Articles | Volume 15, issue 7
https://doi.org/10.5194/tc-15-3083-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-15-3083-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
06 Jul 2021
Research article |
| 06 Jul 2021
| 06 Jul 2021
Assessment of ICESat-2 ice surface elevations over the Chinese Antarctic Research Expedition (CHINARE) route, East Antarctica, based on coordinated multi-sensor observations
Rongxing Li
Center for Spatial Information Science and Sustainable Development Applications, Tongji University, Shanghai 200092, China
College of Surveying and Geo-informatics, Tongji University, Shanghai 200092, China
Hongwei Li
Center for Spatial Information Science and Sustainable Development Applications, Tongji University, Shanghai 200092, China
College of Surveying and Geo-informatics, Tongji University, Shanghai 200092, China
Center for Spatial Information Science and Sustainable Development Applications, Tongji University, Shanghai 200092, China
College of Surveying and Geo-informatics, Tongji University, Shanghai 200092, China
Gang Qiao
CORRESPONDING AUTHOR
Center for Spatial Information Science and Sustainable Development Applications, Tongji University, Shanghai 200092, China
College of Surveying and Geo-informatics, Tongji University, Shanghai 200092, China
Haotian Cui
Center for Spatial Information Science and Sustainable Development Applications, Tongji University, Shanghai 200092, China
College of Surveying and Geo-informatics, Tongji University, Shanghai 200092, China
Youquan He
Center for Spatial Information Science and Sustainable Development Applications, Tongji University, Shanghai 200092, China
College of Surveying and Geo-informatics, Tongji University, Shanghai 200092, China
Gang Hai
Center for Spatial Information Science and Sustainable Development Applications, Tongji University, Shanghai 200092, China
College of Surveying and Geo-informatics, Tongji University, Shanghai 200092, China
Center for Spatial Information Science and Sustainable Development Applications, Tongji University, Shanghai 200092, China
College of Surveying and Geo-informatics, Tongji University, Shanghai 200092, China
Yuan Cheng
Center for Spatial Information Science and Sustainable Development Applications, Tongji University, Shanghai 200092, China
College of Surveying and Geo-informatics, Tongji University, Shanghai 200092, China
Bofeng Li
Center for Spatial Information Science and Sustainable Development Applications, Tongji University, Shanghai 200092, China
College of Surveying and Geo-informatics, Tongji University, Shanghai 200092, China
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Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W13, 1735–1739, https://doi.org/10.5194/isprs-archives-XLII-2-W13-1735-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W13-1735-2019, 2019
R. Li, D. Lv, H. Xiao, S. Liu, Y. Cheng, G. Hai, and X. Tong
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W13, 1759–1763, https://doi.org/10.5194/isprs-archives-XLII-2-W13-1759-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W13-1759-2019, 2019
R. Li, H. Xie, Y. Tian, W. Du, J. Chen, G. Hai, S. Zhang, and X. Tong
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W13, 1765–1769, https://doi.org/10.5194/isprs-archives-XLII-2-W13-1765-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W13-1765-2019, 2019
R. G. Xu, G. Qiao, Y. J. Wu, and Y. J. Cao
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W13, 1797–1801, https://doi.org/10.5194/isprs-archives-XLII-2-W13-1797-2019, https://doi.org/10.5194/isprs-archives-XLII-2-W13-1797-2019, 2019
L. Liu, B. Li, S. Zlatanova, and H. Liu
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4, 373–378, https://doi.org/10.5194/isprs-archives-XLII-4-373-2018, https://doi.org/10.5194/isprs-archives-XLII-4-373-2018, 2018
X. Li, R. Li, G. Qiao, Y. Cheng, W. Ye, T. Gao, Y. Huang, Y. Tian, and X. Tong
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 2625–2628, https://doi.org/10.5194/isprs-archives-XLII-3-2625-2018, https://doi.org/10.5194/isprs-archives-XLII-3-2625-2018, 2018
Y. Tian, S. Zhang, W. Du, J. Chen, H. Xie, X. Tong, and R. Li
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3, 1657–1660, https://doi.org/10.5194/isprs-archives-XLII-3-1657-2018, https://doi.org/10.5194/isprs-archives-XLII-3-1657-2018, 2018
Y. J. Cao and G. Qiao
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W7, 1503–1507, https://doi.org/10.5194/isprs-archives-XLII-2-W7-1503-2017, https://doi.org/10.5194/isprs-archives-XLII-2-W7-1503-2017, 2017
L. M. Chen, G. Qiao, and P. Lu
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W7, 1509–1512, https://doi.org/10.5194/isprs-archives-XLII-2-W7-1509-2017, https://doi.org/10.5194/isprs-archives-XLII-2-W7-1509-2017, 2017
W. Du, L. Chen, H. Xie, G. Hai, S. Zhang, and X. Tong
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W7, 1513–1516, https://doi.org/10.5194/isprs-archives-XLII-2-W7-1513-2017, https://doi.org/10.5194/isprs-archives-XLII-2-W7-1513-2017, 2017
G. Hai, H. Xie, J. Chen, L. Chen, R. Li, and X. Tong
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W7, 1517–1520, https://doi.org/10.5194/isprs-archives-XLII-2-W7-1517-2017, https://doi.org/10.5194/isprs-archives-XLII-2-W7-1517-2017, 2017
H. W. Li, G. Qiao, Y. J. Wu, Y. J. Cao, and H. Mi
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W7, 1529–1533, https://doi.org/10.5194/isprs-archives-XLII-2-W7-1529-2017, https://doi.org/10.5194/isprs-archives-XLII-2-W7-1529-2017, 2017
R. Li, X. Ma, Y. Cheng, W. Ye, S. Guo, G. Tang, Z. Wang, T. Gao, Y. Huang, X. Li, G. Qiao, Y. Tian, T. Feng, and X. Tong
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W7, 1535–1539, https://doi.org/10.5194/isprs-archives-XLII-2-W7-1535-2017, https://doi.org/10.5194/isprs-archives-XLII-2-W7-1535-2017, 2017
Y. J. Li and G. Qiao
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W7, 1541–1546, https://doi.org/10.5194/isprs-archives-XLII-2-W7-1541-2017, https://doi.org/10.5194/isprs-archives-XLII-2-W7-1541-2017, 2017
Y. J. Wu, G. Qiao, and H. W. Li
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W7, 1555–1560, https://doi.org/10.5194/isprs-archives-XLII-2-W7-1555-2017, https://doi.org/10.5194/isprs-archives-XLII-2-W7-1555-2017, 2017
M. Xia, G. Tang, Y. Tian, W. Ye, R. Li, and X. Tong
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W7, 1569–1573, https://doi.org/10.5194/isprs-archives-XLII-2-W7-1569-2017, https://doi.org/10.5194/isprs-archives-XLII-2-W7-1569-2017, 2017
H. Xiao, S. Liu, R. Li, and X. Tong
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2-W7, 1575–1577, https://doi.org/10.5194/isprs-archives-XLII-2-W7-1575-2017, https://doi.org/10.5194/isprs-archives-XLII-2-W7-1575-2017, 2017
Rongxing Li, Haifeng Xiao, Shijie Liu, and Xiaohua Tong
The Cryosphere Discuss., https://doi.org/10.5194/tc-2017-178, https://doi.org/10.5194/tc-2017-178, 2017
Revised manuscript not accepted
Short summary
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Fracturing in the RFIS was slightly increased, particularly at its front, from 2003 to 2015. They do not seem to suggest an immediate significant impact on the stability of the shelf. However, with the rapid changes and 3D measurements of Rifts 1 and 2, the most active activities occurred at the front of the FIS from 2001 to 2016. A potential upcoming major calving event in FIS is estimated to occur in 2051. The stability of the ice shelf, particularly Rifts 1 and 2, should be closely monitored.
