Articles | Volume 14, issue 11
https://doi.org/10.5194/essd-14-4901-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-14-4901-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
04 Nov 2022
Data description paper |
| 04 Nov 2022
| 04 Nov 2022
Mesoscale observations of temperature and salinity in the Arctic Transpolar Drift: a high-resolution dataset from the MOSAiC Distributed Network
Alfred-Wegener-Institut, Helmholtz-Zentrum für Polar- und Meeresforschung, Bremerhaven, Germany
Ivan Kuznetsov
Alfred-Wegener-Institut, Helmholtz-Zentrum für Polar- und Meeresforschung, Bremerhaven, Germany
Ying-Chih Fang
Department of Oceanography, National Sun Yat-sen University, 80424 Kaohsiung, Taiwan
Benjamin Rabe
Alfred-Wegener-Institut, Helmholtz-Zentrum für Polar- und Meeresforschung, Bremerhaven, Germany
Related authors
Salar Karam, Céline Heuzé, Mario Hoppmann, and Laura de Steur
Ocean Sci., 20, 917–930, https://doi.org/10.5194/os-20-917-2024, https://doi.org/10.5194/os-20-917-2024, 2024
Short summary
Short summary
A long-term mooring array in the Fram Strait allows for an evaluation of decadal trends in temperature in this major oceanic gateway into the Arctic. Since the 1980s, the deep waters of the Greenland Sea and the Eurasian Basin of the Arctic have warmed rapidly at a rate of 0.11°C and 0.05°C per decade, respectively, at a depth of 2500 m. We show that the temperatures of the two basins converged around 2017 and that the deep waters of the Greenland Sea are now a heat source for the Arctic Ocean.
Ivan Kuznetsov, Benjamin Rabe, Alexey Androsov, Ying-Chih Fang, Mario Hoppmann, Alejandra Quintanilla-Zurita, Sven Harig, Sandra Tippenhauer, Kirstin Schulz, Volker Mohrholz, Ilker Fer, Vera Fofonova, and Markus Janout
Ocean Sci., 20, 759–777, https://doi.org/10.5194/os-20-759-2024, https://doi.org/10.5194/os-20-759-2024, 2024
Short summary
Short summary
Our research introduces a tool for dynamically mapping the Arctic Ocean using data from the MOSAiC experiment. Incorporating extensive data into a model clarifies the ocean's structure and movement. Our findings on temperature, salinity, and currents reveal how water layers mix and identify areas of intense water movement. This enhances understanding of Arctic Ocean dynamics and supports climate impact studies. Our work is vital for comprehending this key region in global climate science.
Vishnu Nandan, Rosemary Willatt, Robbie Mallett, Julienne Stroeve, Torsten Geldsetzer, Randall Scharien, Rasmus Tonboe, John Yackel, Jack Landy, David Clemens-Sewall, Arttu Jutila, David N. Wagner, Daniela Krampe, Marcus Huntemann, Mallik Mahmud, David Jensen, Thomas Newman, Stefan Hendricks, Gunnar Spreen, Amy Macfarlane, Martin Schneebeli, James Mead, Robert Ricker, Michael Gallagher, Claude Duguay, Ian Raphael, Chris Polashenski, Michel Tsamados, Ilkka Matero, and Mario Hoppmann
The Cryosphere, 17, 2211–2229, https://doi.org/10.5194/tc-17-2211-2023, https://doi.org/10.5194/tc-17-2211-2023, 2023
Short summary
Short summary
We show that wind redistributes snow on Arctic sea ice, and Ka- and Ku-band radar measurements detect both newly deposited snow and buried snow layers that can affect the accuracy of snow depth estimates on sea ice. Radar, laser, meteorological, and snow data were collected during the MOSAiC expedition. With frequent occurrence of storms in the Arctic, our results show that
wind-redistributed snow needs to be accounted for to improve snow depth estimates on sea ice from satellite radars.
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
Short summary
Short summary
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.
Long Lin, Ruibo Lei, Mario Hoppmann, Donald K. Perovich, and Hailun He
The Cryosphere, 16, 4779–4796, https://doi.org/10.5194/tc-16-4779-2022, https://doi.org/10.5194/tc-16-4779-2022, 2022
Short summary
Short summary
Ice mass balance observations indicated that average basal melt onset was comparable in the central Arctic Ocean and approximately 17 d earlier than surface melt in the Beaufort Gyre. The average onset of basal growth lagged behind the surface of the pan-Arctic Ocean for almost 3 months. In the Beaufort Gyre, both drifting-buoy observations and fixed-point observations exhibit a trend towards earlier basal melt onset, which can be ascribed to the earlier warming of the surface ocean.
Ruibo Lei, Mario Hoppmann, Bin Cheng, Guangyu Zuo, Dawei Gui, Qiongqiong Cai, H. Jakob Belter, and Wangxiao Yang
The Cryosphere, 15, 1321–1341, https://doi.org/10.5194/tc-15-1321-2021, https://doi.org/10.5194/tc-15-1321-2021, 2021
Short summary
Short summary
Quantification of ice deformation is useful for understanding of the role of ice dynamics in climate change. Using data of 32 buoys, we characterized spatiotemporal variations in ice kinematics and deformation in the Pacific sector of Arctic Ocean for autumn–winter 2018/19. Sea ice in the south and west has stronger mobility than in the east and north, which weakens from autumn to winter. An enhanced Arctic dipole and weakened Beaufort Gyre in winter lead to an obvious turning of ice drifting.
Christian Katlein, Lovro Valcic, Simon Lambert-Girard, and Mario Hoppmann
The Cryosphere, 15, 183–198, https://doi.org/10.5194/tc-15-183-2021, https://doi.org/10.5194/tc-15-183-2021, 2021
Short summary
Short summary
To improve autonomous investigations of sea ice optical properties, we designed a chain of multispectral light sensors, providing autonomous in-ice light measurements. Here we describe the system and the data acquired from a first prototype deployment. We show that sideward-looking planar irradiance sensors basically measure scalar irradiance and demonstrate the use of this sensor chain to derive light transmittance and inherent optical properties of sea ice.
Julienne Stroeve, Vishnu Nandan, Rosemary Willatt, Rasmus Tonboe, Stefan Hendricks, Robert Ricker, James Mead, Robbie Mallett, Marcus Huntemann, Polona Itkin, Martin Schneebeli, Daniela Krampe, Gunnar Spreen, Jeremy Wilkinson, Ilkka Matero, Mario Hoppmann, and Michel Tsamados
The Cryosphere, 14, 4405–4426, https://doi.org/10.5194/tc-14-4405-2020, https://doi.org/10.5194/tc-14-4405-2020, 2020
Short summary
Short summary
This study provides a first look at the data collected by a new dual-frequency Ka- and Ku-band in situ radar over winter sea ice in the Arctic Ocean. The instrument shows potential for using both bands to retrieve snow depth over sea ice, as well as sensitivity of the measurements to changing snow and atmospheric conditions.
