ABSTRACT

The primary focus of the project is to develop new indirect methods to infer magmatic and vesiculation conditions in volcanic conduits and chambers from statistical analysis of bubble size distributions in vesicular volcanic products. With the appropriate mechanistic framework, bubble size distributions (BSD) should be able to provide a new dimension of understanding of volcanic systems and eruption styles to complement insights that have emerged from petrology, magma chemistry and geophysical observations. In this study, a scientific methodology will be developed for using observed bubble populations to infer the magmatic vesiculation conditions and processes that drive volcanic eruptions. The end result of the study will enable the community to use commonly available vesicular volcanic products as "remote sensing" tools that record magma history prior to and during volcanic eruptions.

To achieve this research goal, high quality "observed BSDs" will be obtained from volcanic products to compare with "simulated BSDs" resulting from numerical Monte Carlo simulations of specific vesiculation processes. A synthesis of observed and simulated BSDs will make possible "remote sensing" of magmatic conditions and volcanic eruption drivers (vesiculation processes) by studying the vesiculation history recorded in the BSDs in volcanic rocks. This will have a broader impact in allowing eruption products to be used to more effectively determine eruption processes and ultimately to predict eruption energy, style, and timing for hazard mitigation.

Please report errors in award information by writing to: awardsearch@nsf.gov.