Articles | Volume 17, issue 4
https://doi.org/10.5194/essd-17-1667-2025
© 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-17-1667-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Airborne gravimetry with quantum technology: observations from Iceland and Greenland
Department of Space Research and Technology, Technical University of Denmark (DTU Space), Elektrovej 328, 2800 Kgs. Lyngby, Denmark
Bjørnar Dale
Department of Space Research and Technology, Technical University of Denmark (DTU Space), Elektrovej 328, 2800 Kgs. Lyngby, Denmark
Andreas Stokholm
Department of Space Research and Technology, Technical University of Denmark (DTU Space), Elektrovej 328, 2800 Kgs. Lyngby, Denmark
René Forsberg
Department of Space Research and Technology, Technical University of Denmark (DTU Space), Elektrovej 328, 2800 Kgs. Lyngby, Denmark
Alexandre Bresson
DPHY, ONERA, Université Paris Saclay, Palaiseau, France
Nassim Zahzam
DPHY, ONERA, Université Paris Saclay, Palaiseau, France
Alexis Bonnin
DPHY, ONERA, Université Paris Saclay, Palaiseau, France
Yannick Bidel
DPHY, ONERA, Université Paris Saclay, Palaiseau, France
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Andreas Stokholm, Jørgen Buus-Hinkler, Tore Wulf, Anton Korosov, Roberto Saldo, Leif Toudal Pedersen, David Arthurs, Ionut Dragan, Iacopo Modica, Juan Pedro, Annekatrien Debien, Xinwei Chen, Muhammed Patel, Fernando Jose Pena Cantu, Javier Noa Turnes, Jinman Park, Linlin Xu, Katharine Andrea Scott, David Anthony Clausi, Yuan Fang, Mingzhe Jiang, Saeid Taleghanidoozdoozan, Neil Curtis Brubacher, Armina Soleymani, Zacharie Gousseau, Michał Smaczny, Patryk Kowalski, Jacek Komorowski, David Rijlaarsdam, Jan Nicolaas van Rijn, Jens Jakobsen, Martin Samuel James Rogers, Nick Hughes, Tom Zagon, Rune Solberg, Nicolas Longépé, and Matilde Brandt Kreiner
The Cryosphere, 18, 3471–3494, https://doi.org/10.5194/tc-18-3471-2024, https://doi.org/10.5194/tc-18-3471-2024, 2024
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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 and the age and ice floe size – using multiple sources of satellite and weather data across the Canadian and Greenlandic Arctic. Professionally drawn operational sea ice charts were used as a reference. A total of 179 students and sea ice and AI specialists participated and produced maps in broad agreement with the sea ice charts.
Alice C. Frémand, Peter Fretwell, Julien A. Bodart, Hamish D. Pritchard, Alan Aitken, Jonathan L. Bamber, Robin Bell, Cesidio Bianchi, Robert G. Bingham, Donald D. Blankenship, Gino Casassa, Ginny Catania, Knut Christianson, Howard Conway, Hugh F. J. Corr, Xiangbin Cui, Detlef Damaske, Volkmar Damm, Reinhard Drews, Graeme Eagles, Olaf Eisen, Hannes Eisermann, Fausto Ferraccioli, Elena Field, René Forsberg, Steven Franke, Shuji Fujita, Yonggyu Gim, Vikram Goel, Siva Prasad Gogineni, Jamin Greenbaum, Benjamin Hills, Richard C. A. Hindmarsh, Andrew O. Hoffman, Per Holmlund, Nicholas Holschuh, John W. Holt, Annika N. Horlings, Angelika Humbert, Robert W. Jacobel, Daniela Jansen, Adrian Jenkins, Wilfried Jokat, Tom Jordan, Edward King, Jack Kohler, William Krabill, Mette Kusk Gillespie, Kirsty Langley, Joohan Lee, German Leitchenkov, Carlton Leuschen, Bruce Luyendyk, Joseph MacGregor, Emma MacKie, Kenichi Matsuoka, Mathieu Morlighem, Jérémie Mouginot, Frank O. Nitsche, Yoshifumi Nogi, Ole A. Nost, John Paden, Frank Pattyn, Sergey V. Popov, Eric Rignot, David M. Rippin, Andrés Rivera, Jason Roberts, Neil Ross, Anotonia Ruppel, Dustin M. Schroeder, Martin J. Siegert, Andrew M. Smith, Daniel Steinhage, Michael Studinger, Bo Sun, Ignazio Tabacco, Kirsty Tinto, Stefano Urbini, David Vaughan, Brian C. Welch, Douglas S. Wilson, Duncan A. Young, and Achille Zirizzotti
Earth Syst. Sci. Data, 15, 2695–2710, https://doi.org/10.5194/essd-15-2695-2023, https://doi.org/10.5194/essd-15-2695-2023, 2023
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This paper presents the release of over 60 years of ice thickness, bed elevation, and surface elevation data acquired over Antarctica by the international community. These data are a crucial component of the Antarctic Bedmap initiative which aims to produce a new map and datasets of Antarctic ice thickness and bed topography for the international glaciology and geophysical community.