R. Li, W. Ye, F. Kong, G. Qiao, X. Tong, X. Ma, S. Guo, and Z. Wang
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B8, 521–524, https://doi.org/10.5194/isprs-archives-XLI-B8-521-2016, https://doi.org/10.5194/isprs-archives-XLI-B8-521-2016, 2016
Huan Xie, Gang Hai, Lei Chen, Shijie Liu, Jun Liu, Xiaohua Tong, and Rongxing Li
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B8, 549–553, https://doi.org/10.5194/isprs-archives-XLI-B8-549-2016, https://doi.org/10.5194/isprs-archives-XLI-B8-549-2016, 2016
Related subject area
Discipline: Ice sheets | Subject: Antarctic
A fast and simplified subglacial hydrological model for the Antarctic Ice Sheet and outlet glaciers
Thwaites Glacier thins and retreats fastest where ice-shelf channels intersect its grounding zone
Melt sensitivity of irreversible retreat of Pine Island Glacier
A model framework for atmosphere–snow water vapor exchange and the associated isotope effects at Dome Argus, Antarctica – Part 1: The diurnal changes
The long-term sea-level commitment from Antarctica
The influence of present-day regional surface mass balance uncertainties on the future evolution of the Antarctic Ice Sheet
How well can satellite altimetry and firn models resolve Antarctic firn thickness variations?
Feedback mechanisms controlling Antarctic glacial-cycle dynamics simulated with a coupled ice sheet–solid Earth model
The effect of ice shelf rheology on shelf edge bending
Hysteresis of idealized, instability-prone outlet glaciers in response to pinning-point buttressing variation
A physics-based Antarctic melt detection technique: combining Advanced Microwave Scanning Radiometer 2, radiative-transfer modeling, and firn modeling
Brief communication: Precision measurement of the index of refraction of deep glacial ice at radio frequencies at Summit Station, Greenland
Widespread increase in discharge from west Antarctic Peninsula glaciers since 2018
Surface dynamics and history of the calving cycle of Astrolabe Glacier (Adélie Coast, Antarctica) derived from satellite imagery
Detecting Holocene retreat and readvance in the Amundsen Sea sector of Antarctica: assessing the suitability of sites near Pine Island Glacier for subglacial bedrock drilling
Weak relationship between remotely detected crevasses and inferred ice rheological parameters on Antarctic ice shelves
Speed-up, slowdown, and redirection of ice flow on neighbouring ice streams in the Pope, Smith and Kohler region of West Antarctica
A history-matching analysis of the Antarctic Ice Sheet since the last interglacial – Part 1: Ice sheet evolution
Extensive palaeo-surfaces beneath the Evans–Rutford region of the West Antarctic Ice Sheet control modern and past ice flow
Towards the systematic reconnaissance of seismic signals from glaciers and ice sheets – Part 1: Event detection for cryoseismology
Towards the systematic reconnaissance of seismic signals from glaciers and ice sheets – Part 2: Unsupervised learning for source process characterization
Geometric amplification and suppression of ice-shelf basal melt in West Antarctica
Alpine topography of the Gamburtsev Subglacial Mountains, Antarctica, mapped from ice sheet surface morphology
Impact of boundary conditions on the modeled thermal regime of the Antarctic ice sheet
The staggered retreat of grounded ice in the Ross Sea, Antarctica, since the Last Glacial Maximum (LGM)
The effect of landfast sea ice buttressing on ice dynamic speedup in the Larsen B embayment, Antarctica
ISMIP6-based Antarctic Projections to 2100: simulations with the BISICLES ice sheet model
Meteoric water and glacial melt in the southeastern Amundsen Sea: a time series from 1994 to 2020
Evaporative controls on Antarctic precipitation: an ECHAM6 model study using innovative water tracer diagnostics
Disentangling the drivers of future Antarctic ice loss with a historically calibrated ice-sheet model
Modelling GNSS-observed seasonal velocity changes of the Ross Ice Shelf, Antarctica, using the Ice-sheet and Sea-level System Model (ISSM)
Insights into the vulnerability of Antarctic glaciers from the ISMIP6 ice sheet model ensemble and associated uncertainty
Evaluation of four calving laws for Antarctic ice shelves
Oceanic gateways in Antarctica – Impact of relative sea-level change on sub-shelf melt
Englacial architecture of Lambert Glacier, East Antarctica
Mass changes of the northern Antarctic Peninsula Ice Sheet derived from repeat bi-static synthetic aperture radar acquisitions for the period 2013–2017
The evolution of future Antarctic surface melt using PISM-dEBM-simple
Characteristics and rarity of the strong 1940s westerly wind event over the Amundsen Sea, West Antarctica
Sensitivity of the MAR regional climate model snowpack to the parameterization of the assimilation of satellite-derived wet-snow masks on the Antarctic Peninsula
Stratigraphic noise and its potential drivers across the plateau of Dronning Maud Land, East Antarctica
Modes of Antarctic tidal grounding line migration revealed by Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) laser altimetry
Evaluating the impact of enhanced horizontal resolution over the Antarctic domain using a variable-resolution Earth system model
Statistically parameterizing and evaluating a positive degree-day model to estimate surface melt in Antarctica from 1979 to 2022
Widespread slowdown in thinning rates of West Antarctic ice shelves
Seasonal variability in Antarctic ice shelf velocities forced by sea surface height variations
Revisiting temperature sensitivity: how does Antarctic precipitation change with temperature?
Cosmogenic-nuclide data from Antarctic nunataks can constrain past ice sheet instabilities
Exploring ice sheet model sensitivity to ocean thermal forcing and basal sliding using the Community Ice Sheet Model (CISM)
High mid-Holocene accumulation rates over West Antarctica inferred from a pervasive ice-penetrating radar reflector
Seasonal and interannual variability of the landfast ice mass balance between 2009 and 2018 in Prydz Bay, East Antarctica
Elise Kazmierczak, Thomas Gregov, Violaine Coulon, and Frank Pattyn
The Cryosphere, 18, 5887–5911, https://doi.org/10.5194/tc-18-5887-2024, https://doi.org/10.5194/tc-18-5887-2024, 2024
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We introduce a new fast model for water flow beneath the ice sheet capable of handling various hydrological and bed conditions in a unified way. Applying this model to Thwaites Glacier, we show that accounting for this water flow in ice sheet model projections has the potential to greatly increase the contribution to future sea level rise. We also demonstrate that the sensitivity of the ice sheet in response to external changes depends on the efficiency of the drainage and the bed type.
Allison M. Chartrand, Ian M. Howat, Ian R. Joughin, and Benjamin E. Smith
The Cryosphere, 18, 4971–4992, https://doi.org/10.5194/tc-18-4971-2024, https://doi.org/10.5194/tc-18-4971-2024, 2024
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This study uses high-resolution remote-sensing data to show that shrinking of the West Antarctic Thwaites Glacier’s ice shelf (floating extension) is exacerbated by several sub-ice-shelf meltwater channels that form as the glacier transitions from full contact with the seafloor to fully floating. In mapping these channels, the position of the transition zone, and thinning rates of the Thwaites Glacier, this work elucidates important processes driving its rapid contribution to sea level rise.
