The short‐period seismometer‐based magnitude saturation problem, especially for events with magnitude > 8, can be improved by a real‐time Global Navigation Satellite System (GNSS) positioning technique, which has enabled rapid estimation of a finite fault model for a large earthquake without any saturation. A new real‐time fault modeling system based on the GNSS Earth Observation Network (GEONET) is developed and is under experimental operation in Japan. In this paper, we present the newly developed system REGARD (the Real‐time GEONET Analysis system for Rapid Deformation monitoring), which consists of real‐time GNSS positioning, automatic detection of coseismic displacement by the event, and quasi real‐time finite fault model inversion routines. The performance of the automatic event detection system is tested through experimental real‐time operation based on GEONET data for 2 months. Furthermore, we also test the reliability of the finite fault model inversion routines using real raw GNSS data observed for past large earthquakes: the 2003 Tokachi‐oki earthquake (moment magnitude (Mw) 8.3), the 2011 Tohoku earthquake (Mw 9.0), and the 2011 off‐Ibaraki earthquake (Mw 7.7). A simulated 1707 Hoei‐type Nankai Trough earthquake (Mw 8.7) is also tested. The real‐time experimental operation shows that real‐time GNSS positioning is precise enough to detect all the tested earthquakes, and the inversion results demonstrate that the REGARD can reliably estimate the earthquake size and its extent within 3 min after the origin time. These results suggest that the REGARD system will complement the seismometer‐based magnitude determination system.

We present the initial results of rapid fault estimations for the 2016 Kumamoto earthquake on April 16 (M j 7.3), and coseismic displacements caused by the two large foreshocks that occurred on April 14 (M j 6.5) and April 15 (M j 6.4) from the GEONET real-time analysis system (REGARD), which is based on a Global Navigation Satellite System (GNSS) kinematic positioning technique. The real-time finite-fault estimate (M w 6.85) was obtained within 1 min and converged to M w 6.96 within 5 min of the origin time of the mainshock (M j 7.3). The finite-fault estimate shows rightlateral strike-slip fault along the Futagawa fault segment, which is consistent with the finite-fault model inferred from post-processed GNSS and InSAR analysis. Furthermore, significant coseismic displacements were observed due to the April 14 and April 15 foreshocks at nearby sites, though these earthquakes were smaller than the pre-assigned system threshold. Our results also demonstrate the potential for the GNSS-based earthquake early warning system for inland earthquakes.

Rapid estimation of the coseismic fault model for medium-to-large-sized earthquakes is key for disaster response. To estimate the coseismic fault model for large earthquakes, the Geospatial Information Authority of Japan and Tohoku University have jointly developed a real-time GEONET analysis system for rapid deformation monitoring (REGARD). REGARD can estimate the single rectangular fault model and slip distribution along the assumed plate interface. The single rectangular fault model is useful as a first-order approximation of a medium-to-large earthquake. However, in its estimation, it is difficult to obtain accurate results for model parameters due to the strong effect of initial values. To solve this problem, this study proposes a new method to estimate the coseismic fault model and model uncertainties in real time based on the Bayesian inversion approach using the Markov Chain Monte Carlo (MCMC) method. The MCMC approach is computationally expensive and hyperparameters should be defined in advance via trial and error. The sampling efficiency was improved using a parallel tempering method, and an automatic definition method for hyperparameters was developed for real-time use. The calculation time was within 30 s for 1 × 106 samples using a typical single LINUX server, which can implement real-time analysis, similar to REGARD. The reliability of the developed method was evaluated using data from recent earthquakes (2016 Kumamoto and 2019 Yamagata-Oki earthquakes). Simulations of the earthquakes in the Sea of Japan were also conducted exhaustively. The results showed an advantage over the maximum likelihood approach with a priori information, which has initial value dependence in nonlinear problems. In terms of application to data with a small signal-to-noise ratio, the results suggest the possibility of using several conjugate fault models. There is a tradeoff between the fault area and slip amount, especially for offshore earthquakes, which means that quantification of the uncertainty enables us to evaluate the reliability of the fault model estimation results in real time.

The 2007 Chuetsu-oki earthquake occurred just west off the coast of Kashiwazaki in Niigata Prefecture, Central Japan on July 16, 2007. The permanent GPS network (GEONET) clarifies the coseismic displacement as a thrust faulting whose compressional axis lies in the NW-SE direction. Interferometric analysis of synthetic aperture radar (SAR) images acquired by "Daichi" satellite (ALOS) maps a detailed spatial pattern of the displacement toward the satellite for both ascending and descending orbits. Peak-to-peak displacement reaches approximately 400 mm in the descending orbit interferometric (In)SAR data. Repeated precise leveling shows uplift near the northeast part of the aftershock area and subsidence near the southwestern part. We construct a preliminary fault model by inverting the observed deformation. The preferred model consists of two segments of rectangular faults whose moment magnitude is 6.7 in total. From only the used geodetic data on land, it is difficult to determine which plane in two conjugate planes of the focal solution was ruptured. It is important to consider the effect of a heterogeneous medium and variable slip on the faults as well as other geophysical data to determine the fault model with confidence.

This short paper reviews the role of real-time global navigation satellite system (GNSS) in near-field tsunami forecasting. Recent efforts highlight that coseismic fault model estimation based on real-time GNSS has contributed substantially to our understanding of large magnitude earthquakes and their fault expansions. We briefly introduce the history of use of real-time GNSS processing in the rapid estimation of the coseismic finite fault model. Additionally, we discuss our recent trials on the estimation of quasi real-time tsunami inundation based on real-time GNSS data. Obtained results clearly suggest the effectiveness of real-time GNSS for tsunami inundation estimation as the GNSS can capture fault expansion and its slip amount in a relatively accurate manner within a short time period. We also discuss the future prospects of using real-time GNSS data for tsunami warning including effective combination of different methods for more reliable forecasting.