Geomagnetic Conditions Research Articles

Inter-Correlation Analysis of Magnetic Activity Indices during Varying Geomagnetic Conditions and Phases

The linear interrelationship between the Dst, AE, ap, and the IMF-Bz were presently investigated in pairs and multiples during magnetic quiet (), disturbed (), and combined activities, as well as for different storm phases using data obtained from 1996-2006. The results from the study indicate the highest correlation percentage (%corr) between pairs of indices was for the AE/ap (73%) occurring during the storm onset phase. The %corr was 21-57%, (50-73%), (23-52%), (5-40%), Bz/ap (24-60%), and (7-37%) across various levels of activities. The results for the multiple correlation relationships of the and showed that the magnitudes of the coefficients of best fit are smallest during quiet magnetic activity in comparison to other activities, suggesting that ap and Bz are well explained by the independent variables carrying the coefficient during the quiet condition and can be better inferred during the same period of magnetic activity. The present results suggest that the ap index is well correlated with the Dst as an intermediate index regarding the ap index and can describe the general state of planetary geomagnetic activity. It contains at least two or more major sources, the auroral electrojet () and the ring current; also, by means of a multiple correlation program, a linear fit can be performed for ap in terms of AE and Dst. Furthermore, only the pair has a %corr of above 50% for any activity class. For the entire data span, the AE/ap pair performed best at 67%, followed by the pair with 59%, and the least was the pair with 37%. Additionally, the results r.evealed that the AE/ap relationship presents the highest values of 73.25%, 62.16% and 68.56% during the storm onset, main, and recovery phases, respectively.

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.

Improved Ionospheric Total Electron Content Maps over China Using Spatial Gridding Approach

Improved Ionospheric Total Electron Content Maps over China Using Spatial Gridding Approach

The high-energy tail of energetic electron precipitation: solar wind drivers and geomagnetic responses

Compositional NOx changes caused by energetic electron precipitation (EEP) at a specific altitude and those co-dependent on vertical transport are referred to as the EEP direct and indirect effect, respectively. The direct effect of EEP at lower mesospheric and upper stratospheric altitudes is linked to the high-energy tail of EEP (≳ 300 keV). The relative importance of this direct effect on NOx, ozone, and atmospheric dynamics remains unresolved due to inadequate particle measurements and scarcity of polar mesospheric NOx observations. An accurate parameterization of the high-energy tail of EEP is, therefore, crucial. This study utilizes EEP flux data from MEPED aboard the POES/Metop satellites from 2004–2014. Data from both hemispheres (55–70° N/S) are combined in daily flux estimates. 164 peaks above the 90th percentile of the ≳ 30 keV flux are identified. These peaks are categorized into absolute E1 and E3 events representing weak and strong ≳ 300 keV responses, respectively. A subset of absolute E1 and E3 events with similar ≳ 30 keV responses is termed overlapping events. Additionally, relative E1 and E3 events are determined by the relative strength of the ≳ 300 keV response, scaled by the initial ≳ 30 keV flux. A comparison between E1 and E3 events aims to identify solar wind and geomagnetic conditions leading to high-energy EEP responses and to gain insight into the conditions that generate a high-energy tail, independent of the initial ≳ 30 keV flux level. Superposed epoch analysis of mesospheric NO density from SOFIE confirms an observable direct impact on lower mesospheric chemistry associated with the absolute E3 events. A probability assessment based on absolute events identifies specific thresholds in the solar wind-magnetosphere coupling function (epsilon) and the geomagnetic indices Kp*10 and Dst, capable of determining the occurrence or exclusion of absolute E1 and E3 events. Elevated solar wind speeds persisting in the recovery phase of a deep Dst trough appear characteristic of overlapping and relative E3 events. This study provides insight into which parameters are important for accurately modeling the high-energy tail of EEP.

