Separation of the Magnetic Field into External and Internal Parts

Olsen, Nils; Glaßmeier, K.‐H.; Jia, Xianzhe

doi:10.1007/s11214-009-9563-0

Cited by 78 publications

(55 citation statements)

References 53 publications

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“…It is not possible to separate external field contributions from internal field contributions for data collected along a single meridian (Olsen et al, 2010a) -i.e. a single half-orbit -hence we can fit by least-squares the residuals defined in Eq.…”

Section: Theorymentioning

confidence: 99%

Post-processing scheme for modelling the lithospheric magnetic field

et al. 2013

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Abstract. We investigated how the noise in satellite magnetic data affects magnetic lithospheric field models derived from these data in the special case where this noise is correlated along satellite orbit tracks. For this we describe the satellite data noise as a perturbation magnetic field scaled independently for each orbit, where the scaling factor is a random variable, normally distributed with zero mean. Under this assumption, we have been able to derive a model for errors in lithospheric models generated by the correlated satellite data noise. Unless the perturbation field is known, estimating the noise in the lithospheric field model is a non-linear inverse problem. We therefore proposed an iterative post-processing technique to estimate both the lithospheric field model and its associated noise model. The technique has been successfully applied to derive a lithospheric field model from CHAMP satellite data up to spherical harmonic degree 120. The model is in agreement with other existing models. The technique can, in principle, be extended to all sorts of potential field data with "along-track" correlated errors.

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Section: Theorymentioning

confidence: 99%

Post-processing scheme for modelling the lithospheric magnetic field

et al. 2013

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“…3. However, such alongtrack corrections require some care as they suffer from spectral leakage due to the impossible separation of the various source fields (see Sabaka and Olsen, 2006;Olsen et al, 2010c). This difficulty is illustrated, for instance, by the expression of the zonal external field coefficient q 0 l that would be estimated from the magnetic field vector data measured only along a complete meridian and that would then be used to correct the data along this meridian.…”

Section: Data Correction For the Main And External Fieldsmentioning

confidence: 99%

“…For the recent CHAMP mission, the complete coverage in space and LT was achieved after about 130 days (Olsen et al, 2010b, figure 8). As a result, in such models the external magnetic fields with higher time frequen-cies may overlap with the small scale and weak lithospheric fields so that both contributions can be difficult to identify without ambiguity (e.g., Olsen et al, 2010c).…”

Section: Introductionmentioning

confidence: 99%

Swarm SCARF Dedicated Lithospheric Field Inversion chain

Thébault

Vigneron

Maus³

et al. 2013

Earth Planet Sp

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The forthcoming Swarm satellite mission is a constellation of three satellites dedicated to the study of the geomagnetic field. The orbital characteristics of the mission, which includes a pair of satellites flying side by side, has prompted new efforts in data processing and modeling. A consortium of several research institutions has been selected by the European Space Agency (ESA) to provide a number of Level-2 data products which will be made available to the scientific community. Within this framework, specific tools have been tailor-made to better recover the lithospheric magnetic field contribution. These tools take advantage of gradient properties measured by the lower pair of Swarm satellites and rely on a regional modeling scheme designed to better detect signatures of small spatial scales. We report on a processing chain specifically designed for the Swarm mission. Using an End-to-End simulation, we show that the tools developed are operational. The chain generates a model that meets the primary scientific objectives of the Swarm mission. We also discuss refinements that could also be implemented during the Swarm operational phase to further improve lithospheric field models and reach unprecedented spatial resolution.

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“…In this kind of dynamic environment interspersed with local electrical currents, the classic Gauss algorithm fails to separate internal and external magnetic fields in a classical spherical harmonic expansion (Gauss, 1839;Olsen et al, 2010;Glassmeier and Tsurutani, 2014). In addition, spacecraft missions provide only incomplete spatial coverage.…”

Section: Introductionmentioning

confidence: 99%

Estimation of a planetary magnetic field using a reduced magnetohydrodynamic model

2017

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Abstract. Knowledge of planetary magnetic fields provides deep insights into the structure and dynamics of planets. Due to the interaction of a planet with the solar wind plasma, a rather complex magnetic environment is generated. The situation at planet Mercury is an example of the complexities occurring as this planet's field is rather weak and the magnetosphere rather small. New methods are presented to separate interior and exterior magnetic field contributions which are based on a dynamic inversion approach using a reduced magnetohydrodynamic (MHD) model and time-varying spacecraft observations. The methods select different data such as bow shock location information or magnetosheath magnetic field data. Our investigations are carried out in preparation for the upcoming dual-spacecraft BepiColombo mission set out to precisely estimate Mercury's intrinsic magnetic field. To validate our new approaches, we use THEMIS magnetosheath observations to estimate the known terrestrial dipole moment. The terrestrial magnetosheath provides observations from a strongly disturbed magnetic environment, comparable to the situation at Mercury. Statistical and systematic errors are considered and their dependence on the selected data sets are examined. Including time-dependent upstream solar wind variations rather than averaged conditions significantly reduces the statistical error of the estimation. Taking the entire magnetosheath data along the spacecraft's trajectory instead of only the bow shock location into account further improves accuracy of the estimated dipole moment.

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Separation of the Magnetic Field into External and Internal Parts

Cited by 78 publications

References 53 publications

Post-processing scheme for modelling the lithospheric magnetic field

Post-processing scheme for modelling the lithospheric magnetic field

Swarm SCARF Dedicated Lithospheric Field Inversion chain

Estimation of a planetary magnetic field using a reduced magnetohydrodynamic model

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