Since the 1960s, array seismology has been developed mainly due to the need for detection of nuclear tests. Now there are many seismic arrays of various sizes in the world which are used for detecting nuclear tests, but also very weak but important seismic phases for refining fine-scale structure of the deep earth.
In this study, we are interested in weak low-frequency surface waves. Low-frequency surface waves are usually the dominant phases in waveforms generated from earthquake. They have been widely used for determining global earth structure and for the retrieval of earthquake source parameters. In addition, they can be used for detecting the existence of special types of seismic sources, such as slow/silent earthquakes(Beroza and Jordan, 1990), back ground free oscillations (Ekström, 2001) and other unknown sources. Usually, the low-frequency surface waves generated from these kinds of sources are too weak to be detected by a single station.
The main goal of this study is to detect weak energy from some low-frequency seismic sources and locate them. To do that, we need to design an optimal array method and guarantee this method to work. Hereafter we call this optimal method an array-based method.
Most array methods are based on beam forming method
(Rost and Thomas, 2002). Beam forming method can enhance
the amplitudes of the same phases with an identical horizontal slowness
u. For body waves, each phase has
a constant slowness, but surface
waves are dispersive, that is, slowness
is a function of frequency. Our array-based method is also based
on beam forming, but it does not use constant slowness,
it uses the dispersive property of surface wave.
The following equation describes the propagation of surface waves over a distance from the source, in the frequency domain.
Our detection method is not completely established. Although we still need more refined detector which can identify signal from noise, the detection of the signal from large events ( 6.0) is obvious because they have much larger amplitudes relative to the back ground amplitude level. Figure 24.1 shows maximum averaged amplitudes in back azimuth as a function of time calculated for three different arrays - FNET (Japan), GRSN (Germany) and BDSN (Northern California). Because low-frequency displacement amplitudes are proportional to scalar seismic moment, maximum averaged amplitudes can be tied to by introducing a scaling factor. Most signals due to large events can be clearly identified in all three arrays. The background noise levels are different for three arrays, GRSN shows much larger noise level than other two networks. This difference can be explained partly by different internal noise of seismometer in GRSN. GRSN consists of STS-2, but STS-1 is installed on other stations which are used in this study..
The final goal of application of array-based method is to detect and locate seismic sources. To check the reliability of the current method, we manually detect signals and compare their arrival time and back azimuth with those calculated from the earthquake catalog (Harvard CMT). There were 13 events with larger than 6 in January, 2000. All 13 events are clearly detected for three arrays. Comparison result is written in following table.
As you can see in the table, all measured back azimuths are within 20 deg. from actual back azimuths and time differences between measured and calculated times are not significant. It indicates that we can locate the source from measured parameters. This result shows an array-based method can measure arrival time and back azimuth precisely enough to locate the source when energy released from the source is quite large. We still need to know the limit of detection and whether there is any detectable signal due to sources that are not standard events. To do that, we will apply this method on whole data of 2000 and look at other frequency bands.
Dziewonski, A.M. and D.L. Anderson, Preliminary reference Earth model (PREM), Phys. Earth Planet. Inter., 25, 289-325, 1981
Ekström, G., Time domain analysis of Earth's long-period background seismic radiation, J. Geophys. Res., 106, 26,483-26,493, 2001.
Muirhead, K.J. and R. Datt, The N-th root process applied to seismic array data, Geophys. J. R. Astr. Soc., 47, 197-210, 1976.
Rost, S. and C. Thomas, Array seismology: Methods and applications, Rev. Geophys., 40(3), 1008, doi:10.1029/2000RG000100, 2002.
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