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We present a source solution for the tsunami generated by the Mw 6.6 earthquake that occurred on 2 May 2020, about 80 km offshore south of Crete, in the Cretan Passage, on the shallow portion of the Hellenic Arc subduction zone (HASZ). The tide gauges recorded this local tsunami on the southern coast of Crete and Kasos island. We used Crete tsunami observations to constrain the geometry and orientation of the causative fault, the rupture mechanism, and the slip amount. We first modelled an ensemble of synthetic tsunami waveforms at the tide gauge locations, produced for a range of earthquake parameter values as constrained by some of the available moment tensor solutions. We allow for both a splay and a back-thrust fault, corresponding to the two nodal planes of the moment tensor solution. We then measured the misfit between the synthetic and the Ierapetra observed marigram for each source parameter set. Our results identify the shallow, steeply dipping back-thrust fault as the one producing the lowest misfit to the tsunami data. However, a rupture on a lower angle fault, possibly a splay fault, with a sinistral component due to the oblique convergence on this segment of the HASZ, cannot be completely ruled out. This earthquake reminds us that the uncertainty regarding potential earthquake mechanisms at a specific location remains quite significant. In this case, for example, it is not possible to anticipate if the next event will be one occurring on the subduction interface, on a splay fault, or on a back-thrust, which seems the most likely for the event under investigation. This circumstance bears important consequences because back-thrust and splay faults might enhance the tsunamigenic potential with respect to the subduction interface due to their steeper dip. Then, these results are relevant for tsunami forecasting in the framework of both the long-term hazard assessment and the early warning systems.

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)., Future Generation Computer Systems, 146, ISSN:0167-739X, ISSN:1872-7115

Special issue EPOS a Research Infrastructure in solid Earth: open science and innovation .-- 21 pages, 8 figures, Tsunamis constitute a significant hazard for European coastal populations, and the impact of tsunami events worldwide can extend well beyond the coastal regions directly affected. Understanding the complex mechanisms of tsunami generation, propagation, and inundation, as well as managing the tsunami risk, requires multidisciplinary research and infrastructures that cross national boundaries. Recent decades have seen both great advances in tsunami science and consolidation of the European tsunami research community. A recurring theme has been the need for a sustainable platform for coordinated tsunami community activities and a hub for tsunami services. Following about three years of preparation, in July 2021, the European tsunami community attained the status of Candidate Thematic Core Service (cTCS) within the European Plate Observing System (EPOS) Research Infrastructure. Within a transition period of three years, the Tsunami candidate TCS is anticipated to develop into a fully operational EPOS TCS. We here outline the path taken to reach this point, and the envisaged form of the future EPOS TCS Tsunami. Our cTCS is planned to be organised within four thematic pillars: (1) Support to Tsunami Service Providers, (2) Tsunami Data, (3) Numerical Models, and (4) Hazard and Risk Products. We outline how identified needs in tsunami science and tsunami risk mitigation will be addressed within this structure and how participation within EPOS will become an integration point for community development, With the institutional support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S)

Destructive tsunamis are most often generated by large earthquakes occurring at subduction interfaces, but also other “atypical” sources—defined as crustal earthquakes and non-seismic sources altogether—may cause significant tsunami threats. Tsunamis may indeed be generated by different sources, such as earthquakes, submarine or coastal landslides, volcano-related phenomena, and atmospheric perturbations. The consideration of atypical sources is important worldwide, but it is especially prominent in complex tectonic settings such as the Mediterranean, the Caribbean, or the Indonesian archipelago. The recent disasters in Indonesia in 2018, caused by the Palu-Sulawesi magnitude Mw 7.5 crustal earthquake and by the collapse of the Anak-Krakatau volcano, recall the importance of such sources. Dealing with atypical sources represents a scientific, technical, and computational challenge, which depends on the capability of quantifying and managing uncertainty efficiently and of reducing it with accurate physical modelling. Here, we first introduce the general framework in which tsunami threats are treated, and then we review the current status and the expected future development of tsunami hazard quantifications and of the tsunami warning systems in Italy, with a specific focus on the treatment of atypical sources. In Italy, where the memory of historical atypical events like the 1908 Messina earthquake or the relatively recent 2002 Stromboli tsunami is still vivid, specific attention has been indeed dedicated to the progressive development of innovative strategies to deal with such atypical sources. More specifically, we review the (national) hazard analyses and their application for coastal planning, as well as the two operating tsunami warning systems: the national warning system for seismically generated tsunamis (SiAM), whose upstream component—the CAT-INGV—is also a Tsunami Service Provider of the North-eastern Atlantic, the Mediterranean and connected seas Tsunami Warning System (NEAMTWS) coordinated by the Intergovernmental Coordination Group established by the Intergovernmental Oceanographic Commission (IOC) of UNESCO, and the local warning system for tsunamis generated by volcanic slides along the Sciara del Fuoco of Stromboli volcano. Finally, we review the state of knowledge about other potential tsunami sources that may generate significant tsunamis for the Italian coasts, but that are not presently considered in existing tsunami warning systems. This may be considered the first step towards their inclusion in the national tsunami hazard and warning programs.

