Articles | Volume 17, issue 5
https://doi.org/10.5194/essd-17-1761-2025
© 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/essd-17-1761-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
06 May 2025
Data description paper |
| 06 May 2025
| 06 May 2025
Advancing geodynamic research in Antarctica: reprocessing GNSS data to infer consistent coordinate time series (GIANT-REGAIN)
Institut für Planetare Geodäsie, TUD Dresden University of Technology, Dresden, Germany
Mirko Scheinert
CORRESPONDING AUTHOR
Institut für Planetare Geodäsie, TUD Dresden University of Technology, Dresden, Germany
Matt A. King
School of Geography, Planning, and Spatial Sciences, University of Tasmania, Hobart, Tasmania, Australia
The Australian Centre for Excellence in Antarctic Science, University of Tasmania, Hobart, Tasmania, Australia
Terry Wilson
School of Earth Sciences, The Ohio State University, Columbus, Ohio, USA
Achraf Koulali
Geospatial Engineering, School of Engineering, Newcastle University, Newcastle, UK
Peter J. Clarke
Geospatial Engineering, School of Engineering, Newcastle University, Newcastle, UK
Demián Gómez
School of Earth Sciences, The Ohio State University, Columbus, Ohio, USA
Eric Kendrick
School of Earth Sciences, The Ohio State University, Columbus, Ohio, USA
Christoph Knöfel
Institut für Planetare Geodäsie, TUD Dresden University of Technology, Dresden, Germany
now at: Federal Agency for Cartography and Geodesy, Frankfurt am Main, Germany
Peter Busch
Institut für Planetare Geodäsie, TUD Dresden University of Technology, Dresden, Germany
now at: Vodafone Group Services GmbH, Düsseldorf, Germany
Related authors
Matthias O. Willen, Bert Wouters, Taco Broerse, Eric Buchta, and Veit Helm
The Cryosphere, 19, 2213–2227, https://doi.org/10.5194/tc-19-2213-2025, https://doi.org/10.5194/tc-19-2213-2025, 2025
Short summary
Short summary
Collapse of the West Antarctic Ice Sheet in the Amundsen Sea Embayment is likely in the near future. Vertical uplift of bedrock due to glacial isostatic adjustment stabilizes the ice sheet and may delay its collapse. So far, only spatially and temporally sparse GPS measurements have been able to observe this bedrock motion. We have combined satellite data and quantified a region-wide bedrock motion that independently matches GPS measurements. This can improve ice sheet predictions.
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.
Matthias O. Willen, Martin Horwath, Eric Buchta, Mirko Scheinert, Veit Helm, Bernd Uebbing, and Jürgen Kusche
The Cryosphere, 18, 775–790, https://doi.org/10.5194/tc-18-775-2024, https://doi.org/10.5194/tc-18-775-2024, 2024
Short summary
Short summary
Shrinkage of the Antarctic ice sheet (AIS) leads to sea level rise. Satellite gravimetry measures AIS mass changes. We apply a new method that overcomes two limitations: low spatial resolution and large uncertainties due to the Earth's interior mass changes. To do so, we additionally include data from satellite altimetry and climate and firn modelling, which are evaluated in a globally consistent way with thoroughly characterized errors. The results are in better agreement with independent data.
Erica M. Lucas, Natalya Gomez, and Terry Wilson
The Cryosphere, 19, 2387–2405, https://doi.org/10.5194/tc-19-2387-2025, https://doi.org/10.5194/tc-19-2387-2025, 2025
Short summary
Short summary
We investigate the effects of incorporating regional-scale lateral variability (ca. 50–100 km) in upper-mantle structure into models of Earth deformation and sea level change associated with ice mass changes in West Antarctica. Regional-scale variability in upper-mantle structure is found to impact relative sea level and crustal rate predictions for modern (last ca. 25–125 years) and projected (next ca. 300 years) ice mass changes, especially in coastal regions that undergo rapid ice mass loss.
Matthias O. Willen, Bert Wouters, Taco Broerse, Eric Buchta, and Veit Helm
The Cryosphere, 19, 2213–2227, https://doi.org/10.5194/tc-19-2213-2025, https://doi.org/10.5194/tc-19-2213-2025, 2025
Short summary
Short summary
Collapse of the West Antarctic Ice Sheet in the Amundsen Sea Embayment is likely in the near future. Vertical uplift of bedrock due to glacial isostatic adjustment stabilizes the ice sheet and may delay its collapse. So far, only spatially and temporally sparse GPS measurements have been able to observe this bedrock motion. We have combined satellite data and quantified a region-wide bedrock motion that independently matches GPS measurements. This can improve ice sheet predictions.
Torsten Kanzow, Angelika Humbert, Thomas Mölg, Mirko Scheinert, Matthias Braun, Hans Burchard, Francesca Doglioni, Philipp Hochreuther, Martin Horwath, Oliver Huhn, Maria Kappelsberger, Jürgen Kusche, Erik Loebel, Katrina Lutz, Ben Marzeion, Rebecca McPherson, Mahdi Mohammadi-Aragh, Marco Möller, Carolyne Pickler, Markus Reinert, Monika Rhein, Martin Rückamp, Janin Schaffer, Muhammad Shafeeque, Sophie Stolzenberger, Ralph Timmermann, Jenny Turton, Claudia Wekerle, and Ole Zeising
The Cryosphere, 19, 1789–1824, https://doi.org/10.5194/tc-19-1789-2025, https://doi.org/10.5194/tc-19-1789-2025, 2025
Short summary
Short summary
The Greenland Ice Sheet represents the second-largest contributor to global sea-level rise. We quantify atmosphere, ice and ocean processes related to the mass balance of glaciers in northeast Greenland, focusing on Greenland’s largest floating ice tongue, the 79° N Glacier. We find that together, the different in situ and remote sensing observations and model simulations reveal a consistent picture of a coupled atmosphere–ice sheet–ocean system that has entered a phase of major change.
