This article was accepted into the corpus but its outbound wikilinks were never NER-processed — typical at the deepest BFS hop or when the run's entity cap was reached. No expansion funnel to show.
| BedMachine | |
|---|---|
| Name | BedMachine |
| Subject | Antarctic and Greenland ice-sheet bed mapping |
| Developers | University of California, San Diego; British Antarctic Survey; National Aeronautics and Space Administration; Norwegian Polar Institute |
| First release | 2013 |
| Latest release | 2019 |
| Genre | Glaciology; geophysical mapping; computational modeling |
| License | Open data |
BedMachine
BedMachine is a high-resolution basal topography and ice-thickness dataset for the Antarctic Peninsula, Greenland Ice Sheet, and other polar regions that synthesizes airborne and satellite observations with geophysical inversion. The product provides bed elevation, ice thickness, and grounded/floatation boundaries used by researchers in glaciology, climate science, and oceanography to assess ice-sheet stability, grounding-line migration, and potential sea-level contributions. It is widely incorporated into analyses by agencies such as NASA, European Space Agency, and national polar institutes.
BedMachine delivers gridded maps of sub-ice-bed topography and ice thickness derived from combining radar sounding, gravity, and altimetry with ice-flow constraints to resolve basal geometries beneath the Antarctic Ice Sheet, Greenland, and peripheral ice caps. The dataset is designed to support work on ice-sheet dynamics, outlet glaciers, grounding lines, and pathways for warm water intrusion that affect ice mass loss. Users include teams at Scripps Institution of Oceanography, University of Colorado Boulder, University of Cambridge, and national agencies monitoring cryospheric change.
The BedMachine methodology integrates airborne radar sounding surveys from platforms operated by British Antarctic Survey, NASA, and the Australian Antarctic Division with satellite altimetry from missions such as ICESat, ICESat-2, and CryoSat-2. Gravity inversion leverages data from campaigns tied to National Aeronautics and Space Administration airborne gravimeters and satellite-derived gravity fields used in studies by California Institute of Technology and the Jet Propulsion Laboratory. Ice-surface velocities are incorporated from feature-tracking and interferometric products produced by European Space Agency and Danish Meteorological Institute teams. Constraints include bedrock geology mapping from institutions like the United States Geological Survey and seismic reflection surveys by organizations such as the National Science Foundation. Computational inversion and mass-conservation techniques were developed in collaboration with researchers at University of California, Los Angeles and University of Washington.
BedMachine revealed previously uncharted over-deepened troughs, fjords, and reverse-sloped basins beneath outlet glaciers, altering assessments of marine ice-sheet vulnerability in regions including the Amundsen Sea Embayment, Pine Island Glacier, and Thwaites Glacier. High-resolution maps show deep channels that connect ice fronts to warm circumpolar deep water studied by NOAA and Woods Hole Oceanographic Institution, clarifying mechanisms of basal melting observed by British Antarctic Survey campaigns. The maps also refined ice-thickness estimates across Greenland, improving regional mass-balance work by groups at Danish Meteorological Institute and GEUS.
BedMachine outputs are used in ice-sheet model initializations at centers such as Los Alamos National Laboratory, National Center for Atmospheric Research, and Potsdam Institute for Climate Impact Research to simulate grounding-line migration and transient ice loss. Coastal impact assessments by Intergovernmental Panel on Climate Change authors and national adaptation agencies rely on BedMachine-informed sea-level rise projections, and ocean-modelers at Scripps Institution of Oceanography use bed geometries to route sub-ice-shelf circulation. Legal and policy analyses concerning coastal hazards in jurisdictions represented by institutions like NOAA and United Kingdom Hydrographic Office also reference BedMachine-derived projections.
Sources of uncertainty include data gaps where airborne radar or gravity coverage is sparse, reliance on noisy satellite altimetry in steep terrain observed in studies by European Space Agency mission teams, and assumptions in inversion regularization developed by academic groups at University of Cambridge and University of Oxford. Error propagation affects grounding-line placement that is critical for projections assessed in IPCC reports. Rapid basal changes documented by field campaigns from British Antarctic Survey and National Science Foundation can outpace static BedMachine releases, necessitating updates and model sensitivity testing by groups at University of Maine and University of Alaska Fairbanks.
BedMachine originated from collaborative efforts led by researchers at Scripps Institution of Oceanography and the British Antarctic Survey who combined radar, gravity, and mass-conservation approaches first formalized in the early 2010s. Subsequent releases incorporated contributions from NASA airborne campaigns, international radar surveys coordinated with the Polar Geospatial Center, and synthesis work by teams at University of California, San Diego and Norwegian Polar Institute. Key updates followed major field campaigns targeting Pine Island Glacier and Thwaites Glacier, with methodology papers appearing in journals associated with American Geophysical Union and European Geosciences Union conferences.
BedMachine is frequently compared to other bed and ice-thickness compilations such as datasets produced by the Scientific Committee on Antarctic Research—including the Bedmap series—and regional products from the National Snow and Ice Data Center and Centre for Polar Observation and Modelling. Modelers contrast BedMachine basal geometries with outputs from ice-sheet models like the ones developed at ICES (University of Copenhagen) and the University of Bristol to evaluate sensitivity to bed uncertainty. Integrations with ocean models from institutions such as Woods Hole Oceanographic Institution and NOAA help test implications for sub-ice-shelf melt and future ice dynamics.