Articles | Volume 16, issue 5
https://doi.org/10.5194/tc-16-1873-2022
© 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/tc-16-1873-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
17 May 2022
Research article |
| 17 May 2022
The sensitivity of landfast sea ice to atmospheric forcing in single-column model simulations: a case study at Zhongshan Station, Antarctica
Fengguan Gu
School of Atmospheric Sciences, Sun Yat-sen University, and Southern
Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082,
China
Qinghua Yang
School of Atmospheric Sciences, Sun Yat-sen University, and Southern
Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082,
China
Frank Kauker
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research,
Am Handelshafen 12, 27570 Bremerhaven, Germany
Ocean Atmosphere Systems, Tewesstseg 4, 20249 Hamburg, Germany
Changwei Liu
School of Atmospheric Sciences, Sun Yat-sen University, and Southern
Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082,
China
Guanghua Hao
Key Laboratory of Marine Hazards Forecasting, National Marine
Environmental Forecasting Center, Ministry of
Natural Resources, Beijing 100081, China
Chao-Yuan Yang
School of Atmospheric Sciences, Sun Yat-sen University, and Southern
Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082,
China
Jiping Liu
Department of Atmospheric and Environmental Sciences, State University of
New York at Albany, Albany, NY, USA
Petra Heil
Australian Antarctic Division, Australian Antarctic Program
Partnership, Private Bag 80, Hobart, Tas 7001, Australia
Xuewei Li
School of Atmospheric Sciences, Sun Yat-sen University, and Southern
Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082,
China
Bo Han
CORRESPONDING AUTHOR
School of Atmospheric Sciences, Sun Yat-sen University, and Southern
Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082,
China
Related authors
No articles found.
Shijie Peng, Qinghua Yang, Matthew D. Shupe, Xingya Xi, Bo Han, Dake Chen, and Changwei Liu
EGUsphere, https://doi.org/10.5194/egusphere-2023-347, https://doi.org/10.5194/egusphere-2023-347, 2023
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
Due to the lack of observations, the structure of Arctic atmospheric boundary layer (ABL) remains to be further explored. By analyzing a year-round radiosonde dataset collected over the Arctic sea-ice surface, we found the annual cycle of the ABL height (ABLH) is primarily controlled by the evolution of ABL thermal structure, and the surface conditions also show high correlation with the ABLH variation. In addition, the Arctic ABLH is found to be decreased in summer compared with 20 years ago.
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.
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
Short summary
Short summary
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.
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
Short summary
Short summary
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.
Jinfei Wang, Chao Min, Robert Ricker, Qian Shi, Bo Han, Stefan Hendricks, Renhao Wu, and Qinghua Yang
The Cryosphere, 16, 4473–4490, https://doi.org/10.5194/tc-16-4473-2022, https://doi.org/10.5194/tc-16-4473-2022, 2022
Short summary
Short summary
The differences between Envisat and ICESat sea ice thickness (SIT) reveal significant temporal and spatial variations. Our findings suggest that both overestimation of Envisat sea ice freeboard, potentially caused by radar backscatter originating from inside the snow layer, and the AMSR-E snow depth biases and sea ice density uncertainties can possibly account for the differences between Envisat and ICESat SIT.
Haihan Hu, Jiechen Zhao, Petra Heil, Jingkai Ma, Fengming Hui, and Xiao Cheng
The Cryosphere Discuss., https://doi.org/10.5194/tc-2022-125, https://doi.org/10.5194/tc-2022-125, 2022
Revised manuscript under review for TC
Short summary
Short summary
The oceanic characteristics beneath sea ice affects significantly the ice growth and melting. Based on the minute-scale observations of the ocean-ice boundary layer in the Prydz Bay, East Antarctica, this study analyzed the diurnal variation of oceanic parameters, and found some interested results from the detailed processes. For example, the change of tide phases raised ocean temperature and further the ocean-to-ice heat flux, causing an observed ice melting in the cold winter.
Sutao Liao, Hao Luo, Jinfei Wang, Qian Shi, Jinlun Zhang, and Qinghua Yang
The Cryosphere, 16, 1807–1819, https://doi.org/10.5194/tc-16-1807-2022, https://doi.org/10.5194/tc-16-1807-2022, 2022
Short summary
Short summary
The Global Ice-Ocean Modeling and Assimilation System (GIOMAS) can basically reproduce the observed variability in Antarctic sea-ice volume and its changes in the trend before and after 2013, and it underestimates Antarctic sea-ice thickness (SIT) especially in deformed ice zones. Assimilating additional sea-ice observations with advanced assimilation methods may result in a more accurate estimation of Antarctic SIT.
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
Short summary
Short summary
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.
Chao-Yuan Yang, Jiping Liu, and Dake Chen
Geosci. Model Dev., 15, 1155–1176, https://doi.org/10.5194/gmd-15-1155-2022, https://doi.org/10.5194/gmd-15-1155-2022, 2022
Short summary
Short summary
We present an improved coupled modeling system for Arctic sea ice prediction. We perform Arctic sea ice prediction experiments with improved/updated physical parameterizations, which show better skill in predicting sea ice state as well as atmospheric and oceanic state in the Arctic compared with its predecessor. The improved model also shows extended predictive skill of Arctic sea ice after the summer season. This provides an added value of this prediction system for decision-making.
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
Short summary
Short summary
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
Short summary
Short summary
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.
Xiaoxu Shi, Dirk Notz, Jiping Liu, Hu Yang, and Gerrit Lohmann
Geosci. Model Dev., 14, 4891–4908, https://doi.org/10.5194/gmd-14-4891-2021, https://doi.org/10.5194/gmd-14-4891-2021, 2021
Short summary
Short summary
The ice–ocean heat flux is one of the key elements controlling sea ice changes. It motivates our study, which aims to examine the responses of modeled climate to three ice–ocean heat flux parameterizations, including two old approaches that assume one-way heat transport and a new one describing a double-diffusive ice–ocean heat exchange. The results show pronounced differences in the modeled sea ice, ocean, and atmosphere states for the latter as compared to the former two parameterizations.
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
Short summary
Short summary
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.
Daniela Krampe, Frank Kauker, Marie Dumont, and Andreas Herber
The Cryosphere Discuss., https://doi.org/10.5194/tc-2021-100, https://doi.org/10.5194/tc-2021-100, 2021
Manuscript not accepted for further review
Short summary
Short summary
Reliable and detailed Arctic snow data are limited. Evaluation of the performance of atmospheric reanalysis compared to measurements in northeast Greenland generally show good agreement. Both data sets are applied to an Alpine snow model and the performance for Arctic conditions is investigated: Simulated snow depth evolution is reliable, but vertical snow profiles show weaknesses. These are smaller with an adapted parametrisation for the density of newly fallen snow for harsh Arctic conditions.
Xuewei Li, Qinghua Yang, Lejiang Yu, Paul R. Holland, Chao Min, Longjiang Mu, and Dake Chen
The Cryosphere Discuss., https://doi.org/10.5194/tc-2020-359, https://doi.org/10.5194/tc-2020-359, 2021
Preprint withdrawn
Short summary
Short summary
The Arctic sea ice thickness record minimum is confirmed occurring in autumn 2011. The dynamic and thermodynamic processes leading to the minimum thickness is analyzed based on a daily sea ice thickness reanalysis data covering the melting season. The results demonstrate that the dynamic transport of multiyear ice and the subsequent surface energy budget response is a critical mechanism actively contributing to the evolution of Arctic sea ice thickness in 2011.
