Stochastic modelling of regional archaeomagnetic series

TL;DR

This paper introduces a Bayesian method to reconstruct continuous geomagnetic field series from archeomagnetic data, accounting for age uncertainties and revealing rapid variations and non-normal distributions in the data.

Contribution

A novel Bayesian approach for inferring continuous geomagnetic field series that incorporates age uncertainties and prior knowledge about geomagnetic spectra.

Findings

Reconstructed more rapid geomagnetic variations than previous studies.

Discovered that geomagnetic field element distributions are often non-normal.

Improved age estimates of archeological artifacts.

Abstract

SUMMARY We report a new method to infer continuous time series of the declination, inclination and intensity of the magnetic field from archeomagnetic data. Adopting a Bayesian perspective, we need to specify a priori knowledge about the time evolution of the magnetic field. It consists in a time correlation function that we choose to be compatible with present knowledge about the geomagnetic time spectra. The results are presented as distributions of possible values for the declination, inclination or intensity. We find that the methodology can be adapted to account for the age uncertainties of archeological artefacts and we use Markov Chain Monte Carlo to explore the possible dates of observations. We apply the method to intensity datasets from Mari, Syria and to intensity and directional datasets from Paris, France. Our reconstructions display more rapid variations than previous studies and we find that the possible values of geomagnetic field elements are not necessarily normally distributed. Another output of the model is better age estimates of archeological artefacts.