Articles | Volume 18, issue 12
https://doi.org/10.5194/tc-18-5769-2024
© Author(s) 2024. 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-18-5769-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
11 Dec 2024
Research article |
| 11 Dec 2024
| 11 Dec 2024
Dual-frequency radar observations of snowmelt processes on Antarctic perennial sea ice by CFOSCAT and ASCAT
Rui Xu
School of Atmospheric Sciences, Sun Yat-sen University, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), 519082 Zhuhai, China
Chaofang Zhao
CORRESPONDING AUTHOR
College of Marine Technology, Ocean University of China, 266100 Qingdao, China
Laoshan Laboratory, 266237 Qingdao, China
Stefanie Arndt
Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung, 27570 Bremerhaven, Germany
Institute of Oceanography, University of Hamburg, 20146 Hamburg, Germany
Christian Haas
Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung, 27570 Bremerhaven, Germany
Institute of Environmental Physics, University of Bremen, 28359 Bremen, Germany
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Lu Zhou, Julienne Stroeve, Vishnu Nandan, Rosemary Willatt, Shiming Xu, Weixin Zhu, Sahra Kacimi, Stefanie Arndt, and Zifan Yang
The Cryosphere, 18, 4399–4434, https://doi.org/10.5194/tc-18-4399-2024, https://doi.org/10.5194/tc-18-4399-2024, 2024
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Snow over Antarctic sea ice, influenced by highly variable meteorological conditions and heavy snowfall, has a complex stratigraphy and profound impact on the microwave signature. We employ advanced radiation transfer models to analyse the effects of complex snow properties on brightness temperatures over the sea ice in the Southern Ocean. Great potential lies in the understanding of snow processes and the application to satellite retrievals.
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.
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.
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.
Moein Mellat, Amy R. Macfarlane, Camilla F. Brunello, Martin Werner, Martin Schneebeli, Ruzica Dadic, Stefanie Arndt, Kaisa-Riikka Mustonen, Jeffrey M. Welker, and Hanno Meyer
EGUsphere, https://doi.org/10.5194/egusphere-2024-719, https://doi.org/10.5194/egusphere-2024-719, 2024
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Our research, utilizing data from the Arctic MOSAiC expedition, reveals how snow on Arctic sea ice changes due to weather conditions. By analyzing snow samples collected over a year, we found differences in snow layers that tell us about their origins and how they've been affected by the environment. We discovered variations in snow and vapour that reflect the influence of weather patterns and surface processes like wind and sublimation.
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.
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.
David N. Wagner, Matthew D. Shupe, Christopher Cox, Ola G. Persson, Taneil Uttal, Markus M. Frey, Amélie Kirchgaessner, Martin Schneebeli, Matthias Jaggi, Amy R. Macfarlane, Polona Itkin, Stefanie Arndt, Stefan Hendricks, Daniela Krampe, Marcel Nicolaus, Robert Ricker, Julia Regnery, Nikolai Kolabutin, Egor Shimanshuck, Marc Oggier, Ian Raphael, Julienne Stroeve, and Michael Lehning
The Cryosphere, 16, 2373–2402, https://doi.org/10.5194/tc-16-2373-2022, https://doi.org/10.5194/tc-16-2373-2022, 2022
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Based on measurements of the snow cover over sea ice and atmospheric measurements, we estimate snowfall and snow accumulation for the MOSAiC ice floe, between November 2019 and May 2020. For this period, we estimate 98–114 mm of precipitation. We suggest that about 34 mm of snow water equivalent accumulated until the end of April 2020 and that at least about 50 % of the precipitated snow was eroded or sublimated. Further, we suggest explanations for potential snowfall overestimation.
Klaus Dethloff, Wieslaw Maslowski, Stefan Hendricks, Younjoo J. Lee, Helge F. Goessling, Thomas Krumpen, Christian Haas, Dörthe Handorf, Robert Ricker, Vladimir Bessonov, John J. Cassano, Jaclyn Clement Kinney, Robert Osinski, Markus Rex, Annette Rinke, Julia Sokolova, and Anja Sommerfeld
The Cryosphere, 16, 981–1005, https://doi.org/10.5194/tc-16-981-2022, https://doi.org/10.5194/tc-16-981-2022, 2022
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Sea ice thickness anomalies during the MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) winter in January, February and March 2020 were simulated with the coupled Regional Arctic climate System Model (RASM) and compared with CryoSat-2/SMOS satellite data. Hindcast and ensemble simulations indicate that the sea ice anomalies are driven by nonlinear interactions between ice growth processes and wind-driven sea-ice transports, with dynamics playing a dominant role.
Arttu Jutila, Stefan Hendricks, Robert Ricker, Luisa von Albedyll, Thomas Krumpen, and Christian Haas
The Cryosphere, 16, 259–275, https://doi.org/10.5194/tc-16-259-2022, https://doi.org/10.5194/tc-16-259-2022, 2022
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Sea-ice thickness retrieval from satellite altimeters relies on assumed sea-ice density values because density cannot be measured from space. We derived bulk densities for different ice types using airborne laser, radar, and electromagnetic induction sounding measurements. Compared to previous studies, we found high bulk density values due to ice deformation and younger ice cover. Using sea-ice freeboard, we derived a sea-ice bulk density parameterisation that can be applied to satellite data.
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.
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
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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
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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
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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.
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
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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.