Alejandra Quintanilla-Zurita, Benjamin Rabe, Claudia Wekerle, Torsten Kanzow, Ivan Kuznetsov, Sinhue Torres-Valdes, Enric Pallàs-Sanz, and Ying-Chih Fang
EGUsphere, https://doi.org/10.5194/egusphere-2025-3773, https://doi.org/10.5194/egusphere-2025-3773, 2025
This preprint is open for discussion and under review for Ocean Science (OS).
Short summary
Short summary
During a year-long Arctic expedition, we discovered nine underwater eddies beneath the sea ice in the central Arctic Ocean. These hidden structures form within a layered part of the ocean just below the surface and may reshape water layers and transport heat, freshwater, and nutrients. Using drifting ice platforms, we measured their size, depth, and motion to understand how they form.
Gaziza Konyssova, Vera Sidorenko, Alexey Androsov, Sabine Horn, Sara Rubinetti, Ivan Kuznetsov, Karen Helen Wiltshire, and Justus van Beusekom
EGUsphere, https://doi.org/10.5194/egusphere-2025-2135, https://doi.org/10.5194/egusphere-2025-2135, 2025
Short summary
Short summary
This study explores how winds, tides, and biological activity influence suspended particle concentrations in a tidal basin of the Wadden Sea. Combining long-term measurements, ocean modelling, and machine learning, we found that wind dominates in winter, while biological processes like algae growth gain importance in spring and summer. The results also reveal contrasting short-term dynamics at shallow and deep stations, identifying the drivers of variability in coastal waters.
Salar Karam, Céline Heuzé, Mario Hoppmann, and Laura de Steur
Ocean Sci., 20, 917–930, https://doi.org/10.5194/os-20-917-2024, https://doi.org/10.5194/os-20-917-2024, 2024
Short summary
Short summary
A long-term mooring array in the Fram Strait allows for an evaluation of decadal trends in temperature in this major oceanic gateway into the Arctic. Since the 1980s, the deep waters of the Greenland Sea and the Eurasian Basin of the Arctic have warmed rapidly at a rate of 0.11°C and 0.05°C per decade, respectively, at a depth of 2500 m. We show that the temperatures of the two basins converged around 2017 and that the deep waters of the Greenland Sea are now a heat source for the Arctic Ocean.
Ivan Kuznetsov, Benjamin Rabe, Alexey Androsov, Ying-Chih Fang, Mario Hoppmann, Alejandra Quintanilla-Zurita, Sven Harig, Sandra Tippenhauer, Kirstin Schulz, Volker Mohrholz, Ilker Fer, Vera Fofonova, and Markus Janout
Ocean Sci., 20, 759–777, https://doi.org/10.5194/os-20-759-2024, https://doi.org/10.5194/os-20-759-2024, 2024
Short summary
Short summary
Our research introduces a tool for dynamically mapping the Arctic Ocean using data from the MOSAiC experiment. Incorporating extensive data into a model clarifies the ocean's structure and movement. Our findings on temperature, salinity, and currents reveal how water layers mix and identify areas of intense water movement. This enhances understanding of Arctic Ocean dynamics and supports climate impact studies. Our work is vital for comprehending this key region in global climate science.
Itzel Ruvalcaba Baroni, Elin Almroth-Rosell, Lars Axell, Sam T. Fredriksson, Jenny Hieronymus, Magnus Hieronymus, Sandra-Esther Brunnabend, Matthias Gröger, Ivan Kuznetsov, Filippa Fransner, Robinson Hordoir, Saeed Falahat, and Lars Arneborg
Biogeosciences, 21, 2087–2132, https://doi.org/10.5194/bg-21-2087-2024, https://doi.org/10.5194/bg-21-2087-2024, 2024
Short summary
Short summary
The health of the Baltic and North seas is threatened due to high anthropogenic pressure; thus, different methods to assess the status of these regions are urgently needed. Here, we validated a novel model simulating the ocean dynamics and biogeochemistry of the Baltic and North seas that can be used to create future climate and nutrient scenarios, contribute to European initiatives on de-eutrophication, and provide water quality advice and support on nutrient load reductions for both seas.
Céline Heuzé, Oliver Huhn, Maren Walter, Natalia Sukhikh, Salar Karam, Wiebke Körtke, Myriel Vredenborg, Klaus Bulsiewicz, Jürgen Sültenfuß, Ying-Chih Fang, Christian Mertens, Benjamin Rabe, Sandra Tippenhauer, Jacob Allerholt, Hailun He, David Kuhlmey, Ivan Kuznetsov, and Maria Mallet
Earth Syst. Sci. Data, 15, 5517–5534, https://doi.org/10.5194/essd-15-5517-2023, https://doi.org/10.5194/essd-15-5517-2023, 2023
Short summary
Short summary
Gases dissolved in the ocean water not used by the ecosystem (or "passive tracers") are invaluable to track water over long distances and investigate the processes that modify its properties. Unfortunately, especially so in the ice-covered Arctic Ocean, such gas measurements are sparse. We here present a data set of several passive tracers (anthropogenic gases, noble gases and their isotopes) collected over the full ocean depth, weekly, during the 1-year drift in the Arctic during MOSAiC.
Vishnu Nandan, Rosemary Willatt, Robbie Mallett, Julienne Stroeve, Torsten Geldsetzer, Randall Scharien, Rasmus Tonboe, John Yackel, Jack Landy, David Clemens-Sewall, Arttu Jutila, David N. Wagner, Daniela Krampe, Marcus Huntemann, Mallik Mahmud, David Jensen, Thomas Newman, Stefan Hendricks, Gunnar Spreen, Amy Macfarlane, Martin Schneebeli, James Mead, Robert Ricker, Michael Gallagher, Claude Duguay, Ian Raphael, Chris Polashenski, Michel Tsamados, Ilkka Matero, and Mario Hoppmann
The Cryosphere, 17, 2211–2229, https://doi.org/10.5194/tc-17-2211-2023, https://doi.org/10.5194/tc-17-2211-2023, 2023
Short summary
Short summary
We show that wind redistributes snow on Arctic sea ice, and Ka- and Ku-band radar measurements detect both newly deposited snow and buried snow layers that can affect the accuracy of snow depth estimates on sea ice. Radar, laser, meteorological, and snow data were collected during the MOSAiC expedition. With frequent occurrence of storms in the Arctic, our results show that
wind-redistributed snow needs to be accounted for to improve snow depth estimates on sea ice from satellite radars.
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
Short summary
Short summary
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.
Francesca Doglioni, Robert Ricker, Benjamin Rabe, Alexander Barth, Charles Troupin, and Torsten Kanzow
Earth Syst. Sci. Data, 15, 225–263, https://doi.org/10.5194/essd-15-225-2023, https://doi.org/10.5194/essd-15-225-2023, 2023
Short summary
Short summary
This paper presents a new satellite-derived gridded dataset, including 10 years of sea surface height and geostrophic velocity at monthly resolution, over the Arctic ice-covered and ice-free regions, up to 88° N. We assess the dataset by comparison to independent satellite and mooring data. Results correlate well with independent satellite data at monthly timescales, and the geostrophic velocity fields can resolve seasonal to interannual variability of boundary currents wider than about 50 km.
