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 secular variation forecast using the NASA GEMS ensemble Kalman fllter: A candidate model for IGRF 2020

2020 ◽  
Author(s):  
Andrew Tangborn ◽  
Weijia Kuang ◽  
Terence Sabaka ◽  
Ce Yi
Keyword(s):  
Secular Variation ◽  
Ensemble Kalman Filter ◽  
Geomagnetic Field ◽  
Candidate Model ◽  
Model Bias ◽  
Geomagnetic Secular Variation ◽  
Forecast Period ◽  
Time Period ◽  
Correction Scheme ◽  
Geomagnetic Field Models

Abstract We have produced a 5 year mean secular variation (SV) of the geomagnetic field for the period 2020-2025. We use the NASA Geomagnetic Ensemble Modeling System (GEMS), which consists of the NASA Goddard geodynamo model and ensemble Kalman filter (EnKF) with 512 ensemble members. Geomagnetic field models are used as observations for the assimilation, including gufm1 (1590-1960), CM4 (1961-2000) and CM6 (2001-2019). The forecast involves a bias correction scheme that assumes that the model bias changes on timescales much longer than the forecast period, so that they can be removed by successive forecasts. The algorithm was validated on the time period 2010-2015 by comparing with the 2015 IGRF before being applied to the 2020-2025 time period. This forecast has been submitted as a candidate model for IGRF 2025.

scholarly journals Physics-based secular variation candidate models for the IGRF

2021 ◽  
Vol 73 (1) ◽  
Author(s):  
Alexandre Fournier ◽  
Julien Aubert ◽  
Vincent Lesur ◽  
Erwan Thébault
Keyword(s):  
Magnetic Field ◽  
Satellite Data ◽  
Secular Variation ◽  
Surface Flow ◽  
Lessons Learned ◽  
Rate Of Change ◽  
Main Magnetic Field ◽  
Time Rate ◽  
Gauss Coefficient

AbstractEach International Geomagnetic Reference Field (IGRF) model released under the auspices of the International Association of Geomagnetism and Aeronomy comprises a secular variation component that describes the evolution of the main magnetic field anticipated for the 5 years to come. Every Gauss coefficient, up to spherical harmonic degree and order 8, is assumed to undergo its own independent linear evolution. With a mathematical model of the core magnetic field and its time rate of change constructed from geomagnetic observations at hand, a standard prediction of the secular variation (SV) consists of taking the time rate of change of each Gauss coefficient at the final time of analysis as the predicted rate of change. The last three generations of the IGRF have additionally witnessed a growing number of candidate SV models relying upon physics-based forecasts. This surge is motivated by satellite data that now span more than two decades and by the concurrent progress in the numerical modelling of Earth’s core dynamics. Satellite data reveal rapid (interannual) geomagnetic features whose imprint can be detrimental to the quality of the IGRF prediction. This calls for forecasting frameworks able to incorporate at least part of the processes responsible for short-term geomagnetic variations. In this letter, we perform a retrospective analysis of the performance of past IGRF SV models and candidates over the past 35 years; we emphasize that over the satellite era, the quality of the 5-year forecasts worsens at times of rapid geomagnetic changes. After the definition of the time scales that are relevant for the IGRF prediction exercise, we cover the strategies followed by past physics-based candidates, which we categorize into a “‘core–surface flow” family and a “dynamo” family, noting that both strategies resort to “input” models of the main field and its secular variation constructed from observations. We next review practical lessons learned from our previous attempts. Finally, we discuss possible improvements on the current state of affairs in two directions: the feasibility of incorporating rapid physical processes into the analysis on the one hand, and the accuracy and quantification of the uncertainty impacting input models on the other hand.

scholarly journals The CSES global geomagnetic field model (CGGM): an IGRF-type global geomagnetic field model based on data from the China Seismo-Electromagnetic Satellite

2021 ◽  
Vol 73 (1) ◽  
Author(s):  
Yanyan Yang ◽  
Gauthier Hulot ◽  
Pierre Vigneron ◽  
Xuhui Shen ◽  
Zeren Zhima ◽  
...  
Keyword(s):  
Magnetic Field ◽  
Secular Variation ◽  
Geomagnetic Field ◽  
Field Model ◽  
Magnetic Data ◽  
Candidate Model ◽  
Main Field ◽  
Data Set ◽  
Geomagnetic Field Model ◽  
Time Period

