Our recent study (Tajima et al., 2001) tested the feasibility of a new automated moment-tensor (AMT) determination system that continuously monitors seismic waveforms from a sparse network of regional broadband stations. This system uses real-time waveforms in a time window that is repeatedly shifted forward with a short time interval (20 sec), and unlike the current methods, performs inversion of moment tensors (MT's) over a grid that is set for a region of interest, without prior knowledge of the location and origin time information. The advantage of this system is its independency of the information that is currently provided by dense short-period networks. Significant improvement of the computational efficiency is expected if the system is fully configured on a powerful PC with multiple CPU's of 1 Gbyte memory, and the inversion over the grid can be updated within the time frame of time window shift (20 sec).
In the AMT inversion the time window of waveforms is shifted forward
by a prescribed amount . Therefore, the CPU time needed to compute
variance reductions () that is defined by
To make the AMT system operational and computationally effective, path calibration is necessary to account for the 3-D structure between virtual sources over the grid and stations. Currently three multi-layered models are used for calculating Green's functions (see the regionalization in Figure 22.1).
If Green's functions ( stands for a virtual source on the grid, for a station, and for the -th elementary moment-tesnsor) are calculated with well constrained velocity models and stored in the memory, the computation time will be shortened significantly, and the efficiency desired for the AMT system can be achieved. However, there is no short cut in calibrating paths for the 3D structure, and this project is still in progress. With Green's functions that account for 3D paths, the gridded structure of the methodology is ideally suited to achieve better resolution and stability.
for a km area. The total size of Green's functions for each station requires
If up to six stations should be used, the memory size will be about 750 Mb, and be slightly increased should the auto correlated Green's functions be also in the memory.
Figure 22.2 illustrates the projected time frame of the AMT as compared with the present standard system. The standard system at the BSL as part of the REDI (Gee et al., 1996; 2001) determines MT's for events of . The time frame between an event occurrence and MT determination (using 2 different methods) is 8-10 min. If the AMT system monitors seismic wavefield continuously, and updates the regional MT search over the grid every 20 sec, the time interval between the origin time and MT determination could be shortened by several minutes or more.
A tsunami warning system can be considered for an effective
application of the AMT method, as the event location and MT
can be determined early enough before the tsunami waves arrive at
the coasts. Here, the interval of the P-wave first arrival
at the station () and the tsunami arrival at the coast
() is roughly estimated as
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