VIII. Future thinking - what's on the horizon that could be a game-changer?  

VIII.1 New approaches using statistical methods in volcanology

Leif Karlstrom; leif@uoregon.edu
Benjamin Black; bblack.ccny@gmail.com
Jacob Richardson; jacob.a.richardson@nasa.gov
Gabor Kereszturi; kereszturi_g@yahoo.com

Statistical methods are central to robust interpretation of volcanological datasets. Such methods hold great promise, both for studying active processes where large quantities of multi-instrumental data are becoming available, and for past eruptions where community databases are becoming more complete and far-reaching. Data from observations derived above or below the surface provide different perspectives that, with proper analysis, can be merged for a more complete view of a volcano and its eruptive behavior. Statistical methods are used to evaluate data quality (including quantifying uncertainty and data coherence), interpolate over data gaps, detect changes, merge multiple datasets, correlate observations, etc. Such methods, combined with predictive and physics-based models, represent a link between modern processes and the geologic record that has the potential to integrate traditionally distinct disciplines. However, significant challenges remain due to the episodic nature of volcanism and the variety, completeness, and quality of data. We welcome contributions from any field of volcanology that emphasizes statistical analysis. We particularly seek contributions that use statistics to compare geochemistry, geophysics, physical volcanology, petrology, remote sensing, topography, InSAR, and other observational datasets with predictions from models to investigate the rich magmatic histories that lead to volcanic eruptions.