Chao Min, Qinghua Yang, Longjiang Mu, Frank Kauker, and Robert Ricker
The Cryosphere, 15, 169–181, https://doi.org/10.5194/tc-15-169-2021, https://doi.org/10.5194/tc-15-169-2021, 2021
Short summary
Short summary
An ensemble of four estimates of the sea-ice volume (SIV) variations in Baffin Bay from 2011 to 2016 is generated from the locally merged satellite observations, three modeled sea ice thickness sources (CMST, NAOSIM, and PIOMAS) and NSIDC ice drift data (V4). Results show that the net increase of the ensemble mean SIV occurs from October to April with the largest SIV increase in December, and the reduction occurs from May to September with the largest SIV decline in July.
Qian Shi, Qinghua Yang, Longjiang Mu, Jinfei Wang, François Massonnet, and Matthew R. Mazloff
The Cryosphere, 15, 31–47, https://doi.org/10.5194/tc-15-31-2021, https://doi.org/10.5194/tc-15-31-2021, 2021
Short summary
Short summary
The ice thickness from four state-of-the-art reanalyses (GECCO2, SOSE, NEMO-EnKF and GIOMAS) are evaluated against that from remote sensing and in situ observations in the Weddell Sea, Antarctica. Most of the reanalyses can reproduce ice thickness in the central and eastern Weddell Sea but failed to capture the thick and deformed ice in the western Weddell Sea. These results demonstrate the possibilities and limitations of using current sea-ice reanalysis in Antarctic climate research.
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
Short summary
Short summary
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.
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.
Jinfei Wang, Chao Min, Robert Ricker, Qinghua Yang, Qian Shi, Bo Han, and Stefan Hendricks
The Cryosphere Discuss., https://doi.org/10.5194/tc-2020-48, https://doi.org/10.5194/tc-2020-48, 2020
Revised manuscript not accepted
Short summary
Short summary
To get a better understanding of the characteristics of the newly-released Envisat sea ice data in the Antarctic, we firstly conduct a comprehensive comparison between Envisat and ICESat sea ice thickness. Their deviations are different considering different seasons, years and regions. Potential reasons mainly deduce from the limitations of radar altimeter, the surface roughness and different retrieval algorithms. The smaller deviation in spring has a potential relation with relative humidity.
Andrew E. Kiss, Andrew McC. Hogg, Nicholas Hannah, Fabio Boeira Dias, Gary B. Brassington, Matthew A. Chamberlain, Christopher Chapman, Peter Dobrohotoff, Catia M. Domingues, Earl R. Duran, Matthew H. England, Russell Fiedler, Stephen M. Griffies, Aidan Heerdegen, Petra Heil, Ryan M. Holmes, Andreas Klocker, Simon J. Marsland, Adele K. Morrison, James Munroe, Maxim Nikurashin, Peter R. Oke, Gabriela S. Pilo, Océane Richet, Abhishek Savita, Paul Spence, Kial D. Stewart, Marshall L. Ward, Fanghua Wu, and Xihan Zhang
Geosci. Model Dev., 13, 401–442, https://doi.org/10.5194/gmd-13-401-2020, https://doi.org/10.5194/gmd-13-401-2020, 2020
Short summary
Short summary
We describe new computer model configurations which simulate the global ocean and sea ice at three resolutions. The coarsest resolution is suitable for multi-century climate projection experiments, whereas the finest resolution is designed for more detailed studies over time spans of decades. The paper provides technical details of the model configurations and an assessment of their performance relative to observations.
Chao Min, Longjiang Mu, Qinghua Yang, Robert Ricker, Qian Shi, Bo Han, Renhao Wu, and Jiping Liu
The Cryosphere, 13, 3209–3224, https://doi.org/10.5194/tc-13-3209-2019, https://doi.org/10.5194/tc-13-3209-2019, 2019
Short summary
Short summary
Sea ice volume export through the Fram Strait has been studied using varied methods, however, mostly in winter months. Here we report sea ice volume estimates that extend over summer seasons. A recent developed sea ice thickness dataset, in which CryoSat-2 and SMOS sea ice thickness together with SSMI/SSMIS sea ice concentration are assimilated, is used and evaluated in the paper. Results show our estimate is more reasonable than that calculated by satellite data only.
Yifan Ding, Xiao Cheng, Jiping Liu, Fengming Hui, and Zhenzhan Wang
The Cryosphere Discuss., https://doi.org/10.5194/tc-2019-208, https://doi.org/10.5194/tc-2019-208, 2019
Preprint withdrawn
Short summary
Short summary
This study develops a new melt pond fraction (MPF) data set over sea ice on Arctic-wide scale, using a method of ensemble-based deep neural network. Based on the new dataset, we analyze the spatial-temporal variations of MPF on different ice types and the prediction of MPF to the Arctic sea ice extent in recent years. The new dataset may help improve the prediction of the Arctic sea ice minimum by assimilating the MPF in models.
Valentin Ludwig, Gunnar Spreen, Christian Haas, Larysa Istomina, Frank Kauker, and Dmitrii Murashkin
The Cryosphere, 13, 2051–2073, https://doi.org/10.5194/tc-13-2051-2019, https://doi.org/10.5194/tc-13-2051-2019, 2019
Short summary
Short summary
Sea-ice concentration, the fraction of an area covered by sea ice, can be observed from satellites with different methods. We combine two methods to obtain a product which is better than either of the input measurements alone. The benefit of our product is demonstrated by observing the formation of an open water area which can now be observed with more detail. Additionally, we find that the open water area formed because the sea ice drifted in the opposite direction and faster than usual.
Haibo Bi, Qinghua Yang, Xi Liang, Liang Zhang, Yunhe Wang, Yu Liang, and Haijun Huang
The Cryosphere, 13, 1423–1439, https://doi.org/10.5194/tc-13-1423-2019, https://doi.org/10.5194/tc-13-1423-2019, 2019
Short summary
Short summary
The Arctic sea ice extent is diminishing, which is deemed an immediate response to a warmer Earth. However, quantitative estimates about the contribution due to transport and melt to the sea ice loss are still vague. This study mainly utilizes satellite observations to quantify the dynamic and thermodynamic aspects of ice loss for nearly 40 years (1979–2016). In addition, the potential impacts on ice reduction due to different atmospheric circulation pattern are highlighted.
Tingfeng Dou, Cunde Xiao, Jiping Liu, Wei Han, Zhiheng Du, Andrew R. Mahoney, Joshua Jones, and Hajo Eicken
The Cryosphere, 13, 1233–1246, https://doi.org/10.5194/tc-13-1233-2019, https://doi.org/10.5194/tc-13-1233-2019, 2019
Short summary
Short summary
The variability and potential trends of rain-on-snow events over Arctic sea ice and their role in sea-ice losses are poorly understood. This study demonstrates that rain-on-snow events are a critical factor in initiating the onset of surface melt over Arctic sea ice, and onset of spring rainfall over sea ice has shifted to earlier dates since the 1970s, which may have profound impacts on ice melt through feedbacks involving earlier onset of surface melt.
Yuanyuan Zhang, Xiao Cheng, Jiping Liu, and Fengming Hui
The Cryosphere, 12, 3747–3757, https://doi.org/10.5194/tc-12-3747-2018, https://doi.org/10.5194/tc-12-3747-2018, 2018
Xinhua Zhou, Qinghua Yang, Xiaojie Zhen, Yubin Li, Guanghua Hao, Hui Shen, Tian Gao, Yirong Sun, and Ning Zheng
Atmos. Meas. Tech., 11, 5981–6002, https://doi.org/10.5194/amt-11-5981-2018, https://doi.org/10.5194/amt-11-5981-2018, 2018
Short summary
Short summary
The three-dimensional wind and sonic temperature data from a physically deformed sonic anemometer was successfully recovered by developing equations, algorithms, and related software. Using two sets of geometry data from production calibration and return re-calibration, this algorithm can recover wind with/without transducer shadow correction and sonic temperature with crosswind correction, and then obtain fluxes at quality as expected. This study is applicable as a reference for related topics.
