著者

大野 圭太郎 太田 雄策

雑誌

日本地球惑星科学連合2019年大会

巻号頁・発行日

2019-03-14

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Rapid understanding of the magnitude of large earthquakes and their associated fault dimensions are extremely important. Since September 2012, Geospatial Information Authority of Japan (GSI) and Tohoku University are jointly developing the GEONET real-time analysis system (REGARD). REGARD system rapidly estimates two types of coseismic fault models, which are slip distribution along the plate interface and single rectangular fault model, using permanent displacement field based on the real-time GNSS tine series. Currently, REGARD adopted the maximum likelihood approach to estimate the optimum model. The system has two points to be improved. As first point, it is difficult to estimate the quantitative uncertainty estimation of the obtained result because of the estimated result should contain both of the observation error of the real time GNSS and modeling error caused by the model settings. Understanding of such uncertainties quantitatively based on the data is important for evaluation of the result for disaster response. Second point, the problem is non-linear to estimate the single rectangular fault model in REGARD. Thus, the result strongly may depend on the initial values of the fault parameters. It is necessary to find the global minimum quickly for real-time use.Based on these backgrounds, we are developing coseismic fault model estimation system using MCMC (Markov Chain Monte Carlo methods), which is probabilistic approach based on Bayesian statistics. MCMC does not specify one maximum likelihood value, but estimates the posterior probability density function (PDF). In addition, dependency on the initial value is relatively small by searching unknown parameters over a wide range randomly. In this study, we focus on the development the algorithm to estimate the single rectangular fault model deduced from permanent coseismic displacement field in real-time. We adopted basic Metropolis Hasting method as sampler and utilized parallel tempering approach to improve the sampling efficiency. One of the challenges for using MCMC in real time is how to make search settings, such as initial value, walk distance, variance of likelihood function, and Burn-in, which are generally decided by the try and error. We suggest a method of deciding these values automatically using scaling law and original sampling flow. Other challenging issue is calculation time. In generally, the calculation cost of MCMC is problem for the real-time purpose. To improve the performance of the MCMC we adopted OpenMP for the parallelization of the computing.We applied this approach to the 2011 Tohoku-Oki earthquake, 2016 Kumamoto earthquake, and 2016 Fukushima-Oki earthquake using the actual permanent displacement time series from REGARD. In each estimations, we got 1×106 samples and obtained posterior PDF within 30 seconds. To emphasize, this algorithm could estimate the magnitude as distributions based on the data. Especially in Tohoku-Oki earthquake, obtained results clearly shows the tradeoff between the fault area and the slip amount. This result suggests that the onshore GNSS data cannot constrain them, which are extremely important factors for precise near-field tsunami forecasting.In our presentation, we will show the more detail characteristic of the algorithm. We are working on development of it for single rectangular fault model aiming at actual operation. Furthermore, we will expand this approach to not only the single rectangular fault but also the slip distribution along the plate interface.

著者

大野 圭太郎 太田 雄策

出版者

日本測地学会

雑誌

測地学会誌 (ISSN:00380830)

巻号頁・発行日

vol.64, pp.39-50, 2018 (Released:2018-10-26)

参考文献数

27

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Rapid understanding of the magnitude of large earthquakes in the offshore region and their associated fault expansions is important for near-field tsunami forecasting. Since September 2012, the Geospatial Information Authority of Japan (GSI) and Tohoku University have been jointly developing the GEONET real-time analysis system (REGARD), which is expected to provide reliable earthquake magnitude estimation. The REGARD system has two different types of coseismic fault model estimation systems. The first system estimates the slip distribution along the plate boundary, while the second comprises single rectangular fault model estimation. One of the challenges of REGARD is the difficulty in the estimation of the quantitative uncertainty in the single rectangular fault estimation. Thus, we focused on quantitatively understanding the single rectangular fault model estimation based on real-time GNSS time series data. We adopted Markov Chain Monte Carlo methods (MCMC) for modeling of the coseismic single fault. We applied the Metropolis–Hastings MCMC method to the 2011 Tohoku-Oki earthquake. The results obtained clearly demonstrated the tradeoff between the fault area and the amount of slip. The posterior probability density function (PDF) of the obtained slip amount showed a complex shape compared with those for the other unknown parameters. Thus, we focused on the stress drop value. Based on multiple Markov chains using Gaussian prior PDF for the stress drop with different mean value (5, 10, 15, 20, and 25 MPa), we successfully obtained the simple posterior PDF shape of the slip amount for each different mean value condition. We also found that the entire fault model explained the data well. These results suggest that the data cannot resolve uncertainties from the tradeoff between the fault area and the slip amount, which are extremely important factors for precise near-field tsunami forecasting. The results obtained using different constraint condition for the stress drop by prior distribution may provide the quantitative uncertainties for the resulting tsunamis.