Post-processing scheme for modelling the lithospheric magnetic field

Lesur, Vincent; Rother, M.; Vervelidou, Foteini; Hamoudi, Mohamed; Thébault, Erwan

doi:10.5194/se-4-105-2013

Cited by 28 publications

(24 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Neither filtering of the data nor regularization is applied during the model estimation procedure, in contrast to other recent models of the high degree lithospheric field (Maus et al 2008;Lesur et al 2013;Olsen et al 2014). This helps highlight the differences between models constructed using only vector field data and models constructed using along-track differences of vector field data.…”

Section: I+1mentioning

confidence: 99%

“…Such models are the magnetic field (MF) model series, for example MF7 1 (Maus et al 2008), and the comprehensive model (CM) series, for example CM5 , the CHAMP, Ørsted and SAC-C model series of Earth's magnetic field (CHAOS), for example CHAOS-4 , and the GFZ reference internal magnetic model (GRIMM) series (e.g. Lesur et al 2013). Detailed discussion of recent progress in lithospheric field modelling using satellites can also be found in the reviews by Thébault et al (2010) and Olsen & Stolle (2012).…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Use of along-track magnetic field differences in lithospheric field modelling

Kotsiaros

Finlay

Olsen

2014

Geophysical Journal International

View full text Add to dashboard Cite

Section: I+1mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Use of along-track magnetic field differences in lithospheric field modelling

Kotsiaros

Finlay

Olsen

2014

Geophysical Journal International

View full text Add to dashboard Cite

“…The lithospheric field also varies in time, but on time scales that are so much longer than the time span of our data set that we can neglect them (Hulot et al 2009). The maximum SH degree used for modelling the field of internal origin is 30, although a constant field covering all SH degrees from 20 to 60 (taken from Lesur et al 2013) is subtracted from the data so that only very small contributions from the lithospheric field remain unmodelled. Therefore the estimated Gauss coefficients from SH degrees 20 to 30 are effectively only a correction to those of the subtracted model.…”

Section: O D E L Pa R a M E T R I Z At I O Nmentioning

confidence: 99%

Are geomagnetic data consistent with stably stratified flow at the core–mantle boundary?

Lesur¹,

Whaler

Wardinski³

2015

Geophysical Journal International

Self Cite

View full text Add to dashboard Cite

S U M M A R YRecent first principles calculations of the Earth's outer core thermal and electrical conductivities have raised their values by a factor of three. This has significant implications for geodynamo operation, in particular, forcing the development of a stably stratified layer at the core-mantle boundary (CMB). This study seeks to test the hypothesis of a stably stratified layer in the uppermost core by analysing geomagnetic observations made by the CHAMP satellite. An inversion method is utilized that jointly solves for the time-dependent main field and the core surface flow, where we assume the temporal variability of the main field, its secular variation (SV), to be entirely due to advective motion within the liquid outer core. The results show that a large-scale pure toroidal flow, consistent with a stably stratified layer atop the outer core, is not compatible with the observed magnetic field during the CHAMP era. However, allowing just a small amount of poloidal flow leads to a model fitting the observations satisfactorily. As this poloidal flow component is large scale, within a predominantly toroidal, essentially tangentially geostrophic flow, it is compatible with a stably stratified upper outer core. Further, our assumption of little or no diffusive SV may not hold, and a small amount of SV generated locally by diffusion might lead to a large-scale pure toroidal flow providing an acceptable fit to the data.Key words: Magnetic field; Rapid time variations; Satellite magnetics. I N T RO D U C T I O NMagnetic data are one of the rare sources of information about the motion of the iron-rich liquid forming the outer core of the Earth. It is generally accepted that the Earth's magnetic field is generated mainly in the outer core by convective flows associated with heat and light element release due to the slow freezing of the Earth's inner core. A better understanding of the evolution of the Earth's deep interior is therefore closely linked to our ability to describe this outer core flow. The magnetic field and core flow are related through the induction equation, derived directly from Maxwell's equations.Most approaches begin by deriving magnetic field models from measurements at the Earth's surface and satellite altitude. These models are then used to deduce the flow in the core, even if the modelling step somehow filters out part of the information available in the data. Several difficulties limit further our ability to describe the core flow.First, the magnetic field is measured at the Earth's surface and, after neglecting mantle electrical conductivity to allow the field to be downward continued to the core-mantle boundary (CMB), only the radial component of the poloidal part of the magnetic field is continuous across the conductivity jump there. This component can reasonably be estimated at the top of the free stream, just under the liquid viscous boundary layer (Roberts & Scott 1965;Jault & Le Mouël 1991). However, it is available only for the longest wavelengths, because the field generated...

show abstract

“…In addition, several issues surrounding SIVW should be explored, such as the optimal SH order m that delineates between the nominal and nuisance lithospheric fields, which could easily lead to better models. In addition, SIVW could be used to account for dayside bias when modeling the lithosphere, which would reflect the current best methods for crustal field modeling (Thomson and Lesur, 2007;Maus et al, 2007Maus et al, , 2008Lesur et al, 2008Lesur et al, , 2013Olsen et al, 2011). Finally, SIVW could be applied to high degree SV modeling by mitigating the bias due to the poor distribution of ground observatories.…”

Section: Discussionmentioning

confidence: 99%