Luisa von Albedyll, Christian Haas, and Wolfgang Dierking
The Cryosphere, 15, 2167–2186, https://doi.org/10.5194/tc-15-2167-2021, https://doi.org/10.5194/tc-15-2167-2021, 2021
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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.
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
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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
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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
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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.
Stefanie Arndt, Mario Hoppmann, Holger Schmithüsen, Alexander D. Fraser, and Marcel Nicolaus
The Cryosphere, 14, 2775–2793, https://doi.org/10.5194/tc-14-2775-2020, https://doi.org/10.5194/tc-14-2775-2020, 2020
H. Jakob Belter, Thomas Krumpen, Stefan Hendricks, Jens Hoelemann, Markus A. Janout, Robert Ricker, and Christian Haas
The Cryosphere, 14, 2189–2203, https://doi.org/10.5194/tc-14-2189-2020, https://doi.org/10.5194/tc-14-2189-2020, 2020
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The validation of satellite sea ice thickness (SIT) climate data records with newly acquired moored sonar SIT data shows that satellite products provide modal rather than mean SIT in the Laptev Sea region. This tendency of satellite-based SIT products to underestimate mean SIT needs to be considered for investigations of sea ice volume transports. Validation of satellite SIT in the first-year-ice-dominated Laptev Sea will support algorithm development for more reliable SIT records in the Arctic.
Thomas Krumpen, Florent Birrien, Frank Kauker, Thomas Rackow, Luisa von Albedyll, Michael Angelopoulos, H. Jakob Belter, Vladimir Bessonov, Ellen Damm, Klaus Dethloff, Jari Haapala, Christian Haas, Carolynn Harris, Stefan Hendricks, Jens Hoelemann, Mario Hoppmann, Lars Kaleschke, Michael Karcher, Nikolai Kolabutin, Ruibo Lei, Josefine Lenz, Anne Morgenstern, Marcel Nicolaus, Uwe Nixdorf, Tomash Petrovsky, Benjamin Rabe, Lasse Rabenstein, Markus Rex, Robert Ricker, Jan Rohde, Egor Shimanchuk, Suman Singha, Vasily Smolyanitsky, Vladimir Sokolov, Tim Stanton, Anna Timofeeva, Michel Tsamados, and Daniel Watkins
The Cryosphere, 14, 2173–2187, https://doi.org/10.5194/tc-14-2173-2020, https://doi.org/10.5194/tc-14-2173-2020, 2020
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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.
Maria-Elena Vorrath, Juliane Müller, Oliver Esper, Gesine Mollenhauer, Christian Haas, Enno Schefuß, and Kirsten Fahl
Biogeosciences, 16, 2961–2981, https://doi.org/10.5194/bg-16-2961-2019, https://doi.org/10.5194/bg-16-2961-2019, 2019
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The study highlights new approaches in the investigation of past sea ice in Antarctica to reconstruct the climate conditions in earth's history and reveal its future development under global warming. We examined the distribution of organic remains from different algae at the Western Antarctic Peninsula and compared it to fossil and satellite records. We evaluated IPSO25 – the sea ice proxy for the Southern Ocean with 25 carbon atoms – as a useful tool for sea ice reconstructions in this region.
Valentin Ludwig, Gunnar Spreen, Christian Haas, Larysa Istomina, Frank Kauker, and Dmitrii Murashkin
The Cryosphere, 13, 2051–2073, https://doi.org/10.5194/tc-13-2051-2019, https://doi.org/10.5194/tc-13-2051-2019, 2019
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Sea-ice concentration, the fraction of an area covered by sea ice, can be observed from satellites with different methods. We combine two methods to obtain a product which is better than either of the input measurements alone. The benefit of our product is demonstrated by observing the formation of an open water area which can now be observed with more detail. Additionally, we find that the open water area formed because the sea ice drifted in the opposite direction and faster than usual.
Stefanie Arndt and Christian Haas
The Cryosphere, 13, 1943–1958, https://doi.org/10.5194/tc-13-1943-2019, https://doi.org/10.5194/tc-13-1943-2019, 2019
Iina Ronkainen, Jonni Lehtiranta, Mikko Lensu, Eero Rinne, Jari Haapala, and Christian Haas
The Cryosphere, 12, 3459–3476, https://doi.org/10.5194/tc-12-3459-2018, https://doi.org/10.5194/tc-12-3459-2018, 2018
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We quantify the sea ice thickness variability in the Bay of Bothnia using various observational data sets. For the first time we use helicopter and shipborne electromagnetic soundings to study changes in drift ice of the Bay of Bothnia. Our results show that the interannual variability of ice thickness is larger in the drift ice zone than in the fast ice zone. Furthermore, the mean thickness of heavily ridged ice near the coast can be several times larger than that of fast ice.
Paul J. Kushner, Lawrence R. Mudryk, William Merryfield, Jaison T. Ambadan, Aaron Berg, Adéline Bichet, Ross Brown, Chris Derksen, Stephen J. Déry, Arlan Dirkson, Greg Flato, Christopher G. Fletcher, John C. Fyfe, Nathan Gillett, Christian Haas, Stephen Howell, Frédéric Laliberté, Kelly McCusker, Michael Sigmond, Reinel Sospedra-Alfonso, Neil F. Tandon, Chad Thackeray, Bruno Tremblay, and Francis W. Zwiers
The Cryosphere, 12, 1137–1156, https://doi.org/10.5194/tc-12-1137-2018, https://doi.org/10.5194/tc-12-1137-2018, 2018
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Here, the Canadian research network CanSISE uses state-of-the-art observations of snow and sea ice to assess how Canada's climate model and climate prediction systems capture variability in snow, sea ice, and related climate parameters. We find that the system performs well, accounting for observational uncertainty (especially for snow), model uncertainty, and chaotic climate variability. Even for variables like sea ice, where improvement is needed, useful prediction tools can be developed.
