2021
DOI: 10.21203/rs.3.rs-923956/v1
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Rapid and Quantitative Uncertainty Estimation of Coseismic Slip Distribution for Large Interplate Earthquakes Using Real-time GNSS Data and Its Application to Tsunami Inundation Prediction

Abstract: This study proposes a new method for the uncertainty estimation of coseismic slip distribution on the plate interface deduced from real-time global navigation satellite system (GNSS) data and explores its application for tsunami inundation prediction. Jointly developed by the Geospatial Information Authority of Japan and Tohoku University, REGARD (REal-time GEONET Analysis system for Rapid Deformation monitoring) estimates coseismic fault models (a single rectangular fault model and slip distribution model) in… Show more

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Cited by 3 publications
(4 citation statements)
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References 34 publications
(34 reference statements)
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“…To verify the accuracy and efficiency of our method, we used the random-walk M-H that was adopted by Ohno et al (2021) to compare the estimation by the HMC method to that by the M-H method (Metropolis et al 1953;Hastings 1970), which is often used to solve the geophysical problem (Fukuda and Johnson 2008;Ito et al 2012;Dettmer et al 2014;Minson et al 2014;Ohno et al 2022). Although Ohno et al (2021) introduced an automatic determination method for likelihood variance and parallel tempering, we use the same variance value as HMC and estimate using only a single Markov chain for a single parameter to compare both methods strictly.…”
Section: Comparison With Metropolis-hastingsmentioning
confidence: 99%
See 2 more Smart Citations
“…To verify the accuracy and efficiency of our method, we used the random-walk M-H that was adopted by Ohno et al (2021) to compare the estimation by the HMC method to that by the M-H method (Metropolis et al 1953;Hastings 1970), which is often used to solve the geophysical problem (Fukuda and Johnson 2008;Ito et al 2012;Dettmer et al 2014;Minson et al 2014;Ohno et al 2022). Although Ohno et al (2021) introduced an automatic determination method for likelihood variance and parallel tempering, we use the same variance value as HMC and estimate using only a single Markov chain for a single parameter to compare both methods strictly.…”
Section: Comparison With Metropolis-hastingsmentioning
confidence: 99%
“…However, the HMC or other MCMC methods have the problem of ensuring minimum global exploration. One of the methods to certainly and efficiently explore more broadly in parameter space is parallel tempering (e.g., Dosso et al 2012;Sambridge 2013;Dettmer et al 2014;Hallo and Gallovič 2020;Ohno et al 2021Ohno et al ,2022. In future work, we will develop a method that introduces this expanding method to the HMC and realize a more efficient and stable fault estimation.…”
Section: Figures 6a (Hmc) and 6b (M-h) Display The Marginal Pdfs Incl...mentioning
confidence: 99%
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“…In this paper, we show that equally good forecasts can be made using only a few minutes of data from an existing network of Global Navigation Satellite System (GNSS) stations. Tsunami warning centers are already starting to incorporate this data in performing earthquake magnitude estimates, and it has been shown that the use of GNSS data can have great benefits, particularly for near‐field forecasting (Crowell et al., 2018; Melgar, Allen, et al., 2016; Ohno et al., 2022; Ohta et al., 2018; Williamson et al., 2020). We show that this can be taken further by training Convolutional Neural Networks (CNNs) to forecast the tsunami waveforms directly from the GNSS waveforms.…”
Section: Introductionmentioning
confidence: 99%