[1] The Anatolian plateau-Caucasus-Caspian region is an area of complex lithospheric structure accompanied by large variations in seismic wave velocities. Despite the complexity of the region, little is known about the detailed lithospheric structure. Using data from 31 new, permanent broadband seismic stations along with results from a previous 29 temporary seismic stations and 3 existing global seismic stations in the region, a 3-D velocity model is developed using joint inversion of teleseismic receiver functions and surface waves. Both group and phase dispersion curves (Love and Rayleigh) were derived from regional and teleseismic events. Additional Rayleigh wave group dispersion curves were determined using ambient noise correlation. Receiver functions were calculated using P arrivals from 789 teleseismic (30°-90°) earthquakes. The stacked receiver functions and surface wave dispersion curves were jointly inverted to yield the absolute shear wave velocity to a depth of 100 km at each station. The depths of major discontinuities (sediment-basement, crust-mantle, and lithosphere-asthenosphere) were inferred from the velocity-depth profiles at the location of each station. Distinct spatial variations in crustal and upper mantle shear velocities were observed. The Kura basin showed slow (∼2.7-2.9 km/s) upper crustal (0-11 km) velocities but elevated (∼3.8-3.9 km/s) velocities in the lower crust. The Anatolian plateau varied from ∼3.1-3.2 in the upper crust to ∼3.5-3.7 in the lower crust, while velocities in the Arabian plate (south of the Bitlis suture) were slightly faster (upper crust between 3.3 and 3.4 km/s and lower crust between 3.8 and 3.9 km/s). The depth of the Moho, which was estimated from the shear velocity profiles, was 35 km in the Arabian plate and increased northward to 54 km at the southern edge of the Greater Caucasus. Moho depths in the Kura and at the edge of the Caspian showed more spatial variability but ranged between 35 and 45 km. Upper mantle velocities were slow under the Anatolian plateau but increased to the south under the Arabian plate and to the east (4.3-4.4 km/s) under the Kura basin and Greater Caucasus. The areas of slow mantle coincided with the locations of Holocene volcanoes. Differences between Rayleigh and Love dispersions at long wavelengths reveal a pronounced variation in anisotropy between the Anatolian plateau and the Kura basin.

Descriptions of validation events and scenarios; fixed and region-dependent parameters; additional goodness-of-fit plots for ground-motion prediction equations (GMPEs) versus data, simulations versus GMPEs, and pseudospectral accelerations (PSA) bias versus distance; and comparison of rupture models with associated PSA bias and time histories for Landers.

Ground‐motion simulations can be viable alternatives to empirical relations for seismic hazard analysis when data are sparse. Interfrequency correlation is revealed in recorded seismic data, which has implications for seismic risk (Bayless and Abrahamson, 2018a). However, in many cases, simulated ground‐motion time series, in particular those originating from stochastic methods, lack interfrequency correlation. Here, we develop a postprocessing method to rectify simulation techniques that otherwise produce synthetic time histories deficient in an interfrequency correlation structure. An empirical correlation matrix is used in our approach to generate correlated random variables that are multiplied in the frequency domain with the Fourier amplitudes of the synthetic ground‐motion time series. The method is tested using the San Diego State University broadband ground‐motion generation module, which is a broadband ground‐motion generator that combines deterministic low‐frequency and stochastic high‐frequency signals, validated for the median of the spectral acceleration. Using our method, the results for seven western U.S. earthquakes with magnitude between 5.0 and 7.2 show that empirical interfrequency correlations are well simulated for a large number of realizations without biasing the fit of the median of the spectral accelerations to data. The best fit of the interfrequency correlation to data is obtained assuming that the horizontal components are correlated with a correlation coefficient of about 0.7.

The Southern California San Jacinto fault is geometrically complex, consisting of several major strands with smaller scale complexity within each strand. The two northernmost strands, the Claremont and the Casa Loma-Clark, are separated by a 25-km-long extensional stepover with an average of 4 km separation between the strands. We use a combined modeling method to assess probable rupture and groundmotion behaviors for this stepover. First, dynamic rupture modeling on geometrically complex fault strands embedded in a state-of-the-art 3D crustal velocity model is used to generate a series of scenario earthquakes. We then use the resulting near-fault lowfrequency (< 1 Hz) ground-motion time histories to generate broadband synthetic seismograms with a hybrid approach. These synthetics are then compared with a distribution of precariously balanced rocks (PBRs) near the fault to constrain our results and assess shaking hazard for the region surrounding the fault. Our dynamic models produce sources between M w 5.4 and 6.9, with rupture limits imposed by sharp contrasts in fault stress or by geometrical barriers. The main stepover serves as a primary barrier to rupture in our model, producing event sizes that are consistent with the historical behavior of the San Jacinto fault. The largest broadband synthetics are a good match to leading ground-motion prediction equations and are generally consistent with the distribution of PBRs, none of which experience accelerations that produce toppling probabilities significantly higher than zero. Thus, although the PBRs do not rule out any of our model scenarios, they confirm that our models produce realistic rupture extents and shaking.Online Material: Figures of total slip for additional rupture models, low-frequency intensity plots, synthetic seismograms, and comparison with ground-motion prediction equations.

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