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Correlations and variability in Pliocene Western US volcanism: Difference between revisions

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(New page: ==People== Leif Karlstrom Sam Scarpino Yixian Song Griffith Rees ==Project Abstract== Volcanoes are outputs to a hidden transport network of magma in the Earth's crust. We hope to use ...)
 
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Griffith Rees
Griffith Rees
Tracey McDole


==Project Abstract==
==Project Abstract==
Volcanoes are outputs to a hidden transport network of magma in the Earth's crust. We hope to use the NAVDAT geologic dataset from volcanoes around the Western US to constrain the topology and dynamics of this network. These data include approximate ages and location of eruptions (best constrained in the last 5.2 Million years - the Pliocene Epoch), along with compositional data that may be used to infer timescales and processes within the network. This project includes statistical analysis of data, network inference, and forward dynamic modeling.
Volcanoes are outputs to a hidden transport network of magma in the Earth's crust. We hope to use the NAVDAT geologic dataset from volcanoes around the Western US to constrain the topology and dynamics of this network. These data include approximate ages and location of eruptions (best constrained in the last 5.2 Million years - the Pliocene Epoch), along with compositional data that may be used to infer timescales and processes within the network. This project includes statistical analysis of data, network inference, and forward dynamic modeling.

Latest revision as of 04:37, 25 June 2010

People

Leif Karlstrom

Sam Scarpino

Yixian Song

Griffith Rees

Tracey McDole

Project Abstract

Volcanoes are outputs to a hidden transport network of magma in the Earth's crust. We hope to use the NAVDAT geologic dataset from volcanoes around the Western US to constrain the topology and dynamics of this network. These data include approximate ages and location of eruptions (best constrained in the last 5.2 Million years - the Pliocene Epoch), along with compositional data that may be used to infer timescales and processes within the network. This project includes statistical analysis of data, network inference, and forward dynamic modeling.