Tsunami Early Warning Within Five Minutes

2012 ◽  
Vol 170 (9-10) ◽  
pp. 1385-1395 ◽  
Author(s):  
Anthony Lomax ◽  
Alberto Michelini
2021 ◽  
Author(s):  
Alberto Armigliato ◽  
Martina Zanetti ◽  
Stefano Tinti ◽  
Filippo Zaniboni ◽  
Glauco Gallotti ◽  
...  

<p>It is well known that for earthquake-generated tsunamis impacting near-field coastlines the focal mechanism, the position of the fault with respect to the coastline and the on fault slip distribution are key factors in determining the efficiency of the generation process and the distribution of the maximum run-up and inundation along the nearby coasts. The time needed to obtain the aforementioned information from the analysis of seismic records is usually too long compared to the time required to issue a timely tsunami warning/alert to the nearest coastlines. In the context of tsunami early warning systems, a big challenge is hence to be able to define 1) the relative position of the hypocenter and of the fault and 2) the earthquake focal mechanism, based only on the preliminary earthquake localization and magnitude estimation, which are made available by seismic networks soon after the earthquake occurs.</p><p>In this study, the intrinsic unpredictability of the position of the hypocenter on the fault plane is studied through a probabilistic approach based on the analysis of two finite fault model datasets (SRCMOD and USGS) and by limiting the analysis to moderate-to-large shallow earthquakes (Mw  6 and depth  50 km). After a proper homogenization procedure needed to define a common geometry for all samples in the two datasets, the hypocentral positions are fitted with different probability density functions (PDFs) separately in the along-dip and along-strike directions.</p><p>Regarding the focal mechanism determination, different approaches have been tested: the most successful is restricted to subduction-type earthquakes. It defines average values and uncertainties for strike, dip and rake angles based on a combination of a proper zonation of the main tsunamigenic subduction areas worldwide and of subduction zone geometries available from publicdatabases.</p><p>The general workflow that we propose can be schematically outlined as follows. Once an earthquake occurs and the magnitude and hypocentral solutions are made available by seismic networks, it is possible to assign the focal mechanism by selecting the characteristic values for strike, dip and rake of the zone where the hypocenter falls into. Fault length and width, as well as the slip distribution on the fault plane, are computed through regression laws against magnitude proposed by previous studies. The resulting rectangular fault plane can be discretized into a matrix of subfaults: the position of the center of each subfault can be considered as a “realization” of the hypocenter position, which can then be assigned a probability. In this way, we can define a number of earthquake fault scenarios, each of which is assigned a probability, and we can run tsunami numerical simulations for each scenario to quantify the classical observables, such as water elevation time series in selected offshore/coastal tide-gauges, flow depth, run-up, inundation distance. The final results can be provided as probabilistic distributions of the different observables.</p><p>The general approach, which is still in a proof-of-concept stage, is applied to the 16 September 2015 Illapel (Chile) tsunamigenic earthquake (Mw = 8.2). The comparison with the available tsunami observations is discussed with special attention devoted to the early-warning perspective.</p>


2021 ◽  
Author(s):  
Malte Metz ◽  
Marius Isken ◽  
Rongjiang Wang ◽  
Torsten Dahm ◽  
Haluk Özener ◽  
...  

<p>The fast inversion of reliable centroid moment tensor and kinematic rupture parameters of earthquakes occurring near coastal margins is a key for the assessment of the tsunamigenic potential and early tsunami warning (TEW). In recent years, more and more multi-channel seismic and geodetic online station networks have been built-up to improve the TEW, for instance the GNSS and strong motion networks in Italy, Greece, and Turkey, additionally to the broadband seismological monitoring. Inclusion of such data for the fast kinematic source inversion can improve the resolution and robustness of its’ solutions. However, methods have to be further developed and tested to fully exploit the potential of such rich joint dataset.</p><p>In this frame, we compare and test two in-house developed, kinematic / dynamic rupture inversion methods which are based on completely different approaches. The IDS (Iterative Deconvolution and Stacking, Zhang et al., 2014) combines an iterative seismic network inversion with back projection techniques to retrieve subfault source time functions. The pseudo dynamic rupture model (Dahm et al., in review) links the rupture front propagation estimate based on the Eikonal equation with the dislocation derived from a boundary element method to model dislocation snapshots. We used the latter in both a fast rupture estimate and a fully probabilistic source inversion.</p><p>We use some Mw > 6.3 earthquakes that occurred in the coastal range of the Aegean Sea as an example for comparison: the Mw 6.3 Lesbos earthquake (12 June 2017), the Mw 6.6 Bodrum earthquake (20 July 2017), and the recent Mw 7.0 earthquake which occurred at Samos on 30 October 2020. The latter earthquake and the resulting tsunami caused fatalities and severe damage at the shorelines of Samos and around the city of Izmir, Turkey.<br>The fast estimates are based on only little data and/or prior information obtained from the regional seismicity catalogue and available active fault information. The large number of seismic (broadband, strong motion) and geodetic (high-rate GNSS) stations in local and regional distance from the earthquake with good azimuthal coverage jointly inverted with InSAR data allows for robust inversion results. These, and other solutions, are used as a reference for the comparison of our fast source estimates.<br>Preliminary results of the slip distribution and the source time function are in good agreement with modelling results from other authors.</p><p>We present our insights into the kinematics of the chosen earthquakes investigated by means of joint inversions. Finally, the accuracy of our first fast source estimates, which could be of potential use in tsunami early warning, will be discussed.</p>


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