Articles | Volume 11, issue 3
https://doi.org/10.5194/tc-11-1247-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/tc-11-1247-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
24 May 2017
Research article |
| 24 May 2017
Self-affine subglacial roughness: consequences for radar scattering and basal water discrimination in northern Greenland
Bristol Glaciology Centre, School of Geographical Sciences, University of Bristol, Bristol, UK
Michael A. Cooper
Bristol Glaciology Centre, School of Geographical Sciences, University of Bristol, Bristol, UK
Dustin M. Schroeder
Department of Geophysics, Stanford University, Stanford, California, USA
Christopher N. Williams
Bristol Glaciology Centre, School of Geographical Sciences, University of Bristol, Bristol, UK
John D. Paden
Center for Remote Sensing of Ice Sheets, University of Kansas, Lawrence, Kansas, USA
Martin J. Siegert
Grantham Institute and Department of Earth Science and Engineering, Imperial College, London, UK
Jonathan L. Bamber
Bristol Glaciology Centre, School of Geographical Sciences, University of Bristol, Bristol, UK
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Julie Z. Miller, Riley Culberg, David G. Long, Christopher A. Shuman, Dustin M. Schroeder, and Mary J. Brodzik
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Fanny Lehmann, Bramha Dutt Vishwakarma, and Jonathan Bamber
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Marie G. P. Cavitte, Duncan A. Young, Robert Mulvaney, Catherine Ritz, Jamin S. Greenbaum, Gregory Ng, Scott D. Kempf, Enrica Quartini, Gail R. Muldoon, John Paden, Massimo Frezzotti, Jason L. Roberts, Carly R. Tozer, Dustin M. Schroeder, and Donald D. Blankenship
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Tun Jan Young, Carlos Martín, Poul Christoffersen, Dustin M. Schroeder, Slawek M. Tulaczyk, and Eliza J. Dawson
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Joseph A. MacGregor, Michael Studinger, Emily Arnold, Carlton J. Leuschen, Fernando Rodríguez-Morales, and John D. Paden
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Tian Li, Geoffrey J. Dawson, Stephen J. Chuter, and Jonathan L. Bamber
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Tom A. Jordan, David Porter, Kirsty Tinto, Romain Millan, Atsuhiro Muto, Kelly Hogan, Robert D. Larter, Alastair G. C. Graham, and John D. Paden
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Neil Ross, Hugh Corr, and Martin Siegert
The Cryosphere, 14, 2103–2114, https://doi.org/10.5194/tc-14-2103-2020, https://doi.org/10.5194/tc-14-2103-2020, 2020
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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
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Marco Meloni, Jerome Bouffard, Tommaso Parrinello, Geoffrey Dawson, Florent Garnier, Veit Helm, Alessandro Di Bella, Stefan Hendricks, Robert Ricker, Erica Webb, Ben Wright, Karina Nielsen, Sanggyun Lee, Marcello Passaro, Michele Scagliola, Sebastian Bjerregaard Simonsen, Louise Sandberg Sørensen, David Brockley, Steven Baker, Sara Fleury, Jonathan Bamber, Luca Maestri, Henriette Skourup, René Forsberg, and Loretta Mizzi
The Cryosphere, 14, 1889–1907, https://doi.org/10.5194/tc-14-1889-2020, https://doi.org/10.5194/tc-14-1889-2020, 2020
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Michael A. Cooper, Thomas M. Jordan, Dustin M. Schroeder, Martin J. Siegert, Christopher N. Williams, and Jonathan L. Bamber
The Cryosphere, 13, 3093–3115, https://doi.org/10.5194/tc-13-3093-2019, https://doi.org/10.5194/tc-13-3093-2019, 2019
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The Cryosphere, 12, 2831–2854, https://doi.org/10.5194/tc-12-2831-2018, https://doi.org/10.5194/tc-12-2831-2018, 2018
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Here, via analysis of radio-echo sounding data, we place a new observational constraint upon the basal water distribution beneath the Greenland Ice Sheet. In addition to the outlet glaciers, we demonstrate widespread water storage in the northern and eastern ice-sheet interior, a notable feature being a "corridor" of basal water extending from NorthGRIP to Petermann Glacier. The basal water distribution and its relationship with basal temperature provides a new constraint for numerical models.
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
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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.
Hafeez Jeofry, Neil Ross, Hugh F. J. Corr, Jilu Li, Mathieu Morlighem, Prasad Gogineni, and Martin J. Siegert
Earth Syst. Sci. Data, 10, 711–725, https://doi.org/10.5194/essd-10-711-2018, https://doi.org/10.5194/essd-10-711-2018, 2018
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Accurately characterizing the complexities of the ice-sheet dynamic specifically close to the grounding line across the Weddell Sea (WS) sector in the ice-sheet models provides challenges to the scientific community. Our main objective is to comprehend these complexities, adding accuracy to the projection of future ice-sheet dynamics. Therefore, we have developed a new bed elevation digital elevation model across the WS sector, which will be of value to ice-sheet modelling experiments.
Ingo Sasgen, Alba Martín-Español, Alexander Horvath, Volker Klemann, Elizabeth J. Petrie, Bert Wouters, Martin Horwath, Roland Pail, Jonathan L. Bamber, Peter J. Clarke, Hannes Konrad, Terry Wilson, and Mark R. Drinkwater
Earth Syst. Sci. Data, 10, 493–523, https://doi.org/10.5194/essd-10-493-2018, https://doi.org/10.5194/essd-10-493-2018, 2018
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We present a collection of data sets, consisting of surface-elevation rates for Antarctic ice sheet from a combination of Envisat and ICESat, bedrock uplift rates for 118 GPS sites in Antarctica, and optimally filtered GRACE gravity field rates. We provide viscoelastic response functions to a disc load forcing for Earth structures present in East and West Antarctica. This data collection enables a joint inversion for present-day ice-mass changes and glacial isostatic adjustment in Antarctica.
Ron Kwok, Nathan T. Kurtz, Ludovic Brucker, Alvaro Ivanoff, Thomas Newman, Sinead L. Farrell, Joshua King, Stephen Howell, Melinda A. Webster, John Paden, Carl Leuschen, Joseph A. MacGregor, Jacqueline Richter-Menge, Jeremy Harbeck, and Mark Tschudi
The Cryosphere, 11, 2571–2593, https://doi.org/10.5194/tc-11-2571-2017, https://doi.org/10.5194/tc-11-2571-2017, 2017
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Since 2009, the ultra-wideband snow radar on Operation IceBridge has acquired data in annual campaigns conducted during the Arctic and Antarctic springs. Existing snow depth retrieval algorithms differ in the way the air–snow and snow–ice interfaces are detected and localized in the radar returns and in how the system limitations are addressed. Here, we assess five retrieval algorithms by comparisons with field measurements, ground-based campaigns, and analyzed fields of snow depth.
