24th Solar Cycle Research Articles

Precision measurements of cosmic ray electron and positron spectra above 50 MeV with the PAMELA magnetic spectrometer

The PAMELA experiment with magnetic spectrometer operated almost ten years on board of the Resurs DK1 satellite. The satellite was launched on 15 June 2006 on polar orbit with an inclination of 70° and an altitude of 350–610 km. The spectrometer continuously measured charged cosmic ray particles in wide energy range from about 50 MeV up to several TeV. In this work the spectra of electrons and positrons averaged over one year were obtained from July of 2006 until January 2016, i.e. from the end of 23th and at the beginning of 24th solar cycle including the period of interplanetary magnetic field polarity reversal. These precise long duration time-dependent measurements of the electron and positron spectra are important to estimate possible contributions of exotic cosmic ray sources such as dark matter annihilation or decay.

Plasma re-distribution in the African low-latitude ionosphere during intense geomagnetic storms

Intense geomagnetic storms offer opportunity to understand ionospheric response to space weather events. Using Total Electron Content (TEC) data from stations along the east African sector, the two most intense storms during the 24th solar cycle, with similarly occurrence season and time were studied. We observe that ionospheric effect during the main phase is not a function of the severity of the storm, whereas the more intense storm shows greater influence on the African ionosphere during the recovery phase. Plasma movement within the equatorial ionization anomaly (EIA) was evident particularly during the recovery phase, especially during the 2015 event. For both storms, the nighttime/early morning ionospheric effect is more pronounced than the daytime effects across all stations.
 

Possibility of Diagnostics of the Beginning of Solar Cycle 25 Based on Its Precursors at Mid-Heliolatitudes

The potential to diagnose the beginning of the solar cycle based on the detection of small-scale magnetic formations, the magnetic nodes of ephemeral active regions in the zone of mid-heliolatitudes from 40° to 60°, has been studied. Magnetic nodes were detected at the stage of their emergence by the multifractal segmentation method, which was previously used to fix new magnetic fluxes of active regions in the zone of low heliolatitudes. Statistical estimates of the number of magnetic nodes recorded by this method were performed based on magnetograph data from the Synoptic Optical Long-term Investigations of the Sun of the National Solar Observatory (SOLIS NSO) for the 24th solar activity cycle, as well as for the beginning of the 25th activity cycle. A precursor of solar cycle 24 has been found in the form of a burst in the number of magnetic nodes in 2007–2008 that significantly exceeds the background value characteristic of the period 2011–2015. Two years later, the first active regions began to appear at latitudes of 30° ± 10°. A similar sequence of phases in the beginning of the cycle was found for cycle 25. Unlike the situation with solar cycle 24, the mass appearance of high-latitude active regions of cycle 25 occurred about 2.5 years after the burst in the number of nodes of ephemeral active regions.

Evidence of a strong relationship between hemispheric asymmetry in solar coronal rotation and solar activity during solar cycle 24

ABSTRACT In this paper, we report evidence of a very strong and statistically significant relationship between hemispheric asymmetry in the solar coronal rotation rate and solar activity. Our approach is based on the cross-correlation of the hemispheric asymmetry index (AI) in the rotation rate with annual solar activity indicators. To obtain the hemispheric asymmetry in the solar rotation rate, we use solar full disc (SFD) images at 30.4-, 19.5- and 28.4-nm wavelengths for the 24th solar cycle, that is, for the period from 2008 to 2018, as recorded by the Solar Terrestrial Relations Observatory (STEREO) space mission. Our analysis shows that the hemispheric asymmetry in rotation rate is high during the solar maxima from 2011 to 2014. However, hemispheric asymmetry decreases gradually on both sides (i.e. from 2008 to 2011 and from 2014 to 2018). The results show that the AI leads sunspot numbers by ∼ 1.56 yr. This is a clear indication that hemispheric asymmetry triggers the formation of sunspots in conjunction with the differential rotation of the Sun.

