Articles | Volume 18, issue 4
https://doi.org/10.5194/tc-18-2001-2024
© 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-18-2001-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
29 Apr 2024
Research article |
| 29 Apr 2024
| 29 Apr 2024
From snow accumulation to snow depth distributions by quantifying meteoric ice fractions in the Weddell Sea
Alfred-Wegener-Institut, Helmholtz-Zentrum für Polar- und Meeresforschung, 27570 Bremerhaven, Germany
Nina Maaß
Alfred-Wegener-Institut, Helmholtz-Zentrum für Polar- und Meeresforschung, 27570 Bremerhaven, Germany
Center for Earth System Research and Sustainability, University of Hamburg, 20146 Hamburg, Germany
Leonard Rossmann
Alfred-Wegener-Institut, Helmholtz-Zentrum für Polar- und Meeresforschung, 27570 Bremerhaven, Germany
Marcel Nicolaus
Alfred-Wegener-Institut, Helmholtz-Zentrum für Polar- und Meeresforschung, 27570 Bremerhaven, Germany
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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
This preprint is open for discussion and under review for The Cryosphere (TC).
Short summary
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Our research explored how icebergs affect the distribution of snow and flooding on Antarctic coastal sea ice. Using aircraft-based radar and laser scanning, we found that icebergs create thick snow drifts on their wind-facing sides and leave snow-free zones in their lee. The weight of these snow drifts often causes the ice below to flood, forming slush. These patterns, driven by wind and iceberg placement, are crucial for understanding sea ice changes and improving climate models.
Yubing Cheng, Bin Cheng, Roberta Pirazzini, Amy R. Macfarlane, Timo Vihma, Wolfgang Dorn, Ruzica Dadic, Martin Schneebeli, Stefanie Arndt, and Annette Rinke
EGUsphere, https://doi.org/10.5194/egusphere-2025-1164, https://doi.org/10.5194/egusphere-2025-1164, 2025
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We study snow density from the MOSAiC expedition. Several snow density schemes were tested and compared with observation. A thermodynamic ice model was employed to assess the impact of snow density and precipitation on the thermal regime of sea ice. The parameterized mean snow densities are consistent with observations. Increased snow density reduces snow and ice temperatures, promoting ice growth, while increased precipitation leads to warmer snow and ice temperatures and reduced ice thickness.
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
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The onset of snowmelt on Antarctic sea ice is an important indicator of sea ice change. In this study, we used two radar scatterometers to detect the onset of snowmelt on perennial Antarctic sea ice. Results show that since 2007, snowmelt onset has demonstrated strong interannual and regional variabilities. We also found that the difference in snowmelt onsets between the two scatterometers is closely related to snow metamorphism.
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.
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
Preprint archived
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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.
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.
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.
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
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
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
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
This preprint is open for discussion and under review for The Cryosphere (TC).
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.
Yubing Cheng, Bin Cheng, Roberta Pirazzini, Amy R. Macfarlane, Timo Vihma, Wolfgang Dorn, Ruzica Dadic, Martin Schneebeli, Stefanie Arndt, and Annette Rinke
EGUsphere, https://doi.org/10.5194/egusphere-2025-1164, https://doi.org/10.5194/egusphere-2025-1164, 2025
Short summary
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We study snow density from the MOSAiC expedition. Several snow density schemes were tested and compared with observation. A thermodynamic ice model was employed to assess the impact of snow density and precipitation on the thermal regime of sea ice. The parameterized mean snow densities are consistent with observations. Increased snow density reduces snow and ice temperatures, promoting ice growth, while increased precipitation leads to warmer snow and ice temperatures and reduced ice thickness.
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
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The onset of snowmelt on Antarctic sea ice is an important indicator of sea ice change. In this study, we used two radar scatterometers to detect the onset of snowmelt on perennial Antarctic sea ice. Results show that since 2007, snowmelt onset has demonstrated strong interannual and regional variabilities. We also found that the difference in snowmelt onsets between the two scatterometers is closely related to snow metamorphism.
