Articles | Volume 14, issue 7
https://doi.org/10.5194/essd-14-3075-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-14-3075-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A new digital elevation model (DEM) dataset of the entire Antarctic continent derived from ICESat-2
Xiaoyi Shen
School of Geography and Ocean Science, Nanjing University, Nanjing,
210023, China
Jiangsu Provincial Key Laboratory of Geographic Information Science
and Technology, Nanjing University, Nanjing, 210023, China
Chang-Qing Ke
CORRESPONDING AUTHOR
School of Geography and Ocean Science, Nanjing University, Nanjing,
210023, China
Jiangsu Provincial Key Laboratory of Geographic Information Science
and Technology, Nanjing University, Nanjing, 210023, China
Yubin Fan
School of Geography and Ocean Science, Nanjing University, Nanjing,
210023, China
Jiangsu Provincial Key Laboratory of Geographic Information Science
and Technology, Nanjing University, Nanjing, 210023, China
Lhakpa Drolma
Institute of Tibetan Plateau Atmospheric and Environmental Sciences,
Tibet Meteorological Bureau, Lhasa, 850000, China
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Yu Cai, Jingjing Wang, Yao Xiao, Zifei Wang, Xiaoyi Shen, Haili Li, and Chang-Qing Ke
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-441, https://doi.org/10.5194/essd-2023-441, 2024
Revised manuscript not accepted
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In this study, we re-explored the potential of passive microwaves in extracting lake ice freeze-thaw events. Brightness temperature and air temperature data were used to extract freeze-up and break-up records of 194 lakes on the Tibetan Plateau, providing complete lake ice records for a large number of small and medium-sized lakes for the first time. The dataset will provide valuable data for users interested in lake ice cover on the Tibetan Plateau over the last decade.
Yubin Fan, Chang-Qing Ke, Xiaoyi Shen, Yao Xiao, Stephen J. Livingstone, and Andrew J. Sole
The Cryosphere, 17, 1775–1786, https://doi.org/10.5194/tc-17-1775-2023, https://doi.org/10.5194/tc-17-1775-2023, 2023
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We used the new-generation ICESat-2 altimeter to detect and monitor active subglacial lakes in unprecedented spatiotemporal detail. We created a new inventory of 18 active subglacial lakes as well as their elevation and volume changes during 2019–2020, which provides an improved understanding of how the Greenland subglacial water system operates and how these lakes are fed by water from the ice surface.
Yubin Fan, Chang-Qing Ke, and Xiaoyi Shen
Earth Syst. Sci. Data, 14, 781–794, https://doi.org/10.5194/essd-14-781-2022, https://doi.org/10.5194/essd-14-781-2022, 2022
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A new digital elevation model of Greenland was provided based on the ICESat-2 observations acquired from November 2018 to November 2019. A model fit method was applied within the grid cells at different spatial resolutions to estimate the surface elevations with a modal resolution of 500 m. We estimated the uncertainty with a median difference of −0.48 m for all of Greenland, which can benefit studies of elevation change and mass balance in Greenland.
Xiaoyi Shen, Chang-Qing Ke, and Haili Li
Earth Syst. Sci. Data, 14, 619–636, https://doi.org/10.5194/essd-14-619-2022, https://doi.org/10.5194/essd-14-619-2022, 2022
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Snow over Antarctic sea ice controls energy budgets and thus has essential effects on the climate. Here, we estimated snow depth using microwave radiometers and a newly constructed, robust method by incorporating lower frequencies, which have been available from AMSR-E and AMSR-2. Comparing the new retrieval with in situ and shipborne snow depth measurements showed that this method outperformed the previously available method.