John Bright Ayabilah, Matt King, Danielle Udy, and Tessa Vance
EGUsphere, https://doi.org/10.5194/egusphere-2025-1187, https://doi.org/10.5194/egusphere-2025-1187, 2025
Short summary
Short summary
Large-scale climate modes significantly influence Antarctic Ice Sheet (AIS) mass variability. This study investigates AIS variability during different El Niño-Southern Oscillation (ENSO) periods using GRACE data (2002–2022). Results show strong spatial variability driven by changes in the Amundsen Sea Low (ASL) and Southern Annular Mode (SAM). This highlights the importance of understanding these patterns for future ice mass estimates and sea level rise predictions.
Erik Loebel, Celia A. Baumhoer, Andreas Dietz, Mirko Scheinert, and Martin Horwath
Earth Syst. Sci. Data, 17, 65–78, https://doi.org/10.5194/essd-17-65-2025, https://doi.org/10.5194/essd-17-65-2025, 2025
Short summary
Short summary
Glacier calving front positions are important for understanding glacier dynamics and constraining ice modelling. We apply a deep-learning framework to multi-spectral Landsat imagery to create a calving front record for 42 key outlet glaciers of the Antarctic Peninsula Ice Sheet. The resulting data product includes 4817 calving front locations from 2013 to 2023 and achieves sub-seasonal temporal resolution.
Katrina Lutz, Lily Bever, Christian Sommer, Thorsten Seehaus, Angelika Humbert, Mirko Scheinert, and Matthias Braun
The Cryosphere, 18, 5431–5449, https://doi.org/10.5194/tc-18-5431-2024, https://doi.org/10.5194/tc-18-5431-2024, 2024
Short summary
Short summary
The estimation of the amount of water found within supraglacial lakes is important for understanding how much water is lost from glaciers each year. Here, we develop two new methods for estimating supraglacial lake volume that can be easily applied on a large scale. Furthermore, we compare these methods to two previously developed methods in order to determine when it is best to use each method. Finally, three of these methods are applied to peak melt dates over an area in Northeast Greenland.
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.
Erik Loebel, Mirko Scheinert, Martin Horwath, Angelika Humbert, Julia Sohn, Konrad Heidler, Charlotte Liebezeit, and Xiao Xiang Zhu
The Cryosphere, 18, 3315–3332, https://doi.org/10.5194/tc-18-3315-2024, https://doi.org/10.5194/tc-18-3315-2024, 2024
Short summary
Short summary
Comprehensive datasets of calving-front changes are essential for studying and modeling outlet glaciers. Current records are limited in temporal resolution due to manual delineation. We use deep learning to automatically delineate calving fronts for 23 glaciers in Greenland. Resulting time series resolve long-term, seasonal, and subseasonal patterns. We discuss the implications of our results and provide the cryosphere community with a data product and an implementation of our processing system.
Matthias O. Willen, Martin Horwath, Eric Buchta, Mirko Scheinert, Veit Helm, Bernd Uebbing, and Jürgen Kusche
The Cryosphere, 18, 775–790, https://doi.org/10.5194/tc-18-775-2024, https://doi.org/10.5194/tc-18-775-2024, 2024
Short summary
Short summary
Shrinkage of the Antarctic ice sheet (AIS) leads to sea level rise. Satellite gravimetry measures AIS mass changes. We apply a new method that overcomes two limitations: low spatial resolution and large uncertainties due to the Earth's interior mass changes. To do so, we additionally include data from satellite altimetry and climate and firn modelling, which are evaluated in a globally consistent way with thoroughly characterized errors. The results are in better agreement with independent data.
Reinhard Dietrich, Christoph Knöfel, Mirko Scheinert, and Ralf Rosenau
Polarforschung, 92, 1–13, https://doi.org/10.5194/polf-92-1-2024, https://doi.org/10.5194/polf-92-1-2024, 2024
Short summary
Short summary
Drygalski führte in den Jahren 1891 und 1892/93 Forschungsarbeiten in Westgrönland durch, wobei zur Überwinterung eine Forschungsstation am Großen Karajak-Gletscher errichtetet wurde. An gleicher Stelle erfolgten durch die TU Dresden 2007 und 2019 geodätische Feldarbeiten. Im Beitrag werden das Areal der damaligen Station sowie die Forschungsarbeiten Drygalskis vorgestellt. Ein Vergleich mit heutigen Messungen zeigt, dass sich der Große Karajak-Gletscher in 120 Jahren kaum verändert hat.
Alexandra M. Zuhr, Erik Loebel, Marek Muchow, Donovan Dennis, Luisa von Albedyll, Frigga Kruse, Heidemarie Kassens, Johanna Grabow, Dieter Piepenburg, Sören Brandt, Rainer Lehmann, Marlene Jessen, Friederike Krüger, Monika Kallfelz, Andreas Preußer, Matthias Braun, Thorsten Seehaus, Frank Lisker, Daniela Röhnert, and Mirko Scheinert
Polarforschung, 91, 73–80, https://doi.org/10.5194/polf-91-73-2023, https://doi.org/10.5194/polf-91-73-2023, 2023
Short summary
Short summary
Polar research is an interdisciplinary and multi-faceted field of research. Its diversity ranges from history to geology and geophysics to social sciences and education. This article provides insights into the different areas of German polar research. This was made possible by a seminar series, POLARSTUNDE, established in the summer of 2020 and organized by the German Society of Polar Research and the German National Committee of the Association of Polar Early Career Scientists (APECS Germany).
