ALBERT

Description: Geomagnetic Virtual Observatories (GVOs) are a method for processing magnetic satellite data in order to simulate the observed behaviour of the geomagnetic field at a static location. Data are collected in a volume of space over a period of time and reduced, via the fitting of a local potential field model, to a point estimate. As low-Earth orbit satellites move very quickly but have an infrequent re-visit time to the same location, a trade off must be made between spatial and temporal resolution. Geomagnetic satellites in polar orbits that drift slowly in local time see uneven sampling of local time dependent signals unless data are gathered over a period as long as the local time drift rate. For example, four months and a radius of influence of 700km was chosen for the ESA Swarm mission.The proposed NanoMagSat constellation would include two satellites at 60° inclined orbits, and one in a near-polar orbit. The inclined orbits would provide comparatively rapid local time coverage at mid-to-low latitudes, in theory allowing GVOs to sample every three weeks compared to seventeen weeks for Swarm. We present the results of calculating GVOs from simulated NanoMagSat mission data and compare to the standard of Swarm GVOs.

Description: A spatial gradient tensor of the magnetic field can be generated from along- and across track data from Swarm, and along-track differences from CHAMP. Tensor secular variation (SV) obtained from first time differences can be inverted for advective core-surface flow, providing higher resolution than vector component data. This allows us to investigate complex regional changes in the flow, such as might be associated with localised geomagnetic jerks, and we compare the use of spatial gradients from CHAMP and Swarm. We invert for core-surface flow models directly from the spatial gradient tensor SV data without any imposed assumptions of flow geometry. We show two different types of model, both damped to minimise spatial complexity and acceleration between epochs. The first set is otherwise unconstrained. The second set has differential damping on the equatorially symmetric and asymmetric flow components in order to investigate the extent to which asymmetry is required to fit the data. The azimuthal acceleration of all models show evidence of fast westward low-latitude waves at the core-surface. During the 2017 geomagnetic jerk, our models show an abrupt westward shift in these wave-features. Previous research suggests that jerks may originate from Alfvén wave packets emitted from the inner-outer core boundary. We propose that the observed westward shift at the jerk epoch may occur when these wave-packets constructively interfere with existing Magneto-Coriolis waves at the core surface. Finally, we find it unlikely that CHAMP yielded data of sufficiently low noise to observe this proposed wave-interaction during jerks.

Description: Investigating the dynamics of liquid iron at the top of the core requires an inversion process from magnetic field measurements. Due to possible leakage, traditional spectral techniques are not optimal for regional investigations or studies of Secular Variation (first time derivative of magnetic field, SV) on short-time periods. Improved data coverage and quality from satellite missions have provided insight into short-period dynamics (such as jerks and waves), and improved understanding of localised features. However, there continues to be a need for new techniques for better spatio-temporal models of flow motions at the top of the core, especially for regional investigations. The aim of this work is to investigate regional dynamics at the Core-Mantle Boundary (CMB) using the SOLA (Subtractive Optimally Localised Averages) methodology. This method allows us to create point estimates of radial field SV at the CMB by considering global satellite measurements. The SOLA methodology allows for a local estimate of radial field SV at any desired location directly at the CMB, which opens the way to investigations of regional dynamics. Producing localised-average estimates at the CMB bypasses many problems encountered when using only a subset of magnetic satellite data, downward continuing data, and models based on spherical harmonics. Finally, we discuss how the SOLA methodology can be incorporated into the PyGeodyn code to produce core flow models. This approach can provide additional information on wave-like flow motions at the top of the Earth’s core where these are most prominent, and permits new investigations of shorter period phenomenon.

Description: Geomagnetic observations, for example from the Swarm satellites and ground observatories, are our best source of information on the dynamics of Earth’s core. However they provide direct constraints on only a small part of the core state and are often used for purely kinematic core flow inversions. Assimilation of geomagnetic observations into a fully dynamic core MHD model provides a much better way to take advantage of the observations, provided the assimilation scheme is suitably balanced and the core MHD model is appropriate. Here we report on ongoing work to use a SEEK (Singular Evolutive Extended Kalman) filter and smoother system (Pham et al. 1998, Cosme et al., 2010) to integrate satellite and ground magnetic data into a reduced (Hybrid Quasi-geostrophic-3D) model of core dynamics. The SEEK algorithm has been successfully used for data assimilation in oceanography; it involves replacing the analysis covariance matrix with a low rank SVD approximation, and does not require the integration of a large ensemble of forward models. We will review the properties of the SEEK algorithm and present experiments using auto-regressive processes using both synthetic and real geomagnetic data (virtual observatories from Swarm and CHAMP and revised 4-monthly ground observatory means). Work towards using the algorithm with a core dynamics model called MHD Pizza (Barrois et al. 2023), where the core velocity field is quasi-geostrophic but the magnetic field is 3D, will also be described.