Andrew J. Tedstone, Jonathan L. Bamber, Joseph M. Cook, Christopher J. Williamson, Xavier Fettweis, Andrew J. Hodson, and Martyn Tranter
The Cryosphere, 11, 2491–2506, https://doi.org/10.5194/tc-11-2491-2017, https://doi.org/10.5194/tc-11-2491-2017, 2017
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The bare ice albedo of the south-west Greenland ice sheet varies dramatically between years. The reasons are unclear but likely involve darkening by inorganic particulates, cryoconite and ice algae. We use satellite imagery to examine dark ice dynamics and climate model outputs to find likely climatological controls. Outcropping particulates can explain the spatial extent of dark ice, but the darkening itself is likely due to ice algae growth controlled by meltwater and light availability.
Frédéric Parrenin, Marie G. P. Cavitte, Donald D. Blankenship, Jérôme Chappellaz, Hubertus Fischer, Olivier Gagliardini, Valérie Masson-Delmotte, Olivier Passalacqua, Catherine Ritz, Jason Roberts, Martin J. Siegert, and Duncan A. Young
The Cryosphere, 11, 2427–2437, https://doi.org/10.5194/tc-11-2427-2017, https://doi.org/10.5194/tc-11-2427-2017, 2017
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The oldest dated deep ice core drilled in Antarctica has been retrieved at EPICA Dome C (EDC), reaching ~ 800 000 years. Obtaining an older palaeoclimatic record from Antarctica is one of the greatest challenges of the ice core community. Here, we estimate the age of basal ice in the Dome C area. We find that old ice (> 1.5 Myr) likely exists in two regions a few tens of kilometres away from EDC:
Little Dome C Patchand
North Patch.
Felicity S. Graham, Jason L. Roberts, Ben K. Galton-Fenzi, Duncan Young, Donald Blankenship, and Martin J. Siegert
Earth Syst. Sci. Data, 9, 267–279, https://doi.org/10.5194/essd-9-267-2017, https://doi.org/10.5194/essd-9-267-2017, 2017
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Antarctic bed topography datasets are interpolated onto low-resolution grids because our observed topography data are sparsely sampled. This has implications for ice-sheet model simulations, especially in regions prone to instability, such as grounding lines, where detailed knowledge of the topography is required. Here, we constructed a high-resolution synthetic bed elevation dataset using observed covariance properties to assess the dependence of simulated ice-sheet dynamics on grid resolution.
Anna Winter, Daniel Steinhage, Emily J. Arnold, Donald D. Blankenship, Marie G. P. Cavitte, Hugh F. J. Corr, John D. Paden, Stefano Urbini, Duncan A. Young, and Olaf Eisen
The Cryosphere, 11, 653–668, https://doi.org/10.5194/tc-11-653-2017, https://doi.org/10.5194/tc-11-653-2017, 2017
Christopher N. Williams, Stephen L. Cornford, Thomas M. Jordan, Julian A. Dowdeswell, Martin J. Siegert, Christopher D. Clark, Darrel A. Swift, Andrew Sole, Ian Fenty, and Jonathan L. Bamber
The Cryosphere, 11, 363–380, https://doi.org/10.5194/tc-11-363-2017, https://doi.org/10.5194/tc-11-363-2017, 2017
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Knowledge of ice sheet bed topography and surrounding sea floor bathymetry is integral to the understanding of ice sheet processes. Existing elevation data products for Greenland underestimate fjord bathymetry due to sparse data availability. We present a new method to create physically based synthetic fjord bathymetry to fill these gaps, greatly improving on previously available datasets. This will assist in future elevation product development until further observations become available.
Lora S. Koenig, Alvaro Ivanoff, Patrick M. Alexander, Joseph A. MacGregor, Xavier Fettweis, Ben Panzer, John D. Paden, Richard R. Forster, Indrani Das, Joesph R. McConnell, Marco Tedesco, Carl Leuschen, and Prasad Gogineni
The Cryosphere, 10, 1739–1752, https://doi.org/10.5194/tc-10-1739-2016, https://doi.org/10.5194/tc-10-1739-2016, 2016
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Contemporary climate warming over the Arctic is accelerating mass loss from the Greenland Ice Sheet through increasing surface melt, emphasizing the need to closely monitor surface mass balance in order to improve sea-level rise predictions. Here, we quantify the net annual accumulation over the Greenland Ice Sheet, which comprises the largest component of surface mass balance, at a higher spatial resolution than currently available using high-resolution, airborne-radar data.
T. M. Jordan, J. L. Bamber, C. N. Williams, J. D. Paden, M. J. Siegert, P. Huybrechts, O. Gagliardini, and F. Gillet-Chaulet
The Cryosphere, 10, 1547–1570, https://doi.org/10.5194/tc-10-1547-2016, https://doi.org/10.5194/tc-10-1547-2016, 2016
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Ice penetrating radar enables determination of the basal properties of ice sheets. Existing algorithms assume stationarity in the attenuation rate, which is not justifiable at an ice sheet scale. We introduce the first ice-sheet-wide algorithm for radar attenuation that incorporates spatial variability, using the temperature field from a numerical model as an initial guess. The study is a step toward ice-sheet-wide data products for basal properties and evaluation of model temperature fields.
Ioana S. Muresan, Shfaqat A. Khan, Andy Aschwanden, Constantine Khroulev, Tonie Van Dam, Jonathan Bamber, Michiel R. van den Broeke, Bert Wouters, Peter Kuipers Munneke, and Kurt H. Kjær
The Cryosphere, 10, 597–611, https://doi.org/10.5194/tc-10-597-2016, https://doi.org/10.5194/tc-10-597-2016, 2016
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We use a regional 3-D outlet glacier model to simulate the behaviour of Jakobshavn Isbræ (JI) during 1990–2014. The model simulates two major accelerations in 1998 and 2003 that are consistent with observations. We find that most of the JI retreat during the simulated period is driven by the ocean parametrization used, and the glacier's subsequent response, which is largely governed by bed geometry. The study shows progress in modelling the temporal variability of the flow at JI.
Tessa R. Vance, Jason L. Roberts, Andrew D. Moy, Mark A. J. Curran, Carly R. Tozer, Ailie J. E. Gallant, Nerilie J. Abram, Tas D. van Ommen, Duncan A. Young, Cyril Grima, Don D. Blankenship, and Martin J. Siegert
Clim. Past, 12, 595–610, https://doi.org/10.5194/cp-12-595-2016, https://doi.org/10.5194/cp-12-595-2016, 2016
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This study details a systematic approach to finding a new high-resolution East Antarctic ice core site. The study initially outlines seven criteria that a new site must fulfil, encompassing specific accumulation, ice dynamics and atmospheric circulation aspects. We then use numerous techniques including Antarctic surface mass balance syntheses, ground-truthing of satellite data by airborne radar surveys and reanalysis products to pinpoint promising regions.
