NH5.1 | Tsunamis: modelling, hazard assessment, forecasting, and warning
EDI
Tsunamis: modelling, hazard assessment, forecasting, and warning
Convener: Hélène Hébert | Co-conveners: Mohammad Heidarzadeh, Jadranka Sepic, Rachid Omira
Orals
| Mon, 15 Apr, 08:30–12:25 (CEST), 14:00–15:40 (CEST)
 
Room 1.14
Posters on site
| Attendance Tue, 16 Apr, 10:45–12:30 (CEST) | Display Tue, 16 Apr, 08:30–12:30
 
Hall X4
Orals |
Mon, 08:30
Tue, 10:45
Tsunamis can produce catastrophic damage on vulnerable coastlines, essentially following major earthquakes, landslides, extreme volcanic activity or atmospheric disturbances. 20 years after the disastrous Indian Ocean tsunami, tsunami science has been considerably renewed, expanding its scope to new fields of research, and also to regions where the tsunami hazard was previously underestimated. The 2022 Hunga Tonga - Hunga Ha'apai tsunami also provided a new and urging challenge, bringing new questions on modeling, hazard assessment and warning at different scales and evidencing again the need for a closer cooperation among different research and operational communities.

The spectrum of topics addressed by tsunami science nowadays encompass:
- analytical and numerical modelling of different generation mechanisms (from large subduction, to more local earthquakes generated in tectonically complex environments, from subaerial/submarine landslides to volcanic eruptions and atmospheric disturbances), and propagation and run-up,
- hazard-vulnerability-risk assessment, especially with probabilistic approaches able to quantify uncertainties,
early warning and monitoring, with a special focus on innovative marine and seafloor data that could help to improve early characterization of sources and detection of tsunamis,
- societal and economic impact of moderate-to-large events on coastal local and nation-wide coastal communities,
- present and future challenges connected to the global climate change.

This session welcomes multidisciplinary as well as focused contributions covering any of the aspects above-mentioned, encompassing field data, geophysical models, regional and local hazard-vulnerability-risk studies, observation databases, numerical and experimental modeling, real time networks, operational tools and procedures towards a most efficient warning, with the general scope of improving our understanding of the tsunami phenomenon, per se and in the context of the global change, and our capacity to build safer and more resilient communities.

Orals: Mon, 15 Apr | Room 1.14

Chairperson: Hélène Hébert
Tsunami models
08:30–08:40
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EGU24-14374
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ECS
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On-site presentation
Ioanna Triantafyllou, Fumihiko Imamura, and Gerassimos Papadopoulos

Seismic tsunamis are produced from the sea floor dislocation (SFD) due to the earthquake rupture. The size of the SFD depends on the earthquake magnitude, depth and mechanism. The seismic moment, Mot, corresponding to the tsunamigenic SFD, is equal to k∗Mo, where Mo is the entire earthquake moment and k is a coefficient smaller than 1. For a first time, we estimated the coefficient k from published data collected for a set of tsunamigenic earthquakes that occurred in the global ocean from 1990 to 2023. The moment magnitude of these earthquakes ranges from 6.0 to 9.3. No default earthquake mechanism has been adopted. However, all the earthquakes considered are of dip-slip (thrust or normal) or oblique dip-slip types. It has been found that logk increases linearly with the earthquake moment Mo, which implies that the coefficient k increases exponentially with the Mo. For tsunami earthquakes it was found that k has a value larger than its value in regular tsunamis for the same Mo. These results provide a better understanding of the tsunami generation from earthquakes and may open possibilities for estimating the tsunami magnitude at the source.

How to cite: Triantafyllou, I., Imamura, F., and Papadopoulos, G.: Global investigation of the tsunamigenic dislocation of the seismic fault, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14374, https://doi.org/10.5194/egusphere-egu24-14374, 2024.

08:40–08:50
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EGU24-8274
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ECS
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On-site presentation
Alice Abbate, José Manuel González Vida, Manuel J. Castro Díaz, Fabrizio Romano, Hafize Başak Bayraktar, Andrey Babeyko, and Stefano Lorito

The initial conditions for the numerical simulation of a seismically-induced tsunami are modeled by transferring the impulse produced by the co-seismic seafloor deformation to the sea-surface. In this process, the water column acts as a hydraulic filter for the smaller wavelengths. The numerical simulation of this process is computationally demanding; this makes  the application of this filter unaffordable in studies that require a large number of simulations, such as the long-term probabilistic tsunami hazard assessment (PTHA). Here, we optimize the numerical modeling of the filter in the case of an instantaneous vertical seafloor deformation, given by an improper Fourier expansion integral in the wave number domain presented by Nosov and Kolesov (PAGEOPH, 2011); the contribution of elementary seafloor displacements can then be linearly combine to obtain a static tsunami initial condition. We first explore the convergence of the integral in one dimension, to identify the range of wavenumbers significantly contributing to the integral. We find that its support can be limited to , being H the sea-depth. We then compare several quadrature formulae, selecting the optimal one in terms of accuracy and efficiency. We grid the domain into cells of equal size and constant depth, and verify that the nonlinear effects are negligible when we recombine them to obtain the initial sea level displacement. In two dimensions, the integral is solved with the optimal quadrature and the results tested on the tsunamigenic Kuril doublet sequence - a megathrust and an outer-rise - occurred in the Central Kuril Islands in late 2006 to early 2007. We also consider the horizontal co-seismic deformation projected on a slope and a simple model of the inelastic deformation of the wedge, on a realistic bathymetry. The approach proposed results accurate and fast enough to be relevant for practical applications, taking a few seconds for solving a single cell, depending on the local depth, and ~3min to recombine ~91k elementary initial conditions. We finally build a database of elementary initial conditions, as a function of the local sea depth, which can be linearly combined to obtain a discretization of any sea floor displacement globally.

How to cite: Abbate, A., González Vida, J. M., Castro Díaz, M. J., Romano, F., Bayraktar, H. B., Babeyko, A., and Lorito, S.: Modeling optimal initial conditions for propagation of seismotectonic tsunamis: a database of smoothed unit sources based on an efficient and accurate numerical integration, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8274, https://doi.org/10.5194/egusphere-egu24-8274, 2024.

08:50–09:00
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EGU24-5650
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On-site presentation
Finn Løvholt, Erlend Briseid Storrøsten, Sylfest Glimsdal, Ida Norderhaug Drøsdal, Steven J. Gibbons, Valentina Magni, Fabrizio Romano, Stefano Lorito, Manuela Volpe, and Beatriz Brizuela

Tsunami maximum inundation heights (MIH) are normally estimated by modelling the hydrodynamics of the overland flow over a limited area using high resolution long wave models. However, in situations where there one need to simulate inundation over large areas, we demand methods that are less resource intensive. The method of amplification factors represents one such simplified and resource efficient method. It is based on precomputed factors using linear shallow water models modelled over bathymetric transects to estimate the ratio of the offshore maximum surface elevation to that at the shoreline. It has been shown previously that we can get a relatively good estimate of the median value of the MIH at given coastline location using amplification factors. Yet, as this method is associated with considerably higher epistemic uncertainty than e.g. solving the nonlinear shallow water equations (due to the additional simplifications), there is need to include a measure of its uncertainty and bias. The main sources of uncertainty include among others the misfit of the method (towards data or more accurate methods) and local spatial variability of the inundation. Here, we present results from recent advancements of the amplification factor method emphasising a much more elaborate uncertainty analysis than employed previously. To this end, we use a unique set of synthetic data from several hundreds of thousands of massive scale nonlinear shallow simulations as a benchmark for estimating uncertainty concerned the amplification factors. The simulation dataset comprises ensembles of about 50 000 scenarios each for six different sites and includes sensitivity studies related to the Manning friction. When analysing the entire ensembles, we have revised the previous mathematical model for the uncertainty treatment (Glimsdal et al., 2019, PAGEOPH) by normalising the ensemble scenario outputs with the median MIH from each simulation. We further measure the bias of the amplification factor method by measuring its offset towards median MIH output from the shallow water simulations. The model provides input to the probabilistic tsunami hazard (PTHA) map for Italy, and we present related results of the amplification factor uncertainty analysis here. We will also discuss further and advocate the use of the method, both for long term hazard (PTHA) and for rapid post assessment following an event, e.g. through the ARISTOTLE framework. 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/). Computational resources were made available through PRACE grant number 2020225386, TsuHazAP.

How to cite: Løvholt, F., Briseid Storrøsten, E., Glimsdal, S., Norderhaug Drøsdal, I., Gibbons, S. J., Magni, V., Romano, F., Lorito, S., Volpe, M., and Brizuela, B.: Uncertainty based amplification factors benchmarked by large ensembles of inundation simulations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5650, https://doi.org/10.5194/egusphere-egu24-5650, 2024.

09:00–09:10
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EGU24-13955
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ECS
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On-site presentation
Raquel Felix, Masashi Watanabe, Andrea Verolino, Elaine Tan, Jun Yu Puah, and Adam Switzer

Following the 2022 Hunga Tonga - Hunga Ha'apai tsunami, there is a renewed interest in assessing tsunami hazards related to tsunamis triggered by landslides, volcanic eruptions, and atmospheric disturbances. This increased interest suggests an expanding cohort of researchers delving into the assessment of tsunami hazards through numerical modelling. However, mastering a numerical model involving tasks such as input file preparation, simulation execution, and output data generation poses a challenge for inexperienced users. The learning process often demands a substantial time investment, potentially causing workflow delays that may prevent researchers from promptly initiating result analysis. To address this challenge, we introduce standalone applications designed to optimize the efficiency of both tsunami model preparation and post-processing stages. We present two MATLAB-based user-friendly applications designed to efficiently generate input files and output tsunami hazard maps. The applications were designed to align with the required input and expected output files of the Fully Nonlinear Boussinesq Wave (FUNWAVE) model. FUNWAVE is a well-established open-source model that has been extensively validated through analytical solutions and experimental investigations. It also offers options to set up initial conditions, such as landslides and meteotsunamis. To facilitate its useability, the applications incorporate tool tips and context menus that provide a comprehensive guide for users. Within the input-generator application, visual warnings pre-empt potential errors in tsunami simulations. Meanwhile, the output map generator application not only facilitates the creation of maps, but also offers users the convenience of converting these maps into raster files,  animations, KML, or shapefiles. This versatility ensures compatibility with various programming and Geographic Information System (GIS) platforms. We tested the functionality of the applications using the benchmark examples from the FUNWAVE model. Through the development of these applications, we aim to advance tsunami modelling research by enhancing technological accessibility, hence reducing the complexity, especially for individuals new to tsunami modelling.

 

How to cite: Felix, R., Watanabe, M., Verolino, A., Tan, E., Puah, J. Y., and Switzer, A.: Advancing User-Friendly Tsunami Hazard Mapping:  MATLAB-based Applications for FUNWAVE modelling, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13955, https://doi.org/10.5194/egusphere-egu24-13955, 2024.

Landslide and volcano generation
09:10–09:20
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EGU24-3383
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ECS
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On-site presentation
Maxwell M. W. Silver, Alexis Marboeuf, Anne Mangeney, Anne Le Friant, Enrique D. Fernandez Nieto, Amaury Belieres-Frendo, Alexis Bougouin, Olivier Roche, Raphael Paris, and Annabelle Moatty

     Granular avalanches that enter a body of water present a hazard to coastal communities via their ability to generate tsunami waves. By improving the accuracy of model estimates of tsunami severity and quantifying the error of said models, we can improve the accuracy of tsunami hazard assessments. Sensitivity analyses were performed of the hybrid finite-difference finite-element model HySEA to changes in the number of vertical layers used to discretize the water column (from a single layer up to 5 layers), non-hydrostatic vs hydrostatic fluid pressures, different friction rheological laws (Pouliquen and μ(I)), and various friction coefficients. Flume experiments with matching conditions were used to benchmark simulations. An improved fit between simulation and experiment wave heights and wave frequencies, as well as improved model stability was found with 3 to 5 vertical water discretization layers compared to using a single water layer. We also demonstrate an improved fit between simulation and experiment wave heights, speeds, and form with non-hydrostatic versus hydrostatic conditions, although most simulations performed here did not accurately estimate wave speeds. Only minor changes in fit were observed between the Pouliquen and μ(I) friction laws. We demonstrate that multilayer HySEA can reliably estimate tsunami wave heights with a reasonable certainty (< 38% error) without any fitting across different granular mass volumes, grain sizes, and slopes of flow and can reach errors < 2% with only limited fitting. Furthermore, we detail how to improve model fit using additional rheological information (e.g., grain size, slope, volume of mass) and friction coefficients.

How to cite: Silver, M. M. W., Marboeuf, A., Mangeney, A., Le Friant, A., Fernandez Nieto, E. D., Belieres-Frendo, A., Bougouin, A., Roche, O., Paris, R., and Moatty, A.: Multilayer HySEA granular flow and tsunami model improves results over single layer models: sensitivity analysis, benchmarking against flume experiments, and implications for field scale models., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3383, https://doi.org/10.5194/egusphere-egu24-3383, 2024.

09:20–09:30
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EGU24-11569
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ECS
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On-site presentation
Jane Earland, James Scourse, Tobias Ehmen, and Sev Kender

The Shetland Islands (UK) are a seminal location for investigating palaeo-tsunami deposits. Onshore evidence suggests three tsunamis have occurred during the Holocene: the Storegga tsunami ca. 8175 cal yr BP, the Garth tsunami ca. 5500 cal yr BP and the Dury Voe tsunami ca. 1500 cal yr BP. However, to date no research has been published on the impact of tsunami on the subtidal shelf where a large amount of North Sea hydrocarbon infrastructure is located. During the SEACHANGE research cruise DY150 (2022), cores were recovered offshore east Shetland from the Fetlar Basin. The cores contained distinct sand and shell lenses within a Holocene mud sequence, indicating increases in bed shear stress. We test the hypothesis that these lenses represent the subtidal expression of North Sea tsunami. Radiocarbon dates bracketing the sand lenses overlap with the published dates for the Storegga tsunami, suggesting these sand lenses result from processes related to the Storegga tsunami. Dates within the deposit are older than the Storegga tsunami, indicating reworking and deposition of older sediments at the core site by the tsunami. Particle size analysis, ITRAX and MSCL data evidence increases in grain size, a reduction in sorting capacity, increased shell concentrations and peaks in associated elements (log(Ca/Fe), log(Ca/Ti) and Sr) and magnetic susceptibility. These attributes are typical of both palaeo and modern offshore tsunami deposits. No evidence was found within the cores for any later Holocene tsunami, due to either bioturbation, active currents, or lack of initial deposit. The data indicate that sediments in the Fetlar Basin were disturbed by the Storegga tsunami to palaeo-water depths of at least 88 m. This highlights the need to assess the potential impact of any future tsunami on existing or proposed hydrocarbon infrastructure.