Site-specific seismic probabilistic tsunami hazard analysis (SPTHA) is a computationally demanding task, as it requires, in principle, a huge number of high-resolution numerical simulations for producing probabilistic inundation maps. We implemented an efficient and robust methodology using a filtering procedure to reduce the number of numerical simulations needed while still allowing for a full treatment of aleatory and epistemic uncertainty. Moreover, to avoid biases in tsunami hazard assessment, we developed a strategy to identify and separately treat tsunamis generated by near-field earthquakes. Indeed, the coseismic deformation produced by local earthquakes necessarily affects tsunami intensity, depending on the scenario size, mechanism and position, as coastal uplift or subsidence tends to diminish or increase the tsunami hazard, respectively. Therefore, we proposed two parallel filtering schemes in the far- and the near-field, based on the similarity of offshore tsunamis and hazard curves and on the similarity of the coseismic fields, respectively. This becomes mandatory as offshore tsunami amplitudes can not represent a proxy for the coastal inundation in the case of near-field sources. We applied the method to an illustrative use case at the Milazzo oil refinery (Sicily, Italy). We demonstrate that a blind filtering procedure can not properly account for local sources and would lead to a nonrepresentative selection of important scenarios. For the specific source–target configuration, this results in an overestimation of the tsunami hazard, which turns out to be correlated to dominant coastal uplift. Different settings could produce either the opposite or a mixed behavior along the coastline. However, we show that the effects of the coseismic deformation due to local sources can not be neglected and a suitable correction has to be employed when assessing local-scale SPTHA, irrespective of the specific signs of coastal displacement.

We present a source solution for the tsunami generated by the Mw 6.6 earthquake that occurred on May 2, 2020, about 807thinsp;km offshore south of Crete, in the Cretan Passage, on the shallow portion of the Hellenic Arc Subduction Zone (HASZ). The tide-gauges recorded this local tsunami on the southern coast of Crete island and Kasos island. We used these tsunami observations to constrain the geometry and orientation of the causative fault, the rupture mechanism and the slip amount. We first modelled an ensemble of synthetic tsunami waveforms at the tide-gauge locations, produced for a range of earthquake parameter values as constrained by some of the available moment tensor solutions. We allow for both a splay and a back-thrust fault, corresponding to the two nodal planes of the moment tensor solution. We then measured the misfit between the synthetic and the observed marigrams for each source parameter set. Our results identify the shallow steeply-dipping back-thrust fault as the one producing the lowest misfit to the tsunami data. However, a rupture on a lower angle fault, possibly a splay fault, with a sinistral component due to the oblique convergence on this segment of the HASZ, cannot be completely ruled out. This earthquake reminds us that the uncertainty regarding potential earthquake mechanisms at a specific location remains quite significant. In this case, for example, it is not possible to anticipate if the next event will be one occurring on the subduction interface, on a splay fault, or on a back-thrust which seems the most likely for the event under investigation. This circumstance bears important consequences because back-thrust and splay faults might enhance the tsunamigenic potential with respect to the subduction interface due to their steeper dip. Then, these results are relevant for tsunami forecasting both in the framework of the long-term hazard assessment and of the early warning systems.

