عنوان مقاله [English]
نویسندگان [English]چکیده [English]
Recent progress in seismology has demonstrated that empirical Greenâs functions (EGFs) of inter-station distances can be extracted using cross correlation of ambient seismic noise recorded in the similar time at two stations (Weaver and Lobkis, 2002; Shapiro and Compillo, 2004; Wapenaar, 2004). Consequently, this method provides a great set of data even in low seismicity regions to apply in the tomographic studies. Thus, the resulted tomographic images using the ambient seismic noise method (hereafter ANT) can showÂ interior earth structures with a higher resolution compared to classical tomography methods (Shapiro et al, 2005; Lin et al., 2007; Shirzad et al, 2013).
Diffused signals are the main assumption in the ANT method (Snider, 2004). Ambient seismic noise sources generate a coherent and transient noise wavefield with random amplitude and phase in a medium (Van-Tighelen, 2003; Gorin et al., 2006). Reconstruction of the propagating path information using the amplitude of the recorded noise wavefield is impossible, but coherent information provided by propagating path can be extracted using cross correlation of long time ambient seismic noise recorded (Weaver and Lobkis, 2004; Gorin et al., 2006). This coherent information is called elastic response of medium or empirical Greenâs functions (Shapiro and Compillo, 2004; Roux et al., 2005; Sabra et al., 2005).
Â Â Â Generally, the ambient seismic noise recorded for each station is composed of surface waves (Rayleigh and Love) with random amplitude and phase (Aki and Richards, 1980). Cross correlation function of these data will be symmetric if the ambient seismic noise wavefields generated by random sources are distributed uniformly (Snider, 2004). Earth structures can be studied using travel-time of extracted EGFs such as Rayleigh wave fundamental mode (Shapiro et al., 2005). Some studies (e.g. Stehly et al., 2006; Pedersen et al., 2007) indicate that the inhomogeneous distribution of the signal energy in various azimuths, which results in directionality of ambient seismic noise, produces deviation in tomography results and causes incorrect interpretations. Consequently, optimization of extracted tomographic maps based on the ANT method needs comprehensive knowledge of spatial and seasonal distribution of the noise wavefield in study areas (Stehly et al., 2006; Pedersen et al, 2007).
Â Â Â Gutenberg (1936) suggested that the sources of primary and secondary oceanic microseisms observed throughout the Europe are located in the northeastern Atlantic Ocean. Primary and secondary microseisms dominate the noise wavefield in certain frequency ranges. The interaction between the swell and the sea bottom generates the primary microseisms which are dominated by periods of 12â25 s. Also, interfering water wavefield components travelling in opposite directions generate the secondary microseisms which are dominated by periods of 5-10 s (Gutenberg, 1936).
Â Â Â In this study, we analyzed three-component recordings of continuous data from 30 stations in the Central Alborz region depicted in Figure 1. The Alborz Mountain range in the southern margin of the Caspian Sea is a part of the AlpineâHimalayan orogenic belt. The Alborz Mountain range resulted from a stress state derived from the horizontal compressive forces of the Central Iran Plateau has been induced by the collision of the Arabian plateau and the Asian continent (Berberian and King, 1981; Zanchi et al., 2006). The dataset used in this study consisted of 10 digital accelerometers with CMG-5TD sensors operated by the Tehran Disaster Mitigation and Management Organization (TDMMO), 18 digital narrow-band seismometers with SS1 seismometer sensors (corner frequency â¥1 Hz) operated by the Iranian Seismological Center (IRSC) at the University of Tehran, and two digital broadband instruments with a CMG-3T sensor operated by the International Institute of Earthquake Engineering and Seismology (IIEES). For the TDMMO acceleration network, the IRSC and the IIEES seismic networks continuous data from 2010 were analyzed.
Â Â Â In the case of azimuthal distribution of the ambient noise, normalized amplitude of the cross-correlations versus azimuth (rose-diagram) constrained the direction to the sources of the ambient seismic noise, based on all available station-pairs. The average fractions (the number of Love/Rayleigh path with a SNR>10 in a given 20Â° azimuthal bin was normalized to the total number of Love/Rayleigh paths in that given bin) of the Love and Rayleigh yearly empirical Greenâs functions with a SNR>10 were in the orders of 0.78 and 0.73, respectively, at the period band of 1â10 s. Our final results indicated that the average fractions per cent of Love and Rayleigh paths with SNR>10 were above 68% and 64% on a yearly scale, and never decreased to 45% and 50% on a monthly scale at the period band of 1-10 s, respectively.