Haili Li, Chang-Qing Ke, Qinghui Zhu, and Xiaoyi Shen
The Cryosphere Discuss., https://doi.org/10.5194/tc-2021-271, https://doi.org/10.5194/tc-2021-271, 2021
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Here, we employ particle filter assimilation to combine snow depth values retrieved from remote sensing with those obtained from reanalysis reconstructions, and INESOSIM-PF is proposed. The results indicate that the proposed method improves the modeled snow depth, and the monthly and seasonal changes in the snow depth are consistent with those in the snow depth determined with two existing snow depth algorithms.
Xiaoyi Shen, Chang-Qing Ke, Yubin Fan, and Lhakpa Drolma
The Cryosphere Discuss., https://doi.org/10.5194/tc-2021-204, https://doi.org/10.5194/tc-2021-204, 2021
Manuscript not accepted for further review
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Obtaining the detailed surface topography in Antarctica is essential for human fieldwork planning, ice surface height changes and mass balance estimations. A definite time-stamped and fine-scale DEM for Antarctica with a modal resolution of 250 m is presented based on the surface height measurements from ICESat-2 by using a model fitting method, which is more valuable for further scientific applications, e.g., land ice height and mass balance estimations.
Yu Cai, Jingjing Wang, Yao Xiao, Zifei Wang, Xiaoyi Shen, Haili Li, and Chang-Qing Ke
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-441, https://doi.org/10.5194/essd-2023-441, 2024
Revised manuscript not accepted
Short summary
Short summary
In this study, we re-explored the potential of passive microwaves in extracting lake ice freeze-thaw events. Brightness temperature and air temperature data were used to extract freeze-up and break-up records of 194 lakes on the Tibetan Plateau, providing complete lake ice records for a large number of small and medium-sized lakes for the first time. The dataset will provide valuable data for users interested in lake ice cover on the Tibetan Plateau over the last decade.
Yubin Fan, Chang-Qing Ke, Xiaoyi Shen, Yao Xiao, Stephen J. Livingstone, and Andrew J. Sole
The Cryosphere, 17, 1775–1786, https://doi.org/10.5194/tc-17-1775-2023, https://doi.org/10.5194/tc-17-1775-2023, 2023
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We used the new-generation ICESat-2 altimeter to detect and monitor active subglacial lakes in unprecedented spatiotemporal detail. We created a new inventory of 18 active subglacial lakes as well as their elevation and volume changes during 2019–2020, which provides an improved understanding of how the Greenland subglacial water system operates and how these lakes are fed by water from the ice surface.
Yu Cai, Claude R. Duguay, and Chang-Qing Ke
Earth Syst. Sci. Data, 14, 3329–3347, https://doi.org/10.5194/essd-14-3329-2022, https://doi.org/10.5194/essd-14-3329-2022, 2022
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Seasonal ice cover is one of the important attributes of lakes in middle- and high-latitude regions. This study used passive microwave brightness temperature measurements to extract the ice phenology for 56 lakes across the Northern Hemisphere from 1979 to 2019. A threshold algorithm was applied according to the differences in brightness temperature between lake ice and open water. The dataset will provide valuable information about the changing ice cover of lakes over the last 4 decades.
Yubin Fan, Chang-Qing Ke, and Xiaoyi Shen
Earth Syst. Sci. Data, 14, 781–794, https://doi.org/10.5194/essd-14-781-2022, https://doi.org/10.5194/essd-14-781-2022, 2022
Short summary
Short summary
A new digital elevation model of Greenland was provided based on the ICESat-2 observations acquired from November 2018 to November 2019. A model fit method was applied within the grid cells at different spatial resolutions to estimate the surface elevations with a modal resolution of 500 m. We estimated the uncertainty with a median difference of −0.48 m for all of Greenland, which can benefit studies of elevation change and mass balance in Greenland.
Xiaoyi Shen, Chang-Qing Ke, and Haili Li
Earth Syst. Sci. Data, 14, 619–636, https://doi.org/10.5194/essd-14-619-2022, https://doi.org/10.5194/essd-14-619-2022, 2022
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Snow over Antarctic sea ice controls energy budgets and thus has essential effects on the climate. Here, we estimated snow depth using microwave radiometers and a newly constructed, robust method by incorporating lower frequencies, which have been available from AMSR-E and AMSR-2. Comparing the new retrieval with in situ and shipborne snow depth measurements showed that this method outperformed the previously available method.