How to cite: Earland, J., Scourse, J., Ehmen, T., and Kender, S.: Identification of the Storegga Tsunami offshore Shetland: implications for seabed infrastructure hazard risk assessment, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11569, https://doi.org/10.5194/egusphere-egu24-11569, 2024.

09:30–09:40
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EGU24-20633
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On-site presentation
Sergio Padilla Álvarez, Iñigo Aniel Quiroga, Mauricio Gonzalez, Rachid Omira, Jihwan Kim, and Maria Ana Baptista

The atmospheric tsunami resulting from the eruption of the Tonga volcano on January 15, 2022 (Tonga22) marked an unprecedented occurrence, encompassing a Volcano-Meteorological Tsunami (VMT) with global ramifications. This study examines the comprehensive effects of Tonga22 on moored vessels, employing a spectral and hydrodynamic analytical framework. The aftermath of the event, including edge waves, resonance phenomena, and wave amplification in specific regions such as La Pampilla port in Peru, revealed substantial maritime challenges. Notably, a vessel in La Pampilla reported the rupture of mooring ropes, a remarkable incident occurring 10,000 kilometers away from the Tonga volcano, manifesting 15 hours post-eruption and resulting in the spillage of over 11,000 barrels of crude oil.

Our research aims to contribute to a nuanced understanding of the Tonga22 event by employing advanced spectral and hydrodynamic analyses. The primary focus lies in assessing its impact on mooring loads within the complex marine port environment. We postulate that atmospheric acoustic waves, a consequence of the volcanic eruption, pose hydrodynamic threats to vessels in port areas, potentially leading to mooring breakage.

Utilizing the Boussinesq model, validated at the local scale in Callao Bay, we establish a foundation for our mooring system model. This model, applied to a vessel analogous to the one docked at La Pampilla Port, aims to discern the nuanced influence of VMT on overstressing and mooring breakage during the Tonga22 event.

Our simulation results underscore the pivotal role of VMT in the displacement and loss of positioning of vessels. Moreover, atmospheric waves are revealed to significantly elevate mooring stresses, with a particular emphasis on the starboard quarter moorings in this specific case.

This research sheds light on a critical realization—the Tonga22 event highlights the inadequacies of existing tsunami early warning systems (TWC) in detecting and managing tsunamis induced by acoustic waves originating from volcanic sources. These findings contribute to the ongoing discourse on maritime safety and hazard preparedness.

How to cite: Padilla Álvarez, S., Quiroga, I. A., Gonzalez, M., Omira, R., Kim, J., and Baptista, M. A.: The Impact of Volcano-Generated Tsunamis on the Safety of Moored Vessels: The 2022 Tonga Incident., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20633, https://doi.org/10.5194/egusphere-egu24-20633, 2024.

09:40–09:50
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EGU24-14400
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ECS
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Virtual presentation
How does Iya Volcano threaten coastal population in Sawu Sea, Indonesia?
(withdrawn)
Saaduddin Saaduddin, Sakka Sakka, Amiruddin Amiruddin, and Muhammad Alimuddin Hamzah
09:50–10:00
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EGU24-19260
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ECS
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On-site presentation
Matteo Trolese, Matteo Cerminara, Tomaso Esposti Ongaro, Mattia de' Michieli Vitturi, and Alessandro Tadini

Understanding the generation of tsunamis from landslides at volcanic islands is crucial due to their infrequent, yet potentially catastrophic, impact on coastal communities. We present a sensitivity analysis of the effects of different rheological and geometrical landslide parameters on the generation and propagation of tsunamis in the near field. In particular, we employed the MultiLayer-HySEA model to simulate tsunamis generated by landslides occurring along the northwestern flank of the Stromboli volcano, specifically in the area known as Sciara del Fuoco, which is considered most prone to instability. This shallow-water model implements a two-way coupling between a granular material layer representing the landslide and 3 fluid layers representing the water. The parameters investigated include the initial position, density, volume, and shape of the landslide, as well as its friction angles and water-landslide friction coefficients. We varied each landslide parameter to examine its effect on the tsunami wave height and energy at specific locations. We found that the principal parameters of the synthetic waveforms and the landslide volumes are logarithmically correlated when considering subaerial landslides, while they correlated linearly when considering submarine landslides. We than explored the effect of the other source parameters on such analytical relationships. Based on the variability observed in waveform characteristics, we suggest a ranking of importance for the source characteristics that contribute significantly to the uncertainty/variability of the model output. Our study aligns with previous predictions at Stromboli and offers a valuable tool for reconstructing the source parameters of tsunamis based on proximal sea-level measurements, enabling rapid forecasting of subsequent impacts around the volcanic island.

How to cite: Trolese, M., Cerminara, M., Esposti Ongaro, T., de' Michieli Vitturi, M., and Tadini, A.: Modeling tsunami generation and propagation: Insights from sensitivity analysis of landslide parameters at Stromboli, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19260, https://doi.org/10.5194/egusphere-egu24-19260, 2024.

10:00–10:10
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EGU24-9919
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ECS
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On-site presentation
Pin-Tzu Su, Ira Didenkulova, and Atle Jensen

We study experimentally tsunami-induced transport of micro-plastic. The micro-plastic is modelled by spheres of different densities, some of which are lying on the bottom slope, while others are floating. The bottom slope is covered with the sand, which allows us to study micro-plastic interaction with sand of different sizes. The spheres are initially placed at different locations along the slope with respect to the wave breaking point. Experiments are performed in a small wave flume of the Hydrodynamics laboratory of the University of Oslo. It is 3 m long and 0.1 m wide. The water depth is 5 cm. The tsunami is modelled by breaking solitary-like waves with amplitude, normalized by the water depth 𝑎/ = 0.47. The waves propagate towards a sandy beach breaking on the slope, impact the floating and/or lying on the bottom spheres, and the spheres get displaced. Here we study the displacement of the spheres from their initial position with respect to their characteristics (densities), initial positions with respect to the wave breaking point, the number of consecutive waves and parameters of the sand.

How to cite: Su, P.-T., Didenkulova, I., and Jensen, A.: Experimental study of tsunami-driven transport of micro-plastic on sedimentary slope, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9919, https://doi.org/10.5194/egusphere-egu24-9919, 2024.

Coffee break
Chairpersons: Jadranka Sepic, Rachid Omira
Meteotsunami
10:45–10:55
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EGU24-4024
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On-site presentation
Ivica Vilibić, Gozde Guney Dogan, Iva Dominović Novković, Xun Huan, Gabriel Jordà, Petra Pranić, Iva Tojčić, Joan Villalonga, Ahmet Cevdet Yalciner, and Petra Zemunik Selak

Meteorological tsunamis - atmospheric ocean waves in the tsunami frequency band - and generally nonseismic sea level oscillations on tsunami timescales attracted a lot of attention in the recent decade due to the global availability of high-resolution sea level and ancillary measurements and advancement of both atmospheric and ocean models. This became even accentuated after the century-level event of the Hunga Tonga-Hunga Ha’apai explosive volcano eruption on 15 January 2022, which created global acoustic-gravity waves in the atmosphere and meteotsunamis in the ocean. In that spirit, the Global Science of Meteorological Tsunamis (GLOMETS) 4-year project has been proposed for funding to the Croatian Science Foundation and launched on New Year’s Eve of 2023 to tackle the following research topics: (1) global meteotsunami hazards from explosive volcanic eruptions and asteroid impacts, (2) meteotsunami hazards at the sub-kilometre scale from both weather- and explosive volcano-induced events, (3) reproducibility of meteotsunami hazard by climate models, for their eventual assessment in the future climate, (4) eventual optimization and improvement of the meteotsunami monitoring, and (5) developing stochastic techniques for meteotsunami uncertainty quantification. To achieve these objectives, state-of-the-art tools will be used, like (1) global quality-checked high-frequency sea level analyses, (2) coupled atmosphere-ocean global and (sub-)kilometre models, (3) climate simulations, reanalyses, and products, and (4) uncertainty quantification techniques and optimal experimental design methods. This presentation will overview state-of-the-art in the quoted topics, with planned work-to-do and research activities, hopefully to initiate fruitful discussions and new research directions and to establish new collaborations around the project.

How to cite: Vilibić, I., Dogan, G. G., Dominović Novković, I., Huan, X., Jordà, G., Pranić, P., Tojčić, I., Villalonga, J., Yalciner, A. C., and Zemunik Selak, P.: Global Science of Meteorological Tsunamis: From Planetary to Mesoscale Processes (GLOMETS), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4024, https://doi.org/10.5194/egusphere-egu24-4024, 2024.

10:55–11:05
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EGU24-10023
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On-site presentation
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Jihwan Kim and Rachid Omira

Originating from atmospheric pressure disturbances, meteotsunamis undergo amplification processes through resonances such as Proudman, Greenspan, and bay/harbor. While Greenspan resonance is often overlooked due to its moderately amplified waves, its recurrent nature makes it a crucial factor in meteotsunami magnification. We briefly review prior analytic studies using linearized shallow water equations on a constant slope with the propagation of Gaussian atmospheric pressure, providing insights into the background of our research. Additionally, we present two recent meteotsunami cases, the June 2009 event in the West coast of Korea, and the October 2018 event in the coast of Portugal, to emphasize the pivotal role of Greenspan resonance in enhancing meteotsunamis. Our study includes  data analysis, numerical simulations, and comparisons with analytical solutions. This work was supported by the project FAST (Development of new forecast skills for meteotsunamis on the Iberian shelf – ref. PTDC/CTA-MET/32004/2017), and by I.P./MCTES through national funds (PIDDAC) – UIDB/50019/2020-IDL, both funded by the Fundação para a Ciência e a Tecnologia (FCT), Portugal.

 

Keywords: meteotsunami, Greenspan resonance, numerical models, analytical solutions 

 

References

 

Greenspan, H. P. “The Generation of Edge Waves by Moving Pressure Distributions.” Journal of Fluid Mechanics, vol. 1, no. 06, 1956, p. 574, https://doi.org/10.1017/S002211205600038X.

Kim, Jihwan, et al. “On the Greenspan Resurgence of Meteotsunamis in the Yellow Sea—Insights from the Newly Discovered 11–12 June 2009 Event.” Natural Hazards, vol. 114, no. 2, 2022, pp. 1323–40, https://doi.org/10.1007/s11069-022-05427-3.

Kim, Jihwan, and Rachid Omira. “Combined Surge-Meteotsunami Dynamics: a numerical model for Hurricane Leslie on the coast of Portugal.” (submitted)

Niu, Xiaojing. “Conditions for the Occurrence of Notable Edge Waves Due to Atmospheric Disturbances.” Applied Ocean Research, vol. 101, 2020, p. 102255, https://doi.org/10.1016/j.apor.2020.102255.

Seo, Seung-Nam, and Philip L. F. Liu. “Edge Waves Generated by Atmospheric Pressure Disturbances Moving along a Shoreline on a Sloping Beach.” Coastal Engineering, vol. 85, 2014, pp. 43–59, https://doi.org/10.1016/j.coastaleng.2013.12.002.

Ursell, Fritz. “Edge Waves on a Sloping Beach.” Proceedings of the Royal Society of London. Series A. Mathematical and Physical Sciences, vol. 214, no. 1116, Aug. 1952, pp. 79–97, https://doi.org/10.1098/rspa.1952.0152.

How to cite: Kim, J. and Omira, R.: Resurgence of Greenspan Resonance in Meteotsunami Dynamics, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10023, https://doi.org/10.5194/egusphere-egu24-10023, 2024.

11:05–11:15
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EGU24-8317
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ECS
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On-site presentation
Alex Gonzalez del Pino, Jorge Macías Sánchez, Manuel Castro Díaz, and Cléa Lumina Denamiel

Atmospherically-driven tsunamis or meteotsunamis are generated by atmospheric disturbances with steep gradients of pressure and/or wind. In recent years, meteotsunamis have received more attention from the tsunami modelling community. Although their destructive potential might be less severe than for earthquake or landslide triggered tsunamis, their frequency is much higher. The two main processes driving the most extreme meteotsunami events are the offshore amplification of the ocean long-waves due to Proudman or Greenspan resonances (i.e., when the atmospheric disturbance travels at the same speed than the long-waves) and, nearshore, the amplification factor of the shelfs, bays or inlets (i.e., resonance frequency associated to the nearshore geometry). As meteotsunamis have a high-dependence on the nearshore geometric characteristics, they often occur at known hotspot locations such as along the coastlines of Croatia, the Balearic Islands, Sicily, Malta, the Nagasaki Bay or the Baltic Sea. One of the most devastating meteotsunami events took place in Menorca (Balearic Islands) in 2006, where tsunami-like oscillations caused an economic loss of several tens millions of euros.

The EDANYA group from the university of Málaga is widely known for its GPU-accelerated tsunami simulation codes, such as Tsunami-HySEA (earthquake source) or Landslide-HySEA (landslide source). Here, we present our brand-new code for simulating meteotsunamis following the same philosophy as the previous codes. Meteotsunami-HySEA incorporates the atmospheric forcing together with additional terms such as Coriolis and the wind drag. The PDE system is written in spherical coordinates and implemented in CUDA. An additional feature related to preserving a linear version of the quasi-geostrophic equilibrium is added to the numerical scheme in order to preserve the structure of geostrophic flows, as large scale geophysical flow are often perturbations of this steady state.

To demonstrate the Meteotsunami-HySEA reliability, we first applied the code to some carefully-crafted benchmark tests, where Proudman resonance is exhibited and precisely capture, enabling accurate measures of the amplification gain due to the coupling of the propagation velocities. Then we followed the NTHMP’s guidelines for simulating a pilot study in the region of the Gulf of Mexico with a real topobathymetry. Further work will be focused on testing real scenarios, incorporating real atmospheric data and bathymetry for reliable forecast.

Acknowledgments: This contribution was supported by the EU project “A Digital Twin for Geophysical Extremes” (DT-GEO) (No: 101058129) and by the Center of Excellence for Exascale in Solid Earth (ChEESE-2P) funded by the European High Performance Computing Joint Undertaking (JU) under grant agreement No 101093038.

