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We collect two months of ambient noise data recorded by 35 broad-band seismic stations in a 9 × 11 km area (1–3 km station interval) near Karamay, China, and do cross-correlation of noise data between all station pairs. Array beamforming analysis of the ambient noise data shows that ambient noise sources are unevenly distributed and the most energetic ambient noise mainly comes from azimuths of 40°–70°. As a consequence of the strong directional noise sources, surface wave components of the cross-correlations at 1–5 Hz show clearly azimuthal dependence, and direct dispersion measurements from cross-correlations are strongly biased by the dominant noise energy. This bias renders that the dispersion measurements from cross-correlations do not accurately reflect the interstation velocities of surface waves propagating directly from one station to the other, that is, the cross-correlation functions do not retrieve empirical Green's functions accurately. To correct the bias caused by unevenly distributed noise sources, we adopt an iterative inversion procedure. The iterative inversion procedure, based on plane-wave modeling, includes three steps: (1) surface wave tomography, (2) estimation of ambient noise energy and biases and (3) phase velocities correction. First, we use synthesized data to test the efficiency and stability of the iterative procedure for both homogeneous and heterogeneous media. The testing results show that: (1) the amplitudes of phase velocity bias caused by directional noise sources are significant, reaching ∼2 and ∼10 per cent for homogeneous and heterogeneous media, respectively; (2) phase velocity bias can be corrected by the iterative inversion procedure and the convergence of inversion depends on the starting phase velocity map and the complexity of the media. By applying the iterative approach to the real data in Karamay, we further show that phase velocity maps converge after 10 iterations and the phase velocity maps obtained using corrected interstation dispersion measurements are more consistent with results from geology surveys than those based on uncorrected data. As ambient noise in high-frequency band (>1 Hz) is mostly related to human activities or climate events, both of which have strong directivity, the iterative approach demonstrated here helps improve the accuracy and resolution of ANT in imaging shallow earth structures.13 page(s

geophysical journal international

Correction of phase velocity bias caused by strong directional noise sources in high-frequency ambient noise tomography: a case study in Karamay, China