Haili Li, Chang-Qing Ke, Qinghui Zhu, and Xiaoyi Shen
The Cryosphere Discuss., https://doi.org/10.5194/tc-2021-271, https://doi.org/10.5194/tc-2021-271, 2021
Revised manuscript not accepted
Short summary
Short summary
Here, we employ particle filter assimilation to combine snow depth values retrieved from remote sensing with those obtained from reanalysis reconstructions, and INESOSIM-PF is proposed. The results indicate that the proposed method improves the modeled snow depth, and the monthly and seasonal changes in the snow depth are consistent with those in the snow depth determined with two existing snow depth algorithms.
Xiaoyi Shen, Chang-Qing Ke, Yubin Fan, and Lhakpa Drolma
The Cryosphere Discuss., https://doi.org/10.5194/tc-2021-204, https://doi.org/10.5194/tc-2021-204, 2021
Manuscript not accepted for further review
Short summary
Short summary
Obtaining the detailed surface topography in Antarctica is essential for human fieldwork planning, ice surface height changes and mass balance estimations. A definite time-stamped and fine-scale DEM for Antarctica with a modal resolution of 250 m is presented based on the surface height measurements from ICESat-2 by using a model fitting method, which is more valuable for further scientific applications, e.g., land ice height and mass balance estimations.
Chang-Qing Ke, Xiu-Cang Li, Hongjie Xie, Dong-Hui Ma, Xun Liu, and Cheng Kou
Hydrol. Earth Syst. Sci., 20, 755–770, https://doi.org/10.5194/hess-20-755-2016, https://doi.org/10.5194/hess-20-755-2016, 2016
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The heavy snow years in China include 1955, 1957, 1964, and 2010, and light snow years include 1953, 1965, 1999, 2002, and 2009. The reduction in number of days with temperature below 0 °C and increase in mean air temperature are the main reasons for the delay of snow cover onset date and advance of snow cover end date. This explains why only 15 % of the stations show significant shortening of snow cover days and differ with the overall shortening of the snow period in the Northern Hemisphere.
J. Chen, C. Q. Ke, and Z. D. Shao
The Cryosphere Discuss., https://doi.org/10.5194/tcd-8-5875-2014, https://doi.org/10.5194/tcd-8-5875-2014, 2014
Revised manuscript not accepted
H. Xie, R. Lei, C. Ke, H. Wang, Z. Li, J. Zhao, and S. F. Ackley
The Cryosphere, 7, 1057–1072, https://doi.org/10.5194/tc-7-1057-2013, https://doi.org/10.5194/tc-7-1057-2013, 2013
Related subject area
Cryosphere – Radar measurements
A 30-year monthly 5 km gridded surface elevation time series for the Greenland Ice Sheet from multiple satellite radar altimeters
Airborne ultra-wideband radar sounding over the shear margins and along flow lines at the onset region of the Northeast Greenland Ice Stream
Polar maps of C-band backscatter parameters from the Advanced Scatterometer
A detailed radiostratigraphic data set for the central East Antarctic Plateau spanning from the Holocene to the mid-Pleistocene
Arctic sea ice cover data from spaceborne synthetic aperture radar by deep learning
First ice thickness measurements in Tierra del Fuego at Schiaparelli Glacier, Chile
Subglacial topography and ice flux along the English Coast of Palmer Land, Antarctic Peninsula
Bed topography of Princess Elizabeth Land in East Antarctica
Baojun Zhang, Zemin Wang, Jiachun An, Tingting Liu, and Hong Geng
Earth Syst. Sci. Data, 14, 973–989, https://doi.org/10.5194/essd-14-973-2022, https://doi.org/10.5194/essd-14-973-2022, 2022
Short summary
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A long-term time series of ice sheet surface elevation change essential for assessing climate change. This study presents a 30-year monthly 5 km gridded surface elevation time series for the Greenland Ice Sheet from multiple satellite radar altimeters. The dataset can provide detailed insight into Greenland Ice Sheet surface elevation change on multiple temporal and spatial scales, thereby providing an opportunity to explore potential associations between ice sheet change and climatic forcing.
