Articles | Volume 15, issue 3
https://doi.org/10.5194/tc-15-1321-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-15-1321-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
12 Mar 2021
Research article |
| 12 Mar 2021
| 12 Mar 2021
Seasonal changes in sea ice kinematics and deformation in the Pacific sector of the Arctic Ocean in 2018/19
Key Laboratory for Polar Science of the MNR, Polar Research Institute
of China, Shanghai, China
Mario Hoppmann
Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und
Meeresforschung, Bremerhaven, Germany
Bin Cheng
Finnish Meteorological Institute, Helsinki, Finland
Guangyu Zuo
Key Laboratory for Polar Science of the MNR, Polar Research Institute
of China, Shanghai, China
College of Electrical and Power Engineering, Taiyuan University of
Technology, Taiyuan, China
Dawei Gui
Key Laboratory for Polar Science of the MNR, Polar Research Institute
of China, Shanghai, China
Chinese Antarctic Center of Surveying and Mapping, Wuhan University,
Wuhan, China
Qiongqiong Cai
National Marine Environmental Forecasting Center of the MNR,
Beijing, China
H. Jakob Belter
Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und
Meeresforschung, Bremerhaven, Germany
Wangxiao Yang
College of Electrical and Power Engineering, Taiyuan University of
Technology, Taiyuan, China
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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.
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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.
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The Cryosphere, 18, 273–288, https://doi.org/10.5194/tc-18-273-2024, https://doi.org/10.5194/tc-18-273-2024, 2024
Short summary
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Variations in Arctic sea ice are related not only to its macroscale properties but also to its microstructure. Arctic ice cores in the summers of 2008 to 2016 were used to analyze variations in the ice inherent optical properties related to changes in the ice microstructure. The results reveal changing ice microstructure greatly increased the amount of solar radiation transmitted to the upper ocean even when a constant ice thickness was assumed, especially in marginal ice zones.
Fanyi Zhang, Ruibo Lei, Mengxi Zhai, Xiaoping Pang, and Na Li
The Cryosphere, 17, 4609–4628, https://doi.org/10.5194/tc-17-4609-2023, https://doi.org/10.5194/tc-17-4609-2023, 2023
Short summary
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Atmospheric circulation anomalies lead to high Arctic sea ice outflow in winter 2020, causing heavy ice conditions in the Barents–Greenland seas, subsequently impeding the sea surface temperature warming. This suggests that the winter–spring Arctic sea ice outflow can be considered a predictor of changes in sea ice and other marine environmental conditions in the Barents–Greenland seas, which could help to improve our understanding of the physical connections between them.
Ying Chen, Ruibo Lei, Xi Zhao, Shengli Wu, Yue Liu, Pei Fan, Qing Ji, Peng Zhang, and Xiaoping Pang
Earth Syst. Sci. Data, 15, 3223–3242, https://doi.org/10.5194/essd-15-3223-2023, https://doi.org/10.5194/essd-15-3223-2023, 2023
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Vishnu Nandan, Rosemary Willatt, Robbie Mallett, Julienne Stroeve, Torsten Geldsetzer, Randall Scharien, Rasmus Tonboe, John Yackel, Jack Landy, David Clemens-Sewall, Arttu Jutila, David N. Wagner, Daniela Krampe, Marcus Huntemann, Mallik Mahmud, David Jensen, Thomas Newman, Stefan Hendricks, Gunnar Spreen, Amy Macfarlane, Martin Schneebeli, James Mead, Robert Ricker, Michael Gallagher, Claude Duguay, Ian Raphael, Chris Polashenski, Michel Tsamados, Ilkka Matero, and Mario Hoppmann
The Cryosphere, 17, 2211–2229, https://doi.org/10.5194/tc-17-2211-2023, https://doi.org/10.5194/tc-17-2211-2023, 2023
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We show that wind redistributes snow on Arctic sea ice, and Ka- and Ku-band radar measurements detect both newly deposited snow and buried snow layers that can affect the accuracy of snow depth estimates on sea ice. Radar, laser, meteorological, and snow data were collected during the MOSAiC expedition. With frequent occurrence of storms in the Arctic, our results show that
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Yafei Nie, Chengkun Li, Martin Vancoppenolle, Bin Cheng, Fabio Boeira Dias, Xianqing Lv, and Petteri Uotila
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The Cryosphere, 17, 917–937, https://doi.org/10.5194/tc-17-917-2023, https://doi.org/10.5194/tc-17-917-2023, 2023
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Ruibo Lei, Mario Hoppmann, Bin Cheng, Marcel Nicolaus, Fanyi Zhang, Benjamin Rabe, Long Lin, Julia Regnery, and Donald K. Perovich
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Manuscript not accepted for further review
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Short summary
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Atmos. Chem. Phys., 22, 4413–4469, https://doi.org/10.5194/acp-22-4413-2022, https://doi.org/10.5194/acp-22-4413-2022, 2022
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We summarize results during the last 5 years in the northern Eurasian region, especially from Russia, and introduce recent observations of the air quality in the urban environments in China. Although the scientific knowledge in these regions has increased, there are still gaps in our understanding of large-scale climate–Earth surface interactions and feedbacks. This arises from limitations in research infrastructures and integrative data analyses, hindering a comprehensive system analysis.
