://doi.org/10.5194/tc-16-1873-2022, 2022
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The sea ice thickness was simulated by a single-column model and compared with in situ observations obtained off Zhongshan Station in the Antarctic. It is shown that the unrealistic precipitation in the atmospheric forcing data leads to the largest bias in sea ice thickness and snow depth modeling. In addition, the increasing snow depth gradually inhibits the growth of sea ice associated with thermal blanketing by the snow.
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.
Yu Liang, Haibo Bi, Haijun Huang, Ruibo Lei, Xi Liang, Bin Cheng, and Yunhe Wang
The Cryosphere, 16, 1107–1123, https://doi.org/10.5194/tc-16-1107-2022, https://doi.org/10.5194/tc-16-1107-2022, 2022
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A record minimum July sea ice extent, since 1979, was observed in 2020. Our results reveal that an anomalously high advection of energy and water vapor prevailed during spring (April to June) 2020 over regions with noticeable sea ice retreat. The large-scale atmospheric circulation and cyclones act in concert to trigger the exceptionally warm and moist flow. The convergence of the transport changed the atmospheric characteristics and the surface energy budget, thus causing a severe sea ice melt.
H. E. Markus Meier, Madline Kniebusch, Christian Dieterich, Matthias Gröger, Eduardo Zorita, Ragnar Elmgren, Kai Myrberg, Markus P. Ahola, Alena Bartosova, Erik Bonsdorff, Florian Börgel, Rene Capell, Ida Carlén, Thomas Carlund, Jacob Carstensen, Ole B. Christensen, Volker Dierschke, Claudia Frauen, Morten Frederiksen, Elie Gaget, Anders Galatius, Jari J. Haapala, Antti Halkka, Gustaf Hugelius, Birgit Hünicke, Jaak Jaagus, Mart Jüssi, Jukka Käyhkö, Nina Kirchner, Erik Kjellström, Karol Kulinski, Andreas Lehmann, Göran Lindström, Wilhelm May, Paul A. Miller, Volker Mohrholz, Bärbel Müller-Karulis, Diego Pavón-Jordán, Markus Quante, Marcus Reckermann, Anna Rutgersson, Oleg P. Savchuk, Martin Stendel, Laura Tuomi, Markku Viitasalo, Ralf Weisse, and Wenyan Zhang
Earth Syst. Dynam., 13, 457–593, https://doi.org/10.5194/esd-13-457-2022, https://doi.org/10.5194/esd-13-457-2022, 2022
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Based on the Baltic Earth Assessment Reports of this thematic issue in Earth System Dynamics and recent peer-reviewed literature, current knowledge about the effects of global warming on past and future changes in the climate of the Baltic Sea region is summarised and assessed. The study is an update of the Second Assessment of Climate Change (BACC II) published in 2015 and focuses on the atmosphere, land, cryosphere, ocean, sediments, and the terrestrial and marine biosphere.
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.
Anna Rutgersson, Erik Kjellström, Jari Haapala, Martin Stendel, Irina Danilovich, Martin Drews, Kirsti Jylhä, Pentti Kujala, Xiaoli Guo Larsén, Kirsten Halsnæs, Ilari Lehtonen, Anna Luomaranta, Erik Nilsson, Taru Olsson, Jani Särkkä, Laura Tuomi, and Norbert Wasmund
Earth Syst. Dynam., 13, 251–301, https://doi.org/10.5194/esd-13-251-2022, https://doi.org/10.5194/esd-13-251-2022, 2022
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A natural hazard is a naturally occurring extreme event with a negative effect on people, society, or the environment; major events in the study area include wind storms, extreme waves, high and low sea level, ice ridging, heavy precipitation, sea-effect snowfall, river floods, heat waves, ice seasons, and drought. In the future, an increase in sea level, extreme precipitation, heat waves, and phytoplankton blooms is expected, and a decrease in cold spells and severe ice winters is anticipated.
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.
Florent Garnier, Sara Fleury, Gilles Garric, Jérôme Bouffard, Michel Tsamados, Antoine Laforge, Marion Bocquet, Renée Mie Fredensborg Hansen, and Frédérique Remy
The Cryosphere, 15, 5483–5512, https://doi.org/10.5194/tc-15-5483-2021, https://doi.org/10.5194/tc-15-5483-2021, 2021
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Snow depth data are essential to monitor the impacts of climate change on sea ice volume variations and their impacts on the climate system. For that purpose, we present and assess the altimetric snow depth product, computed in both hemispheres from CryoSat-2 and SARAL satellite data. The use of these data instead of the common climatology reduces the sea ice thickness by about 30 cm over the 2013–2019 period. These data are also crucial to argue for the launch of the CRISTAL satellite mission.
Nele Lamping, Juliane Müller, Jens Hefter, Gesine Mollenhauer, Christian Haas, Xiaoxu Shi, Maria-Elena Vorrath, Gerrit Lohmann, and Claus-Dieter Hillenbrand
Clim. Past, 17, 2305–2326, https://doi.org/10.5194/cp-17-2305-2021, https://doi.org/10.5194/cp-17-2305-2021, 2021
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We analysed biomarker concentrations on surface sediment samples from the Antarctic continental margin. Highly branched isoprenoids and GDGTs are used for reconstructing recent sea-ice distribution patterns and ocean temperatures respectively. We compared our biomarker-based results with data obtained from satellite observations and estimated from a numerical model and find reasonable agreements. Further, we address caveats and provide recommendations for future investigations.
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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Short summary
In October 2019 the research vessel Polarstern was moored to an ice floe in order to travel with it on the 1-year-long MOSAiC journey through the Arctic. Here we provide historical context of the floe's evolution and initial state for upcoming studies. We show that the ice encountered on site was exceptionally thin and was formed on the shallow Siberian shelf. The analyses presented provide the initial state for the analysis and interpretation of upcoming biogeochemical and ecological studies.
In October 2019 the research vessel Polarstern was moored to an ice floe in order to travel with...