Disturbance Storm Time Research Articles

Comparative Analysis of PCA and ANOVA for Assessing the Subset Feature Selection of the Geomagnetic Disturbance Storm Time

A Disturbance Storm Time (Dst) index represents the geomagnetic storm strength due to interaction of the Sun towards Earth in the space weather. Formation of the Dst contributed by the total of nine (9) input features namely interplanetary magnetic field (IMF), solar wind density (SWD), solar wind speed (SWS), solar wind input energy (SWIP) and also Earth’s magnetic field components comprise of the horizontal intensity component (H), declination component (D), north component (N), east component (E), and vertical intensity component (Z). Large datasets which comprise of 157896 number of data have existed for all features thus require pre-processing and subset feature selection for reducing data dimensionality in order to reduce the data processing time and enhance the performance of the learning algorithm. In this paper two methods of analyzing the features were compared: Principal Component Analysis (PCA) and one-way Analysis of Variance (ANOVA). The main aims for this works are to reduce a large set of input parameters from the Dst index and to compare the subset feature using the proposed methods for acquiring the reduced features. Prior to analyse the features, an independent-samples t-test is used to evaluate if there is a large difference between the mean of two groups that can be correlated with certain characteristics. The results for the features analyzed demonstrated that one-way ANOVA performed better in eliminating seven (7) components out of nine (9) components of features as compared to PCA. This finding was validated with a dendrogram to support that one-way ANOVA outperformed the PCA in reducing the subset features.

Modeling the 10,000-Year Geomagnetic Disturbance Scenarios Based on Extreme Value Analysis

Modeling the extreme geomagnetic disturbance (GMD) scenarios is of great significance for risk assessment of the power system. In this letter, we model the 10,000-year GMD scenarios using the extreme value analysis to complement the classical 100-year and 200-year events. The 10,000-year GMD event is required for safety-critical nodes such as the ultra-high voltage (UHV)/extra-high voltage (EHV) substations and nuclear power plants, etc. The return level of geomagnetic variation is estimated using the geomagnetic observations based on extreme value theory, which is then combined with the theoretical upper limit of the disturbance storm time (Dst) index to establish the 10,000-year GMD scenarios. Finally, we present an application example of 10,000-year geomagnetically induced currents (GICs) in the Sanhua UHV power grid.

Forecasting Global Ionospheric TEC Using Deep Learning Approach

AbstractGlobal ionospheric total electron content (TEC) maps are widely utilized in research regarding ionospheric physics and the associated space weather impacts, so there is a great interest in the community in short‐term ionosphere TEC forecasting. In this study, the long short‐term memory (LSTM) neural network (NN) is applied to forecast the 256 spherical harmonic (SH) coefficients that are traditionally used to construct global ionospheric maps (GIM). Multiple input data, including historical time series of the SH coefficients, solar extreme ultraviolet (EUV) flux, disturbance storm time (Dst) index, and hour of the day, are used in the developed LSTM NN model. Different combinations of the above parameters have been used in constructing the LSTM NN model, and it is found that the model using all four parameters performs the best. Then the best performing LSTM model is used to forecast the SH coefficients, and the global hourly TEC maps are reproduced using the 256 predicted SH coefficients. A comprehensive evaluation is carried out with respect to the CODE GIM TEC. Results show that the first/second hour TEC root mean square error (RMSE) is 1.27/2.20 TECU during storm time and 0.86/1.51 TECU during quiet time, so the developed model performs well during both quiet and storm times. Moreover, typical ionospheric structures, such as equatorial ionization anomaly (EIA) and storm‐enhanced density (SED), are well reproduced in the predicted TEC maps during storm time. The developed model also shows competitive performance in predicting global TEC when compared to the persistence model and two empirical models (IRI‐2016 and NeQuick‐2).

Detection of Large-Scale Noisy Multi-Periodic Patterns with Discrete Double Fourier Transform. II. Study of Correlations Between Patterns

The discrete double Fourier transform (DDFT) was developed to search for large-scale multi-periodic patterns in the presence of noise and is based on detection of the equidistant series of harmonics generated by the periodic patterns in the discrete Fourier transform (DFT) spectra. As DDFT retains all generic features of the Fourier transform, the corresponding pattern correlation function (PCF) related to DDFT can be introduced similarly to the data correlation function (DCF) related to DFT on the basis of the Wiener–Khinchin relationship. Peaks in PCF indicate the number of periodic patterns in a dataset under analysis and have direct correspondence with the counterpart peaks in the DFT spectrum. The close correspondence between positions of the peaks in the PCF and DFT spectra strongly enhances statistical significance of detected periodicities. Similar PCFs can also be defined for the cepstrum transform. The combined DFT–DCF and DDFT–PCF technique was applied to the detection of cycles in geomagnetic activity using disturbance storm-time (Dst) index. In addition to the known 27-day, semiannual and 11-year cycles of geomagnetic activity, we have also found the annual cycle of activity. The results were compared with those obtained by the cepstrum transform. A multiple cross-check makes the combined technique much more efficient and robust in comparison with the detection based on a unique particular method.

