Articles | Volume 18, issue 8
https://doi.org/10.5194/tc-18-3875-2024
© Author(s) 2024. 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-18-3875-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
30 Aug 2024
Research article |
| 30 Aug 2024
| 30 Aug 2024
Layer-optimized synthetic aperture radar processing with a mobile phase-sensitive radar: a proof of concept for detecting the deep englacial stratigraphy of Colle Gnifetti, Switzerland and Italy
Falk M. Oraschewski
CORRESPONDING AUTHOR
Department of Geosciences, University of Tübingen, Tübingen, Germany
Inka Koch
Department of Geosciences, University of Tübingen, Tübingen, Germany
M. Reza Ershadi
Department of Geosciences, University of Tübingen, Tübingen, Germany
Jonathan D. Hawkins
School of Earth and Environmental Sciences, Cardiff University, Cardiff, Wales, United Kingdom
Olaf Eisen
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven, Germany
Department of Geosciences, University of Bremen, Bremen, Germany
Reinhard Drews
Department of Geosciences, University of Tübingen, Tübingen, Germany
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Vjeran Višnjević, Reinhard Drews, Clemens Schannwell, Inka Koch, Steven Franke, Daniela Jansen, and Olaf Eisen
The Cryosphere, 16, 4763–4777, https://doi.org/10.5194/tc-16-4763-2022, https://doi.org/10.5194/tc-16-4763-2022, 2022
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Julian Gutt, Stefanie Arndt, David Keith Alan Barnes, Horst Bornemann, Thomas Brey, Olaf Eisen, Hauke Flores, Huw Griffiths, Christian Haas, Stefan Hain, Tore Hattermann, Christoph Held, Mario Hoppema, Enrique Isla, Markus Janout, Céline Le Bohec, Heike Link, Felix Christopher Mark, Sebastien Moreau, Scarlett Trimborn, Ilse van Opzeeland, Hans-Otto Pörtner, Fokje Schaafsma, Katharina Teschke, Sandra Tippenhauer, Anton Van de Putte, Mia Wege, Daniel Zitterbart, and Dieter Piepenburg
Biogeosciences, 19, 5313–5342, https://doi.org/10.5194/bg-19-5313-2022, https://doi.org/10.5194/bg-19-5313-2022, 2022
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Long-term ecological observations are key to assess, understand and predict impacts of environmental change on biotas. We present a multidisciplinary framework for such largely lacking investigations in the East Antarctic Southern Ocean, combined with case studies, experimental and modelling work. As climate change is still minor here but is projected to start soon, the timely implementation of this framework provides the unique opportunity to document its ecological impacts from the very onset.
A. Clara J. Henry, Reinhard Drews, Clemens Schannwell, and Vjeran Višnjević
The Cryosphere, 16, 3889–3905, https://doi.org/10.5194/tc-16-3889-2022, https://doi.org/10.5194/tc-16-3889-2022, 2022
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We used a 3D, idealised model to study features in coastal Antarctica called ice rises and ice rumples. These features regulate the rate of ice flow into the ocean. We show that when sea level is raised or lowered, the size of these features and the ice flow pattern can change. We find that the features depend on the ice history and do not necessarily fully recover after an equal increase and decrease in sea level. This shows that it is important to initialise models with accurate ice geometry.
Falk M. Oraschewski and Aslak Grinsted
The Cryosphere, 16, 2683–2700, https://doi.org/10.5194/tc-16-2683-2022, https://doi.org/10.5194/tc-16-2683-2022, 2022
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Old snow (denoted as firn) accumulates in the interior of ice sheets and gets densified into glacial ice. Typically, this densification is assumed to only depend on temperature and accumulation rate. However, it has been observed that stretching of the firn by horizontal flow also enhances this process. Here, we show how to include this effect in classical firn models. With the model we confirm that softening of the firn controls firn densification in areas with strong horizontal stretching.
Chaman Gul, Shichang Kang, Siva Praveen Puppala, Xiaokang Wu, Cenlin He, Yangyang Xu, Inka Koch, Sher Muhammad, Rajesh Kumar, and Getachew Dubache
Atmos. Chem. Phys., 22, 8725–8737, https://doi.org/10.5194/acp-22-8725-2022, https://doi.org/10.5194/acp-22-8725-2022, 2022
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This work aims to understand concentrations, spatial variability, and potential source regions of light-absorbing impurities (black carbon aerosols, dust particles, and organic carbon) in the surface snow of central and western Himalayan glaciers and their impact on snow albedo and radiative forcing.
