Articles | Volume 15, issue 5
https://doi.org/10.5194/tc-15-2167-2021
© Author(s) 2021. 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-15-2167-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
04 May 2021
Research article |
| 04 May 2021
| 04 May 2021
Linking sea ice deformation to ice thickness redistribution using high-resolution satellite and airborne observations
Luisa von Albedyll
CORRESPONDING AUTHOR
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, 27570 Bremerhaven, Germany
Christian Haas
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, 27570 Bremerhaven, Germany
Institute of Environmental Physics, University of Bremen, 28359 Bremen, Germany
Wolfgang Dierking
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, 27570 Bremerhaven, Germany
Center for Integrated Remote Sensing and Forecasting for Arctic Operations, UiT – The Arctic University of Norway, 9019 Tromsø, Norway
Related authors
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
Preprint archived
Short summary
Short summary
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.
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
Short summary
Short summary
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.
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
Preprint archived
Short summary
Short summary
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.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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).
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
Thomas Krumpen, Luisa von Albedyll, Helge F. Goessling, Stefan Hendricks, Bennet Juhls, Gunnar Spreen, Sascha Willmes, H. Jakob Belter, Klaus Dethloff, Christian Haas, Lars Kaleschke, Christian Katlein, Xiangshan Tian-Kunze, Robert Ricker, Philip Rostosky, Janna Rückert, Suman Singha, and Julia Sokolova
The Cryosphere, 15, 3897–3920, https://doi.org/10.5194/tc-15-3897-2021, https://doi.org/10.5194/tc-15-3897-2021, 2021
Short summary
Short summary
We use satellite data records collected along the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) drift to categorize ice conditions that shaped and characterized the floe and surroundings during the expedition. A comparison with previous years is made whenever possible. The aim of this analysis is to provide a basis and reference for subsequent research in the six main research areas of atmosphere, ocean, sea ice, biogeochemistry, remote sensing and ecology.
H. Jakob Belter, Thomas Krumpen, Luisa von Albedyll, Tatiana A. Alekseeva, Gerit Birnbaum, Sergei V. Frolov, Stefan Hendricks, Andreas Herber, Igor Polyakov, Ian Raphael, Robert Ricker, Sergei S. Serovetnikov, Melinda Webster, and Christian Haas
The Cryosphere, 15, 2575–2591, https://doi.org/10.5194/tc-15-2575-2021, https://doi.org/10.5194/tc-15-2575-2021, 2021
Short summary
Short summary
Summer sea ice thickness observations based on electromagnetic induction measurements north of Fram Strait show a 20 % reduction in mean and modal ice thickness from 2001–2020. The observed variability is caused by changes in drift speeds and consequential variations in sea ice age and number of freezing-degree days. Increased ocean heat fluxes measured upstream in the source regions of Arctic ice seem to precondition ice thickness, which is potentially still measurable more than a year later.
Luisa von Albedyll
Polarforschung, 89, 115–117, https://doi.org/10.5194/polf-89-115-2021, https://doi.org/10.5194/polf-89-115-2021, 2021
Short summary
Short summary
Submarines and satellites observed a halving of Arctic sea ice thickness in the last 60 years. Sea ice thinning alters the Arctic climate and ecosystem and the weather in our latitudes. Rising air and ocean temperatures and increased ice drift speeds cause the thinning. Thinner ice breaks up easier, and can pile up locally in thick ridges. Understanding the contribution of those processes to the ice thickness enables us to better predict the future of Arctic sea ice.
Steven Franke, Mara Neudert, Veit Helm, Arttu Jutila, Océane Hames, Niklas Neckel, Stefanie Arndt, and Christian Haas
EGUsphere, https://doi.org/10.5194/egusphere-2025-2657, https://doi.org/10.5194/egusphere-2025-2657, 2025
Short summary
Short summary
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.