Thomas Kaminski, Frank Kauker, Leif Toudal Pedersen, Michael Voßbeck, Helmuth Haak, Laura Niederdrenk, Stefan Hendricks, Robert Ricker, Michael Karcher, Hajo Eicken, and Ola Gråbak
The Cryosphere, 12, 2569–2594, https://doi.org/10.5194/tc-12-2569-2018, https://doi.org/10.5194/tc-12-2569-2018, 2018
Short summary
Short summary
We present mathematically rigorous assessments of the observation impact (added value) of remote-sensing products and in terms of the uncertainty reduction in a 4-week forecast of sea ice volume and snow volume for three regions along the Northern Sea Route by a coupled model of the sea-ice–ocean system. We quantify the difference in impact between rawer (freeboard) and higher-level (sea ice thickness) products, and the impact of adding a snow depth product.
Lu Zhou, Shiming Xu, Jiping Liu, and Bin Wang
The Cryosphere, 12, 993–1012, https://doi.org/10.5194/tc-12-993-2018, https://doi.org/10.5194/tc-12-993-2018, 2018
Short summary
Short summary
This work proposes a new data synergy method for the retrieval of sea ice thickness and snow depth by using colocating L-band passive remote sensing and active laser altimetry. Physical models are adopted for the retrieval, including L-band radiation model and buoyancy relationship. Covariability of snow depth and total freeboard is further utilized to mitigate resolution differences and improve retrievability. The method can be applied to future campaigns including ICESat-2 and WCOM.
Chao-Yuan Yang, Jiping Liu, Yongyun Hu, Radley M. Horton, Liqi Chen, and Xiao Cheng
The Cryosphere, 10, 2429–2452, https://doi.org/10.5194/tc-10-2429-2016, https://doi.org/10.5194/tc-10-2429-2016, 2016
Short summary
Short summary
The anomaly correlation analysis between the decadal hindcast and observed sea ice suggests that in the Arctic, the areas showing significant predictive skill become broader associated with increasing lead times. This area expansion is largely because nearly all the models are capable of predicting the observed decreasing Arctic sea ice cover. Antarctic sea ice decadal hindcasts do not show broad predictive skill at any timescales.
Qinghua Yang, Martin Losch, Svetlana N. Losa, Thomas Jung, Lars Nerger, and Thomas Lavergne
The Cryosphere, 10, 761–774, https://doi.org/10.5194/tc-10-761-2016, https://doi.org/10.5194/tc-10-761-2016, 2016
Short summary
Short summary
We assimilate the summer SICCI sea ice concentration data with an ensemble-based Kalman Filter. Comparing with the approach using a constant data uncertainty, the sea ice concentration estimates are further improved when the SICCI-provided uncertainty are taken into account, but the sea ice thickness cannot be improved. We find the data assimilation system cannot give a reasonable ensemble spread of sea ice concentration and thickness if the provided uncertainty are directly used.
S. Xu, B. Wang, and J. Liu
Geosci. Model Dev., 8, 3471–3485, https://doi.org/10.5194/gmd-8-3471-2015, https://doi.org/10.5194/gmd-8-3471-2015, 2015
Short summary
Short summary
This article applies Schwarz-Christoffel (SC) conformal mappings for single-connected and multiple-connected regions to the generation of general orthogonal grids for OGCMs, to achieve 1) the enlarged lat-lon proportion, 2) the removal of landmass and easier load balancing, 3) better spatial resolution on continental boundaries, and 4) alignment of grid lines to large-scale coastlines. The generated grids could be readily utilized by the majority of OGCMs that support general orthogonal grids.
F. Kauker, T. Kaminski, R. Ricker, L. Toudal-Pedersen, G. Dybkjaer, C. Melsheimer, S. Eastwood, H. Sumata, M. Karcher, and R. Gerdes
The Cryosphere Discuss., https://doi.org/10.5194/tcd-9-5521-2015, https://doi.org/10.5194/tcd-9-5521-2015, 2015
Revised manuscript not accepted
Short summary
Short summary
The manuscript describes the use of remotely sensed sea ice observations for the initialization of seasonal sea ice predictions. Among other observations, CryoSat-2 ice thickness is, to our knowledge for the first time, utilized. While a direct assimilation with CryoSat ice thickness could improve the predictions only locally, the use an advanced data assimilation system (4dVar) allows to establish a bias correction scheme, which is shown to improve the seasonal predictions Arctic wide.
Related subject area
Discipline: Sea ice | Subject: Antarctic
The response of sea ice and high-salinity shelf water in the Ross Ice Shelf Polynya to cyclonic atmosphere circulations
Antarctic sea ice regime shift associated with decreasing zonal symmetry in the Southern Annular Mode
Evolution of the dynamics, area, and ice production of the Amundsen Sea Polynya, Antarctica, 2016–2021
Modulation of the seasonal cycle of the Antarctic sea ice extent by sea ice processes and feedbacks with the ocean and the atmosphere
Ice Sheet and Sea Ice Ultrawideband Microwave radiometric Airborne eXperiment (ISSIUMAX) in Antarctica: first results from Terra Nova Bay
Influence of fast ice on future ice shelf melting in the Totten Glacier area, East Antarctica
A comparison between Envisat and ICESat sea ice thickness in the Southern Ocean
An indicator of sea ice variability for the Antarctic marginal ice zone
Physical and mechanical properties of winter first-year ice in the Antarctic marginal ice zone along the Good Hope Line
Altimetric observation of wave attenuation through the Antarctic marginal ice zone using ICESat-2
Flexural and compressive strength of the landfast sea ice in the Prydz Bay, East Antarctic
An evaluation of Antarctic sea-ice thickness from the Global Ice-Ocean Modeling and Assimilation System based on in situ and satellite observations
Rectification and validation of a daily satellite-derived Antarctic sea ice velocity product
Weddell Sea polynya analysis using SMOS–SMAP apparent sea ice thickness retrieval
Eighteen-year record of circum-Antarctic landfast-sea-ice distribution allows detailed baseline characterisation and reveals trends and variability
Brief communication: The anomalous winter 2019 sea-ice conditions in McMurdo Sound, Antarctica
Southern Ocean polynyas in CMIP6 models
Airborne mapping of the sub-ice platelet layer under fast ice in McMurdo Sound, Antarctica
Evaluation of sea-ice thickness from four reanalyses in the Antarctic Weddell Sea
The Antarctic sea ice cover from ICESat-2 and CryoSat-2: freeboard, snow depth, and ice thickness
Seasonal and interannual variability of landfast sea ice in Atka Bay, Weddell Sea, Antarctica
Influence of sea-ice anomalies on Antarctic precipitation using source attribution in the Community Earth System Model
Retrieval of snow freeboard of Antarctic sea ice using waveform fitting of CryoSat-2 returns
Three years of sea ice freeboard, snow depth, and ice thickness of the Weddell Sea from Operation IceBridge and CryoSat-2
Xiaoqiao Wang, Zhaoru Zhang, Michael S. Dinniman, Petteri Uotila, Xichen Li, and Meng Zhou
The Cryosphere, 17, 1107–1126, https://doi.org/10.5194/tc-17-1107-2023, https://doi.org/10.5194/tc-17-1107-2023, 2023
Short summary
Short summary
The bottom water of the global ocean originates from high-salinity water formed in polynyas in the Southern Ocean where sea ice coverage is low. This study reveals the impacts of cyclones on sea ice and water mass formation in the Ross Ice Shelf Polynya using numerical simulations. Sea ice production is rapidly increased caused by enhancement in offshore wind, promoting high-salinity water formation in the polynya. Cyclones also modulate the transport of this water mass by wind-driven currents.
