Validation of linearity assumptions for using tsunami waveforms in joint inversion of kinematic rupture models: Application to the 2010 Mentawai M_w 7.8 tsunami earthquake
Abstract
Tsunami observations have particular importance for resolving shallow offshore slip in finite-fault rupture model inversions for large subduction zone earthquakes. However, validations of amplitude linearity and choice of subfault discretization of tsunami Green's functions are essential when inverting tsunami waveforms. We explore such validations using four tsunami recordings of the 25 October 2010 Mentawai M_w 7.8 tsunami earthquake, jointly inverted with teleseismic body waves and 1 Hz GPS (high-rate GPS) observations. The tsunami observations include near-field and far-field deep water recordings, as well as coastal and island tide gauge recordings. A nonlinear, dispersive modeling code, NEOWAVE, is used to construct tsunami Green's functions from seafloor excitation for the linear inversions, along with performing full-scale calculations of the tsunami for the inverted models. We explore linearity and finiteness effects with respect to slip magnitude, variable rake determination, and subfault dimensions. The linearity assumption is generally robust for the deep water recordings, and wave dispersion from seafloor excitation is important for accurate description of near-field Green's functions. Breakdown of linearity produces substantial misfits for short-wavelength signals in tide gauge recordings with large wave heights. Including the tsunami observations in joint inversions provides improved resolution of near-trench slip compared with inversions of only seismic and geodetic data. Two rupture models, with fine-grid (15 km) and coarse-grid (30 km) spacing, are inverted for the Mentawai event. Stronger regularization is required for the fine model representation. Both models indicate a shallow concentration of large slip near the trench with peak slip of ~15 m. Fully nonlinear forward modeling of tsunami waveforms confirms the validity of these two models for matching the tsunami recordings along with the other data.
Additional Information
© 2015 American Geophysical Union. Received 24 October 2014; Accepted 23 February 2015; Accepted article online 26 February 2015; Published online 27 March 2015. We appreciate helpful reviews by two anonymous reviewers. This work made use of GMT, SAC, and MATLAB software. The IRIS data management center was used to access the seismic data from Global Seismic Network and Federation of Digital Seismic Network stations. The GITEWS GPS buoy data in Mentawai were provided by the Badan Meteorology and Geofisika (BMKG), Indonesia. DART buoy data were obtained fromthe NOAA National Data Buoy Center. The authors thank Jane Sexton of Geoscience Australia for the digital elevation model of Cocos Island and the tide gauge coordinates. The SuGAr network is jointly operated by the Earth Observatory of Singapore and the Indonesia Institute of Sciences (LIPI). This work was supported in part by NSF grant EAR1245717 (T.L.).Attached Files
Published - jgrb51062.pdf
Supplemental Material - jgrb51062-sup-0001-Supplementary.doc
Files
Name | Size | Download all |
---|---|---|
md5:6420a56af5434342cd34684924daa65d
|
6.3 MB | Preview Download |
md5:d331d98cff96fc607e0344c6f94ac114
|
87.0 kB | Download |
Additional details
- Eprint ID
- 57591
- Resolver ID
- CaltechAUTHORS:20150518-101337231
- NSF
- EAR-1245717
- Created
-
2015-05-18Created from EPrint's datestamp field
- Updated
-
2021-11-10Created from EPrint's last_modified field