Because ambient seismic noise provides estimated Green’s function （EGF） between two sites with high accuracy, Rayleigh wave propagation along the path connecting the two sites is well resolved. Therefore, earthquak...Because ambient seismic noise provides estimated Green’s function （EGF） between two sites with high accuracy, Rayleigh wave propagation along the path connecting the two sites is well resolved. Therefore, earthquakes which are close to one seismic station can be well located with calibration extracting from EGF. We test two algorithms in locating the 1998 Zhangbei earthquake, one algorithm is waveform-based, and the other is traveltime-based. We first compute EGF between station ZHB （a station about 40 km away from the epicenter） and five IC/IRIS stations. With the waveform-based approach, we calculate 1D synthetic single-force Green’s functions between ZHB and other four stations, and obtain traveltime corrections by correlating synthetic Green’s functions with EGFs in period band of 10–30 s. Then we locate the earthquake by minimizing the differential travel times between observed earthquake waveform and the 1D synthetic earthquake waveforms computed with focal mechanism provided by Global CMT after traveltime correction from EGFs. This waveform-based approach yields a location which error is about 13 km away from the location observed with InSAR. With the traveltime-based approach, we begin with measuring group velocity from EGFs as well as group arrival time on observed earthquake waveforms, and then locate the earthquake by minimizing the difference between observed group arrival time and arrival time measured on EGFs. This traveltime-based approach yields accuracy of 3 km, Therefore it is feasible to achieve GT5 （ground truth location with accuracy 5 km） with ambient seismic noises. The less accuracy of the waveform-based approach was mainly caused by uncertainty of focal mechanism.展开更多
The method of extracting Green＇s function between stations from cross correlation has proven to be effective theoretically and experimentally. It has been widely applied to surface wave tomography of the crust and up...The method of extracting Green＇s function between stations from cross correlation has proven to be effective theoretically and experimentally. It has been widely applied to surface wave tomography of the crust and upmost mantle. However, there are still controversies about why this method works. Snieder employed stationary phase approximation in evaluating contribution to cross correlation function from scatterers in the whole space, and concluded that it is the constructive interference of waves emitted by the scatterers near the receiver line that leads to the emergence of Green＇s function. His derivation demonstrates that cross correlation function is just the convolution of noise power spectrum and the Green＇s function. However, his derivation ignores influence from the two stationary points at infinities, therefore it may fail when attenuation is absent. In order to obtain accurate noise-correlation function due to scatters over the whole space, we compute the total contribution with numerical integration in polar coordinates. Our numerical computation of cross correlation function indicates that the incomplete stationary phase approximation introduces remarkable errors to the cross correlation function, in both amplitude and phase, when the frequency is low with reasonable quality factor Q. Our results argue that the dis- tance between stations has to be beyond several wavelengths in order to reduce the influence of this inaccuracy on the applications of ambient noise method, and only the station pairs whose distances are above several （〉5） wavelengths can be used.展开更多
Seismic ambient noise of surface wave tomography was applied to estimate Rayleigh wave empirical Green＇s functions （EGFs） and then to study crust and uppermost mantle structure beneath the Makran region in south-ea...Seismic ambient noise of surface wave tomography was applied to estimate Rayleigh wave empirical Green＇s functions （EGFs） and then to study crust and uppermost mantle structure beneath the Makran region in south-east 1mn. 12 months of continuous data from January 2009 through January 2010, recorded at broadband seismic stations, were analyzed. Group velocities of the fundamental mode Rayleigh wave dispersion curves were obtained from the empirical Green＇s functions. Multiple- filter analysis was used to plot group velocity variations at periods from 10 to 50 s. Using group velocity dispersion curves, 1-D Vs velocity models were calculated between several station pairs. The final results demonstrate signifi- cant agreement to known geological and tectonic features. Our tomography maps display low-velocity anomaly with SW-NE trend, comparable with volcanic arc settings of the Makran region which may be attributable to the geometry of Arabian Plate subducting beneath the overriding the Lut block. The northward subducting Arabian Plate is deter- mined by high-velocity anomaly along the Straits of Hor- muz. At short periods （〈20 s）, there is a sharp transition boundary between low- and high-velocity transition zone with the NW trending at the western edge of Makran which is attributable to the Minab fault system.展开更多