Brad Reed, J. A. Mattias Green, Adrian Jenkins, and G. Hilmar Gudmundsson
The Cryosphere, 18, 4567–4587, https://doi.org/10.5194/tc-18-4567-2024, https://doi.org/10.5194/tc-18-4567-2024, 2024
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We use a numerical ice-flow model to simulate the response of a 1940s Pine Island Glacier to changes in melting beneath its ice shelf. A decadal period of warm forcing is sufficient to push the glacier into an unstable, irreversible retreat from its long-term position on a subglacial ridge to an upstream ice plain. This retreat can only be stopped when unrealistic cold forcing is applied. These results show that short warm anomalies can lead to quick and substantial increases in ice flux.
Tianming Ma, Zhuang Jiang, Minghu Ding, Pengzhen He, Yuansheng Li, Wenqian Zhang, and Lei Geng
The Cryosphere, 18, 4547–4565, https://doi.org/10.5194/tc-18-4547-2024, https://doi.org/10.5194/tc-18-4547-2024, 2024
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We constructed a box model to evaluate the isotope effects of atmosphere–snow water vapor exchange at Dome A, Antarctica. The results show clear and invisible diurnal changes in surface snow isotopes under summer and winter conditions, respectively. The model also predicts that the annual net effects of atmosphere–snow water vapor exchange would be overall enrichments in snow isotopes since the effects in summer appear to be greater than those in winter at the study site.
Ann Kristin Klose, Violaine Coulon, Frank Pattyn, and Ricarda Winkelmann
The Cryosphere, 18, 4463–4492, https://doi.org/10.5194/tc-18-4463-2024, https://doi.org/10.5194/tc-18-4463-2024, 2024
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We systematically assess the long-term sea-level response from Antarctica to warming projected over the next centuries, using two ice-sheet models. We show that this committed Antarctic sea-level contribution is substantially higher than the transient sea-level change projected for the coming decades. A low-emission scenario already poses considerable risk of multi-meter sea-level increase over the next millennia, while additional East Antarctic ice loss unfolds under the high-emission pathway.
Christian Wirths, Thomas F. Stocker, and Johannes C. R. Sutter
The Cryosphere, 18, 4435–4462, https://doi.org/10.5194/tc-18-4435-2024, https://doi.org/10.5194/tc-18-4435-2024, 2024
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We investigated the influence of several regional climate models on the Antarctic Ice Sheet when applied as forcing for the Parallel Ice Sheet Model (PISM). Our study shows that the choice of regional climate model forcing results in uncertainties of around a tenth of those in future sea level rise projections and also affects the extent of grounding line retreat in West Antarctica.
Maria T. Kappelsberger, Martin Horwath, Eric Buchta, Matthias O. Willen, Ludwig Schröder, Sanne B. M. Veldhuijsen, Peter Kuipers Munneke, and Michiel R. van den Broeke
The Cryosphere, 18, 4355–4378, https://doi.org/10.5194/tc-18-4355-2024, https://doi.org/10.5194/tc-18-4355-2024, 2024
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The interannual variations in the height of the Antarctic Ice Sheet (AIS) are mainly due to natural variations in snowfall. Precise knowledge of these variations is important for the detection of any long-term climatic trends in AIS surface elevation. We present a new product that spatially resolves these height variations over the period 1992–2017. The product combines the strengths of atmospheric modeling results and satellite altimetry measurements.
Torsten Albrecht, Meike Bagge, and Volker Klemann
The Cryosphere, 18, 4233–4255, https://doi.org/10.5194/tc-18-4233-2024, https://doi.org/10.5194/tc-18-4233-2024, 2024
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We performed coupled ice sheet–solid Earth simulations and discovered a positive (forebulge) feedback mechanism for advancing grounding lines, supporting a larger West Antarctic Ice Sheet during the Last Glacial Maximum. During deglaciation we found that the stabilizing glacial isostatic adjustment feedback dominates grounding-line retreat in the Ross Sea, with a weak Earth structure. This may have consequences for present and future ice sheet stability and potential rates of sea-level rise.
W. Roger Buck
The Cryosphere, 18, 4165–4176, https://doi.org/10.5194/tc-18-4165-2024, https://doi.org/10.5194/tc-18-4165-2024, 2024
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Standard theory predicts that the edge of an ice shelf should bend downward. Satellite observations show that the edges of many ice shelves bend upward. A new theory for ice shelf bending is developed that, for the first time, includes the kind of vertical variations in ice flow properties expected for ice shelves. Upward bending of shelf edges is predicted as long as the ice surface is very cold and the ice flow properties depend strongly on temperature.
Johannes Feldmann, Anders Levermann, and Ricarda Winkelmann
The Cryosphere, 18, 4011–4028, https://doi.org/10.5194/tc-18-4011-2024, https://doi.org/10.5194/tc-18-4011-2024, 2024
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Here we show in simplified simulations that the (ir)reversibility of the retreat of instability-prone, Antarctica-type glaciers can strongly depend on the depth of the bed depression they rest on. If it is sufficiently deep, then the destabilized glacier does not recover from its collapsed state. Our results suggest that glaciers resting on a wide and deep bed depression, such as Antarctica's Thwaites Glacier, are particularly susceptible to irreversible retreat.
Marissa E. Dattler, Brooke Medley, and C. Max Stevens
The Cryosphere, 18, 3613–3631, https://doi.org/10.5194/tc-18-3613-2024, https://doi.org/10.5194/tc-18-3613-2024, 2024
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We developed an algorithm based on combining models and satellite observations to identify the presence of surface melt on the Antarctic Ice Sheet. We find that this method works similarly to previous methods by assessing 13 sites and the Larsen C ice shelf. Unlike previous methods, this algorithm is based on physical parameters, and updates to this method could allow the meltwater present on the Antarctic Ice Sheet to be quantified instead of simply detected.
Christoph Welling and The RNO-G Collaboration
The Cryosphere, 18, 3433–3437, https://doi.org/10.5194/tc-18-3433-2024, https://doi.org/10.5194/tc-18-3433-2024, 2024
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We report on the measurement of the index of refraction in glacial ice at radio frequencies. We show that radio echoes from within the ice can be associated with specific features of the ice conductivity and use this to determine the wave velocity. This measurement is especially relevant for the Radio Neutrino Observatory Greenland (RNO-G), a neutrino detection experiment currently under construction at Summit Station, Greenland.
Benjamin J. Davison, Anna E. Hogg, Carlos Moffat, Michael P. Meredith, and Benjamin J. Wallis
The Cryosphere, 18, 3237–3251, https://doi.org/10.5194/tc-18-3237-2024, https://doi.org/10.5194/tc-18-3237-2024, 2024
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Using a new dataset of ice motion, we observed glacier acceleration on the west coast of the Antarctic Peninsula. The speed-up began around January 2021, but some glaciers sped up earlier or later. Using a combination of ship-based ocean temperature observations and climate models, we show that the speed-up coincided with a period of unusually warm air and ocean temperatures in the region.
Floriane Provost, Dimitri Zigone, Emmanuel Le Meur, Jean-Philippe Malet, and Clément Hibert
The Cryosphere, 18, 3067–3079, https://doi.org/10.5194/tc-18-3067-2024, https://doi.org/10.5194/tc-18-3067-2024, 2024
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The recent calving of Astrolabe Glacier in November 2021 presents an opportunity to better understand the processes leading to ice fracturing. Optical-satellite imagery is used to retrieve the calving cycle of the glacier ice tongue and to measure the ice velocity and strain rates in order to document fracture evolution. We observed that the presence of sea ice for consecutive years has favoured the glacier extension but failed to inhibit the growth of fractures that accelerated in June 2021.
