The 14th generation of the International Geomagnetic Reference Field (IGRF-14) was officially released in November 2024. It is valid from 1900.0 to 2030.0 and supersedes the 13th generation IGRF, which ends at 2025.0. The IGRF-14 model consists of five-yearly snapshots of the magnetic field represented by Gauss coefficients. The main magnetic field is captured up to spherical harmonic degree and order 13.
In this generation, the coefficients for 2020.0 have been updated and are now definitive, and new coefficients for 2025.0 have been computed. An estimate of the secular variation (to degree and order 8) for the next five years, from 2025.0 until 2030.0, has also been created.
Creating the IGRF-14 was a truly international effort involving data from global geomagnetic observatories and multiple satellite missions, including ESA Swarm and Macau Scientific Satellite-1 (MSS-1). The initial call for candidates was released in March 2024, and the final candidates were submitted in October. We received candidate models from 19 different institutions worldwide, some of whom had not previously submitted IGRF candidates. For comparison, the number of teams that submitted candidates was 10 for IGRF-12 (released in 2015) and 15 for IGRF-13 (released in 2020), reflecting the growing community and the importance of geomagnetism.
For this generation, a GitHub repository was established to maintain an open record of the submission and analysis process for the candidate models. To evaluate the candidates and decide how best to combine these submitted models into the final IGRF14 coefficients, a volunteer group of experts was established to make independent recommendations.
In this talk, we describe the candidate models, provide details of the standard analysis of magnetic field models performed, and show how research software engineering tools, such as the IGRF14 GitHub repository, were used to automatically generate an evaluation of each submitted candidate. We discuss the evaluation process and how the final IGRF14 coefficients were agreed upon. We document some of the new features in the latest magnetic field maps.
How to cite: Kloss, C. and Beggan, C.: The 14th Generation of the International Geomagnetic Reference Field, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3566, https://doi.org/10.5194/egusphere-egu25-3566, 2025.
ESA Swarm satellites carry a magnetometry payload consisting of an absolute scalar magnetometer (ASM), a relative flux gate vector magnetometer (VFM), and a set of star trackers (STR). The primary role of the ASM is to provide precise 1 Hz absolute field intensity measurements, while the VFM and STR provide the additional data needed to accurately reconstruct the attitude of the vector field to produce the official nominal Swarm L1b magnetic data. Each ASM instrument, however, can also produce its own self-calibrated 1 Hz experimental vector data, or, when requested, 250 Hz scalar burst data. Self-calibrated 1 Hz experimental vector data have routinely been produced ever since launch and are still run when the ASM instruments are not in burst mode. Such experimental data provide an interesting possibility of building alternative field models to those built from nominal Swarm L1b magnetic data. This possibility has been used to produce the only DGRF 2020 candidate model entirely and only relying on such data in the context of the recent IGRF 2025 call for candidate models. All other candidate models relied on either nominal Swarm L1b, or data from other satellites and ground observatories.
Here we will report on the way this unique DGRF candidate model was built, and on the post-calibration strategy that we used to further improve the quality of this model, only and entirely relying on a dedicated analysis of model residual signals. As will be discussed, our final candidate model turns out to be one of the DGRF 2020 candidate models closest to the final official DGRF model, which a posteriori provides encouraging evidence of both the quality of the Swarm ASM experimental vector mode data and the value of our post-calibration strategy.
How to cite: Chauvet, L., Hulot, G., Deborde, R., Léger, J.-M., and Jager, T.: A DGRF 2020 Candidate Model Only Based on Swarm ASM Experimental Vector Mode Data, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9887, https://doi.org/10.5194/egusphere-egu25-9887, 2025.
The updated World Magnetic Model (WMM) 2025 was released in December 2024, alongside a new WMM – High Resolution version for the first time. The WMM is a spherical harmonic model of the internal magnetic field, designed to provide values of the magnetic field for navigation, heading and direction over 5-years as part of the World Geodetic System 1984 standard coordinate reference frame. WMM is produced jointly by the British Geological Survey and US NOAA National Centers for Environmental Information, funded by the Defence Geographic Centre and National Geospatial Intelligence Agency (NGA), respectively. The WMM is managed by NGA, who define a specification for its performance and accuracy. The WMM is adopted by organisations such as the UK Ministry of Defence, US Department of Defense, NATO, and the International Hydrographic Organisation.
The standard WMM describes the magnetic field to spherical harmonic degree and order 12, while the new High Resolution model includes an extended core field to degree and order 15, and crustal magnetic fields to degree and order 133 (roughly 300km at the equator). The High Resolution model is intended to provide a reference model with greater accuracy for specialist users.
The WMM is released every 5 years, providing a snapshot of the internal field and its predicted rate of change (secular variation), and an uncertainty model. The performance of each WMM release is monitored through its life by comparison to contemporary observations and field models. For the 2025 to 2030 period, we anticipate changes in declination due to evolution of the South Atlantic Anomaly, and a deceleration of the north magnetic pole after rapid acceleration observed in recent years.
How to cite: Brown, W., Gomez Perez, N., Watson, C., Beggan, C., Chulliat, A., and Nair, M.: Release of the World Magnetic Model for 2025 to 2030, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12991, https://doi.org/10.5194/egusphere-egu25-12991, 2025.
