Extreme Space Weather Research Articles

Extreme Space Weather Impacts on GNSS Timing Signals for Electricity Grid Management

AbstractExtreme space weather events can have serious impacts on critical infrastructure, including Global Navigation Satellite Systems (GNSS). The use of GNSS, particularly as sources of accurate timing signals, is becoming more widespread, with one example being the measurement of electricity grid frequency and phase information to aid grid management and stability. Understanding the likelihood of extreme space weather impacts on GNSS timing signals is therefore becoming vital to maintain national electricity grid resilience. This study determines critical intensity thresholds above which the complete failure of a GNSS based timing system may occur. Solar radio bursts are identified as a simple example to investigate in more detail. The probability of occurrence of an extreme space weather event with an intensity equal to or greater than the critical intensity is estimated. Both a power law and extreme value theory were used to evaluate recurrence probabilities based on historical event frequencies. The probability was estimated to be between 3%–12% per decade to cause the complete failure of any GNSS‐based timing system.

May 11–12 Extreme Space Weather Events Brief and Dose Rate Model Response

In this brief paper, we analyze space weather events that occurred on May 11 and 12, 2024, from the perspective of an operational space weather center that provides advisories for civil aviation. One of the key metrics monitored by the center is the radiation dose rate at operational flight altitudes. A model implemented by the center provides the dose rate in real time. The model showed that dangerous levels were momentarily exceeded just above the usual 30,000 feet level during the events. This paper highlights differences in models used by various space weather centers, emphasizing the need for harmonization.

Observational Overview of the May 2024 G5-Level Geomagnetic Storm: From Solar Eruptions to Terrestrial Consequences

This study reports comprehensive observations for the G5-level geomagnetic storm that occurred from May 10 to 12, 2024, the most intense event since the 2003 Halloween storm. The storm was triggered by a series of coronal mass ejections (CMEs) originating from the merging of two active regions 13664/13668, which formed a large and complex photospheric magnetic configuration and produced X-class flares in early May 2024. Among the events, the most significant CME, driven by an X2.2 flare on May 9, caught up with and merged with a preceding slower CME associated with an X-class flare on May 8. These combined CMEs reached 1 AU simultaneously, resulting in an extreme geomagnetic storm. Geostationary satellite observations revealed changes in Earth’s magnetosphere due to solar wind impacts, increased fluxes of high-energy particles, and periodic magnetic field fluctuations accompanied by particle injections. Extreme geomagnetic storms resulting from the interaction of the solar wind with the Earth’s magnetosphere caused significant energy influx into Earth’s upper atmosphere over the polar regions, leading to thermospheric heating and changes in the global atmospheric composition and ionosphere. As part of this global disturbance, significant disruptions were also observed in the East Asian sector, including the Korean Peninsula. Ground-based observations show strong negative storm effects in the ionosphere, which are associated with thermospheric heating and resulting in decreases in the oxygen-to-nitrogen ratio (O/N2) in high-latitude regions. Global responses of storm-time prompt penetration electric fields were also observed from magnetometers over the East-Asian longitudinal sector. We also briefly report storm-time responses of aurora and cosmic rays using all-sky cameras and neutron monitors operated by the Korea Astronomy and Space Science Institute (KASI). The extensive observations of the G5-level storm offer crucial insights into Sun-Earth interactions during extreme space weather events and may help establish better preparation for future space weather challenges.

Unusual Forbush Decreases and Geomagnetic Storms on 24 March, 2024 and 11 May, 2024

As the current solar cycle 25 progresses and moves towards solar maxima, solar activity is increasing and extreme space weather events are taking place. Two severe geomagnetic storms accompanied by two large Forbush decreases in galactic cosmic ray intensity were recorded in March and May, 2024. More precisely, on 24 March 2024, a G4 (according to the NOAA Space Weather Scale for Geomagnetic Storms) geomagnetic storm was registered, with the corresponding geomagnetic indices Kp and Dst equal to 8 and −130 nT, respectively. On the same day, the majority of ground-based neutron monitor stations recorded an unusual Forbush decrease. This event stands out from a typical Forbush decrease because of its high amplitude decrease phase and rapid recovery phase, i.e., 15% decrease and an extremely rapid recovery of 10% within 1.5 h, as recorded at the Oulu neutron monitor station. Furthermore, on 10–13 May 2024, an unusual G5 geomagnetic storm (geomagnetic indices Kp = 9 and Dst = −412 nT) was registered (the last G5 storm had been observed in 2003). In addition, the polar neutron monitor stations recorded a Ground Level Enhancement (GLE74) during the recovery phase of a large Forbush decrease of 15%, which started on 10 May 2024. In this study, a detailed analysis of these two severe events in regard to the accompanying solar activity, interplanetary conditions and solar energetic particle events is provided. Moreover, the results of the NKUA “GLE Alert++ system”, the NKUA/IZMIRAN “FD Precursory Signals” method and the NKUA “ap Prediction tool” concerning these events are presented.

