The irregular variation of geomagnetic activity caused by the solar wind interaction with the magnetosphere/ionosphere (space weather) occurs in wide temporal and amplitude ranges. Major geomagnetic storms can induce geoelectric fields in the Earth conducting layers (through the lithosphere and down to the mantle), which may, in turn, be responsible for generating geomagnetically induced currents (GICs). The vulnerability of grounded conducting infrastructures, particularly electrical power transmission systems, to GICs, makes it important to understand the relation between the varying geomagnetic field components and the generated GICs, as well as the role of the local conductivity, i.e., geology, on the inducing process. Looking for proxies that better translate this relation is an open matter of debate.

In this work, we present a comprehensive study of several possible candidates for GIC proxies. We use geomagnetic time series from the Portuguese mid-latitude Coimbra observatory (COI) to calculate geomagnetic indices considering different periods (whole-storm duration, 3-h, 1-h and 1-min), with different focuses on the field components or their derivatives, and discuss their advantages and limitations. We compare the computed indices with both GIC simulations of the Portuguese mainland high voltage power network (150, 220 and 400 kV) (Alves Ribeiro et al., 2021), and observations from a Hall effect sensor based system installed at a power transformer located in the vicinity of Coimbra. 
We then propose a better GIC proxy, an index obtained from geomagnetic field components filtered by convolution with a uniform conductivity Earth model filter (EGIC index), based on previous work by Marshall et al (2010,2011). We search for empirical parameters that may contain information on local conductivity effects and power network geometry.

This study is funded by national funds through FCT (Portuguese Foundation for Science and Technology, I.P.), under the project MAG-GIC (PTDC/CTA-GEO/31744/2017). FCT is also acknowledged for support through projects UIDB/50019/2020-IDL, PTDC/CTA-GEF/1666/2020 (MN) and PTDC/CTA-GEO/031885/2017 (MN). CITEUC is funded by FCT (UIDB/00611/2020 and UIDP/00611/2020). We acknowledge the collaboration with REN (Redes Energéticas Nacionais).

References:
Alves Ribeiro J., F.J. Pinheiro, M.A. Pais, 2021. First Estimations of Geomagnetically Induced Currents in the South of Portugal. Space Weather, 19(1)
Marshall R. A., C. L. Waters, M. D. Sciffer (2010). Spectral analysis of pipe‐to soil potentials with variations of the Earth’s magnetic field in the Australian region. Space Weather 8.5
Marshall, R. A., et al (2011). "A preliminary risk assessment of the Australian region power network to space weather." Space Weather 9.10

How to cite: Gutiérrez Pinheiro, F. J., Neres, M., Pais, M. A., Alves Ribeiro, J., Santos, R., and Cardoso, J.: Towards an improved proxy for geomagnetically induced currents (GICs), EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8015, https://doi.org/10.5194/egusphere-egu22-8015, 2022.

The rate of change of the horizontal component of the geomagnetic field is a useful proxy for determining the severity of geomagnetically induced currents (GIC). While contemporary measurements for geomagnetic disturbances (GMD) are available from a number of arrays, short timescale datasets are not ideal for the characterisation of extreme events since their data sets are rarely indicative of the most extreme geomagnetic conditions. In the absence of long duration data sets, statistical methods have to be employed to assess the overall longer timescale historical power occurrence distributions, so as to extrapolate the behaviour of their high-end tail and which is required for the assessment of extreme events. Conversely, the CANOPUS array, subsequently expanded and operated as the CARISMA magnetometer array (www.carisma.ca), has been in continuous operation in Canada since 1986, first with a 5-second and then more recently with a 1-second cadence. Using that long timebase dataset we are able to evaluate the occurrence distributions of 5-second cadence measurements for over 10,000 operational days for each of several stations. Of particular significance for the expected magnitude of extreme events is an assessment of whether the disturbances follow a power law or log-normal distribution. Such indications can inform risk assessments on the potential for extremely hazardous GICs, for example in the estimation of a 1-in-100-year event. The CANOPUS/CARISMA GMD occurrence distributions, overall, appear to be well-approximated by log-normal rather than power law distributions. However, for extreme events, the local time at which the largest GMD typically occurs rotates away from the midnight sector, such that the largest events in the tail of the distribution most often occur instead at dawn. This has significant implications for assessing the size of expected extreme GMD events, and indeed the local time of the largest vulnerability, with clear applications for assessing extreme space weather impacts on the electric power grid. 

