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Description

This data set contains a bed topography and bathymetry map of Greenland based on mass conservation, multi-beam data, and other techniques. It also includes surface elevation and ice thickness data, as well as an ice/ocean/land mask.

Version Description

Generated ensemble of bed topography maps using ICESat-2 time series and used the median depth instead of a single estimate for some glaciers; Used ice thickness estimates from IceBoost for periphery glaciers; Added a new field 'RGI' that indicates which pixel belongs to a glacier in the Randolph Glacier Inventory; Added bathymetry data from the Danish Hydrographic Office -Updated bathymetry of Petermann based on Ciraci et al. (2023) gravity inversion

Product Summary

Platforms
NASA DC-8 ,
P-3B
Instruments
MCoRDS
Projects
MULTI_NASA
Spatial Extent

N: 84 S: 59 E: 9 W: -90

Spatial Resolution
150 Meters x 150 Meters
Spatial Reference System(s)
WGS 84 / NSIDC Sea Ice Polar Stereographic North (EPSG:3413)
Location
GREENLAND
Coordinate System
CARTESIAN
Granule Spatial Representation
GEODETIC
Temporal Extent
1993-01-01 to 2021-12-31
Concept ID
C3903728370-NSIDC_CPRD
Data State
COMPLETE
Number of Files/Granules
2
Processing Level
4
Published
Science Keywords
Bathymetry ,
Bed Elevation ,
Glacier/Ice Sheet Thickness ,
Terrain Elevation

Citation

Citation is critically important for dataset documentation and discovery. This dataset is openly shared, without restriction, in accordance with the EOSDIS Data Use and Citation Guidance.

Copy Citation

Morlighem, M., & et al. (2025). IceBridge BedMachine Greenland, Version 6 [Dataset]. NASA National Snow and Ice Data Center Distributed Active Archive Center. https://doi.org/10.5067/6B6B225B8V2D Date Accessed: 2026-08-09

Documents

Publications Citing This Dataset

Filters
Title Year Author Topic
A vast valley network beneath the Greenland Ice Sheet Chartrand, Allison M., MacGregor, Joseph A., Morlighem, Mathieu, Sergienko, Olga V., Ockenden, Helen, Colgan, William T., Cheng, Gong Bathymetry, Bed Elevation, Glacier/Ice Sheet Thickness, Terrain Elevation, Glacier Extent, Ice Velocity, Snow Grain Size, Surface Morphology, Glacier Elevation/Ice Sheet Elevation
Inferring subglacial topography using physics informed machine learning constrained by two conservation laws Krishna, Mansa, Cheng, Gong, Morlighem, Mathieu Bathymetry, Bed Elevation, Glacier/Ice Sheet Thickness, Terrain Elevation, Glacier Elevation/Ice Sheet Elevation, Glacier Thickness/Ice Sheet Thickness, Firn Air Content
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