Published April 8, 2024 | Version v1
Dataset Open

Cordilleran ice sheet improved bedrock simulations continuous variables

  • 1. ROR icon Vrije Universiteit Brussel
  • 2. ROR icon ETH Zurich

Description

These data contain a subset of time-dependent glacier model output variables. The ghf70 data files are an update on the reference below, fixing significant problems affecting the computation of the bedrock deformation in response to ice load (PISM Github issues #370 and #377) and the computation of ice temperature (PISM Github issue #371). The other data files additionally include spatially-variable geothermal heat flux (dav13, gou11combgou11simisha04), different lithospheric rigidity (eet30km) or mantle viscosity (num1e21), and higher horizontal resolution (3km).

Reference:

  • Seguinot, J., Rogozhina, I., Stroeven, A. P.,  Margold, M. and Kleman, J.: Numerical simulations of the Cordilleran ice sheet through the last glacial cycle, The Cryosphere, 10(2), 639–664, doi:10.5194/tc-10-639-2016, 2016.

File names:

cisbed.{res}.{forcing}.{ex.100a|ts.10a}.{ghf}.{props}.nc

  • Horizontal resolution:
    • 10km: 10 km horizontal resolution
    • 5km: 5 km horizontal resolution
    • 3km: 3 km horizontal resolution
  • Temperature forcing:
    • epica: EPICA ice core temperature forcing
    • grip: GRIP ice core temperature forcing
  • Variable types:
    • ex.100a: spatial diagnostics every hundred years
    • ts.10a: scalar time-series every ten years
  • Geothermal heat flow:
    • ghf70: constant 70 mW m-2 heat flow
    • dav13: Davies (2013) geothermal heat flow map
    • gou11comb: Goutorbe et al. (2011) best combination method
    • gou11simi: Goutorbe et al. (2011) similarity method
    • sha04: Shapiro and Ritzwoller (2004) heat flow map
  • Bedrock properties
    • eet30km: lithosphere elastic thickness of 30 km
    • num1e21: astenosphere viscosity of 1e21 Pa s

Data format:

The data use compressed netCDF format. For quick inspection I recommend ncview. Spatial diagnostics (*.ex.100a.nc) can be converted to GeoTIFF (and other GIS formats) e.g. using GDAL:

gdal_translate NETCDF:filename.nc:variable -b band filename.variable.band.tif

The list of variables (subdatasets) can be obtained from ncdump or gdalinfo. Band information can be displayed with:

gdalinfo NETCDF:filename.nc:variable

Variable long names, units, PISM configuration parametres and additional information are contained within the netCDF metadata.

Funding:

Swiss National Supercomputing Centre (CSCS) grants s573 and sm13 to J. Seguinot, Swiss National Science Foundation (SNSF) grants no.~200020-169558 and 200021-153179/1 to M. Funk, and Research Foundation – Flanders (FWO) Odysseus Type II project G0DCA23N 'GlaciersMD' to H. Zekollari.

Changelog:

  • Version 1:
    • Initial version.

Files

Files (21.4 GB)

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Additional details

Related works

Is new version of
Dataset: 10.5281/zenodo.3606535 (DOI)
References
Publication: 10.5194/tc-10-639-2016 (DOI)

Software

Repository URL
https://github.com/pism/pism/
Programming language
C++
Development Status
Active

References

  • Davies, J. H.: Global map of solid Earth surface heat flow, Geochem. Geophys. Geosy., 14, 4608–4622, https://doi.org/10.1002/ggge.20271, 2013.
  • Goutorbe, B., Poort, J., Lucazeau, F., and Raillard, S.: Global heat flow trends resolved from multiple geological and geophysical proxies, Geophys. J. Int., 187, 1405–1419, https://doi.org/10.1111/j.1365-246x.2011.05228.x, 2011.
  • Seguinot, J., Rogozhina, I., Stroeven, A. P.,  Margold, M. and Kleman, J.: Numerical simulations of the Cordilleran ice sheet through the last glacial cycle, The Cryosphere, 10(2), 639–664, https://doi.org/10.5194/tc-10-639-2016, 2016.
  • Shapiro, N. M. and Ritzwoller, M. H.: Inferring surface heat flux distributions guided by a global seismic model: particular application to Antarctica, Earth Planet. Sc. Lett., 223(1–2), 213-224, https://doi.org/10.1016/j.epsl.2004.04.011, 2004.
  • the PISM authors: PISM, a Parallel Ice Sheet Model, http://www.pism-docs.org, 2019.