Data Set ID:
RDBTS4

Likely Basal Thermal State of the Greenland Ice Sheet, Version 1

The Likely Basal Thermal State of the Greenland Ice Sheet (GrIS) product contains key data sets that show how the likely basal thermal state was inferred from existing airborne and satellite data sets and recent methods, and provides a synthesis mask of the likely basal thermal state over the Greenland Ice Sheet.

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Geographic Coverage

Parameter(s):
  • Surface Radiative Properties > Thermal Properties
Spatial Coverage:
  • N: 81.51, S: 58.91, E: 6.62, W: -88.33

Spatial Resolution:
  • 5 x 5
Temporal Coverage:
  • 23 June 1993 to 26 April 2013
Temporal Resolution: Varies
Data Format(s):
  • NetCDF
  • XML
Platform(s) AQUA, DC-8, P-3B, TERRA
Sensor(s): ACORDS, ICORDS, MCRDS, MCoRDS, MODIS
Version: V1
Data Contributor(s): Joseph MacGregor, Mark Fahnestock, Ginny Catania, John Paden, Prasad Gogineni, Mathieu Morlighem, William Colgan, Sophie Nowicki, Andy Aschwanden

Data Citation

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.

MacGregor, J. A., M. Fahnestock, G. Catania, J. Paden, P. Gogineni, M. Morlighem, W. Colgan, S. M. Nowicki, G. Clow, A. Aschwanden, S. F. Price, and H. Seroussi. 2017. Likely Basal Thermal State of the Greenland Ice Sheet, Version 1. [Indicate subset used]. Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center. doi: https://doi.org/10.5067/R4MWDWWUWQF9. [Date Accessed].

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Detailed Data Description

The Likely Basal Thermal State of the Greenland Ice Sheet (GrIS) product contains key datasets that show how the likely basal thermal state was inferred from existing airborne and satellite datasets and recent methods, and provides a synthesis mask of the likely basal thermal state over the Greenland Ice Sheet (MacGregor et al. 2016).

Format

The data files are HDF5-compliant NetCDF (.nc) format.

The data file is paired with an associated XML file. XML files contain point latitudes and longitudes, and file and campaign metadata.

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File and Directory Structure

Data are available on the HTTPS site, accessible via NASA Earthdata Login username and password: https://n5eil01u.ecs.nsidc.org/ICEBRIDGE/RDBTS4.001/

And for a brief time before FTP access is retired, available here: ftp://n5eil01u.ecs.nsidc.org/SAN/ICEBRIDGE/RDBTS4.001/1993.06.23/ directory.

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File Naming Convention

File names:

RDBTS4_Greenland_1993_2013_01_basal_thermal_state.nc
RDBTS4_Greenland_1993_2013_01_basal_thermal_state.nc.xml

RDBTS4_Location_YYYY_yyyy_0X_basal_thermal_state.nc

Where:

Variable Description
Table 1. File Naming Convention
RDBTS4 Short name for Likely Basal Thermal State of the Greenland Ice Sheet data
Location Location, e.g. Greenland
YYYY_yyyy Temporal coverage of data collection from YYYY to yyyy, e.g. 1993_2013
0X Data product version number, e.g. 01
basal_thermal_state Basal thermal state of the Greenland Ice Sheet
xxx Indicates file type, e.g. NetCDF (.nc), XML (.xml)
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File Size

The RDBTS4_Greenland_1993_2013_01_basal_thermal_state.nc data file is approximately 37 MB.

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Volume

The entire data set is approximately 37 MB.

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Spatial Coverage

Southernmost Latitude 58.91° N
Northernmost Latitude: 81.51° N
Westernmost Longitude: -88.33° W
Easternmost Longitude: 6.62° E

Spatial Resolution

5 km grid on EPSG:3413, centered on Greenland

Projection and Grid Description

Table 2. EPSG:3413 NSIDC Sea Ice Polar Stereographic North
Projection: Polar Stereographic
Latitude of the origin 90°
Longitude of the origin (central meridian) -45°
Standard parallel 70°
Scaling factor 1
False eastings 0
False northings 0
Ellipsoid WGS84
Datum WGS84
Units meters
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Temporal Coverage

1993-06-23 and 2013-04-26.

