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# On the modelling of M_{2} tidal magnetic signatures: effects of physical approximations and numerical resolution

- Jakub Velímský
^{1}Email authorView ORCID ID profile, - Alexander Grayver
^{2}, - Alexey Kuvshinov
^{2}and - Libor Šachl
^{1}

**Received:**10 September 2018**Accepted:**3 December 2018**Published:**11 December 2018

## Abstract

## Keywords

- Electromagnetic induction
- Ocean tides
- Ocean-mantle electromagnetic coupling

## Introduction

The phenomenon of electromagnetic fields induced in the Earth’s oceans by the motion of the conductive seawater in the presence of the main magnetic field has been known for decades (Sanford 1971). In particular, the electromagnetic signatures of the ocean flows driven by the gravitational forcing of the Sun and the Moon have recently attracted an increased interest in the geomagnetic field community. Although the existence of compound tides generated by nonlinear ocean dynamics is also well established (Einšpigel and Martinec 2017), the fundamental part of tidal flows consists of the constituents present at discrete frequencies related to the movements of the celestial bodies. This attribute allows us to distinguish the tidally induced magnetic field from the magnetic field originated in the Earth’s liquid core, in the lithosphere, or the external contributions from the magnetosphere and ionosphere, and their induced counterparts. Indeed, the magnetic signatures of the principal lunar semi-diurnal constituent \(\hbox {M}_{2}\), the larger lunar elliptic semi-diurnal constituent \(\hbox {N}_{2}\), and partially also the lunar diurnal constituent \(\hbox {O}_{1}\) have been detected in ground geomagnetic observatory data (Maus and Kuvshinov 2004) and seafloor measurements in the Northwestern Pacific (Schnepf et al. 2014). Similarly, the low-orbit satellite missions, such as CHAMP (Sabaka et al. 2015; Tyler et al. 2003) and Swarm (Sabaka et al. 2016), have successfully recovered the \(\hbox {M}_{2}\) and partially also the \(\hbox {N}_{2}\) tidally induced magnetic signals. Other tidal signal, such as \(\hbox {S}_{2}\), \(\hbox {K}_{1}\), and \(\hbox {P}_{1}\) can be obscured by external fields (Guzavina et al. 2018; Maus and Kuvshinov 2004). Consequently, the tidal signals extracted from satellite data were used to constrain the electrical conductivity across the lithosphere–asthenosphere boundary (Grayver et al. 2016, 2017). Recently, Schnepf et al. (2018) have compared the numerical predictions of magnetic fields generated by oceanic and ionospheric tides. The idea to assimilate the magnetic field measurements directly into the global ocean flow modelling has been implemented by Irrgang et al. (2017); however, tides were not considered there. Another application of the forward modelling of tidal signals is the construction of base functions optimized for tidal signal recovery from satellite and observatory data (Telschow et al. 2018).

The question of accurate calculation of the tidal magnetic signatures embraces several problems. The choice of the tidal flow model from a plethora of purely hydrodynamical or assimilative approaches definitely plays a role (Saynisch et al. 2018). The effect of the seawater conductivity and its seasonal variations has been discussed by Saynisch et al. (2016). This paper returns back to the basic physical formulation of the problem of tidally induced magnetic fields. The two-dimensional (2-D) horizontal characteristics of the tidal flows were traditionally exploited in the solution of the electromagnetic induction equation by assuming a 2-D conductive sheet of infinitesimal or finite thickness with a prescribed distribution of 2-D imposed surface electric currents. Here, we refer to a recent detailed derivation by Tyler (2017) and references therein. Another level of simplification is related to the treatment of the underlying solid mantle. In the simplest case, it is assumed to be a perfect insulator; more advanced methods allow for purely inductive, or inductive and galvanic coupling between the mantle and the ocean. Our paper aims to study the applicability of such simplifications using two state-of-the-art, fully three-dimensional (3-D) global modelling methods. Although the 3-D codes have been around for some time, only recently it has become computationally feasible to carry out such an analysis at sufficient resolutions. We do not attempt to play down the computational effectiveness of the approximate solutions. As discussed later in this manuscript, the computational costs of the fully 3-D solutions at high resolution are still prohibitive for inverse studies. Here, we merely test the validity of various physical approximations for modelling the magnetic field at the Earth’s surface and low-orbit satellite altitude induced by the principal lunar semi-diurnal constituent \(\hbox {M}_{2}\).