Yu Liang, Haibo Bi, Haijun Huang, Ruibo Lei, Xi Liang, Bin Cheng, and Yunhe Wang
The Cryosphere, 16, 1107–1123, https://doi.org/10.5194/tc-16-1107-2022, https://doi.org/10.5194/tc-16-1107-2022, 2022
Short summary
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A record minimum July sea ice extent, since 1979, was observed in 2020. Our results reveal that an anomalously high advection of energy and water vapor prevailed during spring (April to June) 2020 over regions with noticeable sea ice retreat. The large-scale atmospheric circulation and cyclones act in concert to trigger the exceptionally warm and moist flow. The convergence of the transport changed the atmospheric characteristics and the surface energy budget, thus causing a severe sea ice melt.
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.
Bin Cheng, Yubing Cheng, Timo Vihma, Anna Kontu, Fei Zheng, Juha Lemmetyinen, Yubao Qiu, and Jouni Pulliainen
Earth Syst. Sci. Data, 13, 3967–3978, https://doi.org/10.5194/essd-13-3967-2021, https://doi.org/10.5194/essd-13-3967-2021, 2021
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Climate change strongly impacts the Arctic, with clear signs of higher air temperature and more precipitation. A sustainable observation programme has been carried out in Lake Orajärvi in Sodankylä, Finland. The high-quality air–snow–ice–water temperature profiles have been measured every winter since 2009. The data can be used to investigate the lake ice surface heat balance and the role of snow in lake ice mass balance and parameterization of snow-to-ice transformation in snow/ice models.
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.
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.
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
Cited articles
Ackley, S. F. and Sullivan, C. W.: Physical controls on the development and
characteristics of Antarctic sea ice biological communities – a review and
synthesis, Deep-Sea Res., 41, 1583–1604, 1994.
Alam, A. and Curry, J. A.: Evolution of new ice and turbulent fluxes over
freezing winter leads, J. Geophys. Res.-Oceans, 103, 15783–15802, 1998.
Armitage, T. W. K., Bacon, S., Ridout, A. L., Petty, A. A., Wolbach, S., and Tsamados, M.: Arctic Ocean surface geostrophic circulation 2003–2014, The Cryosphere, 11, 1767–1780, https://doi.org/10.5194/tc-11-1767-2017, 2017.
Assmy, P., Fernández-Méndez, M., Duarte, P., Meyer, A., Randelhoff, A., Mundy, C. J., Olsen, L. M., Kauko, H. M., Bailey, A., Chierici, M., Cohen, L., Doulgeris, A. P., Ehn, J. K., Fransson, A., Gerland, S., Hop, H., Hudson, S. R., Hughes, N., Itkin, P., Johnsen, G., King, J. A., Koch, B. P., Koenig, Z., Kwasniewski, S., Laney, S. R., Nicolaus, M., Pavlov, A. K., Polashenski, C. M., Provost, C., Rösel, A., Sandbu, M., Spreen, G., Smedsrud, L. H., Sundfjord, A., Taskjelle, T., Tatarek A., Wiktor J., Wagner, P. M., Wold, A., Steen, H., and Granskog, M. A.:
Leads in Arctic pack ice enable early phytoplankton blooms below
snow-covered sea ice, Sci. Rep., 7, 40850, https://doi.org/10.1038/srep40850,
2017.