Angelika Graiff, Matthias Braun, Amelie Driemel, Jörg Ebbing, Hans-Peter Grossart, Tilmann Harder, Joseph I. Hoffman, Boris Koch, Florian Leese, Judith Piontek, Mirko Scheinert, Petra Quillfeldt, Jonas Zimmermann, and Ulf Karsten
Polarforschung, 91, 45–57, https://doi.org/10.5194/polf-91-45-2023, https://doi.org/10.5194/polf-91-45-2023, 2023
Short summary
Short summary
There are many approaches to better understanding Antarctic processes that generate very large data sets (
Antarctic big data). For these large data sets there is a pressing need for improved data acquisition, curation, integration, service, and application to support fundamental scientific research, and this article describes and evaluates the current status of big data in various Antarctic scientific disciplines, identifies current gaps, and provides solutions to fill these gaps.
Ole Richter, David E. Gwyther, Matt A. King, and Benjamin K. Galton-Fenzi
The Cryosphere, 16, 1409–1429, https://doi.org/10.5194/tc-16-1409-2022, https://doi.org/10.5194/tc-16-1409-2022, 2022
Short summary
Short summary
Tidal currents may play an important role in Antarctic ice sheet retreat by changing the rate at which the ocean melts glaciers. Here, using a computational ocean model, we derive the first estimate of present-day tidal melting that covers all of Antarctica. Our results suggest that large-scale ocean models aiming to accurately predict ice melt rates will need to account for the effects of tides. The inclusion of tide-induced friction at the ice–ocean interface should be prioritized.
Grace A. Nield, Matt A. King, Rebekka Steffen, and Bas Blank
Geosci. Model Dev., 15, 2489–2503, https://doi.org/10.5194/gmd-15-2489-2022, https://doi.org/10.5194/gmd-15-2489-2022, 2022
Short summary
Short summary
We present a finite-element model of post-seismic solid Earth deformation built in the software package Abaqus for the purpose of calculating post-seismic deformation in the far field of major earthquakes. The model is benchmarked against an existing open-source post-seismic model demonstrating good agreement. The advantage over existing models is the potential for simple modification to include 3-D Earth structure, non-linear rheologies and alternative or multiple sources of stress change.
Steven J. Phipps, Jason L. Roberts, and Matt A. King
Geosci. Model Dev., 14, 5107–5124, https://doi.org/10.5194/gmd-14-5107-2021, https://doi.org/10.5194/gmd-14-5107-2021, 2021
Short summary
Short summary
Simplified schemes, known as parameterisations, are sometimes used to describe physical processes within numerical models. However, the values of the parameters are uncertain. This introduces uncertainty into the model outputs. We develop a simple approach to identify plausible ranges for model parameters. Using a model of the Antarctic Ice Sheet, we find that the value of one parameter can depend on the values of others. We conclude that a single optimal set of parameter values does not exist.
Lukas Müller, Martin Horwath, Mirko Scheinert, Christoph Mayer, Benjamin Ebermann, Dana Floricioiu, Lukas Krieger, Ralf Rosenau, and Saurabh Vijay
The Cryosphere, 15, 3355–3375, https://doi.org/10.5194/tc-15-3355-2021, https://doi.org/10.5194/tc-15-3355-2021, 2021
Short summary
Short summary
Harald Moltke Bræ, a marine-terminating glacier in north-western Greenland, undergoes remarkable surges of episodic character. Our data show that a recent surge from 2013 to 2019 was initiated at the glacier front and exhibits a pronounced seasonality with flow velocities varying by 1 order of magnitude, which has not been observed at Harald Moltke Bræ in this way before. These findings are crucial for understanding surge mechanisms at Harald Moltke Bræ and other marine-terminating glaciers.
Mirko Scheinert, Christoph Mayer, Martin Horwath, Matthias Braun, Anja Wendt, and Daniel Steinhage
Polarforschung, 89, 57–64, https://doi.org/10.5194/polf-89-57-2021, https://doi.org/10.5194/polf-89-57-2021, 2021
Short summary
Short summary
Ice sheets, glaciers and further ice-covered areas with their changes as well as interactions with the solid Earth and the ocean are subject of intensive research, especially against the backdrop of global climate change. The resulting questions are of concern to scientists from various disciplines such as geodesy, glaciology, physical geography and geophysics. Thus, the working group "Polar Geodesy and Glaciology", founded in 2013, offers a forum for discussion and stimulating exchange.
Bogdan Matviichuk, Matt King, and Christopher Watson
Solid Earth, 11, 1849–1863, https://doi.org/10.5194/se-11-1849-2020, https://doi.org/10.5194/se-11-1849-2020, 2020
Short summary
Short summary
The Earth deforms as the weight of ocean mass changes with the tides. GPS has been used to estimate displacements of the Earth at tidal periods and then used to understand the properties of the Earth or to test models of ocean tides. However, there are important inaccuracies in these GPS measurements at major tidal periods. We find that combining GPS and GLONASS gives more accurate results for constituents other than K2 and K1; for these, GLONASS or ambiguity resolved GPS are preferred.