We conduct a probabilistic volcanic hazard assessment for Ceboruco volcano (Mexico) using PyBetVH, an e-tool based on the Bayesian event tree (BET) methodology. We use available information about the volcano, including eruptive history, numerical and theoretical models, to generate probability maps. Our hazard assessment accounts for the variability of eruption types expected at Ceboruco and the hazardous volcanic phenomena these eruptions generate. We create a generic event tree for Ceboruco to account for magmatic and amagmatic activity. For a magmatic eruption, we choose three scenarios: i) small (effusive), ii) medium (vulcanian/subPlinian) and iii) large (Plinian) based on the Holocene history of the volcano; with their related hazardous phenomena: ballistics, tephra fallout, pyroclastic density currents, lahars and lava flows. Despite numerous eruptions in the latest Holocene and efforts by several university and government groups to create and sustain a monitoring network, Ceboruco remains under-monitored, meaning that it is intermittently rather than continuously monitored by dedicated groups. With no consistent monitoring data available, we look at the geology and the eruptive history to inform our prior models. We estimate the probability of a magmatic eruption within the next time window (1 year) of ~ 0.002. We show how the BET creates higher probabilities in the absence of monitoring data. That is, there is a cost in terms of higher probabilities and higher uncertainties for having not yet developed a sustained volcano monitoring network. We present absolute probability maps (unconditional in terms of eruption size and vent location) for a magmatic eruption at Ceboruco volcano. With PyBetVH we estimate and visualize the uncertainties associated with each hazard map. Our intent is that hazard maps and uncertainties will be useful to local authorities who need to understand the hazard maps when considering the development of long-term urban and land-use planning and short-term crisis management strategies, and to the scientific community in their efforts to sustain monitoring of this active volcano.

Finite-fault models for the 2010Mw8.8 Maule, Chile earthquake indicate bilateral rupture with large-slip patches located north and south of the epicenter. Previous studies also show that this event features significant slip in the shallow part of the megathrust, which is revealed through correction of the forward tsunami modeling scheme used in tsunami inversions. The presence of shallow slip is consistent with the coseismic seafloor deformation measured off the Maule region adjacent to the trench and confirms that tsunami observations are particularly important for constraining far-offshore slip. Here, we benchmark the method of Optimal Time Alignment (OTA) of the tsunami waveforms in the joint inversion of tsunami (DART and tide-gauges) and geodetic (GPS, InSAR, land-leveling) observations for this event. We test the application of OTA to the tsunami Green’s functions used in a previous inversion. Through a suite of synthetic tests we show that if the bias in the forward model is comprised only of delays in the tsunami signals, the OTA can correct them precisely, independently of the sensors (DART or coastal tide-gauges) and, to the first-order, of the bathymetric model used. The same suite of experiments is repeated for the real case of the 2010 Maule earthquake where, despite the results of the synthetic tests, DARTs are shown to outperform tide-gauges. This gives an indication of the relative weights to be assigned when jointly inverting the two types of data. Moreover, we show that using OTA is preferable to subjectively correcting possible time mismatch of the tsunami waveforms. The results for the source model of the Maule earthquake show that using just the first-order modeling correction introduced by OTA confirms the bilateral rupture pattern around the epicenter, and, most importantly, shifts the inferred northern patch of slip to a shallower position consistent with the slip models obtained by applying more complex physics-based corrections to the tsunami waveforms. This is confirmed by a slip model refined by inverting geodetic and tsunami data complemented with a denser distribution of GPS data nearby the source area. The models obtained with the OTA method are finally benchmarked against the observed seafloor deformation off the Maule region. We find that all of the models using the OTA well predict this offshore coseismic deformation, thus overall, this benchmarking of the OTA method can be considered successful.

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.

