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In atmospheric sciences, sizes of data sets grow continuously due to increasing resolutions. A central task is the comparison of spatiotemporal fields, to assess different simulations and to compare simulations with observations. A significant information reduction is possible by focusing on geometric-topological features of the fields or on derived meteorological objects. Due to the huge size of the data sets, spatial features have to be extracted in time slices and traced over time. Fields with chaotic component, i.e. without 1:1 spatiotemporal correspondences, can be compared by looking upon statistics of feature properties. Feature extraction, however, requires a clear mathematical definition of the features - which many meteorological objects still lack. Traditionally, object extractions are often heuristic, defined only by implemented algorithms, and thus are not comparable. This work surveys our framework designed for efficient development of feature tracking methods and for testing new feature definitions. The framework supports well-established visualization practices and is being used by atmospheric researchers to diagnose and compare data.
In 2004, a team of researchers realized a semi-immersive interactive gallery installation, visualizing an 1834 Mediterranean garden, introduced as “italienisches Kunststück” (Italian legerdemain) by Peter Joseph Lenné. The park was originally realized on the grounds of Schloss Sanssouci in Potsdam, Germany. The installation centered on highly detailed renderings of hundreds of plants projected upon a panoramic display. Interactivity was expressed with a tangible interface which (while presently dated) we believe remains without near-precedent then or since. We present the installation (experienced by roughly 20,000 visitors), focusing on the interaction aspects. We introduce new book and table/door-format mockups. Drawing upon a heuristic of the scientist-philosopher Freeman Dyson, we consider grounded future prospect variations in the contexts of 2018, 2032, and 2202. We see this exercise as prospectively generalizing to a variety of similar and widely diverse application domains.
We present the first general scheme to describe all four types of characteristic curves of flow fields – stream, path, streak, and time lines – as tangent curves of a derived vector field. Thus, all these lines can be obtained by a simple integration of an autonomous ODE system. Our approach draws on the principal ideas of the recently introduced tangent curve description of streak lines. We provide the first description of time lines as tangent curves of a derived vector field, which could previously only be constructed in a geometric manner. Furthermore, our scheme gives rise to new types of curves. In particular, we introduce advected stream lines as a parameter-free variant of the time line metaphor. With our novel mathematical description of characteristic curves, a large number of feature extraction and analysis tools becomes available for all types of characteristic curves, which were previously only available for stream and path lines. We will highlight some of these possible applications including the computation of time line curvature fields and the extraction of cores of swirling advected stream lines.