Sn Attenuation in the Middle-East

Abstract:

The Turkish-Iranian Plateau and Zagros Mountains, a dominant tectonic feature in the Middle-East, were formed as a result of the continental collision (between Arabian plate and Eurasia plates). In order to better understand the nature of the lithosphere mantle and origin of the measure seismic velocity anomalies we have made detailed measurements of the uppermost mantle attenuation using the high frequency regional phase Sn.

In order to measure Sn attenuation. We have collected a large data set consisting of 18 years (1995-2012) of waveforms recorded by 305 permanent and temporary stations. We used a bandpass filter (0.1-0.5Hz) to identify efficient longer period Sn phases. In order to determine Sn Q we applied a Two Station Method (TSM) and Reverse Two Station Method (RTM) to eliminate the source effects. We have used the LSQR algorithm to tomographically map Sn attenuation tomography across the Middle-East.

We also determined the Sn propagation efficiencies visually and tomographically map qualitatively assigned Sn propagation efficiencies across the Middle-East.

The Sn Attenuation Tomography show moderately low Q values beneath the Turkish-Iranian Plateau (~250) and high Q values beneath the south Caspian sea (~400) and Arabian shield (~400). We also observe high Q values beneath the Zagros mountains (~450) that is consistent with the Arabian plate underthrusting beneath the Eurasia plate.

The Sn Efficiency Tomography shows high attenuation within the Turkish-Iranian Plateau and low attenuation in the Arabian Plate and across the Caspian Sea. This is consistent with prior studies that suggest a hot and thin lithosphere beneath the Turkish-Iranian Plateau and it also suggests that intrinsic attenuation is the dominant component in Sn Q across the Turkish-Iranian Plateau.

Due to the signal-to-noise criterion to select amplitudes and the efficiency criterion to select two-station and reverse-two-station paths for the inversion, the data are left-censored and the resulting Q models are incomplete in many regions. As a result, we are now working on a technique to predict missing amplitude caused by Sn blockage and thus avoid biasing our Sn Q model.