1. Comparison between the uncertainty in the tsunami forecast from slip models obtained from geophysical data inversion and by a Phase Variation Method
- Author
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Fabrizio Romano, Patricio Catalan, Stefano Lorito, Escalante Sanchez Cipriano, Simone Atzori, Thorne Lay, Roberto Tonini, Manuela Volpe, Alessio Piatanesi, Macias Sanchez Jorge, and Castro Diaz Manuel J
- Abstract
Subduction zones are the most seismically active regions in the world and hosted many great tsunamigenic earthquakes in the past, often with destructive coastal consequences. Hence, an accurate estimate of the tsunami forecast is crucial in Tsunami Early Warning Systems (TEWS) framework. However, the inherent uncertainties associated with the tsunami source estimation in real-time make tsunami forecasting challenging. In this study, we consider the South American subduction zone, where in the last 15 years occurred, three M8+ tsunamigenic earthquakes; in particular, we focus on the 2014 Mw 8.1 Iquique event.Here, we evaluate the variability of the tsunami forecasting for the Chilean coast as resulting i) from the coseismic slip model obtained by geophysical data inversion and ii) from an expeditious method for the tsunami source estimation, based on an extension of the well-known spectral approach. In the former method, we estimate the slip distribution of the 2014 Iquique earthquake by jointly inverting tsunami (DARTs and tide-gauges) and GPS data; we adopt a 3D fault geometry and Green’s functions approach.On the other hand, a set of stochastic slip models in the latter is generated through a Phase Variation Method (PVM), where realizations are obtained from both the wavenumber and phase spectra of the source.In the analysis, we also evaluate how the different physics complexity included in the tsunami modelling (e.g. by including dispersion or not) can be mapped into the tsunami forecasting uncertainty. Finally, as an independent check, we compare the predicted deformation field from the slip models (inverted or by PVM) with the RADARSAT-2 InSAR data.
- Published
- 2023