Serena Schroeter, Terence J. O'Kane, and Paul A. Sandery
The Cryosphere, 17, 701–717, https://doi.org/10.5194/tc-17-701-2023, https://doi.org/10.5194/tc-17-701-2023, 2023
Short summary
Short summary
Antarctic sea ice has increased over much of the satellite record, but we show that the early, strongly opposing regional trends diminish and reverse over time, leading to overall negative trends in recent decades. The dominant pattern of atmospheric flow has changed from strongly east–west to more wave-like with enhanced north–south winds. Sea surface temperatures have also changed from circumpolar cooling to regional warming, suggesting recent record low sea ice will not rapidly recover.
Grant J. Macdonald, Stephen F. Ackley, Alberto M. Mestas-Nuñez, and Adrià Blanco-Cabanillas
The Cryosphere, 17, 457–476, https://doi.org/10.5194/tc-17-457-2023, https://doi.org/10.5194/tc-17-457-2023, 2023
Short summary
Short summary
Polynyas are key sites of sea ice production, biological activity, and carbon sequestration. The Amundsen Sea Polynya is of particular interest due to its size and location. By analyzing radar imagery and climate and sea ice data products, we evaluate variations in the dynamics, area, and ice production of the Amundsen Sea Polynya. In particular, we find the local seafloor topography and associated grounded icebergs play an important role in the polynya dynamics, influencing ice production.
Hugues Goosse, Sofia Allende Contador, Cecilia M. Bitz, Edward Blanchard-Wrigglesworth, Clare Eayrs, Thierry Fichefet, Kenza Himmich, Pierre-Vincent Huot, François Klein, Sylvain Marchi, François Massonnet, Bianca Mezzina, Charles Pelletier, Lettie Roach, Martin Vancoppenolle, and Nicole P. M. van Lipzig
The Cryosphere, 17, 407–425, https://doi.org/10.5194/tc-17-407-2023, https://doi.org/10.5194/tc-17-407-2023, 2023
Short summary
Short summary
Using idealized sensitivity experiments with a regional atmosphere–ocean–sea ice model, we show that sea ice advance is constrained by initial conditions in March and the retreat season is influenced by the magnitude of several physical processes, in particular by the ice–albedo feedback and ice transport. Atmospheric feedbacks amplify the response of the winter ice extent to perturbations, while some negative feedbacks related to heat conduction fluxes act on the ice volume.
Marco Brogioni, Mark J. Andrews, Stefano Urbini, Kenneth C. Jezek, Joel T. Johnson, Marion Leduc-Leballeur, Giovanni Macelloni, Stephen F. Ackley, Alexandra Bringer, Ludovic Brucker, Oguz Demir, Giacomo Fontanelli, Caglar Yardim, Lars Kaleschke, Francesco Montomoli, Leung Tsang, Silvia Becagli, and Massimo Frezzotti
The Cryosphere, 17, 255–278, https://doi.org/10.5194/tc-17-255-2023, https://doi.org/10.5194/tc-17-255-2023, 2023
Short summary
Short summary
In 2018 the first Antarctic campaign of UWBRAD was carried out. UWBRAD is a new radiometer able to collect microwave spectral signatures over 0.5–2 GHz, thus outperforming existing similar sensors. It allows us to probe thicker sea ice and ice sheet down to the bedrock. In this work we tried to assess the UWBRAD potentials for sea ice, glaciers, ice shelves and buried lakes. We also highlighted the wider range of information the spectral signature can provide to glaciological studies.
Guillian Van Achter, Thierry Fichefet, Hugues Goosse, and Eduardo Moreno-Chamarro
The Cryosphere, 16, 4745–4761, https://doi.org/10.5194/tc-16-4745-2022, https://doi.org/10.5194/tc-16-4745-2022, 2022
Short summary
Short summary
We investigate the changes in ocean–ice interactions in the Totten Glacier area between the last decades (1995–2014) and the end of the 21st century (2081–2100) under warmer climate conditions. By the end of the 21st century, the sea ice is strongly reduced, and the ocean circulation close to the coast is accelerated. Our research highlights the importance of including representations of fast ice to simulate realistic ice shelf melt rate increase in East Antarctica under warming conditions.
Jinfei Wang, Chao Min, Robert Ricker, Qian Shi, Bo Han, Stefan Hendricks, Renhao Wu, and Qinghua Yang
The Cryosphere, 16, 4473–4490, https://doi.org/10.5194/tc-16-4473-2022, https://doi.org/10.5194/tc-16-4473-2022, 2022
Short summary
Short summary
The differences between Envisat and ICESat sea ice thickness (SIT) reveal significant temporal and spatial variations. Our findings suggest that both overestimation of Envisat sea ice freeboard, potentially caused by radar backscatter originating from inside the snow layer, and the AMSR-E snow depth biases and sea ice density uncertainties can possibly account for the differences between Envisat and ICESat SIT.
Marcello Vichi
The Cryosphere, 16, 4087–4106, https://doi.org/10.5194/tc-16-4087-2022, https://doi.org/10.5194/tc-16-4087-2022, 2022
Short summary
Short summary
The marginal ice zone (MIZ) in the Antarctic is the largest in the world ocean. Antarctic sea ice has large year-to-year changes, and the MIZ represents its most variable component. Processes typical of the MIZ have also been observed in fully ice-covered ocean and are not captured by existing diagnostics. A new statistical method has been shown to address previous limitations in assessing the seasonal cycle of MIZ extent and to provide a probability map of sea ice state in the Southern Ocean.
Sebastian Skatulla, Riesna R. Audh, Andrea Cook, Ehlke Hepworth, Siobhan Johnson, Doru C. Lupascu, Keith MacHutchon, Rutger Marquart, Tommy Mielke, Emmanuel Omatuku, Felix Paul, Tokoloho Rampai, Jörg Schröder, Carina Schwarz, and Marcello Vichi
The Cryosphere, 16, 2899–2925, https://doi.org/10.5194/tc-16-2899-2022, https://doi.org/10.5194/tc-16-2899-2022, 2022
Short summary
Short summary
First-year sea ice has been sampled at the advancing outer edge of the Antarctic marginal ice zone (MIZ) along the Good Hope Line. Ice cores were extracted from five pancake ice floes and subsequently analysed for their physical and mechanical properties. Of particular interest was elucidating the transition of ice composition within the MIZ in terms of differences in mechanical stiffness and strength properties as linked to physical and textural characteristics at early-stage ice formation.
Jill Brouwer, Alexander D. Fraser, Damian J. Murphy, Pat Wongpan, Alberto Alberello, Alison Kohout, Christopher Horvat, Simon Wotherspoon, Robert A. Massom, Jessica Cartwright, and Guy D. Williams
The Cryosphere, 16, 2325–2353, https://doi.org/10.5194/tc-16-2325-2022, https://doi.org/10.5194/tc-16-2325-2022, 2022
Short summary
Short summary
The marginal ice zone is the region where ocean waves interact with sea ice. Although this important region influences many sea ice, ocean and biological processes, it has been difficult to accurately measure on a large scale from satellite instruments. We present new techniques for measuring wave attenuation using the NASA ICESat-2 laser altimeter. By measuring how waves attenuate within the sea ice, we show that the marginal ice zone may be far wider than previously realised.
Qingkai Wang, Zhaoquan Li, Peng Lu, Yigang Xu, and Zhijun Li
The Cryosphere, 16, 1941–1961, https://doi.org/10.5194/tc-16-1941-2022, https://doi.org/10.5194/tc-16-1941-2022, 2022
Short summary
Short summary
A large area of landfast sea ice exists in the Prydz Bay, and it is always a safety concern to transport cargos on ice to the research stations. Knowing the mechanical properties of sea ice is helpful to solve the issue; however, these data are rarely reported in this region. We explore the effects of sea ice physical properties on the flexural strength, effective elastic modulus, and uniaxial compressive strength, which gives new insights into assessing the bearing capacity of landfast sea ice.