A methodology for a comprehensive probabilistic tsunami hazard analysis is presented for the major sources of tsunamis (seismic events, landslides, and volcanic activity) and preliminarily applied in the Gulf of Naples (Italy). The methodology uses both a modular procedure to evaluate the tsunami hazard and a Bayesian analysis to include the historical information of the past tsunami events. In the urn:x-wiley:jgrc:media:jgrc23818:jgrc23818-math-0001 the submarine earthquakes and the submarine mass failures are initially identified in a gridded domain and defined by a set of parameters, producing the sea floor deformations and the corresponding initial tsunami waves. Differently volcanic tsunamis generate sea surface waves caused by pyroclastic density currents from Somma‐Vesuvius. In the urn:x-wiley:jgrc:media:jgrc23818:jgrc23818-math-0002 the tsunami waves are simulated and propagated in the deep sea by a numerical model that solves the shallow water equations. In the urn:x-wiley:jgrc:media:jgrc23818:jgrc23818-math-0003 the tsunami wave heights are estimated at the coast using the urn:x-wiley:jgrc:media:jgrc23818:jgrc23818-math-0004's amplification law. The selected tsunami intensity is the wave height. In the urn:x-wiley:jgrc:media:jgrc23818:jgrc23818-math-0005 the probabilistic tsunami analysis computes the long‐term comprehensive Bayesian probabilistic tsunami hazard analysis. In the prior analysis the probabilities from the scenarios in which the tsunami parameter overcomes the selected threshold levels are combined with the spatial, temporal, and frequency‐size probabilities of occurrence of the tsunamigenic sources. The urn:x-wiley:jgrc:media:jgrc23818:jgrc23818-math-0006 probability density functions are integrated with the urn:x-wiley:jgrc:media:jgrc23818:jgrc23818-math-0007 derived from the historical information based on past tsunami data. The urn:x-wiley:jgrc:media:jgrc23818:jgrc23818-math-0008 probability density functions are evaluated to produce the hazard curves in selected sites of the Gulf of Naples. Plain Language Summary Probabilistic analyses are essential to estimate the natural hazards caused by infrequent and devastating events and to elaborate risk assessments aiming to mitigate and reduce the impact of the natural disasters on society. Probabilistic tsunami hazard analyses use procedures that trace and weight the different tsunami sources (submarine earthquakes, aerial/submarine slides, volcanic activity, meteorological events, and asteroid impacts) with varying probability of occurrence. The scope of the present methodology is the reduction of possible biases and underestimations that arise by focusing on a single tunamigenic source. The multisource probabilistic tsunami hazard analysis is applied to a real case study, the Gulf of Naples (Italy), where relevant threats due to natural events exist in a high densely populated district. The probabilistic hazard procedure takes into account multiple tsunamigenic sources in the region and provides a first‐order prioritization of the different sources in a long‐term comprehensive analysis. The methodology is based on a Bayesian approach that merges computational hazard quantification (based on source‐tsunami simulations) and past data, appropriately including in the quantification the epistemic uncertainty. For the first time a probabilistic analysis of the tsunami hazard in the region is presented taking into consideration multiple tsunamigenic sources.

SUMMARY The behaviour of tsunami waves at any location depends on the local morphology of the coasts, the encountered bathymetric features, and the characteristics of the source. However, the importance of accurately modelling the geometric properties of the causative fault for simulations of seismically induced tsunamis is rarely addressed. In this work, we analyse the effects of using two different geometric models of the subduction interface of the Calabrian Arc (southern Italy, Ionian Sea) onto the simulated tsunamis: a detailed 3-D subduction interface obtained from the interpretation of a dense network of seismic reflection profiles, and a planar interface that roughly approximates the 3-D one. These models can be thought of as representing two end-members of the level of knowledge of fault geometry. We define three hypothetical earthquake ruptures of different magnitudes (Mw 7.5, 8.0, 8.5) on each geometry. The resulting tsunami impact is evaluated at the 50-m isobath in front of coastlines of the central and eastern Mediterranean. Our results show that the source geometry imprint is evident on the tsunami waveforms, as recorded at various distances and positions relative to the source. The absolute differences in maximum and minimum wave amplitudes locally exceed one metre, and the relative differences remain systematically above 20 per cent with peaks over 40 per cent. We also observe that tsunami energy directivity and focusing due to bathymetric waveguides take different paths depending on which fault is used. Although the differences increase with increasing earthquake magnitude, there is no simple rule to anticipate the different effects produced by these end-member models of the earthquake source. Our findings suggest that oversimplified source models may hinder our fundamental understanding of the tsunami impact and great care should be adopted when making simplistic assumptions regarding the appropriateness of the planar fault approximation in tsunami studies. We also remark that the geological and geophysical 3-D fault characterization remains a crucial and unavoidable step in tsunami hazard analyses.

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)., Co-financed by the European-Union Civil Protection Mechanism Agreement Number: ECHO/SUB/2015/718568/PREV26

We report on the first ‘real-time' application of the BET_UNREST (Bayesian Event Tree for Volcanic Unrest) probabilistic model, during a VUELCO Simulation Exercise carried out on the island of Dominica, Lesser Antilles, in May 2015. Dominica has a concentration of nine potentially active volcanic centers and frequent volcanic earthquake swarms at shallow depths, intense geothermal activity and recent phreatic explosions (1997) indicate the region is still active. The exercise scenario was developed in secret by a team of scientists from University of West Indies (Trinidad and Tobago) and University of Auckland (New Zealand). The simulated unrest activity was provided to the exercise's Scientific Team in three ‘phases' through exercise injects comprising processed monitoring data. We applied the newly created BET_UNREST model through its software implementation PyBetUnrest, to estimate the probabilities of having i) unrest of ii) magmatic, hydrothermal or tectonic origin, which may or may not lead to iii) an eruption. The probabilities obtained for each simulated phase raised controversy and intense deliberations among the members of the scientific team. The results were often considered to be ‘too high', and were not included in any of the reports presented to ODM (Office for Disaster Management) revealing interesting crisis communication challenges. We concluded that the PyBetUnrest application itself was successful and brought the tool one step closer to a full implementation. However, as with any newly proposed method it needs more testing, and in order to be able to use it in the future we make a series of recommendations for future applications. This article is protected by copyright. All rights reserved.

