Crustal geomagnetic field and secular variation by regional and global models for Austria

Abstract Using 12-year-long series of data (2001-2012) from geomagnetic observatories and repeat stations in Austria and its neighboring countries, a regional spatial-temporal (ST) model is developed based on the polynomial expansion consisting of latitude, longitude, and time of the geomagnetic field components and total magnetic field F. Additionally, we have used three different global models (CHAOS-5, POMME-9, and EMM2015), which are built on spherical harmonics up to a maximum degree Lmax and give the core field and crustal field separately. The normal field provided by the ST model and its “model bias”, which comprise the residuals of the differences between measured and predicted values, are calculated and the respective maps are shown. The residuals are considered an estimate of the local crustal field. In the case of global models, we have applied for each of these three methods to calculate the “model bias”: residuals of the differences between observed values and predicted values of the model, residuals of the differences between observed values and core field values of the model, and the average bias for the period 2001-2012. The normal field of the region of Austria provided by each global model is also calculated. Generally, the regional and global models yield relatively similar crustal fields for the Austrian region, especially when the first method is used. The normal fields calculated by them are in good agreement with each other. Each of the global models directly provides the crustal field, and they are compared with the aeromagnetic data provided by aeromagnetic surveys over the Austrian region. The ST model is in better agreement with aeromagnetic data. We have also analyzed the secular variation over the region, which is calculated from the rate of change of normal field given by the ST and global models.

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

Earth Planets and Space ◽

10.1186/s40623-021-01357-9 ◽

2021 ◽

Vol 73 (1) ◽

Cited By ~ 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.

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

10.21203/rs.3.rs-45638/v2 ◽

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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A regional geomagnetic field model over Southern Africa derived with harmonic splines from Swarm satellite and ground-based data recorded between 2014 and 2019

Earth Planets and Space ◽

10.1186/s40623-021-01563-5 ◽

2022 ◽

Vol 74 (1) ◽

Author(s):

Emmanuel Nahayo ◽

Monika Korte

Keyword(s):

Field Intensity ◽

Southern Africa ◽

Secular Variation ◽

Geomagnetic Field ◽

Field Model ◽

Radial Component ◽

The South ◽

Core Field ◽

Swarm Satellite ◽

Magnetic Observatories

AbstractA regional harmonic spline geomagnetic main field model, Southern Africa Core Field Model (SACFM-3), is derived from Swarm satellite and ground-based data for the southern African region, in the eastern part of the South Atlantic Anomaly (SAA) where the field intensity continues to decrease. Using SACFM-3 and the global CHAOS-6-×9 model, a detailed study was conducted to shed light on the high spatial and temporal geomagnetic field variations over Southern Africa between 2014 and 2019. The results show a steady decrease of the radial component Z in almost the entire region. In 2019, its rate of decrease in the western part of the region has reached high values, 76 nT/year and 78 nT/year at Tsumeb and Keetmanshoop magnetic observatories, respectively. For some areas in the western part of the region the radial component Z and field intensity F have decreased in strength, from 1.0 to 1.3% and from 0.9 to 1.2%, respectively, between the epochs 2014.5 and 2019.5. There is a noticeable decrease of the field intensity from the south-western coast of South Africa expanding towards the north and eastern regions. The results show that the SAA area is continuing to grow in the region. Abrupt changes in the linear secular variation in 2016 and 2017 are confirmed in the region using ground-based data, and the X component shows an abrupt change in the secular variation in 2018 at four magnetic observatories (Hermanus, Hartebeesthoek, Tsumeb and Keetmanshoop) that needs further investigation. The regional model SACFM-3 reflects to some extent these fast core field variations in the Z component at Hermanus, Hartebeesthoek and Keetmanshoop observatories. Graphical Abstract

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

10.21203/rs.3.rs-45638/v1 ◽

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.

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

Earth Planets and Space ◽

10.1186/s40623-020-01254-7 ◽

2020 ◽

Vol 72 (1) ◽

Author(s):

I. Wardinski ◽

D. Saturnino ◽

H. Amit ◽

A. Chambodut ◽

B. 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 are 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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Crustal field recovery and secular variation from regional and global models over Albania

Annals of Geophysics ◽

10.4401/ag-7419 ◽

2018 ◽

Vol 61 (1) ◽

Author(s):

Klaudio Peqini ◽

Beko Duka ◽

Guido Dominici

Keyword(s):

Secular Variation ◽

Global Models ◽

Crustal Field

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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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A secular variation candidate model for IGRF-13 based on Swarm data and ensemble inverse geodynamo modelling

Earth Planets and Space ◽

10.1186/s40623-020-01309-9 ◽

2021 ◽

Vol 73 (1) ◽

Cited By ~ 2

Author(s):

Alexandre Fournier ◽

Julien Aubert ◽

Vincent Lesur ◽

Guillaume Ropp

Keyword(s):

Numerical Integration ◽

Secular Variation ◽

Geomagnetic Field ◽

Initial Conditions ◽

Numerical Models ◽

Average Rate ◽

Rate Of Change ◽

Three Dimensions ◽

Dynamo Model ◽

Initial Condition

AbstractThis paper describes the design of a candidate secular variation model for the 13th generation of the International Geomagnetic Reference Field. This candidate is based upon the integration of an ensemble of 100 numerical models of the geodynamo between epochs 2019.0 and 2025.0. The only difference between each ensemble member lies in the initial condition that is used for the numerical integration, all other control parameters being fixed. An initial condition is defined as follows: an estimate of the magnetic field and its rate-of-change at the core surface for 2019.0 is obtained from a year (2018.5–2019.5) of vector Swarm data. This estimate (common to all ensemble members) is subject to prior constraints: the statistical properties of the numerical dynamo model for the main geomagnetic field and its secular variation, and prescribed covariances for the other sources. One next considers 100 three-dimensional core states (in terms of flow, buoyancy and magnetic fields) extracted at different discrete times from a dynamo simulation that is not constrained by observations, with the time distance between each state exceeding the dynamo decorrelation time. Each state is adjusted (in three dimensions) in order to take the estimate of the geomagnetic field and its rate-of-change for 2019.0 into account. This methodology provides 100 different initial conditions for subsequent numerical integration of the dynamo model up to epoch 2025.0. Focussing on the 2020.0–2025.0 time window, we use the median average rate-of-change of each Gauss coefficient of the ensemble and its statistics to define the geomagnetic secular variation over that time frame and its uncertainties.

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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/v2 ◽

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 are 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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