Robert Ricker, Stefan Hendricks, Lars Kaleschke, Xiangshan Tian-Kunze, Jennifer King, and Christian Haas
The Cryosphere, 11, 1607–1623, https://doi.org/10.5194/tc-11-1607-2017, https://doi.org/10.5194/tc-11-1607-2017, 2017
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We developed the first merging of CryoSat-2 and SMOS sea-ice thickness retrievals. ESA’s Earth Explorer SMOS satellite can detect thin sea ice, whereas its companion CryoSat-2, designed to observe thicker perennial sea ice, lacks sensitivity. Using these satellite missions together completes the picture of the changing Arctic sea ice and provides a more accurate and comprehensive view on the actual state of Arctic sea-ice thickness.
T. Krumpen, R. Gerdes, C. Haas, S. Hendricks, A. Herber, V. Selyuzhenok, L. Smedsrud, and G. Spreen
The Cryosphere, 10, 523–534, https://doi.org/10.5194/tc-10-523-2016, https://doi.org/10.5194/tc-10-523-2016, 2016
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We present an extensive data set of ground-based and airborne electromagnetic ice thickness measurements covering Fram Strait in summer between 2001 and 2012. An investigation of back trajectories of surveyed sea ice using satellite-based sea ice motion data allows us to examine the connection between thickness variability, ice age and source area. In addition, we determine across and along strait gradients in ice thickness and associated volume fluxes.
S. Arndt and M. Nicolaus
The Cryosphere, 8, 2219–2233, https://doi.org/10.5194/tc-8-2219-2014, https://doi.org/10.5194/tc-8-2219-2014, 2014
D. Price, W. Rack, P. J. Langhorne, C. Haas, G. Leonard, and K. Barnsdale
The Cryosphere, 8, 1031–1039, https://doi.org/10.5194/tc-8-1031-2014, https://doi.org/10.5194/tc-8-1031-2014, 2014
S. Willmes, M. Nicolaus, and C. Haas
The Cryosphere, 8, 891–904, https://doi.org/10.5194/tc-8-891-2014, https://doi.org/10.5194/tc-8-891-2014, 2014
L. Rabenstein, T. Krumpen, S. Hendricks, C. Koeberle, C. Haas, and J. A. Hoelemann
The Cryosphere, 7, 947–959, https://doi.org/10.5194/tc-7-947-2013, https://doi.org/10.5194/tc-7-947-2013, 2013
Related subject area
Discipline: Snow | Subject: Antarctic
Contribution of blowing-snow sublimation to the surface mass balance of Antarctica
A decade (2008–2017) of water stable isotope composition of precipitation at Concordia Station, East Antarctica
Extreme precipitation associated with atmospheric rivers over West Antarctic ice shelves: insights from kilometre-scale regional climate modelling
Firn air content changes on Antarctic ice shelves under three future warming scenarios
Surface processes and drivers of the snow water stable isotopic composition at Dome C, East Antarctica – a multi-datasets and modelling analysis
Extreme events of snow grain size increase in East Antarctica and their relationship with meteorological conditions
Local spatial variability in the occurrence of summer precipitation in the Sør Rondane Mountains, Antarctica
Characteristics of the 1979–2020 Antarctic firn layer simulated with IMAU-FDM v1.2A
The sensitivity of satellite microwave observations to liquid water in the Antarctic snowpack
Spectral characterization, radiative forcing and pigment content of coastal Antarctic snow algae: approaches to spectrally discriminate red and green communities and their impact on snowmelt
Distinguishing the impacts of ozone and ozone-depleting substances on the recent increase in Antarctic surface mass balance
Representative surface snow density on the East Antarctic Plateau
Brief communication: Evaluating Antarctic precipitation in ERA5 and CMIP6 against CloudSat observations
Drifting-snow statistics from multiple-year autonomous measurements in Adélie Land, East Antarctica
Impact of exhaust emissions on chemical snowpack composition at Concordia Station, Antarctica
Observation of the process of snow accumulation on the Antarctic Plateau by time lapse laser scanning
Evaluation of CloudSat snowfall rate profiles by a comparison with in situ micro-rain radar observations in East Antarctica
Investigation of a wind-packing event in Queen Maud Land, Antarctica
Archival processes of the water stable isotope signal in East Antarctic ice cores
Srinidhi Gadde and Willem Jan van de Berg
The Cryosphere, 18, 4933–4953, https://doi.org/10.5194/tc-18-4933-2024, https://doi.org/10.5194/tc-18-4933-2024, 2024
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Blowing-snow sublimation is the major loss term in the mass balance of Antarctica. In this study we update the blowing-snow representation in the Regional Atmospheric Climate Model (RACMO). With the updates, results compare well with observations from East Antarctica. Also, the continent-wide variation of blowing snow compares well with satellite observations. Hence, the updates provide a clear step forward in producing a physically sound and reliable estimate of the mass balance of Antarctica.
