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Rapid Centroid Moment Tensor (CMT) Inversion in 3D Earth Structure Model for Earthquakes in Southern California. 1 En-Jui Lee, 1 Po Chen, 2 Thomas H. Jordan, 2 Philip Maechling , 3 Yifeng Cui, 2 Scott Callaghan 1 University of Wyoming , 2 University of Southern California, - PowerPoint PPT Presentation

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Rapid Centroid Moment Tensor (CMT) Inversion in 3D Earth Structure Model for

Earthquakes in Southern California

1En-Jui Lee, 1Po Chen, 2Thomas H. Jordan, 2Philip Maechling, 3Yifeng Cui, 2Scott Callaghan

1University of Wyoming, 2University of Southern California, 3San Diego Supercomputer Center

Overview

• Introduction• Methodology• Results• Reduce source errors for tomo. • (Near) Real-time application • Summary

Introduction• Earthquake-prone

area• 244 broadband

stations• Seismic hazard

analysis• Realistic

interpretation of geological structures

Introduction• 3D updated

velocity model: CVM4SI2

• Improved model better source estimations

Our current tomography results

4:45 pmBallroom D

Source inversion

Automatic window picking

Broadband Data Waveforms

Selected Windows

NCC between data & synthetic

Measurements (NCC, dt, lnA)

Optimal CMT Solution

Bayesian inference

Automatic window picking• Less heterogeneity effects : P, Pnl, S & surface

waves• Continuous wavelet transform (CWT)• Topological watershed (TW)

Source inversion

Automatic window picking

Broadband Data Waveforms

Selected Windows

NCC between data & synthetic

Measurements (NCC, dt, lnA)

Optimal CMT Solution

Bayesian inference

Synthetic seismograms• Any M is linear combination of elementary

seismograms M1 ~ M6• Different subgroups can represent the specific

solutions1

Kikuchi & Kanamori, 1991

Measurements• NCC between data windows & synthetic

seismogram NCC, dt, lnA

Source inversion

Automatic window picking

Broadband Data Waveforms

Selected Windows

NCC between data & synthetic

Measurements (NCC, dt, lnA)

Optimal CMT Solution

Bayesian inference

Bayesian inference• Apply the Bayesian inference to different type

of measurements (Ncc, dt and lnA)• Assuming the measurements are independent• Select the CMT with highest probability

Example of Yorba Linda event• 2002/09/03 Mw 4.3

Results• Compare synthetic waveforms between 1D

multi-layer and 3D models

• An example of small earthquake (ML=3.13)

• Comparison of relocated depths

• Comparison of magnitude estimations

Synthetic waveform comparisons

An example of ML=3.13 earthquake

Comparison of relocated depths

An example of depth comparison

Comparison of magnitude estimations

Reduce source errors for tomography

(Near) Real-time application• Using 10 sec of 2008 Chino Hills earthquake • find an optimal solution in 20 secs (4 cores)

Summary• Rapid and accurate CMT solution

– Store RGTs rapid– 3D velocity structure accurate waveforms

• By applying Bayesian inference provide uncertainty estimates for the source parameters

• Potential application for (near) real-time source inversion (near) real-time ground motion forecast

• Probabilistic Seismic Hazard Analysis (PSHA) - CyberShake

Thank You!

Go tohttp://www-rcf.usc.edu/~pochen/

for PDF preprints and reprints

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