Aims & Objectives
Accurate predictions in weather and climate research require complex physical models, adequate discrete models and efficient solution methods. Typically, a very high number of unknowns and a substantial computational effort is related to the calculation of corresponding numerical simulations. The amount of created data can be enormous. Therefore, in many cases only a small portion of this data is stored for later analysis. One common data reduction approach is to store the system's state only at certain points in time, e.g. in one hour steps, while for the numerical simulation time steps of seconds or minutes was required.
The exploration of the these data sets is challenging, since it is typically three-dimensional, time-dependent and multi-dimensional (e.g. including chemical species). Modern visualization techniques in combination with an immersive 3D visualization environment can help to get a profound understanding of the complex physical processes and structures that are contained in the investigated scenarios. For best perception of the data, high resolution with respect to the spatial and the temporal structure are needed.
We investigate simplified physical models that can be solved significantly faster compared to the original models. This approach allows to increase the temporal resolution and leads to model-based interpolation of the previously reduced data, stored during the numerical simulation.
Data reconstruction in time: Error of linear interpolation at interval's center (purple), error of model-based approach at interval's center (yellow) and interval's end (red). Computational efforts of model-based reconstruction (blue) declines with larger viscosity parameter.
- Institute for Meteorology and Climate Research (IMK), Karlsruhe Institute for Technology (KIT)
- Deutscher Wetterdienst (DWD)
- Martin Baumann (EMCL)
- Prof. Dr. Vincent Heuveline (EMCL)
- Jonas Kratzke (EMCL)
- Bernhard Vogel (IMK)
- Heike Vogel (IMK)
- Ivan Zapryanov (Sofia University): until 2012
- Martin Baumann (EMCL)
- M. Baumann, J. Förstner, V. Heuveline, J. Kratzke, S. Ritterbusch, B. Vogel, H. Vogel, Model-based Visualization of Instationary Geo-Data with Application to Volcano Ash Data, in: W. Freeden, Z. Nahed, T. Sonar (eds.), Handbook of Geomathematics (2nd ed.), Springer (2015).
- Zapryanov, Ivan: Interpolation Operators for 3D volcanic ash visualization, Master's thesis, Karlsruhe Institute of Technology, 2012.
- see the animaion also on the via the Springer website