Belter, H. J., Hummel, S., Hansen, M. L. S., and Nicolaus, M.: Snow height on sea ice and sea ice drift from autonomous measurements from buoy 2018S76, deployed during AKADEMIK TRYOSHNIKOV cruise TRANSDRIFT XXIV (TICE), Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven, PANGAEA, https://doi.org/10.1594/PANGAEA.905725, 2019.
Bi, H., Yang, Q., Liang, X., Zhang, L., Wang, Y., Liang, Y., and Huang, H.: Contributions of advection and melting processes to the decline in sea ice in the Pacific sector of the Arctic Ocean, The Cryosphere, 13, 1423–1439, https://doi.org/10.5194/tc-13-1423-2019, 2019.
Comiso, J. C., Meier, W. N., and Gersten, R.: Variability and trends in the
Arctic sea ice cover: results from different techniques, J. Geophys. Res.-Oceans, 122, 6883–6900, https://doi.org/10.1002/2017JC012768, 2017.
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A. C. M., Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B., Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P., Köhler, M., Matricardi, M., McNally, A. P., Monge‐Sanz, B. M., Morcrette, J.‐J., Park, B.-K., Peubey, C., Rosnay, P., Tavolato, C., Thépaut, J.-N., and Vitart, F.: The ERA-interim
reanalysis: configuration and performance of the data assimilation system,
Q. J. Roy. Meteor. Soc., 137, 553–597,
https://doi.org/10.1002/qj.828, 2011.
Ding, Q., Schweiger, A., L'Heureux, M., Battisti, D. S., Po-Chedley, S.,
Johnson, N. C., Blanchard-Wrigglesworth, E., Harnos, K., Zhang, Q., Eastman,
R., and Steig, E. J.: Influence of high-latitude atmospheric circulation
changes on summertime Arctic sea ice, Nat. Clim. Change, 7, 289–295,
2017.
Fernández-Méndez, M., Olsen, L. M., Kauko, H. M., Meyer, A., Rösel, A., Merkouriadi, I., Mundy, C. J., Ehn, J. K., Johansson, A. M., Wagner, P. M., Ervik, Å., Sorrell, B. K., Duarte, P., Wold, A., Hop, H., and Assmy, P.: Algal hot spots in a changing Arctic Ocean: sea-ice ridges and
the snow-ice interface, Front. Mar. Sci., 5, 75,
https://doi.org/10.3389/fmars.2018.00075, 2018.
Fetterer, F., Knowles, K., Meier, W. N., Savoie, M., and Windnagel, A. K.:
Updated daily sea ice index, version 3, sea ice concentration, Boulder,
Colorado, USA, NSIDC: National Snow and Ice Data Center,
https://doi.org/10.7265/N5K072F8, 2017.
Geiger, C. A. and Perovich, D. K.: Springtime ice motion in the western
Antarctic Peninsula region, Deep-Sea Res., 55, 338–350, 2008.
Gimbert, F., Marsan, D., Weiss, J., Jourdain, N. C., and Barnier, B.: Sea ice inertial oscillations in the Arctic Basin, The Cryosphere, 6, 1187–1201, https://doi.org/10.5194/tc-6-1187-2012, 2012.
Haller, M., Brümmer, B., and Müller, G.: Atmosphere–ice forcing in the transpolar drift stream: results from the DAMOCLES ice-buoy campaigns 2007–2009, The Cryosphere, 8, 275–288, https://doi.org/10.5194/tc-8-275-2014, 2014.
Heil, P. and Hibler III, W. D.: Modeling the high-frequency component of
Arctic sea ice drift and deformation, J. Phys. Oceanogr., 32, 3039–3057,
2002.
Held, A., Brooks, I. M., Leck, C., and Tjernström, M.: On the potential contribution of open lead particle emissions to the central Arctic aerosol concentration, Atmos. Chem. Phys., 11, 3093–3105, https://doi.org/10.5194/acp-11-3093-2011, 2011.
Herman, A. and Glowacki, O.: Variability of sea ice deformation rates in the Arctic and their relationship with basin-scale wind forcing, The Cryosphere, 6, 1553–1559, https://doi.org/10.5194/tc-6-1553-2012, 2012.
Hoppmann, M., Belter, H. J., and Riemann-Campe, K.: GPS data of selected drifting buoys deployed in the Pacific sector of the Arctic Ocean during the TRANSDRIFT/TICE/NABOS expedition in summer 2018, Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven, PANGAEA, https://doi.org/10.1594/PANGAEA.927592, 2021.
