Storm Time Research Articles

Storm-time variability of ionospheric irregularities over South America

The generation and development of ionospheric irregularities is an important topic of study in space weather, mainly because of their adverse effects on navigation and positioning systems, as well as in trans-ionospheric communications. To improve our prediction capabilities, it is necessary to better understand their variabilities during different geomagnetic conditions. The purpose of this research is to analyse the occurrence characteristics of ionospheric irregularities over South America during geomagnetic storms. Using data from six ionosondes and GPS stations in Brazil and Perú, observations from the JULIA radar and Swarm in situ electron density measurements, we examined the presence of irregularities during three intense storms (October 12, 2016, October 7, 2015 and August 25, 2018). Our data show that during the geomagnetic storms that occurred in October 2016 and October 2015, in the Brazilian region, the generation of ionospheric irregularities was usually inhibited during the storm recovery phase. During the main phase, spread-F was generated over the stations located close to the northern crest of the EIA, and it was inhibited over Cachoeira Paulista, a station near the southern crest. During the August 2018 storm, local winter, the geomagnetic activity may have helped generate the irregularities in all the stations analysed regardless of the phase of the storm. We suggest that the generation (inhibition) of irregularities is related to the effect of eastward (westward) storm time electric fields—disturbance dynamo electric fields and prompt penetration electric fields—that created favourable (unfavourable) conditions for the generation of irregularities by uplifting (lowering) the F region.

Statistical analysis of the occurrence rate of geomagnetic storms during solar cycles 20–24

This study examines the occurrences rate of geomagnetic storms during the solar cycles (SCs) 20–24. It also investigates the solar sources at SCs 23 and 24. The Disturbed storm time (Dst) and Sunspot Number (SSN) data were used in the study. The study establishes that the magnitude of the rate of occurrences of geomagnetic storms is higher (lower) at the descending phases (minimum phases) of solar cycle. It as well reveals that severe and extreme geomagnetic storms (Dst < -250 nT) seldom occur at low solar activity but at very high solar activity and are mostly associated with coronal mass ejections (CMEs) when occurred. Storms caused by CME + CH-HSSW are more prominent during the descending phase than any other phase of the solar cycle. Solar minimum features more CH-HSSW- associated storms than any other phase. It was also revealed that all high intensity geomagnetic storms (strong, severe and extreme) are mostly associated with CMEs. However, CH-HSSW can occasionally generate strong storms during solar minimum. The results have proven that CMEs are the leading cause of geomagnetic storms at the ascending, maximum and the descending phases of the cycles 23 and 24 followed by CME + CH-HSSW. The results from this study indicate that the rate of occurrence of geomagnetic storms could be predicted in SC phases.

An Imaging Evidence of the East Wall Structuring of Eastward Drifting Depletions Observed Near the EIA Crest in India

AbstractStructuring on the west (east) wall of eastward (westward) drifting airglow depletion under quiet (storm) time is common. Here, we report for the first time the rare occurrence of the east wall structuring of an eastward drifting depletion near the crest of equatorial ionization anomaly (EIA) in India on 16 April 2012 under quiet geomagnetic conditions. We observed a linear depletion having a westward tilt of ∼25° and eastward drift speed of ∼129 m/s in the beginning. First prominent structuring occurred on its west wall that later swiftly surged poleward within next 6–12 min and bifurcated, that is, behaved like a secondary depletion growing on the primary one. Second west wall structuring then occurred but had considerably subdued growth. Meanwhile, main depletion bent slightly eastward above its branching node, and two structuring appeared on the east wall in succession. Secondary depletion then slightly contracted equatorward, and structuring emerged from its east wall, too, that later stretched eastward, got linked with main depletion and formed grid mesh shaped feature. Second structuring on the west wall started fading; while, those on the east wall swiftly evolved, surged poleward and gained prominence. Also, their westward tilt decreased. During the occurrence of these events, gravity waves (GWs) and the retreat of EIA were active overhead. Current study serves as first imaging evidence of Zalesak et al. (1982, https://doi.org/10.1029/JA087iA01p00151) simulations that the east wall of a westward tilted depletion can become unstable and host secondary instabilities. Possibly these structuring were excited by GWs via Rayleigh‐Taylor instability.