Sutao Liao, Hao Luo, Jinfei Wang, Qian Shi, Jinlun Zhang, and Qinghua Yang
The Cryosphere, 16, 1807–1819, https://doi.org/10.5194/tc-16-1807-2022, https://doi.org/10.5194/tc-16-1807-2022, 2022
Short summary
Short summary
The Global Ice-Ocean Modeling and Assimilation System (GIOMAS) can basically reproduce the observed variability in Antarctic sea-ice volume and its changes in the trend before and after 2013, and it underestimates Antarctic sea-ice thickness (SIT) especially in deformed ice zones. Assimilating additional sea-ice observations with advanced assimilation methods may result in a more accurate estimation of Antarctic SIT.
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
Short summary
Short summary
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.
Alexander Mchedlishvili, Gunnar Spreen, Christian Melsheimer, and Marcus Huntemann
The Cryosphere, 16, 471–487, https://doi.org/10.5194/tc-16-471-2022, https://doi.org/10.5194/tc-16-471-2022, 2022
Short summary
Short summary
In this paper we show that the activity leading to the open-ocean polynyas near the Maud Rise seamount that have occurred repeatedly from 1974–1976 as well as 2016–2017 does not simply stop for polynya-free years. Using apparent sea ice thickness retrieval, we have identified anomalies where there is thinning of sea ice on a scale that is comparable to that of the polynya events of 2016–2017. These anomalies took place in 2010, 2013, 2014 and 2018.
Alexander D. Fraser, Robert A. Massom, Mark S. Handcock, Phillip Reid, Kay I. Ohshima, Marilyn N. Raphael, Jessica Cartwright, Andrew R. Klekociuk, Zhaohui Wang, and Richard Porter-Smith
The Cryosphere, 15, 5061–5077, https://doi.org/10.5194/tc-15-5061-2021, https://doi.org/10.5194/tc-15-5061-2021, 2021
Short summary
Short summary
Landfast ice is sea ice that remains stationary by attaching to Antarctica's coastline and grounded icebergs. Although a variable feature, landfast ice exerts influence on key coastal processes involving pack ice, the ice sheet, ocean, and atmosphere and is of ecological importance. We present a first analysis of change in landfast ice over an 18-year period and quantify trends (−0.19 ± 0.18 % yr−1). This analysis forms a reference of landfast-ice extent and variability for use in other studies.
Greg H. Leonard, Kate E. Turner, Maren E. Richter, Maddy S. Whittaker, and Inga J. Smith
The Cryosphere, 15, 4999–5006, https://doi.org/10.5194/tc-15-4999-2021, https://doi.org/10.5194/tc-15-4999-2021, 2021
Short summary
Short summary
McMurdo Sound sea ice can generally be partitioned into two regimes: a stable fast-ice cover forming south of approximately 77.6° S and a more dynamic region north of 77.6° S that is regularly impacted by polynyas. In 2019, a stable fast-ice cover formed unusually late due to repeated break-out events. This subsequently affected sea-ice operations in the 2019/20 field season. We analysed the 2019 sea-ice conditions and found a strong correlation with unusually large southerly wind events.
Martin Mohrmann, Céline Heuzé, and Sebastiaan Swart
The Cryosphere, 15, 4281–4313, https://doi.org/10.5194/tc-15-4281-2021, https://doi.org/10.5194/tc-15-4281-2021, 2021
Short summary
Short summary
Polynyas are large open-water areas within the sea ice. We developed a method to estimate their area, distribution and frequency for the Southern Ocean in climate models and observations. All models have polynyas along the coast but few do so in the open ocean, in contrast to observations. We examine potential atmospheric and oceanic drivers of open-water polynyas and discuss recently implemented schemes that may have improved some models' polynya representation.
Christian Haas, Patricia J. Langhorne, Wolfgang Rack, Greg H. Leonard, Gemma M. Brett, Daniel Price, Justin F. Beckers, and Alex J. Gough
The Cryosphere, 15, 247–264, https://doi.org/10.5194/tc-15-247-2021, https://doi.org/10.5194/tc-15-247-2021, 2021
Short summary
Short summary
We developed a method to remotely detect proxy signals of Antarctic ice shelf melt under adjacent sea ice. It is based on aircraft surveys with electromagnetic induction sounding. We found year-to-year variability of the ice shelf melt proxy in McMurdo Sound and spatial fine structure that support assumptions about the melt of the McMurdo Ice Shelf. With this method it will be possible to map and detect locations of intense ice shelf melt along the coast of Antarctica.
Qian Shi, Qinghua Yang, Longjiang Mu, Jinfei Wang, François Massonnet, and Matthew R. Mazloff
The Cryosphere, 15, 31–47, https://doi.org/10.5194/tc-15-31-2021, https://doi.org/10.5194/tc-15-31-2021, 2021
Short summary
Short summary
The ice thickness from four state-of-the-art reanalyses (GECCO2, SOSE, NEMO-EnKF and GIOMAS) are evaluated against that from remote sensing and in situ observations in the Weddell Sea, Antarctica. Most of the reanalyses can reproduce ice thickness in the central and eastern Weddell Sea but failed to capture the thick and deformed ice in the western Weddell Sea. These results demonstrate the possibilities and limitations of using current sea-ice reanalysis in Antarctic climate research.
Sahra Kacimi and Ron Kwok
The Cryosphere, 14, 4453–4474, https://doi.org/10.5194/tc-14-4453-2020, https://doi.org/10.5194/tc-14-4453-2020, 2020
Short summary
Short summary
Our current understanding of Antarctic ice cover is largely informed by ice extent measurements from passive microwave sensors. These records, while useful, provide a limited picture of how the ice is responding to climate change. In this paper, we combine measurements from ICESat-2 and CryoSat-2 missions to assess snow depth and ice thickness of the Antarctic ice cover over an 8-month period (April through November 2019). The potential impact of salinity in the snow layer is discussed.
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
Hailong Wang, Jeremy G. Fyke, Jan T. M. Lenaerts, Jesse M. Nusbaumer, Hansi Singh, David Noone, Philip J. Rasch, and Rudong Zhang
The Cryosphere, 14, 429–444, https://doi.org/10.5194/tc-14-429-2020, https://doi.org/10.5194/tc-14-429-2020, 2020
Short summary
Short summary
Using a climate model with unique water source tagging, we found that sea-ice anomalies in the Southern Ocean and accompanying SST changes have a significant influence on Antarctic precipitation and its source attribution through their direct impact on moisture sources and indirect impact on moisture transport. This study also highlights the importance of atmospheric dynamics in affecting the thermodynamic impact of sea-ice anomalies on regional Antarctic precipitation.
Steven W. Fons and Nathan T. Kurtz
The Cryosphere, 13, 861–878, https://doi.org/10.5194/tc-13-861-2019, https://doi.org/10.5194/tc-13-861-2019, 2019
Short summary
Short summary
A method to measure the snow freeboard of Antarctic sea ice from CryoSat-2 data is developed. Through comparisons with data from airborne campaigns and another satellite mission, we find that this method can reasonably retrieve snow freeboard across the Antarctic and shows promise in retrieving snow depth in certain locations. Snow freeboard data from CryoSat-2 are important because they enable the calculation of sea ice thickness and help to better understand snow depth on Antarctic sea ice.