Joanne S. Johnson, John Woodward, Ian Nesbitt, Kate Winter, Seth Campbell, Keir A. Nichols, Ryan A. Venturelli, Scott Braddock, Brent M. Goehring, Brenda Hall, Dylan H. Rood, and Greg Balco
EGUsphere, https://doi.org/10.5194/egusphere-2024-1452, https://doi.org/10.5194/egusphere-2024-1452, 2024
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Determining where and when the Antarctic ice sheet was smaller than present requires recovery and exposure dating of subglacial bedrock. Here we use ice sheet model outputs and field data (geological and glaciological observations, bedrock samples and ground-penetrating radar from subglacial ridges) to assess the suitability for drilling of sites in the Hudson Mountains, West Antarctica. We find that no sites are perfect, but two are feasible, with the most suitable being Winkie Nunatak.
Cristina Gerli, Sebastian Rosier, G. Hilmar Gudmundsson, and Sainan Sun
The Cryosphere, 18, 2677–2689, https://doi.org/10.5194/tc-18-2677-2024, https://doi.org/10.5194/tc-18-2677-2024, 2024
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Recent efforts have focused on using AI and satellite imagery to track crevasses for assessing ice shelf damage and informing ice flow models. Our study reveals a weak connection between these observed products and damage maps inferred from ice flow models. While there is some improvement in crevasse-dense regions, this association remains limited. Directly mapping ice damage from satellite observations may not significantly improve the representation of these processes within ice flow models.
Heather Louise Selley, Anna E. Hogg, Benjamin J. Davison, Pierre Dutrieux, and Thomas Slater
EGUsphere, https://doi.org/10.5194/egusphere-2024-1442, https://doi.org/10.5194/egusphere-2024-1442, 2024
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We used satellite observations to measure recent changes in ice speed and flow direction in the Pope, Smith and Kohler Region of West Antarctica (2005–2022). We found substantial speed up on seven ice streams of up to 87 %. However, Kohler West Glacier has slowed by 10%, due to the redirection of ice flow into its rapidly thinning neighbour. This process of ‘ice piracy’ hasn’t previously been directly observed on this rapid timescale and may influence future ice shelf and sheet mass changes.
Benoit S. Lecavalier and Lev Tarasov
EGUsphere, https://doi.org/10.5194/egusphere-2024-1291, https://doi.org/10.5194/egusphere-2024-1291, 2024
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We present the evolution of the Antarctic Ice Sheet (AIS) over the last 200 ka by means of a history-matching analysis where an updated observational database constrained ~10,000 model simulations. During peak glaciation at the Last Glacial Maximum (LGM), the best-fitting sub-ensemble of AIS simulations reached an excess grounded ice volume relative to present of 9.2 to 26.5 meters equivalent sea-level relative to present. The LGM AIS volume can help resolve the LGM missing ice problem.
Charlotte M. Carter, Michael J. Bentley, Stewart S. R. Jamieson, Guy J. G. Paxman, Tom A. Jordan, Julien A. Bodart, Neil Ross, and Felipe Napoleoni
The Cryosphere, 18, 2277–2296, https://doi.org/10.5194/tc-18-2277-2024, https://doi.org/10.5194/tc-18-2277-2024, 2024
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We use radio-echo sounding data to investigate the presence of flat surfaces beneath the Evans–Rutford region in West Antarctica. These surfaces may be what remains of laterally continuous surfaces, formed before the inception of the West Antarctic Ice Sheet, and we assess two hypotheses for their formation. Tectonic structures in the region may have also had a control on the growth of the ice sheet by focusing ice flow into troughs adjoining these surfaces.
Rebecca B. Latto, Ross J. Turner, Anya M. Reading, and J. Paul Winberry
The Cryosphere, 18, 2061–2079, https://doi.org/10.5194/tc-18-2061-2024, https://doi.org/10.5194/tc-18-2061-2024, 2024
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The study of icequakes allows for investigation of many glacier processes that are unseen by typical reconnaissance methods. However, detection of such seismic signals is challenging due to low signal-to-noise levels and diverse source mechanisms. Here we present a novel algorithm that is optimized to detect signals from a glacier environment. We apply the algorithm to seismic data recorded in the 2010–2011 austral summer from the Whillans Ice Stream and evaluate the resulting event catalogue.
Rebecca B. Latto, Ross J. Turner, Anya M. Reading, Sue Cook, Bernd Kulessa, and J. Paul Winberry
The Cryosphere, 18, 2081–2101, https://doi.org/10.5194/tc-18-2081-2024, https://doi.org/10.5194/tc-18-2081-2024, 2024
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Seismic catalogues are potentially rich sources of information on glacier processes. In a companion study, we constructed an event catalogue for seismic data from the Whillans Ice Stream. Here, we provide a semi-automated workflow for consistent catalogue analysis using an unsupervised cluster analysis. We discuss the defining characteristics of identified signal types found in this catalogue and possible mechanisms for the underlying glacier processes and noise sources.
Jan De Rydt and Kaitlin Naughten
The Cryosphere, 18, 1863–1888, https://doi.org/10.5194/tc-18-1863-2024, https://doi.org/10.5194/tc-18-1863-2024, 2024
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The West Antarctic Ice Sheet is losing ice at an accelerating pace. This is largely due to the presence of warm ocean water around the periphery of the Antarctic continent, which melts the ice. It is generally assumed that the strength of this process is controlled by the temperature of the ocean. However, in this study we show that an equally important role is played by the changing geometry of the ice sheet, which affects the strength of the ocean currents and thereby the melt rates.
Edmund J. Lea, Stewart S. R. Jamieson, and Michael J. Bentley
The Cryosphere, 18, 1733–1751, https://doi.org/10.5194/tc-18-1733-2024, https://doi.org/10.5194/tc-18-1733-2024, 2024
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We use the ice surface expression of the Gamburtsev Subglacial Mountains in East Antarctica to map the horizontal pattern of valleys and ridges in finer detail than possible from previous methods. In upland areas, valleys are spaced much less than 5 km apart, with consequences for the distribution of melting at the bed and hence the likelihood of ancient ice being preserved. Automated mapping techniques were tested alongside manual approaches, with a hybrid approach recommended for future work.
In-Woo Park, Emilia Kyung Jin, Mathieu Morlighem, and Kang-Kun Lee
The Cryosphere, 18, 1139–1155, https://doi.org/10.5194/tc-18-1139-2024, https://doi.org/10.5194/tc-18-1139-2024, 2024
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This study conducted 3D thermodynamic ice sheet model experiments, and modeled temperatures were compared with 15 observed borehole temperature profiles. We found that using incompressibility of ice without sliding agrees well with observed temperature profiles in slow-flow regions, while incorporating sliding in fast-flow regions captures observed temperature profiles. Also, the choice of vertical velocity scheme has a greater impact on the shape of the modeled temperature profile.
Matthew A. Danielson and Philip J. Bart
The Cryosphere, 18, 1125–1138, https://doi.org/10.5194/tc-18-1125-2024, https://doi.org/10.5194/tc-18-1125-2024, 2024
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The post-Last Glacial Maximum (LGM) retreat of the West Antarctic Ice Sheet in the Ross Sea was more significant than for any other Antarctic sector. Here we combined the available dates of retreat with new mapping of sediment deposited by the ice sheet during overall retreat. Our work shows that the post-LGM retreat through the Ross Sea was not uniform. This uneven retreat can cause instability in the present-day Antarctic ice sheet configuration and lead to future runaway retreat.
