Abstract

The traditional Ms:mb discrimination method is routinely used for distinguishing between earthquakes and explosions within dense networks, but there is a need to improve discrimination at smaller magnitudes; therefore, we need magnitude scales that can successfully be applied to data from sparse networks. We developed a unified Rayleigh‐ and Love‐wave magnitude scale (MsU) that is designed to maximize available information from single stations and then combine magnitude estimates into network averages. By combining Love‐ and Rayleigh‐wave amplitudes, we minimize the effect of earthquake radiation patterns from sparse networks, thereby improving discrimination between earthquakes and explosions. MsU is built from Ms(VMAX) (Russell, 2006) and is calculated from Love and Rayleigh waves that are narrowband filtered and corrected for propagation and source effects at periods between 8 and 25 s to find filter bands of maximum energy propagation. The data are also corrected for censoring effects at the station level, because either Rayleigh or Love waves may be below the signal‐to‐noise ratio threshold at a given period.

We applied MsU to 39 earthquakes (3.21<Mw<5.08) located in the Yellow Sea and Korean Peninsula region, as well as to the three North Korean nuclear tests (4.1<mb<5.1). By using MsU:mb as a discriminant, there is an increase in the separation of small magnitude earthquakes and explosions in sparse networks and a significant reduction in outliers, as shown in the application from the Korean Peninsula. This research addresses the theory, methods, and capability of MsU as a discriminant.

Online Material: Detailed spectral analysis and MsU censoring algorithm, and figures of filter specifications.

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