Hutchings, J. K. and Hibler III, W. D.: Small-scale sea ice deformation in
the Beaufort Sea seasonal ice zone, J. Geophys. Res., 113, C08032,
https://doi.org/10.1029/2006JC003971, 2008.
Hutchings, J. K., Roberts, A., Geiger, C. A., and Richter-Menge, J.: Spatial
and temporal characterization of sea-ice deformation, Ann. Glaciol., 52,
360–368, 2011.
Hutchings, J. K., Heil, P., Steer, A., and Hibler III, W. D.: Subsynoptic
scale spatial variability of sea ice deformation in the western Weddell Sea
during early summer, J. Geophys. Res., 117, C01002,
https://doi.org/10.1029/2011JC006961, 2012.
Hutchings, J. K., Roberts, A., Geiger, C. A., and Richter-Menge, J.:
Corrigendum: Spatial and temporal characterization of sea-ice deformation,
J. Glaciol., 64, 343–346, 2018.
Hutter, N. and Losch, M.: Feature-based comparison of sea ice deformation in lead-permitting sea ice simulations, The Cryosphere, 14, 93–113, https://doi.org/10.5194/tc-14-93-2020, 2020.
Hutter, N., Losch, M., and Menemenlis, D.: Scaling properties of arctic sea
ice deformation in a high-resolution viscous-plastic sea ice model and in
satellite observations, J. Geophys. Res.-Oceans, 123, 672–687,
https://doi.org/10.1002/2017JC013119, 2018.
Itkin, P., Spreen, G., Cheng, B., Doble, M., Girard-Ardhuin, F., Haapala,
J., Hughes, N., Kaleschke, L., Nicolaus, M., and Wilkinson, J.: Thin ice and
storms: Sea ice deformation from buoy arrays deployed during N-ICE2015, J.
Geophys. Res., 122, 4661–4674, https://doi.org/10.1002/2016JC012403, 2017.
Itkin, P., Spreen, G., Hvidegaard, S. M., Skourup, H., Wilkinson, J.,
Gerland, S., and Granskog, M. A.: Contribution of deformation to sea ice
mass balance: A case study from an N-ICE2015 storm, Geophys. Res. Lett., 45,
789–796, https://doi.org/10.1002/2017GL076056, 2018.
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.
Kwok, R.: Contrasts in sea ice deformation and production in the Arctic
seasonal and perennial ice zones, J. Geophys. Res., 111, C11S22,
https://doi.org/10.1029/2005JC003246, 2006.
Kwok, R. and Cunningham, G. F.: ICESat over Arctic sea ice: Estimation of
snow depth and ice thickness, J. Geophys. Res., 113, C08010,
https://doi.org/10.1029/2008JC004753, 2008.
Lammert, A., Brümmer, B., and Kaleschke, L.: Observation of
cyclone-induced inertial sea-ice oscillation in Fram Strait, Geophys. Res.
Lett., 36, L10503, https://doi.org/10.1029/2009GL037197, 2009.
Lei, R.: Position data measured by ice-based buoys deployed during the CHINARE Aritic cruise, National Arctic and Antarctic Data Center, 2020, https://doi.org/10.11856/NNS.D.2020.038.v0, 2018.
Lei, R., Tian-Kunze, X., Leppäranta, M., Wang, J., Kaleschke, L., and
Zhang Z.: Changes in summer sea ice, albedo, and portioning of surface solar
radiation in the Pacific sector of Arctic Ocean during 1982–2009, J.
Geophys. Res. Oceans, 121, 5470–5486, https://doi.org/10.1002/2016JC011831, 2016.
Lei, R., Gui, D., Hutchings, J. K., Wang, J., and Pang, X.: Backward and forward
drift trajectories of sea ice in the northwestern Arctic Ocean in response
to changing atmospheric circulation, Int. J. Climatol., 39, 1–20, https://doi.org/10.1002/joc.6080, 2019.
Lei, R., Gui, D., Heil, P., Hutchings, J. K., and Ding, M.: Comparisons of sea
ice motion and deformation, and their responses to ice conditions and
cyclonic activity in the western Arctic Ocean between two summers, Cold Reg.
Sci. Technol., 170, 102925,
https://doi.org/10.1016/j.coldregions.2019.102925, 2020a.