Trystan Surawy-Stepney, Anna E. Hogg, Stephen L. Cornford, Benjamin J. Wallis, Benjamin J. Davison, Heather L. Selley, Ross A. W. Slater, Elise K. Lie, Livia Jakob, Andrew Ridout, Noel Gourmelen, Bryony I. D. Freer, Sally F. Wilson, and Andrew Shepherd
The Cryosphere, 18, 977–993, https://doi.org/10.5194/tc-18-977-2024, https://doi.org/10.5194/tc-18-977-2024, 2024
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Here, we use satellite observations and an ice flow model to quantify the impact of sea ice buttressing on ice streams on the Antarctic Peninsula. The evacuation of 11-year-old landfast sea ice in the Larsen B embayment on the East Antarctic Peninsula in January 2022 was closely followed by major changes in the calving behaviour and acceleration (30 %) of the ocean-terminating glaciers. Our results show that sea ice buttressing had a negligible direct role in the observed dynamic changes.
James F. O'Neill, Tamsin L. Edwards, Daniel F. Martin, Courtney Shafer, Stephen L. Cornford, Helene L. Seroussi, Sophie Nowicki, and Mira Adhikari
EGUsphere, https://doi.org/10.5194/egusphere-2024-441, https://doi.org/10.5194/egusphere-2024-441, 2024
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We use an ice sheet model to simulate the Antarctic contribution to sea level over the 21st century, under a range of future climates, varying how sensitive the ice sheet is to different processes. We find that, under stronger warming scenarios, ocean temperatures increases and more snow falls on the ice sheet. When the ice sheet is sensitive to ocean warming, ocean melting driven loss exceeds snowfall driven gains, so that the sea level contribution is greater with more climate warming.
Andrew N. Hennig, David A. Mucciarone, Stanley S. Jacobs, Richard A. Mortlock, and Robert B. Dunbar
The Cryosphere, 18, 791–818, https://doi.org/10.5194/tc-18-791-2024, https://doi.org/10.5194/tc-18-791-2024, 2024
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A total of 937 seawater paired oxygen isotope (δ18O)–salinity samples collected during seven cruises on the SE Amundsen Sea between 1994 and 2020 reveal a deep freshwater source with δ18O − 29.4±1.0‰, consistent with the signature of local ice shelf melt. Local mean meteoric water content – comprised primarily of glacial meltwater – increased between 1994 and 2020 but exhibited greater interannual variability than increasing trend.
Qinggang Gao, Louise C. Sime, Alison J. McLaren, Thomas J. Bracegirdle, Emilie Capron, Rachael H. Rhodes, Hans Christian Steen-Larsen, Xiaoxu Shi, and Martin Werner
The Cryosphere, 18, 683–703, https://doi.org/10.5194/tc-18-683-2024, https://doi.org/10.5194/tc-18-683-2024, 2024
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Antarctic precipitation is a crucial component of the climate system. Its spatio-temporal variability impacts sea level changes and the interpretation of water isotope measurements in ice cores. To better understand its climatic drivers, we developed water tracers in an atmospheric model to identify moisture source conditions from which precipitation originates. We find that mid-latitude surface winds exert an important control on moisture availability for Antarctic precipitation.
Violaine Coulon, Ann Kristin Klose, Christoph Kittel, Tamsin Edwards, Fiona Turner, Ricarda Winkelmann, and Frank Pattyn
The Cryosphere, 18, 653–681, https://doi.org/10.5194/tc-18-653-2024, https://doi.org/10.5194/tc-18-653-2024, 2024
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We present new projections of the evolution of the Antarctic ice sheet until the end of the millennium, calibrated with observations. We show that the ocean will be the main trigger of future ice loss. As temperatures continue to rise, the atmosphere's role may shift from mitigating to amplifying Antarctic mass loss already by the end of the century. For high-emission scenarios, this may lead to substantial sea-level rise. Adopting sustainable practices would however reduce the rate of ice loss.
Francesca Baldacchino, Nicholas R. Golledge, Huw Horgan, Mathieu Morlighem, Alanna V. Alevropoulos-Borrill, Alena Malyarenko, Alexandra Gossart, Daniel P. Lowry, and Laurine van Haastrecht
EGUsphere, https://doi.org/10.5194/egusphere-2023-2793, https://doi.org/10.5194/egusphere-2023-2793, 2023
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Understanding how the Ross Ice Shelf flow is changing in a warming world is important for monitoring mass changes. The flow displays an intra-annual variation; however, it is unclear what mechanisms drive this variability. Sensitivity maps are modelled showing areas of the ice shelf where changes in basal melt most influence the ice flow. We suggest that basal melting partly drives the flow variability along the calving front of the ice shelf and will continue to do so in a warming world.
Hélène Seroussi, Vincent Verjans, Sophie Nowicki, Antony J. Payne, Heiko Goelzer, William H. Lipscomb, Ayako Abe-Ouchi, Cécile Agosta, Torsten Albrecht, Xylar Asay-Davis, Alice Barthel, Reinhard Calov, Richard Cullather, Christophe Dumas, Benjamin K. Galton-Fenzi, Rupert Gladstone, Nicholas R. Golledge, Jonathan M. Gregory, Ralf Greve, Tore Hattermann, Matthew J. Hoffman, Angelika Humbert, Philippe Huybrechts, Nicolas C. Jourdain, Thomas Kleiner, Eric Larour, Gunter R. Leguy, Daniel P. Lowry, Chistopher M. Little, Mathieu Morlighem, Frank Pattyn, Tyler Pelle, Stephen F. Price, Aurélien Quiquet, Ronja Reese, Nicole-Jeanne Schlegel, Andrew Shepherd, Erika Simon, Robin S. Smith, Fiammetta Straneo, Sainan Sun, Luke D. Trusel, Jonas Van Breedam, Peter Van Katwyk, Roderik S. W. van de Wal, Ricarda Winkelmann, Chen Zhao, Tong Zhang, and Thomas Zwinger
The Cryosphere, 17, 5197–5217, https://doi.org/10.5194/tc-17-5197-2023, https://doi.org/10.5194/tc-17-5197-2023, 2023
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Mass loss from Antarctica is a key contributor to sea level rise over the 21st century, and the associated uncertainty dominates sea level projections. We highlight here the Antarctic glaciers showing the largest changes and quantify the main sources of uncertainty in their future evolution using an ensemble of ice flow models. We show that on top of Pine Island and Thwaites glaciers, Totten and Moscow University glaciers show rapid changes and a strong sensitivity to warmer ocean conditions.
Joel A. Wilner, Mathieu Morlighem, and Gong Cheng
The Cryosphere, 17, 4889–4901, https://doi.org/10.5194/tc-17-4889-2023, https://doi.org/10.5194/tc-17-4889-2023, 2023
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We use numerical modeling to study iceberg calving off of ice shelves in Antarctica. We examine four widely used mathematical descriptions of calving (
calving laws), under the assumption that Antarctic ice shelf front positions should be in steady state under the current climate forcing. We quantify how well each of these calving laws replicates the observed front positions. Our results suggest that the eigencalving and von Mises laws are most suitable for Antarctic ice shelves.
Moritz Kreuzer, Torsten Albrecht, Lena Nicola, Ronja Reese, and Ricarda Winkelmann
EGUsphere, https://doi.org/10.5194/egusphere-2023-2737, https://doi.org/10.5194/egusphere-2023-2737, 2023
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The study investigates how changing sea levels around Antarctica can potentially affect the floating ice shelves. It utilizes numerical models for both the Antarctic Ice Sheet and the solid Earth, investigating features like troughs and sills that control the flow of ocean water onto the continental shelf. The research finds that variations in sea level alone can significantly impact the melting rates of ice shelves.