 

How to cite: Gonzalez del Pino, A., Macías Sánchez, J., Castro Díaz, M., and Lumina Denamiel, C.: Meteotsunami-HySEA: A GPU accelerated code for simulating atmospherically-driven tsunamis on real bathymetries. Benchmark tests., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8317, https://doi.org/10.5194/egusphere-egu24-8317, 2024.

11:15–11:25
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EGU24-4947
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ECS
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On-site presentation
Andrea Verolino, Masashi Watanabe, Raquel Felix, Christopher Conway, and Adam Switzer

Volcanic meteo-tsunamis are rare and potentially devastating natural phenomena. In physical terms, they are comparable to meteorological tsunamis, where a relatively high atmospheric pressure disturbance leads to the formation of tsunami-like waves. A significant recorded example of volcanic meteo-tsunami is the one produced by the Hunga Tonga – Hunga Ha’apai (HT-HH) eruption in January 2022. Volcanic meteo-tsunamis have the peculiarity to generate waves that propagate beyond landmasses, due to the interaction between the air pressure wave and water, such as those observed in the Gulf of Mexico following the HT-HH eruption; they also move much faster than tsunamis generated by other mechanisms. These features increase the hazard potential of a given volcano, and expose countries that are generally protected by landmasses to tsunami waves. The South China Sea (SCS), for example, is relatively protected to the west and south from Indonesia, to the north from Taiwan, and to the east from the Philippines. However, volcanic meteo-tsunamis may be generated from a volcanic eruption from regions such as southern Japan, and affect the SCS and its surrounding coastlines. Southeast Asia (SEA) presents several records in the literature of volcano-induced tsunami events, including as source mechanisms landslides, Pyroclastic Density Currents, lava dome collapse, and underwater explosions. There are also two instances from Taal, Philippines, and Krakatau, Indonesia, where airwaves have been inferred as a possible tsunami source mechanism, with waves reported also across the Indian and Pacific Oceans, in the latter case. Here, we selected four potential candidates for a submarine or near-surface volcanic eruption, both outside (Kikai and Fukutoku-Oka-no-Ba, Japan) and inside the SCS (Banua Wuhu, Indonesia, and KW-23612, Vietnam), capable of generating volcanic meteo-tsunamis, with the aim to have a first-time assessment from such natural phenomena on SEA countries surrounding the SCS. At this stage, we focused on the general wave propagation in the region, based on the different source locations, and offshore wave maximum height (observed at 16 synthetic tide gauges placed around the SCS, at the 50-m water depth contour, to avoid shallow water complexities near coastlines that cannot be resolved through public bathymetry datasets). We modelled three potential scenarios for each selected seamount, with 100%, 66% and 33% of the HT-HH eruption intensity, respectively. This choice allows us to investigate a broad range of explosion intensities expressed through a perturbance of the atmospheric pressure field, following previous works. Initial results from this first assessment show that bathymetry has a strong control on tsunami wave propagation, being rather fast in deep waters (e.g. northern South China Sea) and much slower in shallow waters (e.g. Sunda Shelf). The higher waves are recorded at offshore stations 11 (Hong Kong) and 16 (West Philippines), with ~10 and 20 cm respectively, in both cases generated from within the SCS from seamount KW-23612. Work is ongoing to integrate higher resolution grids near these locations closer to coastlines, and also to assess the hazard at other areas on the Sunda Shelf where water depth is larger in proximity of coastlines (e.g. Singapore Strait).

How to cite: Verolino, A., Watanabe, M., Felix, R., Conway, C., and Switzer, A.: Volcanic meteo-tsunamis in Southeast Asia: A first-time assessment, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4947, https://doi.org/10.5194/egusphere-egu24-4947, 2024.

11:25–11:35
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EGU24-16257
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ECS
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On-site presentation
Joan Villalonga, Patrick Marsaleix, Damià Gomis, and Gabriel Jordà

Meteotsunamis are sea waves with frequencies ranging from 2 minutes to 2 hours (the same frequency band than seismically generated tsunamis) that are generated by high frequency atmospheric perturbations. Extreme meteotsunamis can cause high frequency sea level oscillations of a few meters at the coast which are dangerous for coastal populations. The meteotsunami generation involves both the amplification of the inverse barometer response by Proudman resonance and also harbour resonance. For this reason, meteotsunami generation is highly dependent on the bathymetric and topographic characteristics of the basins, some of them being more suitable than others for the meteotsunamis occurrence. This is the case of the Ciutadella harbour, in the Balearic Islands (Western Mediterranean), where several meteotsunamis of >1 meter of amplitude (difference in the sea level elevation between consecutive maximum and minimum) occur every year. This hotspot for meteotsunamis has been studied for four decades and several forecasting systems have been implemented in the region. However, the accuracy of those systems, in particular in terms of predicting the amplitude at the coast, is still limited.

In a previous work (Villalonga et al., 2022), a new set of ultra dense atmospheric observations allowed a detailed characterization of the atmospheric disturbances generating meteotsunamis.  We found that these disturbances are highly heterogeneous both in time and space, and that heterogeneity is very difficult to reproduce with atmospheric models. With the aim of understanding what is the impact of that heterogeneity in the final meteotsunami amplitude, we have conducted several experiments with the SYMPHONIE model (Estournel et al., 2021). The model has been configured to cover the whole Balearic Islands with a variable spatial resolution reaching up to 5 meters inside Ciutadella harbour. It has been forced with different kinds of atmospheric disturbances, namely analytical functions and observed time series with tuneable propagation velocities over the model’s domain. Random noise with different spectral and spatial characteristics has also been added.

The model has been able to accurately reproduce the amplitude and spectra of real meteotsunamis events when forced with the observed atmospheric pressure time series. We have also tested the sensitivity of the model outputs to different model configurations by changing the friction parameters and comparing 2D to 3D simulations. The results suggest that 3D simulations provide a more realistic energy dissipation by friction, particularly in the higher frequencies. Finally, the experiments forcing the model with random spatially correlated noise have allowed understanding the impact of atmospheric spatial heterogeneities. In particular, the results show that the size of the random structures is a key parameter that determines the amplification of sea level oscillations. Namely,  the structures with a spatial scale of 10-30 km generate more signal amplification than larger structures.

All in all, these simulations have provided new results that will allow a better understanding of the generation of meteotsunamis in the Balearic Islands and the limits of their predictability.

 

How to cite: Villalonga, J., Marsaleix, P., Gomis, D., and Jordà, G.: Influence of spatially correlated noise in the generation of meteotsunamis in Ciutadella, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16257, https://doi.org/10.5194/egusphere-egu24-16257, 2024.

Risk assessment
11:35–11:45
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EGU24-6676
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On-site presentation
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Mathilde Sørensen, Jörn Behrens, Fatemeh Jalayer, Finn Løvholt, Stefano Lorito, Jacopo Selva, Mario Salgado, and Irina Rafliana

Probabilistic tsunami hazard and risk assessment methods (abbreviated PTHA and PTRA, respectively) have evolved quickly over the past 10 to 15 years. Given this rapidly evolving landscape, there is a need to establish best practices for PTHA and PTRA to improve reliability, comparability and reproducibility of studies applying such methods. The recently concluded Cost Action CA18109 AGITHAR (2019-2023) intended to improve the scientific foundation for PTHA and PTRA. To materialize the networking activities into guidelines and best practices, more than 50 tsunami scientists have joined forces to develop a so-called cookbook providing recommendations and workflows for both PTHA and PTRA. The cookbook will give an overview of existing methods, unify the descriptions of named workflows, make best practices examples available to a wider community, and provide background information to various stakeholder groups. We employ the analogy of a cookbook, because successful PTHA/PTRA workflows can be described by essential building blocks (ingredients) combined in specific ways (recipes) to serve the purpose of the analysis of actual application fields. In that regard, we first introduce the main ingredients in seven chapters describing e.g.  source models, tsunami models, vulnerability, exposure, as well as risk communication, and then present a series of recipes (25 in total) providing examples of how the ingredients can be combined in a workflow leading to a meaningful PTHA or PTRA. The cookbook can be used and read in different ways. On the one hand, and again in analogy to a usual cookbook, readers may browse through recipes, and access the ingredients chapters following the corresponding list of ingredients. The recipes all follow a similar organizational structure, so they can be accessed easily. On the other hand, the book can be read consecutively, starting with the study of ingredients, following the general workflow of PTHA and PTRA. By this, scholars will learn in a structured way how to build corresponding hazard and risk assessments. Finally, for the more experienced readers, the book may serve as a reference to the current state-of-the-art in this multidisciplinary research area. In this presentation, we will introduce the key ingredients described in the cookbook, as well as selected recipes. We will then summarize the main recommendations for future PTHA/PTRA studies, as provided in the book. The book is expected to be published in Autumn 2024.

How to cite: Sørensen, M., Behrens, J., Jalayer, F., Løvholt, F., Lorito, S., Selva, J., Salgado, M., and Rafliana, I.: A “cookbook” for probabilistic tsunami hazard and risk assessment, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6676, https://doi.org/10.5194/egusphere-egu24-6676, 2024.

11:45–11:55
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EGU24-14623
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ECS
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On-site presentation
Aisling OKane, Bill Fry, Ciaran King, and Andy Nicol

Tsunamis have the potential to cause catastrophic damage to coastal communities. In Aotearoa New Zealand, where 3.5 million people reside within 5 km of the coast, the threat of experiencing a tsunami within their lifetime is a stark reality. Although these events are infrequent with recurrence intervals of hundreds of years, New Zealand faces an elevated risk due to its location within the tectonically active Pacific, where over 80% of the world's tsunamis occur. The region has experienced over seventy tsunamis in the past two-hundred years, with five of these causing devastating impacts to coastal communities and leaving an indelible mark on the landscape due to wave amplitudes surpassing 5 m at the coast. Recent studies, while crucial, have predominantly focused on assessing the tsunami hazard from local sources, recognising their immediate threat. However, to comprehensively assess the overall tsunami hazard to Aotearoa, we must fully account for the regional and distant sources also. This is informed by the harsh reality that some events, such as the 1877 Northern Chile and the 2004 Indian Ocean tsunamis, have inflicted staggering death tolls in distant locations, emphasising their paramount significance in our hazard assessment efforts.

 

In this talk, I will present our innovative hybrid tsunami hazard model designed for Aotearoa New Zealand. We use observations of accumulated earthquake slip on active faults in the Pacific alongside established earthquake laws to ensure that we capture a wide variability of seismogenic tsunami sources to complement the limited historical and instrumental records. Due to recent computational advancements, we can now calculate the seafloor deformation generated from hundreds of synthetic tsunami sources across twenty subduction zones and simulate the tsunami wave propagation to the coast of New Zealand. For each source, we can estimate the wave amplitudes and timing of potential tsunamis and use these metrics to calculate the hazard that these regional and distant sources pose over common return periods. Each part of the model, from the source characteristics to the wave propagation has been independently tested and benchmarked with recorded events to ensure the rigor of the research.

 

Our hybrid approach of blending observation-driven, physics-based, and probabilistic methodologies offers a comprehensive approach to assessing the full range of earthquakes that could cause a tsunami at the shores of New Zealand. Our work, alongside the recent research carried out on the local tsunami sources will accelerate Aotearoa New Zealand’s natural hazard resilience from Pacific earthquake-generated tsunami sources and will pave the way for other tsunami mechanisms to be incorporated into the model analysis, an urgent need given that these hazardous events do not occur independently. We look forward to having the opportunity to share our Aotearoa New Zealand tsunami hazard model with the wider tsunami community in Europe and discuss pathways that our combined research could follow to help build safer and more resilient coastal communities, globally. 

How to cite: OKane, A., Fry, B., King, C., and Nicol, A.: Building resilient coastlines: A comprehensive physics-based tsunami hazard model for Aotearoa New Zealand, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14623, https://doi.org/10.5194/egusphere-egu24-14623, 2024.

11:55–12:05
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EGU24-17621
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On-site presentation
Fatemeh Jalayer, Hossein Ebrahimian, Patricio Catalan, Natalia Zamora, and Saeed Soltani

Scenario-based tsunami risk assessment provides valuable insights into the socio-economic consequences of a specific scenario. Although it is focused on a specific scenario or a range of scenarios, this type of analysis can still encompass uncertainty characterisation. 

Hazard: Focusing on Coquimbo Bay, which was affected by the 2015 Ilapel tsunami, we demonstrate how the uncertainties are quantified and propagated from the tsunami source level all the way towards risk metrics such as the economic losses.  We have chosen a range of near-field tsunami scenarios with moment magnitude between 8.6 <Mw <9.3 from a subduction interface zone on the Nazca–South American plate interface running parallel to the Chilean coastline. We have worked with a large set of stochastic scenarios generated compatible with the scaling laws, with variable slip distribution according to a prescribed correlation structure. We have estimated the seismicity rate through different sources: paleo seismic data, historical catalogue, and moment balancing and have combined the resulting probability distributions through a logic tree approach. The weights of the logic tree are assigned through a Bayesian model class selection procedure as related to the log-evidence calculated for each model. This will lead to scenario-based hazard curves with confidence intervals for different points of interest in the port city of Coquimbo.

Vulnerability: Based on the exposure model for Coquimbo, we have identified two different pre-dominant building categories in Coquimbo, namely the low-rise mixed (wood and masonry) building type and the high-rise residential buildings. For the first category, we have used empirical fragility curves for a similar building type in Dichato and damaged by the Chile 2010 and have characterised the epistemic uncertainty for these fragility curves. We have derived the vulnerability curves and their confidence band through convolution of the fragility curves and the consequence models. 

Risk: We demonstrate how hazard and vulnerability curves and their confidence intervals can be convolved to obtain loss curves for certain locations of interest and how this information can be processed to derive scenario-based risk maps for Coquimbo for different return periods. 

We conclude by demonstrating the importance of a thorough characterization of uncertainties and their propagation from the tsunami source towards the estimation of the economic losses. This provides important insights about the relative sensitivity of tsunami risk to different sources of uncertainty.

 

How to cite: Jalayer, F., Ebrahimian, H., Catalan, P., Zamora, N., and Soltani, S.: Scenario-based Probabilistic Tsunami Risk Analysis for Coquimbo Bay, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17621, https://doi.org/10.5194/egusphere-egu24-17621, 2024.

The January 1st, 2024, Noto earthquake and tsunami
12:05–12:25
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EGU24-14673
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solicited
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Highlight
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On-site presentation
Shunichi Koshimura, Bruno Adriano, Erick Mas, Shohei Nagata, and Yuriko Takeda

The digital twin is recognized as digital copies of the physical world's objects stored in digital(cyber) space and utilized to simulate the sequences and consequences of target phenomena. Users can fully view the target through real-time feedback by incorporating the physical world's data into the digital twin. Given the importance of the digital twin, the authors propose "Tsunami Digital Twin (TDT)" as a new paradigm in tsunami science and engineering to enhance tsunami disaster resilience.

