Current status of TsunAWI contributions to the Indonesia Tsunami Early Warning System (InaTEWS) with a comparison of warning products from near-realtime easyWave and precomputed TsunAWI simulations

Abstract: The Indonesia Tsunami Early Warning System delivers simulated tsunami forecasts in two different ways: either matching scenario(s) from a pre-computed database or running on-the-fly tsunami simulation. Recently, the database has been extended considerably taking into account additional source regions not covered in earlier stages of the system. In this contribution, we present the current status of the data base coverage as well as a study investigating the warning products obtained by the two modeling approaches. The pre-computed tsunami scenarios are based on the finite element model TsunAWI that employs a triangular mesh with resolution ranging from 20km in deep ocean to 300m in coastal areas and to as much as 50m in some highly resolved areas. TsunAWI solves the nonlinear shallow water equations and contains a wetting-drying inundation scheme. The on-the-fly propagation model easyWave solves the linear shallow water equations on a regular finite-difference grid with a resolution of about 1 km and utilizes several simple options to estimate coastal impact. This model is used for forecasting after a tsunami has been generated in an area not covered by the database or after a moment tensor solution shows an earthquake focal mechanism not present in the database. Since warning products like estimated wave height (EWH) and estimated time of arrival (ETA) along the coast are based on modeling results, it is crucial to compare the resulting forecasted warning levels obtained by the two approaches. Resolutions and numerical settings of both models are quite different, therefore variations in the resulting outputs are to be expected; nevertheless, the extent of differences in warning levels should not be too large for identical sources. In the present study, we systematically investigate differences in resulting warning products along InaTEWS forecast points facing the Sunda arc.  Whereas the finite-element mesh of TsunAWI covers the coast up to a terrain height of 50m and warning products have been pre-calculated directly in the forecast points, easyWave offers several options for their approximation including projections from offshore grid points or vertical wall. Differences and potential reasons for variations of warning products like the role of bathymetry resolution as well as the general approach for the assessment of EWH and ETA for different modeling frameworks are discussed

Comparison of Modeling Approaches and Derived Warning Products in the Framework of the Indonesia Tsunami Early Warning System (InaTEWS)

The Indonesia Tsunami Early Warning System estimates tsunami impact by two methods: either matching scenarios from a pre-computed database or running realtime tsunami simulations. The database scenarios are based on the finite element model TsunAWI using a triangular mesh with resolution ranging from 20km in deep ocean to 300m in coastal areas and up to 50m in some highly-resolved areas. TsunAWI solves the nonlinear shallow water equations and contains an inundation scheme. The on-the-fly propagation model easyWave solves the linear shallow water equations on a regular finite-difference grid with a resolution of about 1km and utilizes several options to estimate coastal impact. This model is used for potential tsunami events in areas not covered by the database. Warning products like estimated wave height (EWH) and estimated time of arrival (ETA) along the coast are based on modeling results. Therefore comparisons of the forecasted warning levels for the two approaches are crucial. Resolutions and numerical settings of both models differ, therefore variations in the resulting outputs are to be expected; nevertheless, the extent of differences in warning levels should not be too large for identical sources. In the present study, we systematically investigate differences in warning products along forecast points facing the Sunda arc. TsunAWI determines warning products are directly in the coastal forecast points, easyWave offers several options for their approximation including projections from offshore grid points. Differences and potential reasons for variations of warning products like the role of bathymetry, resolution as well as the general approach for the assessment of EWH and ETA for different modeling frameworks are discussed

Comparison of modeling approaches and the resulting warning products in the framework of the Indonesia Tsunami Early Warning System (InaTEWS)