Steven Franke, Daniela Jansen, Tobias Binder, John D. Paden, Nils Dörr, Tamara A. Gerber, Heinrich Miller, Dorthe Dahl-Jensen, Veit Helm, Daniel Steinhage, Ilka Weikusat, Frank Wilhelms, and Olaf Eisen
Earth Syst. Sci. Data, 14, 763–779, https://doi.org/10.5194/essd-14-763-2022, https://doi.org/10.5194/essd-14-763-2022, 2022
Short summary
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The Northeast Greenland Ice Stream (NEGIS) is the largest ice stream in Greenland. In order to better understand the past and future dynamics of the NEGIS, we present a high-resolution airborne radar data set (EGRIP-NOR-2018) for the onset region of the NEGIS. The survey area is centered at the location of the drill site of the East Greenland Ice-Core Project (EastGRIP), and radar profiles cover both shear margins and are aligned parallel to several flow lines.
Jessica Cartwright, Alexander D. Fraser, and Richard Porter-Smith
Earth Syst. Sci. Data, 14, 479–490, https://doi.org/10.5194/essd-14-479-2022, https://doi.org/10.5194/essd-14-479-2022, 2022
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Due to the scale and remote nature of the polar regions, it is essential to use satellite remote sensing to monitor and understand them and their dynamics. Here we present data from the Advanced Scatterometer (ASCAT), processed in a manner proven for use in cryosphere studies. The data have been processed on three timescales (5 d, 2 d and 1 d) in order to optimise temporal resolution as each of the three MetOp satellites is launched.
Marie G. P. Cavitte, Duncan A. Young, Robert Mulvaney, Catherine Ritz, Jamin S. Greenbaum, Gregory Ng, Scott D. Kempf, Enrica Quartini, Gail R. Muldoon, John Paden, Massimo Frezzotti, Jason L. Roberts, Carly R. Tozer, Dustin M. Schroeder, and Donald D. Blankenship
Earth Syst. Sci. Data, 13, 4759–4777, https://doi.org/10.5194/essd-13-4759-2021, https://doi.org/10.5194/essd-13-4759-2021, 2021
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We present a data set consisting of ice-penetrating-radar internal stratigraphy: 26 internal reflecting horizons that cover the greater Dome C area, East Antarctica, the most extensive IRH data set to date in the region. This data set uses radar surveys collected over the span of 10 years, starting with an airborne international collaboration in 2008 to explore the region, up to the detailed ground-based surveys in support of the European Beyond EPICA – Oldest Ice (BE-OI) project.
Yi-Ran Wang and Xiao-Ming Li
Earth Syst. Sci. Data, 13, 2723–2742, https://doi.org/10.5194/essd-13-2723-2021, https://doi.org/10.5194/essd-13-2723-2021, 2021
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Sea ice cover is the most fundamental factor that indicates the underlying great changes in the Arctic. We propose novel sea ice cover data in high resolution of a few hundred meters by spaceborne synthetic aperture radar, which is more than 10 times that of the operational sea ice cover and concentration data. The method is based on a deep learning architecture of U-Net. We have been processing data acquired by Sentinel-1 since 2014 to obtain high-quality sea ice cover data in the Arctic.