The components of TDT are the transformation from "Data" to "Information" by integrating sensing, monitoring, and simulation; "Interpretation" of data and information; and "Inference" by using available data and information to draw conclusions and consequences and decide policies and responses for social resilience. Fusing these components is the key to gaining knowledge and insight for optimal solutions in the physical world.

In the session, the authors focus on two functionalities of TDT: Real-time tsunami modeling and forecast capability and Dynamic exposure estimation to verify through the 2024 Noto Peninsula Earthquake Tsunami Disaster.

The rapid tsunami hazard assessment by real-time tsunami modeling implied that severe impacts were expected around Noto Peninsula (Shika to Nanao), and the directivity of tsunami energy was also toward the Japan sea coasts, especially Joetsu city, Niigata Prefecture. We also found that the specific bathymetric features (continental shelf of Noto Peninsula) are responsible for high tsunamis in Suzu city.

The exposure analysis was performed using Mobile Spatial Statistics (the population estimates using mobile phone data) to elucidate population change after the earthquake by elevation (tsunami affected or not).

How to cite: Koshimura, S., Adriano, B., Mas, E., Nagata, S., and Takeda, Y.: Tsunami Digital Twin – Concept, Progress, and Application to the 2024 Noto Peninsula Earthquake Tsunami Disaster, Japan, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14673, https://doi.org/10.5194/egusphere-egu24-14673, 2024.

Lunch break
Chairperson: Mohammad Heidarzadeh
14:00–14:20
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EGU24-22502
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solicited
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Highlight
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On-site presentation
Yuichiro Tanioka and Yusuke Yamanaka

On January 1, 2024, a large earthquake (Mw7.6) occurred along the northern coast of the Noto Peninsula, Japan. Because the faults of the earthquakes were located beneath both land and sea, the large strong motion and tsunami were generated and caused severe disasters near the source area. More than 200 people were killed by the earthquake.

The earthquake occurred on the Eastern Margin of the Japan Sea where several great earthquakes and tsunamis occurred previously such as the 1993 Hokkaido Nansei-oki earthquake (Mw7.8), the 1983 Japan Sea earthquake (Mw7.7), and the 1964 Niigata earthquake (Mw7.6), The 2024 Noto earthquake also occurred on the same Eastern Margin of the Japan Sea where a large number of submarine active faults were identified by the undersea structure surveys and also the GNSS surveys indicted a convergence rate of approximately 1cm/year along the margin. 

The aftershock activity and the seismological analysis by the Japan Meteorological Agency (JMA) and the co-seismic deformation analysis using GNSS data by the Geospatial Information Authority of Japan (GSI) of the 2024 Noto earthquake showed that the fault length is about 150 km. Particularly, a northeast part of the fault was extended to the Japan Sea where the Noto peninsula was terminated. The co-seismic deformation due to the faulting generated a large tsunami observed at several tide gauges along the Japan Sea coast.

How to cite: Tanioka, Y. and Yamanaka, Y.: Characteristics of the 2024 Noto Earthquake and Tsunami occurred in the Eastern Margin of the Japan Sea, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-22502, https://doi.org/10.5194/egusphere-egu24-22502, 2024.

14:20–14:30
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EGU24-21337
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On-site presentation
Cédric Twardzik, Lucie Rolland, Edhah Munaibari, and Thomas Dylan Mikesell

Forecasting the impact of a tsunami on coastal areas requires accurate location of the source of the tsunami. This is particularly challenging because tsunamis often originate far from seismological and geodetic networks. However, tsunami waves often induce total electron content (TEC) perturbations in the ionosphere, which can be detected using Global Navigation Satellite Systems (GNSS). Tracking the source of these perturbations makes it possible to determine the tsunami source area. Previous studies have confirmed this approach. However, this is usually done by (1) using a "quasi-homogeneous" model to propagate the disturbances in the atmosphere and (2) arbitrarily fixing the height of the ionosphere. These approximations lead to relatively large uncertainties in the location of the tsunami source. Therefore, in this study we try to reduce these uncertainties by using a 1D model of the atmospheric structure and by including the search for the optimal height of the ionosp here in the inverse problem. To do this, we use a Bayesian approach to invert the onset times of the TEC disturbances. First, we test our method on synthetic data to determine the potential gain in accuracy between using a "quasi-homogeneous" and a 1D model of the atmosphere. We then apply our approach to study the 2010 M7.7 Mentawai tsunami earthquake and discuss the strength and limitations of the method as well as its usability for tsunami warning. We finally show preliminary results for the 2024 M7.5 Noto peninsula earthquake, and related tsunami offshore Japan.

How to cite: Twardzik, C., Rolland, L., Munaibari, E., and Mikesell, T. D.: Constraining the tsunami initiation area associated with the 2010 M7.7 Mentawai and 2024 M7.5 Noto peninsula earthquakes from first-arrival measurements on TEC data, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21337, https://doi.org/10.5194/egusphere-egu24-21337, 2024.

Technologies and methods for early warning
14:30–14:40
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EGU24-6824
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ECS
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On-site presentation
Amin Aghaee-Naeini, Bill Fry, and Jennifer D.Eccles

The Vanuatu Trench hosts tsunamigenic earthquakes exceeding magnitude 7. For these source locations, current tsunami early warning systems in Aotearoa - New Zealand are based on earthquake point-source parameters and as tsunamis propagate, initial forecasts are refined by DART (Deep-ocean Assessment and Reporting of Tsunamis) sea-level analysis. This study, which is part of the R-CET (The Rapid Characterization of Earthquakes and Tsunami) project led by GNS Science, aims to seismologically characterize the spatio-temporal behavior of the regional tsunamigenic ruptures in near real-time. This transition from basic point sources to 4-D rupture propagation could enhance the accuracy of initial tsunami threat maps and hazard response. A new array of broadband seismic stations, designated as the R-CET array, has been strategically deployed in New Zealand to support this analysis for events in the South Pacific.

In this proof-of-concept study, we applied a beamforming array seismological technique to analyze the R-CET array recordings from a recent tsunamigenic earthquake (Mw 7.7) in the Vanuatu region, the Loyalty Islands, on May 19, 2023. We use sliding window fk-analysis beamforming, which can simultaneously measure backazimuth and slowness. Incorporating the sliding window, in conjunction with the fk diagrams, helps to observe temporal azimuthal changes, which facilitates tracking the rupture length and direction over time. Preliminary results showed the azimuthal and temporal variation of the rupture is in alignment with post-processing estimates of the finite fault solution for this event reported by USGS. We test the utility of this analysis in tsunami forecasts by comparing threat maps generated from the beamforming source and initial response maps used in real-time response on the day. We further compare our results to actual measured coastal cancellation gauges (tide gauges) and DART observations. We show that this analysis has the potential to improve initial tsunami forecasts prior to the onset of tsunami waves at deep ocean tsunamimeters. We further present the technique as an enticing path to meet UN Ocean Decade tsunami warning goals within our framework of ensemble and time-dependent forecasting.

How to cite: Aghaee-Naeini, A., Fry, B., and D.Eccles, J.: Spatial-Temporal Rupture Characterization of Potential Tsunamigenic Earthquakes Using Beamforming: Faster and More Accurate Tsunami Early Warning, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6824, https://doi.org/10.5194/egusphere-egu24-6824, 2024.

14:40–14:50
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EGU24-3037
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ECS
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Highlight
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On-site presentation
Carlos Becerril, Pedro Vidal-Moreno, Anthony Sladen, Jean-Paul Ampuero, and Miguel Gonzalez-Herraez

Although Tsunami Early Warning Systems (TEWS) are in operation, they are yet to become the norm, mainly due to the high cost of installation and operation of offshore instrumentation with sufficient spatial coverage and spatial density of instruments. Tsunami observations are made mostly by coastal tide gauges, fixed moorings located offshore such as DART, or cabled observatories such as S-NET or NEPTUNE. While S-NET is capable of near-field warnings, many systems rely on seismic data, an effective TEWS should rely on direct measurements of the wave to avoid errors in the extrapolation of seismic information, and allow detection of tsunami from other sources (volcanic eruptions and submarine landslides).

To maximize evacuation time for coastal communities, tsunami warning systems should be based on sensors deployed as close as possible to the offshore source areas such as subduction earthquakes. With the advent of seafloor Distributed Acoustic Sensing (DAS), such deployments are becoming feasible at a relatively low cost and can deliver upon other key requirements for early-warning systems: Delivering real-time data from a dense array of strain sensors. DAS is capable of converting the already existing seafloor telecom fiber links into a dense linear array of strain sensors over spans of up to 100 km. With such attributes, DAS is becoming a sensor package to consider in the design of future TEWS, as a cost-effective means of deploying instrumentation directly at offshore locations such as active plate margins and subduction zones where the most destructive tsunamis are generated. Providing several measurements per tsunami wavelength, in real-time would allow faster forecasting of a tsunami.

Despite the aforementioned attributes, there are some aspects of DAS that need to be addressed towards integrating these sensors into future early-warning systems: 1) DAS measures 1D horizontal strain when vertical pressure is the usual means to detect tsunami, and 2) DAS usually has lower performance at long periods typical of a tsunami (a few 100s). In this work, we investigate both aspects. For the former, we present an analysis based on a 3-D full physics simulation which couple the dynamic rupture to the tsunami wave generation and propagation; upon which we estimate the expected strain observable on a submarine cable due to two effects induced by the hydrostatic pressure perturbations arising from tsunami waves: the Poisson’s effect of the submarine cable and the compliance effect of the seafloor. We also consider the effect of seafloor shear stresses induced by the horizontal fluid flow arising from tsunami waves. For the latter point, we review the low-frequency limit of DAS and present recently reported improvements in low-frequency sensitivity of a DAS system using linearly chirped pulses (cp-DAS); attained by suppressing the 1/f noise from the instrument. Tsunamis are expected to be observable with high signal-to-noise ratio, within a few minutes of the source onset, on seafloor cables located above or near the source area.

How to cite: Becerril, C., Vidal-Moreno, P., Sladen, A., Ampuero, J.-P., and Gonzalez-Herraez, M.: Towards Tsunami Early-Warning with Distributed Acoustic Sensing (DAS), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3037, https://doi.org/10.5194/egusphere-egu24-3037, 2024.

14:50–15:00
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EGU24-16261
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Highlight
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On-site presentation
Giuditta Marinaro, Salvatore D'Amico, Davide Embriaco, Alessandra Giuntini, Francesco Simeone, John O'Neill, Bruce Nicholson, Neil Watkiss, and Federica Restelli

Continuous seismic and environmental monitoring at remote seabed sites always faced a major challenge due to technical, logistical and financial effort. Commercial Telecommunication submarine cables continuously expand the coverage of ocean seafloor following society's needs to increase connectivity between distant countries and remote sites. Cables over thousands of kilometres long are equipped with in-line repeaters which compensate for optical losses due to  such long distances. 

A Science Monitoring And Reliable Telecommunications (SMART) Subsea Cables, designed by a Joint Task Force (JTF) across the International Telecommunication Union, World Meteorological Organization, the UNESCO Intergovernmental Oceanographic Commission,  may host, inside repeaters, scientific sensors for seismic, ocean and climate monitoring and disaster risk reduction in cases of tsunamis. 

The recent successful deployment at the Western Ionian Sea, one of EMSO (European Multidisciplinary Seafloor and water column Observatory) Regional Facilities, of the InSEA Wet Demo SMART Cable displays a world first demonstrating the feasibility of such installation using standard cable-laying techniques to show proof of concept. Commercial viability for these systems relies on the cable being laid as if the scientific element did not exist, thereby minimising additional deployment costs and reducing barriers to cooperation with cable laying companies. Güralp Systems Ltd and INGV deployed three seismometer-accelerometer pairs housed in inline repeaters along the 21km cable long. Each repeater also provides temperature and pressure devices which respectivley enable the real time monitoring of sea environment state and of sea surface level for tsunami detection.

This pioneering installation demonstrates the feasibility of smart cable initiative which may lead to global coverage of ocean seafloor with a network of scientific sensors enabling the  real time monitoring of seismicity and tsunami events at remote locations thanks to a collaboration between scientific and commercial parties.

How to cite: Marinaro, G., D'Amico, S., Embriaco, D., Giuntini, A., Simeone, F., O'Neill, J., Nicholson, B., Watkiss, N., and Restelli, F.: A 21 km SMART Cable for earthquakes and tsunami detection operating in the Ionian Sea, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16261, https://doi.org/10.5194/egusphere-egu24-16261, 2024.

15:00–15:10
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EGU24-15140
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On-site presentation
Yannice Faugère, Jean Roger, Antoine Delepoulle, Gerald Dibarboure, and Helene Hebert

During the last decades, trans-oceanic tsunamis have been captured by satellite altimeters on several occasions. The largest event ever measured by an altimeter was the 2004 Indian Ocean tsunami, captured by Jason-1, Topex/Poseidon, GFO and Envisat altimetry missions flying at that time 

 

The new altimetry mission SWOT (Surface Water and Ocean Topography) developed by NASA and CNES, the US and French Space agency respectively, was launched in December 2022. SWOT embarks a novel instrument, a Ka-band Radar INterferometer (KaRIN), providing a 120 km wide swath Sea Level. On 19 May 2023, SWOT was able to measure the tsunami generated by the Mw 7.7 earthquake which occurred southeast of the Loyalty Islands (southwest Pacific Ocean) at 02:57:03 (UTC). SWOT flew over the region about 1 hour after the earthquake and captured the tsunami signature in several locations. For the first time, a 2D mapview image of the height of tsunami wavetrain was measured by a satellite.

 

The tsunami generation and propagation have been simulated using COMCOT model, using source parameters derived from seismic observations and empirical laws. Preliminary simulation results show that a simple fault plane with uniform coseismic slip allows to reproduce the regional coastal gauge and oceanic DART station records with a relatively good level of confidence, considering that the earthquake rupture was strongly not-double couple according to USGS. An array of virtual gauges was designed to cover the satellite pathway, allowing to extract the dynamic representation of the tsunami wavefield corresponding to the satellite propagation time (i.e., the sea surface deformation is observed over a period of time of several minutes, instead of being static at a given time). Comparison between the SWOT sea surface measurement and the simulation result is satisfactory, showing a good agreement between the location of the first wave peaks (propagating toward the southwest and the northeast, respectively), their amplitude and phase.