基金supported by Chinese Acadmy of Sciences Fund(No.KCZX-YW-116-1)Joint Seismological Science Fundation of China (Nos.20080878 and 200708035)
文摘Because ambient seismic noise provides estimated Green’s function （EGF） between two sites with high accuracy, Rayleigh wave propagation along the path connecting the two sites is well resolved. Therefore, earthquakes which are close to one seismic station can be well located with calibration extracting from EGF. We test two algorithms in locating the 1998 Zhangbei earthquake, one algorithm is waveform-based, and the other is traveltime-based. We first compute EGF between station ZHB （a station about 40 km away from the epicenter） and five IC/IRIS stations. With the waveform-based approach, we calculate 1D synthetic single-force Green’s functions between ZHB and other four stations, and obtain traveltime corrections by correlating synthetic Green’s functions with EGFs in period band of 10–30 s. Then we locate the earthquake by minimizing the differential travel times between observed earthquake waveform and the 1D synthetic earthquake waveforms computed with focal mechanism provided by Global CMT after traveltime correction from EGFs. This waveform-based approach yields a location which error is about 13 km away from the location observed with InSAR. With the traveltime-based approach, we begin with measuring group velocity from EGFs as well as group arrival time on observed earthquake waveforms, and then locate the earthquake by minimizing the difference between observed group arrival time and arrival time measured on EGFs. This traveltime-based approach yields accuracy of 3 km, Therefore it is feasible to achieve GT5 （ground truth location with accuracy 5 km） with ambient seismic noises. The less accuracy of the waveform-based approach was mainly caused by uncertainty of focal mechanism.
基金supported by the National Natural Science Foundation of China (No. 40674027)CAS outstanding 100 research program,MOST program 2007FY220100
文摘The method of extracting Green＇s function between stations from cross correlation has proven to be effective theoretically and experimentally. It has been widely applied to surface wave tomography of the crust and upmost mantle. However, there are still controversies about why this method works. Snieder employed stationary phase approximation in evaluating contribution to cross correlation function from scatterers in the whole space, and concluded that it is the constructive interference of waves emitted by the scatterers near the receiver line that leads to the emergence of Green＇s function. His derivation demonstrates that cross correlation function is just the convolution of noise power spectrum and the Green＇s function. However, his derivation ignores influence from the two stationary points at infinities, therefore it may fail when attenuation is absent. In order to obtain accurate noise-correlation function due to scatters over the whole space, we compute the total contribution with numerical integration in polar coordinates. Our numerical computation of cross correlation function indicates that the incomplete stationary phase approximation introduces remarkable errors to the cross correlation function, in both amplitude and phase, when the frequency is low with reasonable quality factor Q. Our results argue that the dis- tance between stations has to be beyond several wavelengths in order to reduce the influence of this inaccuracy on the applications of ambient noise method, and only the station pairs whose distances are above several （〉5） wavelengths can be used.
文摘Seismic ambient noise of surface wave tomography was applied to estimate Rayleigh wave empirical Green＇s functions （EGFs） and then to study crust and uppermost mantle structure beneath the Makran region in south-east 1mn. 12 months of continuous data from January 2009 through January 2010, recorded at broadband seismic stations, were analyzed. Group velocities of the fundamental mode Rayleigh wave dispersion curves were obtained from the empirical Green＇s functions. Multiple- filter analysis was used to plot group velocity variations at periods from 10 to 50 s. Using group velocity dispersion curves, 1-D Vs velocity models were calculated between several station pairs. The final results demonstrate signifi- cant agreement to known geological and tectonic features. Our tomography maps display low-velocity anomaly with SW-NE trend, comparable with volcanic arc settings of the Makran region which may be attributable to the geometry of Arabian Plate subducting beneath the overriding the Lut block. The northward subducting Arabian Plate is deter- mined by high-velocity anomaly along the Straits of Hor- muz. At short periods （〈20 s）, there is a sharp transition boundary between low- and high-velocity transition zone with the NW trending at the western edge of Makran which is attributable to the Minab fault system.