Lena G. Buth, Thomas Krumpen, Niklas Neckel, Melinda A. Webster, Gerit Birnbaum, Niels Fuchs, Philipp Heuser, Ole Johannsen, and Christian Haas
EGUsphere, https://doi.org/10.5194/egusphere-2025-1103, https://doi.org/10.5194/egusphere-2025-1103, 2025
Short summary
Short summary
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.
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
Short summary
Short summary
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.
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
Preprint archived
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Preprint archived
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
Laust Færch, Wolfgang Dierking, Nick Hughes, and Anthony P. Doulgeris
The Cryosphere, 17, 5335–5355, https://doi.org/10.5194/tc-17-5335-2023, https://doi.org/10.5194/tc-17-5335-2023, 2023
Short summary
Short summary
Icebergs in open water are a risk to maritime traffic. We have compared six different constant false alarm rate (CFAR) detectors on overlapping C- and L-band synthetic aperture radar (SAR) images for the detection of icebergs in open water, with a Sentinel-2 image used for validation. The results revealed that L-band gives a slight advantage over C-band, depending on which detector is used. Additionally, the accuracy of all detectors decreased rapidly as the iceberg size decreased.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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).
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
Stefanie Arndt, Christian Haas, Hanno Meyer, Ilka Peeken, and Thomas Krumpen
The Cryosphere, 15, 4165–4178, https://doi.org/10.5194/tc-15-4165-2021, https://doi.org/10.5194/tc-15-4165-2021, 2021
Short summary
Short summary
We present here snow and ice core data from the northwestern Weddell Sea in late austral summer 2019, which allow insights into possible reasons for the recent low summer sea ice extent in the Weddell Sea. We suggest that the fraction of superimposed ice and snow ice can be used here as a sensitive indicator. However, snow and ice properties were not exceptional, suggesting that the summer surface energy balance and related seasonal transition of snow properties have changed little in the past.
Thomas Krumpen, Luisa von Albedyll, Helge F. Goessling, Stefan Hendricks, Bennet Juhls, Gunnar Spreen, Sascha Willmes, H. Jakob Belter, Klaus Dethloff, Christian Haas, Lars Kaleschke, Christian Katlein, Xiangshan Tian-Kunze, Robert Ricker, Philip Rostosky, Janna Rückert, Suman Singha, and Julia Sokolova
The Cryosphere, 15, 3897–3920, https://doi.org/10.5194/tc-15-3897-2021, https://doi.org/10.5194/tc-15-3897-2021, 2021
Short summary
Short summary
We use satellite data records collected along the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) drift to categorize ice conditions that shaped and characterized the floe and surroundings during the expedition. A comparison with previous years is made whenever possible. The aim of this analysis is to provide a basis and reference for subsequent research in the six main research areas of atmosphere, ocean, sea ice, biogeochemistry, remote sensing and ecology.
H. Jakob Belter, Thomas Krumpen, Luisa von Albedyll, Tatiana A. Alekseeva, Gerit Birnbaum, Sergei V. Frolov, Stefan Hendricks, Andreas Herber, Igor Polyakov, Ian Raphael, Robert Ricker, Sergei S. Serovetnikov, Melinda Webster, and Christian Haas
The Cryosphere, 15, 2575–2591, https://doi.org/10.5194/tc-15-2575-2021, https://doi.org/10.5194/tc-15-2575-2021, 2021
Short summary
Short summary
Summer sea ice thickness observations based on electromagnetic induction measurements north of Fram Strait show a 20 % reduction in mean and modal ice thickness from 2001–2020. The observed variability is caused by changes in drift speeds and consequential variations in sea ice age and number of freezing-degree days. Increased ocean heat fluxes measured upstream in the source regions of Arctic ice seem to precondition ice thickness, which is potentially still measurable more than a year later.
