Beschreibung: Data assimilation applications with high-dimensional numerical models show extreme requirements on computational resources. Thus, good scalability of the assimilation system is necessary to make these applications feasible. Sequential data assimilation methods based on ensemble forecasts, like ensemble-based Kalman filters and particle filters, provide such good scalability, because the forecast of each ensemble member can be performed independently. This parallelism has to be combined with the parallelization of both the numerical model and the data assimilation algorithm. While the filter algorithms can be implemented so that they are nearly independent from the model into which they assimilate observations, they need to be coupled to the numerical model. Using separate programs for the model and the data assimilation step coupled by disk files to exchange the model state information between model and ensemble data assimilation methods can be inefficient for high-dimensional models. More efficient is an online coupling strategy in which subroutine calls for the data assimilation are directly inserted into the model source code and augment the numerical model to become a data assimilative model. This strategy avoids model restarts as well as excessive writing of ensemble information into disk files and can hence lead to excellent computational scalability on supercomputers. The required modifications to the model code are very limited, such this strategy allows one to quickly extent a model to a data assimilation system. The online coupling is provided by the Parallel Data Assimilation Framework (PDAF, http://pdaf.awi.de), which is designed to simplify the implementation of scalable data assimilation systems based on existing numerical models. Further, it includes several optimized parallel filter algorithms. We will discuss the coupling strategy, features, and scalability of data assimilation systems based on PDAF.

Beschreibung: 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.

Beschreibung: There is an increasing public interest in sea ice information from both Polar Regions, which requires up-to-date background information and data sets at different levels for various target groups. In order to serve this interest and need, seaiceportal.de (originally: meereisportal.de) was developed as a comprehensive German knowledge platform on sea ice and its snow cover in the Arctic and Antarctic. It was launched in April 2013. Since then, the content and selection of data sets increased and the data portal received increasing attention, also from the international science community. Meanwhile, we are providing near-real time and archive data of many key parameters of sea ice and its snow cover. The data sets result from measurements acquired by various platforms as well as numerical simulations. Satellite observations of sea ice concentration, freeboard, thickness and drift are available as gridded data sets. Sea ice and snow temperatures and thickness as well as atmospheric parameters are available from autonomous platforms (buoys). Additional ship observations, ice station measurements, and mooring time series are compiled as data collections over the last decade. In parallel, we are continuously extending our meta-data and uncertainty information for all data sets. In addition to the data portal, seaiceportal.de provides general comprehensive background information on sea ice and snow as well as expert statements on recent observations and developments. This content is mostly in German in order to complement the various existing international sites for the German speaking public. We will present the portal, its content and function, but we are also asking for direct user feedback.

Beschreibung: 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).

Beschreibung: The numerical simulation code TsunAWI was developed in the framework of the German-Indonesian Tsunami Early Warning System (GITEWS). The Numerical simulation of prototypic tsunami scenarios plays a decisive role in the a priori risk assessment for coastal regions and in the early warning process itself. TsunAWI is suited for both tasks. It is based on a finite element discretisation, employs unstructured grids with high resolution along the coast, and includes inundation. This contribution presents two fields of applications. In the Indonesian tsunami early warning system, the existing TsunAWI scenario database covers the Sunda subduction zone from Sumatra to the Lesser Sunda Islands with 715 epicenters and 4500 scenarios. In a collaboration with Geoscience Australia, we support the scientific staff at the Indonesian warning center to extend the data base to the remaining tectonic zones in the Indonesian Archipelago. The extentension started for North Sulawesi, West and East Maluku Islands. For the Hydrographic and Oceanographic Service of the Chilean Navy (SHOA), we calculated a small scenario database of 100 scenarios (sources by Universidad de Chile) for a lightweight decision support system prototype (built by DLR). The earthquake and tsunami events on 1 April 2014 and 16 November 2016 showed the practical use of this approach in comparison to hind casts of these events.

Beschreibung: Das AWI hat sich den wissenschaftspolitischen Rahmenvorgaben und Herausforderungen gestellt, die Relevanz der Grundlagenforschung für die Gesellschaft zu belegen, „Wissenstransfer und -Dialoge“ sichtbar zu machen und in der Forschung zu verankern. Um dieser zunehmenden Bedeutung Rechnung zu tragen, haben wir diesem Thema im Forschungsprogramm PACES-II in Topic 4 einen hohen Stellenwert eingeräumt. Dieser Weg soll zukünftig in der Weiterentwicklung der Forschung unseres Instituts noch erkennbarer gestaltet werden. In Topic 4 “Bridging research and society – products, tools and climate services“ des PACES-II Programms wird die Kette von der Entwicklung operationeller Analyse und Vorhersagemethoden, über die Zusammenfassung von Datenstrukturen zu Datenbanken und Informationssystemen bis hin zur Entwicklung von Dialogformen und konkreten Produkten für Partner in der Gesellschaft vollzogen. Unsere Beteiligung an dieser Schnittstellenaufgabe wird bereits seit Jahren von einigen Wissenschaftlerinnen und Wissenschaftlern und durch Einrichtungen wie z.B. das Klimabüro, das Nordseebüro oder unsere Mitwirkung an der HGF Earth System Knowledge Platform gelebt. Damit wird das im AWI generierte Wissen z.B. mit gesellschaftlichen Akteuren ausgetauscht und in entscheidungsrelevante Anwendungen und Prozesse eingebracht. In unserer Veranstaltung möchten wir Beispiele für laufende Aktivitäten in diesen Bereichen vorstellen und mit Euch in eine Diskussion über Erfahrungen und Wahrnehmungen der mit dem Thema verbundenen Aufgaben und Aktivitäten im AWI eintreten.

Beschreibung: There is an increasing public interest in sea ice information from both Polar Regions, which requires up-to-date background information and data sets at different levels for various target groups. In order to serve this interest and need, seaiceportal.de (originally: meereisportal.de) was developed as a comprehensive German knowledge platform on sea ice and its snow cover in the Arctic and Antarctic. It was launched in April 2013. Since then, the content and selection of data sets increased and the data portal received increasing attention, also from the international science community. Meanwhile, we are providing near-real time and archive data of many key parameters of sea ice and its snow cover. The data sets result from measurements acquired by various platforms as well as numerical simulations. Satellite observations of sea ice concentration, freeboard, thickness and drift are available as gridded data sets. Sea ice and snow temperatures and thickness as well as atmospheric parameters are available from autonomous platforms (buoys). Additional ship observations, ice station measurements, and mooring time series are compiled as data collections over the last decade. In parallel, we are continuously extending our meta-data and uncertainty information for all data sets. In addition to the data portal, seaiceportal.de provides general comprehensive background information on sea ice and snow as well as expert statements on recent observations and developments. This content is mostly in German in order to complement the various existing international sites for the German speaking public. We will present the portal, its content and function, but we are also asking for direct user feedback.