Behavior of F2-layer parameters and solar activity indices in the 24th cycle

The analysis of the behavior of the critical frequency foF2 during the 24th solar activity cycle (Danilov and Konstantinova, 2020a, c) is prolonged for two more months and the nighttime hours. In addition to the Rz and Ly-α indices used in the aforementioned papers for correction of the F10.7 index during the 24th cycle, the commonly used Mg II index is added. The results confirm the previous conclusions on the existence of the “vague” period with chaotic behavior of foF2 and the recovery of the negative trend in foF2 after 2008–2010. A comparison of the F10.7 index with three other SA indices (Ly-α, Rz, and Mg II) for the 22nd, 23rd, and 24th SA cycles is performed. It is shown that the relationship between F10.7 and other indices is close in the 22nd and 23rd cycles but differs from that in the 24th cycle. The corrected values of F10.7 in the 24th cycle are proposed for analysis of ionospheric trends during that cycle.

Modelling and forecasting of ionospheric TEC irregularities over a low latitude GNSS station

The study aims to take an advantage of the systematic combination of statistical procedures namely Principal Component analysis (PCA), Linear Model to develop a local climatological model for ionospheric Total Electron Content (TEC) irregularities. Further, Auto Regressive Moving Average (ARMA) model, Neural Network (NN) model are used to forecast the ionospheric irregularities over Bengaluru region, India. Bengaluru International GNSS Service (IGS) station dataset (geographic lat.- 13.02°N, long.77.57°E; geomagnetic latitude: 4.4°N) of an 8-year period has been used to implement the proposed algorithm. Retrieval of the main components of the times series using Principal Component Analysis, identifying and analyzing the trends and cycles in the PCA residual to model the un-modelled irregularities using Linear model and finally fitting the residual series using ARMA/NN models to forecast the irregularity es has delivered successful results. The ionospheric TEC irregularities, measured in TECU/hour, are investigated during the 24th solar cycle ascending and descending phases. The MAE and RMSE values are used for the validation of the proposed models in forecasting the ionospheric TEC irregularities during both geomagnetic quiet and storm days (12–14 October 2016). It is observed that MAE value of NN model is 0.5 TECU/hour during geomagnetic quiet period whereas it is 0.98 TECU/hour during geomagnetic disturbed period. Moreover, the RMSE value of ARMA model is 0.73 TECU/hour and 0.67 TECU/hour for NN model which reveals that NN model is comparatively good in forecasting the ionospheric TEC irregularities during geomagnetic quiet period. The proposed model can be useful to develop an ionospheric irregularity climatological tool for low latitude regions.

Physical Conditions in Coronal Holes

The physical conditions in the chromosphere of polar and equatorial coronal holes in the decay phase of the 24-th solar activity cycle are studied. Models of the chromosphere are constructed based on the intensities of the HeI 10830 A and Hα lines and using a non-LTE program. The calculations showed that the temperature in equatorial coronal holes is similar to that of polar coronal holes. The temperature in coronal holes is lower than that of the unperturbed chromosphere and increases depending on height in the chromosphere. The difference between the atmospheres of coronal holes and the quiet Sun begins at the level of the upper photosphere- lower chromosphere.

Modeling and analysis of ionospheric TEC variability from GPS–TEC measurements using SSA model during 24th solar cycle

Ionospheric modeling across the Indian low latitudes continues to be a challenging task because of the day-to-day variability pertaining to the underlying complex equatorial and low latitude electrodynamics. In this paper, we aimed at developing an ionospheric Total Electron Content (TEC) model based on Singular Spectrum Analysis (SSA) using the Global Positioning System (GPS)-TEC observations (from 2009 to 2019) at Bengaluru (Geographic: 13.02° N, 77.57° E; Dip Angle: 13.77° N), a low latitude station in India. SSA has the most significant advantage of extracting information from the noisy time-series data with the first-four SSA modes in the decomposition, almost converging to total variance of about 99%. The proposed SSA-TEC model has been assessed by comparing it with the GPS-TEC observations as well as the outcomes from the latest version of the International Reference Ionosphere model (IRI-2016) and International GNSS Services Global Ionosphere Maps (IGS-GIM). The results demonstrate excellent outcomes with the Root Mean Square Error (RMSE) values between observed and model estimations laying at 1.58 TECU (SSA), 7.04 TECU (IRI-2016), and 8.89 TECU (GIM) with the respective correlation coefficients 0.99, 0.91, and 0.94. The model outcomes are in good agreement with the GPS-TEC observations, presenting relatively better estimates of TEC than the IRI-2016 and GIM during the geomagnetically quiet and disturbed daytime and nighttime conditions under different seasons and solar activity. Moreover, the proposed SSA-TEC model replicates the significant changes and time distribution characteristics of the ionosphere over the low latitude location, foreseeing the scopes for its regional implementation with a wide range of operations.