Astrid Oetting, Emma C. Smith, Jan Erik Arndt, Boris Dorschel, Reinhard Drews, Todd A. Ehlers, Christoph Gaedicke, Coen Hofstede, Johann P. Klages, Gerhard Kuhn, Astrid Lambrecht, Andreas Läufer, Christoph Mayer, Ralf Tiedemann, Frank Wilhelms, and Olaf Eisen
The Cryosphere, 16, 2051–2066, https://doi.org/10.5194/tc-16-2051-2022, https://doi.org/10.5194/tc-16-2051-2022, 2022
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This study combines a variety of geophysical measurements in front of and beneath the Ekström Ice Shelf in order to identify and interpret geomorphological evidences of past ice sheet flow, extent and retreat.
The maximal extent of grounded ice in this region was 11 km away from the continental shelf break.
The thickness of palaeo-ice on the calving front around the LGM was estimated to be at least 305 to 320 m.
We provide essential boundary conditions for palaeo-ice-sheet models.
M. Reza Ershadi, Reinhard Drews, Carlos Martín, Olaf Eisen, Catherine Ritz, Hugh Corr, Julia Christmann, Ole Zeising, Angelika Humbert, and Robert Mulvaney
The Cryosphere, 16, 1719–1739, https://doi.org/10.5194/tc-16-1719-2022, https://doi.org/10.5194/tc-16-1719-2022, 2022
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Radio waves transmitted through ice split up and inform us about the ice sheet interior and orientation of single ice crystals. This can be used to infer how ice flows and improve projections on how it will evolve in the future. Here we used an inverse approach and developed a new algorithm to infer ice properties from observed radar data. We applied this technique to the radar data obtained at two EPICA drilling sites, where ice cores were used to validate our results.
Steven Franke, Daniela Jansen, Tobias Binder, John D. Paden, Nils Dörr, Tamara A. Gerber, Heinrich Miller, Dorthe Dahl-Jensen, Veit Helm, Daniel Steinhage, Ilka Weikusat, Frank Wilhelms, and Olaf Eisen
Earth Syst. Sci. Data, 14, 763–779, https://doi.org/10.5194/essd-14-763-2022, https://doi.org/10.5194/essd-14-763-2022, 2022
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The Northeast Greenland Ice Stream (NEGIS) is the largest ice stream in Greenland. In order to better understand the past and future dynamics of the NEGIS, we present a high-resolution airborne radar data set (EGRIP-NOR-2018) for the onset region of the NEGIS. The survey area is centered at the location of the drill site of the East Greenland Ice-Core Project (EastGRIP), and radar profiles cover both shear margins and are aligned parallel to several flow lines.
Johannes Sutter, Hubertus Fischer, and Olaf Eisen
The Cryosphere, 15, 3839–3860, https://doi.org/10.5194/tc-15-3839-2021, https://doi.org/10.5194/tc-15-3839-2021, 2021
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Projections of global sea-level changes in a warming world require ice-sheet models. We expand the calibration of these models by making use of the internal architecture of the Antarctic ice sheet, which is formed by its evolution over many millennia. We propose that using our novel approach to constrain ice sheet models, we will be able to both sharpen our understanding of past and future sea-level changes and identify weaknesses in the parameterisation of current continental-scale models.
David A. Lilien, Daniel Steinhage, Drew Taylor, Frédéric Parrenin, Catherine Ritz, Robert Mulvaney, Carlos Martín, Jie-Bang Yan, Charles O'Neill, Massimo Frezzotti, Heinrich Miller, Prasad Gogineni, Dorthe Dahl-Jensen, and Olaf Eisen
The Cryosphere, 15, 1881–1888, https://doi.org/10.5194/tc-15-1881-2021, https://doi.org/10.5194/tc-15-1881-2021, 2021
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We collected radar data between EDC, an ice core spanning ~800 000 years, and BELDC, the site chosen for a new
oldest icecore at nearby Little Dome C. These data allow us to identify 50 % older internal horizons than previously traced in the area. We fit a model to the ages of those horizons at BELDC to determine the age of deep ice there. We find that there is likely to be 1.5 Myr old ice ~265 m above the bed, with sufficient resolution to preserve desired climatic information.