Luisa von Albedyll
Polarforschung, 89, 115–117, https://doi.org/10.5194/polf-89-115-2021, https://doi.org/10.5194/polf-89-115-2021, 2021
Short summary
Short summary
Submarines and satellites observed a halving of Arctic sea ice thickness in the last 60 years. Sea ice thinning alters the Arctic climate and ecosystem and the weather in our latitudes. Rising air and ocean temperatures and increased ice drift speeds cause the thinning. Thinner ice breaks up easier, and can pile up locally in thick ridges. Understanding the contribution of those processes to the ice thickness enables us to better predict the future of Arctic sea ice.
Gemma M. Brett, Gregory H. Leonard, Wolfgang Rack, Christian Haas, Patricia J. Langhorne, and Anne Irvin
The Cryosphere Discuss., https://doi.org/10.5194/tc-2021-61, https://doi.org/10.5194/tc-2021-61, 2021
Manuscript not accepted for further review
Short summary
Short summary
Using a geophysical technique, we observe temporal variability in the influence of ice shelf meltwater on coastal sea ice which forms platelet ice crystals which contribute to the thickness of the sea ice and accumulate into a thick mass called a sub-ice platelet layer (SIPL). The variability observed in the SIPL indicated that circulation of ice shelf meltwater out from the cavity in McMurdo Sound is influenced by tides and strong offshore winds which affect surface ocean circulation.
Christian Haas, Patricia J. Langhorne, Wolfgang Rack, Greg H. Leonard, Gemma M. Brett, Daniel Price, Justin F. Beckers, and Alex J. Gough
The Cryosphere, 15, 247–264, https://doi.org/10.5194/tc-15-247-2021, https://doi.org/10.5194/tc-15-247-2021, 2021
Short summary
Short summary
We developed a method to remotely detect proxy signals of Antarctic ice shelf melt under adjacent sea ice. It is based on aircraft surveys with electromagnetic induction sounding. We found year-to-year variability of the ice shelf melt proxy in McMurdo Sound and spatial fine structure that support assumptions about the melt of the McMurdo Ice Shelf. With this method it will be possible to map and detect locations of intense ice shelf melt along the coast of Antarctica.
Maria-Elena Vorrath, Juliane Müller, Lorena Rebolledo, Paola Cárdenas, Xiaoxu Shi, Oliver Esper, Thomas Opel, Walter Geibert, Práxedes Muñoz, Christian Haas, Gerhard Kuhn, Carina B. Lange, Gerrit Lohmann, and Gesine Mollenhauer
Clim. Past, 16, 2459–2483, https://doi.org/10.5194/cp-16-2459-2020, https://doi.org/10.5194/cp-16-2459-2020, 2020
Short summary
Short summary
We tested the applicability of the organic biomarker IPSO25 for sea ice reconstructions in the industrial era at the western Antarctic Peninsula. We successfully evaluated our data with satellite sea ice observations. The comparison with marine and ice core records revealed that sea ice interpretations must consider climatic and sea ice dynamics. Sea ice biomarker production is mainly influenced by the Southern Annular Mode, while the El Niño–Southern Oscillation seems to have a minor impact.
Joshua King, Stephen Howell, Mike Brady, Peter Toose, Chris Derksen, Christian Haas, and Justin Beckers
The Cryosphere, 14, 4323–4339, https://doi.org/10.5194/tc-14-4323-2020, https://doi.org/10.5194/tc-14-4323-2020, 2020
Short summary
Short summary
Physical measurements of snow on sea ice are sparse, making it difficulty to evaluate satellite estimates or model representations. Here, we introduce new measurements of snow properties on sea ice to better understand variability at distances less than 200 m. Our work shows that similarities in the snow structure are found at longer distances on younger ice than older ice.