Climatology Characteristics of Ionospheric Irregularities Described with GNSS ROTI

At equatorial and high latitudes, the intense ionospheric irregularities and plasma density gradients can seriously affect the performances of radio communication and satellite-based navigation systems; that represents a challenging topic for the scientific and engineering communities and operational use of communication and navigation services. The GNSS-based ROTI (rate of TEC index) is one of the most widely used indices to monitor the occurrence and intensity of ionospheric irregularities. In this paper, we examined the long-term performance of the ROTI in terms of finding the climatological characteristics of TEC fluctuations. We considered the different scale temporal signatures and checked the general sensitivity to the solar and geomagnetic activity. We retrieved and analyzed long-term time-series of ROTI values for two chains of GNSS stations located in European and North-American regions. This analysis covers three full years of the 24th solar cycle, which represent different levels of solar activity and include periods of intense geomagnetic storms. The ionospheric irregularities’ geographical distribution, as derived from ROTI, shows a reasonable consistency to be found within the poleward/equatorward boundaries of the auroral oval specified by empirical models. During magnetic midnight and quiet-time conditions, the equatorward boundary of the ROTI-derived ionospheric irregularity zone was observed at 65–70° of north magnetic latitude, while for local noon conditions this boundary was more poleward at 75–85 magnetic latitude. The ionospheric irregularities of low-to-moderate intensity were found to occur within the auroral oval at all levels of geomagnetic activity and seasons. At moderate and high levels of solar activity, the intensities of ionospheric irregularities are larger during local winter conditions than for the local summer and polar day conditions. We found that ROTI displays a selective latitudinal sensitivity to the auroral electrojet activity—the strongest dependence (correlation R > 0.6–0.8) was observed within a narrow latitudinal range of 55–70°N magnetic latitude, which corresponded to a band of the largest ROTI values within the auroral oval zone expanded equatorward during geomagnetic disturbances.

Anomaly effects of 6–10 September 2017 solar flares on ionospheric total electron content over Saudi Arabian low latitudes

Solar flares are sudden eruption of intense high-energy radiation from the Sun causing radio perturbations due to disturbances in ionosphere and magnetosphere of the Earth. The present paper investigates ionospheric response to a series of X- and M-class solar flares during 6–10 September 2017 with simultaneously extracted total electron content (TEC) from six global positioning system (GPS) observatories around Saudi Arabian low latitudes. These solar flares include the most significant event of the 24th solar cycle and the brightest one in the past ten years. The results show noticeable enhancement in TEC magnitudes with the flare induced geomagnetic storms as compared to the average nearest quiet days. An abrupt increase in TEC (~132%) is observed at the eastward location in Oman with a time lag of about 1 h from the brightest solar flare (X9.3) whereas other sites depict increments within 22%–78%, referring to a longitudinal asymmetry during the period. However, a remarkable deviation from the quiet time TEC is visible at all stations about 24 h after the event, with the maximum and the least positive differences in TEC at the westward Israel (~141%) and the southward Djibouti (23%) stations, respectively. Comparable levels of TEC (~200%–300%) were also seen at far equatorial locations after the M-class flare on September 8, 2017, corroborating to the conjugate effects of solar flares and coronal mass ejections (CMEs) induced geomagnetic storms and O/N2 changes. Interestingly, the second brightest solar flare (X8.2) appeared to be less effective confirming a negative ionospheric response at the eastern side during the nighttime hours.

On the observation of magnetic events on broad-band seismometers

The objective of this contribution is to get new insights into the effects of magnetic field variations of natural and anthropogenic origin on broad-band seismic stations. Regarding natural sources of magnetic perturbations, we have investigated if the Sudden Storm Commencements (SSC) cataloged during the 24th solar cycle (2008–2019) can be systematically identified in broad-band seismic stations distributed worldwide. The results show that the 23 SSC events with a mean amplitude above 30 nT and most of those with lower energy but still clearly identified in the magnetometer detection network can be observed at broad-band stations’ network using a simple low-pass filter. Although the preliminary impulse of those signals is usually stronger at stations located at high latitudes, major SSC are observed at seismic stations distributed worldwide. Regarding anthropogenic sources, we focus on the short period seismic signals recorded in urban environments which are correlated with the activity of the railway transportation system. We have analyzed collocated measurements of electric field and seismic signals within Barcelona, evidencing that significant changes in the electric field following the activity of the transportation systems can be attributed to leakage currents transmitted to the soil by trains. During space weather events, electric currents in the magnetosphere and ionosphere experience large variations inducing telluric currents near the Earth surface, which in turn generate a secondary magnetic field. In the case of underground trains, leakage currents are transmitted to the soil, which in turn can result in local variations in the magnetic field. The observed signals in modern seismometers can be related to the reaction of the suspension springs to these magnetic field variations or to the effect of the magnetic field variations on the force transducers used to keep the mass fixed.

