Efficient Local Resorting Techniques with Space Filling Curves Applied to the Tsunami Simulation Model TsunAWI

The OpenMP-parallel model TsunAWI for the simulation of tsunami propagation and inundation discretizes the shallow water quations on an unstructured linear conforming-nonconforming finite element grid. The data access to the variables on the unstructured grid is crucial for the computational performance. A reordering of the unknowns at elements, nodes, and edges along a space filling curve (SFC) guarantees data locality on all levels of the memory hierarchy, thus reducing cash misses and false sharing. The SFC resorting algorithm is presented and its influence on the serial and OpenMP parallel computation times of TsunAWI is compared to other common resorting algorithms like reverse Cuthill-McKee and minimum degree ordering

Systematic Comparison of Tsunami Simulations on the Chilean Coast Based on Different Numerical Approaches

This article belongs to the Special Issue Modelling and Numerical Simulation of Tsunami https://www.mdpi.com/journal/geohazards/special_issues/model_tsunamiTsunami inundation estimates are of crucial importance to hazard and risk assessments. In the context of tsunami forecast, numerical simulations are becoming more feasible with the growth of computational power. Uncertainties regarding source determination within the first minutes after a tsunami generation might be a major concern in the issuing of an appropriate warning on the coast. However, it is also crucial to investigate differences emerging from the chosen algorithms for the tsunami simulations due to a dependency of the outcomes on the suitable model settings. In this study, we compare the tsunami inundation in three cities in central Chile (Coquimbo, Viña del Mar, and Valparaíso) using three different models (TsunAWI, Tsunami-HySEA, COMCOT) while varying the parameters such as bottom friction. TsunAWI operates on triangular meshes with variable resolution, whereas the other two codes use nested grids for the coastal area. As initial conditions of the experiments, three seismic sources (2010 Mw 8.8 Maule, 2015 Mw 8.3 Coquimbo, and 1730 Mw 9.1 Valparaíso) are considered for the experiments. Inundation areas are determined with high-resolution topo-bathymetric datasets based on specific wetting and drying implementations of the numerical models. We compare each model’s results and sensitivities with respect to parameters such as bottom friction and bathymetry representation in the varying mesh geometries. The outcomes show consistent estimates for the nearshore wave amplitude of the leading wave crest based on identical seismic source models within the codes. However, with respect to inundation, we show high sensitivity to Manning values where a non-linear behaviour is difficult to predict. Differences between the relative decrease in inundation areas and the Manning n-range (0.015–0.060) are high (11–65%), with a strong dependency on the characterization of the local topo-bathymery in the Coquimbo and Valparaíso areas. Since simulations carried out with such models are used to generate hazard estimates and warning products in an early tsunami warning context, it is crucial to investigate differences that emerge from the chosen algorithms for the tsunami simulations.This study is part of the tsunami component in the RIESGOS project, with a larger scope of multi-hazard assessments in the Andes region. The RIESGOS project is funded by the German Federal Ministry of Education and Research (Grant numbers 03G0876C and 03G0905C). AG acknowledges the Research Center for Integrated Disaster Risk Management (CIGIDEN), ANID/FONDAP/15110017. NZ has received funding from the Marie Skłodowska-Curie grant agreement H2020-MSCA-COFUND-2016-75443. The Servicio Hidrográfico y Oceanográfico de la Armada de Chile (SHOA) provided high-resolution bathymetry data via the CENDHOC program (Centro Nacional de Datos Hidrográficos y Oceanográficos de Chile). We thank EDANYA Group for sharing the Tsunami-HYSEA code and X. Wang for sharing the COMCOT code. We acknowledge M. Moreno, M. Shrivastava and M. Carvajal for providing the finite faults used in the three experiments. Basemaps by OpenStreetMaps contributors were used in most of the figures. Basemaps in Figure 6 and Figure 10 are taken from Google Earth. Some figures were generated with the GMT software [44]. TsunAWI code optimization was supported by the LEXIS project, funded by the EU’s Horizon 2020 Research and Innovation Programme (2014–2020) under grant agreement no. 825532. Some figures were generated with the software QGIS. We would like to deeply thank the editors and three anonymous reviewers for valuable comments that helped us improving the manuscript.Peer ReviewedPostprint (published version

