AFRP22 Tomographic Model & MTZ Receiver Functions: Data, Software, Plotting
<p>AFRP22 (Boyce et al., 2023), is an adaptively parameterized, absolute P-wave tomographic model for Africa provided with and without crustal correction. Also provided is mantle transition zone Receiver Functions for new stations in the Turkana Depression (data embargo lifted 2024-05-24).</p> <p>Citation:</p> <p>Boyce, A., Kounoudis, R., Bastow, I. D., Cottaar, S., Ebinger, C. J., Ogden, C. S. Mantle Wavespeed and Discontinuity Structure below East Africa: Implications for Cenozoic Hotspot Tectonism and the Development of the Turkana Depression (under revision) Geochemistry, Geophysics, Geosystems.</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-afrp22/ or with the following doi: <a href="https://doi.org/10.17611/dp/emc.2023.afrp22.1">https://doi.org/10.17611/dp/emc.2023.afrp22.1</a>. Please find AFRP22 and its related files for a detailed description of the distributed model.</p> <p>The AFRP22_RFs_SHARE.tar repository contains:</p> <ul> <li>Plotting: Codes and necessary files to reproduce figures in main manuscript.</li> <li>tomography <ul> <li>Tomography_AFRP22: Implementation of MIT inversion algorithm used to produce AFRP22 including formatted data.</li> <li>Raw_data: Hand-picked and processed seismic data (.SAC) from new African seismic networks.</li> <li>Original_documentation: Documentation for original distribution of inversion code from MIT global seismology group </li> </ul> </li> <li>receiver_functions <ul> <li>Processing codes (SMURFPy) already available at doi: <a href="https://doi.org/10.5281/zenodo.4337257">10.5281/zenodo.4337257</a></li> <li>Raw_data - Data files for P, PP and PKP RFs, CCP stacked volumes produced by SMURFPy code and picked discontinuity files</li> </ul> </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> R. Kounoudis: Department of Earth Science and Engineering, Royal School of Mines, Prince Consort Road, Imperial College London, London, UK.<br> I. D. Bastow: Department of Earth Science and Engineering, Royal School of Mines, Prince Consort Road, Imperial College London, London, UK.<br> S. Cottaar: University of Cambridge, Department of Earth Science, Bullard Laboratories, Madingley Road, Cambridge, UK.<br> C. J. Ebinger: Department of Earth and Environmental Sciences, Tulane University, New Orleans, LA 70118, USA.<br> C. S. Ogden: School of Geography and Geology, University of Leicester, Leicester, LE1 7RH, UK.<br> </p>
ShareScore
40/100
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
- 8
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