Data Set ID:

IceBridge BedMachine Greenland, Version 3

This data set contains a bed topography/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.

This is the most recent version of these data.

Version Summary:

Version 3 includes ocean bathymetry all around Greenland based on data from NASA’s Ocean Melting Greenland (OMG) and other campaigns of bathymetry measurements. The subglacial bed topography has also been updated by including more ice thickness data and constraining the ice thickness at the ice/ocean interface based on bathymetry data when available.

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Data Format(s):
  • NetCDF
Spatial Coverage:
N: 90, 
S: 60, 
E: 10, 
W: -80
Platform(s):DC-8, P-3B
Spatial Resolution:
  • 150 m x 150 m
Temporal Coverage:
  • 1 January 1993 to 31 December 2016
(updated 2018)
Temporal ResolutionNot specifiedMetadata XML:View Metadata Record
Data Contributor(s):Mathieu Morlighem

Geographic Coverage

Other Access Options

Other Access Options


As a condition of using these data, you must cite the use of this data set using the following citation. For more information, see our Use and Copyright Web page.

Morlighem, M. et al. 2017, updated 2018. IceBridge BedMachine Greenland, Version 3. [Indicate subset used]. Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center. doi: [Date Accessed].

Literature Citation

As a condition of using these data, we request that you acknowledge the author(s) of this data set by referencing the following peer-reviewed publication.

  • Morlighem, M., C. Williams, E. Rignot, L. An, J. E. Arndt, J. Bamber, G. Catania, N. Chauché, J. A. Dowdeswell, B. Dorschel, I. Fenty, K. Hogan, I. Howat, A. Hubbard, M. Jakobsson, T. M. Jordan, K. K. Kjeldsen, R. Millan, L. Mayer, J. Mouginot, B. Noël, C. O'Cofaigh, S. J. Palmer, S. Rysgaard, H. Seroussi, M. J. Siegert, P. Slabon, F. Straneo, M. R. van den Broeke, W. Weinrebe, M. Wood, and K. Zinglersen. 2017. BedMachine v3: Complete bed topography and ocean bathymetry mapping of Greenland from multi-beam echo sounding combined with mass conservation, Geophysical Research Letters. 44. .

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Detailed Data Description


The data are stored in one netCDF (.nc) file named

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Spatial Coverage

Spatial coverage for this data set currently includes Greenland and the Arctic.

Southernmost Latitude: 60° N
Northernmost Latitude: 90° N
Westernmost Longitude: 80° W
Easternmost Longitude: 10° E

Spatial Resolution

The output product is generated at 150 m resolution. The true resolution varies between 150 m and 5 km.


The following table provides details about the coordinate system for this data set.

Table 1. Geolocation Details
Geographic coordinate system WGS 84
Projected coordinate system WGS 84 / NSIDC Sea Ice Polar Stereographic North
Longitude of true origin -45° E
Latitude of true origin 70° N
Scale factor at longitude of true origin 1
Datum WGS 84
Ellipsoid/spheroid WGS 84
Units meters
False easting 0
False northing 0
EPSG code 3413
PROJ4 string +proj=stere +lat_0=90 +lat_ts=70 +lon_0=-45 +k=1 +x_0=0 +y_0=0 +datum=WGS84 +units=m +no_defs
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Temporal Coverage

The data were collected between 01 January 1993 and 31 December 2016. The nominal year of this data set is 2007.

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Parameter or Variable

Parameter Description

The BedMachine data file contains parameters as described in Table 2.