Nicolaj Hansen, Louise Sandberg Sørensen, Giorgio Spada, Daniele Melini, Rene Forsberg, Ruth Mottram, and Sebastian B. Simonsen
The Cryosphere Discuss., https://doi.org/10.5194/tc-2023-104, https://doi.org/10.5194/tc-2023-104, 2023
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We use ICESat-2 to estimate the surface elevation change over Greenland and Antarctica in the period of 2018 to 2021. Numerical models have been used the compute the firn compaction and the vertical bedrock movement so non-mass-related elevation changes can be taken into account. We have made a parameterization of the surface density so we can convert the volume change to mass change. We find that Antarctica has lost 135.7±27.3 Gt per year, and the Greenland ice sheet 237.5±14.0 Gt per year.
Andreas Stokholm, Andrzej Kucik, Nicolas Longépé, and Sine Munk Hvidegaard
EGUsphere, https://doi.org/10.5194/egusphere-2023-976, https://doi.org/10.5194/egusphere-2023-976, 2023
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To navigate in the Arctic, vessels utilise maps of the local sea ice conditions, that are manually drawn daily. This is a time-consuming and labour-intensive task, which we are trying to automate using convolutional neural networks. In this article, we investigate combining the outputs of models trained with different objectives, leveraging the strengths and avoiding weaknesses to create precise and detailed sea ice concentration maps for navigation in the Arctic and climate or weather models.
Inès N. Otosaka, Andrew Shepherd, Erik R. Ivins, Nicole-Jeanne Schlegel, Charles Amory, Michiel R. van den Broeke, Martin Horwath, Ian Joughin, Michalea D. King, Gerhard Krinner, Sophie Nowicki, Anthony J. Payne, Eric Rignot, Ted Scambos, Karen M. Simon, Benjamin E. Smith, Louise S. Sørensen, Isabella Velicogna, Pippa L. Whitehouse, Geruo A, Cécile Agosta, Andreas P. Ahlstrøm, Alejandro Blazquez, William Colgan, Marcus E. Engdahl, Xavier Fettweis, Rene Forsberg, Hubert Gallée, Alex Gardner, Lin Gilbert, Noel Gourmelen, Andreas Groh, Brian C. Gunter, Christopher Harig, Veit Helm, Shfaqat Abbas Khan, Christoph Kittel, Hannes Konrad, Peter L. Langen, Benoit S. Lecavalier, Chia-Chun Liang, Bryant D. Loomis, Malcolm McMillan, Daniele Melini, Sebastian H. Mernild, Ruth Mottram, Jeremie Mouginot, Johan Nilsson, Brice Noël, Mark E. Pattle, William R. Peltier, Nadege Pie, Mònica Roca, Ingo Sasgen, Himanshu V. Save, Ki-Weon Seo, Bernd Scheuchl, Ernst J. O. Schrama, Ludwig Schröder, Sebastian B. Simonsen, Thomas Slater, Giorgio Spada, Tyler C. Sutterley, Bramha Dutt Vishwakarma, Jan Melchior van Wessem, David Wiese, Wouter van der Wal, and Bert Wouters
Earth Syst. Sci. Data, 15, 1597–1616, https://doi.org/10.5194/essd-15-1597-2023, https://doi.org/10.5194/essd-15-1597-2023, 2023
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By measuring changes in the volume, gravitational attraction, and ice flow of Greenland and Antarctica from space, we can monitor their mass gain and loss over time. Here, we present a new record of the Earth’s polar ice sheet mass balance produced by aggregating 50 satellite-based estimates of ice sheet mass change. This new assessment shows that the ice sheets have lost (7.5 x 1012) t of ice between 1992 and 2020, contributing 21 mm to sea level rise.
