The Italian Earthquakes and Tsunami Monitoring and Surveillance Systems

The Osservatorio Nazionale Terremoti (ONT) is the Italian seismic operational centre for monitoring earthquake, it is part of Istituto Nazionale di Geofisica e Vulcanologia (INGV) the largest Italian research institution, with focus in Earth Sciences. INGV runs the Italian National Seismic Network (network code IV) and other networks at national scale for monitoring earthquakes and tsunami. INGV is a primary node of European Integrated Data Archive (EIDA) for archiving and distributing, continuous, quality checked seismic waveforms (strong motion and weak motion recordings). ONT designed the data acquisition system to accomplish, in near-real-time, automatic earthquake detection, hypocentre and magnitude determination and evaluation of moment tensors, shake maps and other products. Database archiving of all parametric results are closely linked to the existing procedures of the INGV seismic monitoring environment and surveillance procedures. ONT organize the Italian earthquake surveillance service and the tsunami alert service (INGV is Tsunami Service Provider of the ICG/NEAM for the entire Mediterranean basin). We provide information to the Dipartimento di Protezione Civile (DPC) and to several Mediterranean countries. Earthquakes information are revised routinely by the analysts of the Italian Seismic Bulletin. The results are published on the web and are available to the scientific community and the general public.PublishedMontreal1SR TERREMOTI - Sorveglianza Sismica e Allerta Tsunam

The EU Center of Excellence for Exascale in Solid Earth (ChEESE): Implementation, results, and roadmap for the second phase

The EU Center of Excellence for Exascale in Solid Earth (ChEESE) develops exascale transition capabilities in the domain of Solid Earth, an area of geophysics rich in computational challenges embracing different approaches to exascale (capability, capacity, and urgent computing). The first implementation phase of the project (ChEESE-1P; 2018¿2022) addressed scientific and technical computational challenges in seismology, tsunami science, volcanology, and magnetohydrodynamics, in order to understand the phenomena, anticipate the impact of natural disasters, and contribute to risk management. The project initiated the optimisation of 10 community flagship codes for the upcoming exascale systems and implemented 12 Pilot Demonstrators that combine the flagship codes with dedicated workflows in order to address the underlying capability and capacity computational challenges. Pilot Demonstrators reaching more mature Technology Readiness Levels (TRLs) were further enabled in operational service environments on critical aspects of geohazards such as long-term and short-term probabilistic hazard assessment, urgent computing, and early warning and probabilistic forecasting. Partnership and service co-design with members of the project Industry and User Board (IUB) leveraged the uptake of results across multiple research institutions, academia, industry, and public governance bodies (e.g. civil protection agencies). This article summarises the implementation strategy and the results from ChEESE-1P, outlining also the underpinning concepts and the roadmap for the on-going second project implementation phase (ChEESE-2P; 2023¿2026).This work has been funded by the European Union Horizon 2020 research and innovation program under the ChEESE project, Grant Agreemen

The EU Center of Excellence for Exascale in Solid Earth (ChEESE): Implementation, results, and roadmap for the second phase

publishedVersio

Probabilistic Tsunami Hazard Analysis: High Performance Computing for Massive Scale Inundation Simulations

Probabilistic Tsunami Hazard Analysis (PTHA) quantifies the probability of exceeding a specified inundation intensity at a given location within a given time interval. PTHA provides scientific guidance for tsunami risk analysis and risk management, including coastal planning and early warning. Explicit computation of site-specific PTHA, with an adequate discretization of source scenarios combined with high-resolution numerical inundation modelling, has been out of reach with existing models and computing capabilities, with tens to hundreds of thousands of moderately intensive numerical simulations being required for exhaustive uncertainty quantification. In recent years, more efficient GPU-based High-Performance Computing (HPC) facilities, together with efficient GPU-optimized shallow water type models for simulating tsunami inundation, have now made local long-term hazard assessment feasible. A workflow has been developed with three main stages: 1) Site-specific source selection and discretization, 2) Efficient numerical inundation simulation for each scenario using the GPU-based Tsunami-HySEA numerical tsunami propagation and inundation model using a system of nested topo-bathymetric grids, and 3) Hazard aggregation. We apply this site-specific PTHA workflow here to Catania, Sicily, for tsunamigenic earthquake sources in the Mediterranean. We illustrate the workflows of the PTHA as implemented for High-Performance Computing applications, including preliminary simulations carried out on intermediate scale GPU clusters. We show how the local hazard analysis conducted here produces a more fine-grained assessment than is possible with a regional assessment. However, the new local PTHA indicates somewhat lower probabilities of exceedance for higher maximum inundation heights than the available regional PTHA. The local hazard analysis takes into account small-scale tsunami inundation features and non-linearity which the regional-scale assessment does not incorporate. However, the deterministic inundation simulations neglect some uncertainties stemming from the simplified source treatment and tsunami modelling that are embedded in the regional stochastic approach to inundation height estimation. Further research is needed to quantify the uncertainty associated with numerical inundation modelling and to properly propagate it onto the hazard results, to fully exploit the potential of site-specific hazard assessment based on massive simulations.publishedVersio

