DOI: 10.5281/zenodo.8212589
title: Dataset for "Adjoint Waveform Tomography for Crustal and Upper Mantle Structure the Middle East and Southwest Asia for Improved Waveform Simulations Using Openly Available Broadband Data"

description: This dataset contains the MESWA (Middle East and Southwest Asia) seismic model and auxiliary data used in the creation of the model (Rodgers, 2023). MESWA is a three-dimensional model of the seismic properties of crust and upper mantle of the Middle East and Southwest Asia. The MESWA model is provided in NetCDF format (readable by for example, <em>xarray</em>, Hoyer & Hamman, 2017) and HDF5 format for viewing with <em>ParaView</em> (Ahrens et al., 2005) and interaction with <em>Salvus</em> (Afanasiev et al., 2019). Also included are the earthquake source parameters for all 327 Global Centroid Moment Tensor events considered in this study in ASCII text format. Also included are lists of the selected 192 inversion events and 66 validation events in ASCII text format. Lastly, we include a list of all receivers used in the creation and validation of MESWA. This is a simple ASCII file with the event name and receiver name (composed of the network_code and station_code). The following table provides a listing of the files in the dataset: <strong>File</strong> <strong>Description</strong> MESWA.nc MESWA model in NetCDF format MESWA.h5 MESWA model in HDF5 format, used by Salvus MESWA.xmdf Auxiliary file for MESWA.h5, used to import model into Paraview events_project.csv Table of event source parameters for all 327 events considered in the project inversion_events_192.csv Table of 192 inversion events (ASCII comma separated value) validation_events_66.csv Table of 66 validation events (ASCII comma separated value) events_receivers_inversion.csv Table of waveform (event-receiver-channel) data used in the inversion (ASCII comma separated value) events_receivers_validation.csv Table of waveform (event-receiver-channel) data used in the validation (ASCII comma separated value) <strong>References</strong> Afanasiev, M, C Boehm, M van Driel, L Krischer, M Rietmann, DA May, MG Knepley, and A Fichtner (2019). Modular and flexible spectral-element waveform modelling in two and three dimensions, <em>Geophys. J. Int.</em>, 216(3), 1675–1692, doi: 10.1093/gji/ggy469 Ahrens, J., Geveci, B., & Law, C. (2005). Paraview: An end-user tool for large data visualization. <em>The Visualization Handbook</em>, 717(8). https://doi.org/10.1016/b978-012387582-2/50038-1 Hoyer, S., & Hamman, J. (2017). Xarray: N-D labeled arrays and datasets in Python. <em>Journal of Open Research Software</em>, 5(1). https://doi.org/10.5334/jors.148 Rodgers, A. (2023). Adjoint Waveform Tomography for Crustal and Upper Mantle Structure the Middle East and Southwest Asia for Improved Waveform Simulations Using Openly Available Broadband Data, technical report, LLNL-TR- 851939. <strong>Acknowledgements</strong> This project was support by Lawrence Livermore National Laboratory’s Laboratory Directed Research and Development project 20-ERD-008 and the National Nuclear Security Administration. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. LLNL-MI-852402