Cited articles
Altamimi, Z., Rebischung, P., Métivier, L., and Collilieux, X.: ITRF2014: A new release of the International Terrestrial Reference Frame modeling nonlinear station motions, J. Geophys. Res.-Sol. Ea., 121, 6109–6131, https://doi.org/10.1002/2016JB013098, 2016. a
Altamimi, Z., Rebischung, P., Collilieux, X., Métivier, L., and Chanard, K.: ITRF2020: an augmented reference frame refining the modeling of nonlinear station motions, J. Geodesy, 97, 47, https://doi.org/10.1007/s00190-023-01738-w, 2023. a, b
Andrei, C.-O., Lahtinen, S., Nordman, M., Näränen, J., Koivula, H., Poutanen, M., and Hyyppä, J.: GPS Time Series Analysis from Aboa the Finnish Antarctic Research Station, Remote Sens., 10, 1937, https://doi.org/10.3390/rs10121937, 2018. a
Argus, D. F., Blewitt, G., Peltier, W. R., and Kreemer, C.: Rise of the Ellsworth mountains and parts of the East Antarctic coast observed with GPS, Geophys. Res. Lett., 38, L16303, https://doi.org/10.1029/2011GL048025, 2011. a
Argus, D. F., Peltier, W. R., Drummond, R., and Moore, A. W.: The Antarctica component of postglacial rebound model ICE-6G_C (VM5a) based on GPS positioning, exposure age dating of ice thicknesses, and relative sea level histories, Geophys. J. Int., 198, 537–563, https://doi.org/10.1093/gji/ggu140, 2014. a, b
Bar-Sever, Y. E., Kroger, P. M., and Borjesson, J. A.: Estimating horizontal gradients of tropospheric path delay with a single GPS receiver, J. Geophys. Res.-Sol. Ea., 103, 5019–5035, https://doi.org/10.1029/97JB03534, 1998. a
Barletta, V. R., Bevis, M., Smith, B. E., Wilson, T., Brown, A., Bordoni, A., Willis, M., Khan, S. A., Rovira-Navarro, M., Dalziel, I., Smalley, R., Kendrick, E., Konfal, S., Caccamise, D. J., Aster, R. C., Nyblade, A., and Wiens, D. A.: Observed rapid bedrock uplift in Amundsen Sea Embayment promotes ice-sheet stability, Science, 360, 1335–1339, https://doi.org/10.1126/science.aao1447, 2018. a, b, c
Bertiger, W., Desai, S. D., Haines, B., Harvey, N., Moore, A. W., Owen, S., and Weiss, J. P.: Single receiver phase ambiguity resolution with GPS data, J. Geodesy, 84, 327–337, https://doi.org/10.1007/s00190-010-0371-9, 2010. a
Bevis, M. and Brown, A.: Trajectory models and reference frames for crustal motion geodesy, J. Geodesy, 88, 283–311, https://doi.org/10.1007/s00190-013-0685-5, 2014. a
Bevis, M., Kendrick, E., Smalley Jr., R., Dalziel, I., Caccamise, D., Sasgen, I., Helsen, M., Taylor, F. W., Zhou, H., Brown, A., Raleigh, D., Willis, M., Wilson, T., and Konfal, S.: Geodetic measurements of vertical crustal velocity in West Antarctica and the implications for ice mass balance, Geochem. Geophy. Geosy., 10, Q10005, https://doi.org/10.1029/2009GC002642, 2009. a, b
Blewitt, G., Hammond, W. C., and Kreemer, C.: Harnessing the GPS data explosion for interdisciplinary science, EOS, 99, https://doi.org/10.1029/2018EO104623, 2018. a, b, c, d
Boehm, J., Werl, B., and Schuh, H.: Troposphere mapping functions for GPS and very long baseline interferometry from European Centre for Medium-Range Weather Forecasts operational analysis data, J. Geophys. Res.-Sol. Ea., 111, B02406, https://doi.org/10.1029/2005JB003629, 2006. a, b, c
Bos, M. S., Fernandes, R. M. S., Williams, S. D. P., and Bastos, L.: Fast error analysis of continuous GNSS observations with missing data, J. Geodesy, 87, 351–360, https://doi.org/10.1007/s00190-012-0605-0, 2013. a, b
Bouin, M.-N. and Vigny, C.: New constraints on Antarctic plate motion and deformation from GPS data, J. Geophys. Res.-Sol. Ea., 105, 28279–28293, https://doi.org/10.1029/2000JB900285, 2000. a
Buchta, E., Scheinert, M., King, M. A., Wilson, T., Clarke, P. J., Gómez, D., Kendrick, E., Knöfel, C., and Koulali, A.: Daily coordinate time series for GPS stations on bedrock for Antarctica and the sub Antarctic sector, 1995–2021, reprocessed by the GIANT-REGAIN project, PANGAEA [data set], https://doi.org/10.1594/PANGAEA.967515, 2024a. a, b
Buchta, E., Scheinert, M., King, M. A., Wilson, T., Clarke, P. J., Gómez, D., Kendrick, E., Knöfel, C., and Koulali, A.: Daily coordinate time series for GPS stations on bedrock for Antarctica and the sub Antarctic sector, 1995–2021, PANGAEA [data set], https://doi.org/10.1594/PANGAEA.967516, 2024b. a, b
Buchta, E., Scheinert, M., King, M. A., Wilson, T., Clarke, P. J., Gómez, D., Kendrick, E., Knöfel, C., and Koulali, A.: Event list for GPS stations on bedrock for Antarctica and the sub antarctic sector, 1995–2021, PANGAEA [data set], https://doi.org/10.1594/PANGAEA.967533, 2024c. a, b
Buchta, E., Scheinert, M., King, M. A., Wilson, T., Clarke, P. J., Gómez, D., Kendrick, E., Knöfel, C., and Koulali, A.: Station information for GPS stations on bedrock for Antarctica and the sub Antarctic sector, 1995–2021, PANGAEA [data set], https://doi.org/10.1594/PANGAEA.967532, 2024d. a, b