Statistical Study of Loss of GPS Signals Caused by Severe and Great Geomagnetic Storms

AbstractLoss of satellite signals is the most significant disruption to global navigation satellite system (GNSS), such as global positioning system (GPS), associated with a geomagnetic storm. To characterize the lost GPS signals during severe and great geomagnetic storms, we define two indices, that is, the number of lost GPS signals at a single site (SLGS) and the global average rate of lost GPS signals (GLGS). We analyze the response of SLGS and GLGS to 14 intense geomagnetic storms with a minimum disturbance storm time (Dst) index less than −200 nT occurred since 2000. The results calculated from global GPS observation data showed that both the SLGS and GLGS responded well to the change of Dst index for all the studied storms, the loss of satellite signals mainly occurred during the main phase and the early recovery phase of geomagnetic storms. We found that the peak value of GLGS and the standard deviation of SLGS are exponentially correlated with the magnitude of Dst. We further compare the global distribution of SLGS with the relative differential total electron content (RTEC) and the rate of total electron content index (ROTI). The comparison results indicated that the new indices would be useful to evaluate the worst impact on GNSS performance during intense geomagnetic storms, and it is also a complementarity to the existing ionospheric indices.

Clustering of Fast Coronal Mass Ejections during Solar Cycles 23 and 24 and the Implications for CME–CME Interactions

Abstract We study the clustering properties of fast coronal mass ejections (CMEs) that occurred during solar cycles 23 and 24. We apply two methods: the Max Spectrum method can detect the predominant clusters, and the declustering threshold time method provides details on the typical clustering properties and timescales. Our analysis shows that during the different phases of solar cycles 23 and 24, CMEs with speeds ≥1000 km s−1 preferentially occur as isolated events and in clusters with, on average, two members. However, clusters with more members appear, particularly during the maximum phases of the solar cycles. Over the total period and in the maximum phases of solar cycles 23 and 24, about 50% are isolated events, 18% (12%) occur in clusters with two (three) members, and another 20% in larger clusters ≥4, whereas in a solar minimum, fast CMEs tend to occur more frequently as isolated events (62%). During different solar cycle phases, the typical declustering timescales of fast CMEs are τ c = 28–32 hr, irrespective of the very different occurrence frequencies of CMEs during a solar minimum and maximum. These findings suggest that τ c for extreme events may reflect the characteristic energy build-up time for large flare and CME-prolific active regions. Statistically associating the clustering properties of fast CMEs with the disturbance storm time index at Earth suggests that fast CMEs occurring in clusters tend to produce larger geomagnetic storms than isolated fast CMEs. This may be related to CME–CME interaction producing a more complex and stronger interaction with Earth’s magnetosphere.

Dynamic Time Warping as a New Evaluation for Dst Forecast With Machine Learning

Models based on neural networks and machine learning are seeing a rise in popularity in space physics. In particular, the forecasting of geomagnetic indices with neural network models is becoming a popular field of study. These models are evaluated with metrics such as the root-mean-square error (RMSE) and Pearson correlation coefficient. However, these classical metrics sometimes fail to capture crucial behavior. To show where the classical metrics are lacking, we trained a neural network, using a long short-term memory network, to make a forecast of the disturbance storm time index at origin time $t$ with a forecasting horizon of 1 up to 6 hours, trained on OMNIWeb data. Inspection of the model's results with the correlation coefficient and RMSE indicated a performance comparable to the latest publications. However, visual inspection showed that the predictions made by the neural network were behaving similarly to the persistence model. In this work, a new method is proposed to measure whether two time series are shifted in time with respect to each other, such as the persistence model output versus the observation. The new measure, based on Dynamical Time Warping, is capable of identifying results made by the persistence model and shows promising results in confirming the visual observations of the neural network's output. Finally, different methodologies for training the neural network are explored in order to remove the persistence behavior from the results.