Intergroup Cascade Broad Learning System With Optimized Parameters for Chaotic Time Series Prediction

The prediction of chaotic time series can well describe the physical properties and influencing factors of a sequence of numerical data points in successive order and has played an increasingly crucial role in various scientific and engineering communities. These time series data require the prediction model to have strong dynamic feature representation ability, which often leads to excessive calculation burden. As an emerging and effective learning method, a broad learning system (BLS) can be trained quickly by incremental learning, and the system can be reconstructed without requiring a lengthy retraining process, which has been shown to facilitate superior time-saving performance. However, the historical information of time series data is often ignored, resulting in the lack of dynamic feature representation ability of the original BLS algorithm. In this article, a novel intergroup cascade BLS (ICBLS) method and its variant with optimized parameters, termed MOICBLS, are proposed, which can combine the previous knowledge with current information to determine the output results by constructing a novel intergroup cascade structure for the enhancement nodes. The new algorithms try to retain the time-saving advantage of BLS and greatly enhance the extraction ability of dynamic features of chaotic time series data. In addition, it cannot be ignored that the network structure parameters have an unquestionable impact on the performance of a BLS. In response, two conflicting goals of prediction accuracy and diversity are formulated as multiobjective optimization functions in the training phase to generate the optimized network structure parameters needed by multiple candidate models. The experimental results on two benchmark chaotic time series dataset, the Lorenz system and Rossler system, and a geomagnetic disturbance storm time chaotic time series dataset demonstrate that our proposed algorithms are effective for prediction of chaotic time series, and the prediction accuracy is better than some existing approaches.

Effects of 15th January 2010 Annular Solar Eclipse on Traveling Ionospheric Disturbances and Equatorial Plasma Bubbles over Low Latitude Regions of East Africa

The influence of the 15th January 2010 annular solar eclipse on traveling ionospheric disturbances (TIDs) and equatorial plasma bubbles (EPBs) is studied using data from six global navigation and satellite system (GNSS) receivers spread across the path of annularity over the low latitude region of East Africa. The GNSS receivers are stationed at Nairobi (RCMN), Malindi (MAL2), and Eldoret (MOIU) in Kenya; Mbarara (MBAR) in Uganda; Kigali (NURK) in Rwanda; and Mtwara (MTWA) in Tanzania. The study period ranges from 12th to 18th January 2010, three days before and after the 15th January 2010 annular solar eclipse. The year 2010 marked the beginning phase of solar cycle 24, evidently observed in low total electron content (TEC) values and the disturbed storm time index (Dst). The eclipse started at 7 : 06 LT and ended at 10 : 14 LT, with MOIU and RCMN experiencing eclipse magnitudes of 0.946 and 0.93, respectively. The maximum obscuration occurred between 8 : 21 LT and 8 : 34 LT across most of the stations. A detrending on vertical TEC (VTEC) derived from GNSS receivers across or close to the path of totality revealed a reduction of ∼2-3 TECU during the maximum phase of the eclipse. The level of reduction was highly close to the totality path and decreased smoothly away from the totality path. Using a background polynomial fitting technique on diurnal TEC, we analyzed TIDs along NURK-MBAR-MOIU and MOIU-RCMN-MAL2 GPS arrays. The results revealed a wavelike perturbation with a virtual horizontal velocity of 830m/s and ∼1 TECU amplitude propagating eastward along the MOIU-RCMN-MAL2 GPS array. The study reports a moderate scintillation activity of 0.5 ≤ ROTI ≤ 0.9 values, demonstrating the presence of few EPBs over the region. The results show a latitudinal variation in GPS-TEC scintillation activities and suggest a possible influence of the eclipse on the observed increase in average scintillation levels across East Africa.

H1N1 influenza virus dose dependent induction of dysregulated innate immune responses and STAT1/3 activation are associated with pulmonary immunopathological damage