Coen Hofstede, Sebastian Beyer, Hugh Corr, Olaf Eisen, Tore Hattermann, Veit Helm, Niklas Neckel, Emma C. Smith, Daniel Steinhage, Ole Zeising, and Angelika Humbert
The Cryosphere, 15, 1517–1535, https://doi.org/10.5194/tc-15-1517-2021, https://doi.org/10.5194/tc-15-1517-2021, 2021
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Support Force Glacier rapidly flows into Filcher Ice Shelf of Antarctica. As we know little about this glacier and its subglacial drainage, we used seismic energy to map the transition area from grounded to floating ice where a drainage channel enters the ocean cavity. Soft sediments close to the grounding line are probably transported by this drainage channel. The constant ice thickness over the steeply dipping seabed of the ocean cavity suggests a stable transition and little basal melting.
Stefan Kowalewski, Veit Helm, Elizabeth Mary Morris, and Olaf Eisen
The Cryosphere, 15, 1285–1305, https://doi.org/10.5194/tc-15-1285-2021, https://doi.org/10.5194/tc-15-1285-2021, 2021
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This study presents estimates of total mass input for the Pine Island Glacier (PIG) over the period 2005–2014 from airborne radar measurements. Our analysis reveals a total mass input similar to an earlier estimate for the period 1985–2009 and same area. This suggests a stationary total mass input contrary to the accelerated mass loss of PIG over the past decades. However, we also find that its uncertainty is highly sensitive to the geostatistical assumptions required for its calculation.
Mirjam Schaller, Igor Dal Bo, Todd A. Ehlers, Anja Klotzsche, Reinhard Drews, Juan Pablo Fuentes Espoz, and Jan van der Kruk
SOIL, 6, 629–647, https://doi.org/10.5194/soil-6-629-2020, https://doi.org/10.5194/soil-6-629-2020, 2020
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In this study geophysical observations from ground-penetrating radar with pedolith physical and geochemical properties from pedons excavated in four study areas of the climate and ecological gradient in the Chilean Coastal Cordillera are combined. Findings suggest that profiles with ground-penetrating radar along hillslopes can be used to infer lateral thickness variations in pedolith horizons and to some degree physical and chemical variations with depth.
Clemens Schannwell, Reinhard Drews, Todd A. Ehlers, Olaf Eisen, Christoph Mayer, Mika Malinen, Emma C. Smith, and Hannes Eisermann
The Cryosphere, 14, 3917–3934, https://doi.org/10.5194/tc-14-3917-2020, https://doi.org/10.5194/tc-14-3917-2020, 2020
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To reduce uncertainties associated with sea level rise projections, an accurate representation of ice flow is paramount. Most ice sheet models rely on simplified versions of the underlying ice flow equations. Due to the high computational costs, ice sheet models based on the complete ice flow equations have been restricted to < 1000 years. Here, we present a new model setup that extends the applicability of such models by an order of magnitude, permitting simulations of 40 000 years.
Alexander H. Weinhart, Johannes Freitag, Maria Hörhold, Sepp Kipfstuhl, and Olaf Eisen
The Cryosphere, 14, 3663–3685, https://doi.org/10.5194/tc-14-3663-2020, https://doi.org/10.5194/tc-14-3663-2020, 2020
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From 1 m snow profiles along a traverse on the East Antarctic Plateau, we calculated a representative surface snow density of 355 kg m−3 for this region with an error less than 1.5 %.
This density is 10 % higher and density fluctuations seem to happen on smaller scales than climate model outputs suggest. Our study can help improve the parameterization of surface snow density in climate models to reduce the error in future sea level predictions.