Long Lin, Ruibo Lei, Mario Hoppmann, Donald K. Perovich, and Hailun He
The Cryosphere, 16, 4779–4796, https://doi.org/10.5194/tc-16-4779-2022, https://doi.org/10.5194/tc-16-4779-2022, 2022
Short summary
Short summary
Ice mass balance observations indicated that average basal melt onset was comparable in the central Arctic Ocean and approximately 17 d earlier than surface melt in the Beaufort Gyre. The average onset of basal growth lagged behind the surface of the pan-Arctic Ocean for almost 3 months. In the Beaufort Gyre, both drifting-buoy observations and fixed-point observations exhibit a trend towards earlier basal melt onset, which can be ascribed to the earlier warming of the surface ocean.
Vera Fofonova, Tuomas Kärnä, Knut Klingbeil, Alexey Androsov, Ivan Kuznetsov, Dmitry Sidorenko, Sergey Danilov, Hans Burchard, and Karen Helen Wiltshire
Geosci. Model Dev., 14, 6945–6975, https://doi.org/10.5194/gmd-14-6945-2021, https://doi.org/10.5194/gmd-14-6945-2021, 2021
Short summary
Short summary
We present a test case of river plume spreading to evaluate coastal ocean models. Our test case reveals the level of numerical mixing (due to parameterizations used and numerical treatment of processes in the model) and the ability of models to reproduce complex dynamics. The major result of our comparative study is that accuracy in reproducing the analytical solution depends less on the type of applied model architecture or numerical grid than it does on the type of advection scheme.
Amy Solomon, Céline Heuzé, Benjamin Rabe, Sheldon Bacon, Laurent Bertino, Patrick Heimbach, Jun Inoue, Doroteaciro Iovino, Ruth Mottram, Xiangdong Zhang, Yevgeny Aksenov, Ronan McAdam, An Nguyen, Roshin P. Raj, and Han Tang
Ocean Sci., 17, 1081–1102, https://doi.org/10.5194/os-17-1081-2021, https://doi.org/10.5194/os-17-1081-2021, 2021
Short summary
Short summary
Freshwater in the Arctic Ocean plays a critical role in the global climate system by impacting ocean circulations, stratification, mixing, and emergent regimes. In this review paper we assess how Arctic Ocean freshwater changed in the 2010s relative to the 2000s. Estimates from observations and reanalyses show a qualitative stabilization in the 2010s due to a compensation between a freshening of the Beaufort Gyre and a reduction in freshwater in the Amerasian and Eurasian basins.
Francesca Doglioni, Robert Ricker, Benjamin Rabe, and Torsten Kanzow
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2021-170, https://doi.org/10.5194/essd-2021-170, 2021
Manuscript not accepted for further review
Short summary
Short summary
This paper presents a new satellite-derived gridded dataset of sea surface height and geostrophic velocity, over the Arctic ice-covered and ice-free regions up to 88° N. The dataset includes velocities north of 82° N, which were not available before. We assess the dataset by comparison to one independent satellite dataset and to independent mooring data. Results show that the geostrophic velocity fields can resolve seasonal to interannual variability of boundary currents wider than about 50 km.
Ruibo Lei, Mario Hoppmann, Bin Cheng, Guangyu Zuo, Dawei Gui, Qiongqiong Cai, H. Jakob Belter, and Wangxiao Yang
The Cryosphere, 15, 1321–1341, https://doi.org/10.5194/tc-15-1321-2021, https://doi.org/10.5194/tc-15-1321-2021, 2021
Short summary
Short summary
Quantification of ice deformation is useful for understanding of the role of ice dynamics in climate change. Using data of 32 buoys, we characterized spatiotemporal variations in ice kinematics and deformation in the Pacific sector of Arctic Ocean for autumn–winter 2018/19. Sea ice in the south and west has stronger mobility than in the east and north, which weakens from autumn to winter. An enhanced Arctic dipole and weakened Beaufort Gyre in winter lead to an obvious turning of ice drifting.
Christian Katlein, Lovro Valcic, Simon Lambert-Girard, and Mario Hoppmann
The Cryosphere, 15, 183–198, https://doi.org/10.5194/tc-15-183-2021, https://doi.org/10.5194/tc-15-183-2021, 2021
Short summary
Short summary
To improve autonomous investigations of sea ice optical properties, we designed a chain of multispectral light sensors, providing autonomous in-ice light measurements. Here we describe the system and the data acquired from a first prototype deployment. We show that sideward-looking planar irradiance sensors basically measure scalar irradiance and demonstrate the use of this sensor chain to derive light transmittance and inherent optical properties of sea ice.
Julienne Stroeve, Vishnu Nandan, Rosemary Willatt, Rasmus Tonboe, Stefan Hendricks, Robert Ricker, James Mead, Robbie Mallett, Marcus Huntemann, Polona Itkin, Martin Schneebeli, Daniela Krampe, Gunnar Spreen, Jeremy Wilkinson, Ilkka Matero, Mario Hoppmann, and Michel Tsamados
The Cryosphere, 14, 4405–4426, https://doi.org/10.5194/tc-14-4405-2020, https://doi.org/10.5194/tc-14-4405-2020, 2020
Short summary
Short summary
This study provides a first look at the data collected by a new dual-frequency Ka- and Ku-band in situ radar over winter sea ice in the Arctic Ocean. The instrument shows potential for using both bands to retrieve snow depth over sea ice, as well as sensitivity of the measurements to changing snow and atmospheric conditions.
Cited articles
Athanase, M., Sennéchael, N., Garric, G., Koenig, Z., Boles, E., and Provost,
C.: New Hydrographic Measurements of the Upper Arctic Western Eurasian Basin
in 2017 Reveal Fresher Mixed Layer and Shallower Warm Layer Than 2005–2012
Climatology, J. Geophys. Res.-Oceans, 124, 1091–1114,
https://doi.org/10.1029/2018JC014701, 2019. a
Beszczynska-Möller, A., Fahrbach, E., Schauer, U., and Hansen, E.:
Variability in Atlantic water temperature and transport at the entrance to
the Arctic Ocean, 1997–2010, ICES J. Mar. Sci., 69, 852–863,
https://doi.org/10.1093/icesjms/fss056, 2012. a
Biddle, L. C. and Swart, S.: The Observed Seasonal Cycle of Submesoscale
Processes in the Antarctic Marginal Ice Zone, J. Geophys.
Res.-Oceans, 125, e2019JC015587, https://doi.org/10.1029/2019JC015587, 2020. a
Bretherton, F. P., Davis, R. E., and Fandry, C. B.: A technique for objective
analysis and design of oceanographic experiments applied to MODE-73, Deep
Sea Research and Oceanographic Abstracts, 23, 559–582,
https://doi.org/10.1016/0011-7471(76)90001-2, 1976. a
Capet, X., McWilliams, J. C., Molemaker, M. J., and Shchepetkin, A. F.:
Mesoscale to submesoscale transition in the California Current system. Part
I: Flow structure, eddy flux, and observational tests, J. Phys.
