Articles | Volume 19, issue 1
https://doi.org/10.5194/tc-19-37-2025
© Author(s) 2025. 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-19-37-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Machine learning of Antarctic firn density by combining radiometer and scatterometer remote-sensing data
Weiran Li
CORRESPONDING AUTHOR
Department of Geoscience and Remote Sensing, Delft University of Technology, Delft, the Netherlands
Sanne B. M. Veldhuijsen
Institute for Marine and Atmospheric Research Utrecht, Utrecht University, Utrecht, the Netherlands
Stef Lhermitte
Department of Earth & Environmental Sciences, KU Leuven, Leuven, Belgium
Department of Geoscience and Remote Sensing, Delft University of Technology, Delft, the Netherlands
Related authors
Weiran Li, Stef Lhermitte, Bert Wouters, Cornelis Slobbe, Max Brils, and Xavier Fettweis
EGUsphere, https://doi.org/10.5194/egusphere-2024-3251, https://doi.org/10.5194/egusphere-2024-3251, 2024
This preprint is open for discussion and under review for The Cryosphere (TC).
Short summary
Short summary
Due to the melt events in recent decades, the snow condition over Greenland has been changed. To observe this, we use a parameter (leading edge width; LeW) derived from satellite altimetry, and analyse its spatial and temporal variations. By comparing the LeW variations with modelled firn parameters, we concluded that the 2012 melt event has a long-lasting impact on the volume scattering of Greenland firn. This impact cannot fully recover due to the recent and more frequent melt events.
Weiran Li, Cornelis Slobbe, and Stef Lhermitte
The Cryosphere, 16, 2225–2243, https://doi.org/10.5194/tc-16-2225-2022, https://doi.org/10.5194/tc-16-2225-2022, 2022
Short summary
Short summary
This study proposes a new method for correcting the slope-induced errors in satellite radar altimetry. The slope-induced errors can significantly affect the height estimations of ice sheets if left uncorrected. This study applies the method to radar altimetry data (CryoSat-2) and compares the performance with two existing methods. The performance is assessed by comparison with independent height measurements from ICESat-2. The assessment shows that the method performs promisingly.
Weiran Li, Stef Lhermitte, and Paco López-Dekker
The Cryosphere, 15, 5309–5322, https://doi.org/10.5194/tc-15-5309-2021, https://doi.org/10.5194/tc-15-5309-2021, 2021
Short summary
Short summary
Surface meltwater lakes have been observed on several Antarctic ice shelves in field studies and optical images. Meltwater lakes can drain and refreeze, increasing the fragility of the ice shelves. The combination of synthetic aperture radar (SAR) backscatter and interferometric information (InSAR) can provide the cryosphere community with the possibility to continuously assess the dynamics of the meltwater lakes, potentially helping to facilitate the study of ice shelves in a changing climate.
Weiran Li, Stef Lhermitte, Bert Wouters, Cornelis Slobbe, Max Brils, and Xavier Fettweis
EGUsphere, https://doi.org/10.5194/egusphere-2024-3251, https://doi.org/10.5194/egusphere-2024-3251, 2024
This preprint is open for discussion and under review for The Cryosphere (TC).
Short summary
Short summary
Due to the melt events in recent decades, the snow condition over Greenland has been changed. To observe this, we use a parameter (leading edge width; LeW) derived from satellite altimetry, and analyse its spatial and temporal variations. By comparing the LeW variations with modelled firn parameters, we concluded that the 2012 melt event has a long-lasting impact on the volume scattering of Greenland firn. This impact cannot fully recover due to the recent and more frequent melt events.
Julius Sommer, Maaike Izeboud, Sophie de Roda Husman, Bert Wouters, and Stef Lhermitte
EGUsphere, https://doi.org/10.5194/egusphere-2024-3105, https://doi.org/10.5194/egusphere-2024-3105, 2024
This preprint is open for discussion and under review for The Cryosphere (TC).
Short summary
Short summary
Ice shelves, the floating extensions of Antarctica’s ice sheet, play a crucial role in preventing mass ice loss, and understanding their stability is crucial. If surface meltwater lakes drain rapidly through fractures, the ice shelf can destabilize. We analyzed satellite images of three years from the Shackleton Ice Shelf and found that lake drainages occurred in areas where damage is present and developing, and coincided with rising tides, offering insights into the drivers of this process.
Sanne B. M. Veldhuijsen, Willem Jan van de Berg, Peter Kuipers Munneke, Nicolaj Hansen, Fredrik Boberg, Christoph Kittel, Charles Amory, and Michiel R. van den Broeke
EGUsphere, https://doi.org/10.5194/egusphere-2024-2855, https://doi.org/10.5194/egusphere-2024-2855, 2024
Short summary
Short summary
Perennial firn aquifers (PFAs), year-round bodies of liquid water within firn, can potentially impact ice-shelf and ice-sheet stability. We developed a fast XGBoost firn emulator to predict 21st-century distribution of PFAs in Antarctica for 12 climatic forcings datasets. Our findings suggest that under low emission scenarios, PFAs remain confined to the Antarctic Peninsula. However, under a high-emission scenario, PFAs are projected to expand to a region in West Antarctica and East 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
Short summary
Short summary
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.
Filippo Emilio Scarsi, Alessandro Battaglia, Maximilian Maahn, and Stef Lhermitte
EGUsphere, https://doi.org/10.5194/egusphere-2024-1917, https://doi.org/10.5194/egusphere-2024-1917, 2024
Short summary
Short summary
Snowfall measurements at high latitudes are crucial for estimating ice sheet mass balance. Spaceborne radar and radiometer missions help estimate snowfall but face uncertainties. This work evaluates uncertainties in snowfall estimates from a fixed near-nadir radar (CloudSat-like) and a conically scanning radar (WIVERN-like), determining that WIVERN will provide much better estimates than CloudSat, and at much smaller spatial and temporal scales.
Thore Kausch, Stef Lhermitte, Marie G. P. Cavitte, Eric Keenan, and Shashwat Shukla
EGUsphere, https://doi.org/10.5194/egusphere-2024-2077, https://doi.org/10.5194/egusphere-2024-2077, 2024
Short summary
Short summary
Determining the net balance of snow accumulation on the surface of Antarctica is challenging. Sentinel-1 satellite sensors, which can see through snow, offer a promising method. However, linking their signals to snow amounts is complex due to snow's internal structure and limited on-the-ground data. This study found a connection between satellite signals and snow levels at three locations in Dronning Maud Land. Using models and field data, the method shows potential for wider use in Antarctica.
Sanne B. M. Veldhuijsen, Willem Jan van de Berg, Peter Kuipers Munneke, and Michiel R. van den Broeke
The Cryosphere, 18, 1983–1999, https://doi.org/10.5194/tc-18-1983-2024, https://doi.org/10.5194/tc-18-1983-2024, 2024
Short summary
Short summary
We use the IMAU firn densification model to simulate the 21st-century evolution of Antarctic firn air content. Ice shelves on the Antarctic Peninsula and the Roi Baudouin Ice Shelf in Dronning Maud Land are particularly vulnerable to total firn air content (FAC) depletion. Our results also underline the potentially large vulnerability of low-accumulation ice shelves to firn air depletion through ice slab formation.
Lena G. Buth, Valeria Di Biase, Peter Kuipers Munneke, Stef Lhermitte, Sanne B. M. Veldhuijsen, Sophie de Roda Husman, Michiel R. van den Broeke, and Bert Wouters
EGUsphere, https://doi.org/10.5194/egusphere-2023-2000, https://doi.org/10.5194/egusphere-2023-2000, 2023
Preprint archived
Short summary
Short summary
Liquid meltwater which is stored in air bubbles in the compacted snow near the surface of Antarctica can affect ice shelf stability. In order to detect the presence of such firn aquifers over large scales, satellite remote sensing is needed. In this paper, we present our new detection method using radar satellite data as well as the results for the whole Antarctic Peninsula. Firn aquifers are found in the north and northwest of the peninsula, in agreement with locations predicted by models.
Ann-Sofie Priergaard Zinck, Bert Wouters, Erwin Lambert, and Stef Lhermitte
The Cryosphere, 17, 3785–3801, https://doi.org/10.5194/tc-17-3785-2023, https://doi.org/10.5194/tc-17-3785-2023, 2023
Short summary
Short summary
The ice shelves in Antarctica are melting from below, which puts their stability at risk. Therefore, it is important to observe how much and where they are melting. In this study we use high-resolution satellite imagery to derive 50 m resolution basal melt rates of the Dotson Ice Shelf. With the high resolution of our product we are able to uncover small-scale features which may in the future help us to understand the state and fate of the Antarctic ice shelves and their (in)stability.
Diana Francis, Ricardo Fonseca, Kyle S. Mattingly, Stef Lhermitte, and Catherine Walker
The Cryosphere, 17, 3041–3062, https://doi.org/10.5194/tc-17-3041-2023, https://doi.org/10.5194/tc-17-3041-2023, 2023
Short summary
Short summary
Role of Foehn Winds in ice and snow conditions at the Pine Island Glacier, West Antarctica.