Solar Wind‐Magnetosphere Coupling Efficiency and Its Dependence on Solar Activity During Geomagnetic Storms of 23–24 Solar Cycles

AbstractSpace weather forecasts are of utmost importance in safeguarding navigation, communication, and electric power system operations, satellites from orbital drag, and the astronauts in the International Space Station from hazardous space radiation during extreme space weather conditions. The finest space weather prediction requires a clear understanding of solar wind‐magnetosphere coupling. The in‐situ measurements of the solar wind properties give unique information about the Sun and its activity on smaller to longer timescales. The present work investigates the influence of solar activity on the coupling of solar wind and Earth's magnetosphere during 23–24 solar cycles. The geomagnetic storms with Symmetric H‐component (SYMH) ≤ −85 nT during the 23–24 solar cycles are considered. We present the results of statistical analysis and relationships between the various solar wind parameters such as the total strength of interplanetary magnetic field (B) and its three‐axis components (Bx, By, and Bz), solar wind proton density (Nsw), solar wind speed (Vsw), SYMH indices, the amplitude, duration, and profile of the geomagnetic storms. The integrated electric field and integrated SYMH index during storms show the highest correlation of 0.92, implying that integrated SYMH is a better proxy of the injected solar wind energy in the magnetosphere in the form of the ring current. Moreover, we do see the difference in the solar wind‐magnetosphere coupling efficiency during the phases of 23–24 solar cycles which is intriguing.

Modeling of Nitric Oxide Infrared radiative flux in lower thermosphere: A machine learning perspective

Nitric Oxide (NO) significantly impacts energy distribution and chemical processes in the mesosphere and lower thermosphere (MLT). During geomagnetic storms, a substantial influx of energy in the thermosphere leads to an increase in NO infrared emissions. Accurately predicting the radiative flux of Nitric Oxide is crucial for understanding the thermospheric energy budget, particularly during extreme space weather events. With advancements in computational techniques, machine learning (ML) has become a highly effective tool for space weather forecasting. This effort becomes even more worthwhile considering the availability of two decades of continuous NO infrared emissions measurement by TIMED/SABER along with several other key thermospheric variables. We present the scheme of development of an ML-based predictive model for Nitric Oxide Infrared Radiative Flux (NOIRF). Various ML algorithms have been tested for better predictive ability, and an optimized model (NOEMLM) has been developed for the study of NOIRF. This model is able to extract the underlying relationships between the input features and effectively predict the NOIRF. The NOEMLM predictions have very good agreements with SABER observation during quiet time as well as geomagnetic storms. In comparison with the existing TIEGCM model, NOEMLM has very good performance, especially during extreme space weather conditions. The results of this study suggest that utilizing geomagnetic and space weather indices with ML/AI can serve as superior parameters for studying the upper atmosphere, as compared to focusing on specific species having complex chemical processes and associated uncertainties in constituents. ML techniques can effectively carry out the analysis with greater ease than traditional chemical studies.

Daily geomagnetic variations under variable IMF/solar conditions and their connection with underground conductivity changes in Japan

Fluctuations in Solar Wind (SW) and Interplanetary Magnetic Field (IMF) significantly affect the Geomagnetic Field (GF) measurements particularly during extreme space weather events. The current study investigates the variations of horizontal (H), vertical (Z) geomagnetic components under quiet and disturbed IMF and solar conditions as well as the effect of underground conductivity on the stationary geomagnetic measurements in Japan. Results of data analysis show that the response of the GF to IMF and solar parameters fluctuations is variable. The H- and Z-components were in good harmony with high visual correlation along a latitudinal profile across Japan during quiet times. On the other hand, during the disturbed times related to a Coronal Mass Ejection (CME) launched on 13 May 2005, the GF components varied with the disturbance of IMF and solar parameters. The H-components showed highly correlated variations with a significant reduction along the examined profile due to intensified ionospheric currents, while the Z-components recorded in the northern part of Japan showed abnormal daily variations pattern (positive daily variations) with an enhanced amplitude which is opposite to the normal behavior of daily variations recorded in the central and southern parts of Japan (negative daily variations). The observed enhanced and abnormal daily variation of Z-components in north Japan, which we consider a remarkable observation here, is possibly linked with underground conductivity anomaly in this region.

