A secular variation candidate for IGRF-14 based on core-flow inversion via an ensemble Kalman smoother

Abstract

We present a candidate mean secular variation (SV) model for the 2025.0 2030.0 period. The forecasted SV is produced with a data assimilation (DA) system built around a simple frozen-flux model of the core flow and magnetic field near the core–mantle boundary (CMB). An Ensemble Kalman Filter (EnKF) and smoother (EnKS) are used to assimilate Gauss coefficients from the Kalmag field model, to estimate a core flow which is then used to predict changes in the magnetic field. This forecast methodology is tested against past 5-year periods where it is found to be effective in predicting mean SV, and is superior to an otherwise identical setup using an EnKF alone (no EnKS). The inferred core flow is examined and is seen to exhibit structures consistent with the eccentric gyre and westward drift found in traditional inversions. While this study presents an SV candidate, its secondary purpose is to explore and highlight the potential of the EnKS methodology in understanding the geodynamo. Notably, the EnKS algorithm we use requires no adjoint for the model and can be implemented into already existing EnKF-based systems. The ease of implementation and improvement provided by the EnKS make it a desirable addition to other geomagnetic data assimilation systems, particularly those built around full, 3-D numerical dynamo models, for which the production and maintenance of an adjoint can be challenging.