L. S. Koenig, D. J. Lampkin, L. N. Montgomery, S. L. Hamilton, J. B. Turrin, C. A. Joseph, S. E. Moutsafa, B. Panzer, K. A. Casey, J. D. Paden, C. Leuschen, and P. Gogineni
The Cryosphere, 9, 1333–1342, https://doi.org/10.5194/tc-9-1333-2015, https://doi.org/10.5194/tc-9-1333-2015, 2015
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The Greenland Ice Sheet is storing meltwater through the winter season just below its surface in buried supraglacial lakes. Airborne radar from Operation IceBridge between 2009 and 2012 was used to detect buried lakes, distributed extensively around the margin of the ice sheet. The volume of retained water in the buried lakes is likely insignificant compared to the total mass loss from the ice sheet but has important implications for ice temperatures.
P. R. Holland, A. Brisbourne, H. F. J. Corr, D. McGrath, K. Purdon, J. Paden, H. A. Fricker, F. S. Paolo, and A. H. Fleming
The Cryosphere, 9, 1005–1024, https://doi.org/10.5194/tc-9-1005-2015, https://doi.org/10.5194/tc-9-1005-2015, 2015
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Antarctic Peninsula ice shelves have collapsed in recent decades. The surface of Larsen C Ice Shelf is lowering, but the cause of this has not been understood. This study uses eight radar surveys to show that the lowering is caused by both ice loss and a loss of air from the ice shelf's snowpack. At least two different processes are causing the lowering. The stability of Larsen C may be at risk from an ungrounding of Bawden Ice Rise or ice-front retreat past a 'compressive arch' in strain rates.
N. Schoen, A. Zammit-Mangion, J. C. Rougier, T. Flament, F. Rémy, S. Luthcke, and J. L. Bamber
The Cryosphere, 9, 805–819, https://doi.org/10.5194/tc-9-805-2015, https://doi.org/10.5194/tc-9-805-2015, 2015
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This paper provides a proof of concept approach for combining multiple observations and inferences to provide rigorous, error-bounded estimates of mass trends and surface processes for the Antarctic ice sheet. Here we apply the method to West Antarctica, using a time-invariant solution by way of proof of concept. Subsequent work will utilise a time evolving approach to the whole ice sheet.
K. C. Rose, N. Ross, T. A. Jordan, R. G. Bingham, H. F. J. Corr, F. Ferraccioli, A. M. Le Brocq, D. M. Rippin, and M. J. Siegert
Earth Surf. Dynam., 3, 139–152, https://doi.org/10.5194/esurf-3-139-2015, https://doi.org/10.5194/esurf-3-139-2015, 2015
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We use ice-penetrating-radar data to identify a laterally continuous, gently sloping topographic block, comprising two surfaces separated by a distinct break in slope, preserved beneath the Institute and Möller ice streams, West Antarctica. We interpret these features as extensive erosion surfaces, showing that ancient (pre-glacial) surfaces can be preserved at low elevations beneath ice sheets. Different erosion regimes (e.g. fluvial and marine) may have formed these surfaces.
R. T. W. L. Hurkmans, J. L. Bamber, C. H. Davis, I. R. Joughin, K. S. Khvorostovsky, B. S. Smith, and N. Schoen
The Cryosphere, 8, 1725–1740, https://doi.org/10.5194/tc-8-1725-2014, https://doi.org/10.5194/tc-8-1725-2014, 2014
T. Howard, A. K. Pardaens, J. L. Bamber, J. Ridley, G. Spada, R. T. W. L. Hurkmans, J. A. Lowe, and D. Vaughan
Ocean Sci., 10, 473–483, https://doi.org/10.5194/os-10-473-2014, https://doi.org/10.5194/os-10-473-2014, 2014
T. Howard, J. Ridley, A. K. Pardaens, R. T. W. L. Hurkmans, A. J. Payne, R. H. Giesen, J. A. Lowe, J. L. Bamber, T. L. Edwards, and J. Oerlemans
Ocean Sci., 10, 485–500, https://doi.org/10.5194/os-10-485-2014, https://doi.org/10.5194/os-10-485-2014, 2014
I. Sasgen, H. Konrad, E. R. Ivins, M. R. Van den Broeke, J. L. Bamber, Z. Martinec, and V. Klemann
The Cryosphere, 7, 1499–1512, https://doi.org/10.5194/tc-7-1499-2013, https://doi.org/10.5194/tc-7-1499-2013, 2013
I. Joughin, S. B. Das, G. E. Flowers, M. D. Behn, R. B. Alley, M. A. King, B. E. Smith, J. L. Bamber, M. R. van den Broeke, and J. H. van Angelen
The Cryosphere, 7, 1185–1192, https://doi.org/10.5194/tc-7-1185-2013, https://doi.org/10.5194/tc-7-1185-2013, 2013
C. L. Vernon, J. L. Bamber, J. E. Box, M. R. van den Broeke, X. Fettweis, E. Hanna, and P. Huybrechts
The Cryosphere, 7, 599–614, https://doi.org/10.5194/tc-7-599-2013, https://doi.org/10.5194/tc-7-599-2013, 2013
J. L. Bamber, J. A. Griggs, R. T. W. L. Hurkmans, J. A. Dowdeswell, S. P. Gogineni, I. Howat, J. Mouginot, J. Paden, S. Palmer, E. Rignot, and D. Steinhage
The Cryosphere, 7, 499–510, https://doi.org/10.5194/tc-7-499-2013, https://doi.org/10.5194/tc-7-499-2013, 2013
P. Fretwell, H. D. Pritchard, D. G. Vaughan, J. L. Bamber, N. E. Barrand, R. Bell, C. Bianchi, R. G. Bingham, D. D. Blankenship, G. Casassa, G. Catania, D. Callens, H. Conway, A. J. Cook, H. F. J. Corr, D. Damaske, V. Damm, F. Ferraccioli, R. Forsberg, S. Fujita, Y. Gim, P. Gogineni, J. A. Griggs, R. C. A. Hindmarsh, P. Holmlund, J. W. Holt, R. W. Jacobel, A. Jenkins, W. Jokat, T. Jordan, E. C. King, J. Kohler, W. Krabill, M. Riger-Kusk, K. A. Langley, G. Leitchenkov, C. Leuschen, B. P. Luyendyk, K. Matsuoka, J. Mouginot, F. O. Nitsche, Y. Nogi, O. A. Nost, S. V. Popov, E. Rignot, D. M. Rippin, A. Rivera, J. Roberts, N. Ross, M. J. Siegert, A. M. Smith, D. Steinhage, M. Studinger, B. Sun, B. K. Tinto, B. C. Welch, D. Wilson, D. A. Young, C. Xiangbin, and A. Zirizzotti
The Cryosphere, 7, 375–393, https://doi.org/10.5194/tc-7-375-2013, https://doi.org/10.5194/tc-7-375-2013, 2013
M. G. P. Cavitte, D. D. Blankenship, D. A. Young, M. J. Siegert, and E. Le Meur
The Cryosphere Discuss., https://doi.org/10.5194/tcd-7-321-2013, https://doi.org/10.5194/tcd-7-321-2013, 2013
Revised manuscript not accepted
Related subject area
Remote Sensing
Observing glacier elevation changes from spaceborne optical and radar sensors – an inter-comparison experiment using ASTER and TanDEM-X data
Tower-based C-band radar measurements of an alpine snowpack
A study of sea ice topography in the Weddell and Ross seas using dual-polarimetric TanDEM-X imagery
Estimating differential penetration of green (532 nm) laser light over sea ice with NASA's Airborne Topographic Mapper: observations and models
Mapping surface hoar from near-infrared texture in a laboratory
Sentinel-1 detection of ice slabs on the Greenland Ice Sheet
Estimating the uncertainty of sea-ice area and sea-ice extent from satellite retrievals
Thermal infrared shadow-hiding in GOES-R ABI imagery: snow and forest temperature observations from the SnowEx 2020 Grand Mesa field campaign
Sea ice transport and replenishment across and within the Canadian Arctic Archipelago, 2016–2022
SAR deep learning sea ice retrieval trained with airborne laser scanner measurements from the MOSAiC expedition