Oceanogr., 38, 29–43, https://doi.org/10.1175/2007JPO3671.1, 2008. a
Chelton, D. B., DeSzoeke, R. A., Schlax, M. G., El Naggar, K., and Siwertz,
N.: Geographical Variability of the First Baroclinic Rossby Radius of
Deformation, J. Phys. Oceanogr., 28, 433–460,
https://doi.org/10.1175/1520-0485(1998)028<0433:GVOTFB>2.0.CO;2, 1998. a
D'Asaro, E., Lee, C., Rainville, L., Harcourt, R., and Thomas, L.: Enhanced
Turbulence and Energy Dissipation at Ocean Fronts, Science, 332, 318–322, https://doi.org/10.1126/science.1201515, 2011. a
D'Asaro, E. A.: Observations of small eddies in the Beaufort Sea, J.
Geophys. Res.-Oceans, 93, 6669–6684, https://doi.org/10.1029/JC093iC06p06669,
1988. a
du Plessis, M., Swart, S., Ansorge, I. J., Mahadevan, A., and Thompson, A. F.:
Southern Ocean Seasonal Restratification Delayed by Submesoscale
Wind–Front Interactions, J. Phys. Oceanogr., 49, 1035–1053,
https://doi.org/10.1175/JPO-D-18-0136.1, 2019. a
Fadeev, E., Wietz, M., von Appen, W.-J., Iversen, M. H., Nöthig, E.-M., Engel,
A., Grosse, J., Graeve, M., and Boetius, A.: Submesoscale physicochemical
dynamics directly shape bacterioplankton community structure in space and
time, Limnol. Oceanogr., 66, 2901–2913, https://doi.org/10.1002/lno.11799,
2021. a
Ferrari, R. and Wunsch, C.: Ocean Circulation Kinetic Energy: Reservoirs,
Sources, and Sinks, Annu. Rev. Fluid Mech., 41, 253–282,
https://doi.org/10.1146/annurev.fluid.40.111406.102139, 2008. a
Gallaher, S. G., Stanton, T. P., Shaw, W. J., Cole, S. T., Toole, J. M.,
Wilkinson, J. P., Maksym, T., and Hwang, B.: Evolution of a Canada Basin
ice-ocean boundary layer and mixed layer across a developing
thermodynamically forced marginal ice zone, J. Geophys. Res.-Oceans, 121, 6223–6250, https://doi.org/10.1002/2016JC011778, 2016. a
Gaube, P., Chelton, D. B., Samelson, R. M., Schlax, M. G., and O'Neill, L. W.:
Satellite observations of mesoscale eddy-induced Ekman pumping, J.
Phys. Oceanogr., 45, 104–132, https://doi.org/10.1175/JPO-D-14-0032.1, 2015. a
Gill, A., Green, J., and Simmons, A.: Energy partition in the large-scale
ocean circulation and the production of mid-ocean eddies, Deep Sea Research and Oceanographic Abstracts, 21, 509–528,
https://doi.org/10.1016/0011-7471(74)90010-2, 1974. a
Gommenginger, C., Chapron, B., Hogg, A., Buckingham, C., Fox-Kemper, B.,
Eriksson, L., Soulat, F., Ubelmann, C., Ocampo-Torres, F., Nardelli, B. B.,
Griffin, D., Lopez-Dekker, P., Knudsen, P., Andersen, O., Stenseng, L.,
Stapleton, N., Perrie, W., Violante-Carvalho, N., Schulz-Stellenfleth, J.,
Woolf, D., Isern-Fontanet, J., Ardhuin, F., Klein, P., Mouche, A., Pascual,
A., Capet, X., Hauser, D., Stoffelen, A., Morrow, R., Aouf, L., Breivik, O.,
Fu, L.-L., Johannessen, J. A., Aksenov, Y., Bricheno, L., Hirschi, J.,
Martin, A. C. H., Martin, A. P., Nurser, G., Polton, J., Wolf, J., Johnsen,
H., Soloviev, A., Jacobs, G. A., Collard, F., Groom, S., Kudryavtsev, V.,
Wilkin, J., Navarro, V., Babanin, A., Martin, M., Siddorn, J., Saulter, A.,
Rippeth, T., Emery, B., Maximenko, N., Romeiser, R., Graber, H., Azcarate,
A. A., Hughes, C. W., Vandemark, D., Silva, J. d., Leeuwen, P. J. V.,
Naveira-Garabato, A., Gemmrich, J., Mahadevan, A., Marquez, J., Munro, Y.,
Doody, S., and Burbidge, G.: SEASTAR: A Mission to Study Ocean Submesoscale
Dynamics and Small-Scale Atmosphere-Ocean Processes in Coastal, Shelf and
Polar Seas, Frontiers in Marine Science, 6, 457, https://doi.org/10.3389/fmars.2019.00457,
2019. a
Hatakeyama, K., Hosono, M., Shimada, K., Kikuchi, T., and Nishino,
S.: JAMSTEC Compact Arctic Drifter (J-CAD): A new Generation drifting buoy
to observe the Arctic Ocean, Journal of the Japan Society for Marine Surveys
and Technology, 13, 1_55–1_68,
https://ui.adsabs.harvard.edu/abs/2012JJSMS..13.1.55H (last access: 29 September 2022), 2012. a
Hewitt, C. D., Golding, N., Zhang, P., Dunbar, T., Bett, P. E., Camp, J.,
Mitchell, T. D., and Pope, E.: The Process and Benefits of Developing
Prototype Climate Services – Examples in China, Journal of Meteorological
Research, 34, 893–903, https://doi.org/10.1007/s13351-020-0042-6, 2020. a
Hill, V. J., Light, B., Steele, M., and Zimmerman, R. C.: Light Availability and Phytoplankton Growth Beneath Arctic Sea Ice: Integrating Observations and Modeling, J. Geophys. Res.-Oceans, 123, 3651–3667, https://doi.org/10.1029/2017JC013617, 2018. a
Hoppmann, M., Kuznetsov, I., Fang, Y.-C., and Rabe, B.: Raw seawater
temperature, conductivity and salinity obtained at different depths by CTD
buoy 2019O1 as part of the MOSAiC Distributed Network, PANGAEA [data set],
https://doi.org/10.1594/PANGAEA.933934, 2021a. a
Hoppmann, M., Kuznetsov, I., Fang, Y.-C., and Rabe, B.: Raw seawater
temperature, conductivity and salinity obtained at different depths by CTD
buoy 2019O2 as part of the MOSAiC Distributed Network, PANGAEA [data set],
https://doi.org/10.1594/PANGAEA.933928, 2021b. a
Hoppmann, M., Kuznetsov, I., Fang, Y.-C., and Rabe, B.: Raw seawater
temperature, conductivity and salinity obtained at different depths by CTD
buoy 2019O3 as part of the MOSAiC Distributed Network, PANGAEA [data set],
https://doi.org/10.1594/PANGAEA.933932, 2021c. a