Lei, R., Gui, D., Hutchings, J. K., Heil, P., and Li, N.: Annual cycles of sea
ice motion and deformation derived from buoy measurements in the western
Arctic Ocean over two ice seasons, J. Geophys. Res., 125, e2019JC015310,
https://doi.org/10.1029/2019JC015310, 2020b.
Lewis, J. K. and Richter-Menge, J. A.: Motion-induced stresses in pack
ice, J. Geophys. Res., 103, 21831–21843, https://doi.org/10.1029/98JC01262, 1998.
Lindell, D. B. and Long, D. G.: Multiyear Arctic ice classification using
ASCAT and SSMIS, Remote Sens., 8, 294, https://doi.org/10.3390/rs8040294, 2016.
Lukovich, J. V., Babb, D. G., and Barber, D. G.: On the scaling laws derived
from ice beacon trajectories in the southern Beaufort Sea during the
International Polar Year-Circumpolar Flaw Lead study, 2007–2008, J.
Geophys. Res., 116, C00G07, https://doi.org/10.1029/2011JC007049, 2011.
Marsan, D. and Weiss, J.: Space/time coupling in brittle deformation at
geophysical scales, Earth Planet. Sci. Lett., 296, 353–359, 2010.
Marsan, D., Stern, H., Lindsay, R., and Weiss, J.: Scale dependence and
localization of the deformation of Arctic sea ice, Phys. Res. Lett., 93,
178501, https://doi.org/10.1103/PhysRevLett.93.178501, 2004.
Moore, G. W. K., Schweiger, A., Zhang, J., and Steele, M.: Collapse of the
2017 winter Beaufort High: A response to thinning sea ice?, Geophys. Res.
Lett., 45, 2860–2869, https://doi.org/10.1002/2017GL076446, 2018.
Nicolaus, M., Katlein, C., Maslanik, J., and Hendricks, S.: Changes in
Arctic sea ice result in increasing light transmittance and absorption,
Geophys. Res. Lett., 39, L24501, https://doi.org/10.1029/2012GL053738, 2012.
Nicolaus, M., Belter, H. J., Hummel, S., Hansen, M. L. S., Rabe, B., Tippenhauer, S., Vredenborg, M., and Hoppmann, M.: Snow height on sea ice and sea ice drift from autonomous measurements from buoy 2018S75, deployed during AKADEMIK TRYOSHNIKOV cruise TRANSDRIFT XXIV/TICE, Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven, PANGAEA, https://doi.org/10.1594/PANGAEA.927561, 2021.
Oikkonen, A., Haapala, J., Lensu, M., Karvonen, J., and Itkin, P.:
Small-scale sea ice deformation during N-ICE2015: From compact pack ice to
marginal ice zone, J. Geophys. Res.-Oceans, 122, 5105–5120,
https://doi.org/10.1002/2016JC012387, 2017.
Perovich, D., Meier, W., Tschudi, M., Farrell, S., Hendricks, S., Gerland,
S., Kaleschke, L., Ricker, R., Tian-Kunze, X., Webster, M., and Wood, K.:
Sea ice. Arctic report card 2019, 26–34, available at:
http://www.arctic.noaa.gov/Report-Card (last access: 10 April 2020), 2019.
Perovich, D. K. and Polashenski, C.: Albedo evolution of seasonal Arctic
sea ice, Geophys. Res. Lett., 39, L08501, https://doi.org/10.1029/2012GL051432, 2012.
Perovich, D. K., Grenfell, T. C., Richter-Menge, J. A., Light, B., Tucker
III, W. B., and Eicken, H.: Thin and thinner: sea ice mass balance
measurements during SHEBA, J. Geophys. Res., 108, 8050,
https://doi.org/10.1029/2001JC001079, 2003.
Proshutinsky, A., Krishfield, R., Timmermans, M. L., Toole, J., Carmack,
E., McLaughlin, F., Williams, W. J., Zimmermann, S., Itoh, M., and Shimada,
K.: Beaufort Gyre freshwater reservoir: State and variability from
observations, J. Geophys. Res., 114, C00A10, https://doi.org/10.1029/2008JC005104, 2009.
Rampal, P., Weiss, J., Marsan, D., Lindsay, R., and Stern, H.: Scaling
properties of sea ice deformation from buoy dispersion analysis, J. Geophys.
Res., 113, C03002, https://doi.org/10.1029/2007JC004143, 2008.