Buchta, E., Scheinert, M., King, M. A., Wilson, T., Clarke, P. J., Gómez, D., Kendrick, E., Knöfel, C., and Koulali, A.: Sub-daily zenith total delay time series for GPS stations on bedrock for Antarctica and the sub Antarctic sector, 1995–2021, PANGAEA [data set], https://doi.org/10.1594/PANGAEA.967529, 2024e. a, b
Burton-Johnson, A., Black, M., Fretwell, P. T., and Kaluza-Gilbert, J.: An automated methodology for differentiating rock from snow, clouds and sea in Antarctica from Landsat 8 imagery: a new rock outcrop map and area estimation for the entire Antarctic continent, The Cryosphere, 10, 1665–1677, https://doi.org/10.5194/tc-10-1665-2016, 2016. a, b
Busch, P., Scheinert, M., and Knoefel, C.: GNSS measurements in West Antarctica to reconcile glacial-isostatic adjustment, Presented at the IAG/SCAR-SERCE Workshop on Glacial Isostatic Adjustment and Elastic Deformationn, 5–7 September 2017, Reykjavik, Iceland, 2017. a
Dach, R., Andritsch, F., Arnold, D., Bertone, S., Fridez, P., Jäggi, A., Jean, Y., Maier, A., Mervart, L., Meyer, U., Orliac, E., Geist, E., Prange, L., Scaramuzza, S., Schaer, S., Sidorov, D., Susnik, A., Villiger, A., Walser, P., and Thaller, D.: Bernese GNSS Software Version 5.2, ISBN 978-3-906813-05-9, https://doi.org/10.7892/boris.72297, 2015. a, b
Dietrich, R., Dach, R., Engelhardt, G., Ihde, J., Korth, W., Kutterer, H.-J., Lindner, K., Mayer, M., Menge, F., Miller, H., Müller, C., Niemeier, W., Perlt, J., Pohl, M., Salbach, H., Schenke, H.-W., Schöne, T., Seeber, G., Veit, A., and Völksen, C.: ITRF coordinates and plate velocities from repeated GPS campaigns in Antarctica – an analysis based on different individual solutions, J. Geodesy, 74, 756–766, https://doi.org/10.1007/s001900000147, 2001. a, b
Dietrich, R., Rülke, A., Ihde, J., Lindner, K., Miller, H., Niemeier, W., Schenke, H.-W., and Seeber, G.: Plate kinematics and deformation status of the Antarctic Peninsula based on GPS, Global Planet. Chang., 42, 313–321, https://doi.org/10.1016/j.gloplacha.2003.12.003, 2004. a, b
Dong, D., Herring, T. A., and King, R. W.: Estimating regional deformation from a combination of space and terrestrial geodetic data, J. Geodesy, 72, 200–214, https://doi.org/10.1007/s001900050161, 1998. a
Donnellan, A. and Luyendyk, B. P.: GPS evidence for a coherent Antarctic plate and for postglacial rebound in Marie Byrd Land, Global Planet. Chang., 42, 305–311, https://doi.org/10.1016/j.gloplacha.2004.02.006, 2004. a
Fu, Y., Freymueller, J. T., and van Dam, T.: The effect of using inconsistent ocean tidal loading models on GPS coordinate solutions, J. Geodesy, 86, 409–421, https://doi.org/10.1007/s00190-011-0528-1, 2012. a
Gazeaux, J., Williams, S., King, M., Bos, M., Dach, R., Deo, M., Moore, A. W., Ostini, L., Petrie, E., Roggero, M., Teferle, F. N., Olivares, G., and Webb, F. H.: Detecting offsets in GPS time series: First results from the detection of offsets in GPS experiment, J. Geophys. Res.-Sol. Ea., 118, 2397–2407, https://doi.org/10.1002/jgrb.50152, 2013. a
Gómez, D.: Parallel.GAMIT, Github [code], https://github.com/demiangomez/Parallel.GAMIT, last access: 2 August 2024. a
Gómez, D. D., Bevis, M. G., and Caccamise, D. J.: Maximizing the consistency between regional and global reference frames utilizing inheritance of seasonal displacement parameters, J. Geodesy, 96, 9, https://doi.org/10.1007/s00190-022-01594-0, 2022. a
Grapenthin, R., Kyle, P., Aster, R. C., Angarita, M., Wilson, T., and Chaput, J.: Deformation at the open-vent Erebus volcano, Antarctica, from more than 20 years of GNSS observations, J. Volcanol. Geoth. Res., 432, 107703, https://doi.org/10.1016/j.jvolgeores.2022.107703, 2022. a
Groh, A. and Horwath, M.: Antarctic Ice Mass Change Products from GRACE/GRACE-FO Using Tailored Sensitivity Kernels, Remote Sens., 13, 1736, https://doi.org/10.3390/rs13091736, 2021. a
Groh, A., Ewert, H., Scheinert, M., Fritsche, M., Rülke, A., Richter, A., Rosenau, R., and Dietrich, R.: An investigation of Glacial Isostatic Adjustment over the Amundsen Sea sector, West Antarctica, Global Planet. Chang., 98-99, 45–53, https://doi.org/10.1016/j.gloplacha.2012.08.001, 2012. a
Hattori, A., Aoyama, Y., Okuno, J., and Doi, K.: GNSS Observations of GIA-Induced Crustal Deformation in Lützow-Holm Bay, East Antarctica, Geophys. Res. Lett., 48, e2021GL093479, https://doi.org/10.1029/2021GL093479, 2021. a, b, c
Herring, T. A., Melbourne, T. I., Murray, M. H., Floyd, M. A., Szeliga, W. M., King, R. W., Phillips, D. A., Puskas, C. M., Santillan, M., and Wang, L.: Plate Boundary Observatory and related networks: GPS data analysis methods and geodetic products, Rev. Geophys., 54, 759–808, https://doi.org/10.1002/2016RG000529, 2016. a, b
Johnston, G., Riddell, A., and Hausler, G.: The International GNSS Service, Springer International Publishing, Cham, 967–982, ISBN 978-3-319-42928-1, https://doi.org/10.1007/978-3-319-42928-1_33, 2017. a, b
