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Machine learning thermobarometry and chemometry using amphibole and clinopyroxene: a window into the roots of an arc volcano (Mount Liamuiga, Saint Kitts)

Machine learning thermobarometry and chemometry using amphibole and clinopyroxene: a window into the roots of an arc volcano (Mount Liamuiga, Saint Kitts)

This is a Preprint and has not been peer reviewed. The published version of this Preprint is available: http://doi.org/10.1007/s00410-021-01874-6. This is version 2 of this Preprint.

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Authors

Oliver John Higgins, Tom Sheldrake , Luca Caricchi 

Abstract

The physical and chemical properties of magma govern the eruptive style and behaviour of volcanoes. Many of these parameters are linked to the storage pressure and temperature of the erupted magma, and melt chemistry. However, reliable single-phase thermobarometers and chemometers which can recover this information, particularly using amphibole chemistry, remain elusive. We present a suite of single-phase amphibole and clinopyroxene thermobarometers and chemometers, calibrated using machine learning. This approach allows us to intimately track the range of pre-eruptive conditions over the course of a millennial eruptive cycle on an island arc...  more

DOI

https://doi.org/10.31223/X5GD0W

Subjects

Earth Sciences, Geochemistry, Mineral Physics, Stratigraphy, Volcanology

Keywords

stratigraphy, anorthite, single-phase, Mansion Series, compositional gap

Dates

Published: 2021-07-05 02:46

Last Updated: 2021-07-05 09:47

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License

CC BY Attribution 4.0 International

Additional Metadata

Conflict of interest statement:
None

Data Availability (Reason not available):
Upon request to the author