Ron Kwok and Sahra Kacimi
The Cryosphere, 12, 2789–2801, https://doi.org/10.5194/tc-12-2789-2018, https://doi.org/10.5194/tc-12-2789-2018, 2018
Short summary
Short summary
The variability of snow depth and ice thickness in three years of repeat surveys of an IceBridge (OIB) transect across the Weddell Sea is examined. Retrieved thicknesses suggest a highly variable but broadly thicker ice cover compared to that inferred from drilling and ship-based measurements. The use of lidar and radar altimeters to estimate snow depth for thickness calculations is analyzed, and the need for better characterization of biases due to radar penetration effects is highlighted.
Cited articles
Barthélemy, A., Goosse, H., Fichefet, T., and Lecomte, O.: On the
sensitivity of Antarctic sea ice model biases to atmospheric forcing
uncertainties, Clim. Dynam., 51, 1585–1603,
https://doi.org/10.1007/s00382-017-3972-7, 2018.
Bitz, C. M., Holland, M. M., Weaver, A. J., and Eby, M.: Simulating the
ice-thickness distribution in a coupled climate model, J. Geophys. Res.-Oceans, 106, 2441–2463, https://doi.org/10.1029/1999JC000113, 2001.
Bracegirdle, T. J. and Marshall, G. J.: The reliability of Antarctic
tropospheric pressure and temperature in the latest global reanalyses, J.
Climate, 25, 7138–7146, https://doi.org/10.1175/JCLI-D-11-00685.1, 2012.
Briegleb, B. P. and Light, B.: A Delta-Eddington multiple scattering
parameterization for solar radiation in the sea ice component of the
Community Climate System Model, NCAR Tech. Note NCAR/TN-472+ STR, 1-108,
https://github.com/CICE-Consortium/CICE/blob/master/doc/PDF/BL_NCAR2007.pdf (last access: 14 May 2022), 2007.
Bromwich, D. H., Fogt, R. L., Hodges, K. I., and Walsh, J. E.: A
tropospheric assessment of the ERA-40, NCEP, and JRA-25 global reanalyses in
the polar regions, J. Geophys. Res.-Atmos., 112, D10111,
https://doi.org/10.1029/2006JD007859, 2007.
Chemke, R. and Polvani, L. M.: Using multiple large ensembles to elucidate
the discrepancy between the 1979–2019 modeled and observed Antarctic sea
ice trends, Geophys. Res. Lett., 47, e2020G–e88339G,
https://doi.org/10.1029/2020GL088339, 2020.
Cheng, B., Zhang, Z., Vihma, T., Johansson, M., Bian, L., Li, Z., and Wu,
H.: Model experiments on snow and ice thermodynamics in the Arctic Ocean
with CHINARE 2003 data, J. Geophys. Res.-Oceans, 113, C9020,
https://doi.org/10.1029/2007JC004654, 2008.
Cheng, B., Mäkynen, M., Similä, M., Rontu, L., and Vihma, T.:
Modelling snow and ice thickness in the coastal Kara Sea, Russian Arctic,
Ann. Glaciol., 54, 105–113, https://doi.org/10.3189/2013AoG62A180, 2013.
Collins, W. D., Bitz, C. M., Blackmon, M. L., Bonan, G. B., Bretherton, C.
S., Carton, J. A., Chang, P., Doney, S. C., Hack, J. J., and Henderson, T.
B.: The community climate system model version 3 (CCSM3), J. Climate, 19,
2122–2143, https://doi.org/10.1175/JCLI3761.1, 2006.
Fairall, C. W., Bradley, E. F., Hare, J. E., Grachev, A. A., and Edson, J.
B.: Bulk parameterization of air–sea fluxes: Updates and verification for
the COARE algorithm, J. Climate, 16, 571–591,
https://doi.org/10.1175/1520-0442(2003)016<0571:BPOASF>2.0.CO;2,
2003.
Fréville, H., Brun, E., Picard, G., Tatarinova, N., Arnaud, L., Lanconelli, C., Reijmer, C., and van den Broeke, M.: Using MODIS land surface temperatures and the Crocus snow model to understand the warm bias of ERA-Interim reanalyses at the surface in Antarctica, The Cryosphere, 8, 1361–1373, https://doi.org/10.5194/tc-8-1361-2014, 2014.
Frezzotti, M., Pourchet, M., Flora, O., Gandolfi, S., Gay, M., Urbini, S.,
Vincent, C., Becagli, S., Gragnani, R., and Proposito, M.: Spatial and
temporal variability of snow accumulation in East Antarctica from traverse
data, J. Glaciol., 51, 113–124, https://doi.org/10.3189/172756505781829502,
2005.
Gascoin, S., Lhermitte, S., Kinnard, C., Bortels, K., and Liston, G. E.:
Wind effects on snow cover in Pascua-Lama, Dry Andes of Chile, Adv. Water
Resour., 55, 25–39, https://doi.org/10.1016/j.advwatres.2012.11.013, 2013.
Granskog, M. A., Leppäranta, M., Kawamura, T., Ehn, J., and Shirasawa,
K.: Seasonal development of the properties and composition of landfast sea
ice in the Gulf of Finland, the Baltic Sea, J. Geophys. Res.-Oceans, 109,
C02020, https://doi.org/10.1029/2003JC001874, 2004.
Hao, G., Yang, Q., Zhao, J., Deng, X., Yang, Y., Duan, P., Zhang, L., Li,
C., and Cui, L.: Observation and analysis of landfast ice arounding
Zhongshan Station, Antarctic in 2016, Haiyang Xuebao, 9, 26–39,
https://doi.org/10.3969/j.issn.0253-4193.2019.09.003, 2019.
Hao, G., Pirazzini, R., Yang, Q., Tian, Z., and Liu, C.: Spectral albedo of
coastal landfast sea ice in Prydz Bay, Antarctica, J. Glaciol., 67, 1–11,
https://doi.org/10.1017/jog.2020.90, 2020.
Heil, P.: Atmospheric conditions and fast ice at Davis, East Antarctica: A
case study, J. Geophys. Res.-Oceans, 111, C5009,
https://doi.org/10.1029/2005JC002904, 2006.
Heil, P., Allison, I., and Lytle, V. I.: Seasonal and interannual variations
of the oceanic heat flux under a landfast Antarctic sea ice cover, J.
Geophys. Res.-Oceans, 101, 25741–25752, https://doi.org/10.1029/96JC01921,
1996.
Hersbach, H. and Dee, D.: ERA5 reanalysis is in production, ECMWF
Newsletter 147,
https://www.ecmwf.int/en/newsletter/147/news/era5-reanalysis-production (last access: 29 April 2020),
2016.
Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., and Thépaut, J.-N.: ERA5 hourly data on single levels from 1979 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set], https://doi.org/10.24381/cds.adbb2d47, 2018.
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A.,
Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., and Schepers, D.:
The ERA5 global reanalysis, Q. J. Roy. Meteor. Soc., 146, 1999–2049,
https://doi.org/10.1002/qj.3803, 2020.
Hunke, E., Allard, R., Bailey, D. A., Blain, P., Craig, T., Dupont, F.,
DuVivier, A., Grumbine, R., Hebert, D., Holland, M., Jeffery, N., Lemieux,
J., Rasmussen, T., Ribergaard, M., Roberts, A., Turner, M., and Winton, M.:
CICE-Consortium/Icepack: Icepack1.1.1, Zenodo [code],
https://doi.org/10.5281/zenodo.3251032, 2019.
Jakobs, C. L., Reijmer, C. H., Smeets, C. P., Trusel, L. D., Van De Berg, W.
J., Van Den Broeke, M. R., and Van Wessem, J. M.: A benchmark dataset of in
situ Antarctic surface melt rates and energy balance, J. Glaciol., 66,
291–302, https://doi.org/10.1017/jog.2020.6, 2020.