Giuliano Dreossi, Mauro Masiol, Barbara Stenni, Daniele Zannoni, Claudio Scarchilli, Virginia Ciardini, Mathieu Casado, Amaëlle Landais, Martin Werner, Alexandre Cauquoin, Giampietro Casasanta, Massimo Del Guasta, Vittoria Posocco, and Carlo Barbante
The Cryosphere, 18, 3911–3931, https://doi.org/10.5194/tc-18-3911-2024, https://doi.org/10.5194/tc-18-3911-2024, 2024
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Oxygen and hydrogen stable isotopes have been extensively used to reconstruct past temperatures, with precipitation representing the input signal of the isotopic records in ice cores. We present a 10-year record of stable isotopes in daily precipitation at Concordia Station: this is the longest record for inland Antarctica and represents a benchmark for quantifying post-depositional processes and improving the paleoclimate interpretation of ice cores.
Ella Gilbert, Denis Pishniak, José Abraham Torres, Andrew Orr, Michelle Maclennan, Nander Wever, and Kristiina Verro
EGUsphere, https://doi.org/10.5194/egusphere-2024-2111, https://doi.org/10.5194/egusphere-2024-2111, 2024
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We use 3 sophisticated climate models to examine extreme precipitation in a critical region of West Antarctica. We found that rainfall probably occurred during the two cases we examined, and that it was generated by the interaction of air with steep topography. Our results show that kilometre scale models are useful tools for exploring extreme precipitation in this region, and that more observations of rainfall are needed.
Sanne B. M. Veldhuijsen, Willem Jan van de Berg, Peter Kuipers Munneke, and Michiel R. van den Broeke
The Cryosphere, 18, 1983–1999, https://doi.org/10.5194/tc-18-1983-2024, https://doi.org/10.5194/tc-18-1983-2024, 2024
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We use the IMAU firn densification model to simulate the 21st-century evolution of Antarctic firn air content. Ice shelves on the Antarctic Peninsula and the Roi Baudouin Ice Shelf in Dronning Maud Land are particularly vulnerable to total firn air content (FAC) depletion. Our results also underline the potentially large vulnerability of low-accumulation ice shelves to firn air depletion through ice slab formation.
Inès Ollivier, Hans Christian Steen-Larsen, Barbara Stenni, Laurent Arnaud, Mathieu Casado, Alexandre Cauquoin, Giuliano Dreossi, Christophe Genthon, Bénédicte Minster, Ghislain Picard, Martin Werner, and Amaëlle Landais
EGUsphere, https://doi.org/10.5194/egusphere-2024-685, https://doi.org/10.5194/egusphere-2024-685, 2024
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The role of post-depositional processes taking place at the ice sheet's surface on the water stable isotope signal measured in polar ice cores is not fully understood. Using field observations and modelling results, we show that the original precipitation isotopic signal at Dome C, East Antarctica, is modified by post-depositional processes and provide the first quantitative estimation of their mean impact on the isotopic signal observed in the snow.
Claudio Stefanini, Giovanni Macelloni, Marion Leduc-Leballeur, Vincent Favier, Benjamin Pohl, and Ghislain Picard
The Cryosphere, 18, 593–608, https://doi.org/10.5194/tc-18-593-2024, https://doi.org/10.5194/tc-18-593-2024, 2024
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Local and large-scale meteorological conditions have been considered in order to explain some peculiar changes of snow grains on the East Antarctic Plateau from 2000 to 2022, by using remote sensing observations and reanalysis. We identified some extreme grain size events on the highest ice divide, resulting from a combination of conditions of low wind speed and low temperature. Moreover, the beginning of seasonal grain growth has been linked to the occurrence of atmospheric rivers.
Alfonso Ferrone, Étienne Vignon, Andrea Zonato, and Alexis Berne
The Cryosphere, 17, 4937–4956, https://doi.org/10.5194/tc-17-4937-2023, https://doi.org/10.5194/tc-17-4937-2023, 2023
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In austral summer 2019/2020, three K-band Doppler profilers were deployed across the Sør Rondane Mountains, south of the Belgian base Princess Elisabeth Antarctica. Their measurements, along with atmospheric simulations and reanalyses, have been used to study the spatial variability in precipitation over the region, as well as investigate the interaction between the complex terrain and the typical flow associated with precipitating systems.
Sanne B. M. Veldhuijsen, Willem Jan van de Berg, Max Brils, Peter Kuipers Munneke, and Michiel R. van den Broeke
The Cryosphere, 17, 1675–1696, https://doi.org/10.5194/tc-17-1675-2023, https://doi.org/10.5194/tc-17-1675-2023, 2023
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Firn is the transition of snow to glacier ice and covers 99 % of the Antarctic ice sheet. Knowledge about the firn layer and its variability is important, as it impacts satellite-based estimates of ice sheet mass change. Also, firn contains pores in which nearly all of the surface melt is retained. Here, we improve a semi-empirical firn model and simulate the firn characteristics for the period 1979–2020. We evaluate the performance with field and satellite measures and test its sensitivity.