Quantum magnetic sensing offers several powerful advantages over the classic combination of triaxial fluxgate and proton precession magnetometers. Advances in quantum technology, such as optically-pumped magnetometers (OPMs), have enabled single sensors to make full-field, high-frequency, temperature-insensitive measurements of the natural field (i.e., 0-60μT). The low noise, high bandwidth OPMs can be used to detect absolute changes in the field arising from secular variation as well as rapid variations in the Earth’s natural magnetic field from space weather activity. Our newly developed OPM consists of a Cs-vapour cell magnetometer in a double-resonance configuration with two orthogonal coils to provide a full field and vector measurement capability.
As part of a three-year programme, we will build and deploy five ground-based OPMs using state-of-the-art sensor technology from the University of Strathclyde in combination with back-end electronics for the laser driver and high-speed digital signal processing developed by RAL Space. The BGS-run geomagnetic observatory at Eskdalemuir will allow the OPM systems to be compared and checked against the highest scientific standards for observatories (INTERMAGNET-standard). The sensors will then be deployed to five field locations around Britain in 2025. This will reduce the spacing between operational observatories and variometers in the UK to less than 200 km. The systems will return data in near-real-time, allowing one of the densest magnetic networks in the world to be created. We describe the progress to date, including the results from a performance comparison at Eskdalemuir and the first field deployments in England and Wales.
How to cite: Beggan, C., Ingleby, S., Bason, M., Turbitt, C., Hunter, D., Salter, M., Lyon, R., Filip, A., Martyn, T., and Parrianen, J.: A field-deployable absolute vector quantum magnetometer for geomagnetic research, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3169, https://doi.org/10.5194/egusphere-egu25-3169, 2025.
Geomagnetically Induced Currents (GICs) are a manifestation of space weather events at ground level. GICs have the potential to cause power failures in electric grids. The GIC index is a proxy of the ground geoelectric field, derived solely from geomagnetic field data. Information theory can be used to shed light on the dynamics of complex systems, such as the coupled solar wind-magnetosphere-ionosphere-ground system. We perform Block entropy analysis of the GIC activity indices at middle latitude European observatories around the St. Patrick’s Day March 2015 intense magnetic storm and Mother’s Day (or Gannon) May 2024 superintense storm. We find that the GIC indices values are generally higher for the May 2024 storm, indicating elevated risk levels. Furthermore, the entropy values of the SYM-H and GIC indices are higher in the time interval before the storms than during the storms, indicating the transition from a system with lower organization to a system with higher organization. The results show promise for space weather applications.
How to cite: Boutsi, A. Z., Papadimitriou, C., Balasis, G., Brinou, C., Zampa, E., and Giannakis, O.: Dynamical Complexity in Geomagnetically Induced Current Activity Indices Using Block Entropy, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15413, https://doi.org/10.5194/egusphere-egu25-15413, 2025.
The 2022 Hunga Tonga Volcano Eruption (HTVE) had unprecedented impacts on atmospheric space weather. It provided a clear example of how space weather may be impacted by influences both “from above” (e.g. the solar wind, geo-magnetic storms) and “from below” (e.g. powerful volcanoes, hurricanes, earthquakes). Manifestations of unprecedented geophysical effects from HTVE were an acoustic wave that circled the Earth several times, the formation of strong ionospheric plasma bubbles and plasma depletion. An important method for diagnosing ionospheric space weather is ionospheric radio scintillation (IS). The purpose of this work is data analysis, modelling and interpretation of radio scintillation data of ionospheric effects from HTVE using the Low-Frequency Array (LOFAR), supported by observations from the European Space Agency’s Swarm mission and other geophysical instruments. Specifically, LOFAR observed TIDs in the ionospheric plasma over the Europe, which, based on typical velocities and pulse widths (on the order of 10 s), are interpreted as the effect of waves generated as a result of the HTVE. The physical modelling carried out corresponds to a picture corresponding to the penetration of Lamb waves into ionospheric altitudes, with their source being a pressure pulse associated with HTVE. Moreover, the corresponding physical explanation, based on the modelling carried out, is given from two points of view: (1) acoustic mode and (2) acoustic impulse representations. (1) Modes with periods of about 12 min were studied. It turned out that such frequencies correspond to a number of eigenmodes of Lamb waves which, accounting for attenuation, travelled thousands of km from the source to the observation site and having a finite/non-zero excitation efficiency (velocity value) near the Earth’s surface. At the same time, the acoustic field of such waves is concentrated at the heights of the altitude region of the E region of the ionosphere. (2) It has been shown that a pressure pulse with a duration of about 10 s in the lower atmosphere effectively penetrates to the heights of the E region of the ionosphere, its acoustic field is concentrated in the E region and it tends to propagate in the horizontal direction, exciting the E region. An analytical algorithm is proposed to determine the response of the ionosphere to the corresponding acoustic pulse, and a method of complex geometric optics is presented, which makes it possible to simulate the scattering of high-frequency (HF) electromagnetic waves (EMW) in the LOFAR (MHz) range. In general, the observations, estimates and numerical simulations confirm the effect of pulsed impact on the ionosphere of acoustic waves penetrating to ionospheric heights at distances of many thousands of kilometres from the source associated with HTVE and causing the scattering of HF EMW detected by the LOFAR radio telescope. The above-mentioned model is under development now. Its appropriate application will allow us to study and interpret other effects of acoustic waves from a source associated with HTVE and develop further the methods for radio diagnostics of ionospheric space weather.