The Indonesia Tsunami Early Warning System delivers simulated tsunami forecasts in two different ways: either matching scenario(s) from a pre-computed database or running on-the-fly tsunami simulation. The pre-computed tsunami scenarios are based on the finite element model TsunAWI that employs a triangular mesh with resolution ranging from 20km in deep ocean to 300m in coastal areas and to as much as 50m in some highly resolved areas. TsunAWI solves the nonlinear shallow water equations and contains a wetting-drying inundation scheme. The on-the-fly propagation model easyWave solves the linear shallow water equations on a regular finite-difference grid with a resolution of about 1 km and utilizes several simple options to estimate coastal impact. This model is used for forecasting after a tsunami has been generated in an area not covered by the database or after a moment tensor solution shows an earthquake focal mechanism not present in the database. Since warning products like estimated wave height (EWH) and estimated time of arrival (ETA) along the coast are based on modeling results, it is crucial to compare the resulting forecasted warning levels obtained by the two approaches. Resolutions and numerical settings of both models are quite different, therefore variations in the resulting outputs are to be expected; nevertheless, the extent of differences in warning levels should not be too large for identical sources. In the present study, we systematically investigate differences in resulting warning products along InaTEWS forecast points facing the Sunda arc. Whereas the finite-element mesh of TsunAWI covers the coast up to a terrain height of 50m and warning products have been pre-calculated directly in the forecast points, easyWave offers several options for their approximation including projections from offshore grid points or vertical wall. Differences and potential reasons for variations of warning products like the role of bathymetry resolution as well as the general approach for the assessment of EWH and ETA for different modeling frameworks are discussed in this contribution

Controls of the Foreland Deformation Pattern in the Orogen‐Foreland Shortening System: Constraints From High‐Resolution Geodynamic Models

Controls on the deformation pattern (shortening mode and tectonic style) of orogenic forelands during lithospheric shortening remain poorly understood. Here, we use high-resolution 2D thermomechanical models to demonstrate that orogenic crustal thickness and foreland lithospheric thickness significantly control the shortening mode in the foreland. Pure-shear shortening occurs when the orogenic crust is not thicker than the foreland crust or thick, but the foreland lithosphere is thin (∼4 km) sediments that are mechanically weak (friction coefficient <∼0.05) or weakened rapidly during deformation. The formation of fully thin-skinned tectonics in thick and weak foreland sediments, as in the Subandean Ranges, requires the strength of the orogenic upper lithosphere to be less than one-third as strong as that of the foreland upper lithosphere. Our models successfully reproduce foreland deformation patterns in the Central and Southern Andes and the Laramide province

Identification and ranking of subaerial volcanic tsunami hazard sources in Southeast Asia

Tsunamis caused by large volcanic eruptions and flanks collapsing into the sea are major hazards for nearby coastal regions. They often occur with little precursory activity and are thus challenging to detect in a timely manner. This makes the pre-emptive identification of volcanoes prone to causing tsunamis particularly important, as it allows for better hazard assessment and denser monitoring in these areas. Here, we present a catalogue of potentially tsunamigenic volcanoes in Southeast Asia and rank these volcanoes by their tsunami hazard. The ranking is based on a multicriteria decision analysis (MCDA) composed of five individually weighted factors impacting flank stability and tsunami hazard. The data are sourced from geological databases, remote sensing data, historical volcano-induced tsunami records, and our topographic analyses, mainly considering the eruptive and tsunami history, elevation relative to the distance from the sea, flank steepness, hydrothermal alteration, and vegetation coverage. Out of 131 analysed volcanoes, we found 19 with particularly high tsunamigenic hazard potential in Indonesia (Anak Krakatau, Batu Tara, Iliwerung, Gamalama, Sangeang Api, Karangetang, Sirung, Wetar, Nila, Ruang, Serua) and Papua New Guinea (Kadovar, Ritter Island, Rabaul, Manam, Langila, Ulawun, Bam) but also in the Philippines (Didicas). While some of these volcanoes, such as Anak Krakatau, are well known for their deadly tsunamis, many others on this list are lesser known and monitored. We further performed tsunami travel time modelling on these high-hazard volcanoes, which indicates that future events could affect large coastal areas in a short time. This highlights the importance of individual tsunami hazard assessment for these volcanoes, the importance of dedicated volcanological monitoring, and the need for increased preparedness on the potentially affected coasts