Performance analysis of Neural Networks with IRI-2016 and IRI-2012 models over Indian low-latitude GPS stations

The Global Positioning System (GPS) applications are highly vulnerable to the ionospheric space weather effects. Modelling and forecasting the ionospheric effects such as time delays for GPS signals are important for real time alerts of space weather effects on GPS services. In the present work, the performance of Neural Networks (NN) model is compared with International Reference Ionosphere (IRI) models. The ionospheric Total Electron Content (TEC) observations have been collected during 2015 year, descending phase of 24th solar cycle, over three Indian low latitude GPS stations namely, Bengaluru (Geographic coordinates: 13.02°N and 77.57°E), near to geomagnetic equator, Guntur (Geographic coordinates: 16.37°N and 80.37°E), which is at Equatorial Ionization Anomaly (EIA) and Lucknow (Geographic coordinates: 26.83°N and 80.92°E), which is beyond EIA region. The performance of NN model in predicting the ionospheric TEC values is compared with IRI (IRI-2012 and IRI-2016) models during test period, October–December 2015 over three Indian low latitude regions. It is observed that IRI models (IRI-2012 and IRI-2016) have shown more the temporal differences with GPS-VTEC during sunrise hours compared to sunset hours over three low latitude regions. The performance of IRI-2016 model has apparently better than IRI-2012 model. However, it is observed that IRI-2016 model has large discrepancies over Bengaluru and Guntur station due to high VTEC fluctuations at equatorial and low latitudes. The NN models are well predicted the measured diurnal mean VTEC variations with the less errors, ±5 TECU but the differences of IRI models are ±15 TECU over all the three stations. Later, GPS-data for 10 years, 2009–2018, is collected over Bengaluru station during 24th solar cycle. The performance of NN model is validated during 2016, 2017 and 2018 years over Bengaluru GPS station. The error measurements and experimental results reported that the measured GPS-VTEC values are well predicted by NN model compared to IRI-2016 model over equatorial and low latitude GPS stations.

A Statistical Study on the Winter Ionospheric Nighttime Enhancement at Middle Latitudes in the Northern Hemisphere

AbstractThe ionospheric electron density generally decreases after sunset under the effect of recombination, but sometimes, it increases, which forms an ionospheric nighttime enhancement (INE). In this research, the observations from two ionosondes in Mohe and Beijing and NASA's Jet Propulsion Laboratory‐Global Ionosphere Maps during the 24th solar cycle were used to explore the feature and mechanism of INE at midlatitudes. It shows that hmF2 always increases when INE occurs in summer, while it either rises or falls in winter. The increase of hmF2 has a significant contribution to INE in summer. For winter INE, however, the hmF2‐rising and the hmF2‐declining type INEs present no significant differences in durations and amplitudes, except that the former occurs slightly earlier than the latter. This suggests that the uplift of the ionosphere induced by equatorward thermospheric wind may not be a dominant factor for controlling the formation of winter INE at midlatitudes. We found that the electron density difference between the summer hemisphere and the winter hemisphere trends increases when the INE occurs in the winter hemisphere. This increased electron density difference between the two hemispheres is beneficial to the summer‐to‐winter interhemispheric plasma transport and the formation of INE in winter. Meanwhile, it is likely that the ionospheric equivalent slab thickness decreases during the winter INE due to downward transport from the topside. These indicate that downward plasma influxes from the topside ionosphere and the conjugate summer hemisphere play dominant roles for the formation of winter INE at middle latitudes.

