Geomagnetic field evolution from models and vice versa - Richard Bono - 2021 MagIC Workshop(1/21/21)
Channel: Magnetics Information Consortium (MagIC)
Date: 2021-01-22

"DEEP thoughts: insights on geomagnetic field evolution from models, and vice versa " by Richard Bono, School of Environmental Sciences, University of Liverpool

Talk presented at the virtual 2021 MagIC Workshop (https://earthref.org/events/MAGIC/2021/) - Rock and Paleomagnetism through Time and Space. Jan 19th-21st, 2021.

Abstract:
The geodynamo is a long-lived feature of Earth, which allows for inferences on the evolution of Earth’s interior and can be observed through indirect records retained in the rock record. Paleomagnetism allows for instantaneous and time-averaged records of the field to be recovered from rocks back to the Hadean. However, continuous records of the paleomagnetic field of comparable resolution to modern magnetic observatories cannot be achieved. Therefore, statistical field models and numerical dynamo simulations are necessary to better understand the geodynamo. Here we discuss new insights on the long-term evolution of the field, highlighting recent advances in defining trends of field dipolarity and strength, as well as recognizing non-GAD contributions to the field and intervals of very weak field strengths. These new observations allow for insight into evolution of the core and mantle and inferences on the timing of inner core growth and the fixity of Large Low Shear Velocity Provinces (LLSVPs). We further discuss new efforts to use these data to impose requirements on new models and simulations so that they better reproduce the long-term features of the geomagnetic field. 

Based on trends identified in numerical dynamo simulations, we have defined a new proxy for field dipolarity, termed axial dipole dominance. Using paleomagnetic datasets spanning the past 10 million years through the Archean the following inference can be made: the geomagnetic field has been primarily dipolar for most of Earth’s history. However, there is evidence for non-axial dipole components of the field persisting for millions of years, identified in both the signals of the South Atlantic Anomaly since least 10 Ma and in global paleosecular variation datasets (PSV10; Cromwell et al., 2018).  Additionally, new paleointensity data spanning the Devonian through Neoproterozoic suggest that several intervals record extended periods of very weak field strengths (5x to 10x weaker than present day), hinting that there are much larger than million-year influences on magnetic field variation.

These new observations can now serve as set of benchmarks for the next generation of numerical dynamo simulations. The widely used criteria of Christensen et al. (2010), which assess whether a dynamo resembles the present-day field, can be complemented by a set of criteria which examines the time-averaged field. In 2019, we introduced the QPM criteria (Sprain et al., 2019) to identify numerical simulations which best reproduce time-averaged field properties for the past 10 million years. Generally, we found that dynamos which are driven by chemical convection are able to maintain the necessary to simultaneously satisfy our criteria, whereas purely thermally driven dynamos are unable to meet these criteria.  

We have been able to identify a suite of dynamo simulations which are most ‘Earth-like’ using the QPM criteria, allowing for further analysis and application. One such finding is the robust occurrence of a clearly defined covariance among Gauss coefficients, a feature which is consistent with dynamo theory, but often overlooked when considering the statistical properties of the time-averaged field. This covariance has now been incorporated into a new family of giant Gaussian process field models we have named BB18. Our models can reproduce the time-average and spatial correlations observed in the geomagnetic field for the past 10 million years.

The QPM criteria and covariant giant Gaussian process models are flexible tools which can be adapted for other intervals of time when sufficient data are available. We now have a framework which allows us to compare observations from paleomagnetism and numerical dynamo simulations. This framework can then be used to refine the dynamo parameters to produce simulations which best reproduce paleomagnetic observations for different intervals of time. The new dynamo simulations will, in turn, allow for the integration of sparsely distributed paleomagnetic observations into a more informative description of the geodynamo and for new insights into core processes.