Rebecca J. Sanderson, Kate Winter, S. Louise Callard, Felipe Napoleoni, Neil Ross, Tom A. Jordan, and Robert G. Bingham
The Cryosphere, 17, 4853–4871, https://doi.org/10.5194/tc-17-4853-2023, https://doi.org/10.5194/tc-17-4853-2023, 2023
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Ice-penetrating radar allows us to explore the internal structure of glaciers and ice sheets to constrain past and present ice-flow conditions. In this paper, we examine englacial layers within the Lambert Glacier in East Antarctica using a quantitative layer tracing tool. Analysis reveals that the ice flow here has been relatively stable, but evidence for former fast flow along a tributary suggests that changes have occurred in the past and could change again in the future.
Thorsten Seehaus, Christian Sommer, Thomas Dethinne, and Philipp Malz
The Cryosphere, 17, 4629–4644, https://doi.org/10.5194/tc-17-4629-2023, https://doi.org/10.5194/tc-17-4629-2023, 2023
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Existing mass budget estimates for the northern Antarctic Peninsula (>70° S) are affected by considerable limitations. We carried out the first region-wide analysis of geodetic mass balances throughout this region (coverage of 96.4 %) for the period 2013–2017 based on repeat pass bi-static TanDEM-X acquisitions. A total mass budget of −24.1±2.8 Gt/a is revealed. Imbalanced high ice discharge, particularly at former ice shelf tributaries, is the main driver of overall ice loss.
Julius Garbe, Maria Zeitz, Uta Krebs-Kanzow, and Ricarda Winkelmann
The Cryosphere, 17, 4571–4599, https://doi.org/10.5194/tc-17-4571-2023, https://doi.org/10.5194/tc-17-4571-2023, 2023
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We adopt the novel surface module dEBM-simple in the Parallel Ice Sheet Model (PISM) to investigate the impact of atmospheric warming on Antarctic surface melt and long-term ice sheet dynamics. As an enhancement compared to traditional temperature-based melt schemes, the module accounts for changes in ice surface albedo and thus the melt–albedo feedback. Our results underscore the critical role of ice–atmosphere feedbacks in the future sea-level contribution of Antarctica on long timescales.
Gemma K. O'Connor, Paul R. Holland, Eric J. Steig, Pierre Dutrieux, and Gregory J. Hakim
The Cryosphere, 17, 4399–4420, https://doi.org/10.5194/tc-17-4399-2023, https://doi.org/10.5194/tc-17-4399-2023, 2023
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Glaciers in West Antarctica are rapidly melting, but the causes are unknown due to limited observations. A leading hypothesis is that an unusually large wind event in the 1940s initiated the ocean-driven melting. Using proxy reconstructions (e.g., using ice cores) and climate model simulations, we find that wind events similar to the 1940s event are relatively common on millennial timescales, implying that ocean variability or climate trends are also necessary to explain the start of ice loss.
Thomas Dethinne, Quentin Glaude, Ghislain Picard, Christoph Kittel, Patrick Alexander, Anne Orban, and Xavier Fettweis
The Cryosphere, 17, 4267–4288, https://doi.org/10.5194/tc-17-4267-2023, https://doi.org/10.5194/tc-17-4267-2023, 2023
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We investigate the sensitivity of the regional climate model
Modèle Atmosphérique Régional(MAR) to the assimilation of wet-snow occurrence estimated by remote sensing datasets. The assimilation is performed by nudging the MAR snowpack temperature. The data assimilation is performed over the Antarctic Peninsula for the 2019–2021 period. The results show an increase in the melt production (+66.7 %) and a decrease in surface mass balance (−4.5 %) of the model for the 2019–2020 melt season.
Nora Hirsch, Alexandra Zuhr, Thomas Münch, Maria Hörhold, Johannes Freitag, Remi Dallmayr, and Thomas Laepple
The Cryosphere, 17, 4207–4221, https://doi.org/10.5194/tc-17-4207-2023, https://doi.org/10.5194/tc-17-4207-2023, 2023
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Stable water isotopes from firn cores provide valuable information on past climates, yet their utility is hampered by stratigraphic noise, i.e. the irregular deposition and wind-driven redistribution of snow. We found stratigraphic noise on the Antarctic Plateau to be related to the local accumulation rate, snow surface roughness and slope inclination, which can guide future decisions on sampling locations and thus increase the resolution of climate reconstructions from low-accumulation areas.
Bryony I. D. Freer, Oliver J. Marsh, Anna E. Hogg, Helen Amanda Fricker, and Laurie Padman
The Cryosphere, 17, 4079–4101, https://doi.org/10.5194/tc-17-4079-2023, https://doi.org/10.5194/tc-17-4079-2023, 2023
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We develop a method using ICESat-2 data to measure how Antarctic grounding lines (GLs) migrate across the tide cycle. At an ice plain on the Ronne Ice Shelf we observe 15 km of tidal GL migration, the largest reported distance in Antarctica, dominating any signal of long-term migration. We identify four distinct migration modes, which provide both observational support for models of tidal ice flexure and GL migration and insights into ice shelf–ocean–subglacial interactions in grounding zones.
Rajashree Tri Datta, Adam Herrington, Jan T. M. Lenaerts, David P. Schneider, Luke Trusel, Ziqi Yin, and Devon Dunmire
The Cryosphere, 17, 3847–3866, https://doi.org/10.5194/tc-17-3847-2023, https://doi.org/10.5194/tc-17-3847-2023, 2023
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Precipitation over Antarctica is one of the greatest sources of uncertainty in sea level rise estimates. Earth system models (ESMs) are a valuable tool for these estimates but typically run at coarse spatial resolutions. Here, we present an evaluation of the variable-resolution CESM2 (VR-CESM2) for the first time with a grid designed for enhanced spatial resolution over Antarctica to achieve the high resolution of regional climate models while preserving the two-way interactions of ESMs.
Yaowen Zheng, Nicholas R. Golledge, Alexandra Gossart, Ghislain Picard, and Marion Leduc-Leballeur
The Cryosphere, 17, 3667–3694, https://doi.org/10.5194/tc-17-3667-2023, https://doi.org/10.5194/tc-17-3667-2023, 2023
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Positive degree-day (PDD) schemes are widely used in many Antarctic numerical ice sheet models. However, the PDD approach has not been systematically explored for its application in Antarctica. We have constructed a novel grid-cell-level spatially distributed PDD (dist-PDD) model and assessed its accuracy. We suggest that an appropriately parameterized dist-PDD model can be a valuable tool for exploring Antarctic surface melt beyond the satellite era.
Fernando S. Paolo, Alex S. Gardner, Chad A. Greene, Johan Nilsson, Michael P. Schodlok, Nicole-Jeanne Schlegel, and Helen A. Fricker
The Cryosphere, 17, 3409–3433, https://doi.org/10.5194/tc-17-3409-2023, https://doi.org/10.5194/tc-17-3409-2023, 2023
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We report on a slowdown in the rate of thinning and melting of West Antarctic ice shelves. We present a comprehensive assessment of the Antarctic ice shelves, where we analyze at a continental scale the changes in thickness, flow, and basal melt over the past 26 years. We also present a novel method to estimate ice shelf change from satellite altimetry and a time-dependent data set of ice shelf thickness and basal melt rates at an unprecedented resolution.