The paper is organized as follows. We begin by recalling the 3-D formulation of the problem stemming from the quasi-stationary Maxwell equations and proceed to a 2-D approximation. We then look at the effects of electromagnetic interaction of the ocean and mantle, treating separately the galvanic and inductive coupling. Using two independent solutions ensures that the observed effects correspond to real physical phenomena and issues of implementation, resolution, and numerical accuracy are clearly separated.

## Tidally induced magnetic field in the Earth’s oceans

### The three-dimensional electromagnetic induction equation

The solution of Eqs. (7–8) or (10) in the computational domain comprising the oceans and the solid Earth below is a challenging task, in particular in the presence of large lateral variations of conductivity, which coincide with the spatial distribution of the source term on the right-hand side. Here, we employ two numerical methods.

The elmgFD code uses the spherical harmonic-finite element approach, introduced by Martinec (1999), to solve the EMI Eq. (10). It has been recently rewritten using modern parallelized FFT and LAPACK libraries, the BiCGStab(2) iterative solver (Sleijpen and Fokkema 1993), applying an effective pre-conditioner based on the spherical harmonic solution of the 1-D problem (Martinec 1999), and incorporating the zero external field boundary condition (6) at the Earth–atmosphere interface (Velímský and Martinec 2005), and the internal forcing (5). The lateral resolution is controlled by the maximum spherical harmonic degree \(j_{\mathrm{max}}\). The code is very effective in terms of memory usage, avoiding the storage of the full problem matrix. At the highest resolution employed here, \(j_{\mathrm{max}}=480\) with 102 3-D layers in the oceans, and additional 100 1-D layers in the mantle, the calculation of one forward run required 30 GiB of memory and took about 2 days on a 12-core modern PC. Note that the memory requirements scale linearly with the total number of layers and quadratically with \(j_{\mathrm{max}}\). The duration of a single iteration scales with the third power of \(j_{\mathrm{max}}\) and linearly with the number of 3-D layers. Obviously, the total number of iterations depends on the requested accuracy, and convergence rate can be influenced also by the range of lateral conductivity variations. In general, the presented results are at the edge of practicality for single-frequency forward calculations. When employed in the inverse modelling, significant reduction of lateral and radial resolution is needed. For accurate transformations between the spatial and spherical harmonic domains by means of the Gauss–Legendre quadrature, the electrical conductivity, the tidal flows, and the solution itself are distributed on an irregular grid in colatitude, and bilinear interpolation is used for conversions to and from a regular grid.

The x3dg (Kuvshinov 2008) code is based on the contracting integral equation (CIE) approach (Pankratov et al. 1995; Singer 1995). Within the approach, the Maxwell Eqs. (7, 8) are transformed to CIE which is solved using Krylov subspace iterations with pre-calculated Green tensors for a 1-D medium. The approach allows for computing the EM fields in the Earth’s models with fully 3-D conductivity distributions. One of the advantages of the x3dg method lies in the fast iterative process with guaranteed convergence, as the condition number of the system matrix depends only on the square root of maximum lateral conductivity contrast. On the other hand, it is partially offset by the large memory requirements of the Green tensors in the current implementation and lack of parallelization for single-frequency calculations. For example, using a single ocean layer at \(0.25^\circ\) lateral resolution requires over 100 GiB of memory or swap disc space with corresponding speed penalty. The memory requirements scale quadratically with the number of 3-D layers and latitudinal resolution, quickly saturating even the most advanced shared-memory architecture available today.