Hoppmann, M., Kuznetsov, I., Fang, Y.-C., and Rabe, B.: Raw seawater
temperature, conductivity and salinity obtained at different depths by CTD
buoy 2019O4 as part of the MOSAiC Distributed Network, PANGAEA [data set],
https://doi.org/10.1594/PANGAEA.933933, 2021d. a
Hoppmann, M., Kuznetsov, I., Fang, Y.-C., and Rabe, B.: Raw seawater
temperature, conductivity and salinity obtained at different depths by CTD
buoy 2019O5 as part of the MOSAiC Distributed Network, PANGAEA [data set],
https://doi.org/10.1594/PANGAEA.933937, 2021e. a
Hoppmann, M., Kuznetsov, I., Fang, Y.-C., and Rabe, B.: Raw seawater
temperature, conductivity and salinity obtained at different depths by CTD
buoy 2019O6 as part of the MOSAiC Distributed Network, PANGAEA [data set],
https://doi.org/10.1594/PANGAEA.933941, 2021f. a
Hoppmann, M., Kuznetsov, I., Fang, Y.-C., and Rabe, B.: Raw seawater
temperature, conductivity and salinity obtained at different depths by CTD
buoy 2019O7 as part of the MOSAiC Distributed Network, PANGAEA [data set],
https://doi.org/10.1594/PANGAEA.933939, 2021g. a
Hoppmann, M., Kuznetsov, I., Fang, Y.-C., and Rabe, B.: Raw seawater
temperature, conductivity and salinity obtained at different depths by CTD
buoy 2019O8 as part of the MOSAiC Distributed Network, PANGAEA [data set],
https://doi.org/10.1594/PANGAEA.933942, 2021h. a
Hoppmann, M., Kuznetsov, I., Fang, Y.-C., and Rabe, B.: Raw seawater
temperature, conductivity and salinity obtained with CTD buoys as part of the
MOSAiC Distributed Network, PANGAEA [data set], https://doi.org/10.1594/PANGAEA.937271,
2021i. a, b, c
Hoppmann, M., Kuznetsov, I., Fang, Y.-C., and Rabe, B.: Processed seawater
temperature, conductivity and salinity obtained at different depths by CTD
buoy 2019O1 as part of the MOSAiC Distributed Network, PANGAEA [data set],
https://doi.org/10.1594/PANGAEA.940271, 2022a. a
Hoppmann, M., Kuznetsov, I., Fang, Y.-C., and Rabe, B.: Processed seawater
temperature, conductivity and salinity obtained at different depths by CTD
buoy 2019O2 as part of the MOSAiC Distributed Network, PANGAEA [data set],
https://doi.org/10.1594/PANGAEA.940298, 2022b. a
Hoppmann, M., Kuznetsov, I., Fang, Y.-C., and Rabe, B.: Processed seawater
temperature, conductivity and salinity obtained at different depths by CTD
buoy 2019O3 as part of the MOSAiC Distributed Network, PANGAEA [data set],
https://doi.org/10.1594/PANGAEA.940282, 2022c. a
Hoppmann, M., Kuznetsov, I., Fang, Y.-C., and Rabe, B.: Processed seawater
temperature, conductivity and salinity obtained at different depths by CTD
buoy 2019O4 as part of the MOSAiC Distributed Network, PANGAEA [data set],
https://doi.org/10.1594/PANGAEA.940291, 2022d. a
Hoppmann, M., Kuznetsov, I., Fang, Y.-C., and Rabe, B.: Processed seawater
temperature, conductivity and salinity obtained at different depths by CTD
buoy 2019O5 as part of the MOSAiC Distributed Network, PANGAEA [data set],
https://doi.org/10.1594/PANGAEA.940301, 2022e. a
Hoppmann, M., Kuznetsov, I., Fang, Y.-C., and Rabe, B.: Processed seawater
temperature, conductivity and salinity obtained at different depths by CTD
buoy 2019O6 as part of the MOSAiC Distributed Network, PANGAEA [data set],
https://doi.org/10.1594/PANGAEA.940296, 2022f. a
Hoppmann, M., Kuznetsov, I., Fang, Y.-C., and Rabe, B.: Processed seawater
temperature, conductivity and salinity obtained at different depths by CTD
buoy 2019O7 as part of the MOSAiC Distributed Network, PANGAEA [data set],
https://doi.org/10.1594/PANGAEA.940303, 2022g. a
Hoppmann, M., Kuznetsov, I., Fang, Y.-C., and Rabe, B.: Processed seawater
temperature, conductivity and salinity obtained at different depths by CTD
buoy 2019O8 as part of the MOSAiC Distributed Network, PANGAEA [data set],
https://doi.org/10.1594/PANGAEA.940304, 2022h. a
Hoppmann, M., Kuznetsov, I., Fang, Y.-C., and Rabe, B.: Processed data of CTD
buoys 2019O1 to 2019O8 as part of the MOSAiC Distributed Network, PANGAEA [data set],
https://doi.org/10.1594/PANGAEA.940320, 2022i. a, b, c
Huang, X., Wang, Z., Zhang, Z., Yang, Y., Zhou, C., Yang, Q., Zhao, W., and
Tian, J.: Role of Mesoscale Eddies in Modulating the Semidiurnal Internal
Tide: Observation Results in the Northern South China Sea, J.
Phys. Oceanogr., 48, 1749–1770, https://doi.org/10.1175/JPO-D-17-0209.1, 2018. a
Ilicak, M., Drange, H., Wang, Q., Gerdes, R., Aksenov, Y., Bailey, D., Bentsen,
M., Biastoch, A., Bozec, A., Boening, C., Cassou, C., Chassignet, E., Coward,
A. C., Curry, B., Danabasoglu, G., Danilov, S., Fernandez, E., Fogli, P. G.,
Fujii, Y., Griffies, S. M., Iovino, D., Jahn, A., Jung, T., Large, W. G.,
Lee, C., Lique, C., Lu, J., Masina, S., Nurser, A. J. G., Roth, C., Salas y
Melia, D., Samuels, B. L., Spence, P., Tsujino, H., Valcke, S., Voldoire, A.,
Wang, X., and Yeager, S. G.: An assessment of the Arctic Ocean in a suite of
interannual CORE-II simulations. Part III: Hydrography and fluxes, Ocean
Model., 100, 141–161, https://doi.org/10.1016/j.ocemod.2016.02.004, 2016. a
Jackson, K., Wilkinson, J., Maksym, T., Beckers, J., Haas, C., Meldrum, D., and
Mackenzie, D.: A Novel and Low Cost Sea Ice Mass Balance Buoy, J.
