Essential Site Maintenance: Authorea-powered sites will be updated circa 15:00-17:00 Eastern on Tuesday 5 November.
There should be no interruption to normal services, but please contact us at [email protected] in case you face any issues.

loading page

DFENS: Diffusion chronometry using Finite Elements and Nested Sampling
  • +2
  • Euan Mutch,
  • John Maclennan,
  • Oliver Shorttle,
  • John Rudge,
  • David Neave
Euan Mutch
University of Maryland

Corresponding Author:[email protected]

Author Profile
John Maclennan
University of Cambridge
Author Profile
Oliver Shorttle
University of Cambridge
Author Profile
John Rudge
University of Cambridge
Author Profile
David Neave
University of Manchester
Author Profile

Abstract

In order to reconcile petrological and geophysical observations in the temporal domain, the uncertainties of diffusion timescales need to be rigorously assessed. Here we present a new diffusion chronometry method: Diffusion chronometry using Finite Elements and Nested Sampling (DFENS). This method combines a finite element numerical model with a nested sampling Bayesian inversion meaning the uncertainties of the parameters that contribute to diffusion timescale estimates can be rigorously assessed, and that observations from multiple elements can be used to better constrain a single timescale. By accounting for the covariance in uncertainty structure in the diffusion parameters, estimates on timescale uncertainties can be reduced by a factor of 2 over assuming that these parameters are independent of each other. We applied the DFENS method to the products of the Skuggafjöll eruption from the Bárðarbunga volcanic system in Iceland, which contains zoned macrocrysts of olivine and plagioclase that record a shared magmatic history. Olivine and plagioclase provide consistent pre-eruptive mixing and mush disaggregation timescales of less than 1 year. The DFENS method goes some way to improving our ability to rigorously address the uncertainties of diffusion timescales, but efforts still need to be made to understand other systematic sources of uncertainty such as crystal morphology, appropriate choice of diffusion coefficients, growth, and the petrological context of diffusion timescales.
Apr 2021Published in Geochemistry, Geophysics, Geosystems volume 22 issue 4. 10.1029/2020GC009303