How to cite: Rapoport, Y., Grimalsky, V., Dorrian, G., Wood, A., and Petrishchevskii, S.: Experimental data and models for radio diagnostics of extreme impacts “from below” on ionospheric space weather: LOFAR data on ionospheric acoustic-range perturbations caused by Hunga-Tonga volcano eruption., EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10846, https://doi.org/10.5194/egusphere-egu25-10846, 2025.
On May 22, 2021, a magnitude 7.4 earthquake struck Maduo County in Guoluo Prefecture, Qinghai Province, China, with an epicenter at 34.59°N latitude and 98.34°E longitude and a focal depth of 17 kilometers.
Ionospheric disturbances related to this earthquake are analyzed using Global Ionospheric Map Total Electron Content (GIM-TEC) data from May 1 to May 31, 2021. We employ the LSTM-LUBE method, an advanced deep learning model for dynamic range prediction, to detect and analyze anomalies in the GIM-TEC data across both temporal and spatial scales. The core idea of the LSTM-LUBE method is to predict the dynamic range of the input TEC data through a neural network, rather than providing a single point estimate. Data points falling outside the predicted dynamic range are considered anomalies. To ensure the accuracy of the results, disturbances caused by solar activity and geomagnetic fluctuations are excluded. Temporal analysis reveals significant TEC anomalies between May 3 and May 8, as well as a notable TEC anomaly on the day before the earthquake, May 21. From the GIM-TEC spatiotemporal difference maps, conjugate TEC negative disturbances are observed in the earthquake preparation zone and its magnetic conjugate region during UT 6:00-8:00 on May 3. Additionally, conjugate TEC disturbances, characterized by initial positive perturbations followed by negative perturbations, are detected in the Maduo earthquake preparation zone and its magnetic conjugate region during UT 8:00-12:00 and UT 18:00-22:00 on May 5.
This study demonstrates the potential of ionospheric TEC data in earthquake prediction by utilizing the LSTM-LUBE deep learning network to extract TEC anomalies.
Fig. 1. Two typical grid points' TEC time series and difference plots are shown (The red solid line represents ΔTEC, the gray shaded area indicates the dynamic TEC range, and the blue solid line represents the true TEC values). After excluding disturbances from geomagnetic and solar activities, the anomalies observed on May 3, May 5, May 7, May 8, and May 21 may be attributed to earthquake activity.
Fig. 2. On May 3, during UT 6:00-8:00, negative ionospheric disturbances are observed in both the earthquake preparation zone and its magnetic conjugate region in the spatiotemporal difference maps (The red circle represents the preparation zone of the Maduo earthquake epicenter, and the green circle represents the magnetic conjugate region).
Fig. 3. On May 5, during UT 8:00-12:00 and UT 18:00-22:00, anomalous TEC disturbances characterized by initial positive perturbations followed by negative perturbations are observed in both the earthquake preparation zone and its magnetic conjugate region (The red circle represents the preparation zone of the Maduo earthquake epicenter, and the green circle represents the magnetic conjugate region).
How to cite: Yu, Z., Yang, M., Jing, X., and Zhang, J.: Analysis of Ionospheric Disturbances Potentially Associated with the Maduo Ms7.4 Earthquake on 22 May 2021 in China Using GIM-TEC Data, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5978, https://doi.org/10.5194/egusphere-egu25-5978, 2025.
The ionosphere, a crucial interface between Earth’s atmosphere and space, demonstrates complex temporal dynamics influenced by both terrestrial and extraterrestrial factors. This research investigates the potential of detecting precursors to seismic events by analyzing transient phenomena within the ionosphere. We utilized machine learning algorithms to process and analyze extensive VLF electromagnetic spectrum data gathered by the Demeter satellite over the period from 2005 to 2010. During this five-year duration, approximately 8000 earthquakes with magnitudes of 5.0 or higher were recorded.
We employed a grid-based method, segmenting the Earth's surface into 20x20 degree grids and examining eleven low-frequency bands of electric field data. A time-series dataset was developed from the power spectrum by deriving the feature of interest from each frequency band. Our approach utilized an LSTM Autoencoder model trained to identify anomalies in the time-series data from daytime orbital observations. The model demonstrated effective generalization, successfully detecting a high proportion of seismic-correlated anomalies. In the frequency-based analysis, more feature-specific significance was identified, further enhancing detection accuracy across various frequency bands. The model outperformed random sampling methods, underscoring the reliability of the detected anomalies.
These findings highlight the model's proficiency in detecting ionospheric anomalies, thereby enhancing the broader understanding of ionosphere-lithosphere interactions. Incorporating machine learning techniques into ionospheric research marks a significant advancement in the detection of ionospheric disturbances, providing a robust framework for correlating ionospheric disturbances with seismic events.
How to cite: Babu, M., Cristoforetti, M., and Iuppa, R.: Machine Learning for Detecting Time-Transient Phenomena in the Ionosphere and Correlation with Seismo-Induced Events., EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10065, https://doi.org/10.5194/egusphere-egu25-10065, 2025.