Wolfgang Dierking, Harry L. Stern, and Jennifer K. Hutchings
The Cryosphere, 14, 2999–3016, https://doi.org/10.5194/tc-14-2999-2020, https://doi.org/10.5194/tc-14-2999-2020, 2020
Short summary
Short summary
Monitoring deformation of sea ice is useful for studying effects of ice compression and divergent motion on the ice mass balance and ocean–ice–atmosphere interactions. In calculations of deformation parameters not only the measurement uncertainty of drift vectors has to be considered. The size of the area and the time interval used in the calculations have to be chosen within certain limits to make sure that the uncertainties of deformation parameters are smaller than their real magnitudes.
Cited articles
Amundrud, T. L., Melling, H., and Ingram, R. G.: Geometrical constraints on the
evolution of ridged sea ice, J. Geophys. Res., 109, C06005,
https://doi.org/10.1029/2003jc002251, 2004. a, b, c
Baumann, T. M., Polyakov, I. V., Padman, L., Danielson, S., Fer, I., Janout,
M., Williams, W., and Pnyushkov, A. V.: Arctic tidal current atlas,
Scientific Data, 7, 275, https://doi.org/10.1038/s41597-020-00578-z, 2020. a
CICE Consortium Icepack: Icepack version 1.1.0, Zenodo [code],
https://doi.org/10.5281/zenodo.1213462, 2020. a, b
Dierking, W., Stern, H. L., and Hutchings, J. K.: Estimating statistical errors in retrievals of ice velocity and deformation parameters from satellite images and buoy arrays, The Cryosphere, 14, 2999–3016, https://doi.org/10.5194/tc-14-2999-2020, 2020. a
Duncan, K., Farrell, S. L., Hutchings, J., and Richter-Menge, J.: Late Winter
Observations of Sea Ice Pressure Ridge Sail Height, IEEE Geosci.
Remote S., 1–5, https://doi.org/10.1109/lgrs.2020.3004724, 2020. a
Egbert, G. D. and Erofeeva, S. Y.: Efficient Inverse Modeling of Barotropic
Ocean Tides, J. Atmos. Ocean. Tech., 19, 183–204,
https://doi.org/10.1175/1520-0426(2002)019<0183:eimobo>2.0.co;2, 2002. a
Ervik, Å., Høyland, K. V., Shestov, A., and Nord, T. S.: On the decay of
first-year ice ridges: Measurements and evolution of rubble macroporosity,
ridge drilling resistance and consolidated layer strength, Cold Reg.
Sci. Technol., 151, 196–207,
https://doi.org/10.1016/j.coldregions.2018.03.024, 2018. a
ESA: Copernicus Open Access Hub, https://scihub.copernicus.eu/dhus/#/home, last access: 14 January 2020. a
EUMETSAT Ocean and Sea Ice Satellite Application Facility (OSI SAF): Low resolution sea ice drift product, http://osisaf.met.no/p/ice/lr_ice_drift.html, last access: 11 May 2020. a
Flato, G. M. and Hibler, W. D.: Ridging and strength in modeling the thickness
distribution of Arctic sea ice, J. Geophys. Res., 100,
18611, https://doi.org/10.1029/95jc02091, 1995. a
Griebel, J. and Dierking, W.: Impact of Sea Ice Drift Retrieval Errors,
Discretization and Grid Type on Calculations of Ice Deformation, Remote
Sensing, 10, 393, https://doi.org/10.3390/rs10030393, 2018. a, b
Haas, C., Gerland, S., Eicken, H., and Miller, H.: Comparison of sea-ice
thickness measurements under summer and winter conditions in the Arctic using
a small electromagnetic induction device, Geophysics, 62, 749–757,
https://doi.org/10.1190/1.1444184, 1997. a
Haas, C., Hendricks, S., and Doble, M.: Comparison of the Sea-ice thickness
distribution in the Lincoln Sea and adjacent Arctic Ocean in 2004 and 2005,
Ann. Glaciol., 44, 247–252, https://doi.org/10.3189/172756406781811781, 2006. a
