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AGU 2015. Styles of volcanism: Forecasting, Pattern Recognition and Monitoring Developing Eruptions
From: Einat Lev <einatlev@xxxxxxxxxxxxxxxxx>AGU 2015. Styles of volcanism: Forecasting, Pattern Recognition and Monitoring Developing Eruptions
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Dear Colleagues,
We invite you to submit your abstract to our AGU 2015 Fall Meeting season titled
Styles of volcanism: Forecasting, Pattern Recognition and Monitoring Developing Eruptions
Session ID#: 9800
Session Description:
Recent effusive eruptions in Hawaii, Iceland, and Cape Verde, as well as explosive eruptions in Chile and Japan, have emphasized problems in forecasting eruptive behavior. Variations in the amount and diversity of monitoring equipment and eruptive records at different volcanoes make reliable recognition of eruption precursors difficult. Furthermore, it is challenging to incorporate both models and observations into quantitative forecasts of developing eruptions. We welcome multi-disciplinary studies that integrate petrological, experimental, and monitoring data, along with numerical simulations of eruptive processes and statistical analysis, to predict the style of volcanism and provide quantitative forecasts for hazard mitigation, including lava flow paths and advance rates. Particularly relevant are applications of machine learning methods to recognize and classify volcanic processes, investigations of magma ascent processes that impact explosivity, and studies of lava flow emplacement. We further seek to explore how near-real time monitoring can aid emergency management and mitigate developing volcanic hazards.
Session ID#: 9800
Session Description:
Recent effusive eruptions in Hawaii, Iceland, and Cape Verde, as well as explosive eruptions in Chile and Japan, have emphasized problems in forecasting eruptive behavior. Variations in the amount and diversity of monitoring equipment and eruptive records at different volcanoes make reliable recognition of eruption precursors difficult. Furthermore, it is challenging to incorporate both models and observations into quantitative forecasts of developing eruptions. We welcome multi-disciplinary studies that integrate petrological, experimental, and monitoring data, along with numerical simulations of eruptive processes and statistical analysis, to predict the style of volcanism and provide quantitative forecasts for hazard mitigation, including lava flow paths and advance rates. Particularly relevant are applications of machine learning methods to recognize and classify volcanic processes, investigations of magma ascent processes that impact explosivity, and studies of lava flow emplacement. We further seek to explore how near-real time monitoring can aid emergency management and mitigate developing volcanic hazards.
Conveners:
Michael Cassidy (Johannes Gutenberg University of Mainz, Mainz, Germany)
Hannah R Dietterich (U.S. Geological Survey, Volcano Science Center, Menlo Park, CA, USA)Kathi Unglert (University of British Columbia, Vancouver, BC, Canada)Einat Lev (Columbia University of New York, Palisades, NY, United States)
The abstract submission site
http://fallmeeting.agu.org/2015/abstract-submissions/ is now open.
Please submit your abstracts by* Wednesday, 5 August 23:59 EDT/03:59 +1 GMT. *
http://fallmeeting.agu.org/2015/abstract-submissions/ is now open.
Please submit your abstracts by* Wednesday, 5 August 23:59 EDT/03:59 +1 GMT. *
With kind regards,
Einat Lev
Lamont Assistant Research Professor
Lamont-Doherty Earth Observatory
Columbia University
New York, NY
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