Ghislain Picard, Marion Leduc-Leballeur, Alison F. Banwell, Ludovic Brucker, and Giovanni Macelloni
The Cryosphere, 16, 5061–5083, https://doi.org/10.5194/tc-16-5061-2022, https://doi.org/10.5194/tc-16-5061-2022, 2022
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Using a snowpack radiative transfer model, we investigate in which conditions meltwater can be detected from passive microwave satellite observations from 1.4 to 37 GHz. In particular, we determine the minimum detectable liquid water content, the maximum depth of detection of a buried wet snow layer and the risk of false alarm due to supraglacial lakes. These results provide information for the developers of new, more advanced satellite melt products and for the users of the existing products.
Alia L. Khan, Heidi M. Dierssen, Ted A. Scambos, Juan Höfer, and Raul R. Cordero
The Cryosphere, 15, 133–148, https://doi.org/10.5194/tc-15-133-2021, https://doi.org/10.5194/tc-15-133-2021, 2021
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We present radiative forcing (RF) estimates by snow algae in the Antarctic Peninsula (AP) region from multi-year measurements of solar radiation and ground-based hyperspectral characterization of red and green snow algae collected during a brief field expedition in austral summer 2018. Mean daily RF was double for green (~26 W m−2) vs. red (~13 W m−2) snow algae during the peak growing season, which is on par with midlatitude dust attributions capable of advancing snowmelt.
Rei Chemke, Michael Previdi, Mark R. England, and Lorenzo M. Polvani
The Cryosphere, 14, 4135–4144, https://doi.org/10.5194/tc-14-4135-2020, https://doi.org/10.5194/tc-14-4135-2020, 2020
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The increase in Antarctic surface mass balance (SMB, precipitation vs. evaporation/sublimation) is projected to mitigate sea-level rise. Here we show that nearly half of this increase over the 20th century is attributed to stratospheric ozone depletion and ozone-depleting substance (ODS) emissions. Our results suggest that the phaseout of ODS by the Montreal Protocol, and the recovery of stratospheric ozone, will act to decrease the SMB over the 21st century and the mitigation of sea-level rise.
Alexander H. Weinhart, Johannes Freitag, Maria Hörhold, Sepp Kipfstuhl, and Olaf Eisen
The Cryosphere, 14, 3663–3685, https://doi.org/10.5194/tc-14-3663-2020, https://doi.org/10.5194/tc-14-3663-2020, 2020
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From 1 m snow profiles along a traverse on the East Antarctic Plateau, we calculated a representative surface snow density of 355 kg m−3 for this region with an error less than 1.5 %.
This density is 10 % higher and density fluctuations seem to happen on smaller scales than climate model outputs suggest. Our study can help improve the parameterization of surface snow density in climate models to reduce the error in future sea level predictions.
Marie-Laure Roussel, Florentin Lemonnier, Christophe Genthon, and Gerhard Krinner
The Cryosphere, 14, 2715–2727, https://doi.org/10.5194/tc-14-2715-2020, https://doi.org/10.5194/tc-14-2715-2020, 2020
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The Antarctic precipitation is evaluated against space radar data in the most recent climate model intercomparison CMIP6 and reanalysis ERA5. The seasonal cycle is mostly well reproduced, but relative errors are higher in areas of complex topography, particularly in the higher-resolution models. At continental and regional scales all results are biased high, with no significant progress in the more recent models. Predicting Antarctic contribution to sea level still requires model improvements.
Charles Amory
The Cryosphere, 14, 1713–1725, https://doi.org/10.5194/tc-14-1713-2020, https://doi.org/10.5194/tc-14-1713-2020, 2020
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This paper presents an assessment of drifting-snow occurrences and snow mass transport from up to 9 years (2010–2018) of half-hourly observational records collected at two remote locations in coastal Adelie Land (East Antarctica) using second-generation IAV Engineering acoustic FlowCapt sensors. The dataset is freely available to the scientific community and can be used to complement satellite products and evaluate snow-transport models close to the surface and at high temporal frequency.
Detlev Helmig, Daniel Liptzin, Jacques Hueber, and Joel Savarino
The Cryosphere, 14, 199–209, https://doi.org/10.5194/tc-14-199-2020, https://doi.org/10.5194/tc-14-199-2020, 2020
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We present 15 months of trace gas observations from air withdrawn within the snowpack and from above the snow at Concordia Station in Antarctica. The data show occasional positive spikes, indicative of pollution from the station generator. The pollution signal can be seen in snowpack air shortly after it is observed above the snow surface, and lasting for up to several days, much longer than above the surface.
Ghislain Picard, Laurent Arnaud, Romain Caneill, Eric Lefebvre, and Maxim Lamare
The Cryosphere, 13, 1983–1999, https://doi.org/10.5194/tc-13-1983-2019, https://doi.org/10.5194/tc-13-1983-2019, 2019
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To study how snow accumulates in Antarctica, we analyze daily surface elevation recorded by an automatic laser scanner. We show that new snow often accumulates in thick patches covering a small fraction of the surface. Most patches are removed by erosion within weeks, implying that only a few contribute to the snowpack. This explains the heterogeneity on the surface and in the snowpack. These findings are important for surface mass and energy balance, photochemistry, and ice core interpretation.