A Study of Largest Active Region AR12192 of 24th Solar Cycle Using Fractal Dimensions and Mathematical Morphology

An active region (AR) of the sun is an area of strong magnetic field. Sunspots are frequently formed in an AR. Solar activity exhibits in the form of solar flares and coronal mass ejections. Solar active region AR12 192 occurring on October 18, 2014 hosted the largest sunspot of the 24th solar cycle which was of the size of Jupiter. AR12 192 was ranked 33rd largest active region out of 32908 active regions since 1874. This study analyzes the complexity and roughness of AR12 192 by studying the hidden persistency. Here persistency will be studied with the help of self-similar fractal dimension. For this purpose two techniques will be used, the Hausdorff-Besicovich box dimension and correlation dimension. The fractal dimension of the image of solar active region AR12 192 will be studied for its persistency. An image is considered to be persistent if the value of Hurst exponent is greater than 0.5. In addition, an analysis is performed using scaling parameters and wave spectrum. In this regard exponents such as scaling exponent, spectral exponent, and autocorrelation coefficient will be particularly studied. Heavy tail analysis for the data relevant to AR12 192 is also performed. A novelty of this study is the application of segmental image analysis using the transformation tools of mathematical morphology such as dilation, erosion, closing and opening to AR12 192.

Dynamics of Electric Current’s Parameters in Active Regions on the Sun and Their Relation to the Flare Index

Data from the Helioseismic and Magnetic Imager (HMI) on board the Solar Dynamics Observatory (SDO) on the components of the magnetic field vector in the photosphere for 39 active regions (AR) of the 24th solar activity cycle are used to calculate the parameters of the electric current. The time variations in the electric current parameters in the AR over the time the region is within ±35° of the central meridian are studied. An attempt is made to relate the parameters of the current in the photosphere and their dynamics to the level of flare activity of the region. These studies have yielded the following results: (1) The change in the total unsigned current in an AR is synchronous or quasi-synchronous with changes in the magnetic flux; (2) A relation between the total unsigned current and the flare index (FI) exists, but is weak (correlation k = 0.48); (3) The imbalance of the vertical electric currents for all 39 of the AR studied here was low and did not exceed a few percent, which indicates closure of the current structures on all scales within an AR; (4) The highest correlation (k = 0.72) with the flare index is observed for a time averaged absolute value of the density of the vertical electric current; (5) Statistical studies yield a critical level of equal to 2.7 mA/m2: when this level is exceeded in an AR, flares with higher x-ray classes (M and X) are observed and when the current density falls below the threshold value, there is a reduction in the flare productivity of the region; (6) For the example of two regions with an emerging magnetic flux it is shown that pumping magnetic energy into the corona requires some time; the time interval between the jump in and the onset of the development of the first powerful flares in x-ray classes M and X is at least 12-20 hours; (7) The character of the relation between the time variations in the average value of the density of the horizontal current and the imbalance in the vertical current ρjz with the level of flare activity of an AR is more complicated and requires separate, more detailed studies.

GPS derived ionospheric TEC variability with different solar indices over Saudi Arab region

In this paper, we investigate the variation of ionospheric total electron content (TEC) derived from global positioning system (GPS) observations at a low latitude station in Magna (Station code: RASH, Geographic coordinate: 28°17′N, 34°47′E), Saudi Arab. The study includes a linear regression method for validating the relationship between regional TEC and solar indices during the period 2015–2017 representing the descending phase of 24th solar cycle. The results show a relatively better agreement of diurnal variation of TEC with solar extreme ultraviolet (EUV) flux (0.1–50 nm wavelength) as compared to the Sunspot number (SSN) and 10.7 cm radio flux (F10.7). Interestingly, the seasonal variation shows a higher magnitude of TEC during the winter season as compared to the summer and fall equinox seasons, which is reported as the winter anomaly over the low latitude region. The correlation coefficient between VTEC and solar indices is also higher during the winter as compared to summer season. Concerning diurnal variability, the results show a higher correlation coefficient during the local noon time (1200SAST) that gradually descends towards evening time (1800SAST) and after that decays during the night time (2100SAST) to attend the diurnal minima. This manifests the diurnal solar irradiance dependence over the low latitude region. Moreover, the lesser agreement in the linear relationship between the TEC and solar indices during the year 2015 than the year 2017 substantiates the dependence of TEC magnitude and vitiations on solar activity. The outcomes from this strengthens the regional understanding and modeling of ionospheric parameters and would complement towards the global efforts for modeling and mitigating the ionospheric effects on transionospheric communication, timing and navigation services. Above all, the intents of this study are in line with the augmentation of aviation services performances in Saudi Arab that plays a vital role in the international civil aviation and logistic trade due to its central geographic location.