Hannah Niehaus, Gunnar Spreen, Larysa Istomina, and Marcel Nicolaus
EGUsphere, https://doi.org/10.5194/egusphere-2024-3127, https://doi.org/10.5194/egusphere-2024-3127, 2024
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Melt ponds on Arctic sea ice affect how much solar energy is absorbed, influencing ice melt and climate change. This study used satellite data from 2017–2023 to examine how these ponds vary across regions and seasons. The results show that the surface fraction of melt ponds is more stable in the Central Arctic, with air temperature and ice surface roughness playing key roles in their formation. Understanding these patterns can help to improve climate models and predictions for Arctic warming.
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
Short summary
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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.
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
Preprint archived
Short summary
Short summary
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.
Evelyn Jäkel, Sebastian Becker, Tim R. Sperzel, Hannah Niehaus, Gunnar Spreen, Ran Tao, Marcel Nicolaus, Wolfgang Dorn, Annette Rinke, Jörg Brauchle, and Manfred Wendisch
The Cryosphere, 18, 1185–1205, https://doi.org/10.5194/tc-18-1185-2024, https://doi.org/10.5194/tc-18-1185-2024, 2024
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The results of the surface albedo scheme of a coupled regional climate model were evaluated against airborne and ground-based measurements conducted in the European Arctic in different seasons between 2017 and 2022. We found a seasonally dependent bias between measured and modeled surface albedo for cloudless and cloudy situations. The strongest effects of the albedo model bias on the net irradiance were most apparent in the presence of optically thin clouds.
Hannah Niehaus, Larysa Istomina, Marcel Nicolaus, Ran Tao, Aleksey Malinka, Eleonora Zege, and Gunnar Spreen
The Cryosphere, 18, 933–956, https://doi.org/10.5194/tc-18-933-2024, https://doi.org/10.5194/tc-18-933-2024, 2024
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Melt ponds are puddles of meltwater which form on Arctic sea ice in the summer period. They are darker than the ice cover and lead to increased absorption of solar energy. Global climate models need information about the Earth's energy budget. Thus satellite observations are used to monitor the surface fractions of melt ponds, ocean, and sea ice in the entire Arctic. We present a new physically based algorithm that can separate these three surface types with uncertainty below 10 %.
Ruibo Lei, Mario Hoppmann, Bin Cheng, Marcel Nicolaus, Fanyi Zhang, Benjamin Rabe, Long Lin, Julia Regnery, and Donald K. Perovich
The Cryosphere Discuss., https://doi.org/10.5194/tc-2023-25, https://doi.org/10.5194/tc-2023-25, 2023
Manuscript not accepted for further review
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To characterize the freezing and melting of different types of sea ice, we deployed four IMBs during the MOSAiC second drift. The drifting pattern, together with a large snow accumulation, relatively warm air temperatures, and a rapid increase in oceanic heat close to Fram Strait, determined the seasonal evolution of the ice mass balance. The refreezing of ponded ice and voids within the unconsolidated ridges amplifies the anisotropy of the heat exchange between the ice and the atmosphere/ocean.
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.
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
Short summary
Short summary
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.
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.
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
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.
Jutta E. Wollenburg, Morten Iversen, Christian Katlein, Thomas Krumpen, Marcel Nicolaus, Giulia Castellani, Ilka Peeken, and Hauke Flores
The Cryosphere, 14, 1795–1808, https://doi.org/10.5194/tc-14-1795-2020, https://doi.org/10.5194/tc-14-1795-2020, 2020
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Based on an observed omnipresence of gypsum crystals, we concluded that their release from melting sea ice is a general feature in the Arctic Ocean. Individual gypsum crystals sank at more than 7000 m d−1, suggesting that they are an important ballast mineral. Previous observations found gypsum inside phytoplankton aggregates at 2000 m depth, supporting gypsum as an important driver for pelagic-benthic coupling in the ice-covered Arctic Ocean.
