A Flexible Approach for the Statistical Visualization of Ensemble Data
- Univ. of Utah, Salt Lake City, UT (United States). SCI Institute
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
- Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Scientists are increasingly moving towards ensemble data sets to explore relationships present in dynamic systems. Ensemble data sets combine spatio-temporal simulation results generated using multiple numerical models, sampled input conditions and perturbed parameters. While ensemble data sets are a powerful tool for mitigating uncertainty, they pose significant visualization and analysis challenges due to their complexity. We present a collection of overview and statistical displays linked through a high level of interactivity to provide a framework for gaining key scientific insight into the distribution of the simulation results as well as the uncertainty associated with the data. In contrast to methods that present large amounts of diverse information in a single display, we argue that combining multiple linked statistical displays yields a clearer presentation of the data and facilitates a greater level of visual data analysis. We demonstrate this approach using driving problems from climate modeling and meteorology and discuss generalizations to other fields.
- Research Organization:
- Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
- Sponsoring Organization:
- USDOE
- DOE Contract Number:
- W-7405-ENG-48
- OSTI ID:
- 970146
- Report Number(s):
- LLNL-PROC-417462
- Country of Publication:
- United States
- Language:
- English
Similar Records
Collaborative Exploration of Scientific Datasets Using Immersive and Statistical Visualization
Collaborative Exploration of Scientific Datasets Using Immersive and Statistical Visualization: Preprint