Improving geomagnetic field models for the period 1980–1999 using Ørsted data

Ultré-Guérard, Pascale; Jault, D.; Alexandrescu, Mioara; Achache, J.

doi:10.1186/bf03352158

Cited by 3 publications

(3 citation statements)

References 14 publications

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“…As only orders m ≤ 2 are concerned, we suspect here an effect of the ambiguity between internal and large length-scale external sources from instantaneous satellite observations, which largely averages out when considering only annuals means from observatories (see section 3.2). We only weakly find the negative correlations mentioned by Ultré-Guérard et al [1998] between g m n and g m nþ2 coefficients for the period 1980-2000 (see their Figure 5).…”

Section: The Secular Variation Errormentioning

confidence: 61%

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Stochastic modeling of the Earth's magnetic field: Inversion for covariances over the observatory era

Gillet

Jault

Finlay

et al. 2013

Geochem Geophys Geosyst

114

182

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[1] Inferring the core dynamics responsible for the observed geomagnetic secular variation requires knowledge of the magnetic field at the core-mantle boundary together with its associated model covariances. However, most currently available field models have been built using regularization conditions, which force the expansions in the spatial and time domains to converge but also hinder the calculation of reliable second-order statistics. To tackle this issue, we propose a stochastic approach that integrates, through time covariance functions, some prior information on the time evolution of the geomagnetic field. We consider the time series of spherical harmonic coefficients as realizations of a continuous and differentiable stochastic process. Our specific choice of process, such that it is not twice differentiable, mainly relies on two properties of magnetic observatory records (time spectra, existence of geomagnetic jerks). In addition, the required characteristic times for the low degree coefficients are obtained from available models of the magnetic field and its secular variation based on satellite data. We construct the new family COV-OBS of field models spanning the observatory and satellite era of 1840-2010. These models include the external dipole and permit sharper time changes of the internal field compared to previous regularized reconstructions. The a posteriori covariance matrix displays correlations in both space and time, which should be accounted for through the secular variation error model in core flow inversions and geomagnetic data assimilation studies.

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Section: The Secular Variation Errormentioning

confidence: 61%

“…We only weakly find the negative correlations mentioned by Ultré‐Guérard et al . [] between

g_{n}^{m}

and

g_{n + 2}^{m}

coefficients for the period 1980–2000 (see their Figure ).…”

Section: Results and Discussion Of The Cov‐obs Family Of Geomagnetic mentioning

confidence: 99%

Stochastic modeling of the Earth's magnetic field: Inversion for covariances over the observatory era

Gillet

Jault

Finlay

et al. 2013

Geochem Geophys Geosyst

114

182

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“…After decades of work generally performed in parallel but with rather little interaction, specialists of magnetic field observation, on one hand, and modeling, on the other hand, have come to interact much more recently. Papers coauthored by dynamo specialists and geophysicists observing the field over timescales ranging from real time to geological time have appeared [ Gubbins and Coe , 1993; Ultré‐Guérard et al , 1998; Glatzmaier et al , 1999; Coe et al , 2000]. Acceleration of both theoretical and numerical work has produced a number of numerical dynamo models that may have some geophysical relevance.…”

Section: Introductionmentioning

confidence: 99%

Numerical models of the geodynamo and observational constraints

Dormy

Valet

Courtillot

2000

Geochem Geophys Geosyst

164

114

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[1]0 Abstract: The past few years have seen the emergence of a large number of numerical simulations of the geodynamo. In parallel, both new and old geomagnetic, archeomagnetic, and paleomagnetic observations have been interpreted as actual geomagnetic features and used as constraints for dynamo models. Naturally, model predictions should be tested against actual characteristics of the geomagnetic field. Despite huge differences (sometimes in excess of a billion) between the values of parameters used in the simulations and those estimated for the Earth, it is intriguing that many available simulations succeed in producing largely axial dipolar magnetic fields with weaker nondipolar structures, in agreement with the first-order characteristics of the geomagnetic field. Yet, when considering finer characteristics, there are significant differences, and failures to actually produce a number of fundamental characteristic features. In this presentation, we first review numerical results obtained to date, then we attempt to summarize which field characteristics derived from observational data sets can be considered robust. On the basis of simple criteria used to evaluate the degree of confidence that can be placed in each datum, we sort presumably characteristic geomagnetic features into three categories (robust, controversial, and unlikely). We conclude that numerical models should be illustrated with a number of key``predictions,'' averaged over at least 10 dipole diffusion times. These predictions should be tested against the subset of robust observations only. Controversial observations should await additional confirmation.

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Main field and secular variation candidate models for the 12th IGRF generation after 10 months of Swarm measurements

et al. 2015

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We describe the main field and secular variation candidate models for the 12th generation of the International Geomagnetic Reference Field model. These two models are derived from the same parent model, in which the main field is extrapolated to epoch 2015.0 using its associated secular variation. The parent model is exclusively based on measurements acquired by the European Space Agency Swarm mission between its launch on 11/22/2013 and 09/18/2014. It is computed up to spherical harmonic degree and order 25 for the main field, 13 for the secular variation, and 2 for the external field. A selection on local time rather than on true illumination of the spacecraft was chosen in order to keep more measurements. Data selection based on geomagnetic indices was used to minimize the external field contributions. Measurements were screened and outliers were carefully removed. The model uses magnetic field intensity measurements at all latitudes and magnetic field vector measurements equatorward of 50°a bsolute quasi-dipole magnetic latitude. A second model using only the vertical component of the measured magnetic field and the total intensity was computed. This companion model offers a slightly better fit to the measurements. These two models are compared and discussed.We discuss in particular the quality of the model which does not use the full vector measurements and underline that this approach may be used when only partial directional information is known. The candidate models and their associated companion models are retrospectively compared to the adopted IGRF which allows us to criticize our own choices.

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Improving geomagnetic field models for the period 1980–1999 using Ørsted data

Cited by 3 publications

References 14 publications

Stochastic modeling of the Earth's magnetic field: Inversion for covariances over the observatory era

Stochastic modeling of the Earth's magnetic field: Inversion for covariances over the observatory era

Numerical models of the geodynamo and observational constraints

Main field and secular variation candidate models for the 12th IGRF generation after 10 months of Swarm measurements

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