Maciej Miernecki, Lars Kaleschke, Nina Maaß, Stefan Hendricks, and Sten Schmidl Søbjærg
The Cryosphere, 14, 461–476, https://doi.org/10.5194/tc-14-461-2020, https://doi.org/10.5194/tc-14-461-2020, 2020
Nander Wever, Leonard Rossmann, Nina Maaß, Katherine C. Leonard, Lars Kaleschke, Marcel Nicolaus, and Michael Lehning
Geosci. Model Dev., 13, 99–119, https://doi.org/10.5194/gmd-13-99-2020, https://doi.org/10.5194/gmd-13-99-2020, 2020
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Sea ice is an important component of the global climate system. The presence of a snow layer covering sea ice can impact ice mass and energy budgets. The detailed, physics-based, multi-layer snow model SNOWPACK was modified to simulate the snow–sea-ice system, providing simulations of the snow microstructure, water percolation and flooding, and superimposed ice formation. The model is applied to in situ measurements from snow and ice mass-balance buoys installed in the Antarctic Weddell Sea.
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
Evelyn Jäkel, Johannes Stapf, Manfred Wendisch, Marcel Nicolaus, Wolfgang Dorn, and Annette Rinke
The Cryosphere, 13, 1695–1708, https://doi.org/10.5194/tc-13-1695-2019, https://doi.org/10.5194/tc-13-1695-2019, 2019
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The sea ice surface albedo parameterization of a coupled regional climate model was validated against aircraft measurements performed in May–June 2017 north of Svalbard. The albedo parameterization was run offline from the model using the measured parameters surface temperature and snow depth to calculate the surface albedo and the individual fractions of the ice surface subtypes. An adjustment of the variables and additionally accounting for cloud cover reduced the root-mean-squared error.
Friedrich Richter, Matthias Drusch, Lars Kaleschke, Nina Maaß, Xiangshan Tian-Kunze, and Susanne Mecklenburg
The Cryosphere, 12, 921–933, https://doi.org/10.5194/tc-12-921-2018, https://doi.org/10.5194/tc-12-921-2018, 2018
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L-band (1.4 GHz) brightness temperatures from ESA's Soil Moisture and Ocean Salinity SMOS mission have been used to derive thin sea ice thickness. However, the brightness temperature measurements can potentially be assimilated directly in forecasting systems reducing the data latency and providing a more consistent first guess. We studied the forward (observation) operator that translates geophysical sea ice parameters from the ECMWF Ocean ReAnalysis Pilot 5 (ORAP5) into brightness temperatures.
M. Fernández-Méndez, C. Katlein, B. Rabe, M. Nicolaus, I. Peeken, K. Bakker, H. Flores, and A. Boetius
Biogeosciences, 12, 3525–3549, https://doi.org/10.5194/bg-12-3525-2015, https://doi.org/10.5194/bg-12-3525-2015, 2015
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Photosynthetic production in the central Arctic Ocean is controlled by light availability below the ice, nitrate and silicate concentrations in the upper ocean, and the role of sub-ice algae that contributed up to 60% to primary production in summer 2012 during the record sea-ice minimum. As sea ice decreases, an overall change in Arctic PP would be foremost related to a change in the role of the ice algal production and nutrient availability.
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
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
M. Nicolaus, C. Petrich, S. R. Hudson, and M. A. Granskog
The Cryosphere, 7, 977–986, https://doi.org/10.5194/tc-7-977-2013, https://doi.org/10.5194/tc-7-977-2013, 2013
M. Nicolaus and C. Katlein
The Cryosphere, 7, 763–777, https://doi.org/10.5194/tc-7-763-2013, https://doi.org/10.5194/tc-7-763-2013, 2013
Related subject area
Discipline: Sea ice | Subject: Seasonal Snow
Recent changes in pan-Arctic sea ice, lake ice, and snow-on/off timing
Local-scale variability of snow density on Arctic sea ice
Spatiotemporal variability and decadal trends of snowmelt processes on Antarctic sea ice observed by satellite scatterometers
Alicia A. Dauginis and Laura C. Brown
The Cryosphere, 15, 4781–4805, https://doi.org/10.5194/tc-15-4781-2021, https://doi.org/10.5194/tc-15-4781-2021, 2021
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This work examines changes in the timing (on/off dates) of Arctic snow, lake ice, and sea ice to investigate how they have responded to recent climate change and determine if they are responding similarly. We looked at pan-Arctic trends since 1997 and regional trends since 2004 using (mainly) satellite data. Strong regional variability was shown in the snow and ice trends, which highlights the need for a detailed understanding of the regional response to ongoing changes in the Arctic climate.