Lake ice break-up in Greenland: timing and spatiotemporal variability
Temperature-dominated spatiotemporal variability in snow phenology on the Tibetan Plateau from 2002 to 2022
MMSeaIce: a collection of techniques for improving sea ice mapping with a multi-task model
Snow water equivalent retrieved from X- and dual Ku-band scatterometer measurements at Sodankylä using the Markov Chain Monte Carlo method
Lead fractions from SAR-derived sea ice divergence during MOSAiC
Retrieval of airborne Ku-Band SAR Using Forward Radiative Transfer Modeling to Estimate Snow Water Equivalent: The Trail Valley Creek 2018/19 Snow Experiment
Assessing the sea ice microwave emissivity up to submillimeter waves from airborne and satellite observations
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Snow water equivalent retrieval over Idaho – Part 1: Using Sentinel-1 repeat-pass interferometry
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Livia Piermattei, Michael Zemp, Christian Sommer, Fanny Brun, Matthias H. Braun, Liss M. Andreassen, Joaquín M. C. Belart, Etienne Berthier, Atanu Bhattacharya, Laura Boehm Vock, Tobias Bolch, Amaury Dehecq, Inés Dussaillant, Daniel Falaschi, Caitlyn Florentine, Dana Floricioiu, Christian Ginzler, Gregoire Guillet, Romain Hugonnet, Matthias Huss, Andreas Kääb, Owen King, Christoph Klug, Friedrich Knuth, Lukas Krieger, Jeff La Frenierre, Robert McNabb, Christopher McNeil, Rainer Prinz, Louis Sass, Thorsten Seehaus, David Shean, Désirée Treichler, Anja Wendt, and Ruitang Yang
The Cryosphere, 18, 3195–3230, https://doi.org/10.5194/tc-18-3195-2024, https://doi.org/10.5194/tc-18-3195-2024, 2024
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Satellites have made it possible to observe glacier elevation changes from all around the world. In the present study, we compared the results produced from two different types of satellite data between different research groups and against validation measurements from aeroplanes. We found a large spread between individual results but showed that the group ensemble can be used to reliably estimate glacier elevation changes and related errors from satellite data.
Isis Brangers, Hans-Peter Marshall, Gabrielle De Lannoy, Devon Dunmire, Christian Mätzler, and Hans Lievens
The Cryosphere, 18, 3177–3193, https://doi.org/10.5194/tc-18-3177-2024, https://doi.org/10.5194/tc-18-3177-2024, 2024
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To better understand the interactions between C-band radar waves and snow, a tower-based experiment was set up in the Idaho Rocky Mountains. The reflections were collected in the time domain to measure the backscatter profile from the various snowpack and ground surface layers. The results demonstrate that C-band radar is sensitive to seasonal patterns in snow accumulation but that changes in microstructure, stratigraphy and snow wetness may complicate satellite-based snow depth retrievals.
Lanqing Huang and Irena Hajnsek
The Cryosphere, 18, 3117–3140, https://doi.org/10.5194/tc-18-3117-2024, https://doi.org/10.5194/tc-18-3117-2024, 2024
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Interferometric synthetic aperture radar can measure the total freeboard of sea ice but can be biased when radar signals penetrate snow and ice. We develop a new method to retrieve the total freeboard and analyze the regional variation of total freeboard and roughness in the Weddell and Ross seas. We also investigate the statistical behavior of the total freeboard for diverse ice types. The findings enhance the understanding of Antarctic sea ice topography and its dynamics in a changing climate.
Michael Studinger, Benjamin E. Smith, Nathan Kurtz, Alek Petty, Tyler Sutterley, and Rachel Tilling
The Cryosphere, 18, 2625–2652, https://doi.org/10.5194/tc-18-2625-2024, https://doi.org/10.5194/tc-18-2625-2024, 2024
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We use green lidar data and natural-color imagery over sea ice to quantify elevation biases potentially impacting estimates of change in ice thickness of the polar regions. We complement our analysis using a model of scattering of light in snow and ice that predicts the shape of lidar waveforms reflecting from snow and ice surfaces based on the shape of the transmitted pulse. We find that biased elevations exist in airborne and spaceborne data products from green lidars.
James Dillon, Christopher Donahue, Evan Schehrer, Karl Birkeland, and Kevin Hammonds
The Cryosphere, 18, 2557–2582, https://doi.org/10.5194/tc-18-2557-2024, https://doi.org/10.5194/tc-18-2557-2024, 2024
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Surface hoar crystals are snow grains that form when vapor deposits on a snow surface. They create a weak layer in the snowpack that can cause large avalanches to occur. Thus, determining when and where surface hoar forms is a lifesaving matter. Here, we developed a means of mapping surface hoar using remote-sensing technologies. We found that surface hoar displayed heightened texture, hence the variability of brightness. Using this, we created surface hoar maps with an accuracy upwards of 95 %.
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
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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.
Andreas Wernecke, Dirk Notz, Stefan Kern, and Thomas Lavergne
The Cryosphere, 18, 2473–2486, https://doi.org/10.5194/tc-18-2473-2024, https://doi.org/10.5194/tc-18-2473-2024, 2024
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The total Arctic sea-ice area (SIA), which is an important climate indicator, is routinely monitored with the help of satellite measurements. Uncertainties in observations of sea-ice concentration (SIC) partly cancel out when summed up to the total SIA, but the degree to which this is happening has been unclear. Here we find that the uncertainty daily SIA estimates, based on uncertainties in SIC, are about 300 000 km2. The 2002 to 2017 September decline in SIA is approx. 105 000 ± 9000 km2 a−1.
Steven J. Pestana, C. Chris Chickadel, and Jessica D. Lundquist
The Cryosphere, 18, 2257–2276, https://doi.org/10.5194/tc-18-2257-2024, https://doi.org/10.5194/tc-18-2257-2024, 2024
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We compared infrared images taken by GOES-R satellites of an area with snow and forests against surface temperature measurements taken on the ground, from an aircraft, and by another satellite. We found that GOES-R measured warmer temperatures than the other measurements, especially in areas with more forest and when the Sun was behind the satellite. From this work, we learned that the position of the Sun and surface features such as trees that can cast shadows impact GOES-R infrared images.
