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Determining Earth’s Volatile Cycling using Machine Learning

Project Description

Earth’s volatile cycle is fundamental to human existence on the planet. However, precise constraints on this system have proved challenging. The transport of volatiles into the Earth at subduction zones as well as between the lower and the upper mantle at the transition zone are key. For instance, some volatiles that enter the Earth via subduction, escape during volcanic eruptions. Some volatiles rising from the lower mantle may get trapped in dense melts just above the mantle transition zone near 410 km depth. The pathways and quantities of the volatiles are important to understand the evolution of the Earth, and represent a hot, current research topic in the Earth Sciences. This project will involve putting tight constraints on both of these systems using cutting edge techniques, like machine learning, and integration with a range of interdisciplinary constraints, for a better understanding of the inputs, pathways, and fluxes of volatiles in the Earth. There are broad implications for plate tectonics, climate change, and the habitability of the planet.


Agius, M., N. Harmon, C. A. Rychert (2018) Tharimena, S., Kendall, M. Sediment characterisation beneath the PI-LAB experiment at the Mid-Atlantic Ridge from P-to-S conversions, Geophys. Res. Lett., doi: 10.1029/2018GL080565.

Meier et al., (2019) Reliable Real‐Time Seismic Signal/Noise Discrimination With Machine Learning, Journal of Geophysical Research, Solid Earth, 124, 788–800,

Bercovici, D. & Karato, S. I, (2003) Whole-mantle convection and the transition-zone water filter, Nature, v. 425.

How good is research at University of Southampton in Earth Systems and Environmental Sciences?

FTE Category A staff submitted: 68.62

Research output data provided by the Research Excellence Framework (REF)

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