Jeffries, M. O., Krouse, H. R., Hurst-Cushing, B., and Maksym, T.: Snow-ice
accretion and snow-cover depletion on Antarctic first-year sea-ice floes,
Ann. Glaciol., 33, 51–60, https://doi.org/10.3189/172756401781818266, 2001.
Jones, R. W., Renfrew, I. A., Orr, A., Webber, B., Holland, D. M., and
Lazzara, M. A.: Evaluation of four global reanalysis products using in situ
observations in the Amundsen Sea Embayment, Antarctica, J. Geophys. Res.-Atmos., 121, 6240–6257, https://doi.org/10.1002/2015JD024680, 2016.
Kawamura, T., Ohshima, K. I., Takizawa, T., and Ushio, S.: Physical,
structural, and isotopic characteristics and growth processes of fast sea
ice in Lützow-Holm Bay, Antarctica, J. Geophys. Res.-Oceans, 102,
3345–3355, https://doi.org/10.1029/96JC03206, 1997.
Lei, R., Li, Z., Cheng, B., Zhang, Z., and Heil, P.: Annual cycle of
landfast sea ice in Prydz Bay, east Antarctica, J. Geophys. Res.-Oceans,
115, C2006, https://doi.org/10.1029/2008JC005223, 2010.
Leppäranta, M.: A growth model for black ice, snow ice and snow
thickness in subarctic basins, Hydrol. Res., 14, 59–70,
https://doi.org/10.2166/nh.1983.0006, 1983.
Lindsay, R. and Schweiger, A.: Arctic sea ice thickness loss determined using subsurface, aircraft, and satellite observations, The Cryosphere, 9, 269–283, https://doi.org/10.5194/tc-9-269-2015, 2015.
Lindsay, R., Wensnahan, M., Schweiger, A., and Zhang, J.: Evaluation of
seven different atmospheric reanalysis products in the Arctic, J. Climate,
27, 2588–2606, https://doi.org/10.1175/JCLI-D-13-00014.1, 2014.
Liston, G. E., Polashenski, C., Rösel, A., Itkin, P., King, J.,
Merkouriadi, I., and Haapala, J.: A distributed snow-evolution model for
sea-ice applications (SnowModel), J. Geophys. Res.-Oceans, 123, 3786–3810,
https://doi.org/10.1002/2017JC013706, 2018.
Liu, C., Gao, Z., Yang, Q., Han, B., Wang, H., Hao, G., Zhao, J., Yu, L.,
Wang, L., and Li, Y.: Measurements of turbulence transfer in the
near-surface layer over the Antarctic sea-ice surface from April through
November in 2016, Ann. Glaciol., 61, 12–23,
https://doi.org/10.1017/aog.2019.48, 2020.
Liu, C., Hao, G., Li, Y., Zhao, J., Lei, R., Cheng, B., Gao, Z., and Yang,
Q.: The sensitivity of parameterization schemes in thermodynamic modeling of
the landfast sea ice in Prydz Bay, East Antarctica, J. Glaciol., 1–16,
https://doi.org/10.1017/jog.2022.8, 2022.
Massom, R. A., Eicken, H., Hass, C., Jeffries, M. O., Drinkwater, M. R.,
Sturm, M., Worby, A. P., Wu, X., Lytle, V. I., and Ushio, S.: Snow on
Antarctic sea ice, Rev. Geophys., 39, 413–445,
https://doi.org/10.1029/2000RG000085, 2001.
Massonnet, F., Fichefet, T., Goosse, H., Vancoppenolle, M., Mathiot, P., and König Beatty, C.: On the influence of model physics on simulations of Arctic and Antarctic sea ice, The Cryosphere, 5, 687–699, https://doi.org/10.5194/tc-5-687-2011, 2011.
Maykut, G. A. and McPhee, M. G.: Solar heating of the Arctic mixed layer,
J. Geophys. Res.-Oceans, 100, 24691–24703,
https://doi.org/10.1029/95JC02554, 1995.
Maykut, G. A. and Untersteiner, N.: Some results from a time-dependent
thermodynamic model of sea ice, J. Geophys. Res., 76, 1550–1575,
https://doi.org/10.1029/JC076i006p01550, 1971.
McPhee, M. G., Kottmeier, C., and Morison, J. H.: Ocean Heat Flux in the
Central Weddell Sea during Winter, J. Phys. Oceanogr., 29, 1166–1179,
https://doi.org/10.1175/1520-0485(1999)029<1166:OHFITC>2.0.CO;2,
1999.
Merkouriadi, I., Liston, G. E., Graham, R. M., and Granskog, M. A.:
Quantifying the potential for snow-ice formation in the Arctic Ocean,
Geophys. Res. Lett., 47, e2019GL085020,
https://doi.org/10.1029/2019GL085020, 2020.
Parkinson, C. L.: A 40-y record reveals gradual Antarctic sea ice increases
followed by decreases at rates far exceeding the rates seen in the Arctic,
P. Natl. Acad. Sci. USA, 116, 14414–14423,
https://doi.org/10.1073/pnas.1906556116, 2019.
Parkinson, C. L. and Cavalieri, D. J.: Antarctic sea ice variability and trends, 1979–2010, The Cryosphere, 6, 871–880, https://doi.org/10.5194/tc-6-871-2012, 2012.
Perovich, D. K. and Maykut, G. A.: Solar heating of a stratified ocean in
the presence of a static ice cover, J. Geophys. Res.-Oceans, 95,
18233–18245, https://doi.org/10.1029/JC095iC10p18233, 1990.
Powell, D. C., Markus, T., and Stössel, A.: Effects of snow depth forcing on Southern Ocean sea ice simulations, J. Geophys. Res.-Oceans, 110, C6001, https://doi.org/10.1029/2003JC002212, 2005.
Provost, C., Sennéchael, N., Miguet, J., Itkin, P., Rösel, A.,
Koenig, Z., Villacieros Robineau, N., and Granskog, M. A.: Observations of
flooding and snow-ice formation in a thinner Arctic sea-ice regime during
the N-ICE2015 campaign: Influence of basal ice melt and storms, J. Geophys.
Res.-Oceans, 122, 7115–7134, https://doi.org/10.1002/2016JC012011, 2017.
Roussel, M.-L., Lemonnier, F., Genthon, C., and Krinner, G.: Brief communication: Evaluating Antarctic precipitation in ERA5 and CMIP6 against CloudSat observations, The Cryosphere, 14, 2715–2727, https://doi.org/10.5194/tc-14-2715-2020, 2020.
Saloranta, T. M.: Modeling the evolution of snow, snow ice and ice in the
Baltic Sea, Tellus A, 52, 93–108,
https://doi.org/10.3402/tellusa.v52i1.12255, 2000.
Schlosser, E., Haumann, F. A., and Raphael, M. N.: Atmospheric influences on the anomalous 2016 Antarctic sea ice decay, The Cryosphere, 12, 1103–1119, https://doi.org/10.5194/tc-12-1103-2018, 2018.
Stroeve, J. C., Serreze, M. C., Holland, M. M., Kay, J. E., Malanik, J., and
Barrett, A. P.: The Arctic's rapidly shrinking sea ice cover: a research
synthesis, Clim. Change, 110, 1005–1027,
https://doi.org/10.1007/s10584-011-0101-1, 2012.
Stuecker, M. F., Bitz, C. M., and Armour, K. C.: Conditions leading to the
unprecedented low Antarctic sea ice extent during the 2016 austral spring
season, Geophys. Res. Lett., 44, 9008–9019,
https://doi.org/10.1002/2017GL074691, 2017.
Tanji, S., Inatsu, M., and Okaze, T.: Development of a snowdrift model with
the lattice Boltzmann method, Prog. Earth Planet. Sci., 8, 1–16,
https://doi.org/10.1186/s40645-021-00449-0, 2021.