Stephen E. L. Howell, David G. Babb, Jack C. Landy, Isolde A. Glissenaar, Kaitlin McNeil, Benoit Montpetit, and Mike Brady
The Cryosphere, 18, 2321–2333, https://doi.org/10.5194/tc-18-2321-2024, https://doi.org/10.5194/tc-18-2321-2024, 2024
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The CAA serves as both a source and a sink for sea ice from the Arctic Ocean, while also exporting sea ice into Baffin Bay. It is also an important region with respect to navigating the Northwest Passage. Here, we quantify sea ice transport and replenishment across and within the CAA from 2016 to 2022. We also provide the first estimates of the ice area and volume flux within the CAA from the Queen Elizabeth Islands to Parry Channel, which spans the central region of the Northwest Passage.
Karl Kortum, Suman Singha, Gunnar Spreen, Nils Hutter, Arttu Jutila, and Christian Haas
The Cryosphere, 18, 2207–2222, https://doi.org/10.5194/tc-18-2207-2024, https://doi.org/10.5194/tc-18-2207-2024, 2024
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A dataset of 20 radar satellite acquisitions and near-simultaneous helicopter-based surveys of the ice topography during the MOSAiC expedition is constructed and used to train a variety of deep learning algorithms. The results give realistic insights into the accuracy of retrieval of measured ice classes using modern deep learning models. The models able to learn from the spatial distribution of the measured sea ice classes are shown to have a clear advantage over those that cannot.
Christoph Posch, Jakob Abermann, and Tiago Silva
The Cryosphere, 18, 2035–2059, https://doi.org/10.5194/tc-18-2035-2024, https://doi.org/10.5194/tc-18-2035-2024, 2024
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Radar beams from satellites exhibit reflection differences between water and ice. This condition, as well as the comprehensive coverage and high temporal resolution of the Sentinel-1 satellites, allows automatically detecting the timing of when ice cover of lakes in Greenland disappear. We found that lake ice breaks up 3 d later per 100 m elevation gain and that the average break-up timing varies by ±8 d in 2017–2021, which has major implications for the energy budget of the lakes.
Jiahui Xu, Yao Tang, Linxin Dong, Shujie Wang, Bailang Yu, Jianping Wu, Zhaojun Zheng, and Yan Huang
The Cryosphere, 18, 1817–1834, https://doi.org/10.5194/tc-18-1817-2024, https://doi.org/10.5194/tc-18-1817-2024, 2024
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Understanding snow phenology (SP) and its possible feedback are important. We reveal spatiotemporal heterogeneous SP on the Tibetan Plateau (TP) and the mediating effects from meteorological, topographic, and environmental factors on it. The direct effects of meteorology on SP are much greater than the indirect effects. Topography indirectly effects SP, while vegetation directly effects SP. This study contributes to understanding past global warming and predicting future trends on the TP.
Xinwei Chen, Muhammed Patel, Fernando J. Pena Cantu, Jinman Park, Javier Noa Turnes, Linlin Xu, K. Andrea Scott, and David A. Clausi
The Cryosphere, 18, 1621–1632, https://doi.org/10.5194/tc-18-1621-2024, https://doi.org/10.5194/tc-18-1621-2024, 2024
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This paper introduces an automated sea ice mapping pipeline utilizing a multi-task U-Net architecture. It attained the top score of 86.3 % in the AutoICE challenge. Ablation studies revealed that incorporating brightness temperature data and spatial–temporal information significantly enhanced model accuracy. Accurate sea ice mapping is vital for comprehending the Arctic environment and its global climate effects, underscoring the potential of deep learning.
Jinmei Pan, Michael Durand, Juha Lemmetyinen, Desheng Liu, and Jiancheng Shi
The Cryosphere, 18, 1561–1578, https://doi.org/10.5194/tc-18-1561-2024, https://doi.org/10.5194/tc-18-1561-2024, 2024
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We developed an algorithm to estimate snow mass using X- and dual Ku-band radar, and tested it in a ground-based experiment. The algorithm, the Bayesian-based Algorithm for SWE Estimation (BASE) using active microwaves, achieved an RMSE of 30 mm for snow water equivalent. These results demonstrate the potential of radar, a highly promising sensor, to map snow mass at high spatial resolution.
Luisa von Albedyll, Stefan Hendricks, Nils Hutter, Dmitrii Murashkin, Lars Kaleschke, Sascha Willmes, Linda Thielke, Xiangshan Tian-Kunze, Gunnar Spreen, and Christian Haas
The Cryosphere, 18, 1259–1285, https://doi.org/10.5194/tc-18-1259-2024, https://doi.org/10.5194/tc-18-1259-2024, 2024
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Leads (openings in sea ice cover) are created by sea ice dynamics. Because they are important for many processes in the Arctic winter climate, we aim to detect them with satellites. We present two new techniques to detect lead widths of a few hundred meters at high spatial resolution (700 m) and independent of clouds or sun illumination. We use the MOSAiC drift 2019–2020 in the Arctic for our case study and compare our new products to other existing lead products.
Benoit Montpetit, Joshua King, Julien Meloche, Chris Derksen, Paul Siqueira, J. Max Adam, Peter Toose, Mike Brady, Anna Wendleder, Vincent Vionnet, and Nicolas R. Leroux
EGUsphere, https://doi.org/10.5194/egusphere-2024-651, https://doi.org/10.5194/egusphere-2024-651, 2024
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This paper validates the use of free open-source models to link distributed snow measurements to radar measurements in the Canadian Arctic. Using multiple radar sensors, we can decouple the soil from the snow contribution. We then retrieve the "microwave snow grain size" to characterize the interaction between the snow mass and the radar signal. This work supports future satellite mission development to retrieve snow mass information such as the future Canadian Terrestrial Snow Mass Mission.
Nils Risse, Mario Mech, Catherine Prigent, Gunnar Spreen, and Susanne Crewell
EGUsphere, https://doi.org/10.5194/egusphere-2024-179, https://doi.org/10.5194/egusphere-2024-179, 2024
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Satellite passive microwave observations are crucial for monitoring the Arctic's sea ice and atmosphere. To do this effectively, it's important to understand how sea ice emits microwaves. Through unique Arctic sea ice observations, we've improved our understanding, identifying four distinct emission types and expanding current knowledge towards higher frequencies. These findings will enhance our ability to monitor the Arctic climate and provide valuable information for new satellite missions.
Jukes Liu, Madeline Gendreau, Ellyn Mary Enderlin, and Rainey Aberle
EGUsphere, https://doi.org/10.5194/egusphere-2024-374, https://doi.org/10.5194/egusphere-2024-374, 2024
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There are sometimes gaps in global glacier velocity records produced using satellite image feature-tracking algorithms during times of rapid glacier acceleration, which hinders the study of glacier flow processes. We present an open-source pipeline for customizing the feature-tracking parameters and for including images from an additional source. We applied it to 5 glaciers and found that it produced accurate velocity data that supplemented their velocity records during rapid acceleration.