Co-auteur étranger; International audience; A probabilistic hazard analysis of tsunami generated by subaqueous volcanic explosion is applied to the Campi Flegrei caldera (Campania, Italy). An event tree is developed to quantify the tsunami hazard due to the submarine explosions by: i) defining potential size classes of explosion magnitude on the basis of past volcanic activity in the Campi Flegrei caldera and sites in the underwater part of the caldera; ii) simulating the generation and propagation of the consequent tsunami waves able to reach the coasts of the Campania region for all combinations of tsunami-generating vents and sizes; and iii) quantifying the tsunami probability and relative uncertainty, conditional upon the occurrence of an underwater eruption at Campi Flegrei. Tsunami hazard generated by subaqueous volcanic explosions is considered crucial because of its potential high impact on the densely populated coastal areas of the Pozzuoli Bay and Gulf of Naples even if the probability for eruptions in the submarine part of the caldera is certainly low. The tsunami hazard analysis is presented using conditional hazard curves and maps, that is calculating the probability (and relative uncertainties) of exceeding given tsunami intensity thresholds (wave amplitudes at the coast), given the occurrence of a subaqueous eruption. The results indicate that a significant tsunami hazard exists in many areas of the Bay of Naples.

Site-specific Seismic Probabilistic Tsunami Hazard Analysis (SPTHA) is computationally demanding, as it requires in principle a huge number of high-resolution numerical simulations for producing probabilistic inundation maps. We implemented an efficient and robust methodology that, based on the similarity of offshore tsunamis and hazard curves in front of a target site, uses a filtering procedure to reduce the number of numerical simulations needed, while still allowing full treatment of aleatory and epistemic uncertainty. Moreover, near-field sources are identified, on the basis of the tsunami coseismic initial conditions, and treated separately to avoid biases in the tsunami hazard assessment. In fact, coastal coseismic deformation necessarily affects the tsunami intensity, depending on the scenario size, mechanism, and position. Therefore, we developed two parallel filtering schemes in the far- and the near-field, respectively. For near-field sources, offshore tsunami amplitude can not represent a proxy for the coastal inundation, and filtering is based on coseismic field. By comparison of the results obtained with and without the correction for the near-field sources, for a use-case at the Milazzo oil refinery (Sicily, Italy), we demonstrated that special treatment of local sources plays a fundamental role and is applicable in local scale SPTHA.

Phreatic eruptions, although posing a serious threat to people in crater proximity, are often underestimated and have been comparatively understudied. The detailed eruption catalogue for Ruapehu Volcano (New Zealand) provides an exceptional opportunity to study the statistics of recurring phreatic explosions at a crater lake volcano. We performed a statistical analysis on this phreatic eruption database, which suggests that phreatic events at Ruapehu do not follow a Poisson process. Instead they tend to cluster, which is possibly linked to an increased heat flow during periods of a more shallow-seated magma column. Larger explosions are more likely to follow shortly after smaller events, as opposed to longer periods of quiescence. The absolute probability for a phreatic explosion to occur at Ruapehu within the next month is about 10%, when averaging over the last 70 years of recording. However, the frequency of phreatic explosions is significantly higher than the background level in years prior to magmatic episodes. Combining clast ejection simulations with a Bayesian event tree tool (PyBetVH) we perform a probabilistic assessment of the hazard due to ballistic ejecta in the summit area of Ruapehu, which is frequently visited by hikers. Resulting hazard maps show that the absolute probability for the summit to be affected by ballistics within the next month is up to 6%. The hazard is especially high on the northern lakeshore, where there is a mountain refuge. Our results contribute to the local hazard assessment as well as the general perception of hazards due to steam-driven explosions.