ABSTRACT Influenza A virus (IAV) infection poses a substantial challenge and causes high morbidity and mortality. Exacerbated pulmonary inflammatory responses are the major causes of extensive diffuse alveolar immunopathological damage. However, the relationship between the extent of cytokine storm, neutrophils/macrophages infiltration, and different IAV infection dose and time still needs to be further elucidated, and it is still unclear whether the signal transduction and transcriptional activator 1/3 (STAT1/3) signalling pathway plays a beneficial or detrimental role. Here, we established a mouse model of high- and low-dose pH1N1 infection. We found that pH1N1 infection induced robust and early pathological damage and cytokine storm in an infection dose- and time-dependent manner. High-dose pH1N1 infection induced massive and sustained recruitment of neutrophils as well as a higher ratio of M1:M2, which may contribute to severe lung immunopathological damage. pH1N1 infection activated dose- and time-dependent STAT1 and STAT3. Inhibition of STAT1 and/or STAT3 aggravated low-dose pH1N1 infection, induced lung damage, and decreased survival rate. Appropriate activation of STAT1/3 provided survival benefits and pathological improvement during low-dose pH1N1 infection. These results demonstrate that high-dose pH1N1 infection induces robust and sustained neutrophil infiltration, imbalanced macrophage polarization, excessive and earlier cytokine storm, and STAT1/3 activation, which are associated with pulmonary dysregulated proinflammatory responses and progress of acute lung injury. The severe innate immune responses may be the threshold at which protective functions give way to immunopathology, and assessing the magnitude of host innate immune responses is necessary in adjunctive immunomodulatory therapy for alleviating influenza-induced pneumonia.

ML Prediction of Global Ionospheric TEC Maps

AbstractThis paper applies the convolutional long short‐term memory (convLSTM)‐based machine learning models to forecast global ionospheric total electron content (TEC) maps with up to 24 hr of lead time at a 1‐hr interval. Four convLSTM‐based models were investigated, and the one that implements the L1 loss function and the residual prediction strategy demonstrates the best performance. The convLSTM models are trained and evaluated using Center for Orbit Determination in Europe (CODE) global TEC maps over a period of nearly seven years from 19 October 2014 to 21 July 2021. Results show that the best convLSTM model outperforms the 1‐day predicted global TEC products released by CODE analysis center (c1pg) and persistence models under various levels of solar and geomagnetic activities, except for a lead time beyond 8 hr during the storm time where the c1pg has slightly better performance. The convLSTM forecasting performance degrades as the lead time increases.

Assessing the Safety of Settlements from Flood Risk

The fact that Egypt falls within the arid and semi-arid areas, makes it always vulnerable to sudden storms, which have increased significantly during the past ten years. Climate change is one of the factors that cause the increasing of the sudden storms frequency, intensity and expansion to cover new areas. During three days, from November 11 to 13, 2021, a severe storm hit the city of Aswan and its suburbs, leaving behind extensive property damage and loss of life. Where heavy rains, fell in a short time, on the Eastern Desert Mountains led to torrential rains (flash flood) that flowed to the plains through the paths of the valleys, causing severe damage to several villages, which are located in the hydrologically active valleys (Al-Heita, Al-Kimab, Umm Buirat and Abu Al-Rish Qebli). In this paper, the November 2021 storm will be analyzed using Global Precipitation Measurement (GPM) data, with temporal and special resolution of 30 minutes and 0.1^o respectively. The data will give a distribution of the storm for each 1 hour during the storm for three days. The amount of water and its velocity will also be simulated using the (HEC-HMS) hydrological model. In addition, the (HEC-RAC) model is used in order to simulate the distribution and expansion of the flood during the storm time step. The results provide an actual simulation of what happened during the 2021 storm. In addition, this model is applied again with the highest values to produce the worst scenario. The final part of this paper highlights the value of this model as a supportive tool for urban planning to achieve sustainability. So, both results of the simulation and the worst scenario were compared to the development plan of the study area. Then, the suitable planning recommendations were accordingly suggested for the areas at risk to ensure sustainable future development.

Inter‐Calibration Between the Electron Flux Measurements of FengYun‐3B and Van Allen Probe‐A Based on Electron Phase Space Density Conjunctions

AbstractCross‐satellite calibration of energetic particle fluxes is essential to understanding Earth's radiation belt dynamics and modeling the space radiation environment. Using the method of comparing phase space density (PSD) conjunctions in the same set of phase space coordinates, we perform a cross‐satellite calibration of energetic electron fluxes measured by the Low Earth Orbit Chinese FengYun‐3B satellite (FY‐3B) and the near‐equatorial Highly Eccentric Orbit Van Allen Probe‐A (VAP‐A), respectively. VAP‐A provides pitch angle resolved electron (directional) differential fluxes while FY‐3B provides omnidirectional electron differential fluxes. Before calculating the PSDs from FY‐3B high energy electron detector (HEED), a method is introduced to estimate the local pitch angle of FY‐3B based on the installation direction information of HEED and the T89c magnetic field model. We calculate the calibration factors by using the PSD conjunctions inferred from the two satellites for three fixed sets of (μ, K, L*) during the geomagnetic storm times. The calibration factors range from 0.76 to 0.86 varying with fixed sets of (μ, K, L*), which indicates that the electron differential fluxes from FY‐3B are higher than that from VAP‐A. During geomagnetic quiet times, we perform calibration by using independent Gaussian fitting analysis of the number of points with the unaveraged PSDs of FY‐3B and VAP‐A for three fixed sets of (μ, K, L*), with the corresponding calibration factors of 0.78, 0.72, and 0.46. The calibrated electron differential fluxes of FY‐3B measured at the high magnetic latitudes, can be used in the future modeling of the radiation belt electron dynamics.