Temporal Resolution

Temporal resolution is variable

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Parameter or Variable
Parameter Description Units
Table 3. netCDF File Description
agreement_basal_thermal_state 4-method agreement mask; total balance of methods indicating a specific basal thermal state negative: frozen, positive: thawed
agreement_searise SeaRISE agreement mask threshold: -0.05C (standard / 0C (cold-bias) / -0.5C (warm-bias)
basal_melt_rate basal melt rate inferred from Nye+melt 1-D model (std/lo/hi) m/yr
d1_mask D < 1 mask for constraining suitability of 1-D ice-flow models for radiostratigraphy interpretation D < 1: 1  ;  D > 1: 0
likely_basal_thermal_state likely basal thermal state -1: likely frozen; 0: uncertain; +1: likely thawed
mog_undulations mask that outlines onset of MOG-observed surface undulations dimensionless
number of contour points - conservative a NetCDF dimension but not a NetCDF variable. n/a
number of contour points - standard a NetCDF dimension but not a NetCDF variable.   n/a
number of distinct fields: 2 a NetCDF dimension but not a NetCDF variable.  n/a
number of distinct fields: 3 a NetCDF dimension but not a NetCDF variable.  n/a
number of grid points in x-direction a NetCDF dimension but not a NetCDF variable.    n/a
number of grid points in y-direction a NetCDF dimension but not a NetCDF variable. n/a
shape_factor shape factor for ice column (std/lo/hi) dimensionless
shear_layer_thickness basal shear layer thickness m
speed_ratio ratio of observed surface speed to modeled deformation of temperate ice column (std/lo/hi) dimensionless
x projected x-dimension grid centered on Greenland km
x-y a NetCDF dimension but not a NetCDF variable. n/a
xy_mog_undulations_conservative x/y that outlines onset of MOG-observed surface undulations (conservative) km
xy_mog_undulations_standard x/y that outlines onset of MOG-observed surface undulations (standard) km
y projected y-dimension grid centered on Greenland km

Sample Data Record

Figure 1 shows the likely basal thermal state of the GrIS. The findings are that 43% of the bed is likely thawed, 24% is likely frozen, and the thermal state of the remainder (34%) is uncertain (MacGregor et al. 2016).

Figure 1. Likely basal thermal state of the Greenland Ice Sheet, based on where the standard, cold- and warm-bias estimates of this state agree (MacGregor et al. 2016).
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Software and Tools

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The following external links provide access to software for reading and viewing HDF5 and NetCDF data files. Please be sure to review instructions on installing and running the programs.

HDF Explorer: Data visualization program that reads Hierarchical Data Format files (HDF, HDF-EOS and HDF5) and also NetCDF data files.

Panoply NetCDF, HDF and GRIB Data Viewer: Cross-platform application. Plots geo-gridded arrays from NetCDF, HDF and GRIB data sets.

For additional tools, see the HDF-EOS Tools and Information Center.

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Quality Assessment

To qualitatively evaluate the four methods’ inferences of the basal thermal state of the GrIS and our synthesis, we use the temperature–depth profiles measured in the six deep boreholes that have associated ice cores (Camp Century, DYE-3, GISP2, GRIP, NEEM, and NorthGRIP). Additional full-thickness borehole temperature profiles exist for the GrIS from its southwestern margin and elsewhere along the margin, and these are also included in our analysis (MacGregor et al. 2016).

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Data Acquisition and Processing

Theory of Measurements

The basal thermal state of an ice sheet (frozen or thawed) is an important control upon its evolution, dynamics, and response to external forcings. However, this state can only be observed directly at sparse boreholes or inferred conclusively from the presence of subglacial lakes. Here we synthesize spatially extensive inferences of the basal thermal state of the Greenland Ice Sheet to better constrain this state. Existing inferences include outputs from the eight thermomechanical ice-flow models included in the Sea Level Response to Ice Sheet Evolution (SeaRISE) effort. New remote-sensing inferences of the basal thermal state are derived from Holocene radiostratigraphy, modern surface velocity, and Moderate Resolution Imaging Spectroradiometer (MODIS) imagery. Both thermomechanical modeling and remote inferences generally agree that the Northeast Greenland Ice Stream and large portions of the southwestern ice-drainage systems are thawed at the bed, whereas the bed beneath the central ice divides, particularly their west facing slopes, is frozen. Elsewhere, there is poorer agreement regarding the basal thermal state. Both models and remote inferences rarely represent the borehole-observed basal thermal state accurately near NorthGRIP and DYE-3. This synthesis identifies a large portion of the Greenland Ice Sheet (about one third by area), where additional observations would most improve knowledge of its overall basal thermal state (MacGregor et al. 2016).

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Data Acquisition Methods

Multiple airborne and satellite-borne sensors were used to acquire the data that were analyzed directly to generate this dataset or were used directly as boundary conditions for the ice-flow models. These sensors and their data acquisition methods and described in the references cited in MacGregor et al. 2016.

