Alexander V. Grayver

Satellite tidal magnetic signals constrain oceanic lithosphere-asthenosphere boundary

Researchers present results on the oceanic upper mantle electrical structure revealed by satellite-detected tidal magnetic signals. The tidal flow of electrically conductive oceans through the geomagnetic field results in the generation of secondary magnetic signals, which provide information on the subsurface structure. Data from the new generation of satellites were shown to contain magnetic signals due to tidal flow; however, there are no reports that these signals have been used to infer subsurface structure. We use satellite-detected tidal magnetic fields to image the global electrical structure of the oceanic lithosphere and upper mantle down to a depth of about 250 km. The model derived from more than 12 years of satellite data reveals a ≈72-km-thick upper resistive layer followed by a sharp increase in electrical conductivity likely associated with the lithosphere-asthenosphere boundary, which separates colder rigid oceanic plates from the ductile and hotter asthenosphere.

Joint Inversion of Satellite-Detected Tidal and Magnetospheric Signals Constrains Electrical Conductivity and Water Content of the Upper Mantle and Transition Zone

We present a new global electrical conductivity model of Earths mantle. The model was derived by using a novel methodology, which is based on inverting satellite magnetic field measurements from different sources simultaneously. Specifically, we estimated responses of magnetospheric origin and ocean tidal magnetic signals from the most recent Swarm and CHAMP data. The challenging task of properly accounting for the ocean effect in the data was addressed through full three-dimensional solution of Maxwells equations. We show that simultaneous inversion of magnetospheric and tidal magnetic signals results in a model with much improved resolution. Comparison with laboratory-based conductivity profiles shows that obtained models are compatible with a pyrolytic composition and a water content of 0.01 wt% and 0.1 wt% in the upper mantle and transition zone, respectively.

Do ocean tidal signals influence recovery of solar quiet variations

The solar quiet (Sq) source morphology changes on a daily basis and becomes disturbed during periods of increased magnetic activity. Therefore, it may be preferable to use single-day magnetic field recordings for the analysis of Sq variations. However, in short recordings, Sq and ocean tidal magnetic signals are often indistinguishable because of the close periods. As a result, the tidal magnetic signals can be erroneously attributed to signals of Sq origin, which can potentially lead to wrong interpretations, especially when small signals, such as those induced by the 3-D heterogeneities in the mantle, are sought. In this work, we quantitatively estimate the effect of ocean tidal signals in daily variations by performing rigorous 3-D modeling and comparing the results with real measurements from ground and sea floor observatories. We found that the vertical magnetic field component, Z, is affected the most such that at some locations the tidal signals explain the majority of the observed daily variation. Further, horizontal tidal magnetic fields at the sea floor are larger in amplitude and exhibit different spatial structures compared to signals estimated at the sea level. We propose a scheme aimed at correcting data for the ocean tidal signals and show that such correction suppresses the tidal signals in the observed field variations.

Three-Dimensional Multi-Scale and Multi-Method Inversion to Determine the Electrical Conductivity Distribution of the Subsurface (Multi-EM)

Combining different electromagnetic (EM) methods in joint inversion approaches can enhance the overall resolution power. Every method is associated with a particular sensitivity pattern. By assembling complementary patterns, subsurface imaging becomes more complete and reliable. We describe different paths to obtain multi-EM inversions. First, a joint inversion approach using finite difference forward operators is outlined that formulates the problem of minimizing the objective function using different weights for each individual method. Then we address a sequential approach using finite element methods on unstructured grids to cycle through the different EM methods iteratively. Both methods are based on a traditional parametrization using piecewise constant model parameters which may be inefficient when describing the usually rather coarse models. Therefore, we investigate wavelet-based model representations as an alternative.