Nowadays numerical models are a powerful tool in tsunami research since they can be used (i) to reconstruct modern and historical events, (ii) to cast new light on tsunami sources by inverting tsunami data and observations, (iii) to build scenarios in the frame of tsunami mitigation plans, and (iv) to produce forecasts of tsunami impact and inundation in systems of early warning. In parallel with the general recognition of the importance of numerical tsunami simulations, the demand has grown for reliable tsunami codes, validated through tests agreed upon by the tsunami community. This paper presents the tsunami code UBO-TSUFD that has been developed at the University of Bologna, Italy, and that solves the non-linear shallow water (NSW) equations in a Cartesian frame, with inclusion of bottom friction and exclusion of the Coriolis force, by means of a leapfrog (LF) finite-difference scheme on a staggered grid and that accounts for moving boundaries to compute sea inundation and withdrawal at the coast. Results of UBO-TSUFD applied to four classical benchmark problems are shown: two benchmarks are based on analytical solutions, one on a plane wave propagating on a flat channel with a constant slope beach; and one on a laboratory experiment. The code is proven to perform very satisfactorily since it reproduces quite well the benchmark theoretical and experimental data. Further, the code is applied to a realistic tsunami case: a scenario of a tsunami threatening the coasts of eastern Sicily, Italy, is defined and discussed based on the historical tsunami of 11 January 1693, i.e. one of the most severe events in the Italian history.

Most volcanic hazard studies focus on magmatic eruptions and their accompanying phenomena. However, hazardous volcanic events can also occur during non-magmatic unrest, defined as a state of volcanic unrest in which no migration of magma is recognised. Examples include tectonic unrest, and hydrothermal unrest that may lead to phreatic eruptions. Recent events (e.g. Ontake eruption, September 2014) have demonstrated that the successful forecasting of phreatic eruptions is still very difficult. It is therefore of paramount importance to identify indicators that define the state of non-magmatic unrest. Often, this type of unrest is driven by fluids-on-the-move, requiring alternative monitoring setups, beyond the classical seismic-geodetic-geochemical architectures. Here we present a new version of the probabilistic model BET (Bayesian Event Tree), called BET_UNREST, specifically developed to include the forecasting of non-magmatic unrest and related hazards. The structure of BET_UNREST differs from the previous BET_EF (BET for Eruption Forecasting) by adding a dedicated branch to detail non-magmatic unrest outcomes. Probabilities are calculated at each node by merging prior models and past data with new incoming monitoring data, and the results can be updated any time new data has been collected. Monitoring data are weighted through pre-defined thresholds of anomaly, as in BET_EF. The BET_UNREST model is introduced here, together with its software implementation PyBetUnrest, with the aim of creating a user-friendly, open-access, and straightforward tool to support short-term volcanic forecasting (already available on the VHub platform). The BET_UNREST model and PyBetUnrest tool are tested through three case studies in the frame of the EU VUELCO project.

The 2011 Tohoku earthquake produced an unexpected large amount of shallow slip greatly contributing to the ensuing tsunami. How frequent are such events? How can they be efficiently modelled for tsunami hazard? Stochastic slip models, which can be computed rapidly, are used to explore the natural slip variability; however, they generally do not deal specifically with shallow slip features. We study the systematic depth-dependence of slip along a thrust fault with a number of 2D dynamic simulations using stochastic shear stress distributions and a geometry based on the cross section of the Tohoku fault. We obtain a probability density for the slip distribution, which varies both with depth, earthquake size and whether the rupture breaks the surface. We propose a method to modify stochastic slip distributions according to this dynamically-derived probability distribution. This method may be efficiently applied to produce large numbers of heterogeneous slip distributions for probabilistic tsunami hazard analysis. Using numerous M9 earthquake scenarios, we demonstrate that incorporating the dynamically-derived probability distribution does enhance the conditional probability of exceedance of maximum estimated tsunami wave heights along the Japanese coast. This technique for integrating dynamic features in stochastic models can be extended to any subduction zone and faulting style.

We present a database of pre-calculated tsunami waveforms for the entire Mediterranean Sea, obtained by numerical propagation of uniformly spaced Gaussian-shaped elementary sources for the sea level elevation. Based on any initial sea surface displacement, the database allows the fast calculation of full waveforms at coastal sites by linear superposition. A computationally inexpensive procedure is set to estimate the coefficients for the linear superposition. The elementary sources size and spacing is fine enough to satisfactorily reproduce the effects of M >= 6.0 earthquakes. Tsunami propagation is modelled by using the Tsunami-HySEA code, a GPU finite volumes solver for the shallow water equations. Like other existing methods based on the initial sea level elevation, this database is independent on the faulting geometry and mechanism, which makes it applicable in any tectonic environment. However, this is the first time to our knowledge that the uncertainty associated to such a procedure is systematically analysed, and that relatively small earthquakes, which may be relevant in the near field of the source in a complex tectonic setting, are considered. We model a large set of synthetic tsunami test scenarios, selected to explore the uncertainty introduced when approximating tsunami waveforms and their maxima by fast and simplified linear combination. The resulting product is suitable for different applications such as probabilistic tsunami hazard analysis, tsunami source inversions and tsunami warning systems.