Kedar, S., Hajj, G. A., Wilson, B. D., and Heflin, M. B.: The effect of the second order GPS ionospheric correction on receiver positions, Geophys. Res. Lett., 30, 1829, https://doi.org/10.1029/2003GL017639, 2003. a
King, M. A. and Santamaría-Gómez, A.: Ongoing deformation of Antarctica following recent Great Earthquakes, Geophys. Res. Lett., 43, 1918–1927, https://doi.org/10.1002/2016GL067773, 2016. a
King, M. A., Penna, N. T., Clarke, P. J., and King, E. C.: Validation of ocean tide models around Antarctica using onshore GPS and gravity data, J. Geophys. Res.-Sol. Earth, 110, B08401, https://doi.org/10.1029/2004JB003390, 2005. a
King, M. A., Altamimi, Z., Boehm, J., Bos, M., Dach, R., Elosegui, P., Fund, F., Hernández-Pajares, M., Lavallee, D., Mendes Cerveira, P. J., Penna, N., Riva, R. E. M., Steigenberger, P., van Dam, T., Vittuari, L., Williams, S., and Willis, P.: Improved Constraints on Models of Glacial Isostatic Adjustment: A Review of the Contribution of Ground-Based Geodetic Observations, Sur. Geophys., 31, 465–507, https://doi.org/10.1007/s10712-010-9100-4, 2010. a
King, M. A., Bingham, R. J., Moore, P., Whitehouse, P. L., Bentley, M. J., and Milne, G. A.: Lower satellite-gravimetry estimates of Antarctic sea-level contribution, Nature, 491, 586–589, https://doi.org/10.1038/nature11621, 2012. a
King, M. A., Whitehouse, P., and Clarke, P.: CAPGIA – West Antarctica Continuous Network, The GAGE Facility operated by EarthScope Consortium, GPS/GNSS Observations (Aggregation of Multiple Datasets) [data set], https://doi.org/10.7283/T56Q1VN5, 2013. a
Konfal, S., Kendrick, E., Saddler, D., Wilson, T., and Bevis, M.: Crustal velocity solutions in polar environments: GPS position errors caused by ice in antennas, in: SCAR Open Science Conference, Kuala Lumpur, Malaysia, 2016. a
Kouba, J.: Implementation and testing of the gridded Vienna Mapping Function 1 (VMF1), J. Geodesy, 82, 193–205, https://doi.org/10.1007/s00190-007-0170-0, 2008. a
Koulali, A. and Clarke, P. J.: Effect of antenna snow intrusion on vertical GPS position time series in Antarctica, J. Geodesy, 94, 101, https://doi.org/10.1007/s00190-020-01403-6, 2020. a, b
Koulali, A., Whitehouse, P. L., Clarke, P. J., van den Broeke, M. R., Nield, G. A., King, M. A., Bentley, M. J., Wouters, B., and Wilson, T.: GPS-Observed Elastic Deformation Due to Surface Mass Balance Variability in the Southern Antarctic Peninsula, Geophys. Res. Lett., 49, e2021GL097109, https://doi.org/10.1029/2021GL097109, 2022. a, b, c, d, e
Landskron, D. and Böhm, J.: VMF3/GPT3: refined discrete and empirical troposphere mapping functions, J. Geodesy, 92, 349–360, https://doi.org/10.1007/s00190-017-1066-2, 2018. a
Legrand, J., Bergeot, N., Bruyninx, C., Wöppelmann, G., Bouin, M.-N., and Altamimi, Z.: Impact of regional reference frame definition on geodynamic interpretations, J. Geodynam., 49, 116–122, https://doi.org/10.1016/j.jog.2009.10.002, 2010. a
Li, W., Li, F., Shum, C., Shu, C., Ming, F., Zhang, S., Zhang, Q., and Chen, W.: Assessment of Contemporary Antarctic GIA Models Using High-Precision GPS Time Series, Remote Sens., 14, 1070, https://doi.org/10.3390/rs14051070, 2022. a, b
Liu, B., King, M., and Dai, W.: Common mode error in Antarctic GPS coordinate time-series on its effect on bedrock-uplift estimates, Geophys. J. Int., 214, 1652–1664, https://doi.org/10.1093/gji/ggy217, 2018. a, b, c
Luzum, B. and Petit, G.: The IERS Conventions (2010): reference systems and new models, Proceedings of the International Astronomical Union, 10, 227–228, https://doi.org/10.1017/S1743921314005535, 2012. a, b, c
Lyard, F. H., Allain, D. J., Cancet, M., Carrère, L., and Picot, N.: FES2014 global ocean tide atlas: design and performance, Ocean Sci., 17, 615–649, https://doi.org/10.5194/os-17-615-2021, 2021. a, b, c
Männel, B., Dobslaw, H., Dill, R., Glaser, S., Balidakis, K., Thomas, M., and Schuh, H.: Correcting surface loading at the observation level: impact on global GNSS and VLBI station networks, J. Geodesy, 93, 2003–2017, https://doi.org/10.1007/s00190-019-01298-y, 2019. a
Martín-Español, A., King, M. A., Zammit-Mangion, A., Andrews, S. B., Moore, P., and Bamber, J. L.: An assessment of forward and inverse GIA solutions for Antarctica, J. Geophys. Res.-Sol. Ea., 121, 6947–6965, https://doi.org/10.1002/2016JB013154, 2016. a, b
Matsuoka, K., Skoglund, A., Roth, G., de Pomereu, J., Griffiths, H., Headland, R., Herried, B., Katsumata, K., Le Brocq, A., Licht, K., Morgan, F., Neff, P. D., Ritz, C., Scheinert, M., Tamura, T., Van de Putte, A., van den Broeke, M., von Deschwanden, A., Deschamps-Berger, C., Van Liefferinge, B., Tronstad, S., and Melvær, Y.: Quantarctica, an integrated mapping environment for Antarctica, the Southern Ocean, and sub-Antarctic islands, Environ. Modell. Softw., 140, 105015, https://doi.org/10.1016/j.envsoft.2021.105015, 2021. a