Haas, C., Pfaffling, A., Hendricks, S., Rabenstein, L., Etienne, J.-L., and
Rigor, I.: Reduced ice thickness in Arctic Transpolar Drift favors rapid ice
retreat, Geophys. Res. Lett., 35, L17501,
https://doi.org/10.1029/2008GL034457, 2008. a, b
Haas, C., Lobach, J., Hendricks, S., Rabenstein, L., and Pfaffling, A.:
Helicopter-borne measurements of sea ice thickness, using a small and
lightweight, digital EM system, J. Appl. Geophys., 67, 234–241,
https://doi.org/10.1016/j.jappgeo.2008.05.005, 2009. a, b, c, d
Heil, P. and Hibler, W. D.: Modeling the High-Frequency Component of Arctic Sea
Ice Drift and Deformation, J. Phys. Oceanogr., 32, 3039–3057,
https://doi.org/10.1175/1520-0485(2002)032<3039:mthfco>2.0.co;2, 2002. a
Hendricks, S.: Validierung von altimetrischen Meereisdickenmessungen mit einem
helikopter-basierten elektromagnetischen Induktionsverfahren, Ph.D. thesis,
Universität Bremen,
available at: https://epic.awi.de/id/eprint/20890/1/Hen2009b.pdf (last access: 8 May 2020), 2009. a
Hollands, T. and Dierking, W.: Performance of a multiscale correlation
algorithm for the estimation of sea-ice drift from SAR images: initial
results, Ann. Glaciol., 52, 311–317,
https://doi.org/10.3189/172756411795931462, 2011. a, b, c
Hollands, T., Linow, S., and Dierking, W.: Reliability Measures for Sea Ice
Motion Retrieval From Synthetic Aperture Radar Images, IEEE J.
Sel. Top. Appl., 8, 67–75,
https://doi.org/10.1109/jstars.2014.2340572, 2015. a
Hopkins, M. A.: Four stages of pressure ridging, J. Geophys.
Res.-Oceans, 103, 21883–21891, https://doi.org/10.1029/98jc01257, 1998. a, b
Hopkins, M. A., Hibler, W. D., and Flato, G. M.: On the numerical simulation of
the sea ice ridging process, J. Geophys. Res., 96, 4809,
https://doi.org/10.1029/90jc02375, 1991. a
Hopkins, M. A., Tuhkuri, J., and Lensu, M.: Rafting and ridging of thin ice
sheets, J. Geophys. Res.-Oceans, 104, 13605–13613,
https://doi.org/10.1029/1999jc900031, 1999. a, b
Høyland, K. V.: Morphology and small-scale strength of ridges in the
North-western Barents Sea, Cold Reg. Sci. Technol., 48, 169–187,
https://doi.org/10.1016/j.coldregions.2007.01.006, 2007. a
Hutchings, J. K. and Hibler, W. D.: Small-scale sea ice deformation in the
Beaufort Sea seasonal ice zone, J. Geophys. Res., 113, C08032,
https://doi.org/10.1029/2006JC003971, 2008. a
Itkin, P., Spreen, G., Hvidegaard, S. M., Skourup, H., Wilkinson, J., Gerland,
S., and Granskog, M. A.: Contribution of Deformation to Sea Ice Mass Balance:
A Case Study From an N-ICE2015 Storm, Geophys. Res. Lett., 45,
789–796, https://doi.org/10.1002/2017gl076056, 2018. a, b, c, d, e, f, g, h, i, j
Kharitonov, V. V.: Ice ridges in the Shokalsky Strait, the Severnaya Zemlya
Archipelago, Earth's Cryosphere, XXIII,
https://doi.org/10.21782/ec2541-9994-2019-3(43-50), 2019a. a
Kharitonov, V. V.: Ice ridges in landfast ice of Shokal'skogo
Strait, Geography, Environment, Sustainability, 12, 16–26,
https://doi.org/10.24057/2071-9388-2019-43, 2019b. a
Kharitonov, V. V. and Borodkin, V. A.: On the results of studying ice ridges in
the Shokal'skogo Strait, part I: Morphology and physical
parameters in-situ, Cold Reg. Sci. Technol., 174, 103041,
https://doi.org/10.1016/j.coldregions.2020.103041, 2020. a
King, J., Howell, S., Derksen, C., Rutter, N., Toose, P., Beckers, J. F., Haas,
C., Kurtz, N., and Richter-Menge, J.: Evaluation of Operation IceBridge