How to cite: Dimitrakoudis, S., Mann, I. R., Kale, A., and Milling, D. K.: Long-term Trends and Occurrence Distributions of Geomagnetic Fluctuations as Revealed by 35 Years of CARISMA Observations at 5s Cadence, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9999, https://doi.org/10.5194/egusphere-egu22-9999, 2022.

The response of the magnetosphere-ionosphere (MI) system to the forcing by plasma of solar origin gives rise to several phenomena relevant to Space Weather. In particular, part of the energy injected into the ionosphere by means of field-aligned currents (FACs) connecting the magnetosphere with the high-latitude ionosphere is converted into mechanical energy and dissipated via Joule heating. Under reasonable assumptions, in the direction parallel to the geomagnetic field the only relevant contribution to dissipation is from the Ohmic term. Dissipated power density may significantly affect the physical parameters characterizing the upper ionosphere, such as electron temperature and density, and alter its chemical composition. This can result, for example, in the increased atmospheric drag and affect the satellite orbits. For this reason, understanding the dissipation of FACs in the topside ionosphere is important to shed light on the physical processes involved in MI coupling. Power density dissipated by FACs in crossing the topside ionosphere can be estimated by using Swarm data. Here, for the first time, we show statistical maps of power density features dissipated by FACs by using six-year time series of electron density and temperature data acquired by the Langmuir Probes onboard the Swarm A satellite (flying at an altitude of about 460 km) at 1 s cadence, together with the field-aligned current density product provided by the ESA’s Swarm Team at the same cadence. Maps of the same quantity under different levels of geomagnetic activity are also shown and discussed in light of the previous literature.

This work is partially supported by the Italian National Program for Antarctic Research under contract N. PNRA18 00289-SPIRiT and by the Italian MIUR-PRIN grant 2017APKP7T on "Circumterrestrial Environment: Impact of Sun-Earth Interaction".

How to cite: Giannattasio, F., Consolini, G., Coco, I., Pezzopane, M., and Pignalberi, A.: Power density dissipated by field-aligned currents in the topside ionosphere, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-2259, https://doi.org/10.5194/egusphere-egu22-2259, 2022.

How to cite: Lovati, G., De Michelis, P., Consolini, G., and Berrilli, F.: Pressure-Gradient current at high latitude from Swarm measurements , EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6096, https://doi.org/10.5194/egusphere-egu22-6096, 2022.

Solar flares are known to enhance the ionospheric electron density and thus influence the D- and E-region electric currents in the sunlit hemisphere.  The resultant geomagnetic disturbances (called "crochet") are found at both low latitudes and high latitudes with a minimum in between.  The subsolar response, with short-lived and symmetric changes around the subsolar region, is understood as a temporal re-distribution of the electron density.  However, no systematic study has been made of the high-latitude responses, covering the auroral oval, the cusp, and the dayside sub-auroral region.  Even global patterns are not well described or understood.  

Using data from GOES satellites and SuperMAG, we made a statistical study of the high-latitude geomagnetic responses to X-class solar flares in the northern polar region.  First, we needed to create a reliable X-flare database that we could use to get precise timings of when the flares start and when they stop. We merged XRS databases from different GOES satellites to create a X-class solar flare database between 1984 and 2017, gathering 331 X-flares over 34 years.  

For all these X-flares, we plotted the geomagnetic disturbance (∆B) on a polar map during the periods when the X-ray flux exceeds 1e-4 W/m2 (>X1 flare).  Plots were made also for merged data, i.e., different events on the same map organized by geographic coordinates and local time to obtain the average disturbance pattern caused by the flares.  Large events (∆B >300 nT) were excluded to minimize the contamination from substorm events.  