Guisella Gacitúa, Christoph Schneider, Jorge Arigony, Inti González, Ricardo Jaña, and Gino Casassa
Earth Syst. Sci. Data, 13, 231–236, https://doi.org/10.5194/essd-13-231-2021, https://doi.org/10.5194/essd-13-231-2021, 2021
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We performed the first successful ice thickness measurements using terrestrial ground-penetrating radar in the ablation area of Schiaparelli Glacier (Cordillera Darwin, Tierra del Fuego, Chile). Data are fundamental to understand glaciers dynamics, constrain ice dynamical modelling, and predict glacier evolution. Results show a valley-shaped bedrock below current sea level; thus further retreat of Schiaparelli Glacier will probably lead to an enlarged and strongly over-deepened proglacial lake.
Kate Winter, Emily A. Hill, G. Hilmar Gudmundsson, and John Woodward
Earth Syst. Sci. Data, 12, 3453–3467, https://doi.org/10.5194/essd-12-3453-2020, https://doi.org/10.5194/essd-12-3453-2020, 2020
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Satellite measurements of the English Coast in the Antarctic Peninsula reveal that glaciers are thinning and losing mass, but ice thickness data are required to assess these changes, in terms of ice flux and sea level contribution. Our ice-penetrating radar measurements reveal that low-elevation subglacial channels control fast-flowing ice streams, which release over 39 Gt of ice per year to floating ice shelves. This topography could make ice flows susceptible to future instability.
Xiangbin Cui, Hafeez Jeofry, Jamin S. Greenbaum, Jingxue Guo, Lin Li, Laura E. Lindzey, Feras A. Habbal, Wei Wei, Duncan A. Young, Neil Ross, Mathieu Morlighem, Lenneke M. Jong, Jason L. Roberts, Donald D. Blankenship, Sun Bo, and Martin J. Siegert
Earth Syst. Sci. Data, 12, 2765–2774, https://doi.org/10.5194/essd-12-2765-2020, https://doi.org/10.5194/essd-12-2765-2020, 2020
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We present a topographic digital elevation model (DEM) for Princess Elizabeth Land (PEL), East Antarctica. The DEM covers an area of approximately 900 000 km2 and was built from radio-echo sounding data collected in four campaigns since 2015. Previously, to generate the Bedmap2 topographic product, PEL’s bed was characterised from low-resolution satellite gravity data across an otherwise large (>200 km wide) data-free zone.
Cited articles
Bamber, J., Vaughan, D., and Joughin, I.: Widespread complex flow in the
interior of the Antarctic ice sheet, Science, 287, 1248–1250,
https://doi.org/10.1126/science.287.5456.1248, 2000.
Bamber, J. L., Gomez-Dans, J. L., and Griggs, J. A.: A new 1 km digital elevation model of the Antarctic derived from combined satellite radar and laser data – Part 1: Data and methods, The Cryosphere, 3, 101–111, https://doi.org/10.5194/tc-3-101-2009, 2009.
Brunt, K., Neumann, T., and Smith, B.: Assessment of ICESat-2 ice sheet
surface heights, based on comparisons over the interior of the Antarctic ice
sheet, Geophys. Res. Lett., 46, 13072–13078, https://doi.org/10.1029/2019GL084886, 2019.
Cook, A. J., Murray, T., Luckman, A., Vaughan, D. G., and Barrand, N. E.: A new 100-m Digital Elevation Model of the Antarctic Peninsula derived from ASTER Global DEM: methods and accuracy assessment, Earth Syst. Sci. Data, 4, 129–142, https://doi.org/10.5194/essd-4-129-2012, 2012.
Cornford, S. L., Martin, D. F., Payne, A. J., Ng, E. G., Le Brocq, A. M., Gladstone, R. M., Edwards, T. L., Shannon, S. R., Agosta, C., van den Broeke, M. R., Hellmer, H. H., Krinner, G., Ligtenberg, S. R. M., Timmermann, R., and Vaughan, D. G.: Century-scale simulations of the response of the West Antarctic Ice Sheet to a warming climate, The Cryosphere, 9, 1579–1600, https://doi.org/10.5194/tc-9-1579-2015, 2015.