This study explores the processes of generating pre-earthquake abnormalities in the atmosphere/ionosphere associated with significant seismicity. We analyzed two major earthquakes that occurred recently in N. America and Asiа. The M 7.0 of Dec 5, 2024, Offshore Cape Mendocino, California Earthquake is a strike-slip shallow event (10km depth) west of the Mendocino Triple Junction, one of California's most active seismic regions. The M 7.1 of Jan 7, 2025, Southern Tibetan Plateau Earthquake was a typical faulting earthquake, the largest in the area since an M7.1 struck 171 km to the south on 26 April 2015 in Nepal. Оur primary objective is to assess the solar-geophysical conditions preceding both events and, with a thorough validation study of pre-earthquake signals occurrence in the Atmosphere/ionosphere to understand the associated lithosphere-atmosphere coupling phenomena’ similarities and differences.
For the first time, we combine observations from earth and geospace monitoring systems, such as NPOESS, GNSS, CSES1, FORMOSAT-7/COSMIC-2, and NASA assimilation models in such comparison studies. We analyzed: 1/ Cloud features (CF) with NASA EOS MODIS and Thermal Radiation anomalies (TRA) obtained from satellites NPOESS; 2/ Ionospheric plasma observations from China/Italy Seismo-Electromagnetic Satellite (CSES1);3/Electron density variations in the ionosphere via GPS Total Electron Content (GPS/TEC) and FORMOSAT-7/COSMIC-2 and 4/ Atmospheric chemical potential (ACP) obtained from NASA assimilation models. The initial results reveal that the magnetic storms in October – November 2024 could provoke the M7 earthquake in California (December 5, 2024) and the M7.1 earthquake in Tibet (January 7, 2025). Still, additional work is needed to establish the precise connection. The pre-earthquake signatures demonstrate synergetic coordination between the occurrences of CF, TRA, and ACP anomalies of transient effects in the atmosphere and ionosphere. In the case of the Cape Mendocino, CA earthquake, the pre-earthquake signals occurred slightly later because of the ocean type of event compared to Tibetan signatures, which mimicked the sequence of the 2015 M7.8 Gorkha earthquake (Nepal). The continuous detection of atmospheric signatures over the Southern Tibetan Plateau indicated probably that more aftershocks are likely. The spatial characteristics of the pre-earthquake anomalies for both events were associated with large areas and scaled with the earthquake preparation zone, as estimated by the Dobrovolsky-Bowman relationship. In general, we discuss the significance of the re-occurrence of pre-earthquake signals during the preparation process.
How to cite: Ouzounov, D., Zhima, Z., Liu, J., Khachikyan, G., and Yan, R.: Study the Geospace impact and the re-occurrence of pre-earthquake signals in the atmosphere: Preliminary analysis for the 2024 M 7.0 Cape Mendocino, CA and 2025 M 7.1 Southern Tibetan Plateau Earthquakes., EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14299, https://doi.org/10.5194/egusphere-egu25-14299, 2025.
To verify the lithosphere-atmosphere-ionosphere coupling processes around strong earthquakes, a multi-parameter and multi-level approach from ground and satellite data have been paid more and more attention in recent researches. Taking Wushi Ms7.1 earthquake on 22 January 2024 as an example, multi parameters were included in the study, such as the earth resistivity, the geomagnetic field and geoelectric field in lithosphere, surface temperature and outgoing longwave radiation in atmosphere, while foF2 from Ionosonde, GNSS TEC, magnetic field and electron density, energetic particles from electromagnetic satellites for ionosphere, etc.. The results are encouraging confirming a chain of processes starting from ground and proceeding to the above atmosphere and ionosphere. The direct and indirect connection among multi layers and different parameters were discussed to build the energy preparation, developing and coupling processes for Wushi earthquake.
How to cite: Zhang, X., De Santis, A., Xiong, P., Cianchini, G., Liu, J., Campuzano, S., Yisimayili, A., D’Arcangelo, S., Li, X., Fidani, C., Yang, M., Perrone, L., Liu, H., Wang, S., and Feng, M.: The lithosphere-atmosphere-ionosphere coupling processes around the Wushi Ms7.1 earthquake in 2024, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2731, https://doi.org/10.5194/egusphere-egu25-2731, 2025.
On 6 February 2023, Turkey experienced its most powerful seismic event in over 80 years, with a moment magnitude (Mw) of 7.7, followed just nine hours later by a second large earthquake with Mw 7.6. Both events struck the Kahramanmaraş province in southeastern Turkey, within the complex tectonic setting of the East Anatolian Fault Zone (EAFZ), causing widespread destruction and significant loss of life. According to lithosphere–atmosphere–ionosphere coupling (LAIC) models (e.g. Pulinets and Ouzounov, 2011), large seismic events are expected to generate a cascade of anomalies across various geophysical layers, from the lithosphere through the atmosphere to the ionosphere, as part of the earthquake preparation process. This multidisciplinary study investigates the preparatory phase of these two major earthquakes by identifying potential precursors and disturbances across these layers, in order to better understand the mechanisms linking the geospheres prior to seismic events.
