Factors contributing to deep slab dip angles in reconstructions of past mantle flow
<p>This repository contains data files for the manuscript 'Factors contributing to deep slab dip angles in reconstructions of past mantle flow' submitted to Earth-Science Reviews by J. Weber and N. Flament</p> <p>The provided data are vote maps of global tomographic models and global temperature anomalies for case C10.</p> <p>The directory 'pswave_votemap' contains vote maps of 33 global P- and S-wave tomographic models at 32 selected depths between 0 km and 1040 km (depths were selected to match that available for global mantle flow models). The name convention is 'pswave_votemap_$depth.nc' and the file format is NetCDF CF Convention 1.7.</p> <p>The directory 'pwave_votemap' contains vote maps of 15 global P-wave tomographic models at 32 selected depths between 0 km and 1040 km (depths were selected to match that available for global mantle flow models). The name convention is 'pwave_votemap_$depth.nc' and the file format is NetCDF CF Convention 1.7.</p> <p>The directory 'swave_votemap' contains vote maps of 18 global S-wave tomographic models at 11 selected depths between 396 km and 1040 km (depths were selected to match that available for global mantle flow models). The name convention is 'swave_votemap_$depth.nc' and the file format is NetCDF CF Convention 1.7.</p> <p>The directory 'C10' contains the present-day temperature anomalies predicted for case C10 at 32 depths between 396 km and 1040 km. The name convention is 'C10_dimensional_temperature_anomaly_$depth.nc' or 'C10_non_dimensional_temperature_anomaly_$depth.nc' and the file format is NetCDF CF Convention 1.7. Dimensional temperature anomalies were obtained by multiplying non-dimensional temperature anomalies by 3100.</p> <p>These files were created using version 6 of the Generic Mapping Tools (GMT6; Wessel et al., 2019).</p> <p>Please contact nflament@uow.edu.au if you have questions about these files, or require further materials.</p>
ShareScore
40/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 8
- Harmonization
- 4
- Access
- 16
- Reuse readiness
- 8
- Engagement
- 4