Table 2. File Parameters and Units
Parameter Name Description Units
bed Bed elevation (bed topography) Meters
errbed Bed topography/ice thickness error Meters
geoid Geoid height above WGS84 Ellipsoid Meters
mask mask (0 = ocean; 1 = ice-free land; 2 = grounded ice; 3 = floating ice; 4 = non-Greenland land) Flag values (0 - 4)
source data source, Mass Conservation/kriging/bathymetry: (0 = none; 1 = gimpdem; 2 = Mass conservation; 3 = synthetic; 4 = interpolation; 5 = hydrostatic equilibrium; 6 = kriging; 7 = RTOPO-2; 8 = gravity inversion; 10+ = bathymetry data) Flag values (0 - 40)
surface Ice surface elevation Meters
thickness Ice thickness Meters
x projection y coordinate Meters
y projection y coordinate Meters

Sample Data Record

Figure 1 illustrates Greenland bedrock altitude and ice thickness.

Figure 1. Greenland Bedrock Altitude and Ice Thickness

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Software and Tools

See the NetCDF Resources at NSIDC page for tools to work with netCDF files.

The netCDF data file is compatible with HDF5 libraries, and can be read by HDF readers such as HDFView. If the netCDF file reader you are using does not read the data, see and for information on updating the reader.

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Data Acquisition and Processing

Data Acquisition Methods

Source data used in deriving this product include:

  • Operation IceBridge radar-derived thickness data, posted at 30 – 60 m, with a vertical precision of 30 m, collected by the MCoRDS radar (IceBridge MCoRDS L2 Ice Thickness; IRMCR2).
  • Ice thickness data from the Doppler focused radar of the Technical University of Denmark (DTU) for the region of 79 North (Thomsen et al., 1997; Christensen et al., 2000) and Russell (Lindbäck et al., 2014).
  • Ice thickness data from the High CApability Radar Sounder (HiCARS; Peters et al., 2005; Peters et al., 2007) operated by the University of Texas, Institute for Geophysics
  • Ice thickness data from the Pathfinder Advanced Radar Ice Sounder (PARIS; Raney, 2010)
  • Ice thickness data from the Alfred Wegener Institute (AWI; Nixdorf et al., 1999)
  • Ice thickness data from Uppsala University (UU; Lindbäck et al., 2014), collected in the vicinity of Russell Gletscher
  • Multibeam echo sounding data from Oceans Melting Greenland (OMG Mission, 2016) along the coast of West and Southeast Greenland
  • Bathymetry data from Slabon et al. (2016) along the Northwest coast
  • Bathymetry data from Weinrebe et al. (2009) in Torssukataq and Uummannaq Fjords
  • Bathymetry data from O’Cofaigh et al. (2013) in Uummannaq Fjord
  • Bathymetry data from Dowdeswell et al. (2014), Rignot et al. (2015), Fried et al. (2015), and Rignot et al. (2016) in Uummannaq Fjord
  • Bathymetry data from Schumann et al. (2012), Holland et al. (2008) and Straneo et al. (2012) in Illulisat Icefjord
  • Bathymetry data from Mix et al. (2015) in front of Petermann Fjord and the adjacent Hall Basin
  • Bathymetry data from Sutherland et al. (2014) near Kangerdlussuaq
  • Bathymetry data from Dowdeswell et al. (2016) in Nordvestfjord
  • Bathymetry data from Chauché et al. (2014) near Lille Gletscher
  • Bathymetry data from Straneo et al. (2016) in Sermilik fjord
  • Bathymetry data from Motyka et al. (2017) in Godthåbsfjord
  • Bathymetry data from Stevens et al. (2016) in Sarqardleq fjord
  • Bathymetry data from Kjeldsen et al. (2017) in Timmiarmiut Fjord, Heimdal Glacier and Skjoldungen Fjord
  • Bathymetry data from Rysgaard et al. (2003) in Young Sound fjord
  • Bathymetry data from Bendtsen et al. (2017) near Flade Isblink Ice Cap
  • Single beam bathymetry data from Sutherland and Pickart (2008) on the continental shelf along the Southeast coast
  • Single beam data from Olex ( and crowd sourced data from fishing and recreational vessels (MaxSea).
  • Ice velocity measurements derived from satellite radar data collected during 2008-2009, posted at 150 m, with errors of 10 m yr-1 in speed and 1.5° in flow direction (Mouginot et al., 2017):
    • Japanese Advanced Land Observing System (ALOS) PALSAR
    • Canadian RADARSAT-1 SAR
    • German TerraSAR-X
    • European Envisat Advanced SAR (ASAR)