Cited articles
Alean, J., Haeberli, W., and Schädler, B.: Snow Accumulation, Firn Temperature and Solar Radiation in the Area of the Colle Gnifetti Core Drilling Site (Monte Rosa, Swiss Alps): Distribution Patterns and Interrelationships, Zeitschrift für Gletscherkunde und Glazialgeologie, 19, 131–147, 1983. a
Arthern, R. J., J. Corr, H. F., Gillet-Chaulet, F., Hawley, R. L., and Morris, E. M.: Inversion for the Density-depth Profile of Polar Firn Using a Stepped-frequency Radar, J. Geophys. Res.-Earth, 118, 1257–1263, https://doi.org/10.1002/jgrf.20089, 2013. a
Bohleber, P.: Ground-Penetrating Radar Assisted Ice Core Research: The Challenge of Alpine Glaciers and Dielectric Ice Properties, PhD thesis, Heidelberg University, https://doi.org/10.11588/heidok.00012800, 2011. a, b, c
Bohleber, P., Wagner, N., and Eisen, O.: Permittivity of Ice at Radio Frequencies: Part II. Artificial and Natural Polycrystalline Ice, Cold Reg. Sci. Technol., 83–84, 13–19, https://doi.org/10.1016/j.coldregions.2012.05.010, 2012. a
Bohleber, P., Erhardt, T., Spaulding, N., Hoffmann, H., Fischer, H., and Mayewski, P.: Temperature and mineral dust variability recorded in two low-accumulation Alpine ice cores over the last millennium, Clim. Past, 14, 21–37, https://doi.org/10.5194/cp-14-21-2018, 2018. a
Case, E. and Kingslake, J.: Phase-Sensitive Radar as a Tool for Measuring Firn Compaction, J. Glaciol., 68, 139–152, https://doi.org/10.1017/jog.2021.83, 2022. a
Castelletti, D., Schroeder, D. M., Hensley, S., Grima, C., Ng, G., Young, D., Gim, Y., Bruzzone, L., Moussessian, A., and Blankenship, D. D.: An Interferometric Approach to Cross-Track Clutter Detection in Two-Channel VHF Radar Sounders, IEEE T. Geosci. Remote, 55, 6128–6140, https://doi.org/10.1109/TGRS.2017.2721433, 2017. a, b
Cavitte, M. G. P., Parrenin, F., Ritz, C., Young, D. A., Van Liefferinge, B., Blankenship, D. D., Frezzotti, M., and Roberts, J. L.: Accumulation patterns around Dome C, East Antarctica, in the last 73 kyr, The Cryosphere, 12, 1401–1414, https://doi.org/10.5194/tc-12-1401-2018, 2018. a
Clifford, H. M., Spaulding, N. E., Kurbatov, A. V., More, A., Korotkikh, E. V., Sneed, S. B., Handley, M., Maasch, K. A., Loveluck, C. P., Chaplin, J., McCormick, M., and Mayewski, P. A.: A 2000 Year Saharan Dust Event Proxy Record from an Ice Core in the European Alps, J. Geophys. Res.-Atmos., 124, 12882–12900, https://doi.org/10.1029/2019JD030725, 2019. a
Diez, A., Eisen, O., Hofstede, C., Bohleber, P., and Polom, U.: Joint Interpretation of Explosive and Vibroseismic Surveys on Cold Firn for the Investigation of Ice Properties, Ann. Glaciol., 54, 201–210, https://doi.org/10.3189/2013AoG64A200, 2013. a
Drews, R.: Evolution of ice-shelf channels in Antarctic ice shelves, The Cryosphere, 9, 1169–1181, https://doi.org/10.5194/tc-9-1169-2015, 2015. a
Drews, R., Eisen, O., Weikusat, I., Kipfstuhl, S., Lambrecht, A., Steinhage, D., Wilhelms, F., and Miller, H.: Layer disturbances and the radio-echo free zone in ice sheets, The Cryosphere, 3, 195–203, https://doi.org/10.5194/tc-3-195-2009, 2009. a
Drews, R., Eisen, O., Steinhage, D., Weikusat, I., Kipfstuhl, S., and Wilhelms, F.: Potential Mechanisms for Anisotropy in Ice-Penetrating Radar Data, J. Glaciol., 58, 613–624, https://doi.org/10.3189/2012JoG11J114, 2012. a, b
EPICA community members: Eight Glacial Cycles from an Antarctic Ice Core, Nature, 429, 623–628, https://doi.org/10.1038/nature02599, 2004. a
Ershadi, M. R., Drews, R., Martín, C., Eisen, O., Ritz, C., Corr, H., Christmann, J., Zeising, O., Humbert, A., and Mulvaney, R.: Polarimetric radar reveals the spatial distribution of ice fabric at domes and divides in East Antarctica, The Cryosphere, 16, 1719–1739, https://doi.org/10.5194/tc-16-1719-2022, 2022. a
