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

A 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

Tide-induced magnetic signals and their errors derived from CHAMP and Swarm satellite magnetometer observations

Satellite-measured tidal magnetic signals are of growing importance. These fields are mainly used to infer Earth’s mantle conductivity, but also to derive changes in the oceanic heat content. We present a new Kalman filter-based method to derive tidal magnetic fields from satellite magnetometers: KALMAG. The method’s advantage is that it allows to study a precisely estimated posterior error covariance matrix. We present the results of a simultaneous estimation of the magnetic signals of 8 major tides from 17 years of Swarm and CHAMP data. For the first time, robustly derived posterior error distributions are reported along with the reported tidal magnetic fields. The results are compared to other estimates that are either based on numerical forward models or on satellite inversions of the same data. For all comparisons, maximal differences and the corresponding globally averaged RMSE are reported. We found that the inter-product differences are comparable with the KALMAG-based errors only in a global mean sense. Here, all approaches give values of the same order, e.g., 0.09 nT-0.14 nT for M2. Locally, the KALMAG posterior errors are up to one order smaller than the inter-product differences, e.g., 0.12 nT vs. 0.96 nT for M2. Graphical Abstract

Indonesian Earth’s Lithospheric Magnetic Field modelling using Spherical Cap Harmonic Analysis Method

The earth’s lithospheric magnetic field is part of the main earth’s magnetic field. The lithospheric field has a very small value compared to the Earth’s main magnetic field, approximately less than 1%, and this field is generated at the earth’s crust and upper mantle. Modelling of lithospheric field is useful mainly for predicting the distribution of the value of lithospheric fields and to determine the magnetic anomaly. In this research, modelling the Earth’s lithospheric magnetic field uses Spherical Cap Harmonic Analysis (SCHA) method and this method can do modelling using regional magnetic data. The data used for the modelling are magnetic repeat station data in Indonesia region (BMKG’s Epoch) and SWARM satellite data. The results of the modelling using integrated SWARM satellite and repeat station data produce RMSE values of 64.0834 nT and the expansion of index K is 70. In addition, the results of the modelling resolution is 1.50. The value’s range of modelling’s result are -987.192 – 998.239 nT for X component, -968.189 – 949.438 nT for Y component, -981.266 – 608.676 nT for Z component, and -904.151 – 997.389 nT for total intensity are.

Spatio-temporal development of large scale auroral electrojet currents relative to substorm onsets

During auroral substorms the electric currents flowing in the ionosphere change rapidly and a large amount of energy is dissipated in the auroral ionosphere. An important part of the auroral current system are the auroral electrojets whose profiles can be estimated from magnetic field measurements from Low Earth Orbit satellites. In this paper we combine electrojet data derived from the Swarm satellite mission of ESA with the substorm database derived from the SuperMAG ground magnetometer network data. We organize the electrojet data in relation to the location and time of the onset and obtain statistics for the development of the integrated current and latitudinal location for the auroral electrojets relative to the onset. The major features of the behaviour of the westward electrojet are found to be in accordance with earlier studies of field aligned currents and ground magnetometer observations of substorm time statistics. In addition we show that after the onset the latitudinal location of the maximum of the westward electrojet determined from Swarm satellite data is mostly located close to the SuperMAG onset latitude in the local time sector of the onset regardless of where the onset happens. We also show that the SuperMAG onset corresponds to a strengthening of the order of 100 kA in the amplitude of the median of the westward integrated current in the Swarm data from 15 minutes before to 15 minutes after the onset.

Analysis of Swarm Satellite Magnetic Field Data Before the 2016 Ecuador (Mw = 7.8) Earthquake Based on Non-negative Matrix Factorization

In this paper, based on non-negative matrix factorization (NMF), we analyzed the ionosphere magnetic field data of the Swarm Alpha satellite before the 2016 (Mw = 7. 8) Ecuador earthquake (April 16, 0.35°N, 79.93°W), including the whole data collected under quiet and disturbed geomagnetic conditions. The data from each track were decomposed into basis features and their corresponding weights. We found that the energy and entropy of one of the weight components were more concentrated inside the earthquake-sensitive area, which meant that this weight component was more likely to reflect the activity inside the earthquake-sensitive area. We focused on this weight component and used five times the root mean square (RMS) to extract the anomalies. We found that for this weight component, the cumulative number of tracks, which had anomalies inside the earthquake-sensitive area, showed accelerated growth before the Ecuador earthquake and recovered to linear growth after the earthquake. To verify that the accelerated cumulative anomaly was possibly associated with the earthquake, we excluded the influence of the geomagnetic activity and plasma bubble. Through the random earthquake study and low-seismicity period study, we found that the accelerated cumulative anomaly was not obtained by chance. Moreover, we observed that the cumulative Benioff strain S, which reflected the lithosphere activity, had acceleration behavior similar to the accelerated cumulative anomaly of the ionosphere magnetic field, which suggested that the anomaly that we obtained was possibly associated with the Ecuador earthquake and could be described by one of the Lithosphere–Atmosphere–Ionosphere Coupling (LAIC) models.