Crustal and upper-mantle structure in the Eastern Mediterranean from the analysis of surface wave dispersion curves

The dispersive properties of surface waves are used to infer earth structure in the Eastern Mediterranean region. Using group velocity maps for Rayleigh and Love waves from 7100 s, we invert for the best 1D crust and uppermantle structure at a regular series of points. Assembling the results produces a 3D lithospheric model, along with corresponding maps of sediment and crustal thickness. A comparison of our results to other studies finds the uncertainties of the Moho estimates to be about 5 km. We find thick sediments beneath most of the Eastern Mediterranean basin, in the Hellenic subduction zone and the Cyprus arc. The Ionian Sea is more characteristic of oceanic crust than the rest of the Eastern Mediterranean region as demonstrated in particular by the crustal thickness. We also find significant crustal thinning in the Aegean Sea portion of the backarc, particularly towards the south. Notably slower Swave velocities are found in the uppermantle, especially in the northern Red Sea and Dead Sea Rift, central Turkey, and along the subduction zone. The low velocities in the uppermantle that span from North Africa to Crete, in the Libyan Sea, might be an indication of serpentinized mantle from the subducting African lithosphere. We also find evidence of a strong reverse correlation between sediment and crustal thickness which, while previously demonstrated for extensional regions, also seems applicable for this convergence zone

An Analysis of the Mt. Meron Seismic Array

We have performed a quick analysis of the Mt. Meron seismic array to monitor regional seismic events in the Middle East. The Meron array is the only current array in the Levant and Arabian Peninsula and, as such, might be useful in contributing to event location, identification, and other analysis. Here, we provide a brief description of the array and a review of the travel time and array analysis done to assess its performance

Crustal thinning between the Ethiopian and East African Plateaus from modeling Rayleigh wave dispersion

The East African and Ethiopian Plateaus have long been recognized to be part of a much larger topographic anomaly on the African Plate called the African Superswell. One of the few places within the African Superswell that exhibit elevations of less than 1 km is southeastern Sudan and northern Kenya, an area containing both Mesozoic and Cenozoic rift basins. Crustal structure and uppermost mantle velocities are investigated in this area by modeling Rayleigh wave dispersion. Modeling results indicate an average crustal thickness of 25 {+-} 5 km, some 10-15 km thinner than the crust beneath the adjacent East African and Ethiopian Plateaus. The low elevations can therefore be readily attributed to an isostatic response from crustal thinning. Low Sn velocities of 4.1-4.3 km/s also characterize this region

Reconciling data using Markov Chain Monte Carlo: An application to the Yellow Sea - Korean Peninsula region

In an effort to build seismic models that are most consistent with multiple data sets, we have applied a new probabilistic inverse technique. This method uses a Markov Chain Monte Carlo (MCMC) algorithm to sample models from a prior distribution and test them against multiple data types to generate a posterior distribution. While computationally expensive, this approach has several advantages over a single deterministic model, notably the reconciliation of different data types that constrain the model, the proper handling of uncertainties, and the ability to include prior information. We also benefit from the advantage of forward modeling rather than inverting the data. Here, we use this method to determine the crust and upper mantle structure of the Yellow Sea and Korean Peninsula (YSKP) region. We discuss the data sets, parameterization and starting model, outline the technique and its implementation, observe the behavior of the inversion, and demonstrate some of the advantages of this approach

Preliminary Definition of Geophysical Regions in Western Eurasia

The authors present a regionalized crustal model of Western Eurasia, WEA. The model is constructed using results from published studies and maps of geological and geophysical parameters in this region, and was developed in conjunction with the updated regionalization of Middle East and North Africa by Walter et al.[2000]. As this is the first realization of the Eurasian modeling effort, they have limited themselves to only twelve broad regions. Particular attention has been given to identifying the boundaries for each region. The main use of this model will be to assist in monitoring the Comprehensive Nuclear Test Ban Treaty (CTBT). Specifically, this model will help them to calibrate and predict the travel time and amplitudes of various regional seismic phases and to locate events accurately. The model based approach allows them to readily calibrate both the seismic and the aseismic parts of western Eurasia. Each region is specified by an one-dimensional model of compressional and shear velocities, densities and layer thicknesses. Further improvements to this model will involve, but not be limited to, increasing the spatial coverage toward the east and west of Eurasia, identify sub-regions based on their distinct physical properties and the use of new and improved body wave and surface wave datasets. In the future, they expect to use this model and its successors to be the baseline model for calibration techniques, e.g., kriging, to improve their capability to detect, locate and discriminate different seismic events in Eurasia

Surface Wave Simulation and Processing with MatSeis

In order to exploit the information on surface wave propagation that is stored in large seismic event datasets, Sandia and Lawrence Livermore National Laboratories have developed a MatSeis interface for performing phase-matched filtering of Rayleigh arrivals. MatSeis is a Matlab-based seismic processing toolkit which provides graphical tools for analyzing seismic data from a network of stations. Tools are available for spectral and polarization measurements, as well as beam forming and f-k analysis with array data, to name just a few. Additionally, one has full access to the Matlab environment and any functions available there. Previously the authors reported the development of new MatSeis tools for calculating regional discrimination measurements. The first of these performs Lg coda analysis as developed by Mayeda and coworkers at Lawrence Livermore National Laboratory. A second tool measures regional phase amplitude ratios for an event and compares the results to ratios from known earthquakes and explosions. Release 1.5 of MatSeis includes the new interface for the analysis of surface wave arrivals. This effort involves the use of regionalized dispersion models from a repository of surface wave data and the construction of phase-matched filters to improve surface wave identification, detection, and magnitude calculation. The tool works as follows. First, a ray is traced from source to receiver through a user-defined grid containing different group velocity versus period values to determine the composite group velocity curve for the path. This curve is shown along with the upper and lower group velocity bounds for reference. Next, the curve is used to create a phase-matched filter, apply the filter, and show the resultant waveform. The application of the filter allows obscured Rayleigh arrivals to be more easily identified. Finally, after screening information outside the range of the phase-matched filter, an inverse version of the filter is applied to obtain a cleaned raw waveform which can be used for amplitude measurements. Because all the MatSeis tools have been written as Matlab functions, they can be easily modified to experiment with different processing details. The performance of the propagation models can be evaluated using any event available in the repository of surface wave events

SPE 1 Data Quicklook report

Abstract not provide