AbstractUsing magnetic field data from the China Seismo-Electromagnetic Satellite (CSES) mission, we derive a global geomagnetic field model, which we call the CSES Global Geomagnetic Field Model (CGGM). This model describes the Earth’s magnetic main field and its linear temporal evolution over the time period between March 2018 and September 2019. As the CSES mission was not originally designed for main field modelling, we carefully assess the ability of the CSES orbits and data to provide relevant data for such a purpose. A number of issues are identified, and an appropriate modelling approach is found to mitigate these. The resulting CGGM model appears to be of high enough quality, and it is next used as a parent model to produce a main field model extrapolated to epoch 2020.0, which was eventually submitted on October 1, 2019 as one of the IGRF-13 2020 candidate models. This CGGM candidate model, the first ever produced by a Chinese-led team, is also the only one relying on a data set completely independent from that used by all other candidate models. A successful validation of this candidate model is performed by comparison with the final (now published) IGRF-13 2020 model and all other candidate models. Comparisons of the secular variation predicted by the CGGM parent model with the final IGRF-13 2020–2025 predictive secular variation also reveal a remarkable agreement. This shows that, despite their current limitations, CSES magnetic data can already be used to produce useful IGRF 2020 and 2020–2025 secular variation candidate models to contribute to the official IGRF-13 2020 and predictive secular variation models for the coming 2020–2025 time period. These very encouraging results show that additional efforts to improve the CSES magnetic data quality could make these data very useful for long-term monitoring of the main field and possibly other magnetic field sources, in complement to the data provided by missions such as the ESA Swarm mission.

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 Bulgarian Geomagnetic Reference Field (BulGRF) for 2015.0 and secular variation prediction model up to 2020

2017 ◽  
Vol 35 (5) ◽  
pp. 1085-1092
Author(s):  
Metodi Metodiev ◽  
Petya Trifonova
Keyword(s):  
Secular Variation ◽  
Geomagnetic Field ◽  
Field Model ◽  
Field Measurements ◽  
Reference Field ◽  
Main Field ◽  
Close Match ◽  
Secular Variation Model ◽  
Geomagnetic Field Models ◽  
Annual Means

Abstract. The Bulgarian Geomagnetic Reference Field (BulGRF) for 2015.0 epoch and its secular variation model prediction up to 2020.0 is produced and presented in this paper. The main field model is based on the well-known polynomial approximation in latitude and longitude of the geomagnetic field elements. The challenge in our modelling strategy was to update the absolute field geomagnetic data from 1980.0 up to 2015.0 using secular measurements unevenly distributed in time and space. As a result, our model gives a set of six coefficients for the horizontal H, vertical Z, total field F, and declination D elements of the geomagnetic field. The extrapolation of BulGRF to 2020 is based on an autoregressive forecasting of the Panagyurishte observatory annual means. Comparison of the field values predicted by the model with Panagyurishte (PAG) observatory annual mean data and two vector field measurements performed in 2015 shows a close match with IGRF-12 values and some difference with the real (measured) values, which is probably due to the influence of crustal sources. BulGRF proves to be a reliable alternative to the global geomagnetic field models which together with its simplicity makes it a useful tool for reducing magnetic surveys to a common epoch carried out over the Bulgarian territory up to 2020.

A comparison of geomagnetic secular variation as recorded by historical, archaeomagnetic and palaeomagnetic measurements

1982 ◽  
Vol 306 (1492) ◽  
pp. 103-112 ◽  
Keyword(s):  
Magnetic Field ◽  
Lake Sediments ◽  
Secular Variation ◽  
Geomagnetic Field ◽  
Secular Change ◽  
Mathematical Approach ◽  
Geomagnetic Secular Variation ◽  
The Past ◽  
Palaeomagnetic Data ◽  
Field Behaviour

Palaeomagnetic methods can extend the documentary record of changes in the Earth’s magnetic field far into the past. Tolerable agreement is found between various methods, demonstrating the geophysical value of palaeomagnetic experiments. Combining results from the different approaches of investigating secular change can lead to a better perspective and to superior models of geomagnetic field behaviour. Lake sediments have recently been found to hold remarkably detailed signatures of past field changes. A mathematical approach to formulating an empirical description of global geomagnetic field behaviour is proposed and applied to palaeomagnetic data spanning the last 10 ka.