An Extreme Auroral Electrojet Spike During 2023 April 24th Storm

AbstractAbrupt variations of auroral electrojets can induce geomagnetically induced currents, and the ability to model and forecast them is a pressing goal of space weather research. We report an auroral electrojet spike event that is extreme in magnitude, explosive in nature, and global in spatial extent that occurred on 24 April 2023. The event serves as a fundamental test of our understanding of the response of the geospace system to solar wind dynamics. Our results illustrate new and important characteristics that are drastically different from existing knowledge. Most important findings include (a) the event was only of ∼5‐min duration and was limited to a narrow (2°–3°) band of diffuse aurora; (b) the longitudinal span covered the entire nightside sector, possibly extending to the dayside; (c) the trigger seems to be a transient solar wind dynamic pressure pulse. In comparison, substorms usually last 1–2 hr and span almost the entire latitudinal width of the auroral oval. Magnetic perturbation events (MPEs) span hundreds km in radius. Both substorms and MPEs are mainly driven by disturbances in the magnetotail. A possible explanation is that the pressure pulse compresses the magnetosphere and enhances diffuse precipitation of electrons and protons from the inner plasma sheet, which elevates the ionospheric conductivity and intensifies the auroral electrojet. Therefore, the event exhibits a potentially new type of geomagnetic disturbance and highlights a solar wind driver that is enormously influential in driving extreme space weather events.

A solar cycle clock for extreme space weather

The variable solar cycle of activity is a long-standing problem in physics. It modulates the overall level of space weather activity at earth, which in turn can have significant societal impact. The Hilbert transform of the sunspot number is used to map the variable length, approximately 11 year Schwabe cycle onto a uniform clock. The clock is used to correlate extreme space weather seen in the aa index, the longest continuous geomagnetic record at earth, with the record of solar active region areas and latitudes since 1874. This shows that a clear switch-off of the most extreme space weather events occurs when >90\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$>90$$\\end{document}% of solar active region areas have moved to within about 15° of the solar equator, from regions of high gradient in solar differential rotation which can power coronal mass ejections, to a region where solar differential rotation is almost constant with latitude. More moderate space weather events which coincide with 27 day solar rotation recurrences in the aa index, consistent with stable, persistent source regions of high speed streams, commence when the centroid of solar active region areas moves to within 15° of the solar equator. This offers a physical explanation for the longstanding identification of a two component cycle of activity in the aa index.

Prediction of ionospheric total electron content over low latitude region: Case study in Ethiopia

This study mainly focuses on the prediction of the variability of the Total Electron Content (TEC) affecting space and ground-based technological infrastructures vulnerable to extreme space weather events. The impact of solar wind conditions (SWC) can be quantified by measuring the ionosphere’s TEC. We used a machine learning (ML) algorithm based on the Support Vector Machine (SVM), Long Short-Term Memory (LSTM) Neural Network (NN), and International Reference Ionosphere 2016 (IRI 2016) models to predict the hourly TEC over Ethiopia during quiet and storm geomagnetic conditions. We considered TEC data from the Global Positioning System (GPS) stations at ADIS, CURG, and NEGE during the years 2013 to 2016. The results indicated that the SVM model predicted the hourly TEC variation with a root mean square error (RMSE) between 2.136 and 7.923 Total Electron Content Unit (TECU) under different ionospheric conditions. For the LSTM model, the RMSE between the predicted and observed TEC lies between 1.483 and 2.527 TECU. But the empirical IRI 2016 models’ RMSE from GPS TEC is in the range of 4.777 and 14.519 TECU. The statistical study points out the LSTM has the highest prediction accuracy and is the most robust for accurate prediction of ionospheric TEC in comparison to the SVM and IRI 2016 models throughout both storm and quiet periods. The result can be further improved with a lower RMSE (high correlation) by utilizing auxiliary data and increasing the number of stations employed in the study. This research adds fresh insights to deep learning applications in space weather forecasting in the region of interest.

