The Swarm End-to-End mission simulator study: A demonstration of separating the various contributions to Earth’s magnetic field using synthetic data

Olsen, Nils; Haagmans, Roger; Sabaka, Terence J.; Kuvshinov, A. V.; Maus, Stefan; Purucker, Michael E.; Rother, M.; Lesur, Vincent; Mandéa, Mioara

doi:10.1186/bf03351934

Cited by 65 publications

(50 citation statements)

References 22 publications

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“…While testing modeling schemes using the End-to-End synthetic data set for the preparation of the Swarm-Mission (Olsen et al, 2006a), it has been revealed that this slowly increasing lithospheric field contribution leaks into the secular variation (SV) model. In order to avoid this aliasing effect, the GRIMM lithospheric field model from SH degree 17 to degree 80 is subtracted from the data in a preprocessing phase.…”

Section: Model Parameterizationmentioning

confidence: 99%

The second generation of the GFZ Reference Internal Magnetic Model: GRIMM-2

et al. 2010

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We present the second generation of the GFZ Reference Internal Magnetic Model (GRIMM-2), that was derived for the preparation of the GFZ candidate for the 11th generation of the IGRF. The model is built by fitting a vector data set made of CHAMP satellite and observatory data, spanning the period 2001.0 to 2009.5. The data selection technique and the model parametrization are similar to that used for the derivation of the GRIMM model (Lesur et al., 2008). The obtained model is robust over the time span of the data. However, the secular variation above spherical harmonic degree 13 becomes less controlled by the data and is constrained by the applied regularization before 2002 and after 2008.5. At best, only the spherical harmonic degrees 3 to 6 are robustly estimated for the secular acceleration. The problem associated with the first two spherical harmonic degrees of the secular acceleration model arise from the difficulty in separating the core field signal from the external fields and their internally induced counterparts. The regularization technique applied smoothes the magnetic field model in time. This affects all spherical harmonic degrees, but starts to be significant at spherical harmonic degree 5.

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Section: Model Parameterizationmentioning

confidence: 99%

The second generation of the GFZ Reference Internal Magnetic Model: GRIMM-2

et al. 2010

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“…7, third panel from top). The simulated data contains magnetospheric sources up to spherical harmonic degree 3 and order 1 and induced degrees and orders up to 45 (Olsen et al, 2006). Due to a narrow local-time sampling by the Swarm satellites, especially at the start of the mission when all three satellites are in the same orbit plane, a source characterised by a spherical harmonic term of order 1 fixed in local-time could appear as a spurious signal in the FTMM with a period equal to the local-time repeat period of the satellites.…”

Section: Hour Local Time Selectionmentioning

confidence: 99%

Rapid modelling of the large-scale magnetospheric field from Swarm satellite data

Hamilton

2013

Earth Planet Sp

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As part of the European Space Agency (ESA) Swarm mission, ESA has commissioned an independent scientific consortium known as the Swarm satellite Constellation Application and Research Facility (SCARF) to develop and operate the Level 2 Processor (L2PS). Its purpose is to derive high quality scientific products from the mission's data. One such product is the Fast-Track Magnetospheric Model (FTMM), which is a model of the large scale vector magnetospheric field and its induced counterpart. This model is generated once per satellite orbit, in near real-time by a robust, autonomous algorithm. Its intended use is similar to that of the Disturbance storm time Index (Dst): characterising the rapidly varying magnetospheric field, as an input to other global field models, and for the space weather community. In this paper we describe in detail the FTMM algorithm and assess its ability to recover the magnetospheric component from the consortium's test satellite data set as well as real data from the CHAMP satellite.

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“…Fournier et al: A case for variational geomagnetic data assimilation with the launch of the SWARM mission around 2010 (Olsen et al, 2006b). …”

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confidence: 99%

A case for variational geomagnetic data assimilation: insights from a one-dimensional, nonlinear, and sparsely observed MHD system

Fournier¹,

Eymin²,

Alboussière³

2007

Nonlin. Processes Geophys.

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Abstract. Secular variations of the geomagnetic field have been measured with a continuously improving accuracy during the last few hundred years, culminating nowadays with satellite data. It is however well known that the dynamics of the magnetic field is linked to that of the velocity field in the core and any attempt to model secular variations will involve a coupled dynamical system for magnetic field and core velocity. Unfortunately, there is no direct observation of the velocity. Independently of the exact nature of the abovementioned coupled system -some version being currently under construction -the question is debated in this paper whether good knowledge of the magnetic field can be translated into good knowledge of core dynamics. Furthermore, what will be the impact of the most recent and precise geomagnetic data on our knowledge of the geomagnetic field of the past and future? These questions are cast into the language of variational data assimilation, while the dynamical system considered in this paper consists in a set of two oversimplified one-dimensional equations for magnetic and velocity fields. This toy model retains important features inherited from the induction and Navier-Stokes equations: nonlinear magnetic and momentum terms are present and its linear response to small disturbances contains Alfvén waves. It is concluded that variational data assimilation is indeed appropriate in principle, even though the velocity field remains hidden at all times; it allows us to recover the entire evolution of both fields from partial and irregularly distributed information on the magnetic field. This work constitutes a first step on the way toward the reassimilation of historical geomagnetic data and geomagnetic forecast.

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The Swarm End-to-End mission simulator study: A demonstration of separating the various contributions to Earth’s magnetic field using synthetic data

Cited by 65 publications

References 22 publications

The second generation of the GFZ Reference Internal Magnetic Model: GRIMM-2

The second generation of the GFZ Reference Internal Magnetic Model: GRIMM-2

Rapid modelling of the large-scale magnetospheric field from Swarm satellite data

A case for variational geomagnetic data assimilation: insights from a one-dimensional, nonlinear, and sparsely observed MHD system

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