Abstract and subjects
Love waves have the potential to aid in discrimination for anomalous explosion events. We develop a calibrated mathematical formulation for an explosion discriminant that combines Rayleigh-and Love-wave magnitude values and employs an error model that correctly partitions variances among events and stations separately. The discriminant is calibrated using a global data set of 124 earthquakes and 26 nuclear explosions and applied to the May 2009 Democratic Republic of North Korea (DPRK) announced nuclear test, as well as the calibration data set. All 26 explosions were correctly identified; only 6 earthquakes were incorrectly identified as explosions. Compared to an analogous treatment using only Rayleigh data, the combined discriminant improves the DPRK event p-value only nominally but reduces the number of false positives in the calibration data set by 70%, with no additional false negatives. While not dramatically improving the discrimination power for anomalous events, such as the 2009 DPRK test, the combined discriminant proposed here offers improved screening capabilities for typical events.