Sanne B. M. Veldhuijsen, Willem Jan van de Berg, Max Brils, Peter Kuipers Munneke, and Michiel R. van den Broeke
The Cryosphere, 17, 1675–1696, https://doi.org/10.5194/tc-17-1675-2023, https://doi.org/10.5194/tc-17-1675-2023, 2023
Short summary
Short summary
Firn is the transition of snow to glacier ice and covers 99 % of the Antarctic ice sheet. Knowledge about the firn layer and its variability is important, as it impacts satellite-based estimates of ice sheet mass change. Also, firn contains pores in which nearly all of the surface melt is retained. Here, we improve a semi-empirical firn model and simulate the firn characteristics for the period 1979–2020. We evaluate the performance with field and satellite measures and test its sensitivity.
Lena G. Buth, Bert Wouters, Sanne B. M. Veldhuijsen, Stef Lhermitte, Peter Kuipers Munneke, and Michiel R. van den Broeke
The Cryosphere Discuss., https://doi.org/10.5194/tc-2022-127, https://doi.org/10.5194/tc-2022-127, 2022
Manuscript not accepted for further review
Short summary
Short summary
Liquid meltwater which is stored in air bubbles in the compacted snow near the surface of Antarctica can affect ice shelf stability. In order to detect the presence of such firn aquifers over large scales, satellite remote sensing is needed. In this paper, we present our new detection method using radar satellite data as well as the results for the whole Antarctic Peninsula. Firn aquifers are found in the north and northwest of the peninsula, in agreement with locations predicted by models.
Weiran Li, Cornelis Slobbe, and Stef Lhermitte
The Cryosphere, 16, 2225–2243, https://doi.org/10.5194/tc-16-2225-2022, https://doi.org/10.5194/tc-16-2225-2022, 2022
Short summary
Short summary
This study proposes a new method for correcting the slope-induced errors in satellite radar altimetry. The slope-induced errors can significantly affect the height estimations of ice sheets if left uncorrected. This study applies the method to radar altimetry data (CryoSat-2) and compares the performance with two existing methods. The performance is assessed by comparison with independent height measurements from ICESat-2. The assessment shows that the method performs promisingly.
Zhongyang Hu, Peter Kuipers Munneke, Stef Lhermitte, Maaike Izeboud, and Michiel van den Broeke
The Cryosphere, 15, 5639–5658, https://doi.org/10.5194/tc-15-5639-2021, https://doi.org/10.5194/tc-15-5639-2021, 2021
Short summary
Short summary
Antarctica is shrinking, and part of the mass loss is caused by higher temperatures leading to more snowmelt. We use computer models to estimate the amount of melt, but this can be inaccurate – specifically in the areas with the most melt. This is because the model cannot account for small, darker areas like rocks or darker ice. Thus, we trained a computer using artificial intelligence and satellite images that showed these darker areas. The model computed an improved estimate of melt.
Weiran Li, Stef Lhermitte, and Paco López-Dekker
The Cryosphere, 15, 5309–5322, https://doi.org/10.5194/tc-15-5309-2021, https://doi.org/10.5194/tc-15-5309-2021, 2021
Short summary
Short summary
Surface meltwater lakes have been observed on several Antarctic ice shelves in field studies and optical images. Meltwater lakes can drain and refreeze, increasing the fragility of the ice shelves. The combination of synthetic aperture radar (SAR) backscatter and interferometric information (InSAR) can provide the cryosphere community with the possibility to continuously assess the dynamics of the meltwater lakes, potentially helping to facilitate the study of ice shelves in a changing climate.
Annelies Voordendag, Marion Réveillet, Shelley MacDonell, and Stef Lhermitte
The Cryosphere, 15, 4241–4259, https://doi.org/10.5194/tc-15-4241-2021, https://doi.org/10.5194/tc-15-4241-2021, 2021
Short summary
Short summary
The sensitivity of two snow models (SNOWPACK and SnowModel) to various parameterizations and atmospheric forcing biases is assessed in the semi-arid Andes of Chile in winter 2017. Models show that sublimation is a main driver of ablation and that its relative contribution to total ablation is highly sensitive to the selected albedo parameterization and snow roughness length. The forcing and parameterizations are more important than the model choice, despite differences in physical complexity.
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.
Christiaan T. van Dalum, Willem Jan van de Berg, Stef Lhermitte, and Michiel R. van den Broeke
The Cryosphere, 14, 3645–3662, https://doi.org/10.5194/tc-14-3645-2020, https://doi.org/10.5194/tc-14-3645-2020, 2020
Short summary
Short summary
The reflectivity of sunlight, which is also known as albedo, is often inadequately modeled in regional climate models. Therefore, we have implemented a new snow and ice albedo scheme in the regional climate model RACMO2. In this study, we evaluate a new RACMO2 version for the Greenland ice sheet by using observations and the previous model version. RACMO2 output compares well with observations, and by including new processes we improve the ability of RACMO2 to make future climate projections.
Thore Kausch, Stef Lhermitte, Jan T. M. Lenaerts, Nander Wever, Mana Inoue, Frank Pattyn, Sainan Sun, Sarah Wauthy, Jean-Louis Tison, and Willem Jan van de Berg
The Cryosphere, 14, 3367–3380, https://doi.org/10.5194/tc-14-3367-2020, https://doi.org/10.5194/tc-14-3367-2020, 2020
Short summary
Short summary
Ice rises are elevated parts of the otherwise flat ice shelf. Here we study the impact of an Antarctic ice rise on the surrounding snow accumulation by combining field data and modeling. Our results show a clear difference in average yearly snow accumulation between the windward side, the leeward side and the peak of the ice rise due to differences in snowfall and wind erosion. This is relevant for the interpretation of ice core records, which are often drilled on the peak of an ice rise.
Marion Réveillet, Shelley MacDonell, Simon Gascoin, Christophe Kinnard, Stef Lhermitte, and Nicole Schaffer
The Cryosphere, 14, 147–163, https://doi.org/10.5194/tc-14-147-2020, https://doi.org/10.5194/tc-14-147-2020, 2020
Alexandra Gossart, Stephen P. Palm, Niels Souverijns, Jan T. M. Lenaerts, Irina V. Gorodetskaya, Stef Lhermitte, and Nicole P. M. van Lipzig
The Cryosphere Discuss., https://doi.org/10.5194/tc-2019-25, https://doi.org/10.5194/tc-2019-25, 2019
Manuscript not accepted for further review
Short summary
Short summary
Blowing snow measurements are scarce, both in time and space over the Antarctic ice sheet. We compare here CALIPSO satellite blowing snow measurements, to ground-base remote sensing ceilometer retrievals at two coastal stations in East Antarctica. Results indicate that 95 % of the blowing snow occurs under cloudy conditions, and are missed by the satellite. In addition, difficulties arise if comparing point locations to satellite overpasses.
Niels Souverijns, Alexandra Gossart, Stef Lhermitte, Irina V. Gorodetskaya, Jacopo Grazioli, Alexis Berne, Claudio Duran-Alarcon, Brice Boudevillain, Christophe Genthon, Claudio Scarchilli, and Nicole P. M. van Lipzig
The Cryosphere, 12, 3775–3789, https://doi.org/10.5194/tc-12-3775-2018, https://doi.org/10.5194/tc-12-3775-2018, 2018
Short summary
Short summary
Snowfall observations over Antarctica are scarce and currently limited to information from the CloudSat satellite. Here, a first evaluation of the CloudSat snowfall record is performed using observations of ground-based precipitation radars. Results indicate an accurate representation of the snowfall climatology over Antarctica, despite the low overpass frequency of the satellite, outperforming state-of-the-art model estimates. Individual snowfall events are however not well represented.
Niels Souverijns, Alexandra Gossart, Irina V. Gorodetskaya, Stef Lhermitte, Alexander Mangold, Quentin Laffineur, Andy Delcloo, and Nicole P. M. van Lipzig
The Cryosphere, 12, 1987–2003, https://doi.org/10.5194/tc-12-1987-2018, https://doi.org/10.5194/tc-12-1987-2018, 2018
Short summary
Short summary
This work is the first to gain insight into the local surface mass balance over Antarctica using accurate long-term snowfall observations. A non-linear relationship between accumulation and snowfall is discovered, indicating that total surface mass balance measurements are not a good proxy for snowfall over Antarctica. Furthermore, the meteorological drivers causing changes in the local SMB are identified.
Jan Melchior van Wessem, Willem Jan van de Berg, Brice P. Y. Noël, Erik van Meijgaard, Charles Amory, Gerit Birnbaum, Constantijn L. Jakobs, Konstantin Krüger, Jan T. M. Lenaerts, Stef Lhermitte, Stefan R. M. Ligtenberg, Brooke Medley, Carleen H. Reijmer, Kristof van Tricht, Luke D. Trusel, Lambertus H. van Ulft, Bert Wouters, Jan Wuite, and Michiel R. van den Broeke
The Cryosphere, 12, 1479–1498, https://doi.org/10.5194/tc-12-1479-2018, https://doi.org/10.5194/tc-12-1479-2018, 2018
Short summary
Short summary
We present a detailed evaluation of the latest version of the regional atmospheric climate model RACMO2.3p2 (1979-2016) over the Antarctic ice sheet. The model successfully reproduces the present-day climate and surface mass balance (SMB) when compared with an extensive set of observations and improves on previous estimates of the Antarctic climate and SMB.
