Articles | Volume 17, issue 6
https://doi.org/10.5194/tc-17-2231-2023
© Author(s) 2023. 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-17-2231-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Annual evolution of the ice–ocean interaction beneath landfast ice in Prydz Bay, East Antarctica
Haihan Hu
School of Geospatial Engineering and Science, Sun Yat-sen University,
and Southern Marine Science and Engineering Guangdong Laboratory,
Zhuhai 519082, China
Key Laboratory of Comprehensive Observation of Polar Environment (Sun Yat-sen University), Ministry of Education, Zhuhai 519082, China
Qingdao Innovation and Development Base (Centre) of Harbin Engineering University, Qingdao 266500, China
College of Underwater Acoustic Engineering, Harbin Engineering
University, Harbin 150001, China
Petra Heil
Australia Antarctic Division & Australian Antarctic Programmer
Partnership, Private Bag 80, Hobart TAS 7001, Australia
Zhiliang Qin
Qingdao Innovation and Development Base (Centre) of Harbin Engineering University, Qingdao 266500, China
College of Underwater Acoustic Engineering, Harbin Engineering
University, Harbin 150001, China
Jingkai Ma
Key Laboratory of Research on Marine Hazards Forecasting, National
Marine Environmental Forecasting Centre, Beijing 100081, China
Fengming Hui
CORRESPONDING AUTHOR
School of Geospatial Engineering and Science, Sun Yat-sen University,
and Southern Marine Science and Engineering Guangdong Laboratory,
Zhuhai 519082, China
Key Laboratory of Comprehensive Observation of Polar Environment (Sun Yat-sen University), Ministry of Education, Zhuhai 519082, China
Xiao Cheng
School of Geospatial Engineering and Science, Sun Yat-sen University,
and Southern Marine Science and Engineering Guangdong Laboratory,
Zhuhai 519082, China
Key Laboratory of Comprehensive Observation of Polar Environment (Sun Yat-sen University), Ministry of Education, Zhuhai 519082, China
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Mingyue Nong, Xuying Liu, Teng Li, Baogang Zhang, Qi Liang, Lei Zheng, Tiancheng Zhao, and Xiao Cheng
EGUsphere, https://doi.org/10.5194/egusphere-2025-1884, https://doi.org/10.5194/egusphere-2025-1884, 2025
Preprint archived
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We extracted nearshore small icebergs in front of Dalk Glacier using UAV high-resolution data and directly obtained geometric parameters of the icebergs and analyzed their distribution patterns. The area/volume relationship of our icebergs aligns with the medium to large icebergs in existing ocean model. The study demonstrates UAVs' effectiveness in polar research and the importance of including all iceberg sizes in ocean modeling for better environmental impact predictions.
Zilong Chen, Xuying Liu, Zhenfu Guan, Teng Li, Xiao Cheng, Tian Li, Yan Liu, Qi Liang, Lei Zheng, and Jiping Liu
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-51, https://doi.org/10.5194/essd-2025-51, 2025
Revised manuscript under review for ESSD
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Our study uses Google Earth Engine to create a dataset of Antarctic icebergs in the Southern Ocean (south of 55°S) from October 2018 to 2023. The dataset includes icebergs larger than 0.04 km², with details on their locations, sizes, and shapes. It shows significant changes in iceberg number and area, mainly driven by major ice shelf calving events – especially in the Weddell Sea. This resource fills key gaps in understanding iceberg impacts on the ocean and climate.
Fukai Peng, Xiaoli Deng, Yunzhong Shen, and Xiao Cheng
Earth Syst. Sci. Data, 17, 1441–1460, https://doi.org/10.5194/essd-17-1441-2025, https://doi.org/10.5194/essd-17-1441-2025, 2025
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A new reprocessed altimeter coastal sea level dataset, International Altimetry Service 2024 (IAS2024), for monitoring sea level changes along the world’s coastlines is presented. The evaluation and validation results confirm the reliability of this dataset. The altimeter-based virtual stations along the world’s coastlines can be built using this dataset to monitor the coastal sea level changes where tide gauges are unavailable. Therefore, it is beneficial for both oceanographic communities and policymakers.