Importance of lower atmospheric forcing and magnetosphere-ionosphere coupling in simulating neutral density during the February 2016 geomagnetic storm

During geomagnetic storms a large amount of energy is transferred into the ionosphere-thermosphere (IT) system, leading to local and global changes in e.g., the dynamics, composition, and neutral density. The more steady energy from the lower atmosphere into the IT system is in general much smaller than the energy input from the magnetosphere, especially during geomagnetic storms, and therefore details of the lower atmosphere forcing are often neglected in storm time simulations. In this study we compare the neutral density observed by Swarm-C during the moderate geomagnetic storm of 31 January to 3 February 2016 with the Thermosphere-Ionosphere-Electrodynamics-GCM (TIEGCM) finding that the model can capture the observed large scale neutral density variations better in the southern than northern hemisphere. The importance of more realistic lower atmospheric (LB) variations as specified by the Whole Atmosphere Community Climate Model eXtended (WACCM-X) with specified dynamics (SD) is demonstrated by improving especially the northern hemisphere neutral density by up to 15% compared to using climatological LB forcing. Further analysis highlights the importance of the background atmospheric condition in facilitating hemispheric different neutral density changes in response to the LB perturbations. In comparison, employing observationally based field-aligned current (FAC) versus using an empirical model to describe magnetosphere-ionosphere (MI) coupling leads to an 7–20% improved northern hemisphere neutral density. The results highlight the importance of the lower atmospheric variations and high latitude forcing in simulating the absolute large scale neutral density especially the hemispheric differences. However, focusing on the storm time variation with respect to the quiescent time, the lower atmospheric influence is reduced to 1–1.5% improvement with respect to the total observed neutral density. The results provide some guidance on the importance of more realistic upper boundary forcing and lower atmospheric variations when modeling large scale, absolute and relative neutral density variations.

Ionospheric-Thermospheric responses to the May and September 2017 geomagnetic storms over Asian regions

This paper presents the longitudinal dependence of ionospheric responses from Global Navigation Satellite System (GNSS) derived Total Electron Content (TEC) during two intense geomagnetic storms of May and September 2017. The GNSS-TEC is retrieved from four stations installed at the verge of low to mid-latitude Asian regions of Pakistan and China. Two ionospheric enhancements were observed during the storm of May 2017. The first one at local noon–afternoon during the storm main phase on 28 May was due to the southward turning of Interplanetary Magnetic Field (IMF-Bz) and eastward Prompt Penetration Electric Field (PPEF), with the maximum TEC enhancement at Wuhan. The second one at nighttime during the recovery phase of the storm on 29 May triggered ionospheric variations, mainly due to the later southward turning of the IMF-Bz as the Asian regions, were on the nightside with the westward PPEF. Negative storm time ionospheric responses were observed on 30 May, related to the change of the thermospheric composition as O/N2 depletion. Moreover, a significant increase in TEC was recorded during the main phase of the storm on 8 September 2017. This enhancement corresponded with the eastward PPEF and an increase in the O/N2. The TEC increment was also observed during the recovery phase on 9 September in the Pakistani stations. A minor storm on 7 September also gave rise to TEC enhancements, especially in western regions. However, the negative phase was registered from 9 to 10 September at each station because of the changes in the thermospheric composition as O/N2 depletion.