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 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
Cited articles
Ackley, S., Lewis, M., Fritsen, C., and Xie, H.: Internal melting in Antarctic sea ice: Development of “gap layers”, Geophys. Res. Lett., 35, L11503, https://doi.org/10.1029/2008GL033644, 2008.
Ackley, S., Perovich, D., Maksym, T., Weissling, B., and Xie, H.: Surface flooding of Antarctic summer sea ice, Ann. Glaciol., 61, 117–126, https://doi.org/10.1017/aog.2020.22, 2020.
Arndt, S.: Sensitivity of Sea Ice Growth to Snow Properties in Opposing Regions of the Weddell Sea in Late Summer, Geophys. Res. Lett., 49, e2022GL099653, https://doi.org/10.1029/2022GL099653, 2022a.
Arndt, S.: Snow thickness measurements at ice stations during RV POLARSTERN cruise PS111, Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven, PANGAEA [data set], https://doi.org/10.1594/PANGAEA.946183, 2022b.
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. and Haas, C.: Snow thickness measurements at ice stations during POLARSTERN cruise PS118, PANGAEA [data ste], https://doi.org/10.1594/PANGAEA.928966, 2021.
Arndt, S. and Haas, C.: Snow thickness measurements at ice stations during RV POLARSTERN cruise PS124, PANGAEA [data set], https://doi.org/10.1594/PANGAEA.946177, 2022.
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., Hoppmann, M., Schmithüsen, H., Fraser, A. D., and Nicolaus, M.: Seasonal and interannual variability of landfast sea ice in Atka Bay, Weddell Sea, Antarctica, The Cryosphere, 14, 2775–2793, https://doi.org/10.5194/tc-14-2775-2020, 2020.
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.
Bartelt, P. and Lehning, M.: A physical SNOWPACK model for the Swiss avalanche warning: Part I: numerical model, Cold Reg. Sci. Technol., 35, 123–145, 2002.
Bavay, M., Fierz, C., Hirashima, H., Wever, N., Richter, B., Michel, A., and Ebner, P.: SNOWPACK source code, https://snowpack.slf.ch (last access: 1 March 2024), 2024a.
Bavay, M., Egger, T., Michel, A., and Reisecker, M.: MeteoIO source code, https://meteoio.slf.ch (last access: 1 March 2024), 2024b.
Boisvert, L. N., Webster, M. A., Petty, A. A., Markus, T., Cullather, R. I., and Bromwich, D. H.: Intercomparison of precipitation estimates over the Southern Ocean from atmospheric reanalyses, J. Climate, 33, 10627–10651, 2020.
Calonne, N., Flin, F., Morin, S., Lesaffre, B., du Roscoat, S. R., and Geindreau, C.: Numerical and experimental investigations of the effective thermal conductivity of snow, Geophys. Res. Lett., 38, L23501, https://doi.org/10.1029/2011gl049234, 2011.
Copernicus Climate Change Service: ERA5: Fifth generation of ECMWF atmospheric reanalyses of the global climate, https://cds.climate.copernicus.eu/cdsapp#!/home (last access: 1 March 2024), 2017.
Eayrs, C., Li, X., Raphael, M. N., and Holland, D. M.: Rapid decline in Antarctic sea ice in recent years hints at future change, Nat. Geosci., 14, 460–464, https://doi.org/10.1038/s41561-021-00768-3, 2021.
Ebner, L., Heinemann, G., Haid, V., and Timmermann, R.: Katabatic winds and polynya dynamics at Coats Land, Antarctica, Antarct. Sci., 26, 309–326, 2014.
Eicken, H., Lange, M. A., Hubberten, H. W., and Wadhams, P.: Characteristics and distribution patterns of snow and meteoric ice in the Weddell Sea and their contribution to the mass balance of sea ice, Ann. Geophys., 12, 80–93, https://doi.org/10.1007/s00585-994-0080-x, 1994.
Fons, S. W. and Kurtz, N. T.: Retrieval of snow freeboard of Antarctic sea ice using waveform fitting of CryoSat-2 returns, The Cryosphere, 13, 861–878, https://doi.org/10.5194/tc-13-861-2019, 2019.