Siddharth Singh, Michael Durand, Edward Kim, and Ana P. Barros
The Cryosphere, 18, 747–773, https://doi.org/10.5194/tc-18-747-2024, https://doi.org/10.5194/tc-18-747-2024, 2024
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Seasonal snowfall accumulation plays a critical role in climate. The water stored in it is measured by the snow water equivalent (SWE), the amount of water released after completely melting. We demonstrate a Bayesian physical–statistical framework to estimate SWE from airborne X- and Ku-band synthetic aperture radar backscatter measurements constrained by physical snow hydrology and radar models. We explored spatial resolutions and vertical structures that agree well with ground observations.
Jérôme Messmer and Alexander Raphael Groos
The Cryosphere, 18, 719–746, https://doi.org/10.5194/tc-18-719-2024, https://doi.org/10.5194/tc-18-719-2024, 2024
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The lower part of mountain glaciers is often covered with debris. Knowing the thickness of the debris is important as it influences the melting and future evolution of the affected glaciers. We have developed an open-source approach to map variations in debris thickness on glaciers using a low-cost drone equipped with a thermal infrared camera. The resulting high-resolution maps of debris surface temperature and thickness enable more accurate monitoring and modelling of debris-covered glaciers.
Shadi Oveisgharan, Robert Zinke, Zachary Hoppinen, and Hans Peter Marshall
The Cryosphere, 18, 559–574, https://doi.org/10.5194/tc-18-559-2024, https://doi.org/10.5194/tc-18-559-2024, 2024
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The seasonal snowpack provides water resources to billions of people worldwide. Large-scale mapping of snow water equivalent (SWE) with high resolution is critical for many scientific and economics fields. In this work we used the radar remote sensing interferometric synthetic aperture radar (InSAR) to estimate the SWE change between 2 d. The error in the estimated SWE change is less than 2 cm for in situ stations. Additionally, the retrieved SWE using InSAR is correlated with lidar snow depth.
Randall Bonnell, Daniel McGrath, Jack Tarricone, Hans-Peter Marshall, Ella Bump, Caroline Duncan, Stephanie Kampf, Yunling Lou, Alex Olsen-Mikitowicz, Megan Sears, Keith Williams, Lucas Zeller, and Yang Zheng
EGUsphere, https://doi.org/10.5194/egusphere-2024-236, https://doi.org/10.5194/egusphere-2024-236, 2024
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Snow provides water for billions of people, but the amount of snow is difficult to detect remotely. During the 2020 and 2021 winters, a radar was flown over mountains in Colorado, USA to measure the amount of snow on the ground, while our team collected ground observations to test the radar technique’s capabilities. The technique yielded accurate measurements of the snowpack that had good correlation with ground measurements, making it a promising application for the upcoming NISAR satellite.
Dhiraj Kumar Singh, Srinivasarao Tanniru, Kamal Kant Singh, Harendra Singh Negi, and RAAJ Ramsankaran
The Cryosphere, 18, 451–474, https://doi.org/10.5194/tc-18-451-2024, https://doi.org/10.5194/tc-18-451-2024, 2024
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In situ techniques for snow depth (SD) measurement are not adequate to represent the spatiotemporal variability in SD in the Western Himalayan region. Therefore, this study focuses on the high-resolution mapping of daily snow depth in the Indian Western Himalayan region using passive microwave remote-sensing-based algorithms. Overall, the proposed multifactor SD models demonstrated substantial improvement compared to the operational products. However, there is a scope for further improvement.
Yungang Cao, Rumeng Pan, Meng Pan, Ruodan Lei, Puying Du, and Xueqin Bai
The Cryosphere, 18, 153–168, https://doi.org/10.5194/tc-18-153-2024, https://doi.org/10.5194/tc-18-153-2024, 2024
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This study built a glacial lake dataset with 15376 samples in seven types and proposed an automatic method by two-stage (the semantic segmentation network and post-processing) optimizations to detect glacial lakes. The proposed method for glacial lake extraction has achieved the best results so far, in which the F1 score and IoU reached 0.945 and 0.907, respectively. The area of the minimum glacial lake that can be entirely and correctly extracted has been raised to the 100 m2 level.
Michael Durand, Joel T. Johnson, Jack Dechow, Leung Tsang, Firoz Borah, and Edward J. Kim
The Cryosphere, 18, 139–152, https://doi.org/10.5194/tc-18-139-2024, https://doi.org/10.5194/tc-18-139-2024, 2024
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Seasonal snow accumulates each winter, storing water to release later in the year and modulating both water and energy cycles, but the amount of seasonal snow is one of the most poorly measured components of the global water cycle. Satellite concepts to monitor snow accumulation have been proposed but not selected. This paper shows that snow accumulation can be measured using radar, and that (contrary to previous studies) does not require highly accurate information about snow microstructure.
Qin Zhang and Nick Hughes
The Cryosphere, 17, 5519–5537, https://doi.org/10.5194/tc-17-5519-2023, https://doi.org/10.5194/tc-17-5519-2023, 2023
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To alleviate tedious manual image annotations for training deep learning (DL) models in floe instance segmentation, we employ a classical image processing technique to automatically label floes in images. We then apply a DL semantic method for fast and adaptive floe instance segmentation from high-resolution airborne and satellite images. A post-processing algorithm is also proposed to refine the segmentation and further to derive acceptable floe size distributions at local and global scales.
Taha Sadeghi Chorsi, Franz J. Meyer, and Timothy H. Dixon
EGUsphere, https://doi.org/10.5194/egusphere-2023-2605, https://doi.org/10.5194/egusphere-2023-2605, 2023
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Active layer, the soil or sediment layer above permafrost, thaws and freezes seasonally. The annual freeze-thaw cycle of the active layer causes significant surface height change. We estimate subsidence rate and active layer thickness (ALT) for part of northern Alaska’s permafrost zone for summer 2017 to 2022 using satellite radar interferometry and LiDAR. ALT estimates range from ~20 cm to larger than 150 cm. Subsidence rate varies ranging from ~3–20 cm/year during the thaw season.
Daniel Falaschi, Atanu Bhattacharya, Gregoire Guillet, Lei Huang, Owen King, Kriti Mukherjee, Philipp Rastner, Tandong Yao, and Tobias Bolch
The Cryosphere, 17, 5435–5458, https://doi.org/10.5194/tc-17-5435-2023, https://doi.org/10.5194/tc-17-5435-2023, 2023
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Because glaciers are crucial freshwater sources in the lowlands surrounding High Mountain Asia, constraining short-term glacier mass changes is essential. We investigate the potential of state-of-the-art satellite elevation data to measure glacier mass changes in two selected regions. The results demonstrate the ability of our dataset to characterize glacier changes of different magnitudes, allowing for an increase in the number of inaccessible glaciers that can be readily monitored.