Detection of the pre-seismic anomalies in stratospheric temperature and radio emission using space-based observations

The present paper implements new approaches introduced in regard to pre-earthquake geo-chemical activity that results in lithosphere-atmosphere–ionosphere coupling (LAIC). Specifically, stratospheric temperature anomaly as a result of precursory atmospheric gravity wave (AGW) activity in the stratosphere is studied. A new technique is developed based on the parameters a) daily average temperature (Tmean), b) daily maximum temperature (Tmax), c) Tmean averaged over altitude, d) Tmax averaged over altitude. The new approach is applied to six earthquakes of Iran as well as Tohoku earthquake. Detected Anomalies are analyzed and discussed. Possible new variations such as stratospheric cooling as a result of active geomagnetic conditions are determined. Geographical maps and spatial distribution of temperature anomalies are presented to comprehend the possible source of variation. Moreover, space-based ULF emission observed by an in situ electric field detector (EFD) on board of China Seismic-Electromagnetic Satellite (CSES) is presented as associated with 3 earthquakes that occurred in 2019. Detailed analysis of satellite overpass proximity to the earthquake epicenter, earthquake magnitude, and dates are examined and ULF anomalies associated with 3 magnetic field components are discussed. Finally, a systematic approach to be implemented using the new techniques in real time is proposed.

Detection of long-range correlation causing multifractality in H time series of geomagnetic field over the Northern Hemisphere during quiet geomagnetic conditions

The generation of geomagnetic time series frequently involves intricate spatio-temporal dynamics, wherein nonlinearity and scaling emerge as pivotal mechanisms. The present work investigates the fractal properties of geomagnetic field, and its sources during quiet geomagnetic conditions, by analyzing the horizontal component data of 1 min resolution (H time series) from different latitude regions. Analysis using Auto Correlation Function (ACF), Power spectrum analysis (PSA), Rescaled range analysis (R/S) and Detrended Fluctuation Analysis (DFA) gave indications of the presence of long-range correlations, fractal properties and scaling behaviour of quiet period H time series data. The strong q dependence of generalized Hurst exponent h(q) and scaling exponent Ʈ(q), obtained from the Multifractal Detrended Fluctuation Analysis (MFDFA) method, confirmed the multifractal behaviour of quiet period H time series. The multifractal source analysis of the quiet period H time series with its shuffled and surrogate time series data revealed that, the multifractal characteristics are caused almost entirely by the long-range correlations between small and large fluctuations. The analysis of the latitudinal variations in the multifractal characteristics is also performed as a part of the work, by considering H time series belonging to various latitudes under almost same longitude. The observed decrease in the generalized Hurst exponent values with increase in latitude indicates the change in the multifractal characteristics of the time series with latitude. Also the work revealed that, the H time series from high latitude region shows anti-persistent behaviour, even when the H time series from observatories located at the low and mid latitude regions exhibiting persistent behaviour. The change in the persistence, anti-persistence behaviour can be related to the strength of Earth’s magnetic field.

On the variability of the atomic oxygen density in the upper atmosphere under different solar activity and geomagnetic conditions and its impacts on satellite drag

Atomic oxygen (AO) is the most abundant species in the terrestrial thermosphere at altitudes of 180 to 700 km and plays a crucial role in numerous upper atmospheric processes. The drag encountered by a spacecraft is directly influenced by the background atmospheric density, making AO a notable contributor in this regard. The objective of this study is to analyze the variability of the density of AO in the near-Earth space environment under different solar activity conditions, as well as during severe space weather events. The analysis is primarily focused on the altitude range of 300 to 500 km in the Earth’s thermosphere across the globe, which is a crucial operating region for a large number of Low Earth Orbiting satellites. AO exerts significant drag on the Low Earth Orbit (LEO) satellites and reacts with the materials of the satellite body and in situ probes mounted therein, causing considerable degradation to both. Additionally, AO interferes with measurements made by optical instruments through phenomena such as ‘shuttle glow’. Analysis based on NRLMSIS 2.0 model revealed that the concentration of AO displays significant seasonal variations primarily due to the asymmetry in solar insolation. The highest concentration of AO was observed during the spring equinoctial month of the solar maximum year, while the lowest concentration was noted during the winter solstitial month of the solar minimum year. The enhancement seen in AO density contours show an asymmetry in the zonal direction at approximately 50∘ N in June and 50∘ S in December. Similarly, during geomagnetically disturbed days, the AO density shows enhancements along various longitudes, as indicated by the elongated contours. During geomagnetic storms, the heightened Joule heating in the polar region modifies the meridional circulation, which in turn affects the global distribution of AO density. Similarly, an analysis of thermospheric neutral winds obtained from the HWM93 model reveals that the zonal winds exhibit a strong westward acceleration over the region where AO density is enhanced. Furthermore, such an increase in AO density during geomagnetic storms has been found to cause orbital degradation ranging from a few tens of meters to a few hundred meters, depending on the strength and geo-effectiveness of the storms. This study emphasizes the critical contribution of AO density to satellite drag force, necessitating in situ measurements for an accurate estimation of the altitude decay of the spacecraft.