Our comprehensive analysis (De Santis et al., 2019) draws on multiple datasets, including ground-based and satellite observations, to detect anomalous variations in parameters such as ground surface temperature, atmospheric gases, ionosphere electron density and geomagnetic field. These anomalies show a cumulative occurrence with an accelerating trend (De Santis et al, 2017), either exponential or power-law in nature, in the days and weeks preceding the mainshock. The anomalies predominantly exhibit an upward progression from the lithosphere through the atmosphere to the ionosphere, revealing a chain of interconnected processes within these geospheres during the earthquake preparation phase.
Our findings suggest that these anomalies provide valuable evidence in support of a two-way coupling model, where disturbances can propagate upward from the lithosphere. Additionally, the study highlights the potential role of fluid chemistry (Calcara, 2022), particularly the release of gases such as radon, in driving these coupling processes
In conclusion, this study underscores the significance of a multidisciplinary approach to investigating earthquake precursors across the Earth system. The identification of consistent patterns in pre-earthquake anomalies can enhance our understanding of the complex interactions within the lithosphere-atmosphere-ionosphere system and could contribute to the development of more effective early-warning systems for major seismic events.
References
Pulinets, S.; Ouzounov, D. Lithosphere-atmosphere-ionosphere coupling (LAIC) model-an unified concept for earthquake precursors validation. J. Asian Earth Sci. 2011, 41, 371–382
De Santis, A.; Abbattista, C.; Alfonsi, L.; Amoruso, L.; Campuzano, S.A.; Carbone, M.; Cesaroni, C.; Cianchini, G.; De Franceschi, G.; De Santis, A.; et al. Geosystemics View of Earthquakes. Entropy 2019
De Santis A. et al., Potential earthquake precursory pattern from space: the 2015 Nepal event as seen by magnetic Swarm satellites, Earth and Planetary Science Letters, 461, 119-126, 2017
Calcara, M. Chemistry in earthquake: The active chemical role of liquid and supercritical waters in microfracturing at depth. J. Seismol. 2022, 26, 1205–1221
How to cite: Cianchini, G., De Santis, A., Calcara, M., Perrone, L., A. Campuzano, S., D'Arcangelo, S., Orlando, M., Sabbagh, D., Piscini, A., and Fidani, C.: The Preparatory Phase of the 2023 Kahramanmaraş (Turkey) Major Earthquakes: A Multidisciplinary and Comparative Analysis, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8899, https://doi.org/10.5194/egusphere-egu25-8899, 2025.
Launched on 22 November 2013, Swarm is the fourth in a series of pioneering Earth Explorer missions and also the European Space Agency’s (ESA’s) first constellation to advance our understanding of the Earth’s magnetic field and the near-Earth electromagnetic environment. Swarm provides an ideal platform in the topside ionosphere for observing ultra-low-frequency (ULF) waves, as well as equatorial spread-F (ESF) events or plasma bubbles, and, thus, offers an excellent opportunity for space weather studies. For this purpose, a specialized time–frequency analysis (TFA) toolbox has been developed for deriving continuous pulsations (Pc), namely Pc1 (0.2–5 Hz) and Pc3 (22–100 mHz), as well as ionospheric plasma irregularity distribution maps. In this methodological paper, we focus on the ULF pulsation and ESF activity observed by Swarm satellites during a time interval centered around the occurrence of the 24 August 2016 Central Italy M6 earthquake. Due to the Swarm orbit’s proximity to the earthquake epicenter, i.e., a few hours before the earthquake occurred, data from the mission may offer a variety of interesting observations around the time of the earthquake event. These observations could be associated with the occurrence of this geophysical event. Most notably, we observed an electron density perturbation occurring 6 h prior to the earthquake. This perturbation was detected when the satellites were flying above Italy.
How to cite: Balasis, G., De Santis, A., Papadimitriou, C., Boutsi, A. Z., Cianchini, G., Giannakis, O., Potirakis, S. M., and Mandea, M.: Swarm Investigation of Ultra-Low-Frequency (ULF) Pulsation and Plasma Irregularity Signatures Potentially Associated with Geophysical Activity, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13661, https://doi.org/10.5194/egusphere-egu25-13661, 2025.
In summer 2023, continuous observations of the Earth's magnetic field parameters were launched at the Mikhnevo geophysical polygon of the M.A. Sadovsky Institute of Geophysics of the Russian Academy of Sciences (Stupino District, Moscow Region). This observatory is the first modern geomagnetic observatory in the vast territory of the central region of the Russian Federation, registering high-quality data with 1-second sampling. The observatory is located far enough from the sources of anthropogenic electromagnetic interference, which is confirmed by the noise characteristics of the recorded data. Deployment of the observatory was carried out taking into account both the long-term experience accumulated by the specialists of the GC RAS and the recommendations of the INTERMAGNET international geomagnetic observatory network.
How to cite: Kudin, D., Sidorov, R., Ryakhovskiy, I., and Soloviev, A.: Mikhnevo: A new geomagnetic observatory, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-20032, https://doi.org/10.5194/egusphere-egu25-20032, 2025.