Mukund Gupta, Heather Regan, Younghyun Koo, Sean Minhui Tashi Chua, Xueke Li, and Petra Heil
The Cryosphere, 19, 1241–1257, https://doi.org/10.5194/tc-19-1241-2025, https://doi.org/10.5194/tc-19-1241-2025, 2025
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The sea ice cover is composed of floes, whose shapes set the material properties of the pack. Here, we use a satellite product (ICESat-2) to investigate these floe shapes within the Weddell Sea in Antarctica. We find that floes tend to become smaller during the melt season, while their thickness distribution exhibits different behavior between the western and southern regions of the pack. These metrics will help calibrate models and improve our understanding of sea ice physics across scales.
Yan Sun, Shaoyin Wang, Xiao Cheng, Teng Li, Chong Liu, Yufang Ye, and Xi Zhao
EGUsphere, https://doi.org/10.5194/egusphere-2024-2760, https://doi.org/10.5194/egusphere-2024-2760, 2025
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This manuscript proposes to combine semantic segmentation of ice region using a U-Net model and multi-stage detection of ice pixels using the Multi-textRG algorithm to achieve fine ice-water classification. Novel proccessings for the HV/HH polarization ratio and the GLCM textures, as well as the usage of regional growing, largely improve the method accuracy and robustness. The proposed algorithm framework achieved automated sea-ice labelling.
Diana Francis, Ricardo Fonseca, Narendra Nelli, Petra Heil, Jonathan Wille, Irina Gorodetskaya, and Robert Massom
EGUsphere, https://doi.org/10.5194/egusphere-2024-3535, https://doi.org/10.5194/egusphere-2024-3535, 2025
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This study investigates the impact of atmospheric rivers and associated atmospheric dynamics on sea-ice thickness and snow depth at a coastal site in East Antarctica during July–November 2022 using in-situ measurements and numerical modelling. The passage of an atmospheric river induced a reduction of up to 0.06 m in both fields. Precipitation occurred from the convergence of katabatic winds with advected low-latitude moist air.
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
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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.
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
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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.
Yetang Wang, Xueying Zhang, Wentao Ning, Matthew A. Lazzara, Minghu Ding, Carleen H. Reijmer, Paul C. J. P. Smeets, Paolo Grigioni, Petra Heil, Elizabeth R. Thomas, David Mikolajczyk, Lee J. Welhouse, Linda M. Keller, Zhaosheng Zhai, Yuqi Sun, and Shugui Hou
Earth Syst. Sci. Data, 15, 411–429, https://doi.org/10.5194/essd-15-411-2023, https://doi.org/10.5194/essd-15-411-2023, 2023
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Here we construct a new database of Antarctic automatic weather station (AWS) meteorological records, which is quality-controlled by restrictive criteria. This dataset compiled all available Antarctic AWS observations, and its resolutions are 3-hourly, daily and monthly, which is very useful for quantifying spatiotemporal variability in weather conditions. Furthermore, this compilation will be used to estimate the performance of the regional climate models or meteorological reanalysis products.
Yufang Ye, Yanbing Luo, Yan Sun, Mohammed Shokr, Signe Aaboe, Fanny Girard-Ardhuin, Fengming Hui, Xiao Cheng, and Zhuoqi Chen
The Cryosphere, 17, 279–308, https://doi.org/10.5194/tc-17-279-2023, https://doi.org/10.5194/tc-17-279-2023, 2023
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Arctic sea ice type (SITY) variation is a sensitive indicator of climate change. This study gives a systematic inter-comparison and evaluation of eight SITY products. Main results include differences in SITY products being significant, with average Arctic multiyear ice extent up to 1.8×106 km2; Ku-band scatterometer SITY products generally performing better; and factors such as satellite inputs, classification methods, training datasets and post-processing highly impacting their performance.
Chong Liu, Xiaoqing Xu, Xuejie Feng, Xiao Cheng, Caixia Liu, and Huabing Huang
Earth Syst. Sci. Data, 15, 133–153, https://doi.org/10.5194/essd-15-133-2023, https://doi.org/10.5194/essd-15-133-2023, 2023
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Rapid Arctic changes are increasingly influencing human society, both locally and globally. Land cover offers a basis for characterizing the terrestrial world, yet spatially detailed information on Arctic land cover is lacking. We employ multi-source data to develop a new land cover map for the circumpolar Arctic. Our product reveals regionally contrasting biome distributions not fully documented in existing studies and thus enhances our understanding of the Arctic’s terrestrial system.