Martin Horwath, Benjamin D. Gutknecht, Anny Cazenave, Hindumathi Kulaiappan Palanisamy, Florence Marti, Ben Marzeion, Frank Paul, Raymond Le Bris, Anna E. Hogg, Inès Otosaka, Andrew Shepherd, Petra Döll, Denise Cáceres, Hannes Müller Schmied, Johnny A. Johannessen, Jan Even Øie Nilsen, Roshin P. Raj, René Forsberg, Louise Sandberg Sørensen, Valentina R. Barletta, Sebastian B. Simonsen, Per Knudsen, Ole Baltazar Andersen, Heidi Ranndal, Stine K. Rose, Christopher J. Merchant, Claire R. Macintosh, Karina von Schuckmann, Kristin Novotny, Andreas Groh, Marco Restano, and Jérôme Benveniste
Earth Syst. Sci. Data, 14, 411–447, https://doi.org/10.5194/essd-14-411-2022, https://doi.org/10.5194/essd-14-411-2022, 2022
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Global mean sea-level change observed from 1993 to 2016 (mean rate of 3.05 mm yr−1) matches the combined effect of changes in water density (thermal expansion) and ocean mass. Ocean-mass change has been assessed through the contributions from glaciers, ice sheets, and land water storage or directly from satellite data since 2003. Our budget assessments of linear trends and monthly anomalies utilise new datasets and uncertainty characterisations developed within ESA's Climate Change Initiative.
Nicolaj Hansen, Peter L. Langen, Fredrik Boberg, Rene Forsberg, Sebastian B. Simonsen, Peter Thejll, Baptiste Vandecrux, and Ruth Mottram
The Cryosphere, 15, 4315–4333, https://doi.org/10.5194/tc-15-4315-2021, https://doi.org/10.5194/tc-15-4315-2021, 2021
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We have used computer models to estimate the Antarctic surface mass balance (SMB) from 1980 to 2017. Our estimates lies between 2473.5 ± 114.4 Gt per year and 2564.8 ± 113.7 Gt per year. To evaluate our models, we compared the modelled snow temperatures and densities to in situ measurements. We also investigated the spatial distribution of the SMB. It is very important to have estimates of the Antarctic SMB because then it is easier to understand global sea level changes.