Mémin, A., Boy, J.-P., and Santamaría-Gómez, A.: Correcting GPS measurements for non-tidal loading, GPS Solutions, 24, 45, https://doi.org/10.1007/s10291-020-0959-3, 2020. a
Nield, G. A., Barletta, V. R., Bordoni, A., King, M. A., Whitehouse, P. L., Clarke, P. J., Domack, E., Scambos, T. A., and Berthier, E.: Rapid bedrock uplift in the Antarctic Peninsula explained by viscoelastic response to recent ice unloading, Earth Planet. Sc. Lett., 397, 32–41, https://doi.org/10.1016/j.epsl.2014.04.019, 2014. a, b, c
Nield, G. A., King, M. A., Koulali, A., and Samrat, N.: Postseismic Deformation in the Northern Antarctic Peninsula Following the 2003 and 2013 Scotia Sea Earthquakes, J. Geophys. Res.-Sol. Ea., 128, e2023JB026685, https://doi.org/10.1029/2023JB026685, 2023. a, b
Otosaka, I. N., Shepherd, A., Ivins, E. R., Schlegel, N.-J., Amory, C., van den Broeke, M. R., Horwath, M., Joughin, I., King, M. D., Krinner, G., Nowicki, S., Payne, A. J., Rignot, E., Scambos, T., Simon, K. M., Smith, B. E., Sørensen, L. S., Velicogna, I., Whitehouse, P. L., A, G., Agosta, C., Ahlstrøm, A. P., Blazquez, A., Colgan, W., Engdahl, M. E., Fettweis, X., Forsberg, R., Gallée, H., Gardner, A., Gilbert, L., Gourmelen, N., Groh, A., Gunter, B. C., Harig, C., Helm, V., Khan, S. A., Kittel, C., Konrad, H., Langen, P. L., Lecavalier, B. S., Liang, C.-C., Loomis, B. D., McMillan, M., Melini, D., Mernild, S. H., Mottram, R., Mouginot, J., Nilsson, J., Noël, B., Pattle, M. E., Peltier, W. R., Pie, N., Roca, M., Sasgen, I., Save, H. V., Seo, K.-W., Scheuchl, B., Schrama, E. J. O., Schröder, L., Simonsen, S. B., Slater, T., Spada, G., Sutterley, T. C., Vishwakarma, B. D., van Wessem, J. M., Wiese, D., van der Wal, W., and Wouters, B.: Mass balance of the Greenland and Antarctic ice sheets from 1992 to 2020, Earth Syst. Sci. Data, 15, 1597–1616, https://doi.org/10.5194/essd-15-1597-2023, 2023. a, b
Ray, J., Griffiths, J., Collilieux, X., and Rebischung, P.: Subseasonal GNSS positioning errors, Geophys. Res. Lett., 40, 5854–5860, https://doi.org/10.1002/2013GL058160, 2013. a
Ray, R. D. and Ponte, R. M.: Barometric tides from ECMWF operational analyses, Ann. Geophys., 21, 1897–1910, https://doi.org/10.5194/angeo-21-1897-2003, 2003. a
Ray, J.and Altamimi, Z., Collilieux, X., and van Dam, T.: Anomalous harmonics in the spectra of GPS position estimates, GPS Solut., 12, 55–64, https://doi.org/10.1007/s10291-007-0067-7, 2008. a
Raymond, C. A., Ivins, E. R., Heflin, M. B., and James, T. S.: Quasi-continuous global positioning system measurements of glacial isostatic deformation in the Northern Transantarctic Mountains, Global Planet. Chang., 42, 295–303, https://doi.org/10.1016/j.gloplacha.2003.11.013, 2004. a
Rülke, A., Dietrich, R., Capra, A., Cisak, J., Dongchen, E., Eiken, T., Fox, A., Hothem, L. D., Johnston, G., Malaimani, E., A. J., M., Milinevsky, G., Schenke, H.-W., Shibuya, K., Sjöberg, L. E., Zakrajsek, A., Fritsche, M., Groh, A., Knöfel, C., and Scheinert, M.: The Antarctic Regional GPS Network Densification: Status and Results, in: IAG 150 Years, edited by: Rizos, C. and Willis, P., Springer International Publishing, Cham, 133–139, ISBN 978-3-319-30895-1, 2015. a, b
Samrat, N. H., King, M. A., Watson, C., Hooper, A., Chen, X., Barletta, V. R., and Bordoni, A.: Reduced ice mass loss and three-dimensional viscoelastic deformation in northern Antarctic Peninsula inferred from GPS, Geophys. J. Int., 222, 1013–1022, https://doi.org/10.1093/gji/ggaa229, 2020. a
Samrat, N. H., King, M. A., Watson, C., Hay, A., Barletta, V. R., and Bordoni, A.: Upper Mantle Viscosity Underneath Northern Marguerite Bay, Antarctic Peninsula Constrained by Bedrock Uplift and Ice Mass Variability, Geophys. Res. Lett., 48, e2021GL097065, https://doi.org/10.1029/2021GL097065, 2021. a
Savchyn, I., Brusak, I., and Tretyak, K.: Analysis of recent Antarctic plate kinematics based on GNSS data, Geodesy Geodynam., 14, 99–110, https://doi.org/10.1016/j.geog.2022.08.004, 2023. a, b
Scheinert, M., Ivins, E., Dietrich, R., and Rülke, A.: Vertical Crustal Deformation in Dronning Maud Land, Antarctica: Observation versus Model Prediction, Springer Berlin Heidelberg, Berlin, Heidelberg, 357–360, ISBN 978-3-540-32934-3, https://doi.org/10.1007/3-540-32934-X_44, 2006. a
Scheinert, M., Engels, O., Schrama, E. J. O., van der Wal, W., and Horwath, M.: Geodetic observations for constraining mantle processes in Antarctica, in: Geochemistry and Geophysics of the Antarctic Mantle, edited by: Maritn, A. P. and van der Wal, W., Geological Society Memoir, London, 295–313, ISBN 1-78620-586-6, https://doi.org/10.1144/m56-2021-22, 2023. a, b
Sušnik, A., Dach, R., Villiger, A., Maier, A., Arnold, D., Schaer, S., and Jäggi, A.: CODE reprocessing product series, AIUB (Astronomical Institute of Bern) [data set], https://doi.org/10.7892/boris.80011, 2016. a