This study shows that the latest version of RACMO2 can be used for high-resolution future projections over the AIS.
Brice Noël, Willem Jan van de Berg, J. Melchior van Wessem, Erik van Meijgaard, Dirk van As, Jan T. M. Lenaerts, Stef Lhermitte, Peter Kuipers Munneke, C. J. P. Paul Smeets, Lambertus H. van Ulft, Roderik S. W. van de Wal, and Michiel R. van den Broeke
The Cryosphere, 12, 811–831, https://doi.org/10.5194/tc-12-811-2018, https://doi.org/10.5194/tc-12-811-2018, 2018
Short summary
Short summary
We present a detailed evaluation of the latest version of the regional climate model RACMO2.3p2 at 11 km resolution (1958–2016) over the Greenland ice sheet (GrIS). The model successfully reproduces the present-day climate and surface mass balance, i.e. snowfall minus meltwater run-off, of the GrIS compared to in situ observations. Since run-off from marginal narrow glaciers is poorly resolved at 11 km, further statistical downscaling to 1 km resolution is required for mass balance studies.
Alexandra Gossart, Niels Souverijns, Irina V. Gorodetskaya, Stef Lhermitte, Jan T. M. Lenaerts, Jan H. Schween, Alexander Mangold, Quentin Laffineur, and Nicole P. M. van Lipzig
The Cryosphere, 11, 2755–2772, https://doi.org/10.5194/tc-11-2755-2017, https://doi.org/10.5194/tc-11-2755-2017, 2017
Short summary
Short summary
Blowing snow plays an important role on local surface mass balance of Antarctica. We present here the blowing snow detection algorithm, to retrieve blowing snow occurrence from the attenuated backscatter signal of ceilometers set up at two station. There is a good correspondence in detection of heavy blowing snow by the algorithm and the visual observations performed at Neumayer station. Moreover, most of the blowing snow occurs during events bringing precipitation from the coast inland.
Kristof Van Tricht, Stef Lhermitte, Irina V. Gorodetskaya, and Nicole P. M. van Lipzig
The Cryosphere, 10, 2379–2397, https://doi.org/10.5194/tc-10-2379-2016, https://doi.org/10.5194/tc-10-2379-2016, 2016
Short summary
Short summary
Despite the crucial role of polar regions in the global climate system, the limited availability of observations on the ground hampers a detailed understanding of their energy budget. Here we develop a method to use satellites to fill these observational gaps. We show that by sampling satellite observations in a smart way, coverage is greatly enhanced. We conclude that this method might help improve our understanding of the polar energy budget, and ultimately its effects on the global climate.
Brice Noël, Willem Jan van de Berg, Horst Machguth, Stef Lhermitte, Ian Howat, Xavier Fettweis, and Michiel R. van den Broeke
The Cryosphere, 10, 2361–2377, https://doi.org/10.5194/tc-10-2361-2016, https://doi.org/10.5194/tc-10-2361-2016, 2016
Short summary
Short summary
We present a 1 km resolution data set (1958–2015) of daily Greenland ice sheet surface mass balance (SMB), statistically downscaled from the data of RACMO2.3 at 11 km using elevation dependence, precipitation and bare ice albedo corrections. The data set resolves Greenland narrow ablation zones and local outlet glaciers, and shows more realistic SMB patterns, owing to enhanced runoff at the ice sheet margins. An evaluation of the product against SMB measurements shows improved agreement.
Paul Hublart, Denis Ruelland, Inaki García de Cortázar-Atauri, Simon Gascoin, Stef Lhermitte, and Antonio Ibacache
Hydrol. Earth Syst. Sci., 20, 3691–3717, https://doi.org/10.5194/hess-20-3691-2016, https://doi.org/10.5194/hess-20-3691-2016, 2016
Short summary
Short summary
Our paper explores the reliability of conceptual catchment models in the dry Andes. First, we show that explicitly accounting for irrigation water use improves streamflow predictions during dry years. Second, we show that sublimation losses can be easily incorporated into temperature-based melt models without increasing model complexity too much. Our work also highlights areas requiring additional research, including the need for a better conceptualization of runoff generation processes.
S. Lhermitte, J. Abermann, and C. Kinnard
The Cryosphere, 8, 1069–1086, https://doi.org/10.5194/tc-8-1069-2014, https://doi.org/10.5194/tc-8-1069-2014, 2014
K. Van Tricht, I. V. Gorodetskaya, S. Lhermitte, D. D. Turner, J. H. Schween, and N. P. M. Van Lipzig
Atmos. Meas. Tech., 7, 1153–1167, https://doi.org/10.5194/amt-7-1153-2014, https://doi.org/10.5194/amt-7-1153-2014, 2014
Related subject area
Discipline: Ice sheets | Subject: Remote Sensing
A framework for automated supraglacial lake detection and depth retrieval in ICESat-2 photon data across the Greenland and Antarctic ice sheets
Change in grounding line location on the Antarctic Peninsula measured using a tidal motion offset correlation method
AWI-ICENet1: a convolutional neural network retracker for ice altimetry
Sentinel-1 detection of ice slabs on the Greenland Ice Sheet
Mapping the extent of giant Antarctic icebergs with deep learning
Mapping Antarctic crevasses and their evolution with deep learning applied to satellite radar imagery
AutoTerm: an automated pipeline for glacier terminus extraction using machine learning and a “big data” repository of Greenland glacier termini
Recent changes in drainage route and outburst magnitude of the Russell Glacier ice-dammed lake, West Greenland
Grounding line retreat and tide-modulated ocean channels at Moscow University and Totten Glacier ice shelves, East Antarctica
Seasonal land-ice-flow variability in the Antarctic Peninsula
Empirical correction of systematic orthorectification error in Sentinel-2 velocity fields for Greenlandic outlet glaciers
A leading-edge-based method for correction of slope-induced errors in ice-sheet heights derived from radar altimetry
An empirical algorithm to map perennial firn aquifers and ice slabs within the Greenland Ice Sheet using satellite L-band microwave radiometry
Supraglacial lake bathymetry automatically derived from ICESat-2 constraining lake depth estimates from multi-source satellite imagery
Penetration of interferometric radar signals in Antarctic snow
Brief communication: Ice sheet elevation measurements from the Sentinel-3A and Sentinel-3B tandem phase
Using ICESat-2 and Operation IceBridge altimetry for supraglacial lake depth retrievals
Brief communication: Mapping Greenland's perennial firn aquifers using enhanced-resolution L-band brightness temperature image time series
Quantifying spatiotemporal variability of glacier algal blooms and the impact on surface albedo in southwestern Greenland
Aerogeophysical characterization of an active subglacial lake system in the David Glacier catchment, Antarctica
Measuring the location and width of the Antarctic grounding zone using CryoSat-2
Brief Communication: Update on the GPS reflection technique for measuring snow accumulation in Greenland
Improved GNSS-R bi-static altimetry and independent digital elevation models of Greenland and Antarctica from TechDemoSat-1
Melt in Antarctica derived from Soil Moisture and Ocean Salinity (SMOS) observations at L band
Sentinel-3 Delay-Doppler altimetry over Antarctica
The Reference Elevation Model of Antarctica
Assessment of altimetry using ground-based GPS data from the 88S Traverse, Antarctica, in support of ICESat-2
Dual-satellite (Sentinel-2 and Landsat 8) remote sensing of supraglacial lakes in Greenland
Coherent large beamwidth processing of radio-echo sounding data
Multi-channel and multi-polarization radar measurements around the NEEM site
Seasonal variations of the backscattering coefficient measured by radar altimeters over the Antarctic Ice Sheet
Recent dynamic changes on Fleming Glacier after the disintegration of Wordie Ice Shelf, Antarctic Peninsula
Philipp Sebastian Arndt and Helen Amanda Fricker
The Cryosphere, 18, 5173–5206, https://doi.org/10.5194/tc-18-5173-2024, https://doi.org/10.5194/tc-18-5173-2024, 2024
Short summary
Short summary
We develop a method for ice-sheet-scale retrieval of supraglacial meltwater depths using ICESat-2 photon data. We report results for two drainage basins in Greenland and Antarctica during two contrasting melt seasons, where our method reveals a total of 1249 lake segments up to 25 m deep. The large volume and wide variety of accurate depth data that our method provides enable the development of data-driven models of meltwater volumes in satellite imagery.
Benjamin J. Wallis, Anna E. Hogg, Yikai Zhu, and Andrew Hooper
The Cryosphere, 18, 4723–4742, https://doi.org/10.5194/tc-18-4723-2024, https://doi.org/10.5194/tc-18-4723-2024, 2024
Short summary
Short summary
The grounding line, where ice begins to float, is an essential variable to understand ice dynamics, but in some locations it can be challenging to measure with established techniques. Using satellite data and a new method, Wallis et al. measure the grounding line position of glaciers and ice shelves in the Antarctic Peninsula and find retreats of up to 16.3 km have occurred since the last time measurements were made in the 1990s.
