DOI: 10.25349/d9rk6h
title: Main Ethiopian Rift THBI Data

description: This data contains phase velocity maps in the form of .mat files, and in
 .xyz text files. Data is saved in the .xyz format as : Latitude,
 Longitude, phase velocity, standard deviation, and ray density. To be
 added later: RF's, and joint inversion final velocity profiles, also
 in the form of .mat files. 
description: Using the Automated Surface Wave phase velocity Measuring Systems
 (ASWMS) [jin 2015], we developed phase velocity maps at 25, 32, 40, 50,
 60, 80, and 100 s using Rayleigh waves from teleseismic earthquakes to
 characterize lower crustal and mantle wavespeeds. ASWMS autonomously
 estimates Rayleigh wave phase delays between nearby seismic stations using
 inter-station, frequency dependent cross-correlograms on a per-event basis
 at discrete periods. We used 5741 high quality earthquakes occurring
 between 2000-03-10 and 2017-10-03, of Mw &gt;= 5.5, with a maximum
 depth of 250 km, at a distance of 30 -160 degrees from from the center of
 our study area (12N, 39.5E). We processed vertical seismograms for all
 stations between 4N and 20N latitude, and 34E to 45E longitude. Our data
 comprises 415 stations, and 17 public networks dowloaded from the IRIS
 DMC. For each earthquake, vertical cross-correlograms,
 C(t), were computed in the time domain for each possible station pair
 according to: <br> C(t)=S<sub>1</sub>
 *W<sub>s</sub> S<sub>2</sub><br> <br>
 where S<sub>1</sub> and S<sub>2</sub> are the
 de-trended, windowed, vertical seismograms of the two stations with
 instrument response removed, and * denotes cross-correlation.
 W<sub>s</sub> is a 300 s windowing function, with a 75 s
 Hanning taper. C(t) contains lag and coherency information about the
 Rayleigh wave energy traveling between the two stations. The dominant
 energy of the waveform was isolated using another windowing function,
 W<sub>c</sub>(t), and then filtered using a series of Gaussian
 narrow band filters. By fitting the filtered, windowed cross-correlogram
 function, F<sub>i</sub>*(W<sub>c</sub>C(t)) using
 a 5-parameter Gaussian wavelet we extracted frequency-dependent phase
 delays, t<sub>p</sub>, for this station pair.
 Station pairs with inter-station distance (in km) less than 5, or
 greater than 3.55 x the period (in seconds), were discarded to reduce the
 possibility of cycle skipping or spurious measurements. Station pairs with
 cross-coherency gamma<sup>2 </sup>&lt;0.6 were discarded
 to prevent measurement on poorly correlated cross-correlograms.
 t<sub>p</sub> were then inverted using the Eikonal equation to
 develop inter-station phase travel time surfaces at each period [lin
 2009]. Regularization for this step is implemented as in
 [jin2015]. Events for which more station pairs were
 discarded than not were also discarded from the stacks. We also culled
 measurements within earthquake phase velocity maps that had apparent
 velocities below 3.1 km/s or above 4.8 km/s, as velocities outside these
 bounds are unrealistic for continental crust between 25 to 100 s. We
 pieced together temporally and spatially isolated regions by stacking
 individual pixels from events. Pixels were included in the final stack if
 the number of rays crossing those pixels from all event maps exceeded 66
 (providing on average one ray entering each pixel per km of
 circumference). Pixels in the same location between different events were
 assigned a weight, Wg, where Wg = { of rays in event} \ {total
 rays},  such that events with a greater number of observations contributed
 more to the final stack phase velocity. Pixels with phase velocities more
 than three standard deviations from the stack mean were also excluded from
 the final stack. Maps were smoothed using a linear function with a
 lengthscale of 0.4x the wavelength.<br>  
description: The .xyz files are in a very straightforward format: x,y
 locations, a phase velocity, and the standard deviation, which should be
 applicable for most any usage.