In these "merged" plots, we classify the data by season (summer - 4 months, equinox ±2 months, winter 4 months), flare intensity (X1-X2 flares and >X2 flares), and maximum ∆B among all stations > 65° GGlat (< 100 nT and 100-300 nT). 

Except for winter, we found a large poleward ∆B which peaks at 13-16 LT, particularly for > X2 flares, but no enhancements in the pre-noon sector.  This asymmetry, surprisingly, remains even after we consider IMF By polarity.  We do not have any plausible explanation for this result, and we will discuss it during the presentation.

[Acknowledgement: This work is resulted from a 2021 summer internship study at the Swedish Institute of Space Physics, Kiruna.   The GOES X-ray data is provided by NOAA (USA). The geomagnetic data at high latitudes are obtained from SuperMAG and are originally provided by DTU (Denmark), TGO (Norway), FMI (Finland), SGO (Finland), SGU (Sweden), GSC (Canada), USGS (USA), AARI (Russia), PGI (Russia), IZMIRAN (Russia), BAS (UK), BGS (UK), IPGP (France), PAS (Poland), ZAMF (Austria), and ASCR (Czech)]

How to cite: Cavarero, P., Yamauchi, M., Johnsen, M. G., Ohtani, S.-I., and Machol, J.: Dawn-dusk asymmetry of solar flare-driven ionospheric current at high latitudes, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6269, https://doi.org/10.5194/egusphere-egu22-6269, 2022.

The development of satellite measurements over the past four decades has allowed us to understand the magnetic field in the Earth environment at higher temporal and spatial resolution than before. This is most evident for satellite ensembles such as ESA’s Swarm constellation which allows simultaneous global coverage with three independent satellites.

Thanks to Swarm’s particular configuration, we can take advantage of the Local Time sampling difference between Swarm A/C and Swarm B in order to estimate the low degree variation of the external magnetic field in latitude and longitude. We separate the external and induced fields measured at satellite altitude, and obtain the spherical harmonic decomposition of each source to degree and order 3 twice per day. However, there is a trade-off between spatial and temporal resolution and clear disadvantages occur when the measured field varies rapidly during a geomagnetic storm, since the method used will result in coefficients of the averaged field over the chosen time interval rather than the peaks.

We compare our results with previous models of the external field during the St Patrick storm 2015, which used up to four different local time simultaneous coverage, as well as during quiet times and lesser storms using our own solutions. We find good agreement in each case.

In this talk we will describe the algorithm and methodology used and show results over the lifetime of the Swarm mission to date (2013-). A new daily product for the Swarm mission (MMA_SHA_2E) is being developed.

How to cite: Gomez Perez, N. and Beggan, C.: Swarm Fast Track spherical harmonic model of the external magnetic field to degree and order 3, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4733, https://doi.org/10.5194/egusphere-egu22-4733, 2022.

Understanding physical processes that drive dynamics of the radiation belts - the high-energy charged particle population trapped by the geomagnetic field in the inner magnetosphere, is of great importance for science and society. In fact, this population dynamically interacts with the solar wind and geomagnetic field over various temporal and spatial scales, and can have significant impacts on its surrounding environment, including hazards to satellites and astronaut health. Understanding the relevant acceleration mechanisms of these particles can help not only to uncover the underlying physics, but also to improve our ability to predict and to protect. Despite numerous attempts over several decades, unfolding the dynamics of interactions in such systems is still one of the challenging research areas and has not yet been achieved, due to the complex and nonlinear underlying physics of the radiation belts. However, information theory is not constrained by such limitations and has proven itself to be a powerful non-parametric approach to discover the causal interactions among different nonlinear complex systems, and can be considered complementary to physics-based approaches. In this work, we apply entropy-based causality measures such as conditional mutual information to determine the information transfer between various variables including different solar wind parameters and geomagnetic activity indices obtained from NASA’s OmniWeb service and omnidirectional electron fluxes from the MagEIS units onboard Van Allen Probe B in the outer radiation belt, ranging in energy from a few keV to several MeV. We find significant information flow from low energy electrons into high energy ones as well as from some solar wind/geomagnetic field parameters into electron fluxes of various energies. We are confident that our results provide great prospects for future targeted research on the dynamical mechanisms underlying radiation belts dynamics.