Veit Helm, Alireza Dehghanpour, Ronny Hänsch, Erik Loebel, Martin Horwath, and Angelika Humbert
The Cryosphere, 18, 3933–3970, https://doi.org/10.5194/tc-18-3933-2024, https://doi.org/10.5194/tc-18-3933-2024, 2024
Short summary
Short summary
We present a new approach (AWI-ICENet1), based on a deep convolutional neural network, for analysing satellite radar altimeter measurements to accurately determine the surface height of ice sheets. Surface height estimates obtained with AWI-ICENet1 (along with related products, such as ice sheet height change and volume change) show improved and unbiased results compared to other products. This is important for the long-term monitoring of ice sheet mass loss and its impact on sea level rise.
Riley Culberg, Roger J. Michaelides, and Julie Z. Miller
The Cryosphere, 18, 2531–2555, https://doi.org/10.5194/tc-18-2531-2024, https://doi.org/10.5194/tc-18-2531-2024, 2024
Short summary
Short summary
Ice slabs enhance meltwater runoff from the Greenland Ice Sheet. Therefore, it is important to understand their extent and change in extent over time. We present a new method for detecting ice slabs in satellite radar data, which we use to map ice slabs at 500 m resolution across the entire ice sheet in winter 2016–2017. Our results provide better spatial coverage and resolution than previous maps from airborne radar and lay the groundwork for long-term monitoring of ice slabs from space.
Anne Braakmann-Folgmann, Andrew Shepherd, David Hogg, and Ella Redmond
The Cryosphere, 17, 4675–4690, https://doi.org/10.5194/tc-17-4675-2023, https://doi.org/10.5194/tc-17-4675-2023, 2023
Short summary
Short summary
In this study, we propose a deep neural network to map the extent of giant Antarctic icebergs in Sentinel-1 images automatically. While each manual delineation requires several minutes, our U-net takes less than 0.01 s. In terms of accuracy, we find that U-net outperforms two standard segmentation techniques (Otsu, k-means) in most metrics and is more robust to challenging scenes with sea ice, coast and other icebergs. The absolute median deviation in iceberg area across 191 images is 4.1 %.
Trystan Surawy-Stepney, Anna E. Hogg, Stephen L. Cornford, and David C. Hogg
The Cryosphere, 17, 4421–4445, https://doi.org/10.5194/tc-17-4421-2023, https://doi.org/10.5194/tc-17-4421-2023, 2023
Short summary
Short summary
The presence of crevasses in Antarctica influences how the ice sheet behaves. It is important, therefore, to collect data on the spatial distribution of crevasses and how they are changing. We present a method of mapping crevasses from satellite radar imagery and apply it to 7.5 years of images, covering Antarctica's floating and grounded ice. We develop a method of measuring change in the density of crevasses and quantify increased fracturing in important parts of the West Antarctic Ice Sheet.
Enze Zhang, Ginny Catania, and Daniel T. Trugman
The Cryosphere, 17, 3485–3503, https://doi.org/10.5194/tc-17-3485-2023, https://doi.org/10.5194/tc-17-3485-2023, 2023
Short summary
Short summary
Glacier termini are essential for studying why glaciers retreat, but they need to be mapped automatically due to the volume of satellite images. Existing automated mapping methods have been limited due to limited automation, lack of quality control, and inadequacy in highly diverse terminus environments. We design a fully automated, deep-learning-based method to produce termini with quality control. We produced 278 239 termini in Greenland and provided a way to deliver new termini regularly.
Mads Dømgaard, Kristian K. Kjeldsen, Flora Huiban, Jonathan L. Carrivick, Shfaqat A. Khan, and Anders A. Bjørk
The Cryosphere, 17, 1373–1387, https://doi.org/10.5194/tc-17-1373-2023, https://doi.org/10.5194/tc-17-1373-2023, 2023
Short summary
Short summary
Sudden releases of meltwater from glacier-dammed lakes can influence ice flow, cause flooding hazards and landscape changes. This study presents a record of 14 drainages from 2007–2021 from a lake in west Greenland. The time series reveals how the lake fluctuates between releasing large and small amounts of drainage water which is caused by a weakening of the damming glacier following the large events. We also find a shift in the water drainage route which increases the risk of flooding hazards.
Tian Li, Geoffrey J. Dawson, Stephen J. Chuter, and Jonathan L. Bamber
The Cryosphere, 17, 1003–1022, https://doi.org/10.5194/tc-17-1003-2023, https://doi.org/10.5194/tc-17-1003-2023, 2023
Short summary
Short summary
The Totten and Moscow University glaciers in East Antarctica have the potential to make a significant contribution to future sea-level rise. We used a combination of different satellite measurements to show that the grounding lines have been retreating along the fast-flowing ice streams across these two glaciers. We also found two tide-modulated ocean channels that might open new pathways for the warm ocean water to enter the ice shelf cavity.
Karla Boxall, Frazer D. W. Christie, Ian C. Willis, Jan Wuite, and Thomas Nagler
The Cryosphere, 16, 3907–3932, https://doi.org/10.5194/tc-16-3907-2022, https://doi.org/10.5194/tc-16-3907-2022, 2022
Short summary
Short summary
Using high-spatial- and high-temporal-resolution satellite imagery, we provide the first evidence for seasonal flow variability of land ice draining to George VI Ice Shelf (GVIIS), Antarctica. Ultimately, our findings imply that other glaciers in Antarctica may be susceptible to – and/or currently undergoing – similar ice-flow seasonality, including at the highly vulnerable and rapidly retreating Pine Island and Thwaites glaciers.
Thomas R. Chudley, Ian M. Howat, Bidhyananda Yadav, and Myoung-Jong Noh
The Cryosphere, 16, 2629–2642, https://doi.org/10.5194/tc-16-2629-2022, https://doi.org/10.5194/tc-16-2629-2022, 2022
Short summary
Short summary
Sentinel-2 images are subject to distortion due to orthorectification error, which makes it difficult to extract reliable glacier velocity fields from images from different orbits. Here, we use a complete record of velocity fields at four Greenlandic outlet glaciers to empirically estimate the systematic error, allowing us to correct cross-track glacier velocity fields to a comparable accuracy to other medium-resolution satellite datasets.
Weiran Li, Cornelis Slobbe, and Stef Lhermitte
The Cryosphere, 16, 2225–2243, https://doi.org/10.5194/tc-16-2225-2022, https://doi.org/10.5194/tc-16-2225-2022, 2022
Short summary
Short summary
This study proposes a new method for correcting the slope-induced errors in satellite radar altimetry. The slope-induced errors can significantly affect the height estimations of ice sheets if left uncorrected. This study applies the method to radar altimetry data (CryoSat-2) and compares the performance with two existing methods. The performance is assessed by comparison with independent height measurements from ICESat-2. The assessment shows that the method performs promisingly.
Julie Z. Miller, Riley Culberg, David G. Long, Christopher A. Shuman, Dustin M. Schroeder, and Mary J. Brodzik
The Cryosphere, 16, 103–125, https://doi.org/10.5194/tc-16-103-2022, https://doi.org/10.5194/tc-16-103-2022, 2022
Short summary
Short summary
We use L-band brightness temperature imagery from NASA's Soil Moisture Active Passive (SMAP) satellite to map the extent of perennial firn aquifer and ice slab areas within the Greenland Ice Sheet. As Greenland's climate continues to warm and seasonal surface melting increases in extent, intensity, and duration, quantifying the possible rapid expansion of perennial firn aquifers and ice slab areas has significant implications for understanding the stability of the Greenland Ice Sheet.
Rajashree Tri Datta and Bert Wouters
The Cryosphere, 15, 5115–5132, https://doi.org/10.5194/tc-15-5115-2021, https://doi.org/10.5194/tc-15-5115-2021, 2021
Short summary
Short summary
The ICESat-2 laser altimeter can detect the surface and bottom of a supraglacial lake. We introduce the Watta algorithm, automatically calculating lake surface, corrected bottom, and (sub-)surface ice at high resolution adapting to signal strength. ICESat-2 depths constrain full lake depths of 46 lakes over Jakobshavn glacier using multiple sources of imagery, including very high-resolution Planet imagery, used for the first time to extract supraglacial lake depths empirically using ICESat-2.
Helmut Rott, Stefan Scheiblauer, Jan Wuite, Lukas Krieger, Dana Floricioiu, Paola Rizzoli, Ludivine Libert, and Thomas Nagler
The Cryosphere, 15, 4399–4419, https://doi.org/10.5194/tc-15-4399-2021, https://doi.org/10.5194/tc-15-4399-2021, 2021
Short summary
Short summary
We studied relations between interferometric synthetic aperture radar (InSAR) signals and snow–firn properties and tested procedures for correcting the penetration bias of InSAR digital elevation models at Union Glacier, Antarctica. The work is based on SAR data of the TanDEM-X mission, topographic data from optical sensors and field measurements. We provide new insights on radar signal interactions with polar snow and show the performance of penetration bias retrievals using InSAR coherence.
Malcolm McMillan, Alan Muir, and Craig Donlon
The Cryosphere, 15, 3129–3134, https://doi.org/10.5194/tc-15-3129-2021, https://doi.org/10.5194/tc-15-3129-2021, 2021
Short summary
Short summary
We evaluate the consistency of ice sheet elevation measurements made by two satellites: Sentinel-3A and Sentinel-3B. We analysed data from the unique
tandemphase of the mission, where the two satellites flew 30 s apart to provide near-instantaneous measurements of Earth's surface. Analysing these data over Antarctica, we find no significant difference between the satellites, which is important for demonstrating that they can be used interchangeably for long-term ice sheet monitoring.