Geomagnetic storm main phase effect on the equatorial ionosphere over Ile–Ife as measured from GPS observations

The effect of the main phase of two intense geomagnetic storm events which occurred on August 6 and September 26, 2011 on the equatorial ionosphere have been investigated using Global Positioning System (GPS) data obtained from an Ile–Ife station (geomagnetic lat. 9.84 ∘N, long. 77.25 ∘E, dip 7.50∘). Total Electron Content (TEC) profiles during the main phase of the two geomagnetically disturbed days were compared with quiet time average profiles to examine the response of the equatorial ionosphere. The results showed that the intensity of both storm events during the main phase which occurred at night-time correlated well with a strong southward direction of the z-component of the Interplanetary Magnetic Field (IMF-Bz) and Solar Wind Speed (Vsw), with the Disturbance storm time (Dst) profile showing multiple step development. TEC depletion was observed during the main phase of the August 6, 2011 storm event with TEC recording a maximum value of 9.31 TECU. A maximum TEC value of 55.8 TECU was recorded during the main phase of the September 26, 2011 storm event depicting TEC enhancement. Significant scintillation index value of 0.57 was observed when the main phase started on August 6, 2011 followed by a prolonged suppression while there was less significant scintillation impact on September 26, 2011 with a maximum value of 0.33. The present study show that rapid energy input from solar wind during geomagnetic storm events effect large variations in TEC and significant scintillation phenomenon in the equatorial ionosphere over Ile–Ife, Nigeria.

The Extreme Space Weather Event in 1903 October/November: An Outburst from the Quiet Sun

Abstract While the Sun is generally more eruptive during its maximum and declining phases, observational evidence shows certain cases of powerful solar eruptions during the quiet phase of solar activity. Occurring in the weak Solar Cycle 14 just after its minimum, the extreme space weather event in 1903 October–November is one of these cases. Here, we reconstruct the time series of geomagnetic activity based on contemporary observational records. With the mid-latitude magnetograms, the 1903 magnetic storm is thought to be caused by a fast coronal mass ejection (≈1500 km s−1) and is regarded as a superstorm with an estimated minimum of the equivalent disturbance storm time index (Dst’) of ≈−531 nT. The reconstructed time series has been compared with the equatorward extension of auroral oval (≈44.°1 in invariant latitude) and the time series of telegraphic disturbances. This case study shows that potential threats posed by extreme space weather events exist even during weak solar cycles or near their minima.

Relation between the asymmetric ring current effect and the anti-sunward auroral currents, as deduced from CHAMP observations

Abstract. During magnetically active periods the storm-time disturbance signal on the ground commonly develops an azimuthal asymmetry. Negative deflections of the magnetic horizontal (H) component are enhanced in the 18:00 local time sector and smallest in the morning sector. This is commonly attributed to the asymmetric ring current effect. In this study we investigate the average characteristics of anti-sunward net currents that are not closing in the ionosphere. Their intensity is growing proportionally with the amount of solar wind input to the magnetosphere. There is almost twice as much current flowing across the polar region in the winter hemisphere as on the summer side. This seasonal dependence is more pronounced in the dusk sector than in the dawn sector. Event studies reveal that anti-sunward currents are closely related to the main phase of a magnetic storm. Since the asymmetry of storm-time disturbances also builds up during the main phase, we suggest a relation between these two phenomena. From a statistical study of ground-based disturbance levels during magnetically active periods, we obtain support for our suggestion. We propose a new 3D current system responsible for the zonally asymmetric storm-time disturbance signal that does not involve the ring current. The high-latitude anti-sunward currents are connected at their noon and midnight ends to field-aligned currents that lead the currents to the outer magnetosphere. The auroral net current branch on the morning side is closed along the dawn flank near the magnetopause, and the evening side currents flow along the dusk flank magnetosphere. Regardless through which loop the current is flowing, near-Earth storm-time disturbance levels will in both cases be reduced in the morning sector and enhanced in the evening.

Total electron content anomalies associated with earthquakes occurred during 1998–2019

Statistical analyses on the intensification of seismic precursors before and after the earthquakes (EQs) from Global Navigation Satellite System (GNSS) based Total Electron Content (TEC) may provide evidences about the potential mechanisms of lithosphere-ionosphere coupling. In this paper, ionospheric anomalies before and after 1182 (Mw > 5.0) EQs during 1998–2019 at three different latitudinal zones (80°N–25°N, 25°N–25°S, and 25°S–80°S) are investigated from global GNSS TEC observations. Previous studies proposed different time intervals for the occurrence of TEC anomalies triggered by EQs. In this study, we reveal that prominent TEC anomalies in the form of enhancement and depletion occur within 5 days before and after the main shock of the EQs. Further analysis suggests that the probability of TEC anomalies occurred before EQs of Mw ≥ 6.0 and focal depth of less than 220 km (Zone B) is about 0.8. Similarly, a probability of 0.65 for TEC anomalies is recorded before EQs of Mw ≥ 7.0 and focal depth less than 120 km in Zones-A and C. In our analysis, TEC anomalies generated by EQs are isolated from those produced by the geomagnetic storms through the Kp geomagnetic activity index and the disturbance storm time (Dst) index.