Tsunami-WebGIS - Displaying Tsunami Simulations for Indonesia to a Broader Audience

Within the German-Indonesian Tsunami Early Warning System project (GITEWS), a database containing approximately 4500 tsunami simulations for the Sunda arc, was created. Simulations were calculated using the finite element model TsunAWI implemented at AWI. The corresponding data products such as maximum wave height and estimated time of arrival at the coast are used operationally for tsunami early warning purposes. Visualization of tsunami simulation data in general and analyzing the information by non-modelers is nevertheless difficult, since accessing the data requires in depth knowledge on modeling with TsunAWI and specific programming libraries to be installed. However, it was intended to overcome this issue and provide an overview of the modeling efforts in Indonesia to a broader public. This was accomplished within the scope of the project Earth System Knowledge Platform (ESKP), initiated at institutions of the Helmholtz Association. Data products are visualized in the interactive Tsunami-WebGIS, a Geographical Information System (GIS) based web service, hosted on maps.awi.de, a GIS infrastructure implemented at AWI. The Tsunami-WebGIS provides an overview of the tsunami database and enables the user to trigger a tsunami at a certain epicenter and view the respective maximum wave heights as well as arrival time isochrones. This approach provides an overview of the simulation coverage and tsunami propagation in the the Sunda arc region to a non-expert audience. While it may be used for educational purposes, it has also proven to facilitate analysis by the modelers themselves. It is further planned to include extensions of the database in Indonesia as well as historical events in the region

The FESOM model family - recent applications

This contribution focuses on two applications of the FESOM model family. On the one hand, recent runs with the finite volume code FESOM2 on large global meshes with regional focus are presented. FESOM's shallow water branch TsunAWI is the subject of the second part. TsunAWI, still based on finite elements, is used as an operational model in the Indonesia Tsunami Early Warning System (InaTEWS). InaTEWS derives tsunami forecasts in two different ways: from scenarios in a pre-computed database or from an on-the-fly simulation. The pre-computed scenarios are based on TsunAWI simulations with inundation on a triangular mesh with a resolution ranging from 20km in the deep ocean to 300m - 50m in coastal areas. The on-the-fly propagation model EasyWave (Andrey Babeyko, GFZ) solves the linear shallow water equations on a regular finite-difference grid with a resolution of about 1 km and the coast line as a vertical wall. EasyWave is used after a tsunami has been generated in an area not covered by the database or after seismic measurements show an earthquake mechanism not present in the database. As the numerical settings of both models are quite different, variations in the outputs are to be expected; nevertheless, the differences in the warning levels should not be too large for identical sources. In the current study, we systematically compare the warning products like estimated wave height and estimated time of arrival by the two approaches

Towards the new thematic Core service Tsunami within the EPOS research infrastructure

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

Probabilistic tsunami forecasting for early warning

Tsunami warning centres face the challenging task of rapidly forecasting tsunami threat immediately after an earthquake, when there is high uncertainty due to data deficiency. Here we introduce Probabilistic Tsunami Forecasting (PTF) for tsunami early warning. PTF expli- citly treats data- and forecast-uncertainties, enabling alert level definitions according to any predefined level of conservatism, which is connected to the average balance of missed-vs- false-alarms. Impact forecasts and resulting recommendations become progressively less uncertain as new data become available. Here we report an implementation for near-source early warning and test it systematically by hindcasting the great 2010 M8.8 Maule (Chile) and the well-studied 2003 M6.8 Zemmouri-Boumerdes (Algeria) tsunamis, as well as all the Mediterranean earthquakes that triggered alert messages at the Italian Tsunami Warning Centre since its inception in 2015, demonstrating forecasting accuracy over a wide range of magnitudes and earthquake types

Tsunami risk communication and management: Contemporary gaps and challenges

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