Proceedings ArticleDOI
Comparative visual analysis of vector field ensembles
Mihaela Jarema,Ismail Demir,Johannes Kehrer,Rüdiger Westermann +3 more
- pp 81-88
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TLDR
A new visual analysis approach is presented to support the comparative exploration of 2D vector-valued ensemble fields that enables the user to quickly identify the most similar groups of ensemble members, as well as the locations where the variation among the members is high.Abstract:
We present a new visual analysis approach to support the comparative exploration of 2D vector-valued ensemble fields. Our approach enables the user to quickly identify the most similar groups of ensemble members, as well as the locations where the variation among the members is high. We further provide means to visualize the main features of the potentially multimodal directional distributions at user-selected locations. For this purpose, directional data is modelled using mixtures of probability density functions (pdfs), which allows us to characterize and classify complex distributions with relatively few parameters. The resulting mixture models are used to determine the degree of similarity between ensemble members, and to construct glyphs showing the direction, spread, and strength of the principal modes of the directional distributions. We also propose several similarity measures, based on which we compute pairwise member similarities in the spatial domain and form clusters of similar members. The hierarchical clustering is shown using dendrograms and similarity matrices, which can be used to select particular members and visualize their variations. A user interface providing multiple linked views enables the simultaneous visualization of aggregated global and detailed local variations, as well as the selection of members for a detailed comparison.read more
Citations
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Considerations for Visualizing Comparison
TL;DR: Four considerations that abstract comparison are presented that identify issues and categorize solutions in a domain independent manner and provide a process for developers to consider support for comparison in the design of visualization tools.
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Visualization of Time-Varying Weather Ensembles across Multiple Resolutions
TL;DR: A moment independent sensitivity measure is employed to quantify and analyze parameter sensitivity across spatial regions and time domain and a Bayesian approach is formulated to identify which regions are better predicted at which resolutions compared to the observed precipitation.
References
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BookDOI
Finite mixture models: McLachlan/finite mixture models
Geoffrey J. McLachlan,David Peel +1 more
TL;DR: The important role of finite mixture models in statistical analysis of data is underscored by the ever-increasing rate at which articles on mixture applications appear in the statistical and geospatial literature.
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Geoffrey J. McLachlan,David Peel +1 more
TL;DR: The important role of finite mixture models in the statistical analysis of data is underscored by the ever-increasing rate at which articles on mixture applications appear in the mathematical and statistical literature.
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