Mathematical analysis of the 09 March 2012 intense storm

The in-depth investigation of the parameters of the solar wind, the zonal geomagnetic indices and the interplanetary magnetic field (IMF) is the key to furthering space weather researches. The investigations got meaning through modeling various interplanetary parameters and geomagnetic indices. These models, built on the basis of the correlations between solar wind parameters and zonal geomagnetic indices, and that must strictly obey physical principles, will not only reveal the properties of geomagnetic activity but also allow estimates of their formations. This study focuses on the 2012 March 09 phenomenon, the first intense geomagnetic storm of the 24th solar cycle. The deeper understanding of the storm depends on a correct interpretation and visualization of the relationship between solar wind plasma parameters (solar wind dynamic pressure (P), flow speed (v), electric field (E), magnetic field (Bz), proton density (N), temperature (T)) and zonal geomagnetic indices (AE, ap, Kp, Dst). The study investigates, visualizes and interprets the solar wind plasma parameters and zonal geomagnetic indices themselves. The storm variables set included of observations of ten variables from NASA are described. By this investigation a covariance matrix indicates the strength of bivariate relationships, a dendrogram indicates hierarchical clustering into groups, and factor analysis indicates three distinct eigenvectors. In addition, linear and nonlinear models about the problem are introduced to readers. The author discuses mathematically what happened in the storm on 2012 March 09 at the beginning of the 24th solar cycle. The aim of this work is to help the reader understand the storm by providing the models that the representatives of parameters and indices coexist.

Minor Ground Level Enhancements in the Solar Cosmic Rays in the 24th Solar Activity Cycle

The first (preliminary) results of a systematic search for minor ground level enhancement (GLEs) in solar cosmic rays (SCRs) in the 24th solar activity cycle are presented. The search was conducted based on the data of the global network of neutron monitors with allowance for the results of direct satellite measurements. The initial assumption is that such increases point to the possible acceleration of solar particles in shock waves, which are generated by coronal mass ejections. The shape of the integral spectrum of the accelerated particles according to observations of neutron monitors and measurements from near-Earth space vehicles could serve as a determinant for checking that hypothesis. Studying the spectra manifests an informativity of our approach to a better understanding of SCR source properties.

Machine learning algorithm to forecast ionospheric time delays using Global Navigation satellite system observations

Global Navigation satellite systems (GNSS) are predominantly affected by Ionospheric space weather. The GNSS signal delays due to ionospheric Total Electron Content (TEC) can be forecasted using advances in the emerging mathematics tools and algorithms. Machine learning algorithms such as Gaussian Process Regression (GPR) is considered in the present paper to implement in the forecasting of low-latitude ionospheric conditions. The GPS receiver data is obtained for 8 years (2009–2016) during 24th solar cycle from International GNSS Services (IGS) station located in Bengaluru (Geographical latitude: 12.97° N, Geographical longitude: 77.59° E), India. The performance of GPR model is validated using statistical parameters such as Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), Mean Square Error (MSE), Root Mean Square Error (RMSE), and correlation coefficient. The results of the proposed GPR model were compared with the Auto Regressive Moving Average (ARMA) model and Artificial Neural Networks (ANN) model during solar maximum period and descending phase of 24th solar cycle. The experiment results are evident that GPR model is significantly providing the promising results in forecasting the ionospheric time delays for GNSS signals. The outcome of the work can be useful to develop web based Ionospheric TEC forecasting system to alert the GNSS users.

Modelıng of 21 July 2017 Geomagnetıc Storm

This essay involves mathematical analyzes of 21 July 21, 2017, geomagnetic storm in the 24th solar cycle. It focuses on solar wind parameters (Bz, E, P, N, v, T), zonal geomagnetic indices (Dst, ap, AE, Kp) obtained from NASA and discusses the July storm by strictly obeying the cause-effect relationship. The paper examines the phenomenon carefully and tries to reveal properties of the storm with the models governing by the causality principle. In this study, values interval and deviations of the variables are defined via descriptive analysis, binary relationships of the data are displayed with the covariance matrix and the cluster of the data are introduced by the dendrogram. Factor analysis is conducted with the help of normal distributions of the data and the phenomenon is tried to discuss with linear and nonlinear models. The study, without detachment from the context of the discussion, also detects anomalies of total electron content (TEC) data obtained from CODE (GIM).