Ancillary products used include:

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Derivation Techniques and Algorithms

Sparse, airborne, radar sounding-derived ice thickness data are combined with comprehensive, high-resolution, ice motion derived from satellite interferometric synthetic-aperture radar to calculate ice thickness based on Mass Conservation (MC). The MC method solves the mass conservation equation to derive ice thickness, while at the same time minimizing departure from the original radar-derived ice thickness data. The algorithm conserves mass fluxes while minimizing the departure from the original radar-derived ice thickness data. Ice surface motion provides a physical basis for extrapolating sparse ice thickness data to larger areas with few or no data. The method works best in areas of fast flow, where errors in flow direction are small and the glaciers slide on the bed. In the interior regions, where errors in flow direction are larger, kriging is used to interpolate ice thickness (Morlighem et al., 2014).

Ocean bathymetry is mapped by combining sparse bathymetry measurements from single and multibeam measurements and casts and RTopo-2 (Schaffer et al., 2016).

The algorithm neglects ice motion by internal shear, which is an excellent approximation for fast-flowing glaciers (>100 m yr-1) (Morlighem et al., 2014).

The bed topography is derived by subtracting the ice thickness from the Greenland Mapping Project (GIMP) Digital Elevation Model (

Version History

On 19 May 2015, the IceBridge BedMachine Greenland data were replaced by Version 2. Version 2 includes improved processing of some basins and adds some Operation IceBridge 2014 data. Heights are now provided with respect to mean sea level, instead of the WGS84 ellipsoid. The geoid is included in an additional field in the data.

On 25 September 2017, the IceBridge BedMachine Greenland data were replaced by Version 3. Version 3 now includes ocean bathymetry all around Greenland based on data from NASA’s Ocean Melting Greenland (OMG) and other campaigns of bathymetry measurements. The subglacial bed topography has also been updated by including more ice thickness data and constraining the ice thickness at the ice/ocean interface based on bathymetry data when available.

Error Sources

Sources of error include error in ice velocity direction and magnitude, error in surface mass balance and ice thinning rates.

In a trial setting with unusually dense radar sounding coverage, we report errors in the MC-inferred thickness of 36 m, only slightly higher than that of the original data. In areas less well constrained by radar-derived thickness data, or constrained by only one track of data, for example, in south Greenland, errors may exceed 50 m (Morlighem et al., 2013).

No or very little data were available for some fjords, and uncertainty may be high (>500 m).

An error estimate of the bed elevation and ice thickness is provided in the data set, illustrated in Figure 2.

Figure 2. Error Estimate of Greenland Bed Elevation and Ice Thickness

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Sensor or Instrument Description

The Center for Remote Sensing of Ice Sheets (CReSIS) Multichannel Coherent Radar Depth Sounder (MCoRDS) operates over a 180 to 210 MHz frequency range with multiple receivers developed for airborne sounding and imaging of ice sheets. See IceBridge MCoRDS L2 Ice Thickness (IRMCR2) for further information on the MCoRDS radar and the Level-2 data.

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References and Related Publications

Contacts and Acknowledgments

Mathieu Morlighem
Department of Earth System Science
University of California, Irvine
Irvine CA, 92617, USA


This work was performed at the University of California Irvine under a contract with the NASA Cryospheric Sciences Program (#NNX15AD55G), and the National Science Foundation’s ARCSS program (#1504230), and in cooperation with the University of Bristol as part of the Basal Properties of Greenland project (NERC grant NE/M000869/1).

We would like to thank GRISO RCN (Greenland Ice Sheet Ocean Research Coordination Network) for their help in finding available bathymetry data.

No technical references available for this data set.

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