Florentin Lemonnier, Jean-Baptiste Madeleine, Chantal Claud, Christophe Genthon, Claudio Durán-Alarcón, Cyril Palerme, Alexis Berne, Niels Souverijns, Nicole van Lipzig, Irina V. Gorodetskaya, Tristan L'Ecuyer, and Norman Wood
The Cryosphere, 13, 943–954, https://doi.org/10.5194/tc-13-943-2019, https://doi.org/10.5194/tc-13-943-2019, 2019
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Evaluation of the vertical precipitation rate profiles of CloudSat radar by comparison with two surface-based micro-rain radars (MRR) located at two antarctic stations gives a near-perfect correlation between both datasets, even though climatic and geographic conditions are different for the stations. A better understanding and reassessment of CloudSat uncertainties ranging from −13 % up to +22 % confirms the robustness of the CloudSat retrievals of snowfall over Antarctica.
Christian Gabriel Sommer, Nander Wever, Charles Fierz, and Michael Lehning
The Cryosphere, 12, 2923–2939, https://doi.org/10.5194/tc-12-2923-2018, https://doi.org/10.5194/tc-12-2923-2018, 2018
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Wind packing is how wind produces hard crusts at the surface of the snowpack. This is relevant for the local mass balance in polar regions. However, not much is known about this process and it is difficult to capture its high spatial and temporal variability. A wind-packing event was measured in Antarctica. It could be quantified how drifting snow leads to wind packing and generates barchan dunes. The documentation of these deposition dynamics is an important step in understanding polar snow.
Mathieu Casado, Amaelle Landais, Ghislain Picard, Thomas Münch, Thomas Laepple, Barbara Stenni, Giuliano Dreossi, Alexey Ekaykin, Laurent Arnaud, Christophe Genthon, Alexandra Touzeau, Valerie Masson-Delmotte, and Jean Jouzel
The Cryosphere, 12, 1745–1766, https://doi.org/10.5194/tc-12-1745-2018, https://doi.org/10.5194/tc-12-1745-2018, 2018
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Ice core isotopic records rely on the knowledge of the processes involved in the archival processes of the snow. In the East Antarctic Plateau, post-deposition processes strongly affect the signal found in the surface and buried snow compared to the initial climatic signal. We evaluate the different contributions to the surface snow isotopic composition between the precipitation and the exchanges with the atmosphere and the variability of the isotopic signal found in profiles from snow pits.
Cited articles
Andreas, E. L. and Ackley, S. F.: On the differences in ablation seasons of Arctic and Antarctic sea ice, J. Atmos. Sci., 39, 440–447, https://doi.org/10.1175/1520-0469(1982)039<0440:OTDIAS>2.0.CO;2, 1982.
Arndt, S. and Haas, C.: Spatiotemporal variability and decadal trends of snowmelt processes on Antarctic sea ice observed by satellite scatterometers, The Cryosphere, 13, 1943–1958, https://doi.org/10.5194/tc-13-1943-2019, 2019.
Arndt, S., Willmes, S., Dierking, W., and Nicolaus, M.: Timing and regional patterns of snowmelt on Antarctic sea ice from passive microwave satellite observations. J. Geophys. Res.-Oceans, 121, 5916–5930, https://doi.org/10.1002/2015jc011504, 2016.
Arndt, S., Haas, C., Meyer, H., Peeken, I., and Krumpen, T.: Recent observations of superimposed ice and snow ice on sea ice in the northwestern Weddell Sea, The Cryosphere, 15, 4165–4178, https://doi.org/10.5194/tc-15-4165-2021, 2021.
Bozkurt, D., Bromwich, D. H., Carrasco, J., Hines, K. M., Maureira, J. C., and Rondanelli, R.: Recent Near-surface Temperature Trends in the Antarctic Peninsula from Observed, Reanalysis and Regional Climate Model Data, Adv. Atmos. Sci., 37, 477–493, https://doi.org/10.1007/s00376-020-9183-x, 2020.
Colbeck, S. C.: A Review of Sintering in Seasonal Snow, U.S. Army Cold Regions Research and Engineering Laboratory, ISSN 0501-5782, 1997.
Drinkwater, M. R. and Liu, X.: Seasonal to interannual variability in Antarctic sea-ice surface melt, IEEE T. Geosci. Remote, 38, 1827–1842, https://doi.org/10.1109/36.851767, 2000.
Drinkwater, M. R. and Lytle, V. I.: ERS 1 radar and field-observed characteristics of autumn freeze-up in the Weddell Sea, J. Geophys. Res.-Oceans, 102, 12593–12608, https://doi.org/10.1029/97JC00437, 1997.
Forster, R. R., Long, D. G., Jezek, K. C., Drobot, S. D., and Anderson, M. R.: The onset of Arctic sea-ice snowmelt as detected with passive- and active-microwave remote sensing, Ann. Glaciol., 33, 85–93, https://doi.org/10.3189/172756401781818428, 2001.
Gohin, F. and Cavanié, A.: A first try at identification of sea ice using the three beam scatterometer of ERS-1, Int. J. Remote Sens., 15, 1221–1228, https://doi.org/10.1080/01431169408954156, 1994.
Haas, C.: The seasonal cycle of ERS scatterometer signatures over perennial Antarctic sea ice and associated surface ice properties and processes, Ann. Glaciol., 33, 69–73, https://doi.org/10.3189/172756401781818301, 2001.
Haas, C., Nicolaus, M., Willmes, S., Worby, A., and Flinspach, D.: Sea ice and snow thickness and physical properties of an ice floe in the western Weddell Sea and their changes during spring warming, Deep-Sea Res. Pt. II, 55, 963–974, https://doi.org/10.1016/j.dsr2.2007.12.020, 2008.