Processing of VLF Amplitude Measurements: Deduction of a Quiet Time Seasonal Variation

AbstractThe amplitude of Very Low Frequency (VLF) transmissions propagating from transmitter to receiver between the Earth's surface and the ionospheric D‐region is a useful measurement to detect changes in the ionization within the D‐region ranging from 60 to 90 km. The VLF signal amplitude is disturbed by geomagnetic, solar, and atmospheric phenomena. To be able to identify perturbations in the VLF signal amplitude, we determine its averaged seasonal variation under quiet solar and geomagnetic conditions. Here it is challenging, that long time series of the VLF signal amplitude show significant jumps and outliers, which are caused artificially by technical adjustments/maintenance work. This paper presents a new approach for processing long VLF data time series over multiple years resulting in level 2 data. The new level 2 data enables the consideration of time series with artificial jumps since the jumps are leveled. Moreover, the outliers are removed by a robust and systematic 2‐step outlier filtering. The average seasonal and diurnal variation for different transmitter‐receiver combinations can be computed with the new level 2 data by applying a composite analysis. A subsequently applied polynomial fit obtains the quiet time lines for daytime and nighttime, representing the typical seasonal variation under undisturbed conditions of the VLF signal amplitude for each considered link. The developed quiet time lines may serve as a tool to determine perturbations of the VLF signal amplitude with solar and geomagnetic as well as atmospheric origin. Also, they allow comparison of the VLF signal amplitude variation for different transmitter‐receiver links.

Influence of Geomagnetic Storms on Power System Static Voltage Security

The adverse effects of geomagnetic storms on power systems have been confirmed by numerous examples and observations. However, there remains a dearth of research on the quantitative assessment of the safety risks of a system under extreme geomagnetic storm conditions. Accordingly, in this study, we developed a risk assessment model for magnetic storm disasters based on the static voltage security region theory from the global perspective of power grid security. First, we determined the boundary shape of the static security region of a system under magnetic storm conditions and analyzed its influence on the voltage stability of the system from a regional perspective. Subsequently, a static safe-distance index was proposed to characterize the influence of a magnetic storm disaster on the system voltage. Considering the uncertainty in the injected power during a magnetic storm, we calculated the static voltage instability probability of the system. Through probability index analysis, a probabilistic safety assessment of the system under magnetic storm conditions was performed, and its overall static voltage safety level was measured. Finally, a simulation analysis based on the UIUC 150 node showed the proposed method to be reasonable and effective.

Geomagnetic activity affects animal myocardial ischemia/reperfusion injury: an experimental-simulated study

Numerous studies have shown that geomagnetic activity (GMA) contributes to the development and escalation of cardiovascular disease (CVD), as well as increased morbidity and mortality. However, the underlying molecular mechanisms and approaches for understanding GMA remain unclear. This study aimed to investigate the impact of GMA on oxidative stress and inflammatory responses. Myocardial ischemia/reperfusion injury (MI/RI) rat models were created under various geomagnetic field conditions. The range of cardiac function, markers of myocardial injury, inflammatory factors, and the TLR4/NF-κB signaling pathway were measured after the 24-h period. The findings showed that weak GMA significantly improved cardiac function in the MI/RI rat model and reduced the size of myocardial infarction and creatine kinase (CK) and lactic dehydrogenase (LDH) levels. Additionally, weak GMA enhanced superoxide dismutase (SOD) activity and decreased malondialdehyde (MDA) content. Furthermore, weak GMA significantly reduced the levels of the myocardial inflammatory cytokines interleukin-1 (IL-1), interleukin-6 (IL-6), and tumor necrosis factor-α (TNF-α). Conversely, the effects observed under severe GMA conditions were opposite to those observed under weak GMA. Western blot and qPCR analysis demonstrated that weak GMA led to a significant downregulation of TLR4, TRAF6, NF-κB, TNF-α, and MCP-1 in the MI/RI rat models. In contrast to weak GMA, severe GMA increased TLR4, TRAF6, NF-κB, and TNF-α expression. This study suggested that weak GMA had a limiting effect on MI/RI rat models, whereas severe GMA exacerbated injury in MI/RI rats. These effects were associated with oxidative stress and inflammatory responses and might potentially involve the TLR4/NF-κB signaling pathway.

