Acoustic impedance misfits and basal sliding law probabilities for Pine Island Glacier

This dataset contains acoustic impedance misfits between measurements collected on Pine Island Glacier (Brisbourne et al., 2017) and predictions of the Viscous Grain-Shearing theory (Buckingham, 1997, 2000, 2005, 2007). The dataset is presented as netCDF files. The acoustic impedance predictions depend on the effective pressure, which is derived using various basal sliding laws. This link enables the comparison of basal sliding laws within a Bayesian model selection framework (Hank et al., 2025). The posterior probabilities (also included in this dataset) were determined by the authors to infer the most probable basal sliding law.

This work was funded by the GHOST project, a component of the International Thwaites Glacier Collaboration (ITGC). Support from National Science Foundation (NSF: Grant PLR 1738934) and Natural Environment Research Council (NERC: Grant NE/S006672/1), with logistics provided by NSF-U.S. Antarctic Program and NERC-British Antarctic Survey.

Date (Creation): 2025-10-31

Date (Revision): 2025-10-31

Date (Publication): 2025-10-31

Date (released): 2025-10-31

Edition: 1.0

Unique resource identifier: https://doi.org/10.5285/c560ce43-7aa0-4474-90ed-d4ee5f5768ea

Codespace: doi

Unique resource identifier: GB/NERC/BAS/PDC/02099

Codespace: https://data.bas.ac.uk/

Unique resource identifier: NE/S006672/1

Codespace: award

Other citation details: Please cite this item as: Hank, K., Arthern, R., & Williams, C. (2025). Acoustic impedance misfits and basal sliding law probabilities for Pine Island Glacier (Version 1.0) [Data set]. NERC EDS UK Polar Data Centre. https://doi.org/10.5285/c560ce43-7aa0-4474-90ed-d4ee5f5768ea

Credit: No credit.

Status: Completed

Point of contact

Organisation name	Individual name	Electronic mail address	Role
British Antarctic Survey	Hank, Kevin		Author
British Antarctic Survey	Arthern, Robert		Author
British Antarctic Survey	Williams, C Rosie		Author
NERC EDS UK Polar Data Centre		PDCServiceDesk@bas.ac.uk	Point of contact

Maintenance and update frequency: As needed

Maintenance note: Completed

Global Change Master Directory (GCMD) Science Keywords

Theme

Bayesian model selection
ITGC
Pine Island Glacier
acoustic impedance
basal sliding
effective pressure

Place

Amundsen Sea sector, Pine Island Glacier Antarctica

GEMET - INSPIRE themes, version 1.0

Access constraints: Other restrictions

Other constraints: no limitations to public access

Access constraints: Other restrictions

Other constraints: no limitations

Use constraints: License

Other constraints: Open Government Licence v3.0

Use constraints: Other restrictions

Other constraints: Data supplied under Open Government Licence v3.0

Use constraints: Other restrictions

Other constraints: No restrictions apply.

Unique resource identifier: url

Codespace: url

Association Type: Cross reference

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Codespace: url

Association Type: Larger work citation

Unique resource identifier: url

Codespace: url

Association Type: Larger work citation

Spatial representation type: Text, table

Language: English

Character set: UTF8

Topic category

Inland waters

Begin date: 2024-11-13

End date: 2025-09-01

Vertical extent

Minimum value: 0.0

Maximum value: 5000.0

Vertical CS

No information provided.

Vertical datum

No information provided.

Supplemental Information: It is recommended that careful attention be paid to the contents of any data, and that the author be contacted with any questions regarding appropriate use. If you find any errors or omissions, please report them to polardatacentre@bas.ac.uk.

Title: European Petroleum Survey Group (EPSG) Geodetic Parameter Registry

Date (Publication): 2008-11-12

Cited responsible party

Organisation name	Individual name	Electronic mail address	Role
European Petroleum Survey Group		EPSGadministrator@iogp.org	Publisher

Unique resource identifier: urn:ogc:def:crs:EPSG::3031

Version: 6.18.3

Distributor

Distributor contact

Organisation name	Individual name	Electronic mail address	Role
NERC EDS UK Polar Data Centre		PDCServiceDesk@bas.ac.uk	Distributor

Distributor format

Name	Version
application/x-hdf
application/netcdf

Units of distribution: bytes

Transfer size: 88905823027

OnLine resource

Protocol	Linkage	Name
WWW:LINK-1.0-http--link	http://ramadda.data.bas.ac.uk/repository/entry/show?entryid=c560ce43-7aa0-4474-90ed-d4ee5f5768ea	Get Data

Units of distribution: bytes

Transfer size: 88905823027

OnLine resource

Protocol	Linkage	Name
WWW:LINK-1.0-http--link	http://ramadda.data.bas.ac.uk/repository/entry/show?entryid=c560ce43-7aa0-4474-90ed-d4ee5f5768ea	Get Data

Hierarchy level: Dataset

Statement: Methodology:

The misfit between measured and predicted acoustic impedance is used to infer the most probable basal sliding law, as described in Hank et al. (2025). This methodology utilizes the dependence of predicted acoustic impedance on effective pressure, as described by the Viscous Grain-Shearing theory (VGS; Buckingham, 1997, 2000, 2005, 2007).

The effective pressure is determined based on the basal sliding laws. Usually, these laws are expressed so that basal drag is a function of sliding speed and effective pressure. To compute effective pressure, these relationships must be inverted, either by explicitly rearranging the equations or by numerical root-finding. For all sliding laws, we ensure the effective pressure does not exceed the ice overburden pressure.

The VGS provides a model of acoustic propagation in granular material. Substituting the estimated effective pressure (from the basal sliding law) into this model and using independent estimates for the grain diameter and porosity from sediment cores provides an estimate of acoustic impedance for each sliding law. The predicted acoustic impedance is then compared to acoustic impedance measurements collected at five sites on Pine Island Glacier (PIG) in Antarctica (Brisbourne et al., 2017).

More specifically, the different models (VGS + sliding laws) are compared using Bayesian model selection. We assume the error of the data follows a Gaussian distribution and consider each model equally probable at the beginning. Since the parameter space differs between the models (number of individual parameters (dimensions) as well as number of tested parameter values), we apply Occam's razor, penalizing models with a larger parameter space.

Details of all other data sets, including the basal drag and sliding speed inversion (Arthern et al., 2015) as well as the prior distributions, can be found in Hank et al. (2025).

The contributing datasets used to constrain the model and parameter ranges are listed by Hank et al. (2025). The model was run between Nov 13, 2024 and Mar 11, 2025. The output is from the same date range.

Data collection:

The misfit calculations were performed using Julia version 1.8.3. The Bayesian model selection and all other data processing was done using Python version 3.13.2.

Data quality:

Key experiments were repeated with (log-)uniform prior distributions for all parameters to examine the sensitivity to the choice of the prior. Furthermore, experiments with a sub-sampled data set (every 10th acoustic impedance measurement) were carried out. A value of NaN indicates there is no data there.

Metadata

File identifier: c560ce43-7aa0-4474-90ed-d4ee5f5768ea XML

Metadata language: English

Character set: UTF8

Hierarchy level: Dataset

Hierarchy level name: dataset

Date stamp: 2025-10-31

Metadata standard name: ISO 19115 Geographic Information - Metadata

Metadata standard version: ISO 19115:2003(E)

Metadata author

Organisation name	Individual name	Electronic mail address	Role
NERC EDS UK Polar Data Centre		polardatacentre@bas.ac.uk	Point of contact

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