The cross correlation of ambient seismic noise recordings can be used to extract the empirical Green’s functions (hereafter EGFs) between pair of receivers (Shapiro and Compillo, 2004). In the past few years, extensive research has been performed on this topic around the world in various fields including travel‐time tomography (Sabra et al. , 2005; Shapiro et al. , 2005; Yao et al. , 2006; Yang et al. , 2007; Ward et al. 2013; Young et al. , 2013), anisotropy (Guo et al. , 2012; Shirzad and Shomali, 2014), fault detection (Shirzad et al. , 2013) and retrieving body wave (Poli et al. , 2012; Lin and Tsia, 2013; Boue et al. , 2014). Depending on various parameters including the quality of data and its frequency content, different processing approaches have been developed to obtain noise correlation. In the most approaches developed, the stacking was further assumed to be nonindependent on a particular phase. The main scope of these approaches is to remove the deterministic signals (e.g., earthquakes) and also extract the coherent part of ambient seismic noise (Stehly et al. , 2006; Pedersen et al. , 2007; Bensen et al. , 2008). In general, the extracted EGFs are dominated by the surface‐wave signal, even if two stations have a large interstation distance. Additionally, uneven noise source distribution may affect the extracted interstation EGFs of surface waves and consequently dispersion measurements (see Stehly et al. , 2006; Tsai, 2009; Yao and van der Hilst, 2009). Body waves may also be emerged by storm and/or swell interference (Landes et al. , 2010; Obrebski et al. , 2013). Obrebski et al. (2013) indicated that body and surface waves in random wavefields have different patterns resulted from distinctive amplification of ocean wave‐induced pressure …
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