Jennika Hammar, Inge Grünberg, Steven V. Kokelj, Jurjen van der Sluijs, and Julia Boike
The Cryosphere, 17, 5357–5372, https://doi.org/10.5194/tc-17-5357-2023, https://doi.org/10.5194/tc-17-5357-2023, 2023
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Roads on permafrost have significant environmental effects. This study assessed the Inuvik to Tuktoyaktuk Highway (ITH) in Canada and its impact on snow accumulation, albedo and snowmelt timing. Our findings revealed that snow accumulation increased by up to 36 m from the road, 12-day earlier snowmelt within 100 m due to reduced albedo, and altered snowmelt patterns in seemingly undisturbed areas. Remote sensing aids in understanding road impacts on permafrost.
Tao Li, Yuanlin Hu, Bin Liu, Liming Jiang, Hansheng Wang, and Xiang Shen
The Cryosphere, 17, 5299–5316, https://doi.org/10.5194/tc-17-5299-2023, https://doi.org/10.5194/tc-17-5299-2023, 2023
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Raw DEMs are often misaligned with each other due to georeferencing errors, and a co-registration process is required before DEM differencing. We present a comparative analysis of the two classical DEM co-registration and three residual correction algorithms. The experimental results show that rotation and scale biases should be considered in DEM co-registration. The new non-parametric regression technique can eliminate the complex systematic errors, which existed in the co-registration results.
Andreas R. Stokholm, Jørgen Buus-Hinkler, Tore Wulf, Anton Korosov, Roberto Saldo, Leif T. Pedersen, David Arthurs, Ionut Dragan, Iacopo Modica, Juan Pedro, Annekatrien Debien, Xinwei Chen, Muhammed Patel, Fernando J. P. Cantu, Javier N. Turnes, Jinman Park, Linlin Xu, Andrea K. Scott, David A. Clausi, Yuan Fang, Mingzhe Jiang, Saeid Taleghanidoozdoozan, Neil C. Brubacher, Armina Soleymani, Zacharie Gousseau, Michał Smaczny, Patryk Kowalski, Jacek Komorowski, David Rijlaarsdam, Jan N. van Rijn, Jens Jakobsen, Martin S. J. Rogers, Nick Hughes, Tom Zagon, Rune Solberg, Nicolas Longépé, and Matilde B. Kreiner
EGUsphere, https://doi.org/10.5194/egusphere-2023-2648, https://doi.org/10.5194/egusphere-2023-2648, 2023
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The AutoICE challenge encouraged the development of deep learning models to map multiple aspects of sea ice – the amount of sea ice in an area, the age and ice floe size using multiple sources of satellite and weather data across the Canadian and Greenlandic Arctic. To judge the solution, professionally drawn operational sea ice charts were used as reference. 179 students and sea ice and AI specialists participated and produced maps in broad agreement with the sea ice charts.
Fabrizio Troilo, Niccolò Dematteis, Francesco Zucca, Martin Funk, and Daniele Giordan
EGUsphere, https://doi.org/10.5194/egusphere-2023-2771, https://doi.org/10.5194/egusphere-2023-2771, 2023
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One of the main features of glaciers is their movement along slopes. The study of this process is relevant in many aspects of glaciology. In the present study, optical satellite images of Mont Blanc were processed, obtaining surface velocities of 30 glaciers between 2016–2022. The study highlighted different behaviours and velocity variations that have relationships with the glacier morphology. An unexpected accelerating trend was observed, but its origin needs to be further investigated.
Oskar Herrmann, Nora Gourmelon, Thorsten Seehaus, Andreas Maier, Johannes J. Fürst, Matthias H. Braun, and Vincent Christlein
The Cryosphere, 17, 4957–4977, https://doi.org/10.5194/tc-17-4957-2023, https://doi.org/10.5194/tc-17-4957-2023, 2023
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Delineating calving fronts of marine-terminating glaciers in satellite images is a labour-intensive task. We propose a method based on deep learning that automates this task. We choose a deep learning framework that adapts to any given dataset without needing deep learning expertise. The method is evaluated on a benchmark dataset for calving-front detection and glacier zone segmentation. The framework can beat the benchmark baseline without major modifications.
Jordan N. Herbert, Mark S. Raleigh, and Eric E. Small
EGUsphere, https://doi.org/10.5194/egusphere-2023-2543, https://doi.org/10.5194/egusphere-2023-2543, 2023
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Automated stations measure snow properties at a single point, but are frequently used to validate data that represent much larger areas. We use Lidar snow depth data to see how often the mean snow depth surrounding a snow station is within 10 cm of the snow station depth at different scales. We found snow stations overrepresent the area-mean snow depth in ~50 % of cases, but the direction of bias at a site is temporally consistent, suggesting a site could be calibrated to the surrounding area.
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
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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 %.
Jurjen van der Sluijs, Steven V. Kokelj, and Jon F. Tunnicliffe
The Cryosphere, 17, 4511–4533, https://doi.org/10.5194/tc-17-4511-2023, https://doi.org/10.5194/tc-17-4511-2023, 2023
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There is an urgent need to obtain size and erosion estimates of climate-driven landslides, such as retrogressive thaw slumps. We evaluated surface interpolation techniques to estimate slump erosional volumes and developed a new inventory method by which the size and activity of these landslides are tracked through time. Models between slump area and volume reveal non-linear intensification, whereby model coefficients improve our understanding of how permafrost landscapes may evolve over time.
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
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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.
Anssi Rauhala, Leo-Juhani Meriö, Anton Kuzmin, Pasi Korpelainen, Pertti Ala-aho, Timo Kumpula, Bjørn Kløve, and Hannu Marttila
The Cryosphere, 17, 4343–4362, https://doi.org/10.5194/tc-17-4343-2023, https://doi.org/10.5194/tc-17-4343-2023, 2023
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Snow conditions in the Northern Hemisphere are rapidly changing, and information on snow depth is important for decision-making. We present snow depth measurements using different drones throughout the winter at a subarctic site. Generally, all drones produced good estimates of snow depth in open areas. However, differences were observed in the accuracies produced by the different drones, and a reduction in accuracy was observed when moving from an open mire area to forest-covered areas.
Leo-Juhani Meriö, Anssi Rauhala, Pertti Ala-aho, Anton Kuzmin, Pasi Korpelainen, Timo Kumpula, Bjørn Kløve, and Hannu Marttila
The Cryosphere, 17, 4363–4380, https://doi.org/10.5194/tc-17-4363-2023, https://doi.org/10.5194/tc-17-4363-2023, 2023
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Information on seasonal snow cover is essential in understanding snow processes and operational forecasting. We study the spatiotemporal variability in snow depth and snow processes in a subarctic, boreal landscape using drones. We identified multiple theoretically known snow processes and interactions between snow and vegetation. The results highlight the applicability of the drones to be used for a detailed study of snow depth in multiple land cover types and snow–vegetation interactions.
