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The Global Positioning System (GPS) has been repeatedly proven to be a powerful tool to estimate coseismic displacements and waveforms, with accuracies ranging from few millimeters to few centimeters. These promising results were achieved following two main strategies: differential positioning (DP) and precise point positioning (PPP;Bock et al. [1993], Kouba [2003], Larson et al. [2007], Larson [2009], Ohta et al. [2012], Xu et al.[2012], and Hung and Rau [2013]). In particular, both the modeling of fault rupture and the seismic moment estimation could benefit from GPS-derived displacements, because GPS is not affected by the saturation problems experienced by seismometers located near the epicenters of strong earthquakes. Thanks to the robustness of the GPS-derived displacement waveforms, in the last years some authors (Bock et al., 2000;Langbein and Bock, 2004;Blewitt et al., 2006;Bock and Genrich, 2006) addressed the problem to retrieve them in real time, with accuracies of a few centimeters, from GPS high-rate observations (1 Hz or more). In this context, the Variometric Approach for Displacements Analysis Standalone Engine (VADASE) has been proposed (Colosimo et al. [2011a], Colosimo [2013]). The approach is based on time single differences of carrier phase observations continuously collected using a standalone GPS receiver and on standard GPS broadcast products (orbits and clocks) that are available in real time. Therefore, one receiver works in standalone mode and the epoch-by-epoch displacements (equivalent to velocities) are estimated. Then, they are summed over the time interval when the earthquake occurred to retrieve displacements. Because VADASE does not require either additional technological complexity or a centralized data analysis, in principle, it can be embedded into the GPS receiver firmware and therefore can work in real time. Moreover, differently from DP and PPP, VADASE does not re-MO05 station (1 Hz observations over 120 s interval

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The 31 October 2013 M L 6.4 Ruisui earthquake was well recorded by twelve 50-Hz, four 20-Hz and thirteen 1-Hz GPS receivers, and twenty-five strong motion stations located within the epicentral distance of 90 km in eastern Taiwan. Kinematic positioning solutions estimated by four GNSS software (TRACK, RTKLIB, GIPSY, VADASE) are used to derive the seismic waveforms and the co-seismic displacements for this event; strong motion accelerometers are used to verify the capability of high rate GPS to detect seismic waves generated by this earthquake. Results show that the coordinate repeatability of the GPS displacements time series are ~6 mm and ~20 mm standard deviation in the horizontal and vertical components respectively, after applying spatial filtering. The largest co-seismic displacement derived from high-rate GPS is nearly 15 centimeter at 5 km northeast of the epicenter. S waves and surface waves are successfully detected by motions of high-rate GPS and double-integrated accelerometers within the 15 km epicentral distance. For the first time twelve 50-Hz and four 20 Hz GPS observations for seismological study were used and analyzed in Taiwan; a clear benefit was evidenced with regard to the seismic waves features detection, with respect to the 1-Hz GPS data, so that ultra-high rate (> 1-Hz) observations can compensate the sparse coverage of seismic data, provided proper monuments for the GPS permanent stations are realized. Spectra analysis between co-located GPS and strong motion data further suggests that the optimal sampling rate for high-rate GPS Seismology study is 5 Hz. The 2013 Ruisui Taiwan earthquake recorded by the high-rate GPS permanent stations network in Taiwan demonstrates the benefits of GPS Seismology for a moderate size earthquake at a local scale.