Description: The SW Iberian margin is one of the most seismogenic and tsunamigenic areas in W-Europe, where large historical and instrumental destructive events occurred. To evaluate the sensitivity of the tsunami impact on the coast of SW Iberia and NW Morocco to the fault geometry and slip distribution for local earthquakes, we carried out a set of tsunami simulations considering some of the main known active crustal faults in the region: the Gorringe Bank (GBF), Marquês de Pombal (MPF), Horseshoe (HF), North Coral Patch (NCPF) and South Coral Patch (SCPF) thrust faults, and the Lineament South (LSF) strike-slip fault. We started by considering for all of them relatively simple planar faults featuring with uniform slip distribution; we then used a more complex 3D fault geometry for the faults constrained with a large 2D multichannel seismic dataset (MPF, HF, NCPF, and SCPF); and finally, we used various heterogeneous slip distributions for the HF. Our results show that using more complex 3D fault geometries and slip distributions, the peak wave height at the coastline can double compared to simpler tsunami source scenarios from planar fault geometries. Existing tsunami hazard models in the region use homogeneous slip distributions on planar faults as initial conditions for tsunami simulations and therefore underestimate tsunami hazard. Complex 3D fault geometries and non-uniform slip distribution should be considered in future tsunami hazard updates. The tsunami simulations also support the finding that submarine canyons attenuate the wave height reaching the coastline, while submarine ridges and shallow shelves have the opposite effect.

Description: We propose a procedure for uncertainty quantification in Probabilistic Tsunami Hazard Analysis (PTHA), with a special emphasis on the uncertainty related to statistical modelling of the earthquake source in Seismic PTHA (SPTHA), and on the separate treatment of subduction and crustal earthquakes (treated as background seismicity). An event tree approach and ensemble modelling are used in spite of more classical approaches, such as the hazard integral and the logic tree. This procedure consists of four steps: (1) exploration of aleatory uncertainty through an event tree, with alternative implementations for exploring epistemic uncertainty; (2) numerical computation of tsunami generation and propagation up to a given offshore isobath; (3) (optional) site-specific quantification of inundation; (4) simultaneous quantification of aleatory and epistemic uncertainty through ensemble modelling. The proposed procedure is general and independent of the kind of tsunami source considered; however, we implement step 1, the event tree, specifically for SPTHA, focusing on seismic source uncertainty. To exemplify the procedure, we develop a case study considering seismic sources in the Ionian Sea (central-eastern Mediterranean Sea), using the coasts of Southern Italy as a target zone. The results show that an efficient and complete quantification of all the uncertainties is feasible even when treating a large number of potential sources and a large set of alternative model formulations. We also find that (i) treating separately subduction and background (crustal) earthquakes allows for optimal use of available information and for avoiding significant biases; (ii) both subduction interface and crustal faults contribute to the SPTHA, with different proportions that depend on source-target position and tsunami intensity; (iii) the proposed framework allows sensitivity and deaggregation analyses, demonstrating the applicability of the method for operational assessments.

Description: The 6 April 2009 Mw 6.3 L'Aquila destructive earthquake was successfully recorded by closely spaced 10 Hz and 1 Hz recording GPS receivers and strong motion accelerometers located above or close to the 50° dipping activated fault. We retrieved both static and dynamic displacements from very high rate GPS (VHRGPS) recordings by using Precise Point Positioning kinematic analysis. We compared the GPS positions' time series with the closest displacement time series obtained by doubly integrating strong motion data, first, to assess the GPS capability to detect the first seismic arrivals (P waves) and, second, to evaluate the accelerometers' capability to detect coseismic offsets up to ∼45 s after the earthquake occurrence. By comparing seismic and VHRGPS frequency contents, we inferred that GPS sampling rates greater than 2.5 Hz (i.e., 5 or 10 Hz) are required in the near field of moderate-magnitude events to provide “alias-free” solutions of coseismic dynamic displacements. Finally, we assessed the consistency of the dynamic VHRGPS results as a constraint on the kinematic rupture history of the main shock. These results suggested that the high-rate sampling GPS sites in the near field can be as useful as strong motion stations for earthquake source studies.