Performance analysis of NeQuick2 and IRI-Plas models during quiet geomagnetic and low solar activity conditions at Thanjavur equatorial location: Preliminary results

Performance analysis of NeQuick2 and IRI-Plas models during quiet geomagnetic and low solar activity conditions at Thanjavur equatorial location: Preliminary results

Thermosphere model assessment for geomagnetic storms from 2001 to 2023

We present an updated study for thermosphere model assessment under geomagnetic storm conditions, defined when the geomagnetic index ap = 80 or larger. Comparisons between five empirical models, NRLMSISE-00, JB2008, and three versions of DTM2020, and CHAMP, GRACE, GOCE, Swarm-A, and GRACE-FO neutral density data sets for 152 storms are presented. The storms are categorized according to ap, as single peak or multiple peaks. After applying a model debiasing procedure using the density data just before the onset of a storm, the models are on average only slightly biased, often only a few percent. This is an unexpected and reassuring result for these relatively simple models, which were fitted to different observations. The standard deviations of these averages are however up to 12% (1-sigma), which places the small biases into perspective. The smallest biases are achieved at the lowest altitude when comparing with GOCE data, and the highest for GRACE. The best results, i.e. smallest bias and standard deviation on average over all single-peak storms, over the entire 4-Phase storm period are obtained with DTM2020_Intermediate and DTM2020_Research models, while the oldest model, NRLMSISE-00, is the least precise. However, NRLMSISE-00 is the least biased when compared to multiple-peak storms. As could be expected, multiple-peak storms are reproduced with less precision than single-peak storms. The assessment reveals that model precision decreases with altitude, but that bias is independent of altitude, at least in the range covered by the data, 250–550 km.

25-26 Ağustos 2018 Jeomanyetik Fırtına Sırasında Afrika Bölgesi Üzerindeki Manyetik Eşlenik Çiftleri Üzerindeki TEC Değişikliklerinin İncelenmesi

In this study, the electron transport process resulting from electromagnetic drift between two magnetic conjugate pairs over the African region during the August 25-26 2018 geomagnetic storm was investigated. The effects of geomagnetic conditions presented with Dst index and IMF Bz values on Total Electron Content (TEC) values at conjugate stations were compared separately for stormy and quiet periods. During the storm period, the effect of TEC values at stations in the northern hemisphere (Haifa and Djibouti) on the TEC values at stations in the southern hemisphere (Ambalavao and Malindi) is greater than the effect of TEC values in the southern hemisphere on TEC values in the northern hemisphere. According to this result, it can be said that the south-directed electromagnetic convection was more than the north-directed convection in the examined dates. When the coefficients are examined, it can be said that the interaction is more in the magnetic conjugate pair that is closer to the equator during the storm period, and the interaction is more in the magnetic conjugate pair that is far from the equator during the silent period. Considering the coefficients calculated for Dst and IMF Bz, it is seen that the TEC values are very small compared to their coefficients. From this it can be concluded that the effect of Dst and IMF Bz is much smaller than the effect of TEC values at a station on TEC values at its magnetic conjugates.

Occurrence of ionospheric scintillations under different solar and geomagnetic conditions over low latitude station Varanasi

In the present study, occurrences of amplitude scintillations during the ascending phase of the 25th solar cycle from November 2020 to March 2023 are studied over the equatorial anomaly region Varanasi (latitude 25.31° N, longitude 82.97° E, magnetic dip Lat. 16.2° N). Multi-frequency Global navigation satellite system (GNSS) receiver is used to study the occurrence of amplitude scintillation index S4. Diurnal, monthly, and seasonal occurrence characteristics of the S4 index are presented. The scintillation occurrence is observed during nighttime and daytime but is more probable during nighttime. It is observed that maximum scintillation occurred during the equinox season for the solar moderate period whereas the highest occurrence is in summer during the low solar activity period. The highest scintillation occurrences during the summer solstice for a period of low solar activity condition is rare and could be attributed to the gravity waves (GWs) generation due to the weather phenomena in the lower atmosphere. GWs could act as a seeding perturbation in electron density, affecting the growth of ionospheric irregularities through Rayleigh-Taylor instability. The solar flux index (F10.7) is compared with the percentage occurrence of scintillation for the low and moderate solar activity periods to observe the effect of solar activity on scintillation occurrences. Overall, the scintillation occurrence increases with increasing solar activity. To study the effect of geomagnetic storms on scintillations, we have considered seven moderate and intense geomagnetic storms grouped in three categories that occurred during solar cycle 25. It is observed that the occurrence of scintillations is enhanced for the storms with the recovery phase starting at post-midnight. The probability of occurrence of scintillation during the night hours is decreased when the geomagnetic storm occurs during the daytime.