Davis, C. H.: Temporal change in the extinction coefficient of snow on the
Greenland ice sheet from an analysis of Seasat and Geosat altimeter data,
IEEE T. Geosci. Remote, 34, 1066–1073,
https://doi.org/10.1109/36.536522, 1996.
Davis, C. H.: A robust threshold retracking algorithm for measuring
ice-sheet surface elevation change from satellite radar altimeters, IEEE
T. Geosci. Remote, 35, 974–979, https://doi.org/10.1109/36.602540,
1997.
Dehecq, A., Millan, R., Berthier, E., Gourmelen, N., Trouvé, E., and
Vionnet, V.: Elevation changes inferred from TanDEM-X data over the
Mont-Blanc area: Impact of the X-band interferometric bias, IEEE J. Sel.
Top. Appl., 9, 3870–3882, https://doi.org/10.1109/JSTARS.2016.2581482, 2016.
DiMarzio, J., Brenner, A., Schutz, R., Shuman, C. A., and Zwally, H. J.:
GLAS/ICESat 500 m laser altimetry digital elevation model of Antarctica.,
Boulder, Colorado USA, National Snow and Ice Data Center [data set], Digital media,
https://doi.org/10.5067/K2IMI0L24BRJ, 2007.
Egbert, G. D. and Erofeeva, S. Y.: Efficient inverse modeling of barotropic
ocean tides, J. Atmos. Ocean. Tech., 19, 183–204, https://doi.org/10.1175/1520-0426(2002)019<0183:EIMOBO>2.0.CO;2., 2002.
Egbert, G. D., Bennett, A. F., and Foreman, M. G.: TOPEX/POSEIDON tides
estimated using a global inverse model, J. Geophys. Res.-Oceans, 99,
24821–24852, https://doi.org/10.1029/94JC01894, 1994.
Fischer, G., Papathanassiou, K. P., and Hajnsek, I.: Modeling and
Compensation of the Penetration Bias in InSAR DEMs of Ice Sheets at
Different Frequencies, IEEE J. Sel. Top. Appl.,
13, 2698–2707, https://doi.org/10.1109/JSTARS.2020.2992530, 2020.
Flament, T. and Rémy, F.: Dynamic thinning of Antarctic glaciers from
along-track repeat radar altimetry, J. Glaciol., 58, 830–840,
https://doi.org/10.3189/2012JoG11J118, 2012.
Fricker, H. A., Hyland, G., Coleman, R., and Young, N. W.: Digital elevation
models for the Lambert Glacier–Amery Ice Shelf system, East Antarctica,
from ERS-1 satellite radar altimetry, J. Glaciol., 46, 553–560,
https://doi.org/10.3189/172756500781832639, 2000.
Helm, V., Humbert, A., and Miller, H.: Elevation and elevation change of Greenland and Antarctica derived from CryoSat-2, The Cryosphere, 8, 1539–1559, https://doi.org/10.5194/tc-8-1539-2014, 2014.
Howat, I. M., Porter, C., Smith, B. E., Noh, M.-J., and Morin, P.: The Reference Elevation Model of Antarctica, The Cryosphere, 13, 665–674, https://doi.org/10.5194/tc-13-665-2019, 2019.
Hui, F., Kang, J., Liu, Y., Cheng, X., Gong, P., Wang, F., Li, Z., Ye, Y.,
and Guo, Z.: AntarcticaLC2000: The new Antarctic land cover database for the
year 2000, Sci. China Earth Sci., 60, 686–696, https://doi.org/10.1007/s11430-016-0029-2, 2017.
Konrad, H., Gilbert, L., Cornford, S. L., Payne, A., Hogg, A., Muir, A., and
Shepherd, A.: Uneven onset and pace of ice-dynamical imbalance in the
Amundsen Sea Embayment, West Antarctica, Geophys. Res. Lett., 44, 910–918,
https://doi.org/10.1002/2016GL070733, 2017.