Zachary Fair, Mark Flanner, Kelly M. Brunt, Helen Amanda Fricker, and Alex Gardner
The Cryosphere, 14, 4253–4263, https://doi.org/10.5194/tc-14-4253-2020, https://doi.org/10.5194/tc-14-4253-2020, 2020
Short summary
Short summary
Ice on glaciers and ice sheets may melt and pond on ice surfaces in summer months. Detection and observation of these meltwater ponds is important for understanding glaciers and ice sheets, and satellite imagery has been used in previous work. However, image-based methods struggle with deep water, so we used data from the Ice, Clouds, and land Elevation Satellite-2 (ICESat-2) and the Airborne Topographic Mapper (ATM) to demonstrate the potential for lidar depth monitoring.
Julie Z. Miller, David G. Long, Kenneth C. Jezek, Joel T. Johnson, Mary J. Brodzik, Christopher A. Shuman, Lora S. Koenig, and Ted A. Scambos
The Cryosphere, 14, 2809–2817, https://doi.org/10.5194/tc-14-2809-2020, https://doi.org/10.5194/tc-14-2809-2020, 2020
Shujie Wang, Marco Tedesco, Patrick Alexander, Min Xu, and Xavier Fettweis
The Cryosphere, 14, 2687–2713, https://doi.org/10.5194/tc-14-2687-2020, https://doi.org/10.5194/tc-14-2687-2020, 2020
Short summary
Short summary
Glacial algal blooms play a significant role in darkening the Greenland Ice Sheet during summertime. The dark pigments generated by glacial algae could substantially reduce the bare ice albedo and thereby enhance surface melt. We used satellite data to map the spatial distribution of glacial algae and characterized the seasonal growth pattern and interannual trends of glacial algae in southwestern Greenland. Our study is important for bridging microbial activities with ice sheet mass balance.
Laura E. Lindzey, Lucas H. Beem, Duncan A. Young, Enrica Quartini, Donald D. Blankenship, Choon-Ki Lee, Won Sang Lee, Jong Ik Lee, and Joohan Lee
The Cryosphere, 14, 2217–2233, https://doi.org/10.5194/tc-14-2217-2020, https://doi.org/10.5194/tc-14-2217-2020, 2020
Short summary
Short summary
An extensive aerogeophysical survey including two active subglacial lakes was conducted over David Glacier, Antarctica. Laser altimetry shows that the lakes were at a highstand, while ice-penetrating radar has no unique signature for the lakes when compared to the broader basal environment. This suggests that active subglacial lakes are more likely to be part of a distributed subglacial hydrological system than to be discrete reservoirs, which has implications for future surveys and drilling.
Geoffrey J. Dawson and Jonathan L. Bamber
The Cryosphere, 14, 2071–2086, https://doi.org/10.5194/tc-14-2071-2020, https://doi.org/10.5194/tc-14-2071-2020, 2020
Short summary
Short summary
The grounding zone is where grounded ice begins to float and is the boundary at which the ocean has the most significant influence on the inland ice sheet. Here, we present the results of mapping the grounding zone of Antarctic ice shelves from CryoSat-2 radar altimetry. We found good agreement with previous methods that mapped the grounding zone. We also managed to map areas of Support Force Glacier and the Doake Ice Rumples (Filchner–Ronne Ice Shelf), which were previously incompletely mapped.
Kristine M. Larson, Michael MacFerrin, and Thomas Nylen
The Cryosphere, 14, 1985–1988, https://doi.org/10.5194/tc-14-1985-2020, https://doi.org/10.5194/tc-14-1985-2020, 2020
Short summary
Short summary
Reflected GPS signals can be used to measure snow accumulation. The GPS method is accurate and has a footprint that is larger than that of many other methods. This short note makes available 9 years of daily snow accumulation measurements from Greenland that were derived from reflected GPS signals. It also provides information about open-source software that the cryosphere community can use to analyze other datasets.
Jessica Cartwright, Christopher J. Banks, and Meric Srokosz
The Cryosphere, 14, 1909–1917, https://doi.org/10.5194/tc-14-1909-2020, https://doi.org/10.5194/tc-14-1909-2020, 2020
Short summary
Short summary
This study uses reflected GPS signals to measure ice at the South Pole itself for the first time. These measurements are essential to understand the interaction of the ice with the Earth’s physical systems. Orbital constraints mean that satellites are usually unable to measure in the vicinity of the South Pole itself. This is overcome here by using data obtained by UK TechDemoSat-1. Data are processed to obtain the height of glacial ice across the Greenland and Antarctic ice sheets.
Marion Leduc-Leballeur, Ghislain Picard, Giovanni Macelloni, Arnaud Mialon, and Yann H. Kerr
The Cryosphere, 14, 539–548, https://doi.org/10.5194/tc-14-539-2020, https://doi.org/10.5194/tc-14-539-2020, 2020
Short summary
Short summary
To study the coast and ice shelves affected by melt in Antarctica during the austral summer, we exploited the 1.4 GHz radiometric satellite observations. We showed that this frequency provides additional information on melt occurrence and on the location of the water in the snowpack compared to the 19 GHz observations. This opens an avenue for improving the melting season monitoring with a combination of both frequencies and exploring the possibility of deep-water detection in the snowpack.
Malcolm McMillan, Alan Muir, Andrew Shepherd, Roger Escolà, Mònica Roca, Jérémie Aublanc, Pierre Thibaut, Marco Restano, Américo Ambrozio, and Jérôme Benveniste
The Cryosphere, 13, 709–722, https://doi.org/10.5194/tc-13-709-2019, https://doi.org/10.5194/tc-13-709-2019, 2019
Short summary
Short summary
Melting of the Greenland and Antarctic ice sheets is one of the main causes of current sea level rise. Understanding ice sheet change requires large-scale systematic satellite monitoring programmes. This study provides the first assessment of a new long-term source of measurements, from Sentinel-3 satellite altimetry. We estimate the accuracy of Sentinel-3 across Antarctica, show that the satellite can detect regions that are rapidly losing ice, and identify signs of subglacial lake activity.
Ian M. Howat, Claire Porter, Benjamin E. Smith, Myoung-Jong Noh, and Paul Morin
The Cryosphere, 13, 665–674, https://doi.org/10.5194/tc-13-665-2019, https://doi.org/10.5194/tc-13-665-2019, 2019
Short summary
Short summary
The Reference Elevation Model of Antarctica (REMA) is the first continental-scale terrain map at less than 10 m resolution, and the first with a time stamp, enabling measurements of elevation change. REMA is constructed from over 300 000 individual stereoscopic elevation models (DEMs) extracted from submeter-resolution satellite imagery. REMA is vertically registered to satellite altimetry, resulting in errors of less than 1 m over most of its area and relative uncertainties of decimeters.
Kelly M. Brunt, Thomas A. Neumann, and Christopher F. Larsen
The Cryosphere, 13, 579–590, https://doi.org/10.5194/tc-13-579-2019, https://doi.org/10.5194/tc-13-579-2019, 2019
Short summary
Short summary
This paper provides an assessment of new GPS elevation data collected near the South Pole, Antarctica, that will ultimately be used for ICESat-2 satellite elevation data validation. Further, using the new ground-based GPS data, this paper provides an assessment of airborne lidar elevation data collected between 2014 and 2017, which will also be used for ICESat-2 data validation.
Andrew G. Williamson, Alison F. Banwell, Ian C. Willis, and Neil S. Arnold
The Cryosphere, 12, 3045–3065, https://doi.org/10.5194/tc-12-3045-2018, https://doi.org/10.5194/tc-12-3045-2018, 2018
Short summary
Short summary
A new approach is presented for automatically monitoring changes to area and volume of surface lakes on the Greenland Ice Sheet using Landsat 8 and Sentinel-2 satellite data. The dual-satellite record improves on previous work since it tracks changes to more lakes (including small ones), identifies more lake-drainage events, and has higher precision. The results also show that small lakes are important in ice-sheet hydrology as they route more surface run-off into the ice sheet than large lakes.
Anton Heister and Rolf Scheiber
The Cryosphere, 12, 2969–2979, https://doi.org/10.5194/tc-12-2969-2018, https://doi.org/10.5194/tc-12-2969-2018, 2018
Short summary
Short summary
We provide a method based on Fourier analysis of coherent radio-echo sounding data for analyzing angular back-scattering characteristics of the ice sheet and bed. The characteristics can be used for the bed roughness estimation and detection of subglacial water. The method also offers improved estimation of the internal layers' tilt. The research is motivated by a need for a tool for training dictionaries for model-based tomographic focusing of multichannel coherent radio-echo sounders.
Jilu Li, Jose A. Vélez González, Carl Leuschen, Ayyangar Harish, Prasad Gogineni, Maurine Montagnat, Ilka Weikusat, Fernando Rodriguez-Morales, and John Paden
The Cryosphere, 12, 2689–2705, https://doi.org/10.5194/tc-12-2689-2018, https://doi.org/10.5194/tc-12-2689-2018, 2018
Short summary
Short summary
Ice properties inferred from multi-polarization measurements can provide insight into ice strain, viscosity, and ice flow. The Center for Remote Sensing of Ice Sheets used a ground-based radar for multi-channel and multi-polarization measurements at the NEEM site. This paper describes the radar system, antenna configurations, data collection, and processing and analysis of this data set. Comparisons between the radar observations, simulations, and ice core fabric data are in very good agreement.
