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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. © Copyright © 2021 Basili, Brizuela, Herrero, Iqbal, Lorito, Maesano, Murphy, Perfetti, Romano, Scala, Selva, Taroni, Tiberti, Thio, Tonini, Volpe, Glimsdal, Harbitz, Løvholt, Baptista, Carrilho, Matias, Omira, Babeyko, Hoechner, Gürbüz, Pekcan, Yalçıner, Canals, Lastras, Agalos, Papadopoulos, Triantafyllou, Benchekroun, Agrebi Jaouadi, Ben Abdallah, Bouallegue, Hamdi, Oueslati, Amato, Armigliato, Behrens, Davies, Di Bucci, Dolce, Geist, Gonzalez Vida, González, Macías Sánchez, Meletti, Ozer Sozdinler, Pagani, Parsons, Polet, Power, Sørensen and Zaytsev.

The NEAM Tsunami Hazard Model 2018 (NEAMTHM18) is a probabilistic hazard model for tsunamis generated by earthquakes. It covers the coastlines of the North-East Atlantic, the Mediterranean, and connected Seas (NEAM). In this online data product, the hazard results are provided by hazard curves calculated at 2,343 Points of Interest (POI), distributed in the North-East Atlantic (1,076 POIs), the Mediterranean Sea (1,130 POIs), and the Black Sea (137 POIs) at an average spacing of ~20 km. For each POI, hazard curves are given for the mean, 2nd, 16th, 50th, 84th, and 98th percentiles. Maps derived from hazard curves are Probability maps for Maximum Inundation Heights (MIH) of 1, 2, 5, 10, 20 meters; Hazard maps for Average Return Periods (ARP) of 500, 1,000, 2,500, 5,000, 10,000 years. For each map, precalculated displays are provided for the mean, the 16th percentile, and the 84th percentile. All data are also made accessible through an interactive web mapper and through Open Geospatial Consortium standard protocols. The model was prepared in the framework of the European Project TSUMAPS-NEAM (http://www.tsumaps-neam.eu/) funded by the mechanism of the European Civil Protection and Humanitarian Aid Operations (grant no. ECHO/SUB/2015/718568/PREV26).

The NEAM Tsunami Hazard Model 2018 (NEAMTHM18) is a probabilistic hazard model for tsunamis generated by earthquakes. It covers the coastlines of the North-East Atlantic, the Mediterranean, and connected Seas (NEAM). In this online data product, the hazard results are provided by hazard curves calculated at 2,343 Points of Interest (POI), distributed in the North-East Atlantic (1,076 POIs), the Mediterranean Sea (1,130 POIs), and the Black Sea (137 POIs) at an average spacing of ~20 km. For each POI, hazard curves are given for the mean, 2nd, 16th, 50th, 84th, and 98th percentiles. Maps derived from hazard curves are Probability maps for Maximum Inundation Heights (MIH) of 1, 2, 5, 10, 20 meters; Hazard maps for Average Return Periods (ARP) of 500, 1,000, 2,500, 5,000, 10,000 years. For each map, precalculated displays are provided for the mean, the 16th percentile, and the 84th percentile. All data are also made accessible through an interactive web mapper and through Open Geospatial Consortium standard protocols. The model was prepared in the framework of the European Project TSUMAPS-NEAM (http://www.tsumaps-neam.eu/) funded by the mechanism of the European Civil Protection and Humanitarian Aid Operations (grant no. ECHO/SUB/2015/718568/PREV26).

The automated detection of tsunamigenic signals at oceanic observation stations is highly desirable for the advancement of current tsunami early warning systems. These are supported with matching methods using large numbers of tsunami wave propagation modeling scenarios. New techniques using real-time scanning of hydrodynamic signals around a network of stations in an open ocean have been developed for the detection of tsunamis. Spectral ratios with respect to background signals and their levels of similarity across stations were investigated. The new developed algorithms will be wrapped as a reporting web service for the TRIDEC tsunami early warning system in the future.

Chapter is accepted though not yet published

The risk mitigation associated with tsunami events needs robust and accurate numerical tools to provide realistic solutions. We propose a comparative study between the efficiency of a finite volume numerical code, with second-order discretization in space and time, equipped with two different techniques to solve the non-conservative shallow-water equations: 1) the MUSCL (Monotonic Upstream-Centered Scheme for Conservation Laws) and, 2) the MOOD (Multi-dimensional Optimal Order Detection). A benchmarking process is carried out to validate the code. A one-dimensional simulation is performed to compare the MUSCL method equipped with the van Leer limiter, and the MOOD technique. We show that: 1) the quality of the solution may genuinely interfere with the scenario one wants to assess and, 2) the numerical tool equipped with the MOOD technique provides better solutions in comparison with the MUSCL results. At last, we apply and compare the two techniques to the real-case scenario Tohoku-Oki (Japan), 2011 tsunami., FEDER (Programa Operacional Factores de Competitividade - COMPETE). FCT (FCT-ANR/MAT-NAN/0122/2012), info:eu-repo/semantics/publishedVersion

Regional and global tsunami hazard analysis requires simplified and efficient methods for estimating the tsunami inundation height and its related uncertainty. One such approach is the amplification factor (AF) method. Amplification factors describe the relation between offshore wave height and the maximum inundation height, as predicted by linearized plane wave models employed for incident waves with different wave characteristics. In this study, a new amplification factor method is developed that takes into account the offshore bathymetry proximal to the coastal site. The present AFs cover the North-Eastern Atlantic and Mediterranean (NEAM) region. The model is the first general approximate model that quantifies inundation height uncertainty. Uncertainty quantification is carried out by analyzing the inundation height variability in more than 500 high-resolution inundation simulations at six different coastal sites. The inundation simulations are undertaken with different earthquake sources in order to produce different wave period and polarity. We show that the probability density of the maximum inundation height can be modeled with a log-normal distribution, whose median is quite well predicted by the AF. It is further demonstrated that the associated maximum inundation height uncertainties are significant and must be accounted for in tsunami hazard analysis. The application to the recently developed TSUMAPS-NEAM probabilistic tsunami hazard analysis (PTHA) is presented as a use case.

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.

International audience; Applying probabilistic methods to infrequent but devastating natural events is intrinsicallychallenging. For tsunami analyses, a suite of geophysical assessments should be in principle evaluatedbecause of the different causes generating tsunamis (earthquakes, landslides, volcanic activity,meteorological events, and asteroid impacts) with varying mean recurrence rates. Probabilistic TsunamiHazard Analyses (PTHAs) are conducted in different areas of the world at global, regional, and local scaleswith the aim of understanding tsunami hazard to inform tsunami risk reduction activities. PTHAs enhanceknowledge of the potential tsunamigenic threat by estimating the probability of exceeding specificlevels of tsunami intensity metrics (e.g., run-up or maximum inundation heights) within a certain period oftime (exposure time) at given locations (target sites); these estimates can be summarized in hazard mapsor hazard curves. This discussion presents a broad overview of PTHA, including (i) sources and mechanismsof tsunami generation, emphasizing the variety and complexity of the tsunami sources and their generationmechanisms, (ii) developments in modeling the propagation and impact of tsunami waves, and (iii)statistical procedures for tsunami hazard estimates that include the associated epistemic and aleatoricuncertainties. Key elements in understanding the potential tsunami hazard are discussed, in light of therapid development of PTHA methods during the last decade and the globally distributed applications,including the importance of considering multiple sources, their relative intensities, probabilities ofoccurrence, and uncertainties in an integrated and consistent probabilistic framework.