Coseismic slip of the 2010 Mw 8.8 Great Maule, Chile, earthquake quantified by the inversion of GRACE observations

2012 ◽  
Vol 335-336 ◽  
pp. 167-179 ◽  
Author(s):  
Lei Wang ◽  
C.K. Shum ◽  
Frederik J. Simons ◽  
Andrés Tassara ◽  
Kamil Erkan ◽  
...  
Keyword(s):  
Coseismic Slip ◽  
Chile Earthquake

scholarly journals Coseismic slip and afterslip of the 2015 Mw 8.3 Illapel (Chile) earthquake determined from continuous GPS data

2016 ◽  
Vol 43 (20) ◽  
pp. 10,710-10,719 ◽  
Author(s):  
Mahesh N. Shrivastava ◽  
Gabriel González ◽  
Marcos Moreno ◽  
Mohamed Chlieh ◽  
Pablo Salazar ◽  
...  
Keyword(s):  
Gps Data ◽  
Coseismic Slip ◽  
Chile Earthquake ◽  
Continuous Gps

Impact of ionosphere on InSAR observation and coseismic slip inversion: Improved slip model for the 2010 Maule, Chile, earthquake

2021 ◽  
Vol 267 ◽  
pp. 112733
Author(s):  
Bochen Zhang ◽  
Xiaoli Ding ◽  
Falk Amelung ◽  
Chisheng Wang ◽  
Wenbin Xu ◽  
...  
Keyword(s):  
Slip Model ◽  
Coseismic Slip ◽  
Chile Earthquake

scholarly journals Coseismic slip and early afterslip of the 2015 Illapel, Chile, earthquake: Implications for frictional heterogeneity and coastal uplift

2016 ◽  
Vol 121 (8) ◽  
pp. 6172-6191 ◽  
Author(s):  
William D. Barnhart ◽  
Jessica R. Murray ◽  
Richard W. Briggs ◽  
Francisco Gomez ◽  
Charles P. J. Miles ◽  
...  
Keyword(s):  
Coseismic Slip ◽  
Chile Earthquake ◽  
Coastal Uplift

scholarly journals Correction to “Coseismic slip distribution of the February 27, 2010 Mw 8.8 Maule, Chile earthquake”

2011 ◽  
Vol 38 (14) ◽  
pp. n/a-n/a
Author(s):  
Fred F. Pollitz ◽  
Ben Brooks ◽  
Xiaopeng Tong ◽  
Michael G. Bevis ◽  
James H. Foster ◽  
...  
Keyword(s):  
Slip Distribution ◽  
Coseismic Slip ◽  
Chile Earthquake

scholarly journals Coseismic slip distribution of the February 27, 2010 Mw 8.8 Maule, Chile earthquake

2011 ◽  
Vol 38 (9) ◽  
pp. n/a-n/a ◽  
Author(s):  
Fred F. Pollitz ◽  
Ben Brooks ◽  
Xiaopeng Tong ◽  
Michael G. Bevis ◽  
James H. Foster ◽  
...  
Keyword(s):  
Slip Distribution ◽  
Coseismic Slip ◽  
Chile Earthquake

Limited overlap between the seismic gap and coseismic slip of the great 2010 Chile earthquake

2011 ◽  
Vol 4 (3) ◽  
pp. 173-177 ◽  
Author(s):  
S. Lorito ◽  
F. Romano ◽  
S. Atzori ◽  
X. Tong ◽  
A. Avallone ◽  
...  
Keyword(s):  
Seismic Gap ◽  
Coseismic Slip ◽  
Chile Earthquake

scholarly journals Adjoint-based direct data assimilation of GNSS time series for optimizing frictional parameters and predicting postseismic deformation following the 2003 Tokachi-oki earthquake

2020 ◽  
Vol 72 (1) ◽  
Author(s):  
Masayuki Kano ◽  
Shin’ichi Miyazaki ◽  
Yoichi Ishikawa ◽  
Kazuro Hirahara
Keyword(s):  
Time Series ◽  
Data Assimilation ◽  
Evaluation Method ◽  
Temporal Evolution ◽  
Recovery Process ◽  
Postseismic Deformation ◽  
Coseismic Slip ◽  
Megathrust Earthquakes ◽  
Spatio Temporal ◽  
Gnss Time Series

Abstract Postseismic Global Navigation Satellite System (GNSS) time series followed by megathrust earthquakes can be interpreted as a result of afterslip on the plate interface, especially in its early phase. Afterslip is a stress release process accumulated by adjacent coseismic slip and can be considered a recovery process for future events during earthquake cycles. Spatio-temporal evolution of afterslip often triggers subsequent earthquakes through stress perturbation. Therefore, it is important to quantitatively capture the spatio-temporal evolution of afterslip and related postseismic crustal deformation and to predict their future evolution with a physics-based simulation. We developed an adjoint data assimilation method, which directly assimilates GNSS time series into a physics-based model to optimize the frictional parameters that control the slip behavior on the fault. The developed method was validated with synthetic data. Through the optimization of frictional parameters, the spatial distributions of afterslip could roughly (but not in detail) be reproduced if the observation noise was included. The optimization of frictional parameters reproduced not only the postseismic displacements used for the assimilation, but also improved the prediction skill of the following time series. Then, we applied the developed method to the observed GNSS time series for the first 15 days following the 2003 Tokachi-oki earthquake. The frictional parameters in the afterslip regions were optimized to A–B ~ O(10 kPa), A ~ O(100 kPa), and L ~ O(10 mm). A large afterslip is inferred on the shallower side of the coseismic slip area. The optimized frictional parameters quantitatively predicted the postseismic GNSS time series for the following 15 days. These characteristics can also be detected if the simulation variables can be simultaneously optimized. The developed data assimilation method, which can be directly applied to GNSS time series following megathrust earthquakes, is an effective quantitative evaluation method for assessing risks of subsequent earthquakes and for monitoring the recovery process of megathrust earthquakes.

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