Atmos. Ocean. Tech., 30, 2676–2688, https://doi.org/10.1175/jtech-d-13-00058.1, 2013. a
Jakobsson, M., Mayer, L. A., Bringensparr, C., Castro, C. F., Mohammad, R.,
Johnson, P., Ketter, T., Accettella, D., Amblas, D., An, L., Arndt, J. E.,
Canals, M., Casamor, J. L., Chauché, N., Coakley, B., Danielson, S.,
Demarte, M., Dickson, M.-L., Dorschel, B., Dowdeswell, J. A., Dreutter, S.,
Fremand, A. C., Gallant, D., Hall, J. K., Hehemann, L., Hodnesdal, H., Hong,
J., Ivaldi, R., Kane, E., Klaucke, I., Krawczyk, D. W., Kristoffersen, Y.,
Kuipers, B. R., Millan, R., Masetti, G., Morlighem, M., Noormets, R.,
Prescott, M. M., Rebesco, M., Rignot, E., Semiletov, I., Tate, A. J.,
Travaglini, P., Velicogna, I., Weatherall, P., Weinrebe, W., Willis, J. K.,
Wood, M., Zarayskaya, Y., Zhang, T., Zimmermann, M., and Zinglersen, K. B.:
The International Bathymetric Chart of the Arctic Ocean Version 4.0,
Scientific Data, 7, 176, https://doi.org/10.1038/s41597-020-0520-9, 2020. a
Jochum, M. and Murtugudde, R. (Eds.): Physical Oceanography: Developments Since
1950, 1st Edn., Springer-Verlag New York, https://doi.org/10.1007/0-387-33152-2, 2006. a
Kaiser, P., Hagen, W., von Appen, W.-J., Niehoff, B., Hildebrandt, N., and
Auel, H.: Effects of a submesoscale oceanographic filament on zooplankton
dynamics in the Arctic marginal ice zone, Frontiers in Marine Research, 8, 625395,
https://doi.org/10.3389/fmars.2021.625395, 2021. a
Kikuchi, T., Inoue, J., and Langevin, D.: Argo-type profiling float
observations under the Arctic multiyear ice, Deep-Sea Res. I, 54,
1675–1686, https://doi.org/10.1016/j.dsr.2007.05.011, 2007. a
Koenig, Z., Provost, C., Villacieros-Robineau, N., Sennechael, N., and Meyer,
A.: Winter ocean-ice interactions under thin sea ice observed by IAOOS
platforms during N-ICE2015: Salty surface mixed layer and active basal melt,
J. Geophys. Res.-Oceans, 121, 7898–7916,
https://doi.org/10.1002/2016JC012195, 2016. a
Krumpen, T., Birrien, F., Kauker, F., Rackow, T., von Albedyll, L., Angelopoulos, M., Belter, H. J., Bessonov, V., Damm, E., Dethloff, K., Haapala, J., Haas, C., Harris, C., Hendricks, S., Hoelemann, J., Hoppmann, M., Kaleschke, L., Karcher, M., Kolabutin, N., Lei, R., Lenz, J., Morgenstern, A., Nicolaus, M., Nixdorf, U., Petrovsky, T., Rabe, B., Rabenstein, L., Rex, M., Ricker, R., Rohde, J., Shimanchuk, E., Singha, S., Smolyanitsky, V., Sokolov, V., Stanton, T., Timofeeva, A., Tsamados, M., and Watkins, D.: The MOSAiC ice floe: sediment-laden survivor from the Siberian shelf, The Cryosphere, 14, 2173–2187, https://doi.org/10.5194/tc-14-2173-2020, 2020. a
Lee, C. M., Thomson, J., Team, M. I. Z., and Team, A. S. S.: An Autonomous
Approach to Observing the Seasonal Ice Zone in the Western Arctic,
Oceanography, 30, 56–68, https://doi.org/10.5670/oceanog.2017.222, 2017. a
Lévy, M., Iovino, D., Resplandy, L., Klein, P., Madec, G.,
Tréguier, A.-M., Masson, S., and Takahashi, K.: Large-scale impacts of
submesoscale dynamics on phytoplankton: Local and remote effects, Ocean
Model., 43-44, 77–93, https://doi.org/10.1016/j.ocemod.2011.12.003, 2012. a
Lévy, M., Franks, P., and Smith, K. S.: The role of submesoscale
currents in structuring marine ecosystems, Nat. Commun., 9, 4758,
https://doi.org/10.1038/s41467-018-07059-3, 2018. a
Mahadevan, A.: The Impact of Submesoscale Physics on Primary Productivity of
Plankton, Annu. Rev. Mar. Sci., 8, 161–184,
https://doi.org/10.1146/annurev-marine-010814-015912, 2016. a
Mahadevan, A., Tandon, A., and Ferrari, R.: Rapid changes in mixed layer
stratification driven by submesoscale instabilities and winds, J.
Geophys. Res.-Oceans, 115, C03017, https://doi.org/10.1029/2008JC005203, 2010. a, b
Manley, T. O. and Hunkins, K.: Mesoscale eddies of the Arctic Ocean, J. Geophys. Res.-Oceans, 90, 4911–4930,
https://doi.org/10.1029/JC090iC03p04911, 1985. a
Manucharyan, G. E. and Thompson, A. F.: Submesoscale Sea Ice-Ocean
Interactions in Marginal Ice Zones, J. Geophys. Res.-Oceans,
122, 9455–9475, https://doi.org/10.1002/2017JC012895, 2017. a
Manucharyan, G. E. and Timmermans, M.-L.: Generation and Separation of
Mesoscale Eddies from Surface Ocean Fronts, J. Phys.
Oceanogr., 43, 2545–2562, https://doi.org/10.1175/JPO-D-13-094.1, 2013. a
Marcinko, C. L., Martin, A. P., and Allen, J. T.: Characterizing horizontal
variability and energy spectra in the Arctic Ocean halocline, J.
Geophys. Res.-Oceans, 120, 436–450, https://doi.org/10.1002/2014JC010381,
2015. a
McGillicuddy, D. J.: Mechanisms of Physical-Biological-Biogeochemical
Interaction at the Oceanic Mesoscale, Annu. Rev. Mar. Sci., 8,
125–159, https://doi.org/10.1146/annurev-marine-010814-015606, 2016. a
McWilliams, J. C.: Maps from the Mid-Ocean Dynamics Experiment: Part I.