Cyrille Mosbeux, Laurie Padman, Emilie Klein, Peter D. Bromirski, and Helen A. Fricker
The Cryosphere, 17, 2585–2606, https://doi.org/10.5194/tc-17-2585-2023, https://doi.org/10.5194/tc-17-2585-2023, 2023
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Antarctica's ice shelves (the floating extension of the ice sheet) help regulate ice flow. As ice shelves thin or lose contact with the bedrock, the upstream ice tends to accelerate, resulting in increased mass loss. Here, we use an ice sheet model to simulate the effect of seasonal sea surface height variations and see if we can reproduce observed seasonal variability of ice velocity on the ice shelf. When correctly parameterised, the model fits the observations well.
Lena Nicola, Dirk Notz, and Ricarda Winkelmann
The Cryosphere, 17, 2563–2583, https://doi.org/10.5194/tc-17-2563-2023, https://doi.org/10.5194/tc-17-2563-2023, 2023
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For future sea-level projections, approximating Antarctic precipitation increases through temperature-scaling approaches will remain important, as coupled ice-sheet simulations with regional climate models remain computationally expensive, especially on multi-centennial timescales. We here revisit the relationship between Antarctic temperature and precipitation using different scaling approaches, identifying and explaining regional differences.
Anna Ruth W. Halberstadt, Greg Balco, Hannah Buchband, and Perry Spector
The Cryosphere, 17, 1623–1643, https://doi.org/10.5194/tc-17-1623-2023, https://doi.org/10.5194/tc-17-1623-2023, 2023
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This paper explores the use of multimillion-year exposure ages from Antarctic bedrock outcrops to benchmark ice sheet model predictions and thereby infer ice sheet sensitivity to warm climates. We describe a new approach for model–data comparison, highlight an example where observational data are used to distinguish end-member models, and provide guidance for targeted sampling around Antarctica that can improve understanding of ice sheet response to climate warming in the past and future.
Mira Berdahl, Gunter Leguy, William H. Lipscomb, Nathan M. Urban, and Matthew J. Hoffman
The Cryosphere, 17, 1513–1543, https://doi.org/10.5194/tc-17-1513-2023, https://doi.org/10.5194/tc-17-1513-2023, 2023
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Contributions to future sea level from the Antarctic Ice Sheet remain poorly constrained. One reason is that ice sheet model initialization methods can have significant impacts on how the ice sheet responds to future forcings. We investigate the impacts of two key parameters used during model initialization. We find that these parameter choices alone can impact multi-century sea level rise by up to 2 m, emphasizing the need to carefully consider these choices for sea level rise predictions.
Julien A. Bodart, Robert G. Bingham, Duncan A. Young, Joseph A. MacGregor, David W. Ashmore, Enrica Quartini, Andrew S. Hein, David G. Vaughan, and Donald D. Blankenship
The Cryosphere, 17, 1497–1512, https://doi.org/10.5194/tc-17-1497-2023, https://doi.org/10.5194/tc-17-1497-2023, 2023
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Estimating how West Antarctica will change in response to future climatic change depends on our understanding of past ice processes. Here, we use a reflector widely visible on airborne radar data across West Antarctica to estimate accumulation rates over the past 4700 years. By comparing our estimates with current atmospheric data, we find that accumulation rates were 18 % greater than modern rates. This has implications for our understanding of past ice processes in the region.
Na Li, Ruibo Lei, Petra Heil, Bin Cheng, Minghu Ding, Zhongxiang Tian, and Bingrui Li
The Cryosphere, 17, 917–937, https://doi.org/10.5194/tc-17-917-2023, https://doi.org/10.5194/tc-17-917-2023, 2023
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The observed annual maximum landfast ice (LFI) thickness off Zhongshan (Davis) was 1.59±0.17 m (1.64±0.08 m). Larger interannual and local spatial variabilities for the seasonality of LFI were identified at Zhongshan, with the dominant influencing factors of air temperature anomaly, snow atop, local topography and wind regime, and oceanic heat flux. The variability of LFI properties across the study domain prevailed at interannual timescales, over any trend during the recent decades.
Cited articles
Bindschadler, R., Vornberger, P., Fleming, A., Fox, A., Mullins, J., Binnie,
D., Paulsen, S. J., Granneman, B., and Gorodetzky, D.: The Landsat image
mosaic of Antarctica, Remote Sens. Environ., 112, 4214–4226,
https://doi.org/10.1016/j.rse.2008.07.006, 2008.
Born, M., Clemmow, P., Gabor, D., Stokes, A., Taylor, A., Wayman, A.,
Wilcock, W., and Wolf, E. (Eds.): Principles of Optics, 7th (expanded)
edition, Pergamon Press, Oxford, UK, 1999.
Borsa, A. A., Fricker, H. A., and Brunt, K. M.: A Terrestrial Validation of
ICESat Elevation Measurements and Implications for Global Reanalyses, IEEE
T. Geosci. Remote, 57, 6946–6959,
https://doi.org/10.1109/TGRS.2019.2909739, 2019.
Brunt, K. M., Hawley, R. L., Lutz, E. R., Studinger, M., Sonntag, J. G., Hofton, M. A., Andrews, L. C., and Neumann, T. A.: Assessment of NASA airborne laser altimetry data using ground-based GPS data near Summit Station, Greenland, The Cryosphere, 11, 681–692, https://doi.org/10.5194/tc-11-681-2017, 2017.
Brunt, K. M., Neumann, T. A., and Larsen, C. F.: Assessment of altimetry using ground-based GPS data from the 88S Traverse, Antarctica, in support of ICESat-2, The Cryosphere, 13, 579–590, https://doi.org/10.5194/tc-13-579-2019, 2019a.
Brunt, K. M., Neumann, T. A., and Smith, B. E.: 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://https://doi.org/10.1029/2019GL084886, 2019b.
Brunt, K. M., Smith, B. E., Sutterley, T. C., Kurtz, N. T., and Neumann, T.
A.: Comparisons of Satellite and Airborne Altimetry With Ground-Based Data
From the Interior of the Antarctic Ice Sheet, Geophys. Res. Lett., 48, e2020GL090572, https://doi.org/10.1029/2020GL090572, 2021.
Chang, R. F., Currie, D., Alley, C., and Pittman, M.: The far field
diffraction pattern for corner reflectors with complex reflection
coefficients, J. Opt. Soc. Am., 61, 431–438,
https://doi.org/10.1364/JOSA.61.000431, 1971.
Hartzell, P., Dang, Z., Pan, Z., and Glennie, C.: Radiometric evaluation of
an airborne single photon Lidar sensor, IEEE Geosci. Remote S., 15,
1466–1470, https://doi.org/10.1109/LGRS.2018.2841811, 2018.
ICESat-2 Technical Specs: https://icesat-2.gsfc.nasa.gov/science/specs, last access: 27 September 2020.
James, M. R. and Robson, S.: Straightforward reconstruction of 3D surfaces
and topography with a camera: accuracy and geoscience application, J.
Geophys. Res., 117, F03017, https://doi.org/10.1029/2011JF002289, 2012.
Kohler, J., Neumann, T. A., Robbins, J. W., Tronstad, S., and Melland, G.:
ICESat elevations in Antarctica along the 2007-09 Norway-USA Traverse:
validation with ground-based GPS, IEEE T. Geosci. Remote, 51, 1578–1587,
https://doi.org/10.1109/TGRS.2012.2207963, 2013.
Li, B., Zang, N., Ge, H., and Shen, Y.: Single-frequency PPP models:
analytical and numerical comparison, J. Geod., 93, 2499–2514,
https://doi.org/10.1007/s00190-019-01311-4, 2019.