### The three-dimensional and the two-dimensional approaches

The vertical velocity component stemming from the baroclinic internal tides (Kantha and Tierney 1997) is not considered here. A reliable baroclinic tidal model with assimilated altimetry data has not been published yet. Besides, the frequency shift and spread of baroclinic tides would require a multi-frequency or time-domain approach to the solution of the induction Eq. (10), a task out of the scope of the present paper.

*T*,

*s*) measurements (Tyler et al. 2017). Variable thickness of ocean, continental, and shelf sediments is also incorporated along the lines presented by Everett et al. (2003). Two cross sections of \(\sigma _{\mathrm{3D}}^{\mathrm {(T,s)}}\) are shown in the bottom panels of Fig. 2. Near the surface, the seawater conductivity shows significant variations with colatitude. In the deep oceans, the lateral variations are suppressed.

The 2-D approach presented here only suppresses the radial variations of conductivity and imposed currents in the oceans. The formulation still includes both the galvanic and inductive coupling with the underlying mantle. This is in contrast with the 2-D approach by Tyler (2017), where the galvanic coupling is omitted.

### Inductive and galvanic interaction with the underlying mantle

One of the goals of this study is to assess the importance of both inductive and galvanic coupling of the ocean magnetic field with the underlying conductive mantle. We use a recent global 1-D electrical conductivity model by Grayver et al. (2017), derived from Swarm and CHAMP satellite data using a combination of magnetospheric and tidal forcing. The profile, as shown in the upper left panel of Fig. 2, features an abrupt increase in electrical conductivity across the lithosphere–astenosphere boundary. The conductivity further increases in the transition zone in the upper mantle. A highly conductive core is also included in the model.

Two models with limited physics are calculated by both numerical methods to study the ocean–mantle interactions. In the so-called *decoupled* model, the galvanic coupling is removed. In x3dg, it is achieved by inserting a 100-m thin layer with electrical conductivity of \(10^{-12}{\hbox {S}}/{\hbox {m}}\) between the ocean and the mantle. The spherical harmonic approach elmgFD allows us to directly disable the toroidal magnetic field and hence any radial electric currents. Only the inductive interaction between the oceans and the mantle is preserved.

The second model, marked as *insulated* in the following figures and discussion, assumes an insulating mantle below the ocean. In elmgFD, a perfectly insulating analytical boundary condition is applied at \(r=a-h\), while extremely low conductivity of \(10^{-12}{\hbox {S}}/{\hbox {m}}\) is used in x3dg both for the mantle and the core. Hence, the effect of mantle conductivity is completely suppressed.

## Results

### Effect of lateral resolution and dimensionality

In the first series of runs, we have calculated the magnetic signatures of the TPXO8-atlas \(\hbox {M}_{2}\) tides using the elmgFD and x3dg codes with the 2-D settings and full physics. The electrical conductivity was assembled according to Eq. (14), and the elmgFD and x3dg solutions were, respectively, forced by the imposed electric field (16) or electric current (15). The spherical harmonic truncation degree of elmgFD was set in turn to 120, 240, and 480. Similarly, the lateral resolution of x3dg was increased from \(1^\circ \times 1^\circ\) to \(0.5^\circ \times 0.5^\circ\) and finally to \(0.25^\circ \times 0.25^\circ\). In addition, the 3-D solutions were calculated by elmgFD at the highest lateral resolution and discretizing the ocean radially into 40 and 102 layers, respectively, for the conductivity models \(\sigma _{\mathrm{3D}}\) and \(\sigma _{\mathrm{3D}}^{\mathrm {(T,s)}}\). The imposed electric field was calculated using Eq. (5) with quasi-3-D flows assembled according to Eq. (13). The large memory demands of x3dg have so far prevented us from calculating such high-resolution 3-D solutions with this code.

### Effect of conductive mantle on the tidal signatures

*decoupling*of the mantle and the

*insulating*mantle are shown in Fig. 8 by means of power spectra at the Earth’s surface. In spite of implementation differences in both methods, the behaviour is consistent. For the

*decoupled*model, the power spectra are reduced for degrees one to six and increased from degree seven onwards. This is in agreement with the theoretical arguments in Tyler (2017, Section 5.5). The spatial structure of the differences between the full 2-D model and the

*decoupled*model is shown in Fig. 9. It is concentrated into the coastal areas, with the largest differences pronounced around southern Africa, on the Australian eastern coast, in the Labrador Basin, and west of the British Isles.