Assessment of volcanic hazards is necessary for risk mitigation. Typically, hazard assessment is based on one or a few, subjectively chosen representative eruptive scenarios, which use a specific combination of eruptive sizes and intensities to represent a particular size class of eruption. While such eruptive scenarios use a range of representative members to capture a range of eruptive sizes and intensities in order to reflect a wider size class, a scenario approach neglects to account for the intrinsic variability of volcanic eruptions, and implicitly assumes that inter-class size variability (i.e. size difference between different eruptive size classes) dominates over intra-class size variability (i.e. size difference within an eruptive size class), the latter of which is treated as negligible. So far, no quantitative study has been undertaken to verify such an assumption. Here, we adopt a novel Probabilistic Volcanic Hazard Analysis (PVHA) strategy, which accounts for intrinsic eruptive variabilities, to quantify the tephra fallout hazard in the Campania area. We compare the results of the new probabilistic approach with the classical scenario approach. The results allow for determining whether a simplified scenario approach can be considered valid, and for quantifying the bias which arises when full variability is not accounted for. This work was partially supported by the MED-SUV Project funded by the European Union (FP7 Grant Agreement n.308665), the “Futuro in Ricerca 2008 FIRB” ByMuR Project [RBFR0880SR] funded by MIUR (the Italian Ministry of Education, University and Research), and the DPC-INGV V1 (2013–2015) Project, funded by DPC (the Italian Department of Civil Protection) within the agreement between DPC and INGV. Background roadmap, terrain or satellite images in all the pictures were downloaded from Google Maps. The FALL3D simulations have been run at BSC using the MareNostrum supercomputer. We are very grateful to Mary Anne Thompson for providing us with helpful comments. We wish to thank the anonymous reviewers for their suggestions that significantly improved the quality of the manuscript.

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.

Eruption forecasting is a major goal in volcanology. Logically, but unfortunately, forecasting hazards related to non-magmatic unrest is too often overshadowed by eruption forecasting, although many volcanoes often pass through states of non-eruptive and non-magmatic unrest for various and prolonged periods of time. Volcanic hazards related to non-magmatic unrest can be highly violent and/or destructive (e.g., phreatic eruptions, secondary lahars), can lead into magmatic and eventually eruptive unrest, and can be more difficult to forecast than magmatic unrest, for various reasons. The duration of a state of non-magmatic unrest and the cause, type and locus of hazardous events can be highly variable. Moreover, non-magmatic hazards can be related to factors external to the volcano (e.g., climate, earthquake). So far, monitoring networks are often limited to the usual seismic-ground deformation-gas network, whereas recognizing indicators for non-magmatic unrest requires additional approaches. In this study we summarize non-magmatic unrest processes and potential indicators for related hazards. We propose an event-tree to classify non-magmatic unrest, which aims to cover all major hazardous outcomes. This structure could become useful for future probabilistic non-magmatic hazard assessments, and might reveal clues for future monitoring strategies. © 2014 Rouwet et al.

Many volcanic systems are partially or entirely submerged, implying that vents may open underwater. The effect of submerged vents on probabilistic volcanic hazard assessment (PVHA) for tephra fallout has always been neglected, introducing potentially uncontrolled biases. We present a strategy to quantify the effect of submerged vents on PVHA for tephra fallout, based on a simplified empirical model where the efficiency of tephra production decreases as a function of the water depth above the eruptive vent. The method is then applied to Campi Flegrei caldera, comparing its results to those of two reference end-member models and their statistical mixing.

Eastern Sicily is one of the coastal areas most exposed to earthquakes and tsunamis in Italy. The city of Catania that developed between the eastern base of Etna volcano and the Ionian Sea is, together with the neighbour coastal belt, under the strong menace of tsunamis. This paper addresses the estimation of the tsunami hazard for the city of Catania by using the technique of the Worst-case Credible Tsunami Scenario Analysis (WCTSA) and is focused on a target area including the Catania harbour and the beach called La Plaia where many human activities develop and many important structures are present. The aim of the work is to provide a detailed tsunami hazard analysis, firstly by building scenarios that are proposed on the basis of tectonic considerations and of the largest historical events that hit the city in the past, and then by combining all the information deriving from single scenarios into a unique aggregated scenario that can be viewed as the worst virtual scenario. Scenarios have been calculated by means of numerical simulations on computational grids of different resolutions, passing from 3 km on a regional scale to 40 m in the target area. La Plaia beach results to be the area most exposed to tsunami inundation, with inland penetration up to hundreds of meters. The harbour turns out to be more exposed to tsunami waves with low frequencies: in particular, it is found that the major contribution to the hazard in the harbour is due to a tsunami from a remote source, which propagates with much longer periods than tsunamis from local sources. This work has been performed in the framework of the EU-funded project SCHEMA.