Thermospheric Density Estimation Method Using a First-Order Gauss–Markov Process

Low-Earth-orbit (LEO) spacecraft are significantly influenced by atmospheric drag. Accurately estimating thermospheric density is pivotal for the precise calculation of drag acceleration. However, thermospheric density along a specific orbit, computed using existing thermospheric models, has certain inaccuracies. In this work, a first-order Gauss–Markov process is used to model the deviation of atmospheric drag acceleration. With the Markov parameter of the initial state iteratively computed through sequential estimation and the smoothing method, the thermospheric density is derived from high-precision GPS measurements. In simulation scenarios, the root-mean-square error and relative error of the estimated thermospheric density reduce by about 45 and 50% relative to the prior density, respectively. Using the estimated density for orbit propagation, satellite trajectories’ one-day position and velocity error are, respectively, within 100 m and 0.1 m/s, and an average improvement in orbit precision is over 80%. The proposed method has been applied to the real Tsinghua Science Satellite (Q-SAT) GPS measurements for effectiveness verification. It shows strong adaptability under extreme space weather and during the occurrence of geomagnetic storms. Due to the estimated Markov parameter of the initial state obeying the Langevin dynamics properties, the proposed method also offers short-term thermospheric density forecasting potential.

Identification and extraction of type II and III radio bursts based on YOLOv7

Solar radio bursts (SRBs) are extreme space weather events characterized by intense solar radio emissions that are closely related to solar flares. They represent signatures of the same underlying processes that are responsible for well-documented solar phenomena such as sunspots, solar flares, and coronal mass ejections (CMEs). The study of SRBs holds significant importance as it provides a means to monitor and predict solar flares and CMEs, enhancing our ability to forecast potential impacts on Earth’s communications and satellites. Typically, SRBs below several hundred megahertz can be categorized into five types (I–V), with type II and type III bursts being the most prevalent. This study introduces a novel approach based on the YOLOv7 model for the detection and classification of type II and type III SRBs. The proposed method effectively identifies and classifies various SRB types, achieving a mean average precision accuracy of 73.5%. A trained neural network was deployed for SRB detection in the Chashan Broadband Solar radio spectrograph at meter wavelength (CBSm) data, enabling the extraction of valuable SRB information for subsequent research. This demonstrates that even when we are dealing with extensive datasets, this method can automatically recognize outbursts and extract pertinent physical information. Although our experiments with the CBSm dataset currently rely on the daily spectrum, further advancements in CBSm backend data processing techniques are expected to enable near-real-time burst detection, which is a powerful tool for accurately assessing and analyzing SRBs, and significantly contribute to the field of space weather forecasting and protective measures. Furthermore, the applicability of this method to other stations within the Chinese Meridian Project II (e.g., Mingantu Spectral Radioheliograph and Daocheng Solar Radio Telescope) enhances the capability of space weather data fusion and model development. Therefore, this research represents a substantial contribution to the domain of space weather research, offering a valuable tool for the detection and classification of SRBs and thereby improving our ability to predict and mitigate the impacts of extreme space weather events on Earth’s technology and infrastructure.

Modelling electrified railway signalling misoperations during extreme space weather events in the UK

Space weather has the potential to impact ground-based technologies on Earth, affecting many systems including railway signalling. This study uses a recently developed model to analyse the impact of geomagnetically induced currents on railway signalling systems in the United Kingdom during the March 1989 and October 2003 geomagnetic storms. The March 1989 storm is also scaled to estimate a 1-in-100 year and a 1-in-200 year extreme storm. Both the Glasgow to Edinburgh line, and the Preston to Lancaster section of the West Coast Main Line are modelled. No “right side” failures (when unoccupied sections appear occupied) are suggested to have occurred during either storm, and the total number of potential “wrong side” failures (when occupied sections appear clear) is low. However, the modelling indicates “right side” and “wrong side” failures are possible on both routes during the 1-in-100 year and 1-in-200 year extreme storms, with the Glasgow to Edinburgh line showing more total misoperations than the Preston to Lancaster section of the West Coast Main Line. A 1-in-100 year or 1-in-200 year extreme storm would result in misoperations over an extended period of time, with most occurring over a duration of 2–3 h either side of the peak of the storm.

