Core dynamics on millennial timescales

Introduction

PALEOCORE will provide the first comprehensive observational constraints on the dynamics of Earth’s core on multi-centennial to millennial timescales. Such constraints are essential to understand the core processes responsible for the rapid decay of Earth’s dipole field strength over the past century and to forecast future field changes.

Importance of Earth's Magnetic Field

Generated through convective motions in the liquid iron core, Earth’s magnetic field acts as a shield against harmful cosmic radiation and plays a crucial role for the habitability of our planet.

Current Understanding and Limitations

The past two decades of satellite monitoring of the magnetic field, in combination with major advancements in numerical simulations of the geodynamo, have generated a wealth of knowledge on relatively rapid processes in the core.

However, due to the lack of reference data with adequate resolution, the dynamics of the core on timescales longer than the convective overturn time (~130 years) are still poorly understood. Observational constraints of core dynamics on these timescales are crucial to evaluate proposed driving mechanisms of the geodynamo.

Recent Innovations

Through recent technical innovations, models based on indirect paleomagnetic observations of Earth’s magnetic field are providing information on past field changes with unprecedented resolution. These models suggest that the recent dipole decay is part of a millennial-scale recurrent pattern associated with weak field anomalies, like the present-day South Atlantic Anomaly.

Project Aim

The aim of PALEOCORE is to construct the first ever integrated core-field core-flow model over millennial timescales to study such ancient analogues and reveal the underlying core dynamics responsible for driving these changes.

Methodology

This will be achieved through a combination of:

1. Strategic paleomagnetic data acquisition and key modelling innovations (solving bottlenecks in the current approach).
2. Incorporation of independent radionuclide data.
3. Adaptation of data assimilation algorithms for paleomagnetic data.