Extreme Geomagnetic Disturbances (GMDs) Observed in Eastern Arctic Canada: Occurrence Characteristics and Solar Cycle Dependence

AbstractExtreme (>20 nT/s) geomagnetic disturbances (GMDs, also denoted as MPEs—magnetic perturbation events)—impulsive nighttime disturbances with time scale ∼5–10 min, have sufficient amplitude to cause bursts of geomagnetically induced currents (GICs) that can damage technical infrastructure. In this study, we present occurrence statistics for extreme GMD events from five stations in the MACCS and AUTUMNX magnetometer arrays in Arctic Canada at magnetic latitudes ranging from 65° to 75°. We report all large (≥6 nT/s) and extreme GMDs from these stations from 2011 through 2022 to analyze variations of GMD activity over a full solar cycle and compare them to those found in three earlier studies. GMD activity between 2011 and 2022 did not closely follow the sunspot cycle, but instead was lowest during its rising phase and maximum (2011–2014) and highest during the early declining phase (2015–2017). Most of these GMDs, especially the most extreme, were associated with high‐speed solar wind streams (Vsw >600 km/s) and steady solar wind pressure. All extreme GMDs occurred within 80 min after substorm onsets, but few within 5 min. Multistation data often revealed a poleward progression of GMDs, consistent with a tailward retreat of the magnetotail reconnection region. These observations indicate that extreme GIC hazard conditions can occur for a variety of solar wind drivers and geomagnetic conditions, not only for fast‐coronal mass ejection driven storms.

Geomagnetic Anomaly in the Growth Response of Peat Moss Sphagnum riparium to Temperature.

Temperature plays an essential role in a plant's life. The current investigation reveals that photoreceptors, whose activity is affected by the geomagnetic field, are a critical element of its perception. This knowledge suggests that plants' responses to temperature could shift in different geomagnetic conditions. To test this hypothesis, we studied the change in the growth response of the peat moss Sphagnum riparium to temperature with a gradual increase in the geomagnetic Kp index. Growth data for this species were collected from Karelian mires by detailed monitoring over eight full growing seasons. The growth of 209,490 shoots was measured and 1439 growth rates were obtained for this period. The analysis showed a strong positive dependence of sphagnum growth on temperature (r = 0.58; n = 1439; P = 1.7 × 10-119), which is strongest in the Kp range from 0.87 to 1.61 (r = 0.65; n = 464; P = 4.5 × 10-58). This Kp interval is clearer after removing the seasonal contributions from the growth rate and temperature and is preserved when diurnal temperature is used. Our results are consistent with the hypothesis and show the unknown contribution of the geomagnetic field to the temperature responses of plants.

Topside Electron Density Modeling Using Neural Network and Empirical Model Predictions

AbstractWe model the electron density in the topside of the ionosphere with an improved machine learning (ML) model and compare it to existing empirical models, specifically the International Reference Ionosphere (IRI) and the Empirical‐Canadian High Arctic Ionospheric Model (E‐CHAIM). In prior work, an artificial neural network (NN) was developed and trained on two solar cycles worth of Defense Meteorological Satellite Program data (113 satellite‐years), along with global drivers and indices to predict topside electron density. In this paper, we highlight improvements made to this NN, and present a detailed comparison of the new model to E‐CHAIM and IRI as a function of location, geomagnetic condition, time of year, and solar local time. We discuss precision and accuracy metrics to better understand model strengths and weaknesses. The updated neural network shows improved mid‐latitude performance with absolute errors lower than the IRI by 2.5 × 109 to 2.5 × 1010 e−/m3, modestly improved performance in disturbed geomagnetic conditions with absolute errors reduced by about 2.5 × 109 e−/m3 at high Kp compared to the IRI, and high Kp percentage errors reduced by >50% when compared to E‐CHAIM.