We compute magnetic field models from mostly ground-based geomagnetic observations over the period 1956 to 2025. Our magnetic field modeling strategy employs secular variation estimates derived from annual differences of observatories monthly means. The resulting models are compared to a recent satellite-based geomagnetic field model (Chaos 7.16) that covers the entire satellite era from 2000 to 2025. Both models are setup to mimic the geomagnetic field variation by order 6 B-splines, which also provides robust results for the secular acceleration. While the core field descriptions of the two models highly agree (correlation $\sim$0.92 at spherical harmonic degree l = 14), the both descriptions of the secular variation deviates, most noticeable on intermediate length scale. This difference may be explained by the difference of source geometries within satellite and ground-based data sets. Satellite data consider every magnetic field generation below their orbital sphere to be of internal origin. However, this might be difficult as night-time and quiet-time ionospheric field generation may also map into these data as internal sources. An indication for this might be the higher power of ground-based secular variation models for spherical harmonic degrees l = 4 − 12. We also devise a way to derive temporally more detailed secular variation estimates. Here, we aim to identify short-term secular variation most vivid in the equatorial region and the imprint of a quasi-biennial variation that possibly originate in the ionosphere and/or magnetosphere. The presented model was used to deduce candidates for the different IGRF-14 derivatives (definitive field model for 2020, current field model for 2025, secular variation forecast for 2025-2030).
How to cite: Wardinski, I., Terra-Nova, F., and Amit, H.: Short-term secular variation seen in decadal magnetic field models, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16512, https://doi.org/10.5194/egusphere-egu25-16512, 2025.
It is important to be able to predict the impacts of geomagnetic activity at ground level, for example when it comes to estimating the effect of geomagnetically induced currents (GICs). The rate of change of the magnetic field in the horizontal direction (dH/dt) is regularly used as a proxy or indicator for potentially hazardous space weather activity. Most researchers tend to use one of two methods for computing the dH/dt: one is correct and the other is an approximation, with one method taking into account the difference in both the magnitude and direction of the magnetic field vector between timesteps and the other method only looking at the difference in the magnitude of the vector quantities. As the differentiation of the magnetic field in the latter method takes place after the two field directions have been combined to a scalar quantity, the relative sizes of the magnetic field in the two different directions can lead to a difference between the approaches. In particular, when either the northward or eastward magnetic field components are close to zero, such as near the agonic line, a relatively large difference in dH/dt magnitude can appear. We show using geomagnetic observatory measurements that there is an observable difference between the two methods close to the agonic line. We suggest which method for computing dH/dt should be employed.
How to cite: Fielding, S., Whaler, K., Beggan, C., Livermore, P., and Richardson, G.: Computing horizontal geomagnetic field variation near the agonic line, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10311, https://doi.org/10.5194/egusphere-egu25-10311, 2025.
Magnetic sources of small size and modest intensity produce a geomagnetic anomaly of low intensity and limited extent, which is not detectable beyond a few decimeters, one meter at most. It is therefore important to carry out geomagnetic surveys as close as possible to the source in order to detect them. This means that the sensor must be moved along a trajectory that follows the microtopography. This necessity complicates the problem, since in addition to the geomagnetic anomalies sought, there are also anomalies produced by topographical variations. The geometry of anomalies produced in space, above the surface, by low-intensity point sources differs from those produced by the humps and hollows of the surface topography of the area surveyed. Indeed, a point source produces a dipolar anomaly of circumscribed vertical extension, whereas topographical variations produce more diffuse anomalies, positive for humps and negative for hollows, with the dipolar component attenuated. To eliminate the confusion between a point source and a topographical effect, the solution is to explore the volume above the prospected surfaces. In this way, a 3D survey can distinguish anomalies due to microtopography from those due to modest magnetic point sources.
The density of the magnetic field intensity measurement cloud must be adapted to the size of the sources to be detected. The smaller the sources, the tighter the measurement grid must be, and the closer the sensor needs to be to the surface. In practice, the size of the sensor determines the maximum spatial resolution that can be achieved. To achieve a high measurement density in an acceptable measurement time, measurements must be taken continuously at a high rate. The spatialization precision of the measurements remains an important factor for information quality. For decimeter-sized objects, the position of magnetic field intensity measurements is determined using a total station (S8, Trimble) at a maximum rate of 20 Hz by laser tracking a 360° reflector attached to the magnetic field intensity sensor. For metric objects, GNSS geopositioning with differential correction with local base performed in post-processing allows sufficient accuracy to be achieved. The 360° reflector, being non-magnetic, can be attached to the sensor, though GNSS antennas, being magnetic, necessitate the use of a miniature helical antenna offset by at least 0.5 m to mitigate its influence.
This type of 3D geomagnetic survey was originally used in prehistoric caves to locate hearths. A device equipped with a telescopic pole mounted on a tripod is used to scan the space, taking one measurement per 25 cm² of ground area. Measurements are taken at a rate of 10 Hz (G858, Geometrix). Tests with rates up to 100 Hz were carried out with a GSMP35U (GEMsystem), but it turned out that the measurement rate is not continuous, which poses problems for data fusion. In the field, these surveys have been carried out on Neolithic pebble hearths or on an antique shipwreck. For large surfaces, several hundred m², the device is mounted on a cart, or a cart with 4 superimposed sensors is used.
How to cite: Lévêque, F.: Advantages and limitations of 3D acquisition of magnetic field intensity measurements , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17772, https://doi.org/10.5194/egusphere-egu25-17772, 2025.