Cited articles
Bamber, J. L., Layberry, R. L., and Gogineni, S. P.: A new ice thickness and bed data set for the Greenland ice sheet: 1. Measurement, data reduction, and errors, J. Geophys. Res.-Atmos., 106, 33773–33780, https://doi.org/10.1029/2001JD900054, 2001. a
Becker, D., Nielsen, J. E., Ayres-Sampaio, D., Forsberg, R., Becker, M., and Bastos, L.: Drift reduction in strapdown airborne gravimetry using a simple thermal correction, J. Geodesy, 89, 1133–1144, https://doi.org/10.1007/s00190-015-0839-8, 2015. a
Bidel, Y., Zahzam, N., Blanchard, C., Bonnin, A., Cadoret, M., Bresson, A., Rouxel, D., and Lequentrec-Lalancette, M.-F.: Absolute marine gravimetry with matter-wave interferometry, Nat. Commun., 9, 2041–1723, https://doi.org/10.1038/s41467-018-03040-2, 2018. a, b
Bidel, Y., Zahzam, N., Bresson, A., Blanchard, C., Cadoret, M., Olesen, A. V., and Forsberg, R.: Absolute airborne gravimetry with a cold atom sensor, J. Geodesy, 94, 1432–1394, https://doi.org/10.1007/s00190-020-01350-2, 2020. a, b, c, d
Bidel, Y., Zahzam, N., Bresson, A., Blanchard, C., Bonnin, A., Bernard, J., Cadoret, M., Jensen, T. E., Forsberg, R., Salaun, C., Lucas, S., Lequentrec-Lalancette, M. F., Rouxel, D., Gabalda, G., Seoane, L., Vu, D. T., Bruinsma, S., and Bonvalot, S.: Airborne absolute gravimetry with a quantum sensor, comparison with classical technologies, J. Geophys. Res.-Sol. Ea., 128, e2022JB025921, https://doi.org/10.1029/2022JB025921, 2023. a, b
Bresson, A., Zahzam, N., Bidel, Y., Olesen, A. V., and Forsberg, R.: Cold atom gravimetry airborne campaign 2017, ESA Earth Online, https://doi.org/10.57780/esa-b0ed0a3, 2023. a
Brozena, J. M.: The Greenland Aerogeophysics Project: airborne gravity, topographic and magnetic mapping of an entire continent, in: From Mars to Greenland: Charting Gravity With Space and Airborne Instruments, edited by: Colombo, O. L., Springer New York, New York, NY, 203–214, https://doi.org/10.1007/978-1-4613-9255-2_19, 1992. a
Forsberg, R.: A study of terrain reductions, density anomalies and geophysical inversion methods in gravity field modelling, Reports of the Department of Geodetic Science and Surveying 355, The Ohio State University, Department of Geodetic Science and Surveying, Columbus, Ohio, https://doi.org/10.21236/ADA150788, 1984. a
Forsberg, R.: A new covariance model for inertial gravimetry and gradiometry, J. Geophys. Res.-Sol. Ea., 92, 1305–1310, https://doi.org/10.1029/JB092iB02p01305, 1987. a
Forsberg, R. and Jensen, T.: New geoid of Greenland: a case study of terrain and ice effects, GOCE and use of local sea level data, in: IGFS 2014, edited by: Jin, S. and Barzaghi, R., Springer International Publishing, Cham, 153–159, https://doi.org/10.1007/1345_2015_50, 2016. a
Förste, C., Bruinsma, S. L., Abrikosov, O., Lemoine, J.-M., Marty, J. C., Flechtner, F., Balmino, G., Barthelmes, F., and Biancale, R.: EIGEN-6C4 the latest combined global gravity field model including GOCE data up to degree and order 2190 of GFZ Potsdam and GRGS Toulouse, GFZ Data Services, https://doi.org/10.5880/ICGEM.2015.1, 2014. a
Glennie, C. L., Schwarz, K. P., Bruton, A. M., Forsberg, R., Olesen, A. V., and Keller, K.: A comparison of stable platform and strapdown airborne gravity, in: Geodesy Beyond 2000, edited by: Schwarz, K.-P., Springer Berlin Heidelberg, Berlin, Heidelberg, 383–389, https://doi.org/10.1007/978-3-642-59742-8_20, 2000. a
Groves, P. D.: GNSS, Inertial, and Multisensor Integrated Navigation Systems, 2nd edn., Artech House, Boston, London, ISBN 978-1608070053, 2013. a