Fifi Ibrahime Adodo, Frédérique Remy, and Ghislain Picard
The Cryosphere, 12, 1767–1778, https://doi.org/10.5194/tc-12-1767-2018, https://doi.org/10.5194/tc-12-1767-2018, 2018
Short summary
Short summary
In Antarctica, the seasonal cycle of the backscatter behaves differently at high and low frequencies, peaking in winter and in summer, respectively. At the intermediate frequency, some areas behave analogously to low frequency in terms of the seasonal cycle, but other areas behave analogously to high frequency. This calls into question the empirical relationships often used to correct elevation changes from radar penetration into the snowpack using backscatter.
Peter Friedl, Thorsten C. Seehaus, Anja Wendt, Matthias H. Braun, and Kathrin Höppner
The Cryosphere, 12, 1347–1365, https://doi.org/10.5194/tc-12-1347-2018, https://doi.org/10.5194/tc-12-1347-2018, 2018
Short summary
Short summary
Fleming Glacier is the biggest tributary glacier of the former Wordie Ice Shelf. Radar satellite data and airborne ice elevation measurements show that the glacier accelerated by ~27 % between 2008–2011 and that ice thinning increased by ~70 %. This was likely a response to a two-phase ungrounding of the glacier tongue between 2008 and 2011, which was mainly triggered by increased basal melt during two strong upwelling events of warm circumpolar deep water.
Cited articles
Amory, C., Buizert, C., Buzzard, S., Case, E., Clerx, N., Culberg, R., Datta, R. T., Dey, R., Drews, R., Dunmire, D., Eayrs, C., Hansen, N., Humbert, A., Kaitheri, A., Keegan, K., Kuipers Munneke, P., Lenaerts, J. T. M., Lhermitte, S., Mair, D., McDowell, I., Mejia, J., Meyer, C. R., Morris, E., Moser, D., Oraschewski, F. M., Pearce, E., de Roda Husman, S., Schlegel, N.-J., Schultz, T., Simonsen, S. B., Stevens, C. M., Thomas, E. R., Thompson-Munson, M., Wever, N., and Wouters, B.: Firn on ice sheets, Nature Reviews Earth & Environment, 5, 79–99, https://doi.org/10.1038/s43017-023-00507-9, 2024. a, b, c
Anilkumar, R., Bharti, R., Chutia, D., and Aggarwal, S. P.: Modelling point mass balance for the glaciers of the Central European Alps using machine learning techniques, The Cryosphere, 17, 2811–2828, https://doi.org/10.5194/tc-17-2811-2023, 2023. a, b
Archer, K. J. and Kimes, R. V.: Empirical characterization of random forest variable importance measures, Comput. Stat. Data An., 52, 2249–2260, https://doi.org/10.1016/j.csda.2007.08.015, 2008. a
Arndt, S. and Haas, C.: Spatiotemporal variability and decadal trends of snowmelt processes on Antarctic sea ice observed by satellite scatterometers, The Cryosphere, 13, 1943–1958, https://doi.org/10.5194/tc-13-1943-2019, 2019. a
Bingham, A. and Drinkwater, M.: Recent changes in the microwave scattering properties of the Antarctic ice sheet, IEEE T. Geosci. Remote, 38, 1810–1820, https://doi.org/10.1109/36.851765, 2000. a
Breiman, L.: Bagging predictors, Machine Learning, 24, 123–140, https://doi.org/10.1007/bf00058655, 1996. a
Breiman, L.: Random Forests, Machine Learning, 45, 5–32, https://doi.org/10.1023/a:1010933404324, 2001. a
Brucker, L., Picard, G., and Fily, M.: Snow grain-size profiles deduced from microwave snow emissivities in Antarctica, J. Glaciol., 56, 514–526, https://doi.org/10.3189/002214310792447806, 2010. a, b, c, d
Brucker, L., Picard, G., Arnaud, L., Barnola, J.-M., Schneebeli, M., Brunjail, H., Lefebvre, E., and Fily, M.: Modeling time series of microwave brightness temperature at Dome C, Antarctica, using vertically resolved snow temperature and microstructure measurements, J. Glaciol., 57, 171–182, https://doi.org/10.3189/002214311795306736, 2011. a
Brucker, L., Dinnat, E. P., Picard, G., and Champollion, N.: Effect of Snow Surface Metamorphism on Aquarius L-Band Radiometer Observations at Dome C, Antarctica, IEEE T. Geosci. Remote, 52, 7408–7417, https://doi.org/10.1109/tgrs.2014.2312102, 2014. a, b
Cartwright, J., Fraser, A. D., and Porter-Smith, R.: Polar maps of C-band backscatter parameters from the Advanced Scatterometer, Earth Syst. Sci. Data, 14, 479–490, https://doi.org/10.5194/essd-14-479-2022, 2022. a
Champollion, N., Picard, G., Arnaud, L., Lefebvre, E., and Fily, M.: Hoar crystal development and disappearance at Dome C, Antarctica: observation by near-infrared photography and passive microwave satellite, The Cryosphere, 7, 1247–1262, https://doi.org/10.5194/tc-7-1247-2013, 2013. a, b, c, d, e, f, g, h, i, j, k
Craven, M. and Allison, I.: Firnification and the effects of wind-packing on Antarctic snow, Ann. Glaciol., 27, 239–245, https://doi.org/10.3189/1998aog27-1-239-245, 1998. a
de Roda Husman, S., Hu, Z., Wouters, B., Munneke, P. K., Veldhuijsen, S., and Lhermitte, S.: Remote Sensing of Surface Melt on Antarctica: Opportunities and Challenges, IEEE J. Sel. Top. Appl., 16, 2462–2480, https://doi.org/10.1109/jstars.2022.3216953, 2022. a, b
Early, D. and Long, D.: Image reconstruction and enhanced resolution imaging from irregular samples, IEEE T. Geosci. Remote, 39, 291–302, https://doi.org/10.1109/36.905237, 2001. a
Fahnestock, M., Bindschadler, R., Kwok, R., and Jezek, K.: Greenland Ice Sheet Surface Properties and Ice Dynamics from ERS-1 SAR Imagery, Science, 262, 1530–1534, https://doi.org/10.1126/science.262.5139.1530, 1993. a
Fahnestock, M. A., Scambos, T. A., Shuman, C. A., Arthern, R. J., Winebrenner, D. P., and Kwok, R.: Snow megadune fields on the East Antarctic Plateau: Extreme atmosphere-ice interaction, Geophys. Res. Lett., 27, 3719–3722, https://doi.org/10.1029/1999gl011248, 2000. a
Figa-Saldaña, J., Wilson, J. J., Attema, E., Gelsthorpe, R., Drinkwater, M. R., and Stoffelen, A.: The advanced scatterometer (ASCAT) on the meteorological operational (MetOp) platform: A follow on for European wind scatterometers, Can. J. Remote Sens., 28, 404–412, https://doi.org/10.5589/m02-035, 2002. a
Fraser, A. D., Nigro, M. A., Ligtenberg, S. R. M., Legrésy, B., Inoue, M., Cassano, J. J., Kuipers Munneke, P., Lenaerts, J. T. M., Young, N. W., Treverrow, A., van den Broeke, M., and Enomoto, H.: Drivers of ASCAT C band backscatter variability in the dry snow zone of Antarctica, J. Glaciol., 62, 170–184, https://doi.org/10.1017/jog.2016.29, 2016. a, b, c, d, e, f, g, h, i, j, k, l, m, n, o, p, q
Fujita, S., Goto-Azuma, K., Hirabayashi, M., Hori, A., Iizuka, Y., Motizuki, Y., Motoyama, H., and Takahashi, K.: Densification of layered firn in the ice sheet at Dome Fuji, Antarctica, J. Glaciol., 62, 103–123, https://doi.org/10.1017/jog.2016.16, 2016. a
Fung, A., Li, Z., and Chen, K.: Backscattering from a randomly rough dielectric surface, IEEE T. Geosci. Remote, 30, 356–369, https://doi.org/10.1109/36.134085, 1992. a
Hastie, T., Tibshirani, R., and Friedman, J.: Random Forests, Springer New York, 587–604, ISBN 9780387848587, https://doi.org/10.1007/978-0-387-84858-7_15, 2008. a
Hengl, T., Nussbaum, M., Wright, M. N., Heuvelink, G. B., and Gräler, B.: Random forest as a generic framework for predictive modeling of spatial and spatio-temporal variables, PeerJ, 6, e5518, https://doi.org/10.7717/peerj.5518, 2018. a
Johnson, A., Fahnestock, M., and Hock, R.: Evaluation of passive microwave melt detection methods on Antarctic Peninsula ice shelves using time series of Sentinel-1 SAR, Remote Sens. Environ., 250, 112044, https://doi.org/10.1016/j.rse.2020.112044, 2020. a
Judson, A. and Doesken, N.: Density of Freshly Fallen Snow in the Central Rocky Mountains, B. Am. Meteorol. Soc., 81, 1577–1587, https://doi.org/10.1175/1520-0477(2000)081<1577:doffsi>2.3.co;2, 2000. a
