- Determination of significant associations between interrelated climate simulation parameters and outputs is a challenge due to the rapid increases in data quantity, quality, and the number of different variables.
- Classical approaches restrict exploration.
- Integrate automated statistical analytics with interactive information visualization techniques to guide the analyst to significant associations.
- Exploratory analysis of large CLM4 ensembles in close collaboration with model researchers from ORNL, PNNL, and LANL.
- Dynamic visual queries provide “live” access to data behind the visualization.
Benefits and Highlights
- Interactive exploratory analysis provides intuitive dynamic visual queries to allow hypothesis generation and validation.
- Facilitates simultaneous analysis large multi-dimensional data in a single 2-D display.
- Can reveals unexpected relationships and serendipitous discoveries.
Department of Energy (DOE)