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

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

Earth Planets and Space ◽

10.1186/s40623-020-01324-w ◽

2021 ◽

Vol 73 (1) ◽

Cited By ~ 1

Author(s):

Andrew Tangborn ◽

Weijia Kuang ◽

Terence J. Sabaka ◽

Ce Yi

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. Graphical abstract

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

10.21203/rs.3.rs-45638/v3 ◽

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

Earth Planets and Space ◽

10.1186/s40623-020-01279-y ◽

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.

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

Earth Planets and Space ◽

10.1186/s40623-020-01316-w ◽

2021 ◽

Vol 73 (1) ◽

Cited By ~ 6

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.

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

Annales Geophysicae ◽

10.5194/angeo-35-1085-2017 ◽

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.

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

Philosophical Transactions of the Royal Society of London. Series A, Mathematical and Physical Sciences ◽

10.1098/rsta.1982.0070 ◽

1982 ◽

Vol 306 (1492) ◽

pp. 103-112 ◽

Cited By ~ 15

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.

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Correlation of Late Pleistocene Glaciolacustrine and Marine Deposits by Means of Geomagnetic Secular Variation, with Examples from Northern New York and Southern Ontario

Quaternary Research ◽

10.1006/qres.1994.1078 ◽

1994 ◽

Vol 42 (3) ◽

pp. 277-287 ◽

Cited By ~ 3

Author(s):

Donald L. Pair ◽

Ernest H. Muller ◽

Peter W. Plumley

Keyword(s):

New York ◽

Marine Sediments ◽

Secular Variation ◽

Stratigraphic Correlation ◽

Geomagnetic Secular Variation ◽

Southern Ontario ◽

Marine Deposits ◽

Time Period ◽

Variation Curve ◽

Lake Cores

AbstractThe geomagnetic secular variation record retained by glaciolacustrine and marine sediments at nine sites in northern New York and southern Ontario provides a means for stratigraphic correlation of glacial deposits for the time period between about 12,600 to 9900 14C yr B.P. Measurement of the depositional remanent magnetism of sediments deposited in Glacial Lake Iroquois and the Champlain Sea has produced a geomagnetic secular variation curve that represents the time period immediately following deglaciation about 12,600 14 C yr B.P. The curve varies from about 358° to 344° declination and 51° to 61° inclination over approximately 180 valve years. Marine sediments of the Champlain Sea have preserved a record approximately 1500 yr long that varies from about 2° to 29° declination and 47° to 60° inclination. These combined glacial-paleomagnetic records may also correlate with those from glacial sequences beyond our study area. The shape and amplitude of the secular variation record in glaciolacustrine and marine sediments from the western Adirondack borderland show agreement with other glacial varve secular variation records and suggest possible correlations with secular variation curves from lake cores.

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

10.21203/rs.3.rs-26497/v1 ◽

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.

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