Kar, R. and Aksoy, M.: Passive Microwave Remote Sensing of the Antarctic Ice Sheet: Retrieval of Firn Properties Near the Concordia Station, IEEE Geosci. Remote S., 21, 1–5, https://doi.org/10.1109/lgrs.2023.3343594, 2024. a
Keenan, E., Wever, N., Dattler, M., Lenaerts, J. T. M., Medley, B., Kuipers Munneke, P., and Reijmer, C.: Physics-based SNOWPACK model improves representation of near-surface Antarctic snow and firn density, The Cryosphere, 15, 1065–1085, https://doi.org/10.5194/tc-15-1065-2021, 2021. a
Kingslake, J., Ely, J. C., Das, I., and Bell, R. E.: Widespread movement of meltwater onto and across Antarctic ice shelves, Nature, 544, 349–352, https://doi.org/10.1038/nature22049, 2017. a
Koenig, L. and Montgomery, L.: Surface Mass Balance and Snow Depth on Sea Ice Working Group (SUMup) snow density subdataset, Greenland and Antartica, 1950–2018, Arctic Data Center instead of National Snow and Ice Data Center [data set], https://doi.org/10.18739/A2JH3D23R, 2018. a, b
Kuipers Munneke, P., Ligtenberg, S. R. M., Noël, B. P. Y., Howat, I. M., Box, J. E., Mosley-Thompson, E., McConnell, J. R., Steffen, K., Harper, J. T., Das, S. B., and van den Broeke, M. R.: Elevation change of the Greenland Ice Sheet due to surface mass balance and firn processes, 1960–2014, The Cryosphere, 9, 2009–2025, https://doi.org/10.5194/tc-9-2009-2015, 2015. a
Kunkee, D. B., Poe, G. A., Boucher, D. J., Swadley, S. D., Hong, Y., Wessel, J. E., and Uliana, E. A.: Design and Evaluation of the First Special Sensor Microwave Imager/Sounder, IEEE T. Geosci. Remote, 46, 863–883, https://doi.org/10.1109/tgrs.2008.917980, 2008. a
Larue, F., Picard, G., Aublanc, J., Arnaud, L., Robledano-Perez, A., Meur, E. L., Favier, V., Jourdain, B., Savarino, J., and Thibaut, P.: Radar altimeter waveform simulations in Antarctica with the Snow Microwave Radiative Transfer Model (SMRT), Remote Sens. Environ., 263, 112534, https://doi.org/10.1016/j.rse.2021.112534, 2021. a, b, c, d, e
Leduc-Leballeur, M., Picard, G., Macelloni, G., Arnaud, L., Brogioni, M., Mialon, A., and Kerr, Y.: Influence of snow surface properties on L-band brightness temperature at Dome C, Antarctica, Remote Sens. Environ., 199, 427–436, https://doi.org/10.1016/j.rse.2017.07.035, 2017. a
Lehning, M., Bartelt, P., Brown, B., Fierz, C., and Satyawali, P.: A physical SNOWPACK model for the Swiss avalanche warning: Part II. Snow microstructure, Cold Reg. Sci. Technol., 35, 147–167, https://doi.org/10.1016/s0165-232x(02)00073-3, 2002. a
Lenaerts, J. T. M., Lhermitte, S., Drews, R., Ligtenberg, S. R. M., Berger, S., Helm, V., Smeets, C. J. P. P., van den Broeke, M. R., van de Berg, W. J., van Meijgaard, E., Eijkelboom, M., Eisen, O., and Pattyn, F.: Meltwater produced by wind–albedo interaction stored in an East Antarctic ice shelf, Nat. Clim. Change, 7, 58–62, https://doi.org/10.1038/nclimate3180, 2016. a
Li, J. and Zwally, H. J.: Modeling the density variation in the shallow firn layer, Ann. Glaciol., 38, 309–313, https://doi.org/10.3189/172756404781814988, 2004. a
Li, W., Lhermitte, S., and López-Dekker, P.: The potential of synthetic aperture radar interferometry for assessing meltwater lake dynamics on Antarctic ice shelves, The Cryosphere, 15, 5309–5322, https://doi.org/10.5194/tc-15-5309-2021, 2021. a
Ligtenberg, S. R. M., Helsen, M. M., and van den Broeke, M. R.: An improved semi-empirical model for the densification of Antarctic firn, The Cryosphere, 5, 809–819, https://doi.org/10.5194/tc-5-809-2011, 2011. a
Lindsley, R. D. and Long, D. G.: Standard BYU ASCAT Land/Ice Image Products, Tech. Rep., Brigham Young University Microwave Earth Remote Sensing (MERS) Laboratory, https://www.scp.byu.edu/docs/pdf/MERS1002.pdf (last access: 20 June 2022), 2010. a
Long, D. and Drinkwater, M.: Azimuth variation in microwave scatterometer and radiometer data over Antarctica, IEEE T. Geosci. Remote, 38, 1857–1870, https://doi.org/10.1109/36.851769, 2000. a, b
Long, D., Hardin, P., and Whiting, P.: Resolution enhancement of spaceborne scatterometer data, IEEE T. Geosci. Remote, 31, 700–715, https://doi.org/10.1109/36.225536, 1993. a
Macelloni, G., Brogioni, M., Pampaloni, P., and Cagnati, A.: Multifrequency Microwave Emission From the Dome-C Area on the East Antarctic Plateau: Temporal and Spatial Variability, IEEE T. Geosci. Remote, 45, 2029–2039, https://doi.org/10.1109/tgrs.2007.890805, 2007. a
Mätzler, C.: Improved Born approximation for scattering of radiation in a granular medium, J. Appl. Phys., 83, 6111–6117, https://doi.org/10.1063/1.367496, 1998. a
Meier, W. N., Stewart, J. S., Wilcox, H., Scott, D. J., and Hardman, M. A.: DMSP SSM/I-SSMIS Daily Polar Gridded Brightness Temperatures, Boulder, Colorado USA, Version 6, NASA National Snow and Ice Data Center Distributed Active Archive Center [data set], https://doi.org/10.5067/MXJL42WSXTS1, 2021. a, b
Meredith, M., Sommerkorn, M., Cassotta, S., Derksen, C., Ekaykin, A., Hollowed, A., Kofinas, G., Mackintosh, A., Melbourne-Thomas, J., Muelbert, M., Ottersen, G., Pritchard, H., and Schuur, E.: Polar Regions, chap. 3, 203–320, Cambridge University Press, Cambridge, UK and New York, NY, USA, https://doi.org/10.1017/9781009157964.005, 2019. a
Michel, A., Flament, T., and Rémy, F.: Study of the Penetration Bias of ENVISAT Altimeter Observations over Antarctica in Comparison to ICESat Observations, Remote Sensing, 6, 9412–9434, https://doi.org/10.3390/rs6109412, 2014. a
Montgomery, L., Koenig, L., and Alexander, P.: The SUMup dataset: compiled measurements of surface mass balance components over ice sheets and sea ice with analysis over Greenland, Earth Syst. Sci. Data, 10, 1959–1985, https://doi.org/10.5194/essd-10-1959-2018, 2018. a
Muñoz-Sabater, J.: ERA5-Land hourly data from 1950 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS) [data set], https://doi.org/10.24381/cds.e2161bac, 2019. a, b
Muñoz-Sabater, J., Dutra, E., Agustí-Panareda, A., Albergel, C., Arduini, G., Balsamo, G., Boussetta, S., Choulga, M., Harrigan, S., Hersbach, H., Martens, B., Miralles, D. G., Piles, M., Rodríguez-Fernández, N. J., Zsoter, E., Buontempo, C., and Thépaut, J.-N.: ERA5-Land: a state-of-the-art global reanalysis dataset for land applications, Earth Syst. Sci. Data, 13, 4349–4383, https://doi.org/10.5194/essd-13-4349-2021, 2021. a
Nicolas, J. P., Vogelmann, A. M., Scott, R. C., Wilson, A. B., Cadeddu, M. P., Bromwich, D. H., Verlinde, J., Lubin, D., Russell, L. M., Jenkinson, C., Powers, H. H., Ryczek, M., Stone, G., and Wille, J. D.: January 2016 extensive summer melt in West Antarctica favoured by strong El Niño, Nat. Commun., 8, 15799, https://doi.org/10.1038/ncomms15799, 2017. a, b, c, d, e, f
Pattyn, F. and Morlighem, M.: The uncertain future of the Antarctic Ice Sheet, Science, 367, 1331–1335, https://doi.org/10.1126/science.aaz5487, 2020. a
Picard, G., Fily, M., and Gallee, H.: Surface melting derived from microwave radiometers: a climatic indicator in Antarctica, Ann. Glaciol., 46, 29–34, https://doi.org/10.3189/172756407782871684, 2007. a, b, c, d
Picard, G., Brucker, L., Fily, M., Gallée, H., and Krinner, G.: Modeling time series of microwave brightness temperature in Antarctica, J. Glaciol., 55, 537–551, https://doi.org/10.3189/002214309788816678, 2009. a, b, c, d
Picard, G., Royer, A., Arnaud, L., and Fily, M.: Influence of meter-scale wind-formed features on the variability of the microwave brightness temperature around Dome C in Antarctica, The Cryosphere, 8, 1105–1119, https://doi.org/10.5194/tc-8-1105-2014, 2014. a
