Abstract
Advances in physics-based earthquake simulations, utilizing high-performance computing, have been exploited to better understand the generation and characteristics of the high-frequency seismic wavefield. However, direct comparison to ground motion observations of a specific earthquake is challenging. We here propose a new approach to simulate data-fused broadband ground motion synthetics using 3D dynamic rupture modeling of the 2016 M-w 6.2 Amatrice, Italy earthquake. We augment a smooth, best-fitting model from Bayesian dynamic rupture source inversion of strong-motion data (<1 Hz) with fractal fault roughness, frictional heterogeneities, viscoelastic attenuation, and topography. The required consistency to match long periods allows us to quantify the role of small-scale dynamic source heterogeneities, such as the 3D roughness drag, from observational broadband seismic waveforms. We demonstrate that 3D data-constrained fully dynamic rupture synthetics show good agreement with various observed ground-motion metrics up to similar to 5 Hz and are an important avenue toward non-ergodic, physics-based seismic hazard assessment.
Dokumententyp: | Zeitschriftenartikel |
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Fakultät: | Geowissenschaften > Department für Geo- und Umweltwissenschaften |
Themengebiete: | 500 Naturwissenschaften und Mathematik > 550 Geowissenschaften, Geologie |
ISSN: | 0094-8276 |
Sprache: | Englisch |
Dokumenten ID: | 110749 |
Datum der Veröffentlichung auf Open Access LMU: | 02. Apr. 2024, 07:20 |
Letzte Änderungen: | 02. Apr. 2024, 07:20 |