Grosfeld, K., Treffeisen, R., Asseng, J., Bartsch, A., Bräuer, B., Fritzsch, B., Gerdes, R., Hendricks, S., Hiller, W., and Heygster, G.: Online sea-ice knowledge and data platform www.meereisportal.de, Polarforschung, 85, 143–155, 2015.
Haas, C. and Eicken, H.: Interannual variability of summer sea ice thickness in the Siberian and central Arctic under different atmospheric circulation regimes, J. Geophys. Res.-Oceans, 106, 4449–4462, 2001.
Haas, C., Thomas, D. N., and Bareiss, J.: Surface properties and processes of perennial Antarctic sea ice in summer, J. Glaciology, 47, 613–625, https://doi.org/10.3189/172756501781831864, 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., Arndt, S., Peeken, I., and Allhusen, E.: Sea Ice, Chapter in: The Expedition PS118 of the Research Vessel POLARSTERN to the Weddell Sea in 2019, Berichte zur Polar-und Meeresforschung – Reports on polar and marine research, 735, 97–123, https://doi.org/10.2312/BzPM_0735_2019, 2019.
Haas, C., Arndt, S., Peeken, I., Eggers, S. L., and Neudert, M.: Chapter Sea Ice Geophysics and Biogeochemistry in: The Expedition PS124 of the Research Vessel POLARSTERN to the Weddell Sea in 2021, Berichte zur Polar-und Meeresforschung – Reports on polar and marine research, Bremerhaven, Alfred Wegener Institute for Polar and Marine Research, 755, p. 237, https://doi.org/10.48433/BzPM_0755_202, 2021.
Harms, S., Fahrbach, E., and Strass, V. H.: Sea ice transports in the Weddell Sea, J. Geophys. Res.-Oceans, 106, 9057–9073, https://doi.org/10.1029/1999JC000027, 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.
Holtslag, A. and De Bruin, H.: Applied modeling of the nighttime surface energy balance over land, J. Appl. Meteorol. Clim., 27, 689–704, https://doi.org/10.1175/1520-0450(1988)027<0689:AMOTNS>2.0.CO;2, 1988.
Kawamura, T., Ohshima, K., Takizawa, T., and Ushio, S.: Physical, structural, and isotopic characteristics and growth processes of fast sea ice in Lützow-Holm Bay, Antarctica, J. Geophys. Res.-Oceans, 102, 3345–3355, 1997.
Kottmeier, C. and Sellmann, L.: Atmospheric and oceanic forcing of Weddell Sea ice motion, J. Geophys. Res.-Oceans, 101, 20809–20824, 1996.
Kottmeier, C., Olf, J., Frieden, W., and Roth, R.: Wind forcing and ice motion in the Weddell Sea region, J. Geophys. Res.-Atmos., 97, 20373–20383, 1992.
Kwok, R. and Kacimi, S.: Three years of sea ice freeboard, snow depth, and ice thickness of the Weddell Sea from Operation IceBridge and CryoSat-2, The Cryosphere, 12, 2789–2801, https://doi.org/10.5194/tc-12-2789-2018, 2018.
Kwok, R., Kacimi, S., Webster, M., Kurtz, N., and Petty, A.: Arctic snow depth and sea ice thickness from ICESat-2 and CryoSat-2 freeboards: A first examination, J. Geophys. Res.-Oceans, 125, e2019JC016008, https://doi.org/10.1029/2019JC016008, 2020.
Lehning, M., Bartelt, P., Brown, B., and Fierz, C.: A physical SNOWPACK model for the Swiss avalanche warning Part III: meteorological forcing, thin layer formation and evaluation, Cold Reg. Sci. Technol., 35, 169–184, 2002a.
Lehning, M., Bartelt, P., Brown, B., Fierz, C., and Satyawali, P.: A physical SNOWPACK model for the Swiss avalanche warning: Part II. Snow microstructure, Cold Reg. Sci. Technol., 35, 147–167, 2002b.
Lytle, V. and Ackley, S.: Heat flux through sea ice in the western Weddell Sea: Convective and conductive transfer processes, J. Geophys. Res.-Oceans, 101, 8853–8868, 1996.
