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A reduced stochastic model of core surface dynamics based on geodynamo simulations

We make use of recent geodynamo simulations to propose a reduced stochastic model of the dynamics at the surface of Earth’s core. On decadal and longer periods, this model replicates the most energetic eigen directions of the geodynamo computation. Towards shorter timescales, it proposes a compensation for weaknesses of these simulations. This model furthermore accounts for the signature, in the geomagnetic secular variation, of errors of representativeness associated with unresolved processes. We incorporate the reduced stochastic model into a geomagnetic data assimilation algorithm—an augmented state ensemble Kalman filter—and apply it to re-analyse magnetic field changes over the period 1880–2015. Errors of representativeness appear to be responsible for an important fraction of the observed changes in the secular variation, as it is the case in the dynamo simulation.Recovered core surface motions are primarily symmetric with respect to the equator. We observe the persistence of the eccentric westward gyre over the whole studied era and vortices that partly follow isocontours of the radial magnetic field at the core surface. Our flow models provide a good fit to decadal changes in the length-of-day and predict its interannual variations over the period 1940–2005. The largest core flow acceleration patterns are found in an equatorial belt below 10° in latitude and are associated with non-axisymmetric features. No systematic longitudinal drift of acceleration patterns is found, even over the past decades where satellite data are available. The acceleration of the high-latitude westward jet in the Pacific hemisphere is, during the satellite era, a factor 5 smaller than previously reported and its structure shows some evidence for equatorial asymmetry. The era of continuous satellite records provides enhanced contrast on the rapid core flow variations. The proposed assimilation algorithm offers the prospect of evaluating Earth-likeness of geodynamo simulations.