Ershadi, M. R., Drews, R., Hawkins, J., Elliott, J., Lines, A. P., Koch, I., and Eisen, O.: Autonomous Rover Enables Radar Profiling of Ice-Fabric Properties in Antarctica, IEEE T. Geosci. Remote, 62, 5913809, https://doi.org/10.1109/TGRS.2024.3394594, 2024. a, b
Freitag, J., Kerch, J., Hoffmann, H., Spaulding, N., and Bohleber, P.: XCT Density from the Alpine Ice Core KCC (2013), PANGAEA [data set], https://doi.org/10.1594/PANGAEA.887691, 2018. a, b, c
Fujita, S., Maeno, H., and Matsuoka, K.: Radio-Wave Depolarization and Scattering within Ice Sheets: A Matrix-Based Model to Link Radar and Ice-Core Measurements and Its Application, J. Glaciol., 52, 407–424, https://doi.org/10.3189/172756506781828548, 2006. a
Gabrieli, J. and Barbante, C.: The Alps in the Age of the Anthropocene: The Impact of Human Activities on the Cryosphere Recorded in the Colle Gnifetti Glacier, Rendiconti Lincei, 25, 71–83, https://doi.org/10.1007/s12210-014-0292-2, 2014. a
Gillet-Chaulet, F., Hindmarsh, R. C. A., Corr, H. F. J., King, E. C., and Jenkins, A.: In-Situ Quantification of Ice Rheology and Direct Measurement of the Raymond Effect at Summit, Greenland Using a Phase-Sensitive Radar, Geophys. Res. Lett., 38, L24503, https://doi.org/10.1029/2011GL049843, 2011. a
Hati, A., Nelson, C. W., and Howe, D. A.: Vibration-Induced PM and AM Noise in Microwave Components, IEEE T. Ultrason. Ferr., 56, 2050–2059, https://doi.org/10.1109/TUFFC.2009.1288, 2009. a
Heister, A. and Scheiber, R.: Coherent large beamwidth processing of radio-echo sounding data, The Cryosphere, 12, 2969–2979, https://doi.org/10.5194/tc-12-2969-2018, 2018. a
Hélière, F., Lin, C.-C., Corr, H., and Vaughan, D.: Radio Echo Sounding of Pine Island Glacier, West Antarctica: Aperture Synthesis Processing and Analysis of Feasibility from Space, IEEE T. Geosci. Remote, 45, 2573–2582, https://doi.org/10.1109/TGRS.2007.897433, 2007. a
Hoelzle, M., Darms, G., Lüthi, M. P., and Suter, S.: Evidence of accelerated englacial warming in the Monte Rosa area, Switzerland/Italy, The Cryosphere, 5, 231–243, https://doi.org/10.5194/tc-5-231-2011, 2011. a
Hoffmann, H., Preunkert, S., Legrand, M., Leinfelder, D., Bohleber, P., Friedrich, R., and Wagenbach, D.: A New Sample Preparation System for Micro-14C Dating of Glacier Ice with a First Application to a High Alpine Ice Core from Colle Gnifetti (Switzerland), Radiocarbon, 60, 517–533, https://doi.org/10.1017/RDC.2017.99, 2018. a
Holschuh, N., Christianson, K., and Anandakrishnan, S.: Power Loss in Dipping Internal Reflectors, Imaged Using Ice-Penetrating Radar, Ann. Glaciol., 55, 49–56, https://doi.org/10.3189/2014AoG67A005, 2014. a, b
Holschuh, N., Parizek, B. R., Alley, R. B., and Anandakrishnan, S.: Decoding Ice Sheet Behavior Using Englacial Layer Slopes, Geophys. Res. Lett., 44, 5561–5570, https://doi.org/10.1002/2017GL073417, 2017. a, b
Holschuh, N., Christianson, K., Paden, J., Alley, R., and Anandakrishnan, S.: Linking Postglacial Landscapes to Glacier Dynamics Using Swath Radar at Thwaites Glacier, Antarctica, Geology, 48, 268–272, https://doi.org/10.1130/G46772.1, 2020. a, b
Jenk, T. M., Szidat, S., Bolius, D., Sigl, M., Gäggeler, H. W., Wacker, L., Ruff, M., Barbante, C., Boutron, C. F., and Schwikowski, M.: A Novel Radiocarbon Dating Technique Applied to an Ice Core from the Alps Indicating Late Pleistocene Ages, J. Geophys. Res.-Atmos., 114, 2009JD011860, https://doi.org/10.1029/2009JD011860, 2009. a, b, c, d, e
Jordan, T. M., Schroeder, D. M., Elsworth, C. W., and Siegfried, M. R.: Estimation of Ice Fabric within Whillans Ice Stream Using Polarimetric Phase-Sensitive Radar Sounding, Ann. Glaciol., 61, 74–83, https://doi.org/10.1017/aog.2020.6, 2020. a