 

The objective of this study is first to present this unprecedented observation, and to analyze the level of consistency with simulations.

How to cite: Faugère, Y., Roger, J., Delepoulle, A., Dibarboure, G., and Hebert, H.: The 19 May 2023 tsunami near the Loyalty Islands captured by the new SWOT satellite, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15140, https://doi.org/10.5194/egusphere-egu24-15140, 2024.

15:10–15:20
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EGU24-9348
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ECS
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On-site presentation
Yuchen Wang and Kentaro Imai

The high-frequency (HF) ocean radar system is a shore-based remote sensing system that monitors sea surface currents, waves, and wind over large areas. It can measure tsunami-induced surface current velocity and provide information for tsunami early warning. An HF ocean radar system, installed by the Ministry of Land, Infrastructure, Transport, and Tourism in Japan, measured the tsunami velocity in the Kii Channel during the 2011 Tohoku earthquake. The Kii Channel is a strait that separates the Japanese island of Shikoku from the Kii Peninsula on the main island of Honshu. It connects the Osaka Bay with the Pacific Ocean.

We adopted the tsunami data assimilation approach to predict coastal tsunami waveforms. It is a method that reconstructs the tsunami wavefield using offshore data without the need for source information (Maeda et al., 2015). To process the HF radar data as the input, we initially converted the current velocity along the beam direction to into u, v directions (i.e., EW, NS directions). This process also involved the spatial interpolation of observational points from the beam of two HF radar land stations. In addition, recognizing the tradeoff between the sampling rate and velocity resolution, we applied a 10-min moving average to enhance data quality. The processed velocity data exhibited consistency with numerical simulations derived from the source model of Satake et al. (2013). The data assimilation started at 08:05 (UTC, hereafter) on March 11, 2011.

We predicted coastal tsunami waveform at Kobe, located in the Osaka Bay, and compared it with real observation recorded by the tide gauge. The forecast at 08:10 underestimated the tsunami amplitude, achieving an accuracy of 50.1% with a mean squared prediction error (MSPE) of 0.0101. However, the forecast at 08:20 matched well with the real observation, boasting an accuracy of 82.9% and a reduced MSPE of 0.0098. At 08:30, it continued to perform similarly, maintaining consistency between the predicted and observed waveforms. The accuracy was 81.3% and the MSPE further decreased to 0.0093. Given that the tsunami arrived in Kobe at 09:10, our approach can make an accurate prediction at least 50 min before its arrival.

To summarize, we demonstrated the effectiveness of the HF ocean radar system in tsunami early warning. The case study of the 2011 Tohoku tsunami yielded a remarkable accuracy of over 80% at Kobe station. In the future, we will investigate the relationship between the number and location of HF radar observational points and the forecast accuracy.

How to cite: Wang, Y. and Imai, K.: Tsunami early warning using high-frequency ocean radar system in the Kii Channel, Japan, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9348, https://doi.org/10.5194/egusphere-egu24-9348, 2024.

15:20–15:30
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EGU24-8319
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ECS
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On-site presentation
Juan Francisco Rodríguez Gálvez, Jorge Macías Sánchez, Beatriz Gaite, Manuel Jesús Castro Díaz, Juan Vicente Cantavella, and Luis Carlos Puertas

Tsunami Early Warning Systems (TEWS) play a crucial role in minimizing the impact of tsunamis on coastal communities globally. In the NEAM region (North-East Atlantic, the Mediterranean, and connected Seas), historical approaches involve using Decision Matrices and precomputed databases due to the short time between tsunami generation and coastal impact. Overcoming real-time simulation challenges, the EDANYA group at the University of Málaga developed Tsunami-HySEA, a GPU code enabling Faster Than Real Time (FTRT) tsunami simulations. This code is successfully implemented and tested in TEWS of countries like Spain, Italy, and Chile, this code has undergone rigorous verification and validation processes.

In collaboration with the National Geographic Institute of Spain, we have extended the work previously done where we take advantage of the machine learning techniques and proposed a first approach to the use of neural networks (NN) to predict the maximum wave height and arrival time of tsunamis in the context of TEWS with very good results. This approach offers the advantage of minimal inference time and can be executed on any computer. It accommodates uncertain input data, delivering results within seconds.

As tsunamis are rare events, numerical simulations using the Tsunami-HySEA are used to train the NN model. This phase demands numerous simulations, necessitating substantial High-Performance Computing (HPC) resources. Approximately 300,000 simulations have been done to cover different faults in the Atlantic Ocean.

The goal is to develop neural network models for predicting the maximum wave height of such tsunamis at multiple coastal locations simultaneously.  To cover Huelva and Cádiz coast, 78 points in the coastline have been selected for their predictions. The main importance of this work is that the models developed will be implemented in the Spanish TEWS which will produce an estimation of the tsunami impact in seconds.

 

Acknowledgements

  • This project has received funding from the European High-Performance Computing Joint Undertaking (JU) through the projects eFlows4HPC (No 955558) and ChEESE-2P (No 101093038) and by the EU project DT-GEO (No: 101058129).
  • Spanish Network for Supercomputing (RES) grants AECT-2022-1-002, AECT-2022-3-0015 and AECT-2023-1-0028.

How to cite: Rodríguez Gálvez, J. F., Macías Sánchez, J., Gaite, B., Castro Díaz, M. J., Cantavella, J. V., and Puertas, L. C.: Optimizing Maximum Height Inferences through Neural Networks for the Spanish Tsunami Early Warning System, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8319, https://doi.org/10.5194/egusphere-egu24-8319, 2024.

15:30–15:40
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EGU24-479
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ECS
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On-site presentation
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Luce Lacoua, Bill Fry, Andrew Gorman, Yi-Wun Mika Liao, Laetitia Foundotos, Chris Zweck, and Anthony Jamelot

Aotearoa New Zealand, located in the Southwest Pacific Ocean, is vulnerable to tsunamis. The Rapid Characterization of Earthquakes and Tsunami (RCET) project, led by GNS Science (Geological and Nuclear Sciences), aims to improve rapid analysis of large local and regional earthquakes to determine their tsunamigenic potential. Within this project, we are focusing on a simple but rapid and robust estimation of the location and magnitude of an earthquake by refining automated moment tensor inversions. A method to estimate these parameters is the W-phase inversion. Unlike simpler automated magnitude determinations routinely used to analyze earthquakes in New Zealand, the W-phase does not saturate with magnitude, making it better at quantifying Mw for the largest earthquakes. It also provides the centroid, rather than the hypocentre of an earthquake, allowing better estimation of the spatial distribution of shaking impacts. For these reasons we are developing synthetic earthquake waveforms to refine W-phase inversions for Mw ~5+ earthquakes in New Zealand and Mw 6.5+ earthquakes in the southwest Pacific, including the Hikurangi-Kermadec subduction zone. The current tsunami early warning procedure calculates W-phase solutions within 20 minutes of earthquake origins and aims to reduce it to 5-10 minutes. 

With a large set of high-magnitude events adapted to New Zealand and Hikurangi-Kermadec context, we will refine our understanding of the limits regional W- phase inversion. We are focusing on the minimum magnitude we can accurately estimate, the minimal station coverage required and the complexity of the source that can be apprehended by the W-phase.

To improve W-phase solutions for New Zealand, we simulate earthquake waveforms using a catalogue of synthetic ruptures on the Hikurangi-Kermadec subduction zone, produced by RSQSim (Rate and State Earthquake Simulator) under the RNC2 (Resilience to Nature’s Challenge 2) project. To generate the waveforms, we use SPECFEM3D Globe, a finite element method-based software that simulates wave propagation through a global velocity model of the Earth. The simulated waveforms are then postprocessed and inverted to obtain a W-phase solution. Preliminary results define which minimum waveform resolution is required to observe a W-phase and that a simple centroid moment tensor source provides an adequate W-phase solution. 

How to cite: Lacoua, L., Fry, B., Gorman, A., Liao, Y.-W. M., Foundotos, L., Zweck, C., and Jamelot, A.: Improving Rapid Earthquake Characterization of Tsunami Early Warning for Aotearoa New Zealand and the Southwest Pacific, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-479, https://doi.org/10.5194/egusphere-egu24-479, 2024.

Posters on site: Tue, 16 Apr, 10:45–12:30 | Hall X4

Display time: Tue, 16 Apr, 08:30–Tue, 16 Apr, 12:30
X4.68
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EGU24-5841
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Highlight
James Foster, Todd Ericksen, Bruce Thomas, Jonathan Avery, Yuke Xie, and Robin Knogl

We demonstrated the potential for ship-based GNSS systems to contribute to tsunami warning with a pilot network of 10 ships – 8 commercial and 2 research vessels - equipped with a tsunami detection package that included a geodetic-grade GNSS antenna and receiver, and a satellite internet communication system. The ships we instrumented operated throughout the Pacific, and transmitted real-time precise positions to our shore server from 2015-2018. This data set is used to examine the performance that an operational system would be able to expect if employed for tsunami detection. The estimated accuracy for our real-time vertical position solutions is 5.6 cm, commensurate with the advertised accuracy of the positioning service we employed. This indicates it is plausible to expect to observe the sea surface perturbation of a potentially dangerous tsunami with open ocean wave amplitude of more than 10 cm.  Significant numbers of long period (10s of minutes) excursions, however, appear in the data in the absence of actual tsunami. The similarity of these excursions with the signals expected from a tsunami would result in a high rate of false positive detections if the ship data were used to independently identify tsunami events. A significant number of these were associated with ships changing speed as they were approaching or leaving port. A simple masking strategy based on the ship’s speed reduces the number of these artifacts by 48%. The rate of false positive detections can be reduced to negligible levels by treating the network as an ensemble detection system and examining the data from 4 or more ships together. The density of ships in the open oceans are shown to be well matched to the source regions of historical fatal tsunamis, confirming this approach could provide valuable additional data to tsunami warning centers. We suggest that a network of ships, equipped with geodetic GNSS packages, based on a voluntary participation model, and leveraging the results from our pilot project would provide a valuable low-cost augmentation to the current tsunami detection systems. Furthermore, extended tsunami detection capability from this proposed ship network is possible by leveraging the ability of dual frequency GNSS to detect ionospheric perturbations. Tracking perturbations in the total electron count along the ray paths between each ship and each GNSS satellite provides multiple additional time series that have demonstrated capability to detect the ionospheric signals induced by open ocean tsunamis.  Implementing these data streams would therefore expand the effective monitoring zone of each ship in the network from a single tide-gauge-like point to multiple observations within a circle with radius more than 500 km.

How to cite: Foster, J., Ericksen, T., Thomas, B., Avery, J., Xie, Y., and Knogl, R.: Augmenting Tsunami Detection with a Ship-based GNSS Network, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5841, https://doi.org/10.5194/egusphere-egu24-5841, 2024.

X4.69
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EGU24-18892
Fabrizio Romano, Stefano Lorito, Alessio Piatanesi, Manuela Volpe, Hafize Basak Bayraktar, Nikos Kalligeris, and Alessandro Amato

Tsunami warning and forecasting largely benefit from using offshore bottom pressure gauges (OBPG); these sensors, installed far offshore and typically close to causative sources, can measure the tsunami waves before reaching the coasts to maximize the lead time for alerting. Most of these sensors are installed around the Pacific Ring of Fire (e.g., DART buoys, S-NET), which hosts ~90% of the global seismicity and most significant tsunamigenic earthquakes. Even though less frequent than in the Pacific Ocean, tsunamigenic earthquakes can also occur in the Mediterranean Sea (e.g., the M8+ 365 AD in Crete or the M7 2020 Samos earthquakes), in which the Ionian Sea is characterized by relatively high tsunami hazard (Basili et al., 2021). However, offshore sensors are not present in the Mediterranean Sea and the Tsunami Service Providers operating in the basin (CAT-INGV for Italy, NOA for Greece, KOERI for Türkiye, and CENALT for France) can rely for the tsunami monitoring activities only on the coastal tide gauges networks. One of the objectives of the Italian MEET project (MONITORING EARTH'S EVOLUTION AND TECTONICS), in the framework of the National Recovery and Resilience Plan (PNRR) funded by EU, is the deployment of two OBPGs offshore the Italian coasts. To maximize the lead time gain and due to the high cost of the instruments (including both the maintenance and installation), a careful analysis of the optimal locations where to deploy these instruments is required.

Here, we present the results of the study carried out to identify the more suitable locations to deploy two OBPGs offshore the Ionian coasts of southern Italy. The method proposed considers an ensemble composed of more than 150k scenarios selected from the NEAMTHM18 source model; these scenarios are the ones capable of causing at least a 20 cm tsunami height in front of the Ionian coasts of Italy. For each scenario, we compute i) the tsunami detection times for each point within a target area (i.e., more than 200 possible locations) where the OBPG deployment is envisaged, and ii) the tsunami detection times at all tide-gauges on the coasts of the Ionian Sea. The optimal location for the two OBPGs is established by minimizing a cost function which is a summation of the minimum travel times, for each potential tsunami source, to all available existing coastal gauges and all the potential pairs of OBPGs, weighted by the rate of occurrence of each individual source according to NEAMTHM18.

 

Basili et al. (2021). The Making of the NEAM Tsunami Hazard Model 2018 (NEAMTHM18). Front. Earth Sci. 8:616594, doi: 10.3389/feart.2020.616594

How to cite: Romano, F., Lorito, S., Piatanesi, A., Volpe, M., Bayraktar, H. B., Kalligeris, N., and Amato, A.: Optimal positioning of two deep ocean bottom pressure gauges for tsunami wave detection in the western Ionian Sea, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18892, https://doi.org/10.5194/egusphere-egu24-18892, 2024.

X4.70
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EGU24-799
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ECS
Emeline Wavelet, Bill Fry, Andrew Gorman, and Sarah-Jayne McCurrach

New Zealand’s (NZ) entire coastline is at risk of tsunami from local, regional, and distant sources. With more than 75% of New Zealanders living or working within 10 km of the coast, the tsunami risk is significant.

The Rapid Characterization of Earthquakes and Tsunamis (RCET) research programme is being undertaken to better understand, mitigate and respond to tsunami events in NZ. Within this project, my PhD focuses on improving the communication of tsunami threats to local stakeholders and the emergency response sector by creating a new concept: a time-dependent forecast for tsunami.

I have been using the software ComMIT (a tsunami model developed by the NOAA Center for Tsunami Research) to create a catalogue of synthetic tsunamis focusing on the cities of Tauranga and Whangarei, situated on the northeast coast of the North Island. These two cities have been selected due to their exposure to tsunamis: flat topography, densely populated, infrastructure-rich harbour, exposed coastline, proximity to the Kermadec-Tonga trench. 