Thomas, I. D., King, M. A., Bentley, M. J., Whitehouse, P. L., Penna, N. T., Williams, S. D. P., Riva, R. E. M., Lavallee, D. A., Clarke, P. J., King, E. C., Hindmarsh, R. C. A., and Koivula, H.: Widespread low rates of Antarctic glacial isostatic adjustment revealed by GPS observations, Geophys. Res. Lett., 38, L22302, https://doi.org/10.1029/2011GL049277, 2011. a
Tregoning, P. and Watson, C.: Atmospheric effects and spurious signals in GPS analyses, J. Geophys. Res.-Sol. Ea., 114, B09403, https://doi.org/10.1029/2009JB006344, 2009. a
Tregoning, P., Twilley, B., Hendy, M., and Zwartz, D.: Monitoring Isostatic Rebound in Antarctica with the Use of Continuous Remote GPS Observations, GPS Solut., 2, 70–75, https://doi.org/10.1007/PL00012759, 1999. a
Tregoning, P., Welsh, A., McQueen, H., and Lambeck, K.: The search for postglacial rebound near the Lambert Glacier, Antarctica, Earth Planet. Space, 52, 1037–1041, https://doi.org/10.1186/BF03352327, 2000. a
VanderPlas, J. T.: Understanding the Lomb–Scargle Periodogram, Astrophys. J. Suppl. Ser., 236, 16, https://doi.org/10.3847/1538-4365/aab766, 2018. a
Vardić, K., Clarke, P. J., and Whitehouse, P. L.: A GNSS velocity field for crustal deformation studies: The influence of glacial isostatic adjustment on plate motion models, Geophys. J. Int., 231, 426–458, https://doi.org/10.1093/gji/ggac047, 2022. a
Vázquez Becerra, G. E.: Geodesy in Antarctica: A Pilot Study Based on the TAMDEF GPS Network, Victoria Land, Antarctica, Ph.D. thesis, Ohio State University, Division of Geodetic Science, 2009. a
Webb, F. H. and Zumberge, J. F.: An introduction to GIPSY/OASIS-II precision software for the analysis of data from the Global Positioning System, Jet Propulsion Laboratory, Pasadena, California, 1995. a
Wessel, P., Luis, J. F., Uieda, L., Scharroo, R., Wobbe, F., Smith, W. H. F., and Tian, D.: The Generic Mapping Tools Version 6, Geochem. Geophy. Geosy., 20, 5556–5564, https://doi.org/10.1029/2019GC008515, 2019. a
Whitehouse, P., Clarke, P. J., Koulali, A., King, M. A., Wilson, T. J., Saddler, D. M., Maxfield, D. J., Nylen, T., and Pettit, J.: UKANET: Logistical Challenges and Preliminary Results from a Geodetic Network Recording Crustal Deformation in Antarctica, in: AGU Fall Meeting Abstracts, vol. 2020, C032–11, 2020. a
Whitehouse, P. L.: Glacial isostatic adjustment modelling: historical perspectives, recent advances, and future directions, Earth Surf. Dynam., 6, 401–429, https://doi.org/10.5194/esurf-6-401-2018, 2018. a
Wilson, T., Bevis, M., Konfal, S., Saddler, D., Kendrick, E., Matheny, P., Bartletta, V., Smalley, R., Dalziel, I., Aster, R., Nyblade, A., and Wiens, D.: Understanding the mismatch between measured and model-predicted crustal motions across West Antarctica: Insights from POLENET-ANET GPS results, in: Workshop on Glacial Isostatic Adjustment, Ice Sheets, and Sea-level Change–Observations, Analysis, and Modelling, 24-26 September, Ottawa, Canada, 24–26, 2019. a
Wolstencroft, M., King, M. A., Whitehouse, P. L., Bentley, M. J., Nield, G. A., King, E. C., McMillan, M., Shepherd, A., Barletta, V., Bordoni, A., Riva, R. E., Didova, O., and Gunter, B. C.: Uplift rates from a new high-density GPS network in Palmer Land indicate significant late Holocene ice loss in the southwestern Weddell Sea, Geophys. J. Int., 203, 737–754, https://doi.org/10.1093/gji/ggv327, 2015. a
Zanutta, A., Negusini, M., Vittuari, L., Cianfarra, P., Salvini, F., Mancini, F., Sterzai, P., Dubbini, M., Galeandro, A., and Capra, A.: Monitoring geodynamic activity in the Victoria Land, East Antarctica: Evidence from GNSS measurements, J. Geodynam., 110, 31–42, https://doi.org/10.1016/j.jog.2017.07.008, 2017. a, b, c
Zanutta, A., Negusini, M., Vittuari, L., Martelli, L., Cianfarra, P., Salvini, F., Mancini, F., Sterzai, P., Dubbini, M., and Capra, A.: New Geodetic and Gravimetric Maps to Infer Geodynamics of Antarctica with Insights on Victoria Land, Remote Sens., 10, 1608, https://doi.org/10.3390/rs10101608, 2018. a
Zumberge, J. F., Heflin, M. B., Jefferson, D. C., Watkins, M. M., and Webb, F. H.: Precise point positioning for the efficient and robust analysis of GPS data from large networks, J. Geophys. Res.-Sol. Ea., 102, 5005–5017, https://doi.org/10.1029/96JB03860, 1997. a
Short summary
Geodetic GPS measurements in Antarctica have been used to track bedrock displacement, which is vital for understanding geodynamic processes such as plate motion and glacial isostatic adjustment. However, the potential of GPS data has been limited by its partially fragmented availability and unreliable metadata. A new dataset, which spans the period from 1995 to 2021, offers consistently processed coordinate time series for 286 GPS sites and promises to enhance future geodynamic research.
Geodetic GPS measurements in Antarctica have been used to track bedrock displacement, which is...
Altmetrics
Final-revised paper
Preprint