*insulating*mantle, the effects become even more interesting. Judging from the spectra in Fig. 8, the amplitude of the signal is increased, especially at the lower degrees. The spatial pattern of differences, as displayed in Fig. 10, repeats most of the features from Fig. 9. However, the magnetic field is significantly strengthened over the deep oceans, missing the counteracting field generated by the large-scale induced currents in the mantle. This effect is evidently stronger than the galvanic coupling, shifting the entire spectrum upwards.

*decoupled*, and the

*insulated*solutions is provided by means of electric current density at the seafloor, as plotted, respectively, in Figs. 11, 12 and 13. The vertical currents, which are present only in the full solution, are concentrated in the coastal areas. The pattern of the horizontal electric currents is changed and the amplitude mostly weakened in both the

*decoupled*and

*insulated*solutions.

## Conclusions

The recent advances in 3-D EM modelling allow us to calculate the magnetic signatures of the ocean tides in high resolution and in the full complexity. However, various physical approximations still can provide significant reduction of computational time and/or memory requirements, which can be exploited, especially in the inversion scenarios. We have evaluated the effect of various traditional approximations. The predictions of the 2-D approach match well with the 3-D approach locally above deep oceans, or in the interpretation of low-orbit satellite data dealing with spherical harmonic degrees below 20. However, for accurate prediction of signals at the coastal and island geomagnetic observatories, or more generally, in the areas with significant variations of bathymetry and coastlines, full 3-D calculations still may be required. This conclusion does not confirm the argument presented by Tyler (2017, Section 5.2) that the Earth oceans behave as an electrically thin sheet for periods above 10 min. Note that Tyler’s criterion is based on the penetration depth of magnetic field from the boundary. However, the imposed electric currents are distributed everywhere in the ocean volume and for tidal movements do not decrease significantly with depth.

The 3-D approach presented here is still based on the 2-D barotropic tidal flows. The prediction of the magnetic field induced by the 3-D tidal flows comprising the baroclinic component (Stammer et al. 2014) has not yet been performed. Although the comparison of Saynisch et al. (2018) includes several baroclinic models, the induced magnetic field was still calculated from horizontal transports only.

The electromagnetic interactions of the oceans with the underlying conductive mantle are significant enough to be treated comprehensively in numerical modelling, including the galvanic coupling and possibility of vertical electric currents flowing from or into the mantle. The omission of the galvanic coupling leads to an underestimation of the tidal signals at degrees below six, in agreement with the analytical estimates by Tyler (2017, Section 5.5). Using a completely insulating mantle has the opposite effect.

## Declarations

### Authors' contributions

JV carried out the calculations using his own elmgFD code and the x3dg code, with support from AG and AK (its original author). LŠ contributed to data preparation and testing of the elmgFD code. JV was responsible for producing the figures and writing the manuscript with discussions and contributions from all other authors. All authors read and approved the final manuscript.

### Acknowledgements

This research was supported by the Grant Agency of the Czech Republic, Project No. P210/17-03689S, the Charles University Grant SVV 115-09/260447, and the European Space Agency Contract No. 4000109562/14/NL/CBi ‘Swarm+Oceans’. The computational resources were provided by The Ministry of Education, Youth and Sports from the Large Infrastructures for Research, Experimental Development and Innovations Project “IT4Innovations National Supercomputing Center—LM2015070”, Project ID OPEN-13-21. We thank R. Tyler, L. Erofeeva, and G. Egbert for making the 3-D electrical conductivity and the TPXO8 datasets, respectively, freely available. We also thank R. Tyler and an anonymous reviewer for their helpful comments.

### Competing interests

The authors declare that they have no competing interests.

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## Authors’ Affiliations

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