Studying the geological conditions and processes on land, by the coast and offshore to monitor natural resources and climate. Programme areas include studying the Greenland ice sheet, land and sea, climate change adaptation, earthquakes and seismology and palaeoclimate.

The Nature and climate programme includes contributions from the following departments at GEUS:
  • Geochemistry
  • Geophysics
  • Glaciology and Climate
  • Groundwater and Quaternary Geology Mapping
  • Hydrology
  • Marine Geology
  • Reservoir Geology
  • Stratigraphy

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51 to 60 of 161 Results
Oct 28, 2023 - Programme for Monitoring of the Greenland Ice Sheet (PROMICE) and the Greenland Climate Network (GC-Net)
Khan, Shfaqat Abbas, 2023, "Greenland Ice Sheet Surface Elevation Change", https://doi.org/10.22008/FK2/GQJJEA, GEUS Dataverse, V2
Description Annual (April to April) elevation change rates of the Greenland Ice Sheet from April 2011 to April 2020 from CryoSat-2, ICESat-2 and NASA’s ATM flights on a 1x1 km grid. Methods We have used radar altimetry data from ESA’s Earth Explorer CryoSat-2 mission (Wingham et...
Oct 26, 2023 - Student reports
Larsen, E.; Storm, D., 2023, "Modelling Snow Water Equivalent, A Research Project with GEUS on Greenland Ice Sheet Data", https://doi.org/10.22008/FK2/NAPVQX, GEUS Dataverse, V1
Abstract: Measuring snow water equivalent (SWE) is time-consuming, costly, and at times even simply impossible in remote locations such as on the Greenland ice sheet. This motivates the modelling of SWE from more easily accessible input variables such as snow depth. This study ap...
Oct 9, 2023 - A380 Engine Search
Lines, Austin; Elliott, Joshua, 2023, "Ground penetrating radar data over the ONERA targets", https://doi.org/10.22008/FK2/XJPWLK, GEUS Dataverse, V1
Human-towed and robot-towed GPR lines over the ONERA targets from the 5th field campaign
Oct 9, 2023
Data associated with the A380 Engine Search. Mankoff, K. D. et al. (2020). Search and recovery of aircraft parts in ice-sheet crevasse fields using airborne and in situ geophysical sensors. Journal of Glaciology 66(257), 496–508. doi: 10.1017/ jog.2020.26
Sep 11, 2023
Larocca, L. J.; Twining–Ward, M.; Axford, Y.; Schweinsberg, A. D.; Larsen, S. H.; Westergaard–Nielsen, A.; Luetzenburg, G.; Briner, J. P.; Kjeldsen, K. K.; Bjørk, A. A., 2023, "Retreat rates of land-terminating glaciers in Greenland in the twentieth and twenty–first centuries", https://doi.org/10.22008/FK2/EUSXMI, GEUS Dataverse, V1
The dataset contains data published in this paper by Larocca et al. "Greenland–wide accelerated retreat of peripheral glaciers in the twenty–first century"
Aug 30, 2023
Karlsson, Nanna B.; Mankoff, Kenneth D.; Solgaard, Anne M., 2022, "Greenland Freshwater Flux on Glacier-basin Scales", https://doi.org/10.22008/FK2/BOVBVR, GEUS Dataverse, V5
This dataset contains derived mass loss data from marine-terminating glaciers in Greenland on a monthly timescale from 2010 up to and including 2020. Reference: Karlsson et al., 202, GEUS Bulletin (DOI: 10.34194/geusb.v53.833) File structure: Data for each glacier outlet are stor...
Aug 6, 2023 - Freshwater Runoff
Mankoff, Ken, 2020, "Streams, Outlets, Basins, and Discharge [k=1.0]", https://doi.org/10.22008/FK2/XKQVL7, GEUS Dataverse, V5
Greenland land and ice sheet streams, outlets, basins, and discharge. Routing assumes k = 1.0 for subglacial routing algorithm
Jul 19, 2023 - SICE - Arctic and Antarctic land ice snow and ice surface properties from Sentinel-3 OLCI
Picard, G.; Vandecrux, B.; Kokhanovsky, A.; Box, J.E., 2023, "Antarctica SSA and broadband albedo austral summer 2022/2023 from Sentinel-3’s OLCI and pySICEv1.6", https://doi.org/10.22008/FK2/QWN906, GEUS Dataverse, V1
Timespan 15 Oct, 2022 to 28 Feb 2023 Description 0.5 km daily SSA and broadband albedo. Albedo is 'spherical', meaning 'white sky' or 'diffuse', i.e. does not depend on the position of the sun. Data format is NetCDF. Embedded are attributes. We suggest using xarray to read the da...
Jul 4, 2023
Vandecrux, B., 2023, "Greenland ice sheet ice and firn temperature reconstruction at 10 m depth, 1950-2022", https://doi.org/10.22008/FK2/C24WVN, GEUS Dataverse, V3
This dataset contains monthly grids of 10 m subsurface temperatures (T10m) for the Greenland ice sheet between 1954 and 2022. These grids have been produced by an Artificial Neural Network (ANN) which take as input ERA5 snowfall and air temperatures and is trained on more than 45...
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