Geostrophic Streamfunction, J. Phys. Oceanogr., 6, 810–827,
https://doi.org/10.1175/1520-0485(1976)006<0810:MFTMOD>2.0.CO;2, 1976. a
McWilliams, J. C.: Submesoscale currents in the ocean, P. R. Soc. A, 472, 20160117, https://doi.org/10.1098/rspa.2016.0117, 2016. a
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,
2021a. a
Nicolaus, M., Riemann-Campe, K., Hutchings, J. K., Granskog, M. A., Krishfield,
R. A., Lei, R., Li, T., Hoppmann, M., and Rabe, B.: Drift trajectories of the
main sites of the Distributed Network of MOSAiC 2019/2020, PANGAEA [data set],
https://doi.org/10.1594/PANGAEA.937204, 2021b. a
Nicolaus, M., Perovich, D. K., Spreen, G., Granskog, M. A., von Albedyll, L.,
Angelopoulos, M., Anhaus, P., Arndt, S., Belter, H. J., Bessonov, V.,
Birnbaum, G., Brauchle, J., Calmer, R., Cardellach, E., Cheng, B.,
Clemens-Sewall, D., Dadic, R., Damm, E., de Boer, G., Demir, O., Dethloff,
K., Divine, D. V., Fong, A. A., Fons, S., Frey, M. M., Fuchs, N., Gabarró,
C., Gerland, S., Goessling, H. F., Gradinger, R., Haapala, J., Haas, C.,
Hamilton, J., Hannula, H.-R., Hendricks, S., Herber, A., Heuzé, C.,
Hoppmann, M., Høyland, K. V., Huntemann, M., Hutchings, J. K., Hwang, B.,
Itkin, P., Jacobi, H.-W., Jaggi, M., Jutila, A., Kaleschke, L., Katlein, C.,
Kolabutin, N., Krampe, D., Kristensen, S. S., Krumpen, T., Kurtz, N.,
Lampert, A., Lange, B. A., Lei, R., Light, B., Linhardt, F., Liston, G. E.,
Loose, B., Macfarlane, A. R., Mahmud, M., Matero, I. O., Maus, S.,
Morgenstern, A., Naderpour, R., Nandan, V., Niubom, A., Oggier, M., Oppelt,
N., Pätzold, F., Perron, C., Petrovsky, T., Pirazzini, R., Polashenski, C.,
Rabe, B., Raphael, I. A., Regnery, J., Rex, M., Ricker, R., Riemann-Campe,
K., Rinke, A., Rohde, J., Salganik, E., Scharien, R. K., Schiller, M.,
Schneebeli, M., Semmling, M., Shimanchuk, E., Shupe, M. D., Smith, M. M.,
Smolyanitsky, V., Sokolov, V., Stanton, T., Stroeve, J., Thielke, L.,
Timofeeva, A., Tonboe, R. T., Tavri, A., Tsamados, M., et al.: Overview of
the MOSAiC expedition: Snow and sea ice, Elementa: Science of the
Anthropocene, 10, 000046, https://doi.org/10.1525/elementa.2021.000046, 2022. a
Nixdorf, U., Dethloff, K., Rex, M., Shupe, M., Sommerfeld, A., Perovich, D. K.,
Nicolaus, M., Heuzé, C., Rabe, B., Loose, B., Damm, E., Gradinger, R., Fong,
A., Maslowski, W., Rinke, A., Kwok, R., Spreen, G., Wendisch, M., Herber, A.,
Hirsekorn, M., Mohaupt, V., Frickenhaus, S., Immerz, A., Weiss-Tuider, K.,
König, B., Mengedoht, D., Regnery, J., Gerchow, P., Ransby, D., Krumpen, T.,
Morgenstern, A., Haas, C., Kanzow, T., Rack, F. R., Saitzev, V., Sokolov, V.,
Makarov, A., Schwarze, S., Wunderlich, T., Wurr, K., and Boetius, A.: MOSAiC
Extended Acknowledgement, Zenodo, https://doi.org/10.5281/zenodo.5541624, 2021. a
Nurser, A. J. G. and Bacon, S.: The Rossby radius in the Arctic Ocean, Ocean Sci., 10, 967–975, https://doi.org/10.5194/os-10-967-2014, 2014. a, b
Ocean University of China: The Drift-Towing Ocean Profiler,
http://coas.ouc.edu.cn/pogoc/2021/0713/c9714a342585/page.htm (last access: 29 September 2022),
2021. a
Polyakov, I. V., Pnyushkov, A. V., Rember, R., Padman, L., Carmack, E. C., and
Jackson, J. M.: Winter Convection Transports Atlantic Water Heat to the
Surface Layer in the Eastern Arctic Ocean, J. Phys.
Oceanogr., 43, 2142–2155, https://doi.org/10.1175/JPO-D-12-0169.1, 2013. a
Porter, M., Henley, S. F., Orkney, A., Bouman, H. A., Hwang, B., Dumont, E.,
Venables, E. J., and Cottier, F.: A Polar Surface Eddy Obscured by Thermal
Stratification, Geophys. Res. Lett., 47, e2019GL086281,
https://doi.org/10.1029/2019GL086281, 2020. a
Rabe, B., Heuzé, C., Regnery, J., Aksenov, Y., Allerholt, J., Athanase, M.,
Bai, Y., Basque, C., Bauch, D., Baumann, T. M., Chen, D., Cole, S. T., Craw,
L., Davies, A., Damm, E., Dethloff, K., Divine, D. V., Doglioni, F., Ebert,
F., Fang, Y.-C., Fer, I., Fong, A. A., Gradinger, R., Granskog, M. A.,
Graupner, R., Haas, C., He, H., He, Y., Hoppmann, M., Janout, M., Kadko, D.,
Kanzow, T., Karam, S., Kawaguchi, Y., Koenig, Z., Kong, B., Krishfield,
R. A., Krumpen, T., Kuhlmey, D., Kuznetsov, I., Lan, M., Laukert, G., Lei,
R., Li, T., Torres-Valdés, S., Lin, L., Lin, L., Liu, H., Liu, N., Loose,
B., Ma, X., McKay, R., Mallet, M., Mallett, R. D. C., Maslowski, W., Mertens,
C., Mohrholz, V., Muilwijk, M., Nicolaus, M., O’Brien, J. K., Perovich, D.,
Ren, J., Rex, M., Ribeiro, N., Rinke, A., Schaffer, J., Schuffenhauer, I.,
Schulz, K., Shupe, M. D., Shaw, W., Sokolov, V., Sommerfeld, A., Spreen, G.,
Stanton, T., Stephens, M., Su, J., Sukhikh, N., Sundfjord, A., Thomisch, K.,
Tippenhauer, S., Toole, J. M., Vredenborg, M., Walter, M., Wang, H., Wang,
L., Wang, Y., Wendisch, M., Zhao, J., Zhou, M., and Zhu, J.: Overview of the
MOSAiC expedition: Physical oceanography, Elementa: Science of the
Anthropocene, 10, 00062, https://doi.org/10.1525/elementa.2021.00062, 2022. a, b, c
Schulz, K., Mohrholz, V., Fer, I., Janout, M., Hoppmann, M., Schaffer, J., and Koenig, Z.: A full year of turbulence measurements from a drift campaign in the Arctic Ocean 2019–2020, Sci. Data, 9, 472, https://doi.org/10.1038/s41597-022-01574-1, 2022. a
Shupe, M. D., Rex, M., Blomquist, B., Persson, P. O. G., Schmale, J., Uttal,
T., Althausen, D., Angot, H., Archer, S., Bariteau, L., Beck, I., Bilberry,
J., Bucci, S., Buck, C., Boyer, M., Brasseur, Z., Brooks, I. M., Calmer, R.,
Cassano, J., Castro, V., Chu, D., Costa, D., Cox, C. J., Creamean, J.,
Crewell, S., Dahlke, S., Damm, E., de Boer, G., Deckelmann, H., Dethloff, K.,
Dütsch, M., Ebell, K., Ehrlich, A., Ellis, J., Engelmann, R., Fong, A. A.,
Frey, M. M., Gallagher, M. R., Ganzeveld, L., Gradinger, R., Graeser, J.,
Greenamyer, V., Griesche, H., Griffiths, S., Hamilton, J., Heinemann, G.,
Helmig, D., Herber, A., Heuzé, C., Hofer, J., Houchens, T., Howard, D.,
Inoue, J., Jacobi, H.-W., Jaiser, R., Jokinen, T., Jourdan, O., Jozef, G.,
King, W., Kirchgaessner, A., Klingebiel, M., Krassovski, M., Krumpen, T.,
Lampert, A., Landing, W., Laurila, T., Lawrence, D., Lonardi, M., Loose, B.,
Lüpkes, C., Maahn, M., Macke, A., Maslowski, W., Marsay, C., Maturilli, M.,
Mech, M., Morris, S., Moser, M., Nicolaus, M., Ortega, P., Osborn, J.,
Pätzold, F., Perovich, D. K., Petäjä, T., Pilz, C., Pirazzini, R., Posman,
K., Powers, H., Pratt, K. A., Preußer, A., Quéléver, L., Radenz, M., Rabe,
B., Rinke, A., Sachs, T., Schulz, A., Siebert, H., Silva, T., Solomon, A.,
Sommerfeld, A., et al.: Overview of the MOSAiC expedition – Atmosphere,
Elementa: Science of the Anthropocene, 10, 00060,
https://doi.org/10.1525/elementa.2021.00060, 2022. a
Smith, K. S.: The geography of linear baroclinic instability in Earth's
oceans, J. Mar. Res., 65, 655–683,
https://doi.org/10.1357/002224007783649484, 2007. a, b
Stedmon, C. A., Amon, R. M. W., Bauch, D., Bracher, A., Gonçalves-Araujo, R., Hoppmann, M., Krishfield, R., Laney, S., Rabe, B., Reader, H., and Granskog, M. A.: Insights into Water Mass Circulation and Origins in the Central
Arctic Ocean from in-situ Dissolved Organic Matter Fluorescence, J.