Rampal, P., Dansereau, V., Olason, E., Bouillon, S., Williams, T., Korosov, A., and Samaké, A.: On the multi-fractal scaling properties of sea ice deformation, The Cryosphere, 13, 2457–2474, https://doi.org/10.5194/tc-13-2457-2019, 2019.
Salganik, E., Høyland, K. V., and Maus, S.: Consolidation of fresh ice
ridges for different scales, Cold Reg. Sci. Technol., 171, 102959,
https://doi.org/10.1016/j.coldregions.2019.102959, 2020.
Screen, J. A. and Simmonds, I.: Increasing fall-winter energy loss from the
Arctic Ocean and its role in Arctic temperature amplification, Geophys. Res.
Lett., 37, L16707, https://doi.org/10.1029/2010GL044136, 2010.
Serreze, M. C. and Meier, W. N.: The Arctic's sea ice cover: trends,
variability, predictability, and comparisons to the Antarctic, Ann. N.Y.
Acad. Sci., 1436, 36–53, https://doi.org/10.1111/nyas.13856, 2018.
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.
Spreen, G., Kwok, R., and Menemenlis, D.: Trends in Arctic sea ice drift and
role of wind forcing: 1992–2009, Geophys. Res. Lett., 38, L19501, https://doi.org/10.1029/2011GL048970, 2011.
Spreen, G., Kwok, R., Menemenlis, D., and Nguyen, A. T.: Sea-ice deformation in a coupled ocean–sea-ice model and in satellite remote sensing data, The Cryosphere, 11, 1553–1573, https://doi.org/10.5194/tc-11-1553-2017, 2017.
Steele, M. and Dickinson, S.: The phenology of Arctic Ocean surface
warming, J. Geophys. Res.-Oceans, 121, 6847–6861, https://doi.org/10.1002/2016JC012089,
2016.
Stern, H. L. and Lindsay, R. W.: Spatial scaling of Arctic sea ice
deformation, J. Geophys. Res., 114, C10017, https://doi.org/10.1029/2009JC005380, 2009.
Stern, H. L. and Moritz, R. E.: Sea ice kinematics and surface properties
from RADARSAT synthetic aperture radar during the SHEBA drift, J. Geophys.
Res., 107, 8028, https://doi.org/10.1029/2000JC000472, 2002.
Strong, C. and Rigor, I. G.: Arctic marginal ice zone trending wider in
summer and narrower in winter, Geophys. Res. Lett., 40, 4864–4868,
https://doi.org/10.1002/grl.50928, 2013.
Tschudi, M., Meier, W. N., Stewart, J. S., Fowler, C., and Maslanik, J.:
Polar Pathfinder Daily 25 km EASE-Grid Sea Ice Motion Vectors, Version 4,
Boulder, CA, USA, NASA National Snow and Ice Data Center Distributed Active
Archive Center, https://doi.org/10.5067/INAWUWO7QH7B, 2019.
Tschudi, M. A., Meier, W. N., and Stewart, J. S.: An enhancement to sea ice motion and age products at the National Snow and Ice Data Center (NSIDC), The Cryosphere, 14, 1519–1536, https://doi.org/10.5194/tc-14-1519-2020, 2020.
Vihma, T., Tisler, P., and Uotila, P.: Atmospheric forcing on the drift of
Arctic sea ice in 1989–2009, Geophys. Res. Lett., 39, L02501,
https://doi.org/10.1029/2011GL050118, 2012.
Wang, J., Zhang, J., Watanabe, E., Mizobata, K., Ikeda, M., Walsh, J. E.,
Bai, X., and Wu, B.: Is the Dipole Anomaly a major driver to record lows in the
Arctic sea ice extent?, Geophys. Res. Lett., 36, L05706,
https://doi.org/10.1029/2008GL036706, 2009.
Woodgate, R. A., Weingartner, T. J., and Lindsay, R.: Observed increases in
Bering Strait oceanic fluxes from the Pacific to the Arctic from 2001 to
2011 and their impacts on the Arctic Ocean water column, Geophys. Res.
Lett., 39, L24603, https://doi.org/10.1029/2012GL054092, 2012.
Zhang, Y., Maslowski, W., and Semtner, A. J.: Impact of mesoscale ocean
currents on sea ice in high-resolution Arctic ice and ocean simulations, J.
Geophys. Res., 104, 18409–18429, https://doi.org/10.1029/1999JC900158, 1999.
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.
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.
Quantification of ice deformation is useful for understanding of the role of ice dynamics in...