Haas, C., Thomas, D. N., and Bareiss, J.: Surface properties and processes of perennial Antarctic sea ice in summer, J. Glaciol., 47, 613–625, https://doi.org/10.3189/172756501781831864, 2001.
Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., and Thépaut, J.-N.: ERA5 hourly data on single levels from 1940 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set], https://doi.org/10.24381/cds.adbb2d47, 2023.
Jeffries, M., Veazey, A., Morris, K., and Krouse, H. R.: Depositional environment of the snow cover on West Antarctic pack-ice floes, Ann. Glaciol., 20, 33–38, https://doi.org/10.3189/1994AoG20-1-33-38, 1994.
Jena, B., Bajish, C. C., Turner, J., Ravichandran, M., Anilkumar, N., and Kshitija, S.: Record low sea ice extent in the Weddell Sea, Antarctica in April/May 2019 driven by intense and explosive polar cyclones, Npj Climate Atmos. Sci., 5, 19, https://doi.org/10.1038/s41612-022-00243-9, 2022.
Kawamura, T., Jeffries, M. O., Tison, J.-L., and Krouse, H. R.: Superimposed-ice formation in summer on Ross Sea pack-ice floes, Ann. Glaciol., 39, 563–568, https://doi.org/10.3189/172756404781814168, 2017.
King, J. C., Marshall, G. J., Colwell, S., Arndt, S., Allen-Sader, C., and Phillips, T.: The Performance of the ERA-Interim and ERA5 Atmospheric Reanalyses Over Weddell Sea Pack Ice, J. Geophys. Res.-Oceans, 127, e2022JC018805, https://doi.org/10.1029/2022JC018805, 2022.
Lindsley, R. D. and Long, D. G.: Enhanced-resolution reconstruction of ASCAT backscatter measurements, IEEE T. Geosci. Remote, 54, 2589–2601, https://doi.org/10.1109/TGRS.2015.2503762, 2016.
Liu, J., Lin, W., Dong, X., Lang, S., Yun, R., Zhu, D., Zhang, K., Sun, C., Mu, B., Ma, J., He, Y., Wang, Z., Li, X., Zhao, X., and Jiang, X.: First Results from the Rotating Fan Beam Scatterometer Onboard CFOSAT, IEEE T. Geosci. Remote, 58, 8793–8806, https://doi.org/10.1109/tgrs.2020.2990708, 2020.
Long, D. G., Hardin, P. J., and Whiting, P. T.: Resolution enhancement of spaceborne scatterometer data, IEEE T. Geosci. Remote, 31, 700–715, https://doi.org/10.1109/36.225536, 1993.
Massom, R. A., Eicken, H., Hass, C., Jeffries, M. O., Drinkwater, M. R., Sturm, M., Worby, A. P., Wu, X., Lytle, V. I., Ushio, S., Morris, K., Reid, P. A., Warren, S. G., and Allison, I.: Snow on Antarctic sea ice, Rev. Geophys., 39, 413–445, https://doi.org/10.1029/2000rg000085, 2001.
Meereisportal: Das Meereisportal – Logbuch einer schwindenden Welt, Meereisportal [data set], https://www.meereisportal.de/ (last access: 2 July 2024), 2024.
Mortin, J., Howell, S. E. L., Wang, L., Derksen, C., Svensson, G., Graversen, R. G., and Schrøder, T. M.: Extending the QuikSCAT record of seasonal melt–freeze transitions over Arctic sea ice using ASCAT, Remote Sens. Environ., 141, 214–230, https://doi.org/10.1016/j.rse.2013.11.004, 2014.
Mou, X., Lin, W., and He, Y: Towards a consistent wind data record for the cfosat scatterometer, Remote Sens., 15, 2081, https://doi.org/10.3390/rs15082081, 2023.
Nandan, V., Geldsetzer, T., Mahmud, M., Yackel, J., and Ramjan, S.: Ku-, X- and C-Band Microwave Backscatter Indices from Saline Snow Covers on Arctic First-Year Sea Ice, Remote Sens., 9, 757, https://doi.org/10.3390/rs9070757, 2017.
Nicolaus, M., Haas, C., and Willmes, S.: Evolution of first-year and second-year snow properties on sea ice in the Weddell Sea during spring-summer transition, J. Geophys. Res.-Atmos., 114, D17109, https://doi.org/10.1029/2008JD011227, 2009.
Nicolaus, M., Hoppmann, M., Arndt, S., Hendricks, S., Katlein, C., Nicolaus, A., Rossmann, L., Schiller, M., and Schwegmann, S.: Snow Depth and Air Temperature Seasonality on Sea Ice Derived From Snow Buoy Measurements, Front. Marine Sci., 8, 655446, https://doi.org/10.3389/fmars.2021.655446, 2021.
NSOAS: The National Satellite Ocean Application Service [data set], https://osdds.nsoas.org.cn/, last access: 2 July 2024.
NASA SCP: NASA Scatterometer Climate Record Pathfinder [data set], https://www.scp.byu.edu/, last access: 2 July 2024.
Onstott, R. G. and Shuchman, R. A.: SAR Measurements of Sea Ice, in: Synthetic Aperture Radar Marine User's Manual, edited by: Jackson, C. R. and Apel J. R., 81–115, https://www.sarusersmanual.com/ (last access: 2 July 2024), 2004.