Massom, R., Eicken, H., Haas, C., Jeffries, M. O., Drinkwater, M. R., Sturm, M., Worby, A. P., Wu, X. R., 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.
McPhee, M. G., Kottmeier, C., and Morison, J. H.: Ocean heat flux in the central Weddell Sea during winter, J. Phys. Oceanogr., 29, 1166–1179, 1999.
Melsheimer, C., Spreen, G., Ye, Y., and Shokr, M.: First results of Antarctic sea ice type retrieval from active and passive microwave remote sensing data, The Cryosphere, 17, 105–126, https://doi.org/10.5194/tc-17-105-2023, 2023.
Nicolaus, M., Haas, C., Bareiss, J., and Willmes, S.: A model study of differences of snow thinning on Arctic and Antarctic first-year sea ice during spring and summer, Ann. Glaciol., 44, 147–153, https://doi.org/10.3189/172756406781811312, 2006.
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., 114, D17109, https://doi.org/10.1029/2008JD011227, 2009.
Nicolaus, M., Hoppmann, M., Arndt, S., Hendricks, S., Katlein, C., König-Langlo, G., Nicolaus, A., Rossmann, L., Schiller, M., Schwegmann, S., Langevin, D., and Bartsch, A.: Snow height and air temperature on sea ice from Snow Buoy measurements, Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven, PANGAEA [data set], https://doi.org/10.1594/PANGAEA.875638, 2017.
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, Frontiers in Marine Science, 8, 655446, https://doi.org/10.3389/fmars.2021.655446, 2021.
Paul, S., Willmes, S., and Heinemann, G.: Long-term coastal-polynya dynamics in the southern Weddell Sea from MODIS thermal-infrared imagery, The Cryosphere, 9, 2027–2041, https://doi.org/10.5194/tc-9-2027-2015, 2015.
Paul, S., Hendricks, S., Ricker, R., Kern, S., and Rinne, E.: Empirical parametrization of Envisat freeboard retrieval of Arctic and Antarctic sea ice based on CryoSat-2: progress in the ESA Climate Change Initiative, The Cryosphere, 12, 2437–2460, https://doi.org/10.5194/tc-12-2437-2018, 2018.
Purich, A. and Doddridge, E. W.: Record low Antarctic sea ice coverage indicates a new sea ice state, Communications Earth & Environment, 4, 314, https://doi.org/10.1038/s43247-023-00961-9, 2023.
Rabenstein, L. (Ed.): Endurance22, Cruise Scientific Report, 1–95, https://endurance22.org/uploads/2022/06/Science_Report_Endurance22_final_version.pdf (last access: 10 June 2022), 2022.
Ricker, R., Hendricks, S., Perovich, D. K., Helm, V., and Gerdes, R.: Impact of snow accumulation on CryoSat-2 range retrievals over Arctic sea ice: An observational approach with buoy data, Geophys. Res. Lett., 42, 4447–4455, 2015.
Robertson, R., Padman, L., and Levine, M. D.: Fine structure, microstructure, and vertical mixing processes in the upper ocean in the western Weddell Sea, J. Geophys. Res.-Oceans, 100, 18517–18535, 1995.
Robertson, R., Padman, L., and Egbert, G. D.: Tides in the Weddell Sea, Ocean, Ice and Atmosphere: Interactions at the Antarctic Continental Margin, Antarct. Res. Ser., 75, 341–369, 1998.
Schwegmann, S., Haas, C., Fowler, C., and Gerdes, R.: A comparison of satellite-derived sea-ice motion with drifting-buoy data in the Weddell Sea, Antarctica, Ann. Glaciol., 52, 103–110, https://doi.org/10.3189/172756411795931813, 2011.
Schwegmann, S., Rinne, E., Ricker, R., Hendricks, S., and Helm, V.: About the consistency between Envisat and CryoSat-2 radar freeboard retrieval over Antarctic sea ice, The Cryosphere, 10, 1415–1425, https://doi.org/10.5194/tc-10-1415-2016, 2016.