Observations of the Earth's magnetic field made in Edinburgh from 1670 to the present day

1994 ◽  
Vol 85 (4) ◽  
pp. 239-252 ◽  
Author(s):  
D. R. Barraclough
Keyword(s):  
Magnetic Field ◽  
Mathematical Models ◽  
Secular Variation ◽  
Geomagnetic Field ◽  
Upper Atmosphere ◽  
The Difference ◽  
Time Changes ◽  
Relative Measurements ◽  
Magnetic North ◽  
Made In

AbstractMagnetic observations made at the same site give valuable information about the time changes (the secular variation) of the geomagnetic field. This paper gives details of all known measurements of the geomagnetic field in and around Edinburgh since the earliest observation of magnetic declination (the difference between true and magnetic north) by George Sinclair in 1670. Early observations of the strength of the field were only relative measurements. Approximate conversion factors are derived to enable these data to be expressed in modern absolute units (nanoteslas). Observed values of declination, inclination and the horizontal intensity of the geomagnetic field are plotted and compared with values computed from mathematical models of the field covering the interval 1690 to 1990, inclusive. The earlier observations were not corrected for the effects of the rapidly varying magnetic fields caused by electric currents in the upper atmosphere. The consequences of this are estimated.

scholarly journals Geomagnetic core field models and secular variation forecasts for the 13th International Geomagnetic Reference Field (IGRF-13)

2020 ◽  
Author(s):  
Ingo Wardinski ◽  
Diana Saturnino ◽  
Hagay Amit ◽  
Aude Chambodut ◽  
Benoit Langlais ◽  
...  
Keyword(s):  
Secular Variation ◽  
Geomagnetic Field ◽  
Singular Spectrum Analysis ◽  
Reference Field ◽  
Candidate Model ◽  
Main Field ◽  
International Geomagnetic Reference Field ◽  
Core Field ◽  
International Geomagnetic Reference ◽  
Continuous Models

Abstract Observations of the geomagnetic field taken at Earth's surface and at satellite altitude were combined to construct continuous models of the geomagnetic field and its secular variation from 1957 to 2020. From these parent models, we derive candidate main field models for the epochs 2015 and 2020 to the 13th generation of the International Geomagnetic Reference Field (IGRF). The secular variation candidate model for the period 2020 - 2025 is derived from a forecast of the secular variation in 2022.5, which results from a multi-variate singular spectrum analysis of the secular variation from 1957 to 2020.

scholarly journals Geomagnetic secular variation forecast using the NASA GEMS ensemble Kalman filter: A candidate SV model for IGRF-13

2020 ◽  
Author(s):  
Andrew Tangborn ◽  
Weijia Kuang ◽  
Terence Sabaka ◽  
Ce Ye
Keyword(s):  
Kalman Filter ◽  
Secular Variation ◽  
Ensemble Kalman Filter ◽  
Geomagnetic Field ◽  
Model Bias ◽  
Geomagnetic Secular Variation ◽  
Forecast Period ◽  
Time Period ◽  
Correction Scheme ◽  
Geomagnetic Field Models

Abstract We have produced a 5-year mean secular variation (SV) of the geomagnetic field for the period 2020-2025. We use the NASA Geomagnetic Ensemble Modeling System (GEMS), which consists of the NASA Goddard geodynamo model and ensemble Kalman filter (EnKF) with 400 ensemble members. Geomagnetic field models are used as observations for the assimilation, including gufm1 (1590-1960), CM4 (1961-2000) and CM6 (2001-2019). The forecast involves a bias correction scheme that assumes that the model bias changes on timescales much longer than the forecast period, so that they can be removed by successive forecast series. The algorithm was validated on the time period 2010-2015 by comparing with CM6 before being applied to the 2020-2025 time period. This forecast has been submitted as a candidate predictive model of IGRF-13 for the period 2020-2025.

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