Geophys. Res.-Oceans, 126, e2021JC017407, https://doi.org/10.1029/2021JC017407, 2021. a
Steele, M.: UpTempO buoys deployed in the Arctic Ocean in 2017, Arctic Data
Center [data set], https://doi.org/10.18739/A2JS9H85P, 2017. a
Thomas, L. N.: Destruction of Potential Vorticity by Winds, J.
Phys. Oceanogr., 35, 2457–2466, https://doi.org/10.1175/JPO2830.1, 2005. a
Thomas, L. N., Tandon, A., and Mahadevan, A.: Submesoscale Processes and
Dynamics, in: Ocean Modeling in an Eddying Regime, Vol. 177, edited by: Hecht, M. W. and Hasumi, H., Geophysical Monograph Series, American Geophysical Union, https://doi.org/10.1029/177GM04, 2008. a, b
Timmermans, M.-L. and Marshall, J.: Understanding Arctic Ocean Circulation: A
Review of Ocean Dynamics in a Changing Climate, J. Geophys.
Res.-Oceans, 125, e2018JC014378, https://doi.org/10.1029/2018JC014378, 2020. a
Timmermans, M.-L., Cole, S., and Toole, J.: Horizontal Density Structure and
Restratification of the Arctic Ocean Surface Layer, J. Phys.
Oceanogr., 42, 659–668, https://doi.org/10.1175/JPO-D-11-0125.1, 2012. a, b
Toole, J., Krishfield, R., Proshutinsky, A., Ashjian, C., Doherty, K., Frye,
D., Hammar, T., Kemp, J., Peters, D., Timmermans, M.-L., von der Heydt, K.,
Packard, G., and Shanahan, T.: Ice-tethered profilers sample the upper Arctic
Ocean, Eos, Transactions American Geophysical Union, 87, 434–438,
https://doi.org/10.1029/2006EO410003, 2006.
a, b, c
UNESCO-IOC: Ocean Data Standards Volume 3. Recommendation for a Quality Flag
Scheme for the Exchange of Oceanographic and Marine Meteorological Data,
https://doi.org/10.25607/OBP-6, 2013. a, b
von Appen, W. J., Wekerle, C., Hehemann, L., Schourup-Kristensen, V., Konrad,
C., and Iversen, M. H.: Observations of a Submesoscale Cyclonic Filament in
the Marginal Ice Zone, Geophys. Res. Lett., 45, 6141–6149,
https://doi.org/10.1029/2018GL077897, 2018. a
von Appen, W.-J., Baumann, T., Janout, M., Koldunov, N., Lenn, Y.-D., Pickart,
R., Scott, R., and Wang, Q.: Eddies and the Distribution of Eddy Kinetic
Energy in the Arctic Ocean, Oceanography, 35,
https://doi.org/10.5670/oceanog.2022.122, 2022. a
Wang, Q., Koldunov, N. V., Danilov, S., Sidorenko, D., Wekerle, C., Scholz, P.,
Bashmachnikov, I. L., and Jung, T.: Eddy Kinetic Energy in the Arctic Ocean
From a Global Simulation With a 1-km Arctic, Geophys. Res. Lett.,
47, e2020GL088550, https://doi.org/10.1029/2020GL088550, 2020. a, b
Wessel, P. and Smith, W. H. F.: A global, self-consistent, hierarchical,
high-resolution shoreline database, J. Geophys. Res.-Sol.
Ea., 101, 8741–8743, https://doi.org/10.1029/96JB00104, 1996. a
Zhang, X., Dai, H., Zhao, J., and Yin, H.: Generation mechanism of an observed
submesoscale eddy in the Chukchi Sea, Deep-Sea Res. Pt. I, 148, 80–87, https://doi.org/10.1016/j.dsr.2019.04.015,
2019. a
Zhao, M., Timmermans, M.-L., Cole, S., Krishfield, R., Proshutinsky, A., and
Toole, J.: Characterizing the eddy field in the Arctic Ocean halocline,
J. Geophys. Res.-Oceans, 119, 8800–8817,
https://doi.org/10.1002/2014JC010488, 2014. a, b, c
Zhao, M., Timmermans, M.-L., Cole, S., Krishfield, R., and Toole, J.:
Evolution of the eddy field in the Arctic Ocean's Canada Basin, 2005–2015,
Geophys. Res. Lett., 43, 8106–8114,
https://doi.org/10.1002/2016GL069671, 2016. a, b
Short summary
The role of eddies and fronts in the oceans is a hot topic in climate research, but there are still many related knowledge gaps, particularly in the ice-covered Arctic Ocean. Here we present a unique dataset of ocean observations collected by a set of drifting buoys installed on ice floes as part of the 2019/2020 MOSAiC campaign. The buoys recorded temperature and salinity data for 10 months, providing extraordinary insights into the properties and processes of the ocean along their drift.
The role of eddies and fronts in the oceans is a hot topic in climate research, but there are...
Altmetrics
Final-revised paper
Preprint