SENSOR(Web) and Overview of Metadata Flow in MOSAiC

Slides for MOSAiC Data Webinar for Chief Editors and Data Contact Person

IT-Unterstützung der Arktisexpedition MOSAiC (IT support of the Arctic Expedition MOSAiC)

Ab September 2019 beginnt die vom AWI geleitete größte Arktisexpedition aller Zeiten: Bei der MOSAiC-Expedition erforschen Wissenschaftler*innen aus 17 Nationen die Arktis mit dem Forschungsschiff Polarstern, um den Einfluss der Arktis auf das globale Klima besser zu verstehen. Antonia Immerz ist als Data Scientist in MOSAiC tätig und bildet dort die Schnittstelle zur Wissenschaft. Daniela Ransby ist Datenkuratorin für die geowissenschaftliche und umweltwissenschaftliche Datenbank PANGAEA, in der die während der MOSAiC-Expedition erfassten Daten gespeichert werden. In ihrem Vortrag berichten sie über IT-Hintergründe dieser Expedition und wie die erhobenen Daten möglichst zeitnah zu den Klimaforscher*innen gelangen und der Wissenschaft langfristig zur Verfügung stehen. (Slides provided in English

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

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)