This work has benefitted from discussions within the International Space Science Institute (ISSI) Team # 455 “Complex Systems Perspectives Pertaining to the Research of the Near-Earth Electromagnetic Environment.”  P.M. and M.P. are supported by the Czech Science Foundation, Project No. GA19-16066S and by the Czech Academy of Sciences, Praemium Academiae awarded to M. Paluš.

How to cite: Manshour, P., Papadimitriou, C., Balasis, G., Palus, M., Wing, S., Daglis, I. A., Donner, R., Boutsi, A. Z., Consolini, G., Kurths, J., and Tsurutani, B. T.: Causality and information transfer in interactions of solar wind, radiation belts and geomagnetic field, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10681, https://doi.org/10.5194/egusphere-egu22-10681, 2022.

The outer belt electron radiation belt is highly dynamic, responding to a superposition of a variety of acceleration and loss processes imposed along the electron drift orbits to produce increases and decreases in flux on timescales from minutes, to hours, days and years. These trapped relativistic so-called ‘satellite killer’ electrons can penetrate spacecraft shielding and cause damage to internal electronics and single-event upsets. Understanding and predicting the radiation belt environment, therefore, is valuable for the understanding and mitigation of these potentially catastrophic impacts. Magnetic measurements from the constellation of Swarm satellites in low-Earth orbit (LEO) can be used to monitor the populations of electromagnetic ion cyclotron (EMIC) waves along their orbits. This is significant for radiation belt applications since these waves are believed to be potentially responsible for some fast losses of radiation from the Van Allen belts through fast scattering into the loss cone. Despite being far from the equatorial plane where most of the radiation belts are trapped, the propagation of EMIC waves along field lines allows an assessment of these wave populations from LEO, Swarm and similar satellites in LEO traversing the radiation belts four times in each approximately 90-minute orbit. Here we demonstrate how Swarm can be used to detect and characterize the EMIC wave populations, and compare the observed EMIC wave populations to simulations of two strong magnetic storms where radiation belt modeling based on radial diffusion demonstrated the likelihood of a missing fast loss process and which might be explained by EMIC wave-particle interactions. The current state-of-the-art for the incorporation of EMIC-related wave losses is based on empirical means, related for example to solar wind compressions. Here we investigate, despite the often spatio-temporally localized character of some EMIC wave populations, whether magnetic field data from the Swarm constellation could be used in an observational data-constrained approach for the inclusion of EMIC wave losses in radiation belt modelling. LEO satellites have the advantage over high-apogee near-equatorial satellites in that the latter only cross L-shells comparatively slowly; similarly, the interpretation of EMIC wave location from ground-based magnetometer networks is complicated by propagation in the ionospheric duct. Through the use of multi-spacecraft techniques, and/or those which utilise electric and magnetic data together, we demonstrate how it is possible to reliably disentangle EMIC waves from nearby field-aligned currents. Such techniques provide hitherto unprecedented observation capability for the specification of EMIC waves from LEO for use in radiation belt modelling. Future work could examine the utility of such data for both improving the accuracy of radiation belt models, and for the nowcasting and even forecasting of belt dynamics.

How to cite: Pakhotin, I., Mann, I., Ozeke, L., Olifer, L., and Dimitrakoudis, S.: Swarm as an EMIC Wave Monitor: Applications for Radiation Belt Modelling and Specification, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10887, https://doi.org/10.5194/egusphere-egu22-10887, 2022.

Ground-based indices, such as the Dst, ap and AE, have been used for decades to describe the interplay of the terrestrial magnetosphere with the solar wind and provide quantifiable indications of the state of geomagnetic activity in general. These indices have been traditionally derived from ground-based observations from magnetometer stations all around the Earth. In the last 7 years though, the highly successful satellite mission Swarm has provided the scientific community with an abundance of high quality magnetic measurements at Low Earth Orbit (LEO), which can be used to produce the space-based counterparts of these indices, such the Swarm-Dst, Swarm-ap and Swarm-AE indices. In this work, we present the first results from this endeavour, with comparisons against traditionally used parameters. We postulate on the possible usefulness of these Swarm-based products for a more accurate monitoring of the dynamics of the magnetosphere and thus, for providing a better diagnosis of space weather conditions.