Using Python, I have generated a diverse assembly of forecasts where the tsunami waves amplitude  measured on the coastline are linked to threat levels, resulting in the creation of the final product: a time-dependent forecast. I have also been engaging with stakeholders and various end user communities with the aim of adapting these models to their needs. We anticipate that this new tool will help them to respond to these threats more efficiently.

How to cite: Wavelet, E., Fry, B., Gorman, A., and McCurrach, S.-J.: Exploration of a Time-dependent Forecast for Tsunami in New Zealand, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-799, https://doi.org/10.5194/egusphere-egu24-799, 2024.

X4.71
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EGU24-8679
Valentina Magni, Manuela Volpe, Louise Cordrie, Michel Bänsch, Finn Løvholt, Stefano Lorito, Fabrizio Romano, Roberto Tonini, Ida Drøsdal, Steven Gibbons, and Jörn Behrens

Probabilistic Tsunami Forecasting (PTF) uses the initial magnitude and location of a seismic event to forecast the tsunami intensity at coastal locations as a probability distribution (Selva et al., 2021). The PTF workflow can be summarized in the following steps: 1) select the ensemble of scenarios and the probability of a scenario coinciding with the actual earthquake; 2) for each scenario, compute a tsunami intensity measure (e.g., maximum inundation height) at coastal locations of interest – either by running shallow water tsunami propagation models with the code Tsunami-HySEA, or by retrieving it from a precomputed database of scenarios; 3) combine the intensity measure with scenario probabilities to compute hazard curves; 4) convert the probabilities into alert levels according to a predefined rule; and 5) visualise the results. More recently, developments in the context of the eFlows4HPC project have allowed for the possibility of updating the probabilities of the ensemble elements based on new data (focal mechanism and sea level data) to make the forecast more precise and/or reduce the uncertainties. Building on these new developments, we present the first results using an even more general PTF workflow here, implementing dynamically the assimilation of new data, such as new estimates of the earthquake magnitude and location, focal mechanism, GNSS displacements, and sea level data. In particular, new estimates of the source will be used to compute a new ensemble, new probabilities, and will trigger Tsunami-HySEA simulations of the new scenarios in the ensemble. If sea level and/or GNSS data are available, we compute the misfit between the data and the results of the simulations to further update the probabilities and reduce the overall uncertainty in the forecast. We use the 2020 Samos earthquake as a first test of the new workflow that includes data assimilation, but further testing will be done for other events in the Mediterranean Sea and Pacific Ocean. Implementing a continuous update of the results within the above outlined dynamic workflow triggered by the arrival of new data represents a crucial element in transforming the PTF into a digital twin.

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/).

How to cite: Magni, V., Volpe, M., Cordrie, L., Bänsch, M., Løvholt, F., Lorito, S., Romano, F., Tonini, R., Drøsdal, I., Gibbons, S., and Behrens, J.: Towards data assimilation in the Probabilistic Tsunami Forecasting digital twin, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8679, https://doi.org/10.5194/egusphere-egu24-8679, 2024.

X4.72
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EGU24-17432
Yuichiro Tanioka and Yota Atobe

 After the dense observation network for earthquakes and tsunamis along the Japan trench (S-net) was available, the tsunami data assimilation became a powerful technique to compute tsunamis in real-time. However, a problem exists for this technique to forecast tsunamis in real-time because the observation data near the source area are always unstable as shown in the 2016 Fukushima earthquake. Therefore, the data near the source area may not be available for real-time tsunami forecast.

 In this paper, we try to solve this problem by combining the tsunami data assimilation with the source estimation using real-time GNSS observation such as REGARD. We tested our method for two cases, the 2016 Fukushima earthquake case and the 1896 Sanriku earthquake case. We first computed the tsunamis from the source models estimated by Kubota et al. (2021) for the 2016 Fukushima case and that estimated by Satake et al. (2017) for the 1896 Sanriku earthquake case as reference tsunamis. We used those commuted data at stations of S-net as observation data without the stations near the source area. Then the tsunami data assimilations with and without the rectangular fault model are performed.

 The result of the 2016 Fukushima case shows that the tsunami data assimilation worked well although the quickly estimated rectangular fault model using the GNSS observation data was not acceptable for the tsunami simulation. The result of the 1896 Sanriku case shows that the tsunami data assimilation with the estimated rectangular fault forecast the acceptable tsunami waveforms along the coast about 20 minutes faster that that without the rectangular fault. This improvement is significant, so our method can be used as a real-time tsunami forecast technique even the tsunami data near the source area will not be available.  

References

Kubota, et al. (2021). Improving the constraint on the Mw 7.1 2016 off-fukushima shallow normal-faulting earthquake with the high azimuthal coverage tsunami data from the s-net wide and dense network: Implication for the stress regime in the tohoku overriding plate. Journal of Geophysical Research: Solid Earth126(10), 79. https://doi.org/10.1029/2021jb022223

Satake, K., Fujii, Y. & Yamaki, S. (2017) Different depths of near-trench slips of the 1896 Sanriku and 2011 Tohoku earthquakes. Geosci. Lett. 4, 33. https://doi.org/10.1186/s40562-017-0099-y

How to cite: Tanioka, Y. and Atobe, Y.: Rapid and Accurate Tsunami Forecast Method Using Tsunami Data Assimilation with Real-time Source Estimation., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17432, https://doi.org/10.5194/egusphere-egu24-17432, 2024.

X4.73
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EGU24-1142
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ECS
Naveen Ragu Ramalingam, Erlend Briseid Storrøsten, Steven Gibbons, Kendra Johnson, Gareth Davies, Stefano Lorito, Alice Abbate, Manuela Volpe, Fabrizio  Romano, Finn Løvholt, Marco Pagani, and Mario Martina

Addressing the challenges associated with the high computational cost of tsunami inundation simulation has been a persistent issue, particularly in capturing earthquake source uncertainty and solving the nonlinear shallow water equations on high-resolution grids. This study aims to alleviate this computational burden by leveraging machine learning surrogates. Further, evaluating these ML models is often hindered by their black-box nature and the limited size of training and testing datasets, posing challenges for practitioners. We propose an encoder-decoder neural network where offshore tsunami waveforms and local co-seismic deformation fields serve as the basis for predicting high-resolution inundation maps at 10m grids. The model is applied to the coastal region of Catania in Sicily, Italy, integrating diverse earthquake scenarios from a large simulation dataset of 53,550 tsunamigenic events in the Mediterranean Sea. We adopt a pretraining-fine-tuning approach for building the machine learning surrogate and address crucial questions regarding the efficient selection of training scenarios, model design, and training. Leveraging this large simulation dataset, we identify specific locations, scenarios and model conditions where the machine-learning surrogate demonstrates sufficient accuracy and reliability. This provides an efficient mechanism for long-term tsunami hazard assessment or urgent tsunami prediction in real-time situations.

How to cite: Ragu Ramalingam, N., Briseid Storrøsten, E., Gibbons, S., Johnson, K., Davies, G., Lorito, S., Abbate, A., Volpe, M., Romano, F., Løvholt, F., Pagani, M., and Martina, M.: ML Surrogate for Tsunami Forecasting and Hazard Assessment in Eastern Sicily, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1142, https://doi.org/10.5194/egusphere-egu24-1142, 2024.

X4.74
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EGU24-60
Chi-Min Liu

In this study, tsunamis which are induced by round-shaped seabed deformations and then propagate outwards in an axisymmetric form are analytically analyzed. The derivation of such an asymmetric wave is firstly reviewed, and followed by an introduction of a novel mathematical approach which is applied to decompose the Bessel function appearing in the wave solution. This approach not only provides an easier way to perform the calculation, but also addresses some physical understanding of axisymmetric tsunamis. A simplest scenario is simulated by the derived solution to observe the characteristics in the propagation phase. The major finding addresses that the first wave is not always the biggest one.

References

  • B. Le Méhauté, S. Wang, Water waves generated by underwater explosion (1995).
  • E. A. Okal, C. E. Synolakis, Geophys J. Int., 204 (2016), 719-735.
  • C. M. Liu, Wave Motion, 93 (2020), 102489.
  • C. M. Liu, Math. Prob. Eng., 2021 (2021), 1113733.
  • M. Abramowitz, I. A. Stegun, Handbook of mathematical functions with formulas, graphs, and mathematical tables(1964).
  • F. Maass, P. Martin, J. Olivares, Comput Appl Math., 39 (2020), 222.

How to cite: Liu, C.-M.: Tsunamis induced by round-shaped seabed deformations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-60, https://doi.org/10.5194/egusphere-egu24-60, 2024.

X4.75
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EGU24-8620
Exploring fault parameters impact on tsunami modelling on strike-slip faults off SW Iberia
(withdrawn after no-show)
Sara Martínez-Loriente, Manel Prada, Jorge Macías, Carlos Sánchez-Linares, Beatriz Gaite, Luis Carlos Puertas, and Hector Perea
X4.76
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EGU24-13527
Robert Weiss and Tina Dura

Sandy tsunami deposits are essential stratigraphic markers to document the impact of tsunamis in the geologic record. Tsunami sands are also the only record of past tsunamis that can be interrogated to retrieve quantitative information about the causative tsunami event. Inversion of flow speed and flow depth from tsunami deposits is often employed to understand a tsunami event better and evaluate the impact of different tsunami events in the same stratigraphic sequence or geographic area. 

After deposition, like any other deposit, sandy tsunami deposits are exposed to a series of processes that alter the deposits, collectively called post-depositional processes. These post-depositional processes can change the characteristics significantly. If tsunami deposits are employed to gain quantitative insights into a past event, these post-depositional processes can potentially alter respective inversion results. The influence of post-depositional processes on the inversion of flow depths and speeds has been considered but remains understudied.

To gain more insight into the influence of flow speed and flow depth inversions, we present a new model to simulate different post-depositional processes, such as erosion, bioturbation, winnowing, compaction, and dissolution of minerals. We employ stochastic processes for all these sediment alteration possibilities on a grain-size distribution level. In this context, we use a large number of reference grains for each grain-size class in a given deposit and calculate an individual grain's fate depending on the post-depositional process. This new model allows us to consider different combinations of processes to simulate different sedimentary environments and to quantify the influence of different post-depositional processes with time. We employ the established TSUFLIND model to invert flow speed and depth from the altered grain-size distribution. 

Our results indicate how individual post-depositional processes have a more significant influence on inverted flow speeds and depths than others, but they also show how they can influence each other to have a more substantial impact on the sum than individually. Furthermore, our results shed light on potential uncertainties any inversion of the flow characteristics might have depending on the sedimentary environment in which the tsunami deposit was created. In turn, this contributes to a better understanding of uncertainties in tsunami hazard assessments that include tsunami deposits.

How to cite: Weiss, R. and Dura, T.: The impact of post-depositional processes on tsunami deposits - A quantitative analysis for tsunami hazard assessments, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13527, https://doi.org/10.5194/egusphere-egu24-13527, 2024.

X4.77
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EGU24-15775
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ECS
Carlos Sánchez-Linares, Jorge Macías Sánchez, Hernán Porras, and Víctor Huérfano

This study integrates high-resolution tsunami simulations with land use-dependent variable friction across the entire coastal region of Puerto Rico. By using the Tsunami-HySEA model, developed by the EDANYA Research group at the University of Malaga, this research transcends traditional practices, exploring the interplay between terrain characteristics and tsunami dynamics through the incorporation of variable friction. The execution of high-resolution simulations covering the entire coast of Puerto Rico represents a computational and scientific challenge unprecedented in prior research, reinforcing the applicability of this study.

Computational topo-bathymetric grids are constructed to create a coherent model, smoothing irregularities in topo-bathymetric data. Provided by the Puerto Rico Seismic Network, these data have been processed for optimized numerical simulations. The study employs five sets of nested grids, corresponding to different regions (Northeast, Northwest, East, West, and South) of Puerto Rico, and within each configuration, four nested grids with resolutions ranging from 480 meters to 7.5 meters facilitate simulations with varying levels of detail. This strategy optimizes computational resources and ensures precise results in specific coastal areas. The high-resolution discretization, at 7.5 meter per pixel, spans the entire 1,100 km coastline of Puerto Rico. Additionally, simulations have been conducted for 29 distinct seismic sources, comparing this approach to the traditional constant friction approach with Manning coefficient set at 0.03.

The influence of the Manning coefficient is evident in its effects on velocities, momentum flux, and, on the inundation area extension. Understanding the different land uses is crucial for accurately analyzing the effects of a tsunami on the coast and predicting the magnitude of the resulting inundation. The topography, vegetation, and structures built in coastal areas can significantly modulate wave propagation and water depth inland. Identifying these variations in land uses allows for a more precise planning of tsunami mitigation and response measures, as well as a detailed assessment of vulnerable areas.

Acknowledges
This contribution was supported by the Center of Excellence for Exascale in Solid Earth (ChEESE-2P) funded by the European High Performance Computing Joint Undertaking (JU) under grant agreement No 101093038 and by the EU project “A Digital Twin for Geophysical Extremes” (DT-GEO) (No: 101058129). The authors thankfully acknowledges the computer resources at CTE-Power and the technical support provided by Barcelona Supercomputing Center (AECT-2023-3-0017 - Tsunami Hazard Assessment for Puerto Rico. A first study of variable friction coefficient with Tsunami-HySEA)

How to cite: Sánchez-Linares, C., Macías Sánchez, J., Porras, H., and Huérfano, V.: High-Resolution Tsunami Simulations including Land Use-Dependent Variable Friction Along Puerto Rico's Coast, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15775, https://doi.org/10.5194/egusphere-egu24-15775, 2024.

X4.78
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EGU24-19130
Ira Didenkulova, Cesare Angeli, Alberto Armigliato, and Efim Pelinovsky

The study of long wave runup is a classical problem in fluid dynamics, in both linear and nonlinear formulations. However, little attention has been given to the inverse problem, i.e. the reconstruction of the initial condition from a known runup time history.

According to the piston model of tsunami generation, the problem can be modelled as an initial value problem with assigned initial water surface displacement and zero velocity. In this framework, the solution of the linear problem, i.e. the runup as a function of time, can be written as the convolution of the initial water surface with an Abel kernel. This solution can be analytically and uniquely inverted, obtaining the initial wave surface as a functional of the runup function.