Operational tsunami modelling with TsunAWI – recent developments and applications

In this article, the tsunami model TsunAWI (Alfred Wegener Institute) and its application for hindcasts, inundation studies, and the operation of the tsunami scenario repository for the Indonesian tsunami early warning system are presented. TsunAWI was developed in the framework of the German-Indonesian Tsunami Early Warning System (GITEWS) and simulates all stages of a tsunami from the origin and the propagation in the ocean to the arrival at the coast and the inundation on land. It solves the non-linear shallow water equations on an unstructured finite element grid that allows to change the resolution seamlessly between a coarse grid in the deep ocean and a fine representation of coastal structures. During the GITEWS project and the following maintenance phase, TsunAWI and a framework of pre- and postprocessing routines was developed step by step to provide fast computation of enhanced model physics and to deliver high quality results

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

Tsunami-Simulation für das indonesische Tsunami-Frühwarnsystem

Nach dem verheerenden Tsunami im Indischen Ozean 2004 wurde das internationale Kooperationsprojekt ''German-Indonesian Tsunami Early Warning System'' ins Leben gerufen und das Frühwarnzentrum am Amt für Meteorologie, Klimatologie und Geophysik in Jakarta aufgebaut. Auf deutscher Seite wurde das Projekt vom Helholtz-Zentrum Potsdam, Deutsches Geoforschungszentrum geleitet. Die Warnung nach einem starken Erdbeben basiert auf einer Datenbank möglicher Tsunamiszenarien, so dass schnell die Gefährdung der Küsten abgeschätzt werden kann. Im Vorfeld dienen detailiierte Überflutungsrechnungen als Basis für Evakuierungspläne. Der Vortrag stellt den Aufbau des Warnsystems mit einem Schwerpunkt auf der Rolle der Tsunami-Simulation vor. Insbesondere werden die physikalischen und numerischen Grundlagen des Simulationsmodells TsunAWI beleuchtet und am Beispiel einiger Modellrechnungen Möglichkeiten und Grenzen der Simulation aufgezeigt

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

FESOM_coastal

There is a growing need in the high quality estimations of long-term dynamics and circulation features in the coastal areas to answer major present and future societal, ecosystem and other questions, because of changing climate. On long time scales, the coastal dynamics change not only because of variable forcing, but also due to exchanges with the evolving global ocean. Over recent years, considerable efforts have been invested into developing regional models and applying them to the coastal areas. These models are used by different institutions to study currents, sediment transport and ecosystem dynamics. They are well-established tools equipped with necessary parameterizations and modules that may be required in shelf or coastal modeling. However, they are regional models with open boundaries. When it comes to applying them to study long-term trends and variability in the regional sea, they have to be coupled to a large-scale modeling system. However, numerical algorithms used by global models can be insufficient to simulate coastal dynamics. There are issues related to vertical advection and mixing, stability in case of very thin sigma layers, absence of wetting/drying option etc. One more point is the choice of time step in case of highly varying resolution. Coastal refinement can be added to the global models, but at the same time they will lose efficiency. Unstructured-mesh coastal models are too dissipative and expensive to simulate global circulation at present. A way out of this situation is coupling global and coastal models (one or two ways nesting). To reach this goal we present a coastal branch of the global model FESOM (Danilov et al. 2004, Wang et al. 2014). FESOM is a well-established large-scale ocean circulation model which is tested in numerous applications and participates in ocean model intercomparison project (see CORE-II virtual special issue of Ocean Modelling). It is the first model worldwide which provides multi-resolution functionality to large-scale ocean modeling, allowing one to bridge the gap between the scales and has the finite volume version at the current stage. FESOM_coastal treats the input/output characteristics in the same manner and share partly physical core with the global solution. It supports full coastal functionality, has cell-vortex finite volume discretization and works on any configurations of triangular, quadrangular or hybrid meshes

The role of the tsunami modeling component in the early warning framework

The talk covers the basics of tsunami modelling with a focus on sources of uncertainty in the early warning process. The tsunami scenario database for Indonesia is briefly introduced and Hovmöller diagramms along virtual SMART cables are compared for some scenarios (varying epicenter and magnitude)