------------------- GENERAL INFORMATION ------------------- 1. Title of Dataset Data for: Effects of 2.5-D ultra-low and ultra-high velocity zones on flip-reverse-stacking (FRS) of the ScS wavefield 2. Author Information Principal Investigator Contact Information Name: Michael S. Thorne Institution: University of Utah Address: Frederick Albert Sutton Building 115 S 1460 E, ROOM 383 Salt Lake City, UT 84112-0102 Email: michael.thorne@utah.edu ORCID: 0000-0002-7087-1771 3. Date of data collection (single date, range, approximate date): Data included here were collected from approximately 1/1/2024 to 6/1/2024. 4. Geographic location of data collection (where was data collected?): NA 5. Information about funding sources that supported the collection of the data: This work was supported by NSF grant EAR-2132400. -------------------------- SHARING/ACCESS INFORMATION -------------------------- 1. Licenses/restrictions placed on the data: Public Domain – This data is free of copyright restrictions (e.g. government sponsored data). 2. Links to publications that cite or use the data: Thorne, Michael S., Pachhai, Surya, and Garnero, Edward J. (2024) Effects of 2.5-D ultra-low and ultra-high velocity zones on flip-reverse-stacking (FRS) of the ScS wavefield 3. Links to other publicly accessible locations of the data: NA 4. Links/relationships to ancillary data sets: NA 5. Was data derived from another source? Yes This collection of data were compiled from publicly available data sources: (1) Incorporated Research Institutions for Seismology (IRIS) (2) the Caltech/USGS Southern California Earthquake Data Center (SCEDC), The earthquake used in this study occurred on Oct. 22, 2008. 6. Recommended citation for the data: Michael S. Thorne. 2024. "Data for: Effects of 2.5-D ultra-low and ultra-high velocity zones on flip-reverse-stacking (FRS) of the ScS wavefield". The Hive: University of Utah Research Data Repository. DOI 10.7278/S5d-gsmt-m8bc --------------------- DATA & FILE OVERVIEW --------------------- 1. File List A. Filename: DATA.tar.gz Short description: Seismic data are provided for 1 earthquake occurring on Oct. 22, 2008. Data for this earthquake is provided in its own directory. The naming convention for each directory is: yyyymmddhhmm (i.e., the directory name is given in terms of event year, month, day, hour, and minute that the earthquake occurred). Within each directory the seismograms for that earthquake are stored in Seismic Analysis Code (SAC) format. Tangential component seismograms are given that are windowed in time around the S seismic arrival. The naming convention of each file is: eventid.network.stationcode.component.sac eventid = the same ID as given above (yyyymmddhhmm) for the event network = the two letter seismic network code for the station stationcode = the seismic station abbreviation component = either BHT or HHT for broadband tangential or highgain tangential component seismogram sac = file format (seismic analysis code) In total: 834 individual seismic recordings are provided. 2. Relationship between files: NA 3. Additional related data collected that was not included in the current data package: NA 4. Are there multiple versions of the dataset? No B. Filename: 1-D_UHVZ_MODELS.tar.gz Short description: Synthetic seismograms computed for 1-D UHVZ models used in this study are provided. Synthetics are computed for 620 1-D models. All synthetics are computed using the SHaxi method (see Jahnke et al. 2008 for details on the method). All synthetics are computed for a 500 km deep source and are tangential component recordings. Synthetics are windowed in time from -50 s to +150 s with respect to the direct S-wave arrival. Within each model directory there are 401 synthetic seismograms computed on an epicentral distance interval of 0.1 deg. Model parameters are given in the model directory. The naming convention is uvhz_dVs_thickness_density_length_edge-position. For example, uhvz_23_h40_r5_w180_e0, corresponds to a model with dVs=+23%, a thickness of h=40 km, a density of +5%, a length in the great circle arc direction of l=180 deg, with an l1 edge position of 0 deg. In total: 248,620 synthetic seismograms for 1-D UHVZ models are provided. 2. Relationship between files: NA 3. Additional related data collected that was not included in the current data package: NA 4. Are there multiple versions of the dataset? No C. Filename: 2.5-D_UHVZ_MODELS.tar.gz Short description: Synthetic seismograms computed for 2.5-D UHVZ models used in this study are provided. Synthetics are computed for 624 2.5-D models. All synthetics are computed using the SHaxi method. Parameters and naming conventions are the same as for the 1-D models. In total: 250,224 synthetic seismograms for 2.5-D UHVZ models are provided. 2. Relationship between files: NA 3. Additional related data collected that was not included in the current data package: NA 4. Are there multiple versions of the dataset? No -------------------------- METHODOLOGICAL INFORMATION -------------------------- 1. Description of methods used for collection/generation of data: All of the earthquakes occurred in the Fiji/Tonga retion. Data collection is described in the manuscript associated with this data collection. Synthetic seismograms were computed using the SHaxi method. See the following paper for a description of the numerical approach for computing the synthetic seismograms: Jahnke, G., Thorne, M.S., Cochard, A., Igel, H., Global SH-wave propagation using a parallel axi-symmetric spherical finite-difference scheme: application to whole mantle scattering, Geophysical Journal International, doi: 10.1111/j.1365-246X.2008.03744.x, 2008. The background model used is a smoothed version of the PREM model. In this model the crust is removed with the upper mantle properties extended to the surface. In addition, the upper mantle discontinuties (220 km, 410 km, and 670 km) are smoothed in order to reduce additional small amplitude arrivals that interfere with the ScS wavefield. Because of these modifications, the absolute arrival time of the direct S-wave arrival may not match the predicted arrival times of the PREM model. 2. Methods for processing the data: