Interannual Fluctuations of the Core Angular Momentum Inferred from Geomagnetic Field Models

2018 ◽  
pp. 111-123
Author(s):  
Seiki Asari ◽  
Ingo Wardinski
Keyword(s):  
Angular Momentum ◽  
Geomagnetic Field ◽  
The Core ◽  
Geomagnetic Field Models ◽  
Interannual Fluctuations

Sequential modelling of the Earth magnetic field

2020 ◽  
Author(s):  
Vincent Lesur ◽  
Guillaume Ropp
Keyword(s):  
Geomagnetic Field ◽  
Magnetic Data ◽  
Mathematical Representation ◽  
High Temporal Resolution ◽  
Core Field ◽  
The Core ◽  
Earth Magnetic Field ◽  
Geomagnetic Field Models ◽  
Modelling Techniques ◽  
Derived Series

<p>Geomagnetic field models derived from satellite data cover now more than twenty years and are obtained through the processing and analyses of a massive amount of vector magnetic data. As our understanding of the geomagnetic field progresses, these models have to describe contributions of more and more sources with rather complex mathematical representation. In order to handle this increasing complexity and amount of available data, we use a sequential modelling approach (a Kalman filter), combined with a correlation based modelling step (Holschneider et al; 2016). In order to reach high temporal resolution for the core field, a sequence of snapshot models, 3-months apart, has been built. The main characteristics of the derived series of Gauss coefficients are the same as those of recently released field models based on classic modelling techniques. The results we obtained show the importance of a careful calibration of the Kalman prediction steps as well as applying Kalman smoother at the end of the modelling. We identify also the induced fields as the main limitation for an increase resolution of the core field. We will present how these induced fields have been handle in a recent version of the model and future steps to progress further in the representation of the different sources of the geomagnetic field.</p>

scholarly journals Predictions of the geomagnetic secular variation based on the ensemble sequential assimilation of geomagnetic field models by dynamo simulations

2020 ◽  
Vol 72 (1) ◽  
Author(s):  
Sabrina Sanchez ◽  
Johannes Wicht ◽  
Julien Bärenzung
Keyword(s):  
Magnetic Field ◽  
Secular Variation ◽  
Geomagnetic Field ◽  
Wave Number ◽  
Main Magnetic Field ◽  
Candidate Model ◽  
Uncertainty Estimates ◽  
Geomagnetic Field Models ◽  
Dipole Configuration

Abstract The IGRF offers an important incentive for testing algorithms predicting the Earth’s magnetic field changes, known as secular variation (SV), in a 5-year range. Here, we present a SV candidate model for the 13th IGRF that stems from a sequential ensemble data assimilation approach (EnKF). The ensemble consists of a number of parallel-running 3D-dynamo simulations. The assimilated data are geomagnetic field snapshots covering the years 1840 to 2000 from the COV-OBS.x1 model and for 2001 to 2020 from the Kalmag model. A spectral covariance localization method, considering the couplings between spherical harmonics of the same equatorial symmetry and same azimuthal wave number, allows decreasing the ensemble size to about a 100 while maintaining the stability of the assimilation. The quality of 5-year predictions is tested for the past two decades. These tests show that the assimilation scheme is able to reconstruct the overall SV evolution. They also suggest that a better 5-year forecast is obtained keeping the SV constant compared to the dynamically evolving SV. However, the quality of the dynamical forecast steadily improves over the full assimilation window (180 years). We therefore propose the instantaneous SV estimate for 2020 from our assimilation as a candidate model for the IGRF-13. The ensemble approach provides uncertainty estimates, which closely match the residual differences with respect to the IGRF-13. Longer term predictions for the evolution of the main magnetic field features over a 50-year range are also presented. We observe the further decrease of the axial dipole at a mean rate of 8 nT/year as well as a deepening and broadening of the South Atlantic Anomaly. The magnetic dip poles are seen to approach an eccentric dipole configuration.

scholarly journals Geomagnetic Virtual Observatories: monitoring geomagnetic secular variation with the Swarm satellites

2021 ◽  
Vol 73 (1) ◽  
Author(s):  
Magnus D. Hammer ◽  
Grace A. Cox ◽  
William J. Brown ◽  
Ciarán D. Beggan ◽  
Christopher C. Finlay
Keyword(s):  
Time Series ◽  
Secular Variation ◽  
Geomagnetic Field ◽  
Time Windows ◽  
Low Earth Orbit ◽  
Data Selection ◽  
Spherical Harmonic Analysis ◽  
Core Field ◽  
The Core ◽  
Swarm Satellites

AbstractWe present geomagnetic main field and secular variation time series, at 300 equal-area distributed locations and at 490 km altitude, derived from magnetic field measurements collected by the three Swarm satellites. These Geomagnetic Virtual Observatory (GVO) series provide a convenient means to globally monitor and analyze long-term variations of the geomagnetic field from low-Earth orbit. The series are obtained by robust fits of local Cartesian potential field models to along-track and East–West sums and differences of Swarm satellite data collected within a radius of 700 km of the GVO locations during either 1-monthly or 4-monthly time windows. We describe two GVO data products: (1) ‘Observed Field’ GVO time series, where all observed sources contribute to the estimated values, without any data selection or correction, and (2) ‘Core Field’ GVO time series, where additional data selection is carried out, then de-noising schemes and epoch-by-epoch spherical harmonic analysis are applied to reduce contamination by magnetospheric and ionospheric signals. Secular variation series are provided as annual differences of the Core Field GVOs. We present examples of the resulting Swarm GVO series, assessing their quality through comparisons with ground observatories and geomagnetic field models. In benchmark comparisons with six high-quality mid-to-low latitude ground observatories we find the secular variation of the Core Field GVO field intensities, calculated using annual differences, agrees to an rms of 1.8 nT/yr and 1.2 nT/yr for the 1-monthly and 4-monthly versions, respectively. Regular sampling in space and time, and the availability of data error estimates, makes the GVO series well suited for users wishing to perform data assimilation studies of core dynamics, or to study long-period magnetospheric and ionospheric signals and their induced counterparts. The Swarm GVO time series will be regularly updated, approximately every four months, allowing ready access to the latest secular variation data from the Swarm satellites.

Global propagation of interannual fluctuations in atmospheric angular momentum

Nature ◽  
1992 ◽  
Vol 357 (6378) ◽  
pp. 484-488 ◽  
Author(s):  
J. O. Dickey ◽  
S. L. Marcus ◽  
R. Hide
Keyword(s):  
Angular Momentum ◽  
Atmospheric Angular Momentum ◽  
Interannual Fluctuations

Kalmag: a high spatio temporal model of the Geomagnetic field

2021 ◽  
Author(s):  
Julien Baerenzung ◽  
Matthias Holschneider
Keyword(s):  
Geomagnetic Field ◽  
Learning Algorithm ◽  
Dynamical Evolution ◽  
Small Scale ◽  
Large Set ◽  
The Core ◽  
Resolution Model ◽  
Auto Regressive ◽  
Spatio Temporal ◽  
Marine Vessels

<p>We present a new high resolution model of the Geomagnetic field spanning the last 121 years. The model derives from a large set of data taken by low orbiting satellites, ground based observatories, marine vessels, airplane and during land surveys. It is obtained by combining a Kalman filter to a smoothing algorithm. Seven different magnetic sources are taken into account. Three of them are of internal origin. These are the core, the lithospheric  and the induced / residual ionospheric fields. The other four sources are of external origin. They are composed by a close, a remote and a fluctuating magnetospheric fields as well as a source associated with field aligned currents. The dynamical evolution of each source is prescribed by an auto regressive process of either first or second order, except for the lithospheric field which is assumed to be static. The parameters of the processes were estimated through a machine learning algorithm with a sample of data taken by the low orbiting satellites of the CHAMP and Swarm missions. In this presentation we will mostly focus on the rapid variations of the core field, and the small scale lithospheric field.  We will also discuss the nature of model uncertainties and the limitiations they imply.</p>

scholarly journals Mapping of steady-state electric fields and convective drifts in geomagnetic fields – Part 1: Elementary models

2016 ◽  
Vol 34 (1) ◽  
pp. 55-65 ◽  
Author(s):  
A. D. M. Walker ◽  
G. J. Sofko
Keyword(s):  
Magnetic Field ◽  
Steady State ◽  
Electric Field ◽  
Electric Fields ◽  
Magnetic Field Line ◽  
Geomagnetic Field ◽  
Geomagnetic Field Models ◽  
Spatial Derivatives ◽  
Field Lines ◽  
The Magnetic Field

Abstract. When studying magnetospheric convection, it is often necessary to map the steady-state electric field, measured at some point on a magnetic field line, to a magnetically conjugate point in the other hemisphere, or the equatorial plane, or at the position of a satellite. Such mapping is relatively easy in a dipole field although the appropriate formulae are not easily accessible. They are derived and reviewed here with some examples. It is not possible to derive such formulae in more realistic geomagnetic field models. A new method is described in this paper for accurate mapping of electric fields along field lines, which can be used for any field model in which the magnetic field and its spatial derivatives can be computed. From the spatial derivatives of the magnetic field three first order differential equations are derived for the components of the normalized element of separation of two closely spaced field lines. These can be integrated along with the magnetic field tracing equations and Faraday's law used to obtain the electric field as a function of distance measured along the magnetic field line. The method is tested in a simple model consisting of a dipole field plus a magnetotail model. The method is shown to be accurate, convenient, and suitable for use with more realistic geomagnetic field models.

scholarly journals Evaluation of candidate geomagnetic field models for IGRF-11

2010 ◽  
Vol 62 (10) ◽  
pp. 787-804 ◽  
Author(s):  
C. C. Finlay ◽  
S. Maus ◽  
C. D. Beggan ◽  
M. Hamoudi ◽  
F. J. Lowes ◽  
...  
Keyword(s):  
Geomagnetic Field ◽  
Geomagnetic Field Models
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