Description: In this paper we present and discuss the performance of the procedure for earthquake location and characterization implemented in the Italian Candidate Tsunami Service Provider at the Istituto Nazionale di Geofisica e Vulcanologia (INGV) in Rome. Following the ICG/NEAMTWS guidelines, the first tsunami warning messages are based only on seismic information, i.e., epicenter location, hypocenter depth, and magnitude, which are automatically computed by the software Early-est. Early-est is a package for rapid location and seismic/tsunamigenic characterization of earthquakes. The Early-est software package operates using offline-event or continuous-real-time seismic waveform data to perform trace processing and picking, and, at a regular report interval, phase association, event detection, hypocenter location, and event characterization. Early-est also provides mb, Mwp, and Mwpd magnitude estimations. mb magnitudes are preferred for events with Mwp ≲ 5.8, while Mwpd estimations are valid for events with Mwp ≳ 7.2. In this paper we present the earthquake parameters computed by Early-est between the beginning of March 2012 and the end of December 2014 on a global scale for events with magnitude M ≥ 5.5, and we also present the detection timeline. We compare the earthquake parameters automatically computed by Early-est with the same parameters listed in reference catalogs. Such reference catalogs are manually revised/verified by scientists. The goal of this work is to test the accuracy and reliability of the fully automatic locations provided by Early-est. In our analysis, the epicenter location, hypocenter depth and magnitude parameters do not differ significantly from the values in the reference catalogs. Both mb and Mwp magnitudes show differences to the reference catalogs. We thus derived correction functions in order to minimize the differences and correct biases between our values and the ones from the reference catalogs. Correction of the Mwp distance dependency is particularly relevant, since this magnitude refers to the larger and probably tsunamigenic earthquakes. Mwp values at stations with epicentral distance Δ ≲ 30° are significantly overestimated with respect to the CMT-global solutions, whereas Mwp values at stations with epicentral distance Δ ≳ 90° are slightly underestimated. After applying such distance correction the Mwp provided by Early-est differs from CMT-global catalog values of about δ Mwp ≈ 0.0 ∓ 0.2. Early-est continuously acquires time-series data and updates the earthquake source parameters. Our analysis shows that the epicenter coordinates and the magnitude values converge within less than 10 min (5 min in the Mediterranean region) toward the stable values. Our analysis shows that we can compute Mwp magnitudes that do not display short epicentral distance dependency overestimation, and we can provide robust and reliable earthquake source parameters to compile tsunami warning messages within less than 15 min after the event origin time.

Description: Tsunami warning centres face the challenging task of rapidly forecasting tsunami threat immediately after an earthquake, when there is high uncertainty due to data deficiency. Here we introduce Probabilistic Tsunami Forecasting (PTF) for tsunami early warning. PTF explicitly treats data- and forecast-uncertainties, enabling alert level definitions according to any predefined level of conservatism, which is connected to the average balance of missed-vs-false-alarms. Impact forecasts and resulting recommendations become progressively less uncertain as new data become available. Here we report an implementation for near-source early warning and test it systematically by hindcasting the great 2010 M8.8 Maule (Chile) and the well-studied 2003 M6.8 Zemmouri-Boumerdes (Algeria) tsunamis, as well as all the Mediterranean earthquakes that triggered alert messages at the Italian Tsunami Warning Centre since its inception in 2015, demonstrating forecasting accuracy over a wide range of magnitudes and earthquake types.

Description: The complexity of coseismic slip distributions influences the tsunami hazard posed by local and, to a certain extent, distant tsunami sources. Large slip concentrated in shallow patches was observed in recent tsunamigenic earthquakes, possibly due to dynamic amplification near the free surface, variable frictional conditions or other factors. We propose a method for incorporating enhanced shallow slip for subduction earthquakes while preventing systematic slip excess at shallow depths over one or more seismic cycles. The method uses the classic k−2 stochastic slip distributions, augmented by shallow slip amplification. It is necessary for deep events with lower slip to occur more often than shallow ones with amplified slip to balance the long-term cumulative slip. We evaluate the impact of this approach on tsunami hazard in the central and eastern Mediterranean Sea adopting a realistic 3D geometry for three subduction zones, by using it to model ~ 150,000 earthquakes with Mw from 6.0 to 9.0. We combine earthquake rates, depth-dependent slip distributions, tsunami modeling, and epistemic uncertainty through an ensemble modeling technique. We found that the mean hazard curves obtained with our method show enhanced probabilities for larger inundation heights as compared to the curves derived from depth-independent slip distributions. Our approach is completely general and can be applied to any subduction zone in the world.