The Ionospheric Responses from Satellite Observations within Middle Latitudes to the Strong Magnetic Storm on 25–26 August 2018

The multi observations from the China Seismo-Electromagnetic Satellite (CSES) were presented and analyzed during the biggest magnetic storm on 25–26 August in the quiet solar activity year of 2018, together with the Swarm satellite and GNSS TEC (Global Navigation Satellite System, Total Electron Content). The whole tempo-spatial evolutional process was demonstrated in electromagnetic fields and in-situ plasma parameters within the whole magnetic storm time period of three phases, the main phase with quick decrease in SYM-H, the quick recovery phase, and the slow recovery phase. Strong correlations were revealed in time and space between electric fields and electron density. During the main phase, the penetrated electric field was the major factor to induce the injection of electric fields to low latitudes even to the equator and contribute to constructing the double peaks of Ne at altitudes above 500 km of CSES in daytime. In the quick recovery phase, Ne depletion was found in low middle and low latitudes in the daytime, associated with a quick decrease in solar wind dynamic pressure, but in the nightside Ne maintained or increased. Due to the high solar wind speed following the quick recovery phase, it controlled the enhancements in an electric field below 1125 Hz at medium and low latitudes in daytime and produced similar structures in a 225 Hz electric field with the mid-latitude trough of Ne in local nighttime and maintained their equator-ward movements in this time period. Ne/TEC showed typical local time-dependence in this magnetic storm, which illustrated that although the electron density in the ionosphere was mainly caused by this solar activity event, local background environments must also not be ignored for their final evolutional modes.

Improving estimates of the ionosphere during geomagnetic storm conditions through assimilation of thermospheric mass density

Dynamical changes in the ionosphere and thermosphere during geomagnetic storm times can have a significant impact on our communication and navigation applications, as well as satellite orbit determination and prediction activities. Because of the complex electrodynamics coupling processes during storms, which cannot be fully described with the sparse set of thermosphere–ionosphere (TI) observations, it is crucial to accurately model the state of the TI system. The approximation closest to the true state can be obtained by assimilating relevant measurements into physics-based models. Thermospheric mass density (TMD) derived from satellite measurements is ideal to improve the thermosphere through data assimilation. Given the coupled nature of the TI system, the changes in the thermosphere will also influence the ionosphere state. This study presents a quantification of the changes and improvement of the model state produced by assimilating TMD not only for the thermosphere density but also for the ionosphere electron density under storm conditions. TMD estimates derived from a single Swarm satellite and the Coupled Thermosphere Ionosphere Plasmasphere electrodynamics (CTIPe) physics-based model are used for the data assimilation. The results are presented for a case study during the St. Patricks Day storm 2015. It is shown that the TMD data assimilation generates an improvement of the model’s thermosphere density of up to 40% (measured along the orbit of the non-assimilated Swarm satellites). The model’s electron density during the course of the storm has been improved by approximately 8 and 22% relative to Swarm-A and GRACE, respectively. The comparison of the model’s global electron density against a high-quality 3D electron density model, generated through assimilation of total electron content, shows that TMD assimilation modifies the model’s ionosphere state positively and negatively during storm time. The major improvement areas are the mid-low latitudes during the storm’s recovery phase.Graphical

Traveling Ionospheric Disturbances in the Vicinity of Storm-Enhanced Density at Midlatitudes.

This study provides first storm time observations of the westward‐propagating medium‐scale traveling ionospheric disturbances (MSTIDs), particularly, associated with characteristic subauroral storm time features, storm‐enhanced density (SED), subauroral polarization stream (SAPS), and enhanced thermospheric westward winds over the continental US. In the four recent (2017–2019) geomagnetic storm cases examined in this study (i.e., 2018‐08‐25/26, 2017‐09‐07/08, 2017‐05‐27/28, and 2016‐02‐02/03 with minimum SYM‐H index −206, −146, −142, and −58 nT, respectively), MSTIDs were observed from dusk‐to‐midnight local times predominately during the intervals of interplanetary magnetic field (IMF) Bz stably southward. Multiple wavefronts of the TIDs were elongated NW‐SE, 2°–3° longitude apart, and southwestward propagated at a range of zonal phase speeds between 100 and 300 m/s. These TIDs initiated in the northeastern US and intensified or developed in the central US with either the coincident SED structure (especially the SED basis region) or concurrent small electron density patches adjacent to the SED. Observations also indicate coincident intense storm time electric fields associated with the magnetosphere–ionosphere–thermosphere coupling electrodynamics at subauroral latitudes (such as SAPS) as well as enhanced thermospheric westward winds. We speculate that these electric fields trigger plasma instability (with large growth rates) and MSTIDs. These electrified MSTIDs propagated westward along with the background westward ion flow which resulted from the disturbance westward wind dynamo and/or SAPS.