Li, R., Li, H., Hao, T., Qiao, G., Cui, H., He, Y., Hai, G., Xie, H., Cheng, Y., and Li, B.: The calibration and validation data used in ICESat-2 Antarctic surface elevation assessment, available at: https://datadryad.org/stash/share/5 mU52z7OSWAG07tTsGCWXt0Rm0MmT12qwdPORBIUpsnw, last access: 12 April 2021.
Luthcke, S. B., Thomas, T. C., Pennington, T. A., Rebold, T. W., Nicholas,
J. B., Rowlands, D. D., Gardner, A. S., and Bae, S.: ICESat-2 Pointing
Calibration and Geolocation Performance, Earth Space Sci.,
https://doi.org/10.1029/2020EA001494, 2021.
Magruder, L. A. and Brunt, K. M.: Performance analysis of airborne
photon-counting lidar data in preparation for the ICESat-2 mission, IEEE T.
Geosci. Remote, 56, 2911–2918, https://doi.org/10.1109/TGRS.2017.2786659,
2018.
Magruder, L. A., Brunt, K. M., and Alonzo, M.: Early ICESat-2 on-orbit
geolocation validation using ground-based corner cube retro-reflectors,
Remote Sensing, 12, 3653, https://doi.org/10.3390/rs12213653, 2020.
Markus, T., Neumann, T., Martino, A., Abdalati, W., Brunt, K., Csatho, B.,
Farrell, S., Fricker, H., Gardner, A., Harding, D., Jasinski, M., Kwok, R.,
Magruder, L., Lubin, D., Luthcke, S., Morison, J., Nelson, R.,
Neuenschwander, A., Palm, S., Popescu, S., Shum, B. E., Schutz, R., Smith,
B., Yang, Y., and Zwally, J.: The Ice, Cloud, and Land Elevation Satellite-2
(ICESat-2): Science requirements, concept, and implementation, Remote Sens.
Environ., 190, 260–273, https://doi.org/10.1016/j.rse.2016.12.029, 2017.
McGlone, J. C.: Manual of Photogrammetry, Sixth Edition, ASPRS Publications,
Maryland, MD, USA, 2013
National Research Council: Earth science and applications from space:
national imperatives for the next decade and beyond, the national academies
press, Washington, DC, https://doi.org/10.17226/11820, 2007.
Neumann, T., Brenner, A., Hancock, D., Harbeck, K., Luthcke, S., Robbins,
J., Saba, J., and Gibbons, A.: Ice, Cloud, and Land Elevation Satellite-2
project algorithm theoretical basis document for global geolocated photons
(ATL03), https://icesat-2.gsfc.nasa.gov/science/data-products (last access: 27 September 2020), 2018.
Neumann, T. A., Martino, A. J., Markus, T., Bae, S., Bock, M. R., Brenner,
A. C., Brunt, K. M., Cavanaugh, J., Fernandes, S. T., Hancock, D. W.,
Harbeck, K., Lee, J., Kurtz, N. T., Luers, P. J., Luthcke, S. B., Magruder,
L., Pennington, T. A., Ramos-Izquierdo, L., Rebold, T., Skoog, J., and
Thomas, T. C.: 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.
Neumann, T., Brenner, A., Hancock, D., Robbins, J., Saba, J., Harbeck, K.,
Gibbons, A., Lee, J., Luthcke, S., and Rebold, T.: ATLAS/ICESat-2 L2A global
geolocated photon data, Version 3, NASA National Snow and Ice Data Center,
Distributed Active Archive Center, Boulder, Colorado USA,
https://doi.org/10.5067/ATLAS/ATL03.003, 2020.
NSIDC: https://nsidc.org/data/icesat-2, last access: 8 January 2021.
Petit, G. and Luzum, B.: IERS conventions (2010), IERS Technical Note 36,
Verlag des Bundesamts für Kartographie und Geodäsie, Frankfurt am
Main, 2010.
Richter, A., Horwath M., and Dietrich R.: Comment on Zwally and others
(2015) – Mass gains of the Antarctic ice sheet exceed losses, J. Glaciol.,
62, 604–606, https://doi.org/10.1017/jog.2016.60, 2016.
Scambos, T. and Shuman C.: Comment on “Mass gains of the Antarctic ice
sheet exceed losses” by H. J. Zwally and others, J. Glaciol., 62, 599–603,
https://doi.org/10.1017/jog.2016.59, 2016.
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.
Schutz, B. E., Bae, S., Smith, N., and Sirota, M.: Precision orbit and
attitude determination for ICESat, Adv. Astronaut. Sci, 115, 416–427, 2008.
Smith, B., Fricker, H. A., Holschuh, N., Gardner, A. S., Adusumilli, S.,
Brunt, K. M., Csatho, B., Huth, A., Neumann, T., Nilsson, J., and Siegfried,
M. R.: Land ice height-retrieval algorithms 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., Siegfried, M. R., Adusumilli, S., Csathó, B. M., Holschuh, N., Nilsson, J., Paolo, F. S., and the ICESat-2 Science Team: ATLAS/ICESat-2 L3A Land Ice Height, Version 3, https://doi.org/10.5067/ATLAS/ATL06.003, 2020.
Sun, X., Smith, D. E., Hoffman, E. D., Wake, S. W., Cremons, D. R.,
Mazarico, E., Lauenstein, J., Zuber, M. T., and Aaron, E. C.: Small and
lightweight laser retro-reflector arrays for lunar landers, Appl. Opt.,
58, 9259–9266, https://doi.org/10.1364/AO.58.009259, 2019.
Takasu, T. and Yasuda, A.: Development of the low-cost RTK-GPS receiver with
an open source program package RTKLIB, International Symposium on GPS/GNSS,
International Convention Center Jeju, Korea, 4–6 November 2009.
Takasu, T.: RTKLIB ver. 2.4.2 Manual, available at:
http://www.rtklib.com/prog/manual_2.4.2.pdf (last access: 21
October 2020), 2013.
Turner, D., Lucieer, A., and Wallace, L.: Direct georeferencing of
ultrahigh-resolution UAV imagery, IEEE T. Geosci. Remote, 52, 27380-2745,
https://doi.org/10.1109/TGRS.2013.2265295, 2014.
Zwally, H. J., Schutz, B., Abdalati, W., Abshire, J., Bentley, C., Brenner,
A., Bufton, J., Dezio, J., Hancock, D., Harding, D., Herring, T., Minster,
B., Quinn, K., Palm, S., Spinhirne, J., and Thomas, R.: ICESat's laser
measurements of polar ice, atmosphere, ocean, and land, J. Geodyn., 34,
405-0445, https://doi.org/10.1016/S0264-3707(02)00042-X, 2002.
Zwally, H. J., Li, J., Robbins, J. W., Saba, J. L., Yi, D., and Brenner, A.
C.: Mass gains of the Antarctic ice sheet exceed losses, J. Glaciol.,
61, 1019–1036, https://doi.org/10.3189/2015JoG15J071, 2015.
Short summary
We present the results of an assessment of ICESat-2 surface elevations along the 520 km CHINARE route in East Antarctica. The assessment was performed based on coordinated multi-sensor observations from a global navigation satellite system, corner cube retroreflectors, retroreflective target sheets, and UAVs. The validation results demonstrate that ICESat-2 elevations are accurate to 1.5–2.5 cm and can potentially overcome the uncertainties in the estimation of mass balance in East Antarctica.
We present the results of an assessment of ICESat-2 surface elevations along the 520 km CHINARE...