Korona, J., Berthier, E., Bernard, M., Rémy, F., and Thouvenot, E.:
SPIRIT. SPOT 5 stereoscopic survey of polar ice: reference images and
topographies during the fourth International Polar Year (2007–2009), ISPRS
J. Photogramm. Remote Sens., 64, 204–212, https://doi.org/10.1016/j.isprsjprs.2008.10.005, 2009.
Kurtz, N. T., Farrell, S. L., Studinger, M., Galin, N., Harbeck, J. P., Lindsay, R., Onana, V. D., Panzer, B., and Sonntag, J. G.: Sea ice thickness, freeboard, and snow depth products from Operation IceBridge airborne data, The Cryosphere, 7, 1035–1056, https://doi.org/10.5194/tc-7-1035-2013, 2013.
Kwok, R., Cunningham, G. F., Manizade, S. S., and Krabill, W. B.: Arctic sea
ice freeboard from IceBridge acquisitions in 2009: Estimates and comparisons
with ICESat, J. Geophys. Res.-Oceans, 117, C02018,
https://doi.org/10.1029/2011JC007654, 2012.
McMillan, M., Shepherd, A., Sundal, A., Briggs, K., Muir, A., Ridout, A.,
Hogg, A., and Wingham, D.: Increased ice losses from Antarctica detected by
CryoSat-2, Geophys. Res. Lett., 41, 3899–3905, https://doi.org/10.1002/2014GL060111, 2014.
Mengel, M., Nauels, A., Rogelj, J., and Schleussner, C.-F.: Committed
sea-level rise under the Paris Agreement and the legacy of delayed
mitigation action, Nat. Commun., 9, 1–10, https://doi.org/10.1038/s41467-018-02985-8, 2018.
Moholdt, G., Nuth, C., Hagen, J. O., and Kohler, J.: Recent elevation
changes of Svalbard glaciers derived from ICESat laser altimetry, Remote
Sens. Environ., 114, 2756–2767, https://doi.org/10.1016/j.rse.2010.06.008,
2010.
Neumann, T. A., Martino, A. J., Markus, T., Bae, S., Bock, M. R., Brenner,
A. C., Brunt, K. M., Cavanaugh, J., Fernandes, S. T., and Hancock, D. W.:
The Ice, Cloud, and Land Elevation Satellite–2 Mission: A global geolocated
photon product derived from the advanced topographic laser altimeter system,
Remote Sens. Environ., 233, 111325, https://doi.org/10.1016/j.rse.2019.111325, 2019.
Padman, L., Fricker, H. A., Coleman, R., Howard, S., and Erofeeva, L.: A new
tide model for the Antarctic ice shelves and seas, Ann. Glaciol., 34,
247–254, https://doi.org/10.3189/172756402781817752, 2002.
Ritz, C., Edwards, T. L., Durand, G., Payne, A. J., Peyaud, V., and
Hindmarsh, R. C.: Potential sea-level rise from Antarctic ice-sheet
instability constrained by observations, Nature, 528, 115–118,
https://doi.org/10.1038/nature16147, 2015.
Schröder, L., Richter, A., Fedorov, D. V., Eberlein, L., Brovkov, E. V., Popov, S. V., Knöfel, C., Horwath, M., Dietrich, R., Matveev, A. Y., Scheinert, M., and Lukin, V. V.: Validation of satellite altimetry by kinematic GNSS in central East Antarctica, The Cryosphere, 11, 1111–1130, https://doi.org/10.5194/tc-11-1111-2017, 2017.
Shen, X., Ke, C.-Q., and Fan, Y.: A digital elevation model of Antarctica
derived from ICESat-2 (May 2019), National Tibetan Plateau Data Center [data
set],
https://doi.org/10.11888/Geogra.tpdc.271448,
2021a.