[1] A tsunami-like sea disturbance of nonseismic origin was observed on 7 May 2007 on the Bulgarian Black Sea coast. The maximum wave amplitude was three meters, and the sea oscillations lasted for several hours. The anomalous behaviour was seen in many places of the coast of Bulgaria and was stronger in the north. Several accounts of eyewitnesses as well as reports of local port authorities and three tide-gauge recordings are available and have been collected and analysed. The tsunami could have been produced by a submarine landslide or by atmospheric pressure pulses. Here, we explore the former hypothesis, i.e., the possibility that the tsunami was induced by a landslide that may have occurred on the shelf margin off Bulgaria. By making use of numerical modelling we find that submarine mass movements taking place within a certain delimited source area off Bulgaria may have generated tsunamis compatible with the observations.

The evolution of High-Performance Computing (HPC) platforms enables the design and execution of progressively larger and more complex workflow applications in these systems. The complexity comes not only from the number of elements that compose the workflows but also from the type of computations they perform. While traditional HPC workflows target simulations and modelling of physical phenomena, current needs require in addition data analytics (DA) and artificial intelligence (AI) tasks. However, the development of these workflows is hampered by the lack of proper programming models and environments that support the integration of HPC, DA, and AI, as well as the lack of tools to easily deploy and execute the workflows in HPC systems. To progress in this direction, this paper presents use cases where complex workflows are required and investigates the main issues to be addressed for the HPC/DA/AI convergence. Based on this study, the paper identifies the challenges of a new workflow platform to manage complex workflows. Finally, it proposes a development approach for such a workflow platform addressing these challenges in two directions: first, by defining a software stack that provides the functionalities to manage these complex workflows; and second, by proposing the HPC Workflow as a Service (HPCWaaS) paradigm, which leverages the software stack to facilitate the reusability of complex workflows in federated HPC infrastructures. Proposals presented in this work are subject to study and development as part of the EuroHPC eFlows4HPC project., This work has received funding from the European High-Performance Computing Joint Undertaking (JU) under grant agreement No 955558. The JU receives support from the European Union’s Horizon 2020 research and innovation programme and Spain, Germany, France, Italy, Poland, Switzerland and Norway. In Spain, it has received complementary funding from MCIN/AEI/10.13039/501100011033, Spain and the European Union NextGenerationEU/PRTR (contracts PCI2021-121957, PCI2021-121931, PCI2021-121944, and PCI2021-121927). In Germany, it has received complementary funding from the German Federal Ministry of Education and Research (contracts 16HPC016K, 6GPC016K, 16HPC017 and 16HPC018). In France, it has received financial support from Caisse des dépôts et consignations (CDC) under the action PIA ADEIP (project Calculateurs). In Italy, it has been preliminary approved for complimentary funding by Ministero dello Sviluppo Economico (MiSE) (ref. project prop. 2659). In Norway, it has received complementary funding from the Norwegian Research Council, Norway under project number 323825. In Switzerland, it has been preliminary approved for complimentary funding by the State Secretariat for Education, Research, and Innovation (SERI), Norway. In Poland, it is partially supported by the National Centre for Research and Development under decision DWM/EuroHPCJU/4/2021. The authors also acknowledge financial support by MCIN/AEI /10.13039/501100011033, Spain through the “Severo Ochoa Programme for Centres of Excellence in R&D” under Grant CEX2018-000797-S, the Spanish Government, Spain (contract PID2019-107255 GB) and by Generalitat de Catalunya, Spain (contract 2017-SGR-01414). Anna Queralt is a Serra Húnter Fellow., With funding from the Spanish government through the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2018-000797-S).

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., Probabilistic tsunami forecasting (PTF) defines an approach to tsunami early warning based on uncertainty quantification, enhancing forecast accuracy and enabling rational decision making. PTF is here developed for near-source tsunami warning, and tested in hindcasting mode over a wide range of past earthquakes.