quick-look snow depth estimates on sea ice, Geophys. Res. Lett., 42,
9302–9310, https://doi.org/10.1002/2015gl066389, 2015. a
Kirillov, S., Dmitrenko, I., Rysgaard, S., Babb, D., Toudal Pedersen, L., Ehn, J., Bendtsen, J., and Barber, D.: Storm-induced water dynamics and thermohaline structure at the tidewater Flade Isblink Glacier outlet to the Wandel Sea (NE Greenland), Ocean Sci., 13, 947–959, https://doi.org/10.5194/os-13-947-2017, 2017. a
Kwok, R.: Seasonal ice area and volume production of the Arctic Ocean: November
1996 through April 1997, J. Geophys. Res., 107, 8038,
https://doi.org/10.1029/2000JC000469, 2002. a, b
Kwok, R.: Sea ice convergence along the Arctic coasts of Greenland and the
Canadian Arctic Archipelago: Variability and extremes (1992–2014),
Geophys. Res. Lett., 42, 7598–7605, https://doi.org/10.1002/2015gl065462,
2015. a, b
Kwok, R.: Arctic sea ice thickness, volume, and multiyear ice coverage: losses
and coupled variability (1958–2018), Enviro. Res.
Lett., 13, 105005, https://doi.org/10.1088/1748-9326/aae3ec, 2018. a
Kwok, R., Cunningham, G. F., and Hibler, W. D.: Sub-daily sea ice motion and
deformation from RADARSAT observations, Geophys. Res. Lett., 30,
2218, https://doi.org/10.1029/2003gl018723, 2003. a, b
Kwok, R., Hunke, E. C., Maslowski, W., Menemenlis, D., and Zhang, J.:
Variability of sea ice simulations assessed with RGPS kinematics, J.
Geophys. Res., 113, C11012, https://doi.org/10.1029/2008jc004783, 2008. a
Lavergne, T., Eastwood, S., Teffah, Z., Schyberg, H., and Breivik, L.-A.: Sea
ice motion from low-resolution satellite sensors: An alternative method and
its validation in the Arctic, J. Geophys. Res., 115, C10032,
https://doi.org/10.1029/2009jc005958, 2010. a
Lindsay, R. and Schweiger, A.: Arctic sea ice thickness loss determined using subsurface, aircraft, and satellite observations, The Cryosphere, 9, 269–283, https://doi.org/10.5194/tc-9-269-2015, 2015. a
Lindsay, R. W. and Stern, H. L.: The RADARSAT Geophysical Processor System: Quality of Sea Ice Trajectory and Deformation Estimates, J. Atmos.
Ocean. Tech., 20, 1333–1347,
https://doi.org/10.1175/1520-0426(2003)020<1333:TRGPSQ>2.0.CO;2, 2003. a
Losch, M., Menemenlis, D., Campin, J.-M., Heimbach, P., and Hill, C.: On the
formulation of sea-ice models. Part 1: Effects of different solver
implementations and parameterizations, Ocean Modelling, 33, 129–144,
https://doi.org/10.1016/j.ocemod.2009.12.008, 2010. a
Ludwig, V., Spreen, G., Haas, C., Istomina, L., Kauker, F., and Murashkin, D.: The 2018 North Greenland polynya observed by a newly introduced merged optical and passive microwave sea-ice concentration dataset, The Cryosphere, 13, 2051–2073, https://doi.org/10.5194/tc-13-2051-2019, 2019. a, b, c, d, e
Maykut, G. A.: The Surface Heat and Mass Balance, Springer US,
Boston, MA, 395–463, https://doi.org/10.1007/978-1-4899-5352-0_6, 1986. a, b
Menemenlis, D., Hill, C., Adcrocft, A., Campin, J.-M., Cheng, B., Ciotti, B.,
Fukumori, I., Heimbach, P., Henze, C., Köhl, A., Lee, T., Stammer, D., Taft,
J., and Zhang, J.: NASA supercomputer improves prospects for ocean climate
research, Eos, Transactions American Geophysical Union, 86, 89–96,
https://doi.org/10.1029/2005eo090002, 2005. a
Moore, G. W. K., Schweiger, A., Zhang, J., and Steele, M.: What Caused the
Remarkable February 2018 North Greenland Polynya?, Geophys. Res.
