Cordilleran ice sheet glacial cycle simulations continuous variables

• Main Author: Seguinot
• Other Authors: Rogozhina, Irina, Stroeven, Arjen P., Margold, Martin, Kleman, Johan
• Format: Other/Unknown Material
• Language: English
• Published: Zenodo 2023
• Subjects: cordillera; glacier; ice sheet; modelling; EPICA; ice core; Ice Sheet; NGRIP
• Online Access: https://doi.org/10.5281/zenodo.7802345

These data contain a subset of time-dependent glacier model output variables: Reference: J.Seguinot, I.Rogozhina, A.P.Stroeven, M.Margold, and J.Kleman. Numerical simulations of the Cordilleran ice sheet through the last glacial cycle, The Cryosphere , 10(2):639–664, 10.5194/tc-10-639-2016 , 2016. File names: <code>ciscyc4.{10km|5km}.{forcing}.{ex.100a|ex.1ka|ts.10a}.nc</code> Horizontal resolution: 10km : 10 km horizontal resolution 5km : 5 km horizontal resolution Temperature forcing: epica : EPICA ice core temperature forcing grip : GRIP ice core temperature forcing ngrip : NGRIP ice core temperature forcing odp1012 : ODP 1012 ocean core temperature forcing odp1020 : ODP 1020 ocean core temperature forcing vostok : Vostok ice core temperature forcing Variable types: ex.100a : spatial diagnostics every hundred years ex.1ka : spatial diagnostics every thousand years ts.10a : scalar time-series every ten years Data format: The data use compressed netCDF format. For quick inspection I recommend ncview. Spatial diagnostics ( *.ex.*.nc ) can be converted to GeoTIFF (and other GIS formats) e.g. using GDAL: <code>gdal_translate NETCDF:filename.nc:variable -b band filename.variable.band.tif</code> The list of variables (subdatasets) can be obtained from ncdump or gdalinfo. The band number equals 120 minus the age in ka. Band information can be displayed with: <code>gdalinfo NETCDF:filename.nc:variable</code> Variable long names, units, PISM configuration parametres and additional information are contained within the netCDF metadata. Changelog: Version 2: Add spatial diagnostics every hundred years ( *.ex.100a.nc ) Version 1: Initial version. This work was supported by the Swedish Research Council (VR) grant 2008-3449, the German Academic Exchange Service (DAAD) grant 50015537, the Knut and Alice Wallenberg Foundation, the Swedish National Infrastructure for Computing (SNIC) grants 2013/1-159 and 2014/1-159, and the Swiss National Supercomputing Centre (CSCS) grant s573.