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Matteo Taroni

Publications and source records attributed to Matteo Taroni.

2 recordsLinked to original sources

The making of the NEAM Tsunami Hazard Model 2018 (NEAMTHM18)

The NEAM Tsunami Hazard Model 2018 (NEAMTHM18) is a probabilistic hazard model for tsunamis generated by earthquakes. It covers the coastlines of the North-eastern Atlantic, the Mediterranean, and connected seas (NEAM). NEAMTHM18 was designed as a three-phase project. The first two phases were dedicated to the model development and hazard calculations, following a formalized decision-making process based on a multiple-expert protocol. The third phase was dedicated to documentation and dissemination. The hazard assessment workflow was structured in Steps and Levels. There are four Steps: Step-1) probabilistic earthquake model; Step-2) tsunami generation and modeling in deep water; Step-3) shoaling and inundation; Step-4) hazard aggregation and uncertainty quantification. Each Step includes a different number of Levels. Level-0 always describes the input data; the other Levels describe the intermediate results needed to proceed from one Step to another. Alternative datasets and models were considered in the implementation. The epistemic hazard uncertainty was quantified through an ensemble modeling technique accounting for alternative models’ weights and yielding a distribution of hazard curves represented by the mean and various percentiles. Hazard curves were calculated at 2,343 Points of Interest (POI) distributed at an average spacing of ∼20 km. Precalculated probability maps for five maximum inundation heights (MIH) and hazard intensity maps for five average return periods (ARP) were produced from hazard curves. In the entire NEAM Region, MIHs of several meters are rare but not impossible. Considering a 2% probability of exceedance in 50 years (ARP≈2,475 years), the POIs with MIH >5 m are fewer than 1% and are all in the Mediterranean on Libya, Egypt, Cyprus, and Greece coasts. In the North-East Atlantic, POIs with MIH >3 m are on the coasts of Mauritania and Gulf of Cadiz. Overall, 30% of the POIs have MIH >1 m. NEAMTHM18 results and documentation are available through the TSUMAPS-NEAM project website (http://www.tsumaps-neam.eu/), featuring an interactive web mapper. Although the NEAMTHM18 cannot substitute in-depth analyses at local scales, it represents the first action to start local and more detailed hazard and risk assessments and contributes to designing evacuation maps for tsunami early warning.

Frontiers in Earth Science

Ensemble smoothed seismicity models for the new Italian Probabilistic Seismic Hazard Map

We develop a long‐term (a few decades or longer) earthquake rate forecast for Italy based on smoothed seismicity for incorporation in the 2017–2018 Italian Probabilistic Seismic Hazard Maps (IPSHM). Because the earthquake rate models from previous IPSHM were computed using source zones that were drawn around seismicity and tectonic provinces, the present model will be the first introduction of the smoothed seismicity method into the IPSHM. Smoothed seismicity models are constructed from both historical CPTI15 (Catalogo Parametrico dei Terremoti Italiani, 1000–2014) and instrumental (1981–2016) earthquake catalogs and use both fixed and adaptive smoothing methods. We compute spatial likelihood values comparing the spatial distribution of observed earthquakes with a suite of trial earthquake rate models to optimize smoothing parameters and catalogs. Then we produce an ensemble model using two different smoothing models (adaptive and fixed) and two earthquake catalogs (historical and instrumental), which are weighted equally through a logic‐tree approach to improve the forecast capability. We also compare our optimized smoothed seismicity models with the best two models of the Italian Collaboratory for the Study of Earthquake Predictability (CSEP) experiment and retrospectively test them with the CSEP methodology. We observed that the ensemble model performs slightly better than the optimized fixed and the adaptive smoothing seismicity models obtained in this study and the best time‐independent model of the CSEP Italian experiment. The preferred ensemble model forecasts an annual rate of 1.47 M ≥ 5.0 "> M ≥ 5.0 earthquakes, with higher rates mainly concentrating along the Apennines chain, eastern Alps, Calabria, and northeast Sicily. Finally, six ensemble models are created from the different smoothing methods using different weights through a logic‐tree approach to estimate the uncertainty associated with the model.

Seismological Research Letters