Kapai, S., Schroeder, D., Broome, A., Young, T. J., and Stewart, C.: SAR Focusing of Mobile ApRES Surveys, in: IGARSS 2022 – 2022 IEEE International Geoscience and Remote Sensing Symposium, IEEE, Kuala Lumpur, Malaysia, 17–22 July 2022, 1688–1691, ISBN 978-1-66542-792-0, https://doi.org/10.1109/IGARSS46834.2022.9883784, 2022. a, b, c, d
Karlsson, N. B., Dahl-Jensen, D., Gogineni, S. P., and Paden, J. D.: Tracing the Depth of the Holocene Ice in North Greenland from Radio-Echo Sounding Data, Ann. Glaciol., 54, 44–50, https://doi.org/10.3189/2013AoG64A057, 2013. a
Kerch, J. K.: Crystal-Orientation Fabric Variations on the Cm-Scale in Cold Alpine Ice: Interaction with Paleo-Climate Proxies under Deformation and Implications for the Interpretation of Seismic Velocities, PhD thesis, Heidelberg University, https://doi.org/10.11588/heidok.00022326, 2016. a
Kingslake, J., Hindmarsh, R. C. A., Aðalgeirsdóttir, G., Conway, H., Corr, H. F. J., Gillet-Chaulet, F., Martín, C., King, E. C., Mulvaney, R., and Pritchard, H. D.: Full-Depth Englacial Vertical Ice Sheet Velocities Measured Using Phase-Sensitive Radar: Measuring Englacial Ice Velocities, J. Geophys. Res.-Earth, 119, 2604–2618, https://doi.org/10.1002/2014JF003275, 2014. a
Koch, I., Drews, R., Franke, S., Jansen, D., Oraschewski, F. M., Muhle, L. S., Višnjević, V., Matsuoka, K., Pattyn, F., and Eisen, O.: Radar Internal Reflection Horizons from Multisystem Data Reflect Ice Dynamic and Surface Accumulation History along the Princess Ragnhild Coast, Dronning Maud Land, East Antarctica, J. Glaciol., 1–19, https://doi.org/10.1017/jog.2023.93, 2023. a
Konrad, H., Bohleber, P., Wagenbach, D., Vincent, C., and Eisen, O.: Determining the Age Distribution of Colle Gnifetti, Monte Rosa, Swiss Alps, by Combining Ice Cores, Ground-Penetrating Radar and a Simple Flow Model, J. Glaciol., 59, 179–189, https://doi.org/10.3189/2013JoG12J072, 2013. a, b, c, d, e, f, g, h
Koutnik, M. R., Fudge, T. J., Conway, H., Waddington, E. D., Neumann, T. A., Cuffey, K. M., Buizert, C., and Taylor, K. C.: Holocene Accumulation and Ice Flow near the West Antarctic Ice Sheet Divide Ice Core Site, J. Geophys. Res.-Earth, 121, 907–924, https://doi.org/10.1002/2015JF003668, 2016. a
Kusk, A. and Dall, J.: SAR Focusing of P-band Ice Sounding Data Using Back-Projection, in: 2010 IEEE International Geoscience and Remote Sensing Symposium, IEEE, Honolulu, HI, USA, 25–30 July 2010, 4071–4074, ISBN 978-1-4244-9565-8, https://doi.org/10.1109/IGARSS.2010.5651038, 2010. a
Licciulli, C., Bohleber, P., Lier, J., Gagliardini, O., Hoelzle, M., and Eisen, O.: A Full Stokes Ice-Flow Model to Assist the Interpretation of Millennial-Scale Ice Cores at the High-Alpine Drilling Site Colle Gnifetti, Swiss/Italian Alps, J. Glaciol., 66, 35–48, https://doi.org/10.1017/jog.2019.82, 2020. a
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Oraschewski, F. M., Koch, I., Ershadi, M. R., Hawkins, J., Eisen, O., and Drews, R.: Raw Data of Mobile Phase-Sensitive Radio Echo Sounder (pRES) Profiling Data of Deep Radiostratigraphy of Colle Gnifetti (Swiss–Italian Alps), 2021, PANGAEA [data set], https://doi.org/10.1594/PANGAEA.965199, 2024a. a
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Short summary
Mountain glaciers have a layered structure which contains information about past snow accumulation and ice flow. Using ground-penetrating radar instruments, the internal structure can be observed. The detection of layers in the deeper parts of a glacier is often difficult. Here, we present a new approach for imaging the englacial structure of an Alpine glacier (Colle Gnifetti, Switzerland and Italy) using a phase-sensitive radar that can detect reflection depth changes at sub-wavelength scales.
Mountain glaciers have a layered structure which contains information about past snow...