Lett., 45, 13342–13350, https://doi.org/10.1029/2018gl080902, 2018. a, b, c, d
Nghiem, S. V., Rigor, I. G., Perovich, D. K., Clemente-Colón, P.,
Weatherly, J. W., and Neumann, G.: Rapid reduction of Arctic perennial sea
ice, Geophys. Res. Lett., 34, L19504, https://doi.org/10.1029/2007gl031138, 2007. a
Operation Icebridge: IceBridge Sea Ice Freeboard, Snow Depth, and Thickness Quick Look, Version 1. [22 March 2018], https://doi.org/10.5067/GRIXZ91DE0L9 (last access: 20 November 2019), 2016, updated 2019.
Pfaffling, A., Haas, C., and Reid, J. E.: Direct helicopter EM –
Sea-ice thickness inversion assessed with synthetic and field data,
Geophysics, 72, F127–F137, https://doi.org/10.1190/1.2732551, 2007. a, b
Rabenstein, L., Hendricks, S., Martin, T., Pfaffhuber, A., and Haas, C.:
Thickness and surface-properties of different sea-ice regimes within the
Arctic Trans Polar Drift: Data from summers 2001, 2004 and 2007, J.
Geophys. Res., 115, C12059, https://doi.org/10.1029/2009jc005846, 2010. a, b, c, d
Rampal, P., Weiss, J., and Marsan, D.: Positive trend in the mean speed and
deformation rate of Arctic sea ice, 1979–2007, J.
Geophys. Res., 114, C05013, https://doi.org/10.1029/2008jc005066, 2009. a, b, c, d
Rohde, J., Herber, A., Hendricks, S., and Haas, C.: Snow and ice thickness from airborne electromagnetic (EM) induction sounding over polynya event and surrounding multi-year ice off the North Coast of Greenland in March 2018, 2018-03-30, PANGAEA [data set], https://doi.org/10.1594/PANGAEA.927445, 2021a. a
Rohde, J., Herber, A., Hendricks, S., and Haas, C.: Snow and ice thickness from airborne electromagnetic (EM) induction sounding over polynya event and surrounding multi-year ice off the North Coast of Greenland in March 2018, 2018-03-31, PANGAEA [data set], https://doi.org/10.1594/PANGAEA.927448, 2021b. a
Semtner, A. J.: A Model for the Thermodynamic Growth of Sea Ice in Numerical
Investigations of Climate, J. Phys. Oceanogr., 6, 379–389,
https://doi.org/10.1175/1520-0485(1976)006<0379:amfttg>2.0.co;2, 1976. a
SNAP: ESA Sentinel Application Platform v8.0, http://step.esa.int, last access: 19 September 2020. a
Spreen, G., Kwok, R., and Menemenlis, D.: Trends in Arctic sea ice drift and
role of wind forcing: 1992–2009, Geophys. Res. Lett., 38, L19501,
https://doi.org/10.1029/2011gl048970, 2011. a
Stern, H. L., Rothrock, D. A., and Kwok, R.: Open water production in Arctic
sea ice: Satellite measurements and model parameterizations, J.