Geomagnetic Storm Effects on the LEO Proton Flux During Solar Energetic Particle Events

AbstractDuring a few solar energetic particle (SEP) events, solar protons were trapped within the geomagnetic field and reached the outer edge of the inner radiation belt. We reproduced this phenomenon by modeling the proton flux distribution at the Low‐Earth Orbit (LEO) for different geomagnetic conditions during solar particle events. We developed a three‐dimensional relativistic test particle simulation code to compute the 70–180 MeV solar proton Lorentz trajectories in low L‐shell range from 1 to 3. The Tsyganenko model (T01) generated the background static magnetic field with the IGRF (v12) model. We have selected three Dst index values: −7, −150, and −210 nT, to define quiet time, strong, and severe geomagnetic storms and to generate the corresponding inner magnetic field configurations. Our results showed that the simulated solar proton flux was more enhanced in the high‐latitude regions and more expanded toward the lower latitude range as long as the geomagnetic storm was intensified. Satellite observations and geomagnetic cutoff rigidities confirmed the numerical results. Furthermore, the LEO proton flux distribution was deformed, so the structure of the proton flux inside the South Atlantic Anomaly (SAA) became longitudinally extended as the Dst index decreased. Moreover, we have assessed the corresponding radiation environment of the LEO mission. We realized that, for a higher inclined LEO mission during an intense geomagnetic storm (Dst = −210 nT), the probability of the occurrence of the Single Event Upset (SEU) rates increased by 19% and the estimated accumulated absorbed radiation doses increased by 17% in comparison with quiet conditions.

A New Approach to the Ionosphere at Middle and Low Latitudes under the Geomagnetic Quiet Time of December 2019 by ICON and GOLD Observations

It has been found that the total electron content (TEC) and the ionospheric electric fields indicated by the geomagnetic data showed inconsistent changes with each other at the mid- and low latitudes in both the American and the Asian–Australian sectors during geomagnetic quiet time (GQT) from 30 November to 8 December 2019 (Kpmax = 1.7). Meanwhile, the effects of thermospheric compositions are still indistinct. In this work, we analyze the mid/low-latitude ionospheric variations during this period, utilizing multi-instrument observations. The vertical drift velocities from the Ionospheric Connection Explorer (ICON) show significant variations and are in line with the changes in TEC at low latitudes in both of the two sectors. The zonal electric fields are supposed to play the main role in the TEC changes. This is also confirmed by the ionospheric F2 layer parameters data from the ionosonde stations at Sanya in the Asian–Australian sectors. The correlation between the variations in the geomagnetic H component (ΔH) and ionospheric F-layer electric fields can be affected by solar activity levels. The geomagnetic data ΔH sometimes may not indicate the magnitude of the electric fields in the F-region ionosphere under geomagnetic quiet conditions. The column density ratio of atomic oxygen (O) to molecular nitrogen (N2) (∑O/N2) from the Global Scale Observations of the Limb and Disk (GOLD) showed a strong enhancement at mid-latitudes in the American sector on 30 November. It is speculated that the neutral compositions should make a minor contribution to the changes in TEC during this event, compared with the electric fields.

Large regional variability in geomagnetic storm effects in the auroral zone

A digital society is fragile and vulnerable to space-originated electromagnetic disturbances. Global geomagnetic conditions have been actively monitored since the invention of the magnetometer in 1833. However, regional changes in the magnetic environment have been widely left unstudied because of the sparsity of the observing networks. The Scandinavian Magnetometer Array (SMA) was the densest magnetometer network in history, and it was in operation in Fennoscandia during the International Magnetospheric Study (IMS) in 1976–1979. The data has been left mainly unstudied because it was recorded on 35 mm films, which are difficult to use for scientific studies. We used the DigiMAG digitization method to digitize magnetic data from all 32 SMA stations for a geomagnetic storm on 10–12 December 1977. Using these digitized values and modern magnetic data, we found large regional differences about up to 2 nT/km during strong geomagnetic storms (Dst 100–200 nT) and 7 nT/km for major scale Halloween geomagnetic storm, which correspond to 400 and 1400 nT difference for a typical 200 km station separation, respectively. The average size of substorms is 400 nT in the auroral zone. We conclude that the sparse magnetometer network can cause an underestimation of the regional magnetic disturbances and their effects. Misestimation of regional disturbances during extreme storms like the Carrington event may lead to insufficient planning of mitigation procedures and strategies.