Continuous Enhancements of Electron Temperature in the Subauroral Ionosphere Over Eight Days During the 2015 St. Patrick’s Day Storm

AbstractWe have used measurements of the Defense Meteorological Satellite Program (DMSP) satellites to study variations of electron temperature in the subauroral ionosphere during the magnetic storm on 17–25 March 2015. This magnetic storm had a long recovery phase of 7 days, and the ionospheric behavior over the entire storm time was seldom investigated. In this study, we find that the electron temperature at subauroral latitudes was continuously enhanced for 8 days, from the storm onset to the end of the recovery phase. The maximum electron temperature during the storm times was 1000–4000 K higher than the maximum electron temperature during quiet times. This long‐lasting enhancement of subauroral electron temperature was attributed to energy transfer among the solar wind, magnetosphere, ring current, plasmasphere, and ionosphere driven by high‐speed solar wind streams and fluctuating interplanetary magnetic field during the entire 8‐day period of the storm. The electron temperature enhancements were quite symmetric in the post‐midnight sector but became strongly asymmetric near dawn between the southern and northern hemispheres. The asymmetric enhancements of electron temperature near dawn may be related to the magnetic declination and the daytime midlatitude trough in the southern hemisphere. Large daily variations of maximum electron temperature in the post‐midnight sector were observed and may be related to the offset between geomagnetic and geographic latitudes. These DMSP observations provide new insight on ionospheric response to intense magnetic storms.

Probabilistic Prediction of Dst Storms One‐Day‐Ahead Using Full‐Disk SoHO Images

AbstractWe present a new model for the probability that the disturbance storm time (Dst) index exceeds −100 nT, with a lead time between 1 and 3 days. Dst provides essential information about the strength of the ring current around the Earth caused by the protons and electrons from the solar wind, and it is routinely used as a proxy for geomagnetic storms. The model is developed using an ensemble of Convolutional Neural Networks that are trained using Solar and Heliospheric Observatory (SoHO) images (Michelson Doppler Imager, Extreme ultraviolet Imaging Telescope, and Large Angle and Spectrometric Coronagraph). The relationship between the SoHO images and the solar wind has been investigated by many researchers, but these studies have not explicitly considered using SoHO images to predict the Dst index. This work presents a novel methodology to train the individual models and to learn the optimal ensemble weights iteratively, by using a customized class‐balanced mean square error (CB‐MSE) loss function tied to a least‐squares based ensemble. The proposed model can predict the probability that Dst &lt; −100 nT 24 hr ahead with a True Skill Statistic (TSS) of 0.62 and Matthews Correlation Coefficient (MCC) of 0.37. The weighted TSS and MCC is 0.68 and 0.47, respectively. An additional validation during non‐Earth‐directed CME periods is also conducted which yields a good TSS and MCC score.

Ionospheric storm due to solar Coronal mass ejection in September 2017 over the Brazilian and African longitudes

Coronal mass ejection (CME) occurs when there is an abrupt release of a large amount of solar plasma, and this cloud of plasma released by the Sun has an intrinsic magnetic field. In addition, CMEs often follow solar flares (SF). The CME cloud travels outward from the Sun to the interplanetary medium and eventually hits the Earth’s system. One of the most significant aspects of space weather is the ionospheric response due to SF or CME. The direction of the interplanetary magnetic field, solar wind speed, and the number of particles are relevant parameters of the CME when it hits the Earth’s system. A geomagnetic storm is most geo-efficient when the plasma cloud has an interplanetary magnetic field southward and it is accompanied by an increase in the solar wind speed and particle number density. We investigated the ionospheric response (F-region) in the Brazilian and African sectors during a geomagnetic storm event on September 07–10, 2017, using magnetometer and GPS-TEC networks data. Positive ionospheric disturbances are observed in the VTEC during the disturbed period (September 07–08, 2017) over the Brazilian and African sectors. Also, two latitudinal chains of GPS-TEC stations from the equatorial region to low latitudes in the East and West Brazilian sectors and another chain in the East African sector are used to investigate the storm time behavior of the equatorial ionization anomaly (EIA). We noted that the EIA was disturbed in the American and African sectors during the main phase of the geomagnetic storm. Also, the Brazilian sector was more disturbed than the African sector.