In this work, this solution is applied to analytically generated runup time series and its properties are analyzed. In particular, the robustness of the solution to added noise is verified and the effect of nonlinearity is investigated through the use of a Riemann transform of the coordinates.

How to cite: Didenkulova, I., Angeli, C., Armigliato, A., and Pelinovsky, E.: Tsunami source reconstructed from runup time-series, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19130, https://doi.org/10.5194/egusphere-egu24-19130, 2024.

X4.79
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EGU24-4815
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ECS
Kyungman Kwon, Sung-Gwan Myoung, Byoung-Ju Choi, and Kwang-Young Jeong

Meteotsunami, which cause fluctuations on the sea surface, occur due to atmospheric pressure jumps and atmospheric gravity waves. This is a long ocean wave with almost the same spatio-temporal scale as regular tsunamis, causing significant damage to coastal areas. To understand the relationship between meteotsunami and climate change in Korea, research on the genesis and development processes of meteotsunami is necessary. This study examines the generation and propagation process of a meteotsunami that occurred in the Korea Strait on April 7, 2019, using observational data and numerical models. Coastal tidal observation stations detected a meteotsunami in the Korea Strait, characterized by oceanic long waves with heights ranging from 0.2 to 0.9 meters and a period of about 60 minutes. Atmospheric pressure jumps, starting in the Yellow Sea and moving into the Korea Strait, propagated in succession, observed to range from 2 to 4 jumps with magnitudes of 1.5 to 3.9 hPa. Analysis of meteorological data showed that the isobars of the atmospheric pressure jumps were oriented eastward in a counterclockwise direction at angles of 75 to 83 degrees, moving at speeds of 26.5 to 31.0 m/s. The Regional Ocean Model System (ROMS) was used to reproduce this meteotsunami's generation and propagation process. Numerical model results indicated that long ocean waves were amplified in the southwestern part of the Yellow Sea with depths greater than 75 m due to Proudman resonance. This long ocean wave refracts towards the coast in shallow areas north of the Korea Strait, with refraction and reflection by offshore islands influencing the wave heights at the coast. In particular, the high maximum amplitude of long ocean wave in Masan Bay is mainly due to refraction and reflection by nearby islands, increasing the amplitude by approximately 72.7%. Sensitivity experiments were conducted to examine the relationship between the height changes of long ocean wave on the coast and the speed and angle of the atmospheric pressure jumps moving from west to east across the Korea Strait. In the numerical model experiments, atmospheric pressure jumps moving at angles of 80 to 118 degrees and speeds of 27 to 30 m/s significantly increased the amplitude of the ocean long waves. Regionally, Seogwipo and Goheung showed increased amplitudes at speeds of 24 to 30 m/s and were relatively less affected by the angle. In Masan, the maximum amplitude of sea surface oscillation occurred when the atmospheric pressure jump moved at angles of 85 to 100 degrees at a speed of 30 m/s.

How to cite: Kwon, K., Myoung, S.-G., Choi, B.-J., and Jeong, K.-Y.: Propagation Process of Long Ocean Wave from the Yellow Sea to the Korea Strait in Spring 2019, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4815, https://doi.org/10.5194/egusphere-egu24-4815, 2024.

X4.80
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EGU24-14855
Jadranka Sepic, Nikola Metlicic, and Mirko Orlic

An online catalogue of meteorological tsunamis in the Adriatic Sea was recently published. The catalogue contains information on 36 meteorological tsunamis, all with a wave height of at least 1 m, which occurred between 1931 and 2021. During this period, there were 10 exceptionally strong events with observed tsunami wave heights of over 3 metres. The strongest event was characterised by tsunami waves of up to 6 m. For all 36 events, available sea level and air pressure measurements, atmospheric synoptic conditions (using ERA5 reanalysis) and satellite images were analysed. Based on the background sea level height (from the nearest tide gauge), the meteorological tsunamis were divided into three categories: (1) storm surge meteotsunamis, i.e. tsunamis that occur at the time of a storm surge; (2) ordinary meteotsunamis, i.e. tsunamis that occur when the background sea level is low; (3) transitional tsunamis. All three types were associated with a strong south-westerly to westerly jet stream in the middle and upper troposphere, which mainly led to the advection of warm air from the southern Mediterranean to the Adriatic Sea. Similarly, convective clouds were observed over the Adriatic Sea during most events before or at the time of the meteotsunamis.

At the surface, three types of events were distinguished from each other. Storm surge meteotsunamis (10 events in total) were associated with a mid-latitude cyclone, centred over the northern Adriatic or the Bay of Genoa, with the cyclone warm sector or advancing cold front over the area affected by the meteotsunami. The associated surface winds were strong and usually of a south-easterly direction (sirocco). The meteotsunamigenic air pressure disturbances were therefore probably generated in the areas of strong updrafts related to the advancing temperature fronts. Ordinary meteotsunamis (21 events) were associated with fair weather, i.e. with a gradient-free mean sea level pressure field over the Adriatic and very weak surface winds. In this type of event, the meteotsunamigenic atmospheric pressure disturbances were probably due to convective disturbances or the atmospheric gravity waves. Transitional events (5 of them) were associated with either a weak gradient of mean sea level pressure field over the Adriatic, with corresponding southeasterly winds of moderate strength, or with a closed shallow low over the Adriatic.

Stronger events were more likely to occur under fair weather conditions but were also observed under stormier weather. The analysis suggests that meteotsunamis in the Adriatic occur under variety of conditions, all of which should be considered when assessing the risk of meteotsunamis.

How to cite: Sepic, J., Metlicic, N., and Orlic, M.: Synoptic conditions corresponding to the Adriatic meteorological tsunamis, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14855, https://doi.org/10.5194/egusphere-egu24-14855, 2024.

X4.81
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EGU24-11223
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ECS
Alexis Marboeuf, Pablo Poulain, Anne Mangeney, Anne Le Friant, Maxwell Silver, Enrique Fernandez Nieto, and Annabelle Moatty

Since May 2018, Mayotte Island has been experiencing seismo-volcanic activities which may trigger submarine landslides and tsunamis. Numerical models are a powerful tool to build tsunami hazard maps and to establish evacuation plans, improving early-warning systems. However, a lot of uncertainties still remain in model parameters making it difficult to reproduce the landslide dynamics and the generated waves. 

In this work, we perform a sensitivity analysis using the multilayer HySEA shallow water model [1, references therein]. HySEA simulates both a landslide and a generated tsunami. We focus on a scenario posing the greatest threat to the local community, involving a submarine landslide on the eastern side of Mayotte's lagoon at a shallow water depth [2]. Hydrostatic and non-hydrostatic results are compared and several numeric and physical parameters are investigated: grid resolution, number of water layers in the vertical direction, rheological laws, friction coefficients and grain sizes.

Our results show that using non-hydrostatic conditions, increasing the grid resolution and the number of water layers greatly impacts the computed waves. Increasing these parameters is worth the larger computational cost. Physical parameters related to the landslide also affect the dynamic and the final deposit of the granular mass. While the choice of the grain size, the used rheological law or the friction angles may lead to different results, almost no change was observed over an hour of simulation when the Manning coefficient is modified. In all our test cases, the differences appear mainly at the early stages of the simulations. Numerical gauges placed at locations of interest on Mayotte's coast allow a closer look at the numerical waves for a finer sensitivity analysis.

References

[1] J. Macìas, C. Escalante, M. J. Castro. Multilayer-HySEA model validation for landslide-generated tsunamis - Part 2: Granular slides. Natural Hazards and Earth System Sciences, Volume 21 (2021).
[2] A. Lemoine; R. Pedreros; A. Filippini. Scénarios d’impact des tsunamis pour Mayotte. BRGM Report BRGM/RP-69869-FR (April 2020).
 

 

How to cite: Marboeuf, A., Poulain, P., Mangeney, A., Le Friant, A., Silver, M., Fernandez Nieto, E., and Moatty, A.: Sensitivity analysis of a shallow-water model for landslide-generated tsunamis in Mayotte, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11223, https://doi.org/10.5194/egusphere-egu24-11223, 2024.

X4.82
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EGU24-6087
Peng Du, Linlin Li, and Dawei Wang

The consensus in earlier studies was that the tsunami threat along the coast of south China primarily comes from destructive earthquakes occurring in the Manila subduction zone. However, two seismogenic structures on the continental shelf of the Northern South China Sea, namely the Littoral Fault Zone and the Slope Fault Zone, have been overlooked in these assessments. Both fault zones have a history of destructive earthquakes accompanied by tsunamis. In particular, the Slope Fault Zone, located in the shelf-slope bending zone, is prone to triggering submarine landslides after earthquakes, which can result in devastating tsunamis. This study aims to assess the potential threats posed by earthquake-submarine landslide-tsunami cascading events in the Qiongdongnan segment of the Slope Fault Zone to the coastal regions of Southern China.

To achieve this, we conducted a probabilistic seismic hazard analysis using the latest findings on the fault structure of the Qiongdongnan segment and the comprehensive regional seismic catalog. This analysis provides important information about the likelihood of earthquakes in the region. Based on the seismic hazard analysis results, we assessed the stability of gentle slope areas (submarine landslide gap) using high-resolution bathymetric data, multi-channel seismic profiles, and gravity core samples of seafloor sediments. Finally, we established a model for potential submarine landslide sources in these areas and evaluated the tsunami hazard resulting from earthquake-triggered landslides.

By comprehensively evaluating earthquake-submarine landslide-tsunami cascading events on the continental shelf fault zone of the Northern South China Sea, this study aims to provide a new perspective and understanding for earthquake and tsunami disaster prevention. Additionally, it seeks to establish the scientific foundations for the development of effective tsunami warning and risk management strategies.

How to cite: Du, P., Li, L., and Wang, D.: Hazard Assessment of Earthquake-Submarine Landslide-Tsunami Cascading Events on the Slope Fault Zone of Northern SCS, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6087, https://doi.org/10.5194/egusphere-egu24-6087, 2024.

X4.83
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EGU24-19584
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ECS
Inês Ramalho, Rachid Omira, and Jihwan Kim

Mass-wasting events on volcano islands flanks are a recognized source of tsunami. Nonetheless, little is known about the failure mechanisms, dynamics that lead to the wave formation and the tsunami extent when the displaced material plunges into the sea and moves downslope. Owing to the lack of direct and instrumental observations, the main indicator of tsunamigenesis for mass-wasting events is the volume of the failure material, often inferred from mass transport deposits offshore and/or collapse scars onshore.

This work addresses the influence of islands offshore morphology on the formation and hazard extent of tsunamis triggered by coastal cliff-failures. Particularly, we explore two common coastal morphologies of ocean volcanic islands: a volcanic island with and without insular shelves. We seek to better understand how the presence of these shallow submarine platforms constrains the dynamics of the collapses and, consequently, the tsunami generation and its hazard extent. To this end, we performed numerical simulations using different morphologic configurations and landslide volumes and allowing to simulate and analyse the formed tsunami energy (both potential and kinetic). The results show that, for the same coastal cliff-failure volume, the islands offshore morphology highly influence the tsunami generation and hazard extent. We found that tsunamis forming on islands with insular shelves have initial solitary-like waveshape with relatively short wavelength, while those on islands without shelves show N-wave shape with longer wavelength. The latter have higher energy, both potential and kinetic, allowing the tsunami to travel away from the shore and cause larger hazard extent than those occurring on islands without shelves. Our results demonstrate that offshore island morphology is a particularly determining factor in the dynamics of collapsed sectors and, therefore, on their tsunamigenesis and hazard extent.

This work is supported by projects MAGICLAND (PTDC/CTA-GEO/30381/2017) and HAZARDOUS (PTDC/CTA-GEO/0798/2020) FCT-funded projects. This work was funded by the Portuguese Fundação para a Ciência e a Tecnologia (FCT) I.P./MCTES through national funds (PIDDAC) – UIDB/50019/2020 (https://doi.org/10.54499/UIDB/50019/2020), UIDP/50019/2020 (https://doi.org/10.54499/UIDP/50019/2020) and LA/P/0068/2020 (https://doi.org/10.54499/LA/P/0068/2020).

How to cite: Ramalho, I., Omira, R., and Kim, J.: Effect of volcanic islands offshore morphology on the tsunami generation and hazard extent from coastal cliff-failures., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19584, https://doi.org/10.5194/egusphere-egu24-19584, 2024.

X4.84
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EGU24-212
James Terry, Piero Bellanova, Lisa Feist, Margret Mathes-Schmidt, Aaron Micallef, Derek Mottershead, and Klaus Reicherter

The Mediterranean Sea has experienced extreme waves (including large tsunamis) in the past.  However, the pattern of timing, frequency and magnitudes of these events, and the relative importance of possible storm and tsunamigenic mechanisms (undersea earthquakes, volcanic eruptions, major landslides) are not so well understood.  The Maltese archipelago is uniquely situated for extreme wave  research in the Mediterranean Sea, since this group of small islands is exposed to waves approaching from any direction.  Previous studies in Malta investigating sediment deposits from Holocene palaeotsunamis have tended to focus on the hydrodynamic characteristics of large coastal boulders.  This study adopts an alternative approach.  In the Aħrax area on the northernmost peninsula of Malta Island, we examined ‘karst pockets’ (solution hollows) that pockmark the exposed limestone terrain at elevations of up to 10-12 m asl.  Deposited in the pockets are shelly marine sands.  Lined by insoluble terra rossa soils, the pockets act as sediment traps during inundation by wave flow and are excellent repositories from which the accumulated marine sands cannot easily be removed.

This presentation describes the sampling methods, some challenges and results of subsequent laboratory analysis.  Findings show the moderately-sorted sands contain a rich microfossil assemblage of mostly benthic species, comprising foraminifera, gastropods, echinoidea, serpulidae and bryozoa.  Wave-abraded forms occur alongside well-preserved forms.  Sediment stratigraphy within the karst pockets suggests various depositional episodes, contrasted by differing grain sizes, microfossil contents, colours and erosional contacts, while the cliff-top elevations of 10-12 m require consideration of the potential of both storm waves and tsunamis and their respective capabilities with regard to the exposed coastal geomorphology.

How to cite: Terry, J., Bellanova, P., Feist, L., Mathes-Schmidt, M., Micallef, A., Mottershead, D., and Reicherter, K.: Mediterranean extreme wave sediments preserved in karst solution pockets in cliff-top sites on the island of Malta, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-212, https://doi.org/10.5194/egusphere-egu24-212, 2024.