Minghu Ding, Xiaowei Zou, Qizhen Sun, Diyi Yang, Wenqian Zhang, Lingen Bian, Changgui Lu, Ian Allison, Petra Heil, and Cunde Xiao
Earth Syst. Sci. Data, 14, 5019–5035, https://doi.org/10.5194/essd-14-5019-2022, https://doi.org/10.5194/essd-14-5019-2022, 2022
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The PANDA automatic weather station (AWS) network consists of 11 stations deployed along a transect from the coast (Zhongshan Station) to the summit of the East Antarctic Ice Sheet (Dome A). It covers the different climatic and topographic units of East Antarctica. All stations record hourly air temperature, relative humidity, air pressure, wind speed and direction at two or three heights. The PANDA AWS dataset commences from 1989 and is planned to be publicly available into the future.
Qi Liang, Wanxin Xiao, Ian Howat, Xiao Cheng, Fengming Hui, Zhuoqi Chen, Mi Jiang, and Lei Zheng
The Cryosphere, 16, 2671–2681, https://doi.org/10.5194/tc-16-2671-2022, https://doi.org/10.5194/tc-16-2671-2022, 2022
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Using multi-temporal ArcticDEM and ICESat-2 altimetry data, we document changes in surface elevation of a subglacial lake basin from 2012 to 2021. The long-term measurements show that the subglacial lake was recharged by surface meltwater and that a rapid drainage event in late August 2019 induced an abrupt ice velocity change. Multiple factors regulate the episodic filling and drainage of the lake. Our study also reveals ~ 64 % of the surface meltwater successfully descended to the bed.
Fengguan Gu, Qinghua Yang, Frank Kauker, Changwei Liu, Guanghua Hao, Chao-Yuan Yang, Jiping Liu, Petra Heil, Xuewei Li, and Bo Han
The Cryosphere, 16, 1873–1887, https://doi.org/10.5194/tc-16-1873-2022, https://doi.org/10.5194/tc-16-1873-2022, 2022
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The sea ice thickness was simulated by a single-column model and compared with in situ observations obtained off Zhongshan Station in the Antarctic. It is shown that the unrealistic precipitation in the atmospheric forcing data leads to the largest bias in sea ice thickness and snow depth modeling. In addition, the increasing snow depth gradually inhibits the growth of sea ice associated with thermal blanketing by the snow.
Tian R. Tian, Alexander D. Fraser, Noriaki Kimura, Chen Zhao, and Petra Heil
The Cryosphere, 16, 1299–1314, https://doi.org/10.5194/tc-16-1299-2022, https://doi.org/10.5194/tc-16-1299-2022, 2022
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This study presents a comprehensive validation of a satellite observational sea ice motion product in Antarctica by using drifting buoys. Two problems existing in this sea ice motion product have been noticed. After rectifying problems, we use it to investigate the impacts of satellite observational configuration and timescale on Antarctic sea ice kinematics and suggest the future improvement of satellite missions specifically designed for retrieval of sea ice motion.
Yijing Lin, Yan Liu, Zhitong Yu, Xiao Cheng, Qiang Shen, and Liyun Zhao
The Cryosphere Discuss., https://doi.org/10.5194/tc-2021-325, https://doi.org/10.5194/tc-2021-325, 2021
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We introduce an uncertainty analysis framework for comprehensively and systematically quantifying the uncertainties of the Antarctic mass balance using the Input and Output Method. It is difficult to use the previous strategies employed in various methods and the available data to achieve the goal of estimation accuracy. The dominant cause of the future uncertainty is the ice thickness data gap. The interannual variability of ice discharge caused by velocity and thickness is also nonnegligible.