How to cite: Papadimitriou, C., Balasis, G., Boutsi, A. Z., Antonopoulou, A., Moutsiana, G., Daglis, I. A., Giannakis, O., Consolini, G., Gjerloev, J., and Trenchi, L.: Swarm-derived indices of geomagnetic activity, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6336, https://doi.org/10.5194/egusphere-egu22-6336, 2022.

Earth's magnetospheric dynamics displays dynamical complexity during magnetic substorms and storms. This complex dynamics includes both  stochastic and deterministic features, which manifest at different timescales. In this work, we investigate the stochastic properties of the  magnetospheric substorm dynamics by analysing the Markovian character of the SuperMAG SME time series, which is used as a proxy of the energy  deposition rate in the auroral regions. In detail, performing the Chapman-Kolmogorov test, the SME dynamics appears to satisfy the Markov condition  below 100 minutes. Moreover, the Kramer-Moyal analysis allows to highlight that a purely diffusive process is not representative of the magnetospheric  dynamics, as the fourth order Kramers-Moyal coefficient does not vanish. As a consequence, we show that a model comprising both diffusion and  Poisson-jump processes is more suitable to reproduce the SME dynamical features at small scales. A discussion of the similarities and differences  between this model and the actual SME properties is provided with a special emphasis on the metastability of the Earth’s magnetospheric dynamics.  Finally, the relevance of our results in the framework of Space Weather is also addressed.

How to cite: Benella, S., Consolini, G., Stumpo, M., and Alberti, T.: Markovian features of the Super-MAG Auroral Electrojet Index, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-4513, https://doi.org/10.5194/egusphere-egu22-4513, 2022.

In order to monitor space weather events and their impacts, ground magnetic field data has proven to be a long-lasting and powerful source of information. For the determination of space weather effects, it is essential to extract and understand the evolution of the quiet-time magnetic field. However, the data shows a high degree of complexity since the Earth’s magnetic field is a superposition of sources that cover a broad amplitude and frequency spectrum. In sub-auroral regions, it is well understood that the solar quiet current system contributes to the quiet signal with smooth patterns that depend on season and local time, having distinct periods of 24 hours and beneath.

In this work, we apply signal filtering techniques on time-series magnetic data from ground observatories in sub-auroral regions. In order to extract the solar quiet current contributions, we use its specific periods of 24h and beneath and analyse the results with respect to season, local time, and day-to-day variability between 1991 and 2019. Careful investigations and interpretation of the contributing sources are given, confirming the main contribution to the filtered signal is the solar quiet current system. This implies that the filter approach is able to extract the quiet magnetic field variations and due to its simplicity may be used for real-time determination of the quiet magnetic field, including magnetic baselines. 

How to cite: Haberle, V., Marchaudon, A., Chambodut, A., and Blelly, P.-L.: Extraction of ground magnetic signatures from solar quiet current systems in sub-auroral regions, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-1416, https://doi.org/10.5194/egusphere-egu22-1416, 2022.