ULF geomagnetic anomaly associated with the Sumatra-Pagai Islands earthquake swarm during 2020

Observations of earthquake precursors via geomagnetic anomalies from ultra-low frequency (ULF) could provide an expectation for short-term earthquake prediction. However, there are still several obstacles in determining this precursor, one of which is the presence of a precursor bias if the earthquake occurs at a close time and location. To cope with this problem, we analysed six earthquakes with a magnitude &gt;5 on Pagai Island, Mentawai, Sumatra, during 2020. These earthquakes have epicentres close to each other and occur within a short time (one month). This study used geomagnetic data recorded by the Magnetic Data Acquisition System (MAGDAS) magnetometer network at Sicincin station (SCN), West Sumatra, and Kepahiyang station (KPY), Bengkulu, with a span of one month before the earthquake. The anomaly of ULF emission was analysed using the power spectral density method at a frequency of 0.012 Hz for the H and Z components of the geomagnetic data. The onset time of the ULF emission anomaly was determined by the standard deviation value (pz + σ, pz – σ) of the SZ/SH power ratio polarization. The disturbance storm time index (Dst) was used to ensure that the anomaly occurred was not caused by geomagnetic storm. Also, the single station transfer function was used to calculate the azimuth, and the empirical formula between the anomaly amplitude and the magnitude was used to calculate the earthquake magnitude as the validation of the anomaly source. Several ULF anomalies as earthquake precursors were observed, especially at the KPY station. The estimated azimuth shows a good accuracy compared to the earthquake's azimuth, with an average value of 97.8%. Furthermore, the earthquake magnitude calculated from the ULF anomaly shows a good agreement with the actual earthquake magnitude, with an average accuracy of 98.13%.

Equatorial plasma bubbles for solar maximum & moderate year of the solar cycle 24

The fluctuations in the electron density of the F-region in the ionosphere as compared to the background electron density are the sign of plasma irregularities which is a well-known phenomenon. They occur during post-sunset hours and degrade ionospheric radio wave communication majorly the navigation signals. To explore the features of equatorial plasma bubbles (EPBs) over the Indian region throughout the solar maximum year 2014 and the solar moderate year 2017, we have examined day and night hours plasma irregularities from Defense Meteorological Satellite Program (DMSP) with spacecraft as F15 with total crossings as 9698. From the total crossings, 1115 crossings were obtained with EPBs degrading the communication and navigation signals. The distribution of EPBs was studied monthly, seasonally, and longitudinally for the solar maximum and moderate years which has given significant results. We have also analyzed the occurrence of EPBs during the geomagnetic storms with Disturbed storm time index (Dst) ≤ -100 nT occurred in the solar maximum and moderate years. We have observed that the regular occurrence of EPBs was there during the initial and main phase but smoothens up in course of the recovery phases of the storm. These results are discussed with those of earlier results and are in good agreement too. The observed inferences will help to improve the telecommunication sector in the Indian region.

Assessment of solar wind driven ionospheric storm forecasts: The case of the Solar Wind driven autoregression model for Ionospheric Forecast (SWIF)

This paper reports the results of the most recent validation tests on the performance of the Solar Wind driven autoregression model for Ionospheric Forecast (SWIF). SWIF uses the Interplanetary Magnetic Field (IMF) observations at L1 point as a proxy for upcoming ionospheric storm time disturbances, issuing an alert in case certain quantitative criteria are met. These criteria apply to the IMF total magnitude and the IMF-Bz component. The validation tests address the SWIF alert detection efficiency in the period 2014–2020 and were designed to complement previous efforts and allow the comprehensive discussion of SWIF's alert ability over one and a half solar cycle. The model's efficiency is quantified through probability of detection, false alarm rate and the success ratio for SWIF's users. The results are further discussed in terms of the intensity and the interplanetary causes of the storms to reveal high forecasting ability for specific storm scenarios (i.e. intense storms that are usually driven by coronal mass ejections), but also certain limitations in the efficiency of SWIF's alert criteria in capturing storm related interplanetary structures at L1 point: mainly structures that are not related to coronal mass ejections and typically, drive storms of moderate intensity. Additional results obtained by superposed epoch analysis of IMF key components indicate the potential relevance of the IMF-By component in ionospheric forecasting applications. The consideration of the IMF-By in SWIF's formulation can drive future improvements in its forecasting efficiency in all different faces of solar wind forcing. The findings of this work may also help the better understanding of the processes that control the coupling of the solar wind-magnetosphere-ionosphere.