Halldórsson, S. A., Marshall, E. W., Caracciolo, A., Matthews, S., Bali, E., Rasmussen, M. B., Ranta, E., Robin, J. G., Guðfinnsson, G. H., Sigmarsson, O., Maclennan, J., Jackson, M. G., Whitehouse, M. J., Jeon, H., van der Meer, Q. H. A., Mibei, G. K., Kalliokoski, M. H., Repczynska, M. M., Rúnarsdóttir, R. H., Sigurðsson, G., Pfeffer, M. A., Scott, S. W., Kjartansdóttir, R., Kleine, B. I., Oppenheimer, C., Aiuppa, A., Ilyinskaya, E., Bitetto, M., Giudice, G., and Stefánsson, A.: Rapid shifting of a deep magmatic source at Fagradalsfjall volcano, Iceland, Nature, 609, 1476–4687, https://doi.org/10.1038/s41586-022-04981-x, 2022. a
Jekeli, C.: Inertial Navigation Systems with Geodetic Applications, De Gruyter, Berlin, Boston, https://doi.org/10.1515/9783110800234, 2001. a
Jensen, T. E.: Spatial resolution of airborne gravity estimates in Kalman filtering, Journal of Geodetic Science, 12, 185–194, https://doi.org/10.1515/jogs-2022-0143, 2022. a
Jensen, T. E.: iMAR iNAT-RQH-4001, Technical University of Denmark, https://doi.org/10.11583/DTU.25673604.v1, 2024. a, b
Jensen, T. E., Olesen, A. V., Forsberg, R., Olsson, P.-A., and Josefsson, O.: New results from strapdown airborne gravimetry using temperature stabilisation, Remote Sens., 11, 2682, https://doi.org/10.3390/rs11222682, 2019. a
Jensen, T. E., Forsberg, R., Bidel, Y., Zahzam, N., Bonnin, A., and Bresson, A.: Airborne Quantum Gravimetry (AirQuantumGrav 2023), ESA Earth Online [data set], https://doi.org/10.57780/esa-58c58c5, 2024. a, b
Johann, F., Becker, D., Becker, M., Forsberg, R., and Kadir, M.: The Direct Method in Strapdown Airborne Gravimetry – A Review, ZFV, 5, https://doi.org/10.12902/zfv-0263-2019, 2019. a
Lawrence, A.: The Pendulous Accelerometer, Springer New York, New York, NY, 57–71, https://doi.org/10.1007/978-1-4612-1734-3_5, 1998. a
Moritz, H.: Geodetic reference system 1980, J. Geodesy, 74, 1432–1394, https://doi.org/10.1007/s001900050278, 2000. a
Pagli, C., Sigmundsson, F., Árnadóttir, T., Einarsson, P., and Sturkell, E.: Deflation of the Askja volcanic system: constraints on the deformation source from combined inversion of satellite radar interferograms and GPS measurements, J. Volcanol. Geoth. Res., 152, 97–108, https://doi.org/10.1016/j.jvolgeores.2005.09.014, 2006. a
Sigmundsson, F., Parks, M., Hooper, A., Geirsson, H., Vogfjörd, K. S., Drouin, V., Ófeigsson, B. G., Hreinsdóttir, S., Hjaltadóttir, S., Jónsdóttir, K., Einarsson, P., Barsotti, S., Horálek, J., and Ágústsdóttir, T.: Deformation and seismicity decline before the 2021 Fagradalsfjall eruption, Nature, 609, 1476–4687, https://doi.org/10.1038/s41586-022-05083-4, 2022. a
Tino, G. and Kasevich, M.: Atom Interferometry: Proceedings of the International School of Physics “Enrico Fermi”, Course 188, Varenna on Lake Como, Villa Monastero, 15–20 July 2013, International School of Physics Enrico Fermi Series, IOS Press, https://books.google.dk/books?id=OV7IrQEACAAJ, 2014. a
Torge, W., Müller, J., and Pail, R.: Geodesy, 5th edn., De Gruyter, Berlin, Boston, ISBN 978-3-11-072329-8, 2023. a
Short summary
The availability of data from two airborne gravity campaigns using sensors based on both classical and quantum technology is presented. Data are made available by the European Space Agency as raw, intermediate, and final data products. Here “raw” refers to the sensor output, while “final” refers to the along-track gravity estimates. This makes the data relevant for users interested in applications ranging from data processing and quantum studies to geophysical studies using gravity observations.
The availability of data from two airborne gravity campaigns using sensors based on both...
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