The geomagnetic observatories managed by INGV (Istituto Nazionale di Geofisica e Vulcanologia), both in Italy and Antarctica, send data to a server and the data are collected and stored in a MySQL database. The database has been operating for almost two decades and it is implemented on a local server which serves also as a web portal for the data display and distribution. By analyzing the data of all the INGV geomagnetic observatories at middle and polar latitudes, i.e. the values of the H, D and Z components, the F module and the K indices, the algorithm aims to distinguish the activity of the Earth's magnetic field in the following categories: “Quiet Period”, “Local disturbance” and “Magnetic Activity”, possibly distinguishing, within the latter, the level and the kind of event (sudden impulse, sudden ionospheric and magnetic disturbance driven by solar flare, magnetic storm or substorm). A preliminary automatic procedure allows to detect possible instrumental failure from a comparison between the vector components and the total field intensity in each observatory. A second level of check allows to discriminate local or regional against global features with the final goal to reject local noise, possibly of anthropic nature, eventually present in a single observatory through a majority logic based procedure. After these first filtering steps an automatic software procedure provides an empirical estimation of the current  Magnetic Activity (nowcasting) organized according to the above three possible categories. The embedded algorithm in the procedure operates on the geomagnetic field element (H, D, Z and F) and the local K indices of all observatories. The operations that the algorithm performs are aimed to identify the impulsive components in the signal, which are caused by external events. The quiet field component is removed from the signal, leaving the impulsive components present in the signal almost unaltered. If in the residual field is present a significant activity (with respect to an appropriate threshold) a procedure is performed that distinguishes between an isolated impulse or a cluster of impulses, by using time windows of different sizes. The whole procedure allows us to generate two different geomagnetic activity indices, one at low and the other at high latitude. In a final step we compute a cross correlated geomagnetic index comparing processed data at low and high latitude to retrieve a large spatial scale index.

How to cite: Bagiacchi, P., Cafarella, L., Del Corpo, A., Di Mauro, D., Lepidi, S., and Regi, M.: A quasi-real time geomagnetic activity index from ground based measurements at geomagnetic observatories run by italian INGV for space weather nowcasting, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-8752, https://doi.org/10.5194/egusphere-egu22-8752, 2022.

The purpose of this study is to analyze the associated spectrum of geomagnetic field, frequencies intensity and the time of occurrence of geomagnetic storms. Also, we set out to analyze the possibility of predicting these geomagnetic storms.

A geomagnetic storm is a temporary disturbance of the Earth's magnetosphere caused by solar coronal mass ejections, coronal holes or solar flares. Solar wind shock wave typically strikes the Earth’s magnetic field 24 to 36 hours after the event.

This only happens if the shock wave travels in a direction toward Earth. The solar wind pressure on the magnetosphere will increase or decrease depending on the Sun's activity. These solar wind pressure changes modify the electric currents in the ionosphere. The data used in this paper are acquired within the Surlari Observatory, and additional information to characterize the geomagnetic storms analyzed, we obtained from the specialized sites such as www.intermagnet.org and www.noaa.gov. Information about geomagnetic data from other observatories, as well as planetary physical parameters allowed us to perform comparative studies between the data recorded in different observatories.

We calculated the variation of the correlation coefficients, with mobile windows of various sizes, for the recorded magnetic components at different latitudes and latitudes. Also, we have used for this purpose a series of filtering algorithms, spectral analysis and wavelet with different mather functions at different levels.

Wavelets allow local analysis of magnetic field components through variable frequency windows. Windows that contain longer time intervals allow us to extract low-frequency information, average ranges of different sizes lead to extraction of medium frequency information, and very narrow windows highlight the high frequencies or details of the analyzed signals. The wavelet functions describe the orthogonal bases with signal approximation properties, while the orthonormal bases in the Fourier analysis are made up of sinusoidal waves.

Estimation of geomagnetic field disturbances is similar to the standard problem of estimating a signal disturbed by signal theory.

The term noise refers to any modification that changes the periodic or quasi-periodic characteristics of the original signal.

The Dst index is used to assess the severity of geomagnetic storms and to determine the effects of the solar wind on space and terrestrial infrastructures and is very important to be able to predict the effects of the geomagnetic storm.

The numerical experiments presented in this paper are part of different methodological categories, with the same purpose, but with different approaches. The common goal is the prediction of geomagnetic disturbances and the methodologies used comparatively are Fourier spectral deconvolution, autoregressive models on time series and recurrent Long Short Term Memory (LSTM) neural networks that are capable of long-term dependence.

How to cite: Asimopolos, L., Asimopolos, N.-S., Stanciu, A., and Asimopolos, A.-A.: Statistical and spectral study of geomagnetic storm forecasting, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-6037, https://doi.org/10.5194/egusphere-egu22-6037, 2022.