dpeterson@usgs.gov
2021-06-28 17:04:43
Dear Colleagues,
We would like to draw your attention to our AGU session: "V013. Multidisciplinary Imaging of Magmatic and Hydrothermal Architecture."
A key goal of volcanology and eruption forecasting is developing process-based volcanic models, rooted in the unified understanding of magmatic system storage and evolution, that are broadly applicable and self-consistent across multiple observation types. For this session, we seek presentations that highlight the value of multiparametric investigations of volcanic systems. Of special interest are contributions that focus on the utilization of geophysical, geochemical, and geologic datasets integrated with conceptual, analytical, numerical modeling and/or inversion approaches to investigate the locations and conditions of magma storage and hydrothermal pathways and their evolution through time. We particularly encourage multidisciplinary work or contributions that leverage findings to reduce the ambiguities and uncertainties that arise when interpreting single datasets.
We hope you will consider submitting an abstract. The deadline is August 4, 2021.
Regards,
Patricia MacQueen
Mary Grace Bato
Dana E Peterson
Nathan L Andersen
We would like to draw your attention to our AGU session: "V013. Multidisciplinary Imaging of Magmatic and Hydrothermal Architecture."
A key goal of volcanology and eruption forecasting is developing process-based volcanic models, rooted in the unified understanding of magmatic system storage and evolution, that are broadly applicable and self-consistent across multiple observation types. For this session, we seek presentations that highlight the value of multiparametric investigations of volcanic systems. Of special interest are contributions that focus on the utilization of geophysical, geochemical, and geologic datasets integrated with conceptual, analytical, numerical modeling and/or inversion approaches to investigate the locations and conditions of magma storage and hydrothermal pathways and their evolution through time. We particularly encourage multidisciplinary work or contributions that leverage findings to reduce the ambiguities and uncertainties that arise when interpreting single datasets.
We hope you will consider submitting an abstract. The deadline is August 4, 2021.
Regards,
Patricia MacQueen
Mary Grace Bato
Dana E Peterson
Nathan L Andersen