Geomagnetic prospecting is traditionally carried out in two dimensions (2D) on the surface of the ground to search for archaeological remains, unexploded ordnance (UXO) or industrial waste. Despite the efficacy of the method in identifying the target, it does not facilitate the precise determination of the depth and geometry of the sources. To reduce this uncertainty, additional data is requisite. One approach is to integrate the vertical variation of the geomagnetic field to provide a more accurate understanding of the depth and geometry of the sources. To this end, we propose an inversion algorithm designed for 3D geomagnetic prospecting data. This algorithm is based on simulated annealing (SA) and extended by a hierarchical refinement strategy.
The SA was chosen for its ability to explore complex, multi-dimensional solution spaces, minimizing the likelihood of hitting the local optimum trap by probabilistically accepting sub-optimal solutions in the early stages of the process, thus allowing a more extensive search before converging on the optimum. A hierarchical refinement strategy has been incorporated into the SA algorithm, which subdivides the model into smaller regions as the inversion stabilizes. This allows the algorithm to continually adjust each subpart until the stop condition is met. This generational approach improves the accuracy of the inversion results and provides a more detailed insight into the geometry of irregular or complex subsurface structures, which is more representative of reality than traditional parametric inversion methods, which rely on predefined geometries and may result in local details being overlooked. In accordance with the refinement strategy, subcomponents self-adjust their boundaries, contingent on their neighborhood, while searching for optimal solutions. This approach enables the model to maintain depth and spatial consistency over successive iterations.
In order to assess the effectiveness of the algorithm, 3D geomagnetic data were collected from two case studies within the ANR's GEOPRAS project. These cases are shipwrecks located on the beaches of Sables-d'Or-les-Pins (Fréhel, Côtes-d'Armor) and Trez Rouz (Camaret-sur-Mer, Finistère) in France. The inversion program provides two subsurface models of shipwrecks as its results. These models contain the information on the magnetization, location and geometry of the shipwrecks. Subsequent excavations showed that the predicted models differed by a few decimeters from the actual finds. Considering the size of the shipwrecks, this demonstrates the robustness and accuracy of the algorithm in reconstructing subsurface shapes and locations.
By reducing uncertainties in depth and geometry, this three-dimensional inversion technique provides a scalable solution for subsurface investigations. While the current focus is on archaeological shipwrecks, the approach is adaptable to broader applications ranging from small-scale cultural heritage studies to large-scale geological exploration. This versatility makes it a powerful tool for advancing geomagnetic prospection across disciplines.
How to cite: Liu, Y., Lévêque, F., and Hulot, O.: Probabilistic inversion method for 3D geomagnetic data: A new approach to determine the geometry and depth of subsurface sources, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10676, https://doi.org/10.5194/egusphere-egu25-10676, 2025.
In this work, the improved relativistic hybrid particle-in-cell & lattice Boltzmann method (RHPIC-LBM2), by adding multi-layer and the multi-component-abundance (M-CAI, Fe, Ni, electrons) module, is developed and applied to investigate the geomagnetic reversal on the supercomputer platform. Firstly, the explicit expression of the M-CAI terms under fully coupled hydro-dynamic-kinetic continuous scales was deduced by considering the turbulence-resistance-induced self-generated organization and the turbulence-viscosity-induced self-feeding-sustaining with dynamo mean field theory. Then, the input module was improved, and a new M-CAI module with the original RHPIC-LBM model algorithm code was added. Finally, the improved turbulence Debye-shielding model, which provides a way to describe the macro-dynamic averaging effect (2,200 kilometers) from numerous micro-kinematic (Debye length scale) evolutions, was used to explore the 2,200-kilometer-thick charged flow, current density, and magnetic field under fully coupled scale. The main findings of the present study are as follows: 1) the combined effect of buoyancy force (generated by mantle convection in the direction of the celestial axis; the convection from the heat of the inner core, outer core, and mantle), the centrifugal force-I (generated by the Earth rotates in the direction outward away from the celestial axis), the centrifugal force-II (generated by the earth revolution around the sun in the direction of Earth's axis of revolution, perpendicular to the ecliptic plane), the friction force-I (generated by the different velocity between the outer core and inner core in the tangential direction at the equatorial plane), the friction force-II(generated by the spin of the outer core and the mantel), the tidal force (generated by the gravitational attraction between the Earth and the moon); 2) the magnetic field will flap in 150~170 million years with 2~4 thousand years. These results may be a key point and give new insights for the investigation of the Earth-Moon space environment, which serves for the planetary environment research in 'National Mid- and Long-term Plan for Space Science in China (2024-2050) through the observational Earth magnetic model (Macao Science 1. WM3 real-time observational data).
URL:分享文件：https://pan.cstcloud.cn/s/ftqeokDkRzc
How to cite: Li, Y.: Investigation of the geomagnetic reversal through the multi-layer and multi-component-abundance model and improved RHPIC-LBM code on the supercomputer platform , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9248, https://doi.org/10.5194/egusphere-egu25-9248, 2025.
Posters virtual: Tue, 29 Apr, 14:00–15:45 | vPoster spot 2
EGU25-11991 | Posters virtual | VPS28
Harnessing Swarm Satellite Magnetic Data to Revolutionize Earthquake PredictionTue, 29 Apr, 14:00–15:45 (CEST) | vP2.5
Predicting earthquakes remains one of the most profound challenges in seismology and a long-standing aspiration for humanity. Among the array of potential precursors, changes in the Earth’s magnetic field have emerged as a promising yet contentious avenue of research (e.g., De Santis et al., 2015). With advancements in satellite technology, especially with the advent of the European Space Agency’s Swarm mission, we now have the unprecedented ability to measure the magnetic field with extraordinary precision, unlocking exciting opportunities for earthquake forecasting.
