CAP22 Tomographic model: Data, Software, Plotting
<p>CAP22 (Boyce et al., 2023), is an absolute P-wavespeed tomographic model with focus on North American, specifically Canadian and Alaskan, mantle structure, provided with and without crustal correction.</p> <p>Please cite the following work when using this data set:</p> <p>Boyce, A., Liddell, M. V., Pugh, S., Brown, J., McMurchie, E., Parsons, A., Estève, C., Burdick, S., Darbyshire, F. A., Cottaar, S. Bastow, I. D., Schaeffer, A. J., Audet, P., Schutt, D. L., Aster, R. C. (2023). A new P-wave tomographic model (CAP22) for North America: Implications for the subduction and cratonic metasomatic modification history of western Canada and Alaska. <em>Journal of Geophysical Research: Solid Earth</em>, 128, e2022JB025745. <a href="https://doi.org/10.1029/2022JB025745">https://doi.org/10.1029/2022JB025745</a></p> <p>This repository accompanies the publication of the tomographic model on the IRIS-EMC that can be found here: https://ds.iris.edu/ds/products/emc-cap22/ or with the following doi: 10.17611/dp/emc.2023.cap22.1. Please find CAP22 and its related files for a detailed description of the distributed model.</p> <p>The CAP22_TOMO_SHARE.tar repository contains:</p> <ul> <li>Raw_data: Hand-picked and processed seismic data (.SAC) from western Canada and Alaskan seismic networks.</li> <li>Original_documentation: Documentation for original distribution of inversion code from MIT global seismology group.</li> <li>Tomography_CAP22: Implementation of MIT inversion algorithm used to produce CAP22 including formatted data.</li> <li>Plotting: Codes and necessary files to reproduce figures in main manuscript.</li> </ul> <p>The following authors contributed to this work:</p> <p>A. Boyce: University of Cambridge, Department of Earth Science, Bullard Laboratories, Madingley Road, Cambridge, UK.<br> M. V. Liddell: Centre de recherche Geotop, Université du Québec à Montréal, QC, Canada.<br> S. Pugh: University of Cambridge, Department of Earth Science, Bullard Laboratories, Madingley Road, Cambridge, UK.<br> J. Brown: University of Cambridge, Department of Earth Science, Bullard Laboratories, Madingley Road, Cambridge, UK.<br> E. McMurchie: University of Cambridge, Department of Earth Science, Bullard Laboratories, Madingley Road, Cambridge, UK.<br> A. Parsons: University of Cambridge, Department of Earth Science, Bullard Laboratories, Madingley Road, Cambridge, UK.<br> C. Estève: Department of Meteorology and Geophysics, University of Vienna, Vienna, Austria.<br> S. Burdick: Wayne State University, Geology Department, Detroit, MI, USA.<br> F. A. Darbyshire: Centre de recherche Geotop, Université du Québec à Montréal, QC, Canada.<br> S. Cottaar: University of Cambridge, Department of Earth Science, Bullard Laboratories, Madingley Road, Cambridge, UK.<br> I. D. Bastow: Department of Earth Science and Engineering, Royal School of Mines, Prince Consort Road, Imperial College London, London, UK.<br> A. J. Schaeffer: Geological Survey of Canada Pacific Division, Sidney, BC, Canada.<br> P. Audet: University of Ottawa, Department of Earth and Environmental Sciences, Ottawa, ON, Canada.<br> D. L. Schutt: Colorado State University, Department of Geosciences and Warner College of Natural Resources, Fort Collins, CO, USA.<br> R. C. Aster: Colorado State University, Department of Geosciences and Warner College of Natural Resources, Fort Collins, CO, USA.</p> <p> </p> <p> </p>
ShareScore
36/100
Overall dataset sharing score
Score breakdown
These five areas show where the dataset supports — or may limit — practical reuse.
- Stewardship
- 4
- Harmonization
- 4
- Access
- 16
- Reuse readiness
- 8
- Engagement
- 4
Dataset details
- Repository
- zenodo
- Published
- January 18, 2023
- License
- cc-by-4.0
- DOI
- 10.5281/zenodo.7510590
Scored with release 0.9.0
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