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Derivation Techniques and Algorithms

The present basal thermal state of the GrIS was evaluated using four independent methods: 3-D thermomechanical modeling and basal motion inferred from radiostratigraphy, surface velocity, and surface texture, respectively.

There are four data sources:

  • Basal temperature fields from SeaRISE control runs of 8 ice-sheet models from Nowicki et al. 2013
  • Gridded basal melt rate, shear layer thickness and shape factor inferred from 1-D modeling of the radiostratigraphy presented by MacGregor et al. 2015
  • Modeled ratio of surface speed (Joughin et al. 2010) to modeled maximum deformation speed
  • Traced onset of surface undulations in the MODIS Mosaic of Greenland (Haran et al. 2013)

Data Collection Methods:

  • 3-D thermomechanical numerical modeling
  • 1-D steady-state modeling of dated Holocene radiostratigraphy
  • Modeling of the maximum deformation speed of a temperate ice column and comparison with observed surface speed
  • Visual analysis of MOG surface texture

Each method is included without weighting so as to generate an unbiased assessment of the agreement between these methods and the likely basal thermal state. See MacGregor et al. 2016 for additional details regarding the algorithm applied. 

We synthesize these multiple methods of constraining the basal thermal state across Greenland described above by simply assessing where each of the above independent methods produces a clear signal regarding this state. We initialize a 5-km gridded ice-sheet “agreement” mask to zero. For each method at each grid point, if a signal exists for a frozen (thawed) bed, then –1 (+1) is added to this mask.

If a given method does not yield an unambiguous signal regarding the basal thermal state, then this agreement is not adjusted there based on that method. We do not weight any of the methods with respect to each other. Prior to but following the same procedure as for the main mask, a separate mask is generated using the 3-D thermomechanical model outputs, each weighted equally. In this manner, each independent method contributes to an unbiased synthesis of the basal thermal state.

Based on confidence bounds or uncertainty estimates for each of the four methods described above and their discriminating characteristics, two additional instances of the agreement mask are generated: a cold-bias instance and a warm-bias instance. We then generate a new likely basal thermal state mask that synthesizes the agreement between the different methods and represents the likely thermal state of the bed. This new mask is also initialized to zero and then assigned –1 (+1), representing a frozen (thawed) bed where at least two of the three instances of the agreement mask agree on the basal thermal state (sign, regardless of their degree of agreement in this state (magnitude). If only two instances agree, then the assignment is made only if the other instance does not suggest the opposite basal thermal state.

We assume that regions of the bed where the likely basal thermal state is uncertain that are surrounded by likely thawed or frozen bed are more likely than not to possess the same basal thermal state as their surroundings. Following this reasoning, we reassign uncertain “holes” less than 10 grid cells in size (≤250 km2) with their surrounding basal thermal state. Similarly, in regions where this mask is uncertain, we reassign likely frozen or thawed “holes” of the same limited size to the surrounding basal thermal state.

Trajectory and Attitude Data

Processing Steps

See Derivation Techniques and Algorithms.

Version History

First release, Version 1.

Error Sources

Potential error sources are numerous and are considered explicitly in this dataset. Confidence intervals or existing uncertainties for the datasets used are incorporated into the cold-bias and warm-bias agreement masks, which ultimately inform the likely basal thermal state mask.

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Sensor or Instrument Description
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References and Related Publications

Contacts and Acknowledgments

Joseph A. MacGregor, Sophie M.J. Nowicki
NASA Goddard Space Flight Center
Cryospheric Sciences Laboratory (Code 615)
Greenbelt, MD 20771  USA

Mark A Fahnestock, Andy Aschwanden
Geophysical Institute
University of Alaska Fairbanks
Fairbanks, AK 99775  USA

Ginny A Catania
University of Texas at Austin
Institute for Geophysics
Austin, TX, 78759-8500  USA

Gary D. Clow
U.S. Geological Survey
Denver, Colorado  USA

William T Colgan
Department of Earth and Space Science and Engineering
York University
Toronto, Ontario, Canada

S. P. Gogineni, John D. Paden
Center for Remote Sensing of Ice Sheets
University of Kansas
Lawrence, Kansas  USA

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

Stephen F. Price
Fluid Dynamics Group
Los Alamos National Laboratory
Los Alamos, New Mexico  USA

Hélène Seroussi
Jet Propulsion Laboratory
California Institute of Technology
Pasadena, California  USA

Acknowledgments: 

The project that led to the development of this data set was supported by NASA IceBridge Research NNX12AB71G.

Document Information

DOCUMENT CREATION DATE

DOCUMENT REVISION DATE

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