X4.85
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EGU24-14625
Gerasimos Papadopoulos and Ioanna Triantafyllou

The European Plate Observing System (EPOS) provides research infrastructure, including data and services, in solid Earth science. Recently EPOS decided also to create a Tsunami Core Service (TCS). In addition to the existing databases, we contribute to the TCS initiative by providing two new tsunami databases in the eastern Mediterranean as new EPOS services. The first database compiles data on Tsunami Observation Points (TOPs) of past tsunamis.  For a specific tsunami event the TOPs DB includes the source epicenter, the TOPs names and the corresponding geographical coordinates, names of the localities and a characterization of the tsunami intensity level, K, in each TOP. The second database compiles data on the impact of past tsunamis. Depending on the data availability an effort has been made to introduce quantitative impact data to the extent it is possible (e.g., numbers of fatalities and injuries, numbers of buildings or vessels damaged, etc.). From the impact of a tsunami event the maximum tsunami intensity, K, has been estimated according to the 12-grade scale of Papadopoulos and Imamura (2001). The new service is of great importance since it may help in studies of several kinds such as understanding better of the tsunami source type, determination of the inundation area, verification of tsunami simulation results and tsunami risk assessment. 

 

How to cite: Papadopoulos, G. and Triantafyllou, I.: Tsunami databases in the eastern Mediterranean as new EPOS services, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14625, https://doi.org/10.5194/egusphere-egu24-14625, 2024.

X4.86
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EGU24-18134
Anika Braun, Katrin Dohmen, and Tomas Manuel Fernandez-Steeger

Landslides can induce extremely high tsunami waves, reaching several tens of meters. These tsunamis typically impact only localized areas within about 100 km of the landslide. The most significant impact is generated in the immediate proximity to the landslide. Due to the short time between wave initiation and reaching the coast, early warning systems for these events have not yet been developed. This study aims to assess the exposure of particular regions to this specific form of tsunami with a focus on the Indonesian coastline. The approach not only evaluates the potential for the occurrence of landslides but also assesses whether there is a potential for the formation of particularly high tsunami waves, e.g. due to reflection or superposition of waves.

The limited number of known landslides that have triggered tsunamis in the past is not sufficient to enable a data-driven analysis. Hence, a heuristic approach is adopted in this study. It consists of the following 4 steps.

(1) Orientation workshop: A group of international scientists working on landslides and tsunamis discusses and selects parameters that might be relevant for the analysis.

(2) Online survey: The parameters selected in step (1) are ranked by a larger group of scientists.

(3) Result workshop: The survey results are discussed in another workshop.

(4) Susceptibility analysis: The parameter ratings from the online survey are transformed into a model for tsunamigenic landslide susceptibility evaluation and a susceptibility analysis for a pilot area in Indonesia is conducted.

During the orientation workshop, 37 parameters were selected to be considered for the susceptibility analysis. As part of the online survey, these were evaluated by a total of 25 scientists working on landslides and tsunamis. For landslide susceptibility in Indonesia, subaerial and submarine slope angle, presence of oversteeped slopes, landform, lithology, presence of lowly consolidated sediments, distance to active tectonic faults, depth and magnitude of historic earthquakes, precipitation, and pore water pressures were voted as crucial parameters. The work on this study is still ongoing and step (4) is planned to be conducted in the future.

The results of tsunamigenic landslide susceptibility mapping can aid local officials in elaborating mitigation measures for this type of tsunami. Even minor earthquakes in these areas could trigger landslides, creating waves despite not typically causing seismic tsunamis. Hence, it might be necessary to adapt land-use and evacuation plans in at-risk regions to account for both seismic and landslide-induced tsunamis. The limited availability of high-resolution data representing the submarine environment is the main obstacle, which hampers a deeper analysis of submarine landslide susceptibility and the potential for tsunami wave generation. Future efforts must be made to close this data gap and enable effective protection of coastal populations from landslide-induced tsunamis.

How to cite: Braun, A., Dohmen, K., and Fernandez-Steeger, T. M.: An expert-based framework for susceptibility analysis for tsunamigenic landslides in Indonesia, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18134, https://doi.org/10.5194/egusphere-egu24-18134, 2024.

X4.87
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EGU24-14559
Stefano Lorito, Fabrizio Romano, Manuela Volpe, Roberto Tonini, Valeria Cascone, Finn Løvholt, Steven Gibbons, Sylfest Glimsdal, Carl Harbitz, Micheal Bader, Alice Agnes Gabriel, Gareth Davies, Jorge Macias, Andrey Babeyko, Jörn Behrens, Kendra Johnson, Helen Crowley, Marco Pagani, and Piero Lanucara

The EU ChEESE-2P project (Centre of Excellence for Exascale in Solid Earth, second Phase, https://cheese2.eu/) aims to developing Pilot Demonstrators (PD) in different areas of Solid Earth (SE) addressing 12 SE Exascale Computational Challenges. 

One of these is a new Probabilistic Tsunami Hazard Assessment (PTHA) for earthquake-generated tsunamis at the global scale, in the framework of the GTM (Global Tsunami Model) initiative. The GTM PTHA model is meant to be an update of the previous one of its kind (Davies et al., 2018, Geological Society of London). The new model will present enhanced source variability (e.g. stochastic slip) and spatially higher resolution of the calculation points. 

“Capacity” simulations will involve on the order of several 100k unit sources, using grids with a 30 arc-sec resolution. The offshore simulations will require on the order of a few million GPU hrs. Inundation simulations for some pilot localities may need up to 5-10 million GPU hrs. They encompass tens of millions of global tsunami scenarios and create high-resolution inundation maps for 10-20 hotspot locations. The global and local models will be distributed through EPOS-TCS Tsunami, showcasing EuroHPC resource utilization for local hazard and risk analysis.

Further than representing a new global reference hazard model, some tools will be provided to allow to:

  • Take the global model as an input to perform local PTHA anywhere globally;
  • Recalculate the hazard using a custom source treatment, including probability, rates, fault data, and earthquake source models with dynamic and heterogeneous slip, using pre-calculated or on-the-fly HPC-based tsunami modelling with the Tsunami-HySEA GPU code;
  • Publish results via the EPOS-TCS Tsunami service delivery framework.

The GTM PTHA model and tools will be interoperable with the other seismic source models and risk calculation tools (e.g. OpenQuake), thus establishing a connection between the Global Tsunami Model (GTM) and Global Earthquake Model (GEM).

We will also seek to establish compatibility and potential coupling with the Digital Twins from different EU projects (DT-GEO, DT-Ocean) towards DestinE.

How to cite: Lorito, S., Romano, F., Volpe, M., Tonini, R., Cascone, V., Løvholt, F., Gibbons, S., Glimsdal, S., Harbitz, C., Bader, M., Gabriel, A. A., Davies, G., Macias, J., Babeyko, A., Behrens, J., Johnson, K., Crowley, H., Pagani, M., and Lanucara, P.: The GTM global probabilistic tsunami hazard model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14559, https://doi.org/10.5194/egusphere-egu24-14559, 2024.

X4.88
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EGU24-14980
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ECS
Vedran Kapitanovic, Jadranka Sepic, Miroslava Pasaric, and Mohammad Heidarzadeh

On April 15, 1979, the coastal region of Montenegro was shaken by a devastating earthquake (M = 6.8, Modified Mercalli Intensity = IX-X). Towns and villages were severely damaged, numerous cultural heritage sites were destroyed and around 150 people were killed. The hypocenter was in the sea near the coast between Bar and Ulcinj at a depth of 13 km. The earthquake triggered a tsunami, which was registered by several tide gauges. The strongest waves with an initial height of 45 cm were registered in nearby Bar, where oscillations lasted for more than 24 hours. Tsunami waves of up to 10 cm in height were also recorded on the opposite Adriatic coast, at the Bari (Italy) tide gauge. According to newspaper reports, the tsunami had a strong impact along the Montenegrin coast, with waves reaching a height of up to 3 metres and one person drowning. The numerical model COMCOT (Cornell Multi-grid Coupled Tsunami model) was used to simulate the tsunami. Since various parameters for the earthquake source fault parameters are given in the literature, with varying values for the location of the epicentre, the depth, the earthquake magnitude, and the properties of the nodal plane, we carried out a series of simulations by considering a reasonable range for each parameter. The simulations differed in the parameters of the earthquake source - as given in the literature, as well as in the length and width of the fault plane. The simulation that best reproduced the waves recorded at the tide gauges was selected as representative and was further analysed to determine maximum heights, currents, inundation areas and tsunami propagation in the Adriatic Sea.

How to cite: Kapitanovic, V., Sepic, J., Pasaric, M., and Heidarzadeh, M.: Numerical modelling of the Montenegro tsunami of 15 April 1979, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14980, https://doi.org/10.5194/egusphere-egu24-14980, 2024.

X4.89
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EGU24-16049
Philippe Heinrich, Aurélien Dupont, Marine Menager, Aurélie Trilla, Audrey Gailler, Bertrand Delouis, and Hélène Hebert

On March 18, 2021, a magnitude Mw 6.0 earthquake occurred offshore the Algerian coasts near Bejaia, resulting in a tsunami with offshore amplitudes smaller than a few millimeters that crossed the western Mediterranean Sea. This study pursues three primary objectives: firstly, to assess the ability of tsunami simulations to replicate tide-gauge observations; secondly, to ascertain the relevance of seismic sources calculated within the context of tsunami early warning systems, against tsunami generation and observations; and thirdly, to evaluate the sensitivity of simulations to grid resolutions and earthquake parameters.
Within the Mediterranean Sea, only a limited number of coastal tide gauges recorded the tsunami. Among these, select French tide gauge stations captured water waves with amplitudes smaller than a few centimeters and periods ranging from five to twenty minutes, often associated with harbor or bay resonances.
Numerical simulations of the tsunami were conducted utilizing the operational code Taitoko employing six distinct source fault models. Notably, two of these models provided rapid source detection and characterization within the framework of tsunami warning systems at CENALT (Centre National d’Alerte aux Tsunamis, France). The integrated code Taitoko employs a system of multiple nested grids. For this event, it solved standard Boussinesq equations within the Mediterranean grid, while employing nonlinear shallow water equations in coastal and harbor grids, each with resolutions of 25 and 5 meters, respectively. Regardless of the fault model employed, the model satisfactorily reproduced the observed time series of water heights in both phase and amplitude at Nice and Monaco, while some discrepancies are found and discussed for most of the other locations.

How to cite: Heinrich, P., Dupont, A., Menager, M., Trilla, A., Gailler, A., Delouis, B., and Hebert, H.:   Tsunami Simulation and Seismic Source Characterization: A Case Study of the March 18, 2021 Offshore Bejaia Earthquake (Mw 6.0) in the Western Mediterranean, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16049, https://doi.org/10.5194/egusphere-egu24-16049, 2024.

X4.90
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EGU24-4192
Mohammad Heidarzadeh, Aditya Riadi Gusman, Iyan E. Mulia, and Anawat Suppasri

On 2nd December 2023, the eastern coasts of Philippines were struck by an M7.6 earthquake followed by a moderate tsunami measuring 0.5 m in height. The earthquake was the result of thrust faulting in the Philippine Trench (subduction zone) at the depth of 32.8 km according to the United States Geological Survey. Philippine Trench is the result of tectonic convergence between the Philippine Sea and Sunda plates. The December 2023 earthquake resulted in three deaths; however, no death or casualty was reported due to the tsunami. This event reminds another M7.6 tsunamigenic earthquake on 31st August 2012 in the outer-rise region of the Philippine Trench that occurred approximately 300 km from the 2023 epicenter causing one death (https://doi.org/10.1007/s00024-014-0790-2).

From historical records, two prominent events in the region are an M 8.0 – 8.3 tsunamigenic earthquakes in 1918, and an M 7.9 earthquake in August 1976. The latter event generated a locally destructive tsunami that killed 5,000 people. It appears the largest recorded event in the region is the 1918 earthquake with a magnitude in the range of M 8.0 – 8.3. Considering the relatively short span of recorded earthquake history, the 1918 event cannot conclusively be regarded as the largest possible event from the Philippine Trench. Recent insights from global earthquakes in various subduction zones suggest that the occurrence of M9 earthquakes is feasible in any subduction zone, provided that the zone's length is sufficient to accommodate such events. Therefore, it is important to study the hazards from M9 earthquakes and potential tsunamis in the Philippine Trench and investigate the risks to infrastructure. 

The purpose of this research is to study the tsunamigenic potential of the Philippine Trench by modeling the 2012 and 2023 events and comparing them, modelling potential worst-case tsunamigenic earthquakes in the region and investigating their hazards and risks to infrastructure. The methodology used in this research are waveform analyses, spectral and wavelet analysis, numerical modelling, and fault tree analysis (FTA). We develop a cascading risk model based on FTA for critical infrastructure in the region.

How to cite: Heidarzadeh, M., Gusman, A. R., Mulia, I. E., and Suppasri, A.: The 2012 and 2023 Mw 7.6 tsunamigenic earthquakes at the Philippine trench and tsunami hazard implications, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4192, https://doi.org/10.5194/egusphere-egu24-4192, 2024.

X4.91
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EGU24-22527
Shunichi Koshimura, Bruno Adriano, Ayumu Mizutani, Erick Mas, Yusaku Ohta, Shohei Nagata, Yuriko Takeda, Ruben Vescovo, Sesa Wiguna, Takashi Abe, and Takayuki Suzuki

The tsunami was generated by the Mw7.6 Noto Peninsula Earthquake and left widespread impact. After the event occurred, we modeled the tsunami propagation and coastal inundation with various tsunami source models and discussed its propagation and inundation features.


Preliminary tsunami modeling results imply that the impacts were severe around Noto Peninsula (Shika to Nanao). Specific bathymetric features of the continental shelf of Noto Peninsula were responsible for high tsunamis in Suzu City. The directivity of tsunami energy was also toward the Japan Sea coasts, especially Joetsu City, Nigata Prefecture. Early tsunami arrival at Toyama City with the leading negative wave could not be explained by fault rupture. The post-tsunami field survey teams at Suzu City preliminarily found tsunami run-ups of 3 m or higher with flow depths of 2.5m or higher. Inside the tsunami inundation zone around Noto Peninsula, we found at least 648 houses were destroyed by both the strong ground motion and tsunami.

How to cite: Koshimura, S., Adriano, B., Mizutani, A., Mas, E., Ohta, Y., Nagata, S., Takeda, Y., Vescovo, R., Wiguna, S., Abe, T., and Suzuki, T.: The 2004 Noto Peninsula Earthquake Tsunami - It's Generation, Propagation, Inundation, and Impact, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-22527, https://doi.org/10.5194/egusphere-egu24-22527, 2024.