Geophys. Res., 100, 20601, https://doi.org/10.1029/95jc02306, 1995. a
Strub-Klein, L. and Sudom, D.: A comprehensive analysis of the morphology of
first-year sea ice ridges, Cold Reg. Sci. Technol., 82, 94–109,
https://doi.org/10.1016/j.coldregions.2012.05.014, 2012. a, b
Thomas, M., Geiger, C., and Kambhamettu, C.: High resolution (400 m) motion
characterization of sea ice using ERS-1 SAR imagery, Cold Reg. Sci.
Technol., 52, 207–223, https://doi.org/10.1016/j.coldregions.2007.06.006, 2008. a
Thomas, M., Kambhamettu, C., and Geiger, C. A.: Motion Tracking of
Discontinuous Sea Ice, IEEE T. Geosci. Remote S.,
49, 5064–5079, https://doi.org/10.1109/tgrs.2011.2158005, 2011. a
Thorndike, A. S.: Estimates of sea ice thickness distribution using
observations and theory, J. Geophys. Res., 97, 12601,
https://doi.org/10.1029/92jc01199, 1992. a, b, c
Tschudi, M., Meier, W. N., Stewart, J. S., Fowler, C., and Maslanik, J.: Polar Pathfinder Daily 25 km EASE-Grid Sea Ice Motion Vectors, Version 4.1. Boulder, Colorado USA, NASA National Snow and Ice Data Center Distributed Active Archive Center, https://doi.org/10.5067/INAWUWO7QH7B (last access: 30 July 2020), 2019.
Ungermann, M. and Losch, M.: An Observationally Based Evaluation of Subgrid
Scale Ice Thickness Distributions Simulated in a Large-Scale Sea Ice-Ocean
Model of the Arctic Ocean, J. Geophys. Res.-Oceans, 123,
8052–8067, https://doi.org/10.1029/2018jc014022, 2018.
a, b
von Albedyll, L., Haas, C., and Dierking, W.: High resolution sea ice drift and deformation off the North Coast of Greenland in March 2018, PANGAEA [data set], https://doi.org/10.1594/PANGAEA.927451, 2021. a
Vihma, T.: Effects of Arctic Sea Ice Decline on Weather and Climate: A Review,
Surv. Geophys., 35, 1175–1214, https://doi.org/10.1007/s10712-014-9284-0, 2014. a
Vinje, T., Nordlund, N., and Kvambekk, Å.: Monitoring ice thickness in Fram
Strait, J. Geophys. Res.-Oceans, 103, 10437–10449,
https://doi.org/10.1029/97jc03360, 1998. a
Wadhams, P.: Sea Ice Thickness Changes and Their Relation to Climate, in: The
Polar Oceans and Their Role in Shaping the Global Environment,
American Geophysical Union, 337–361, https://doi.org/10.1029/GM085p0337, 1994. a, b
Wadhams, P. and Horne, R. J.: An Analysis Of Ice Profiles Obtained By Submarine
Sonar In The Beaufort Sea, J. Glaciol., 25, 401–424,
https://doi.org/10.3189/s0022143000015264, 1980. a
Warren, S. G., Rigor, I. G., Untersteiner, N., Radionov, V. F., Bryazgin,
N. N., Aleksandrov, Y. I., and Colony, R.: Snow Depth on Arctic Sea Ice,
J. Climate, 12, 1814–1829,
https://doi.org/10.1175/1520-0442(1999)012<1814:sdoasi>2.0.co;2, 1999. a
Short summary
Convergent sea ice motion produces a thick ice cover through ridging. We studied sea ice deformation derived from high-resolution satellite imagery and related it to the corresponding thickness change. We found that deformation explains the observed dynamic thickness change. We show that deformation can be used to model realistic ice thickness distributions. Our results revealed new relationships between thickness redistribution and deformation that could improve sea ice models.
Convergent sea ice motion produces a thick ice cover through ridging. We studied sea ice...
