Sea ice kinematic features in the Arctic outflow region and their associations with Arctic Northeast Passage accessibility
Dawei Gui
Chinese Antarctic Center of Surveying and Mapping, Wuhan University, Wuhan 430079, China
SOA Key Laboratory for Polar Science, Polar Research Institute of China, Shanghai 200136, China
Xiaoping Pang
Chinese Antarctic Center of Surveying and Mapping, Wuhan University, Wuhan 430079, China
Ruibo Lei
SOA Key Laboratory for Polar Science, Polar Research Institute of China, Shanghai 200136, China
Chinese Antarctic Center of Surveying and Mapping, Wuhan University, Wuhan 430079, China
Xi Zhao
Chinese Antarctic Center of Surveying and Mapping, Wuhan University, Wuhan 430079, China
Jia Wang
National Oceanic and Atmospheric Administration Great Lakes Environmental Research Laboratory, Ann Arbor, USA
Related authors
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.
Fanyi Zhang, Ruibo Lei, Meng Qu, Na Li, Ying Chen, and Xiaoping Pang
EGUsphere, https://doi.org/10.5194/egusphere-2024-2723, https://doi.org/10.5194/egusphere-2024-2723, 2024
Short summary
Short summary
We reconstructed sea ice drift trajectories and identified optimal deployment areas for Lagrangian observations. It revealed a preference for ice advection towards the Transpolar Drift region over the Beaufort Gyre, with endpoints influenced by large-scale atmospheric circulation patterns. This study could help the future ice camp/buoy deployment strategies, ensuring the sustainability of crucial Arctic observations in the face of changing environmental conditions.
Yi Zhou, Xianwei Wang, Ruibo Lei, Arttu Jutila, Donald K. Perovich, Luisa von Albedyll, Dmitry V. Divine, Yu Zhang, and Christian Haas
EGUsphere, https://doi.org/10.5194/egusphere-2024-2821, https://doi.org/10.5194/egusphere-2024-2821, 2024
Short summary
Short summary
This study examines how the bulk density of Arctic sea ice varies seasonally, a factor often overlooked in satellite measurements of sea ice thickness. From October to April, we found significant seasonal variations in sea ice bulk density at different spatial scales using direct observations as well as airborne and satellite data. New models were then developed to indirectly predict sea ice bulk density. This advance can improve our ability to monitor changes in Arctic sea ice.
Yi Zhou, Xianwei Wang, Ruibo Lei, Luisa von Albedyll, Donald K. Perovich, Yu Zhang, and Christian Haas
EGUsphere, https://doi.org/10.5194/egusphere-2024-1240, https://doi.org/10.5194/egusphere-2024-1240, 2024
Preprint archived
Short summary
Short summary
This study examines how the density of Arctic sea ice varies seasonally, a factor often overlooked in satellite measurements of sea ice thickness. From October to April, using direct observations and satellite data, we found that sea ice density decreases significantly until mid-January due to increased porosity as the ice ages, and then stabilizes until April. We then developed new models to estimate sea ice density. This advance can improve our ability to monitor changes in Arctic sea ice.
Yan Sun, Shaoyin Wang, Xiao Cheng, Teng Li, Chong Liu, Yufang Ye, and Xi Zhao
EGUsphere, https://doi.org/10.5194/egusphere-2024-1177, https://doi.org/10.5194/egusphere-2024-1177, 2024
Preprint archived
Short summary
Short summary
Arctic sea ice has rapidly declined due to global warming, leading to extreme weather events. Accurate ice monitoring is vital for understanding and forecasting these impacts. Combining SAR and AMSR2 data with machine learning is efficient but requires sufficient labels. We propose a framework integrating the U-Net model with the Multi-textRG algorithm to achieve ice-water classification at SAR-level resolution and to generate accurate labels for improved U-Net model training.
Miao Yu, Peng Lu, Matti Leppäranta, Bin Cheng, Ruibo Lei, Bingrui Li, Qingkai Wang, and Zhijun Li
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
Short summary
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
Short summary
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
Short summary
Short summary
The sea ice concentration product derived from the Microwave Radiation Image sensors on board the FengYun-3 satellites can reasonably and independently identify the seasonal and long-term changes of sea ice, as well as extreme cases of annual maximum and minimum sea ice extent in polar regions. It is comparable with other sea ice concentration products and applied to the studies of climate and marine environment.
Na Li, Ruibo Lei, Petra Heil, Bin Cheng, Minghu Ding, Zhongxiang Tian, and Bingrui Li
The Cryosphere, 17, 917–937, https://doi.org/10.5194/tc-17-917-2023, https://doi.org/10.5194/tc-17-917-2023, 2023
Short summary
Short summary
The observed annual maximum landfast ice (LFI) thickness off Zhongshan (Davis) was 1.59±0.17 m (1.64±0.08 m). Larger interannual and local spatial variabilities for the seasonality of LFI were identified at Zhongshan, with the dominant influencing factors of air temperature anomaly, snow atop, local topography and wind regime, and oceanic heat flux. The variability of LFI properties across the study domain prevailed at interannual timescales, over any trend during the recent decades.
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.
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
Short summary
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.
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.
Y. Chen, X. Zhao, M. Qu, Z. Cheng, X. Pang, and Q. Ji
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B3-2020, 861–867, https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-861-2020, https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-861-2020, 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
Short summary
Short summary
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.
Haiyan Liu and Xiaoping Pang
Abstr. Int. Cartogr. Assoc., 1, 221, https://doi.org/10.5194/ica-abs-1-221-2019, https://doi.org/10.5194/ica-abs-1-221-2019, 2019
Xiaoping Pang, Pei Fan, Xi Zhao, and Qing Ji
Abstr. Int. Cartogr. Assoc., 1, 289, https://doi.org/10.5194/ica-abs-1-289-2019, https://doi.org/10.5194/ica-abs-1-289-2019, 2019
Meng Qu, Xiaoping Pang, Xi Zhao, Jinlun Zhang, Qing Ji, and Pei Fan
The Cryosphere, 13, 1565–1582, https://doi.org/10.5194/tc-13-1565-2019, https://doi.org/10.5194/tc-13-1565-2019, 2019
Short summary
Short summary
Can we ignore the contribution of small ice leads when estimating turbulent heat flux? Combining bulk formulae and a fetch-limited model with surface temperature from MODIS and Landsat-8 Thermal Infrared Sensor (TIRS) images, we found small leads account for 25 % of the turbulent heat flux, due to its large total area. Estimated turbulent heat flux is larger from TIRS than that from MODIS with a coarser resolution and larger using a fetch-limited model than that using bulk formulae.