Detection and analysis of seismic induced GNSS station motion in a North American network following the 2017 Chiapas earthquake

The 2017 Chiapas earthquake with moment magnitude M_w = 8.2, caused seismic induced surface motion which has been well recorded and analyzed globally using broadband seismometers. In contrast, Global Navigation Satellite System (GNSS) measurements of absolute receiver positions at cm accuracy have been marginally used for seismic wave analysis. We show that GNSS station displacement measurements, located in North America, can detect traveling seismic surface waves through a GNSS network for the 2017 Chiapas earthquake with a single station precise point positioning (PPP) measurement accuracy of 1–2 cm, evaluating 1 Hz data. We found that the network data show a total amplitude in temporal filtered horizontal displacement data of up to 5 cm, which is in good agreement with absolute measurements of a broadband seismometer. The multi constellation (primarily GPS and GLONASS) GNSS measurements are most sensitive to seismic surface waves such as e.g. given by Love and Rayleigh wave components in the frequency range of 20–35 s determined by FTAN (Frequency Time Analysis) where the Rayleigh component dominates the measured GNSS signals. We provide estimates of phase velocities and epicenter location determined by a cross-correlation procedure and evaluate its accuracy within the framework of a comparison to state-of-the-art seismic models. Hereby GNSS station data suffer from double measurement noise in the vertical displacement component, which results in a low signal to noise ratio that deny proper pressure wave analysis. While the derived phase velocities have typical uncertainties of 200 m/s in standard deviation, which may seem inappropriate for geophysical interpretation of a single station they might be appropriate in a large and dense GNSS network (spatial distance < 25 km). Determination of the seismic source location is possible and even offers the ability to provide tsunami early warning. Consequently, we see GNSS network station data may be a complementary and independent observation type – prior to well established geophone or accelerometer measurements – which is suited for seismic wave detection and analysis, although limited in accuracy.