Joey J. Voermans, Qingxiang Liu, Aleksey Marchenko, Jean Rabault, Kirill Filchuk, Ivan Ryzhov, Petra Heil, Takuji Waseda, Takehiko Nose, Tsubasa Kodaira, Jingkai Li, and Alexander V. Babanin
The Cryosphere, 15, 5557–5575, https://doi.org/10.5194/tc-15-5557-2021, https://doi.org/10.5194/tc-15-5557-2021, 2021
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We have shown through field experiments that the amount of wave energy dissipated in landfast ice, sea ice attached to land, is much larger than in broken ice. By comparing our measurements against predictions of contemporary wave–ice interaction models, we determined which models can explain our observations and which cannot. Our results will improve our understanding of how waves and ice interact and how we can model such interactions to better forecast waves and ice in the polar regions.
Mengzhen Qi, Yan Liu, Jiping Liu, Xiao Cheng, Yijing Lin, Qiyang Feng, Qiang Shen, and Zhitong Yu
Earth Syst. Sci. Data, 13, 4583–4601, https://doi.org/10.5194/essd-13-4583-2021, https://doi.org/10.5194/essd-13-4583-2021, 2021
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A total of 1975 annual calving events larger than 1 km2 were detected on the Antarctic ice shelves from August 2005 to August 2020. The average annual calved area was measured as 3549.1 km2, and the average calving rate was measured as 770.3 Gt yr-1. Iceberg calving is most prevalent in West Antarctica, followed by the Antarctic Peninsula and Wilkes Land in East Antarctica. This annual iceberg calving dataset provides consistent and precise calving observations with the longest time coverage.
Linlu Mei, Vladimir Rozanov, Evelyn Jäkel, Xiao Cheng, Marco Vountas, and John P. Burrows
The Cryosphere, 15, 2781–2802, https://doi.org/10.5194/tc-15-2781-2021, https://doi.org/10.5194/tc-15-2781-2021, 2021
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This paper presents a new snow property retrieval algorithm from satellite observations. This is Part 2 of two companion papers and shows the results and validation. The paper performs the new retrieval algorithm on the Sea and Land
Surface Temperature Radiometer (SLSTR) instrument and compares the retrieved snow properties with ground-based measurements, aircraft measurements and other satellite products.
Diana Francis, Kyle S. Mattingly, Stef Lhermitte, Marouane Temimi, and Petra Heil
The Cryosphere, 15, 2147–2165, https://doi.org/10.5194/tc-15-2147-2021, https://doi.org/10.5194/tc-15-2147-2021, 2021
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The unexpected September 2019 calving event from the Amery Ice Shelf, the largest since 1963 and which occurred almost a decade earlier than expected, was triggered by atmospheric extremes. Explosive twin polar cyclones provided a deterministic role in this event by creating oceanward sea surface slope triggering the calving. The observed record-anomalous atmospheric conditions were promoted by blocking ridges and Antarctic-wide anomalous poleward transport of heat and moisture.
Yu Zhou, Jianlong Chen, and Xiao Cheng
Earth Surf. Dynam. Discuss., https://doi.org/10.5194/esurf-2021-21, https://doi.org/10.5194/esurf-2021-21, 2021
Preprint withdrawn
Joey J. Voermans, Jean Rabault, Kirill Filchuk, Ivan Ryzhov, Petra Heil, Aleksey Marchenko, Clarence O. Collins III, Mohammed Dabboor, Graig Sutherland, and Alexander V. Babanin
The Cryosphere, 14, 4265–4278, https://doi.org/10.5194/tc-14-4265-2020, https://doi.org/10.5194/tc-14-4265-2020, 2020
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In this work we demonstrate the existence of an observational threshold which identifies when waves are most likely to break sea ice. This threshold is based on information from two recent field campaigns, supplemented with existing observations of sea ice break-up. We show that both field and laboratory observations tend to converge to a single quantitative threshold at which the wave-induced sea ice break-up takes place, which opens a promising avenue for operational forecasting models.
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Short summary
The oceanic characteristics beneath sea ice significantly affect ice growth and melting. The high-frequency and long-term observations of oceanic variables allow us to deeply investigate their diurnal and seasonal variation and evaluate their influences on sea ice evolution. The large-scale sea ice distribution and ocean circulation contributed to the seasonal variation of ocean variables, revealing the important relationship between large-scale and local phenomena.
The oceanic characteristics beneath sea ice significantly affect ice growth and melting. The...