Spreen, G., Kaleschke, L., and Heygster, G.: Sea ice remote sensing using AMSR-E 89-GHz channels, J. Geophys. Res.-Oceans, 113, C02S03, https://doi.org/10.1029/2005jc003384, 2008.
Sturm, M. and Holmgren, J.: An automatic snow depth probe for field validation campaigns, Water Resour. Res., 54, 9695–9701, 2018.
Sturm, M., Holmgren, J., Konig, M., and Morris, K.: The thermal conductivity of seasonal snow, J. Glaciology, 43, 26–41, 1997.
Thorndike, A.: A toy model linking atmospheric thermal radiation and sea ice growth, J. Geophys. Res.-Oceans, 97, 9401–9410, 1992.
Tian, L. J., Gao, Y. L., Weissling, B., and Ackley, S. F.: Snow-ice contribution to the structure of sea ice in the Amundsen Sea, Antarctica, Ann. Glaciol., 61, 369–378, https://doi.org/10.1017/aog.2020.55, 2020.
Turner, J., Holmes, C., Caton Harrison, T., Phillips, T., Jena, B., Reeves-Francois, T., Fogt, R., Thomas, E. R., and Bajish, C.: Record low Antarctic sea ice cover in February 2022, Geophys. Res. Lett., 49, e2022GL098904, https://doi.org/10.1029/2022GL098904, 2022.
Venegas, S. A. and Drinkwater, M. R.: Sea ice, atmosphere and upper ocean variability in the Weddell Sea, Antarctica, J. Geophys. Res.-Oceans, 106, 16747–16765, https://doi.org/10.1029/2000jc000594, 2001.
Vernet, M., Geibert, W., Hoppema, M., Brown, P. J., Haas, C., Hellmer, H., Jokat, W., Jullion, L., Mazloff, M., and Bakker, D.: The Weddell Gyre, Southern Ocean: present knowledge and future challenges, Rev. Geophys., 57, 623–708, 2019.
Vihma, T., Launiainen, J., and Uotila, J.: Weddell Sea ice drift: Kinematics and wind forcing, J. Geophys. Res.-Oceans, 101, 18279–18296, https://doi.org/10.1029/96JC01441, 1996.
Webster, M., Gerland, S., Holland, M., Hunke, E., Kwok, R., Lecomte, O., Massom, R., Perovich, D., and Sturm, M.: Snow in the changing sea-ice systems, Nat. Clim. Change, 8, 946–953, https://doi.org/10.1038/s41558-018-0286-7, 2018.
Wever, N., Schmid, L., Heilig, A., Eisen, O., Fierz, C., and Lehning, M.: Verification of the multi-layer SNOWPACK model with different water transport schemes, The Cryosphere, 9, 2271–2293, https://doi.org/10.5194/tc-9-2271-2015, 2015.
Wever, N., Würzer, S., Fierz, C., and Lehning, M.: Simulating ice layer formation under the presence of preferential flow in layered snowpacks, The Cryosphere, 10, 2731–2744, https://doi.org/10.5194/tc-10-2731-2016, 2016.
Wever, N., Rossmann, L., Maaß, N., Leonard, K. C., Kaleschke, L., Nicolaus, M., and Lehning, M.: Version 1 of a sea ice module for the physics-based, detailed, multi-layer SNOWPACK model, Geosci. Model Dev., 13, 99–119, https://doi.org/10.5194/gmd-13-99-2020, 2020.
Wever, N., Leonard, K., Maksym, T., White, S., Proksch, M., and Lenaerts, J. T. M.: Spatially distributed simulations of the effect of snow on mass balance and flooding of Antarctic sea ice, J. Glaciol., 67, 1055–1073, https://doi.org/10.1017/jog.2021.54, 2021.
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.-Oceans, 114, C03006, https://doi.org/10.1029/2008jc004919, 2009.
Worby, A. P., Geiger, C. A., Paget, M. J., Van Woert, M. L., Ackley, S. F., and DeLiberty, T. L.: Thickness distribution of Antarctic sea ice, J. Geophys. Res.-Oceans, 113, C05S92, https://doi.org/10.1029/2007jc004254, 2008.
Short summary
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.
Antarctic sea ice maintains year-round snow cover, crucial for its energy and mass budgets....