Kirsty Wivell, Stuart Fox, Melody Sandells, Chawn Harlow, Richard Essery, and Nick Rutter
The Cryosphere, 17, 4325–4341, https://doi.org/10.5194/tc-17-4325-2023, https://doi.org/10.5194/tc-17-4325-2023, 2023
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Satellite microwave observations improve weather forecasts, but to use these observations in the Arctic, snow emission must be known. This study uses airborne and in situ snow observations to validate emissivity simulations for two- and three-layer snowpacks at key frequencies for weather prediction. We assess the impact of thickness, grain size and density in key snow layers, which will help inform development of physical snow models that provide snow profile input to emissivity simulations.
Konstantin Muzalevskiy, Zdenek Ruzicka, Alexandre Roy, Michael Loranty, and Alexander Vasiliev
The Cryosphere, 17, 4155–4164, https://doi.org/10.5194/tc-17-4155-2023, https://doi.org/10.5194/tc-17-4155-2023, 2023
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A new all-weather method for determining the frozen/thawed (FT) state of soils in the Arctic region based on satellite data was proposed. The method is based on multifrequency measurement of brightness temperatures by the SMAP and GCOM-W1/AMSR2 satellites. The created method was tested at sites in Canada, Finland, Russia, and the USA, based on climatic weather station data. The proposed method identifies the FT state of Arctic soils with better accuracy than existing methods.
Alexander Mchedlishvili, Christof Lüpkes, Alek Petty, Michel Tsamados, and Gunnar Spreen
The Cryosphere, 17, 4103–4131, https://doi.org/10.5194/tc-17-4103-2023, https://doi.org/10.5194/tc-17-4103-2023, 2023
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In this study we looked at sea ice–atmosphere drag coefficients, quantities that help with characterizing the friction between the atmosphere and sea ice, and vice versa. Using ICESat-2, a laser altimeter that measures elevation differences by timing how long it takes for photons it sends out to return to itself, we could map the roughness, i.e., how uneven the surface is. From roughness we then estimate drag force, the frictional force between sea ice and the atmosphere, across the Arctic.
Whyjay Zheng, Shashank Bhushan, Maximillian Van Wyk De Vries, William Kochtitzky, David Shean, Luke Copland, Christine Dow, Renette Jones-Ivey, and Fernando Pérez
The Cryosphere, 17, 4063–4078, https://doi.org/10.5194/tc-17-4063-2023, https://doi.org/10.5194/tc-17-4063-2023, 2023
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We design and propose a method that can evaluate the quality of glacier velocity maps. The method includes two numbers that we can calculate for each velocity map. Based on statistics and ice flow physics, velocity maps with numbers close to the recommended values are considered to have good quality. We test the method using the data from Kaskawulsh Glacier, Canada, and release an open-sourced software tool called GLAcier Feature Tracking testkit (GLAFT) to help users assess their velocity maps.
Eunsang Cho, Carrie M. Vuyovich, Sujay V. Kumar, Melissa L. Wrzesien, and Rhae Sung Kim
The Cryosphere, 17, 3915–3931, https://doi.org/10.5194/tc-17-3915-2023, https://doi.org/10.5194/tc-17-3915-2023, 2023
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As a future snow mission concept, active microwave sensors have the potential to measure snow water equivalent (SWE) in deep snowpack and forested environments. We used a modeling and data assimilation approach (a so-called observing system simulation experiment) to quantify the usefulness of active microwave-based SWE retrievals over western Colorado. We found that active microwave sensors with a mature retrieval algorithm can improve SWE simulations by about 20 % in the mountainous domain.
Philip Rostosky and Gunnar Spreen
The Cryosphere, 17, 3867–3881, https://doi.org/10.5194/tc-17-3867-2023, https://doi.org/10.5194/tc-17-3867-2023, 2023
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During winter, storms entering the Arctic region can bring warm air into the cold environment. Strong increases in air temperature modify the characteristics of the Arctic snow and ice cover. The Arctic sea ice cover can be monitored by satellites observing the natural emission of the Earth's surface. In this study, we show that during warm air intrusions the change in the snow characteristics influences the satellite-derived sea ice cover, leading to a false reduction of the estimated ice area.
Ellen M. Buckley, Sinéad L. Farrell, Ute C. Herzfeld, Melinda A. Webster, Thomas Trantow, Oliwia N. Baney, Kyle A. Duncan, Huilin Han, and Matthew Lawson
The Cryosphere, 17, 3695–3719, https://doi.org/10.5194/tc-17-3695-2023, https://doi.org/10.5194/tc-17-3695-2023, 2023
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In this study, we use satellite observations to investigate the evolution of melt ponds on the Arctic sea ice surface. We derive melt pond depth from ICESat-2 measurements of the pond surface and bathymetry and melt pond fraction (MPF) from the classification of Sentinel-2 imagery. MPF increases to a peak of 16 % in late June and then decreases, while depth increases steadily. This work demonstrates the ability to track evolving melt conditions in three dimensions throughout the summer.
Monika Pfau, Georg Veh, and Wolfgang Schwanghart
The Cryosphere, 17, 3535–3551, https://doi.org/10.5194/tc-17-3535-2023, https://doi.org/10.5194/tc-17-3535-2023, 2023
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Cast shadows have been a recurring problem in remote sensing of glaciers. We show that the length of shadows from surrounding mountains can be used to detect gains or losses in glacier elevation.
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
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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.
Guanyu Li, Mingyang Lv, Duncan J. Quincey, Liam S. Taylor, Xinwu Li, Shiyong Yan, Yidan Sun, and Huadong Guo
The Cryosphere, 17, 2891–2907, https://doi.org/10.5194/tc-17-2891-2023, https://doi.org/10.5194/tc-17-2891-2023, 2023
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Kyagar Glacier in the Karakoram is well known for its surge history and its frequent blocking of the downstream valley, leading to a series of high-magnitude glacial lake outburst floods. Using it as a test bed, we develop a new approach for quantifying surge behaviour using successive digital elevation models. This method could be applied to other surge studies. Combined with the results from optical satellite images, we also reconstruct the surge process in unprecedented detail.
Yujia Qiu, Xiao-Ming Li, and Huadong Guo
The Cryosphere, 17, 2829–2849, https://doi.org/10.5194/tc-17-2829-2023, https://doi.org/10.5194/tc-17-2829-2023, 2023
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Spaceborne thermal infrared sensors with kilometer-scale resolution cannot support adequate parameterization of Arctic leads. For the first time, we applied the 30 m resolution data from the Thermal Infrared Spectrometer (TIS) on the emerging SDGSAT-1 to detect Arctic leads. Validation with Sentinel-2 data shows high accuracy for the three TIS bands. Compared to MODIS, the TIS presents more narrow leads, demonstrating its great potential for observing previously unresolvable Arctic leads.
Cited articles
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Short summary
Using radio-echo sounding data from northern Greenland, we demonstrate that subglacial roughness exhibits self-affine (fractal) scaling behaviour. This enables us to assess topographic control upon the bed-echo waveform, and explain the spatial distribution of the degree of scattering (specular and diffuse reflections). Via comparison with a prediction for the basal thermal state (thawed and frozen regions of the bed) we discuss the consequences of our study for basal water discrimination.
Using radio-echo sounding data from northern Greenland, we demonstrate that subglacial roughness...