Parkinson, C. L.: A 40-y record reveals gradual Antarctic sea ice increases followed by decreases at rates far exceeding the rates seen in the Arctic, P. Natl. Acad. Sci. USA, 116, 14414–14423, https://doi.org/10.1073/pnas.1906556116, 2019.
Purich, A. and Doddridge, E. W.: Record low Antarctic sea ice coverage indicates a new sea ice state, Commun. Earth Environ., 4, 314, https://doi.org/10.1038/s43247-023-00961-9, 2023.
Remund, Q. P. and Long, D. G.: Sea ice extent mapping using Ku band scatterometer data, J. Geophys. Res., 104, 11515–11527, https://doi.org/10.1029/98JC02373, 1999.
Schroeter, S. and Sandery, P. A.: Large-ensemble analysis of Antarctic sea ice model sensitivity to parameter uncertainty, Ocean Model., 177, 102090, https://doi.org/10.1016/j.ocemod.2022.102090, 2022.
Spreen, G., Kaleschke, L., and Heygster, G.: Sea ice remote sensing using AMSR-E 89-GHz channels, J. Geophys. Res., 113, C02S03, https://doi.org/10.1029/2005JC003384, 2008.
Stammerjohn, S. E., Martinson, D. G., Smith, R. C., Yuan, X., and Rind, D.: Trends in Antarctic annual sea ice retreat and advance and their relation to ENSO and Southern Annular Mode variability, J. Geophys. Res., 113, C03S90, https://doi.org/10.1029/2007JC004269, 2008.
Stroeve, J. C., Markus, T., Boisvert, L., Miller, J., and Barrett, A.: Changes in Arctic melt season and implications for sea ice loss, Geophys. Res. Lett., 41, 1216–1225, https://doi.org/10.1002/2013GL058951, 2014.
Sturdivant, E. J., Frey, K. E., and Urban, F. E.: Snowmelt detection from QuikSCAT and ASCAT satellite radar scatterometer data across the Alaskan North Slope, GIScience & Remote Sensing, 56, 87–108, https://doi.org/10.1080/15481603.2018.1493045, 2018.
Takei, I. and Maeno, N.: The low-frequency conductivity of snow near the melting temperature, Ann. Glaciol., 32, 14–18, https://doi.org/10.3189/172756401781819193, 2001.
Turner, J., Holmes, C., Caton Harrison, T., Phillips, T., Jena, B., Reeves-Francois, T., Ryan F., Elizabeth R. T., and Bajish, C. C.: Record Low Antarctic Sea Ice Cover in February 2022, Geophys. Res. Lett., 49, e2022GL098904, https://doi.org/10.1029/2022GL098904, 2022.
Vihma, T., Johansson, M. M., and Launiainen, J.: Radiative and turbulent surface heat fluxes over sea ice in the western Weddell Sea in early summer, J. Geophys. Res.-Oceans, 114, C04019, https://doi.org/10.1029/2008JC004995, 2009.
Wang, X.-D., Li, X.-W., Wang, C., and Li, X.-G.: Antarctic ice-sheet near-surface snowmelt detection based on the synergy of SSM/I data and QuikSCAT data, Geosci. Front., 9, 955–963, https://doi.org/10.1016/j.gsf.2017.09.007, 2018.
Willmes, S., Bareiss, J., Haas, C., and Marcel N.: The importance of diurnal processes for the Seasonal cycle of Sea-ice microwave brightness temperatures during early Summer in the Weddell Sea, Antarctica, Ann. Glaciol., 44, 297–302, https://doi.org/10.3189/172756406781811817, 2006.
Willmes, S., Haas, C., Nicolaus, M., and Bareiss, J.: Satellite microwave observations of the interannual variability of snowmelt on sea ice in the Southern Ocean, J. Geophys. Res., 114, C03006, https://doi.org/10.1029/2008jc004919, 2009.
Xu, R., Zhao, C., Zhai, X., and Chen, G.: Arctic sea ice type classification by combining CFOSCAT and AMSR-2 data, Earth Space Sci., 9, e2021EA002052, https://doi.org/10.1029/2021EA002052, 2022.
Yackel, J., Barber, D., Papakyriakou, T., and Breneman, C.: First-year sea ice spring melt transitions in the Canadian Arctic Archipelago from time-series synthetic aperture radar data, 1992–2002, Hydrol. Process., 21, 253–265, https://doi.org/10.1002/hyp.6240, 2007.
Yu, L., Zhong, S., Vihma, T., Sui, C., and Sun, B.: Linking the Antarctic sea ice extent changes during 1979–2020 to seasonal modes of Antarctic sea ice variability, Environ. Res. Lett., 17, 114026, https://doi.org/10.1088/1748-9326/ac9c73, 2022.
Yu, L., Zhong, S., Sui, C., and Sun, B.: Sea surface temperature anomalies related to the Antarctic sea ice extent variability in the past four decades, Theor. Appl. Climatol., 155, 2415–2426, https://doi.org/10.1007/s00704-023-04820-7, 2024.
Zheng, L., Cheng, X., Chen, Z., Wang, S., Liang, Q., and Wang, K.: Global Snowmelt Onset Reflects Climate Variability: Insights from Spaceborne Radiometer Observations, J. Climate, 35, 2945–2959, https://doi.org/10.1175/jcli-d-21-0265.1, 2022.
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.
The onset of snowmelt on Antarctic sea ice is an important indicator of sea ice change. In this...