Picard, G., Sandells, M., and Löwe, H.: SMRT: an active–passive microwave radiative transfer model for snow with multiple microstructure and scattering formulations (v1.0), Geosci. Model Dev., 11, 2763–2788, https://doi.org/10.5194/gmd-11-2763-2018, 2018. a, b, c
Picard, G., Löwe, H., and Mätzler, C.: Brief communication: A continuous formulation of microwave scattering from fresh snow to bubbly ice from first principles, The Cryosphere, 16, 3861–3866, https://doi.org/10.5194/tc-16-3861-2022, 2022. a, b
Rignot, E.: Mass balance of East Antarctic glaciers and ice shelves from satellite data, Ann. Glaciol., 34, 217–227, https://doi.org/10.3189/172756402781817419, 2002. a
Rizzoli, P., Martone, M., Rott, H., and Moreira, A.: Characterization of Snow Facies on the Greenland Ice Sheet Observed by TanDEM-X Interferometric SAR Data, Remote Sensing, 9, 315, https://doi.org/10.3390/rs9040315, 2017. a, b, c
Rott, H., Sturm, K., and Miller, H.: Active and passive microwave signatures of Antarctic firn by means of field measurements and satellite data, Ann. Glaciol., 17, 337–343, https://doi.org/10.3189/S0260305500013070, 1993. a, b, c
Santi, E., Brogioni, M., Paloscia, S., and Pampaloni, P.: Analysis of the frequency and polarization indexes over snow cover areas by means of experimental and theoretical data, in: 2012 12th Specialist Meeting on Microwave Radiometry and Remote Sensing of the Environment (MicroRad), IEEE, Rome, Italy, 5–9 March 2012, https://doi.org/10.1109/microrad.2012.6185250, 2012a. a
Santi, E., Fontanelli, G., Pettinato, S., and Crepaz, A.: Monitoring of snow cover on Italian Alps using AMSR-E and Artificial Neural Networks, in: 2012 IEEE International Geoscience and Remote Sensing Symposium, IEEE, Munich, Germany, 22–27 July 2012, https://doi.org/10.1109/igarss.2012.6351095, 2012b. a
Schmidt, K., Tous Ramon, N., and Schwerdt, M.: Radiometric accuracy and stability of sentinel-1A determined using point targets, International Journal of Microwave and Wireless Technologies, 10, 538–546, https://doi.org/10.1017/s1759078718000016, 2018. a
Schröder, L., Horwath, M., Dietrich, R., Helm, V., van den Broeke, M. R., and Ligtenberg, S. R. M.: Four decades of Antarctic surface elevation changes from multi-mission satellite altimetry, The Cryosphere, 13, 427–449, https://doi.org/10.5194/tc-13-427-2019, 2019. a, b
Spergel, J. J., Kingslake, J., Creyts, T., van Wessem, M., and Fricker, H. A.: Surface meltwater drainage and ponding on Amery Ice Shelf, East Antarctica, 1973–2019, J. Glaciol., 67, 985–998, https://doi.org/10.1017/jog.2021.46, 2021. a
Stiles, W. H. and Ulaby, F. T.: The active and passive microwave response to snow parameters: 1. Wetness, J. Geophys. Res.-Oceans, 85, 1037–1044, https://doi.org/10.1029/jc085ic02p01037, 1980. a, b
Stokes, C. R., Abram, N. J., Bentley, M. J., Edwards, T. L., England, M. H., Foppert, A., Jamieson, S. S. R., Jones, R. S., King, M. A., Lenaerts, J. T. M., Medley, B., Miles, B. W. J., Paxman, G. J. G., Ritz, C., van de Flierdt, T., and Whitehouse, P. L.: Response of the East Antarctic Ice Sheet to past and future climate change, Nature, 608, 275–286, https://doi.org/10.1038/s41586-022-04946-0, 2022. a
Strobl, C., Boulesteix, A.-L., and Augustin, T.: Unbiased split selection for classification trees based on the Gini Index, Comput. Stat. Data An., 52, 483–501, https://doi.org/10.1016/j.csda.2006.12.030, 2007. a
Sugiyama, S., Enomoto, H., Fujita, S., Fukui, K., Nakazawa, F., Holmlund, P., and Surdyk, S.: Snow density along the route traversed by the Japanese-Swedish Antarctic Expedition 2007/08, J. Glaciol., 58, 529–539, https://doi.org/10.3189/2012jog11j201, 2012. a
Tedesco, M.: Snowmelt detection over the Greenland ice sheet from SSM/I brightness temperature daily variations, Geophys. Res. Lett., 34, L02504, https://doi.org/10.1029/2006gl028466, 2007. a
Tedesco, M.: Assessment and development of snowmelt retrieval algorithms over Antarctica from K-band spaceborne brightness temperature (1979–2008), Remote Sens. Environ., 113, 979–997, https://doi.org/10.1016/j.rse.2009.01.009, 2009. a
Tedesco, M. and Kim, E.: Retrieval of dry-snow parameters from microwave radiometric data using a dense-medium model and genetic algorithms, IEEE T. Geosci. Remote, 44, 2143–2151, https://doi.org/10.1109/tgrs.2006.872087, 2006. a
Trusel, L. D., Frey, K. E., and Das, S. B.: Antarctic surface melting dynamics: Enhanced perspectives from radar scatterometer data, J. Geophys. Res.-Earth, 117, F02023, https://doi.org/10.1029/2011jf002126, 2012. a, b
Ulaby, F., Siquera, P., Nashashibi, A., and Sarabandi, K.: Semi-empirical model for radar backscatter from snow at 35 and 95 GHz, IEEE T. Geosci. Remote, 34, 1059–1065, https://doi.org/10.1109/36.536521, 1996. a
Vafakhah, M., Nasiri Khiavi, A., Janizadeh, S., and Ganjkhanlo, H.: Evaluating different machine learning algorithms for snow water equivalent prediction, Earth Sci. Inform., 15, 2431–2445, https://doi.org/10.1007/s12145-022-00846-z, 2022. a, b
van den Broeke, M.: Depth and Density of the Antarctic Firn Layer, Arct. Antarct. Alp. Res., 40, 432–438, https://doi.org/10.1657/1523-0430(07-021)[broeke]2.0.co;2, 2008. a, b
van den Broeke, M. R., Winther, J.-G., 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. a
van Wessem, J. M., van de Berg, W. J., Noël, B. P. Y., van Meijgaard, E., Amory, C., Birnbaum, G., Jakobs, C. L., Krüger, K., Lenaerts, J. T. M., Lhermitte, S., Ligtenberg, S. R. M., Medley, B., Reijmer, C. H., van Tricht, K., Trusel, L. D., van Ulft, L. H., Wouters, B., Wuite, J., and van den Broeke, M. R.: Modelling the climate and surface mass balance of polar ice sheets using RACMO2 – Part 2: Antarctica (1979–2016), The Cryosphere, 12, 1479–1498, https://doi.org/10.5194/tc-12-1479-2018, 2018. a
Veldhuijsen, S. B. M., van de Berg, W. J., Brils, M., Kuipers Munneke, P., and van den Broeke, M. R.: Characteristics of the 1979–2020 Antarctic firn layer simulated with IMAU-FDM v1.2A, The Cryosphere, 17, 1675–1696, https://doi.org/10.5194/tc-17-1675-2023, 2023. a, b, c, d
Verjans, V., Leeson, A. A., Nemeth, C., Stevens, C. M., Kuipers Munneke, P., Noël, B., and van Wessem, J. M.: Bayesian calibration of firn densification models, The Cryosphere, 14, 3017–3032, https://doi.org/10.5194/tc-14-3017-2020, 2020. a, b
Viallon-Galinier, L., Hagenmuller, P., and Eckert, N.: Combining modelled snowpack stability with machine learning to predict avalanche activity, The Cryosphere, 17, 2245–2260, https://doi.org/10.5194/tc-17-2245-2023, 2023. a
Ward, Jr., J. H.: Hierarchical Grouping to Optimize an Objective Function, J. Am. Stat. Assoc., 58, 236–244, https://doi.org/10.1080/01621459.1963.10500845, 1963. a
Zwally, H. J., Giovinetto, M. B., Li, J., Cornejo, H. G., Beckley, M. A., Brenner, A. C., Saba, J. L., and Yi, D.: Mass changes of the Greenland and Antarctic ice sheets and shelves and contributions to sea-level rise: 1992–2002, J. Glaciol., 51, 509–527, https://doi.org/10.3189/172756505781829007, 2005. a
Short summary
This study used a machine learning approach to estimate the densities over the Antarctic Ice Sheet, particularly in the areas where the snow is usually dry. The motivation is to establish a link between satellite parameters to snow densities, as measurements are difficult for people to take on site. It provides valuable insights into the complexities of the relationship between satellite parameters and firn density and provides potential for further studies.
This study used a machine learning approach to estimate the densities over the Antarctic Ice...