ALBERT

Description: Tsunamis are unpredictable and infrequent but potentially large impact natural disasters. To prepare, mitigate and prevent losses from tsunamis, probabilistic hazard and risk analysis methods have been developed and have proved useful. However, large gaps and uncertainties still exist and many steps in the assessment methods lack information, theoretical foundation, or commonly accepted methods. Moreover, applied methods have very different levels of maturity, from already advanced probabilistic tsunami hazard analysis for earthquake sources, to less mature probabilistic risk analysis. In this review we give an overview of the current state of probabilistic tsunami hazard and risk analysis. Identifying research gaps, we offer suggestions for future research directions. An extensive literature list allows for branching into diverse aspects of this scientific approach.

Description: 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).

Description: Applying probabilistic methods to infrequent but devastating natural events is intrinsically challenging. For tsunami analyses, a suite of geophysical assessments should be in principle evaluated because of the different causes generating tsunamis (earthquakes, landslides, volcanic activity, meteorological events, and asteroid impacts) with varying mean recurrence rates. Probabilistic Tsunami Hazard Analyses (PTHAs) are conducted in different areas of the world at global, regional, and local scales with the aim of understanding tsunami hazard to inform tsunami risk reduction activities. PTHAs enhance knowledge of the potential tsunamigenic threat by estimating the probability of exceeding specific levels of tsunami intensity metrics (e.g., run-up or maximum inundation heights) within a certain period of time (exposure time) at given locations (target sites); these estimates can be summarized in hazard maps or hazard curves. This discussion presents a broad overview of PTHA, including (i) sources and mechanisms of tsunami generation, emphasizing the variety and complexity of the tsunami sources and their generation mechanisms, (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 aleatoric uncertainties. Key elements in understanding the potential tsunami hazard are discussed, in light of the rapid development of PTHA methods during the last decade and the globally distributed applications, including the importance of considering multiple sources, their relative intensities, probabilities of occurrence, and uncertainties in an integrated and consistent probabilistic framework.

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: 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.

Description: 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).

Description: Very large tsunamis are associated with low probabilities of occurrence. In many parts of the world, these events have usually occurred in a distant time in the past. As a result, there is low risk perception and a lack of collective memories, making tsunami risk communication both challenging and complex. Furthermore, immense challenges lie ahead as population and risk exposure continue to increase in coastal areas. Through the last decades, tsunamis have caught coastal populations off-guard, providing evidence of lack of preparedness. Recent tsunamis, such as the Indian Ocean Tsunami in 2004, 2011 Tohoku and 2018 Palu, have shaped the way tsunami risk is perceived and acted upon. Based on lessons learned from a selection of past tsunami events, this paper aims to review the existing body of knowledge and the current challenges in tsunami risk communication, and to identify the gaps in the tsunami risk management methodologies. The important lessons provided by the past events call for strengthening community resilience and improvement in risk-informed actions and policy measures. This paper shows that research efforts related to tsunami risk communication remain fragmented. The analysis of tsunami risk together with a thorough understanding of risk communication gaps and challenges is indispensable towards developing and deploying comprehensive disaster risk reduction measures. Moving from a broad and interdisciplinary perspective, the paper suggests that probabilistic hazard and risk assessments could potentially contribute towards better science communication and improved planning and implementation of risk mitigation measures.

Description: Probabilistic Tsunami Hazard and Risk Analysis (PTHA/PTRA) has its roots in the corresponding probabilistic approaches in the seismic sciences. However, there are several substantial differences in the cascading source and effect modeling chain, necessitating for complex workflows, involving still larger gaps in data and knowledge, and requiring different approaches in dealing with uncertainties. The European Cooperation in Science and Technology (COST) Action AGITHAR (Accelerating Global Science in Probabilistic Hazard and Risk Analysis) has run for four years and has since then gathered parts of the scientific community around PTHA/PTRA and made some substantial progress in communicating and unifying the underlying concepts. Additionally, the effort has allowed the European tsunami community to coordinate a number of new research efforts and infrastrucutral developments, which are of benefit for the global science in PTHA/PTRA. In this presentation we will outline the results of AGITHAR's major deliverables, a compilation of research gaps in PTHA/PTRA and uncertainty communication, findings in interdisciplinary tsunami research cooperation, and a collection of current practices in PTHA/PTRA. Ideas and opportunities of sustaining AGITHAR's output into the future will be given.

Description: Probabilistic Tsunami Forecasting (PTF) combines early estimates of earthquake parameters with ensembles of urgent tsunami propagation simulations through the Tsunami-HySEA model. In the present implementation, the PTF is initialised by the earthquake information, but not updated further with new data. In the recently started Horizon Europe project DT-GEO work has started upgrading it into a Digital Twin providing a time dependent update of the model when new data becomes available. This enables a close to real time synthesis of data products and numerical models, continuously updating the model forecast as new data are continuously assimilated. In DT-GEO, an extended set of data sources, including improved earthquake solutions, sea level tsunami data, and GNSS, will be integrated. Secondly, the Digital Twin will implement a modularised inclusion of improved wave and source physics through dispersion, non-hydrostatic tsunami generation, inundation, improved earthquake physics, and cascading earthquake triggered landslide tsunamis. The model will be tested at site demonstrators, in the Mediterranean Sea for eastern Sicily and Samos, and in the Pacific Ocean for Chile and Japan. The presentation will explain how the PTF as it works today, followed by an outline of the design of the components in the Digital Twin. The presentation will finally describe initial improvements and plans for further development, including long term plans such as potential integration into Destination Earth and service provision within EPOS-ERIC. This work is supported by the European Union’s Horizon Europe Research and Innovation Program under grant agreement No 101058129 (DT-GEO, https://dtgeo.eu/).

Description: Nowadays, Tsunami Early Warning Systems (TEWS) issue the first alert between three and five minutes after the occurrence of a potentially tsunamigenic earthquake. For offshore earthquakes, for which a significant network azimuthal gap limits the accuracy of standard techniques for source location, this time is spent to obtain stable estimations of the event magnitude and depth. This large warning time affects the efficiency of TEWS for near-coastal large earthquakes. Recent developments in Earthquake Early Warning Systems (EEWS) mitigates this issue. Here, we consider a P-wave, shaking-forecast based EEW method (Zollo et al., 2023) to provide fast and accurate estimations of event location and magnitude along with the Potential Damage Zone (PDZ). As a first test of a combined E- and T- EWS, we applied the method by playing-back the simulated records of two events of Mw 6 and 7 in the Messina strait, with source characteristics that mimic the 1908 Messina earthquake. The events are simulated at the INGV and RAN seismic stations along the Sicily and Calabria coasts. We estimated stable and accurate hypocenter locations and magnitude determinations in 20-25 seconds for both events. The shape of the PDZ obtained after 30 s from the earthquake origin well reproduces the geometry of the rupture surface. These first results show that combining EEWS and TEWS can speed up the tsunami forecasting, thus increasing the lead-time available for actions to protect the exposed population.