A simplified geospace model for satellite design

This study introduced a simplified, integrated computational model to estimate the drag coefficient and surface charging within the plasma wake of Low Earth Orbit (LEO) spacecraft influenced by various solar activities. The model constituted four core modules: a solver for the solar wind-magnetosphere interaction, a magnetosphere-ionosphere coupling for electric field mapping, an ionization model for the F-layer of the ionosphere, and an estimation model for excess satellite drag and plasma wake size. The initial module adopted a simplified 1D ideal Magnetohydrodynamic (MHD) model while incorporating magnetosphere-ionosphere interactions to derive electric field data near Earth’s boundary. A simplified ionospheric model for the F-layer was implemented to compute the O+ and electron densities. Subsequently, the spacecraft drag coefficient and the plasma wake size were determined for varying solar wind speed inputs corresponding to quiet, intense, and extreme space weather conditions. In the case of extreme conditions with a solar wind speed of 1000 km/s, the results indicated that the excess satellite drag coefficient and plasma wake size increased to around ten percent.

Robust and Autonomous Space Weather Charge Mitigation Coatings

National Space Weather Strategy and Action plan calls for the need to enhanceProtection of National Security, Homeland Security, and Commercial Assets and Operations against Effects of Space Weather. Extreme space weather event like solar flares, cosmic rays, and radiation belts cause ionizing radiation that can damage electronics, solar arrays, and optical systems on satellites reducing their functionality and lifetimes, by inducing an ionic charge on the spacecraft’s surface, when a spacecraft fly in and out of the ionosphere. This negative charge buildup can lead to ion sputtering/arcing, and producing irreparable damage in spacecraft components. Therefore, the local application of materials systems that can passively mitigate the negative charge build up by emitting the electron back into space, while improving resistance to erosion during ion sputtering is of interest. Accordingly, Faraday Technology is developing a low-cost, efficient and scalable manufacturing process for the local deposition of lightweight passive highly emissive and erosion resistant coating onto spacecraft viable substrates that can mitigate charging and erosion effects from ionizing radiation. The composite coating showed a ~1500% increase in maximum (Emax) total electron yield over bare aluminum, extending by 4 times the range of electron yields between crossover energies >1, and demonstrated the potential for erosion resilience in modeled International Space Station plasma erosion conditions. The composite coating could be applied to various spacecraft platforms include spacecraft skin, solar arrays, circuit boards, and emitters such that their lifetime, effectiveness and durability within LEO/GEO environments events can be enhanced. Acknowledgements:The financial support of NASA SBIR/STTR program through contract No.80NSSC22PB020 is acknowledged.

The Extreme Space Weather Event of 1872 February: Sunspots, Magnetic Disturbance, and Auroral Displays

We review observations of solar activity, geomagnetic variation, and auroral visibility for the extreme geomagnetic storm on 1872 February 4. The extreme storm (referred to here as the Chapman–Silverman storm) apparently originated from a complex active region of moderate area (≈ 500 μsh) that was favorably situated near disk center (S19° E05°). There is circumstantial evidence for an eruption from this region at 9–10 UT on 1872 February 3, based on the location, complexity, and evolution of the region, and on reports of prominence activations, which yields a plausible transit time of ≈29 hr to Earth. Magnetograms show that the storm began with a sudden commencement at ≈14:27 UT and allow a minimum Dst estimate of ≤ −834 nT. Overhead aurorae were credibly reported at Jacobabad (British India) and Shanghai (China), both at 19.°9 in magnetic latitude (MLAT) and 24.°2 in invariant latitude (ILAT). Auroral visibility was reported from 13 locations with MLAT below ∣20∣° for the 1872 storm (ranging from ∣10.°0∣–∣19.°9∣ MLAT) versus one each for the 1859 storm (∣17.°3∣ MLAT) and the 1921 storm (∣16.°2∣ MLAT). The auroral extension and conservative storm intensity indicate a magnetic storm of comparable strength to the extreme storms of 1859 September (25.°1 ± 0.°5 ILAT and −949 ± 31 nT) and 1921 May (27.°1 ILAT and −907 ± 132 nT), which places the 1872 storm among the three largest magnetic storms yet observed.