Tetzner, D., Thomas, E., and Allen, C.: A Validation of ERA5 Reanalysis Data
in the Southern Antarctic Peninsula–Ellsworth Land Region, and Its
Implications for Ice Core Studies, Geosciences, 9, 289,
https://doi.org/10.3390/geosciences9070289, 2019.
Thiery, W., Gorodetskaya, I. V., Bintanja, R., Van Lipzig, N. P. M., Van den Broeke, M. R., Reijmer, C. H., and Kuipers Munneke, P.: Surface and snowdrift sublimation at Princess Elisabeth station, East Antarctica, The Cryosphere, 6, 841–857, https://doi.org/10.5194/tc-6-841-2012, 2012.
Tsamados, M., Feltham, D. L., and Wilchinsky, A. V.: Impact of a new
anisotropic rheology on simulations of Arctic sea ice, J. Geophys. Res.-Oceans, 118, 91–107, https://doi.org/10.1029/2012JC007990, 2013.
Turner, A. K. and Hunke, E. C.: Impacts of a mushy-layer thermodynamic
approach in global sea-ice simulations using the CICE sea-ice model, J.
Geophys. Res.-Oceans, 120, 1253–1275, https://doi.org/10.1002/2014JC010358,
2015.
Turner, A. K., Hunke, E. C., and Bitz, C. M.: Two modes of sea-ice gravity
drainage: A parameterization for large-scale modeling, J. Geophys. Res.-Oceans, 118, 2279–2294, https://doi.org/10.1002/jgrc.20171, 2013.
Turner, J., Phillips, T., Marshall, G. J., Hosking, J. S., Pope, J. O.,
Bracegirdle, T. J., and Deb, P.: Unprecedented springtime retreat of
Antarctic sea ice in 2016, Geophys. Res. Lett., 44, 6868–6875,
https://doi.org/10.1002/2017GL073656, 2017.
Uotila, P., Goosse, H., Haines, K., Chevallier, M., Barthélemy, A.,
Bricaud, C., Carton, J., Fučkar, N., Garric, G., and Iovino, D.: An
assessment of ten ocean reanalyses in the polar regions, Clim. Dynam., 52,
1613–1650, https://doi.org/10.1007/s00382-018-4242-z, 2019.
Urraca, R., Huld, T., Gracia-Amillo, A., Martinez-de-Pison, F. J., Kaspar,
F., and Sanz-Garcia, A.: Evaluation of global horizontal irradiance
estimates from ERA5 and COSMO-REA6 reanalyses using ground and
satellite-based data, Sol. Energy, 164, 339–354,
https://doi.org/10.1016/j.solener.2018.02.059, 2018.
Vancoppenolle, M., Timmermann, R., Ackley, S. F., Fichefet, T., Goosse, H.,
Heil, P., Leonard, K. C., Lieser, J., Nicolaus, M., and Papakyriakou, T.:
Assessment of radiation forcing data sets for large-scale sea ice models in
the Southern Ocean, Deep-Sea Res., Pt. II, 58, 1237–1249,
https://doi.org/10.1016/j.dsr2.2010.10.039, 2011.
Van Den Broeke, M. R., Winther, J., Isaksson, E., Pinglot, J. F.,
Karlöf, L., Eiken, T., and Conrads, L.: Climate variables along a
traverse line in Dronning Maud Land, East Antarctica, J. Glaciol., 45,
295–302, https://doi.org/10.3189/S0022143000001799, 1999.
Van Den Broeke, M., Reijmer, C., and Van De Wal, R.: Surface radiation
balance in Antarctica as measured with automatic weather stations, J.
Geophys. Res.-Atmos., 109, D09103, https://doi.org/10.1029/2003JD004394,
2004.
van den Broeke, M., van de Berg, W. J., van Meijgaard, E., and Reijmer, C.: Identification of Antarctic ablation areas using a regional atmospheric climate model, J. Geophys. Res.-Atmos, 111, D18110, https://doi.org/10.1029/2006JD007127, 2006.
Van Den Broeke, M. R., Reijmer, C. H., and Van De Wal, R. S.: A study of the
surface mass balance in Dronning Maud Land, Antarctica, using automatic
weather stations, J. Glaciol., 50, 565–582,
https://doi.org/10.3189/172756504781829756, 2004.
Vignon, é., Traullé, O., and Berne, A.: On the fine vertical structure of the low troposphere over the coastal margins of East Antarctica, Atmos. Chem. Phys., 19, 4659–4683, https://doi.org/10.5194/acp-19-4659-2019, 2019.
Wang, C., Cheng, B., Wang, K., Gerland, S., and Pavlova, O.: Modelling snow ice and superimposed ice on landfast sea ice in Kongsfjorden, Svalbard, Polar Res., 34, 20828, https://doi.org/10.3402/polar.v34.20828, 2015.
Wang, C., Graham, R. M., Wang, K., Gerland, S., and Granskog, M. A.: Comparison of ERA5 and ERA-Interim near-surface air temperature, snowfall and precipitation over Arctic sea ice: effects on sea ice thermodynamics and evolution, The Cryosphere, 13, 1661–1679, https://doi.org/10.5194/tc-13-1661-2019, 2019.
Wang, G., Hendon, H. H., Arblaster, J. M., Lim, E., Abhik, S., and van
Rensch, P.: Compounding tropical and stratospheric forcing of the record low
Antarctic sea-ice in 2016, Nat. Commun., 10, 1–9,
https://doi.org/10.1038/s41467-018-07689-7, 2019.
Wang, Y., Zhou, D., Bunde, A., and Havlin, S.: Testing reanalysis data sets
in Antarctica: Trends, persistence properties, and trend significance, J.
Geophys. Res.-Atmos., 121, 12–839, https://doi.org/10.1002/2016JD024864,
2016.
Yang, Q., Liu, J., Leppäranta, M., Sun, Q., Li, R., Zhang, L., Jung, T.,
Lei, R., Zhang, Z., and Li, M.: Albedo of coastal landfast sea ice in Prydz
Bay, Antarctica: Observations and parameterization, Adv. Atmos. Sci., 33,
535–543, https://doi.org/10.1007/s00376-015-5114-7, 2016a.
Yang, Y., Zhijun, L., Leppäranta, M., Cheng, B., Shi, L., and Lei, R.:
Modelling the thickness of landfast sea ice in Prydz Bay, East Antarctica,
Antarct. Sci., 28, 59–70, https://doi.org/10.1017/S0954102015000449, 2016b.
Zhang, J.: Increasing Antarctic sea ice under warming atmospheric and
oceanic conditions, J. Climate, 20, 2515–2529,
https://doi.org/10.1175/JCLI4136.1, 2007.
Zhang, J.: Modeling the impact of wind intensification on Antarctic sea ice
volume, J. Climate, 27, 202–214, https://doi.org/10.1175/JCLI-D-12-00139.1,
2014.
Zhao, J., Cheng, B., Yang, Q., Vihma, T., and Zhang, L.: Observations and
modelling of first-year ice growth and simultaneous second-year ice ablation
in the Prydz Bay, East Antarctica, Ann. Glaciol., 58, 59–67,
https://doi.org/10.1017/aog.2017.33, 2017.
Zhao, J., Cheng, B., Vihma, T., Yang, Q., Hui, F., Zhao, B., Hao, G., Shen,
H., and Zhang, L.: Observation and thermodynamic modeling of the influence
of snow cover on landfast sea ice thickness in Prydz Bay, East Antarctica,
Cold Reg. Sci. Technol., 168, 102869,
https://doi.org/10.1016/j.coldregions.2019.102869, 2019.
Short summary
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.
The sea ice thickness was simulated by a single-column model and compared with in situ...
