Fields and parameters related to the flow of ice in the Antarctic Ice Sheet recovered using inverse methods and satellite data
We can learn about the flow of ice in Antarctica by evaluating the key parameters that control the flow speed. These parameters include the basal drag coefficient and the ice viscosity. They can be estimated by adjusting their values so that model velocities at the upper surface agree with satellite observations. This dataset was produced using inverse methods to obtain the parameter values. In this approach a cost function that describes the mismatch between model and satellite data is minimised iteratively by making small adjustments to the parameters at each iteration to improve the fit. The result is better information about the flow field in the Antarctic ice sheet. Once the flow field is available it can be used as an initial state from which begin temporally evolving simulations using the model. A number of different examples are included to show how varying different parameters alters the temporally evolving simulations.
The contributing datasets used to constrain the model are listed by Arthern et al (2015) and Arthern and Williams (2017). Multidecadal model simulations span up to 100 years of simulation time.
This work was funded by NERC standard grant NE/L005212/1.
Simple
- Date (Creation)
- 2022-04-08
- Date (Revision)
- 2022-04-08
- Date (Publication)
- 2022-04-08
- Date (released)
- 2022-04-08
- Edition
- 1.0
- Unique resource identifier
- https://doi.org/10.5285/5f0ac285-cca3-4a0e-bcbc-d921734395ab
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- doi
- Unique resource identifier
- GB/NERC/BAS/PDC/01632
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- https://data.bas.ac.uk/
- Unique resource identifier
- NE/L005212/1
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- Please cite this item as: Arthern, R., Williams, R., Hindmarsh, R., & Pritchard, H. (2022). Fields and parameters related to the flow of ice in the Antarctic Ice Sheet recovered using inverse methods and satellite data (Version 1.0) [Data set]. NERC EDS UK Polar Data Centre. https://doi.org/10.5285/5f0ac285-cca3-4a0e-bcbc-d921734395ab
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https://www.bas.ac.uk/team/business-teams/information-services/uk-polar-data-centre/
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- asNeeded As needed
- Maintenance note
- completed Completed
- Global Change Master Directory (GCMD) Science Keywords
-
- EARTH SCIENCE > Cryosphere > Glaciers/Ice Sheets > Glacier Elevation/Ice Sheet Elevation
- EARTH SCIENCE > Cryosphere > Glaciers/Ice Sheets > Glacier Motion/Ice Sheet Motion
- EARTH SCIENCE > Cryosphere > Glaciers/Ice Sheets > Glacier Thickness/Ice Sheet Thickness
- EARTH SCIENCE > Cryosphere > Glaciers/Ice Sheets > Glacier Topography/Ice Sheet Topography
- EARTH SCIENCE > Cryosphere > Glaciers/Ice Sheets > Ice Sheets
- EARTH SCIENCE > Hydrosphere > Glaciers/Ice Sheets > Glacier Elevation/Ice Sheet Elevation
- EARTH SCIENCE > Hydrosphere > Glaciers/Ice Sheets > Glacier Motion/Ice Sheet Motion
- EARTH SCIENCE > Hydrosphere > Glaciers/Ice Sheets > Glacier Thickness/Ice Sheet Thickness
- EARTH SCIENCE > Hydrosphere > Glaciers/Ice Sheets > Glacier Topography/Ice Sheet Topography
- EARTH SCIENCE > Hydrosphere > Glaciers/Ice Sheets > Ice Sheets
- Theme
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- Antarctica
- basal drag
- ice flow
- ice viscosity
- Place
-
- Amundsen Sea sector of West Antarctica Antarctica
- GEMET - INSPIRE themes, version 1.0
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- no limitations to public access
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- Open Government Licence v3.0
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- Data supplied under Open Government Licence v3.0
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- Topic category
-
- Elevation
- Environment
- Geoscientific information
- Oceans
Vertical extent
- Minimum value
- 0.0
- Maximum value
- 5.0
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- 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.
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- Statement
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Methodology:
The processing of the data is described by Arthern et al. (2015) and Arthern and Williams (2017) (see references section). Inverse methods were used to find the basal drag and ice viscosity parameters that allow the model to agree best with satellite observations. Once the ice flow parameters have been obtained, the modelled ice flow within the ice sheet can be evaluated and used to start temporally evolving simulations for a variety of different parameter choices, as described by Arthern and Williams (2017).
Data collection:
Data processing and modelling was done using MATLAB (Version 8).
The contributing datasets used to constrain the model are listed by Arthern et al (2015) and Arthern and Williams (2017). Multidecadal model simulations span up to 100 years of simulation time.
Data quality:
The algorithm used was evaluated on idealised test cases as described by Arthern and Gudmundsson (2010). Arthern et al (2015) shows maps of discrepancy between model velocity and satellite derived velocity, and histograms of the differences between model elevation changes and elevation changes derived using satellite altimetry. For the temporally evolving simulations two datasets are included; one as originally computed and one with accumulation rates corrected for a processing error.
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