A Global Database of Strong‐Motion Displacement GNSS Recordings and an Example Application to PGD Scaling

Abstract

Displacement waveforms derived from Global Navigation Satellite System (GNSS) data have become more commonly used by seismologists in the past 15 yrs. Unlike strong-motion accelerometer recordings that are affected by baseline offsets during very strong shaking, GNSS data record displacement with fidelity down to 0 Hz. Unfortunately, fully processed GNSS waveform data are still scarce because of limited public availability and the highly technical nature of GNSS processing. In an effort to further the use and adoption of high-rate (HR) GNSS for earthquake seismology, ground-motion studies, and structural monitoring applications, we describe and make available a database of fully curated HR-GNSS displacement waveforms for significant earthquakes. We include data from HR-GNSS networks at near-source to regional distances (1-1000 km) for 29 earthquakes between M w 6.0 and 9.0 worldwide. As a demonstration of the utility of this dataset, we model the magnitude scaling properties of peak ground displacements (PGDs) for these events. In addition to tripling the number of earthquakes used in previous PGD scaling studies, the number of data points over a range of distances and magnitudes is dramatically increased. The data are made available as a compressed archive with the article.

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“…Scaling laws have been derived from PGD observations, and made operational in real time. These relate the observed PGD, as a function of source to site distance, to the final magnitude of an earthquake (Text S4; Melgar et al, ; Crowell et al, ; Ruhl et al, ). Specifically, we applied the algorithm described by Melgar et al () which inverts the PGD observations and solves for magnitude.…”

“…The PGA, PGV, and PGD for all strong‐motion (PGA and PGV) and GNSS recordings (PGD) of these earthquakes are in Figure , along with values from a global database of 16 large ( M 6– M 9) megathrust earthquakes recorded by both geodetic and strong motion networks (Ruhl et al, ; Ruhl et al, ). These are plotted along with the estimated values for each intensity measure from ground‐motion models (GMMs).…”

“…As such, they represent “mean” earthquake behavior, and GMM residuals show deviations of a particular event's properties from the mean (Baltay & Boatwright, ; Sahakian, Baltay, et al, , Sahakian, Melgar, et al, ). Using waveforms from the two databases of HR‐GNSS and acceleration data (Ruhl et al, , ), we find the observed values of peak ground acceleration (PGA), peak ground velocity (PGV), and peak ground displacement (PGD), for near‐field sites (<500 km away from the event). PGA and PGV are obtained from the strong motion data while PGD is from the HR‐GNSS observations.…”

“…The HR‐GNSS data analyzed in this study are from the global database of HR‐GNSS recordings from Ruhl et al (), and the strong‐motion data are from a follow up global earthquake early warning study by Ruhl et al (). Both of those data sets are freely available, and the peak intensity measures can be found in Table S2.…”

“…In particular, for the strong motion data of the Mentawai earthquake we would like to thank Agency for Meteorology, Climatology and Geophysics of Indonesia (BMKG). GNSS data are available for download from Ruhl et al (), https://zenodo.org/record/1434374), and strong‐motion data are available for download from the Ruhl et al () paper (https://zenodo.org/record/1469833). Mentawai strong‐motion records are available at Zenodo (Sahakian et al, ).…”