From Seismic Monitoring to Tsunami Warning in the Mediterranean Sea

Abstract The Italian Tsunami Alert Center based at the Istituto Nazionale di Geofisica e Vulcanologia (CAT-INGV) has been monitoring the Mediterranean seismicity in the past 8 yr to get fast and reliable information for seismically induced tsunami warnings. CAT-INGV is a tsunami service provider in charge of monitoring the seismicity of the Mediterranean Sea and of alerting Intergovernmental Oceanographic Commission (IOC)/UNESCO subscriber Member States and the Italian Department of Civil Protection of a potentially impending tsunami, in the framework of the Tsunami Warning and Mitigation System in the North-eastern Atlantic, the Mediterranean and connected seas (NEAMTWS). CAT-INGV started operating in 2013 and became operational in October 2016. Here, after describing the NEAMTWS in the framework of the global effort coordinated by IOC/UNESCO, we focus on the tsunami hazard in the Mediterranean Sea. We then describe CAT-INGV mandate, functioning, and operational procedures. Furthermore, the article discusses the lessons learned from past events occurring in the Mediterranean Sea, such as the Kos-Bodrum in 2017 (Mw 6.6) and the Samos-Izmir in 2020 (Mw 7.0) earthquakes, which generated moderately damaging tsunamis. Based on these lessons, we discuss some potential improvements for the CAT-INGV and the NEAMTWS, including better seismic and sea level instrumental coverage. We emphasize the need for tsunami risk awareness raising, better preparation, and full implementation of the tsunami warning “last-mile” to foster the creation of a more integrated, interoperable, and sustainable risk reduction framework. If we aim to be better prepared for the next tsunami, these important challenges should be prioritized in the agenda of the IOC/UNESCO Member States and the European Commission

Probabilistic Tsunami Hazard Analysis: High Performance Computing for Massive Scale Inundation Simulations

Probabilistic Tsunami Hazard Analysis (PTHA) quantifies the probability of exceeding a specified inundation intensity at a given location within a given time interval. PTHA provides scientific guidance for tsunami risk analysis and risk management, including coastal planning and early warning. Explicit computation of site-specific PTHA, with an adequate discretization of source scenarios combined with high-resolution numerical inundation modelling, has been out of reach with existing models and computing capabilities, with tens to hundreds of thousands of moderately intensive numerical simulations being required for exhaustive uncertainty quantification. In recent years, more efficient GPU-based High-Performance Computing (HPC) facilities, together with efficient GPU-optimized shallow water type models for simulating tsunami inundation, have now made local long-term hazard assessment feasible. A workflow has been developed with three main stages: 1) Site-specific source selection and discretization, 2) Efficient numerical inundation simulation for each scenario using the GPU-based Tsunami-HySEA numerical tsunami propagation and inundation model using a system of nested topo-bathymetric grids, and 3) Hazard aggregation. We apply this site-specific PTHA workflow here to Catania, Sicily, for tsunamigenic earthquake sources in the Mediterranean. We illustrate the workflows of the PTHA as implemented for High-Performance Computing applications, including preliminary simulations carried out on intermediate scale GPU clusters. We show how the local hazard analysis conducted here produces a more fine-grained assessment than is possible with a regional assessment. However, the new local PTHA indicates somewhat lower probabilities of exceedance for higher maximum inundation heights than the available regional PTHA. The local hazard analysis takes into account small-scale tsunami inundation features and non-linearity which the regional-scale assessment does not incorporate. However, the deterministic inundation simulations neglect some uncertainties stemming from the simplified source treatment and tsunami modelling that are embedded in the regional stochastic approach to inundation height estimation. Further research is needed to quantify the uncertainty associated with numerical inundation modelling and to properly propagate it onto the hazard results, to fully exploit the potential of site-specific hazard assessment based on massive simulations