Shen, X., Ke, C.-Q., Yu, X., Cai, Y., and Fan, Y.: Evaluation of Ice, Cloud,
And Land Elevation Satellite-2 (ICESat-2) land ice surface heights using
Airborne Topographic Mapper (ATM) data in Antarctica, Int. J.
Remote Sens., 42, 2556–2573, https://doi.org/10.1080/01431161.2020.1856962, 2021b.
Slater, T., Shepherd, A., McMillan, M., Muir, A., Gilbert, L., Hogg, A. E., Konrad, H., and Parrinello, T.: A new digital elevation model of Antarctica derived from CryoSat-2 altimetry, The Cryosphere, 12, 1551–1562, https://doi.org/10.5194/tc-12-1551-2018, 2018.
Smith, B., Fricker, H. A., Holschuh, N., Gardner, A. S., Adusumilli, S.,
Brunt, K. M., Csatho, B., Harbeck, K., Huth, A., and Neumann, T.: Land ice
height-retrieval algorithm for NASA's ICESat-2 photon-counting laser
altimeter, Remote Sens. Environ., 233, 111352, https://doi.org/10.1016/j.rse.2019.111352, 2019.
Smith, B., Fricker, H. A., Gardner, A. S., Medley, B., Nilsson, J., Paolo,
F. S., Holschuh, N., Adusumilli, S., Brunt, K., Csatho, B., Harbeck, K.,
Markus, T., Neumann, T., Siegfried, M. R., and Zwally, H. J.: Pervasive ice
sheet mass loss reflects competing ocean and atmosphere processes, Science,
368, 1239–1242, https://doi.org/10.1126/science.aaz5845, 2020.
Studinger, M.: IceBridge ATM L2 Icessn Elevation, Slope, and Roughness,
version 2. Boulder, Colorado USA, National Snow and Ice Data Center [data set], Digital
media, https://doi.org/10.5067/CPRXXK3F39RV, 2014.
Wesche, C., Eisen, O., Oerter, H., Schulte, D., and Steinhage, D.: Surface
topography and ice flow in the vicinity of the EDML deep-drilling site,
Antarctica, J. Glaciol., 53, 442–448,
https://doi.org/10.3189/002214307783258512, 2007.
Wessel, B., Huber, M., Wohlfart, C., Bertram, A., Osterkamp, N., Marschalk, U., Gruber, A., Reuß, F., Abdullahi, S., Georg, I., and Roth, A.: TanDEM-X PolarDEM 90 m of Antarctica: generation and error characterization, The Cryosphere, 15, 5241–5260, https://doi.org/10.5194/tc-15-5241-2021, 2021.
Young, D. A., Kempf, S. D., Blankenship, D. D., Holt, J. W., and Morse, D.
L.: New airborne laser altimetry over the Thwaites Glacier catchment, West
Antarctica, Geochem. Geophy. Geosy., 9, Q06006,
https://doi.org/10.1029/2007GC001935, 2008.
Zwally, H. J., Giovinetto, M. B., Beckley, M. A., and Saba, J. L.: Antarctic
and Greenland Drainage Systems, NASA's Goddard Space Flight Center:
Cryospheric Sciences Laboratory, Digital media,
https://earth.gsfc.nasa.gov/cryo/data/polar-altimetry/antarctic-and-greenland-drainage-system (last access: 27 June 2022), 2012.
Short summary
Obtaining the detailed surface topography in Antarctica is essential for fieldwork planning, surface height change and mass balance estimations. A new and reliable DEM for Antarctica with a modal resolution of 500 m is presented based on the surface height measurements from ICESat-2 by using a model fitting method. The high accuracy of elevations and the possibility for annual updates make the ICESat-2 DEM an addition to the existing Antarctic DEM groups.
Obtaining the detailed surface topography in Antarctica is essential for fieldwork planning,...
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