In this study, we leverage data from Swarm satellites to investigate whether magnetic anomalies can serve as reliable precursors to earthquakes. Our approach integrates two complementary methodologies: a) global statistical analysis: We applied superposed epoch and spatial techniques to several years of global earthquake data, correlating it with Swarm's magnetic field measurements (De Santis et al., 2019; Marchetti et al., 2022); b) tectonic case study: We focused on major earthquakes occurring from 2014 to 2023 within the tectonically active Alpine-Himalayan belt (Alimoradi et al., 2024).
To analyze these events, we employed an advanced automated algorithm (De Santis et al., 2017) to detect magnetic anomalies in satellite data recorded up to 90 days prior to global earthquakes and up to 10 days before events in the Alpine-Himalayan region. The findings revealed compelling evidence of clear magnetic anomalies preceding earthquakes. Notably, in the Alpine-Himalayan case study, we observed a striking correlation between earthquake magnitude and the duration and intensity of these anomalies: larger earthquakes were associated with stronger and more prolonged signals.
Our predictive framework demonstrated remarkable performance, achieving an accuracy of 79%, a precision of 88%, and a hit rate of 84%. These results underscore the transformative potential of satellite-based magnetic field analysis, paving the way for an operational earthquake prediction system. Such a system could serve as a powerful tool for mitigating the devastating impacts of earthquakes and safeguarding communities worldwide.
The work has been developed in the framework of the following projects: UNITARY- Pianeta Dinamico (funds from MUR), SPACE IT UP (PNRR), Limadou Scienza + (ASI) and FURTHER (INGV).
References
Alimoradi, H., Rahimi, H., De Santis, A. Successful Tests on Detecting Pre-Earthquake Magnetic Field Signals from Space, Remote Sensing, 16(16), 2985, 2024.
De Santis et al., Geospace perturbations induced by the Earth: the state of the art and future trends, Phys. & Chem. Earth, 85-86, 17-33, 2015.
De Santis A. et al., Potential earthquake precursory pattern from space: the 2015 Nepal event as seen by magnetic Swarm satellites, Earth and Planetary Science Letters, 461, 119-126, 2017.
De Santis A. et al. Precursory worldwide signatures of earthquake occurrences on Swarm satellite data, Scientific Reports, 9:20287, 2019.
Marchetti D., De Santis A., Campuzano S.A., et al. Worldwide Statistical Correlation of eight years of Swarm satellite data with M5.5+ earthquakes, Remote Sensing, 14 (11), 2649, 2022.
How to cite: De Santis, A., Campuzano, S. A., Cianchini, G., Alimoradi, H., Perrone, L., and Rahimi, H.: Harnessing Swarm Satellite Magnetic Data to Revolutionize Earthquake Prediction, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11991, https://doi.org/10.5194/egusphere-egu25-11991, 2025.
EGU25-2898 | ECS | Posters virtual | VPS28
Measurements of Earth's magnetic field anomalies caused by meteorite impactsTue, 29 Apr, 14:00–15:45 (CEST) | vP2.24
Meteorites that have impacted the Earth's surface in the past have created impact craters. Most of these craters have not been preserved in a form that allows for their contemporary identification, but some, especially in Central and Northern Europe, have been described and classified as geological structures formed by meteorite impacts. When a celestial body strikes the Earth's surface, it causes a temporary increase in temperature to several hundred degrees Celsius, sometimes exceeding the Curie temperature for ferromagnetic rocks and minerals that make up the near-surface layer. Magnetization is relatively stable from a geological time perspective. The magnetic record in magnetite is usually stable and is quite difficult to remagnetize (Fassbinder, 2015).
The impact leads to a change in the direction of magnetization in the minerals, which sometimes persists after the impact. This phenomenon is known as Thermoremanent Magnetization (TRM). It is characteristic of meteorite impact sites. This property is attributed to minerals cooled from high temperatures resulting from plutonic/volcanic processes or meteorite impacts. It is one of several types of remanent magnetization, but only this type will be present in impact structures (Fassbinder, 2015).
The project aims to conduct research in the field of applied geophysics and the magnetic properties of rock and mineral samples in the area of craters formed by meteorite impacts in the context of thermomagnetic anomalies.
As part of this project, proton magnetometer measurements have been conducted in the areas of the Morasko craters in Poland, the Dobele crater in Latvia, the Vepriai crater in Lithuania, and several craters in Estonia. Samples from the Estonian craters have been collected for paleomagnetic studies, which will soon be analyzed using a rotational magnetometer and a magnetic susceptibility instrument. The results of the magnetometric measurements are very promising and exhibit characteristic patterns of magnetic field anomalies typical of impact craters.
The project is funded under the 'Pearls of Science' program by the Ministry of Science and Higher Education of the Republic of Poland.
How to cite: Zawadzki, M., Godlewska, N., and Oryński, S.: Measurements of Earth's magnetic field anomalies caused by meteorite impacts, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2898, https://doi.org/10.5194/egusphere-egu25-2898, 2025.
