Network Sensitivity Solutions for Regional Moment-Tensor Inversions

Well-resolved moment-tensor solutions reveal information about the sources of seismic waves. In this paper, we introduce a new way of assessing confidence in the regional full moment-tensor inversion via the introduction of the network sensitivity solution (NSS). The NSS takes into account the unique station distribution, frequency band, and signal-to-noise ratio of a given event scenario. The NSS compares both a hypothetical pure source (for example, an explosion or an earthquake) and the actual data with several thousand sets of synthetic data from a uniform distribution of all possible sources. The comparison with a hypothetical pure source provides the theoretically best-constrained source-type distribution for a given set of stations; and with it, one can determine whether further analysis with the data is warranted. The NSS that employs the actual data gives a direct comparison of all other source types with the best-fit source. In this way, one can choose a threshold level of fit in which the solution is comfortably constrained. The method is tested for the well-recorded nuclear test, JUNCTION, at the Nevada Test Site. Sources that fit comparably well to a hypothetical pure explosion recorded with no noise at the JUNCTION data stations have a large volumetric component and are not described well by a double-couple (DC) source. The NSS using the real data from JUNCTION is even more tightly constrained to an explosion because the data contain some energy that precludes fitting with any type of deviatoric source. We also calculate the NSS for the October 2006 North Korea test and a nearby earthquake, where the station coverage is poor and the event magnitude is small. The earthquake solution is very well fit by a DC source, and the best-fit solution to the nuclear test (M-w 4.1) is dominantly explosion.