Next-decade needs for 3-D ionosphere imaging

Accurately imaging the 3-D ionospheric variation and its temporal evolution has always been a challenging task for the space weather community. Recent decades have witnessed tremendous steps forward in implementing ionospheric imaging, with the rapid growth of ionospheric data availability from multiple ground-based and space-borne sources. 3-D ionospheric imaging can yield altitude-resolved electron density and total electron content (TEC) distribution in the target region. It offers an essential tool for better specification and understanding of ionospheric dynamical variations, as well as for space weather applications to support government and industry preparedness and mitigation of extreme space weather impact. To better meet the above goals within the next decade, this perspective paper recommends continuous investment across agencies and joint studies through the community, in support of advancing 3-D ionospheric imaging approach with finer resolution and precision, better error covariance specification and uncertainty quantification, improved ionospheric driver estimation, support space weather nowcast and forecast, and sustained effort to increase global data coverage.

Space Weather in the Saturn–Titan System

New evidence based on Cassini magnetic field and plasma data has revealed that the discovery of Titan outside Saturn’s magnetosphere during the T96 flyby on 2013 December 1 was the result of the impact of two consecutive interplanetary coronal mass ejections (ICMEs) that left the Sun in 2013 early November and interacted with the moon and the planet. We study the dynamic evolution of Saturn's magnetopause and bow shock, which evidences a magnetospheric compression from late November 28 to December 4 (at least), under prevailing solar wind dynamic pressures of 0.16–0.3 nPa. During this interval, transient disturbances associated with the two ICMEs are observed, allowing for the identification of their magnetic structures. By analyzing the magnetic field direction, and the pressure balance in Titan’s induced magnetosphere, we show that Cassini finds Saturn’s moon embedded in the second ICME after being swept by its interplanetary shock and amid a shower of solar energetic particles that may have caused dramatic changes in the moon’s lower ionosphere. Analyzing a list of Saturn's bow shock crossings during 2004–2016, we find that the magnetospheric compression needed for Titan to be in the supersonic solar wind can be generally associated with the presence of an ICME or a corotating interaction region. This leads to the conclusion that Titan would rarely face the pristine solar wind, but would rather interact with transient solar structures under extreme space weather conditions.

Upstream Proton Cyclotron Waves at Mars During the Passage of ICMEs

AbstractThe presence of proton cyclotron waves (PCWs) upstream from Mars indicates picked up protons originating from the Martian extended hydrogen (H) exosphere by the solar wind and loss of H to interplanetary space. The occurrences and properties of PCWs associated with normal solar wind conditions have been extensively investigated since their initial detection about 32 years ago, but little attention has been paid to PCW activity under extreme space weather conditions. Here we characterize PCWs during the passage of interplanetary coronal mass ejections (ICMEs) through the Martian environment using the measurements by the Mars Atmosphere and Volatile EvolutioN spacecraft from December 2014 to February 2019. It is found that PCWs occur more frequently during perihelion periods (Ls = 180°–360°) than during aphelion periods (Ls = 0°–180°) for disturbed times of ICME passage. In the perihelion season, the PCW occurrence rate is increased on average by a factor of about 2 during the ICME phase relative to the pre‐ICME and post‐ICME phases. Moreover, PCWs reveal more pronounced wave characteristics with larger amplitudes, higher ellipticity, and smaller propagation angle with respect to the ambient magnetic field direction during the ICME phase.

Impacts of Extreme Space Weather Events on September 6th, 2017 on Ionosphere and Primary Cosmic Rays

The strongest X-class solar flare (SF) event in 24th solar cycle, X9.3, occurred on 6 September 2017, accompanied by earthward-directed coronal mass ejections (CMEs). Such space weather episodes are known to cause various threats to human activities ranging from radio communication and navigation disturbances including wave blackout to producing geomagnetic storms of different intensities. In this study, SFs’ ionospheric impacts and effects of accompanied heliospheric disturbances on primary cosmic rays (CR) are investigated. This work offers the first detailed investigation of characteristics of these extreme events since they were inspected both from the perspective of their electromagnetic nature, through very low frequency (VLF) radio waves, and their corpuscular nature of CR by multi-instrumental approach. Aside data recorded by Belgrade VLF and CR stations, data from GOES and SOHO space probes were used for modeling and analysis. Conducted numerical simulations revealed a significant change of ionospheric parameters (sharpness and effective reflection height) and few orders of magnitude increase of electron density. We compared our findings with those existing in the literature regarding the ionospheric response and corresponding parameters. In addition, Forbush decrease (FD) magnitude, corrected for magnetospheric effect, derived from measurements, and one predicted from power exponents used to parametrize the shape of energetic proton fluence spectra at L1 were compared and found to be in good agreement. Presented findings could be useful for investigation of atmospheric plasma properties, particles’ modeling, and prediction of extreme weather impacts on human activities.