Study of the Influence of the Solar Wind Energy on the Geomagnetic Activity for Space Weather Science

Abstract This paper addresses the investigation of the interaction of the solar wind energy with the Earth’s magnetosphere, by studying its correlation with the disturbance storm time (Dst) index, a proxy of the geomagnetic activity. Some relevant parameters of the solar wind (the bulk speed and the z-component of the interplanetary magnetic field) are explored in the energy−Dst space. It results that (i) the solar wind energy and the geomagnetic activity are strictly related, with the coronal mass ejections representing the most energetic and geoeffective driver; (ii) the slow solar wind has negligible effects on Earth regardless of its energy content, whereas high-speed streams may induce severe geomagnetic storming depending on the advected energy; and (iii) while at low and mid energies, geomagnetic disturbances are induced provided the magnetic reconnection between the interplanetary and terrestrial magnetic fields occurs, high-energy solar wind plasma can impact Earth even without reconnecting with the geomagnetic field at the dayside magnetopause. The most significant result in the framework of space weather science resides in the observational evidence that the Earth’s magnetosphere has a maximum response to the energetic content of the solar wind, which leads to the derivation of an empirical law allowing the proper forecast of the upper limit of the intensity of any geomagnetic disturbance on the basis of the solar wind energy derived in situ at the Lagrangian point L1.

On the Relationship Between the Transit Time of ICMEs and Strength of the Initiated Geomagnetic Storms

More than 140 isolated non-recurrent geomagnetic storms (GMSs) of various intensities from extreme to weak are considered, which are reliably identified with solar eruptive sources (coronal mass ejections, CMEs). The analysis aims to obtain a possibly complete picture of the relationship between the transit time of propagation of CMEs and interplanetary coronal mass ejections (ICMEs) from the Sun to the Earth (more precisely, the time interval dtp from the moment of an eruption until the peak of the corresponding GMS) and the maximum intensity of this GMS, as measured by the disturbance storm time geomagnetic index Dst. Two groups of events are singled out: one includes GMSs, the source of which was an eruption from an active region (AR events), the other GMSs caused by filament eruptions from quiescent areas of the Sun located outside ARs (QS events). The distribution of the large number of the analyzed events on a dtp - Dst plane confirms and substantially clarifies the known regularities. The AR events are characterized by a shorter transit time (dtp ~ 1-4 days) and much stronger GMSs (Dst up to -600 nT mainly) in comparison with the QS events (dtp ~ 3-5 days, Dst > -200 nT). For events of both groups, the shorter transit time of CMEs/ICMEs, the more intense GMSs; in particular, for AR events when dtp declines from 4 to 1 day, Dst decreases on average from -100 to -470 nT and can reach -900 nT. From the point of view of the nature of GMSs and their sources on the Sun, the obtained results mean that both the speed of CMEs/ICMEs and the strength of the magnetic field transferred by them are largely determined by the parameters of the corresponding eruptions, in particular, by the eruptive magnetic flux and the released energy.

The ULF geomagnetic anomalous signal associated with Nias earthquake M5.3 North Sumatra Indonesia on September 6, 2018

A study of ultra-low-frequency (ULF) geomagnetic signals has been carried out prior to the onset of Nias earthquake M5.3 that occurred at 07:13:49 LT (Local Time) on September 6, 2018, in West Nias regency, North Sumatra, Indonesia. We analyzed three components of geomagnetic data H, D, and Z measured in Gunung Sitoli (GSI) geomagnetic station which is about 108 km from the epicenter, from January 2018 until December 2018. We used the polarization ratio method in terms of power spectrum density within 0.027-0.033 Hz frequency range to evaluate the geomagnetic data by applying Fast Fourier Transform (FFT). This work presents evidence of ULF geomagnetic anomalies exceeding the statistical threshold associated with Nias earthquake M5.3 which appeared starting from 3.5 months until 3 weeks before the earthquake. When these anomalies occurred, the value of disturbance storm time (Dst) index shows that there is no high global geomagnetic activity. Thus, it is concluded that the clear precursory anomalies detected are related to the earthquake.

AE, DST, and Their SuperMAG Counterparts: The Effect of Improved Spatial Resolution in Geomagnetic Indices

AbstractFor decades, geomagnetic indices have been used extensively to parameterize space weather events, as input to various models and as space weather specifications. The auroral electrojet (AE) index and disturbance storm time index (DST) are two such indices that span multiple solar cycles and have been widely studied. The production of improved spatial coverage analogs to AE and DST is now possible using the SuperMAG collaboration of ground‐based magnetometers. SME is an electrojet index that shares methodology with AE. SMR is a ring current index that shares methodology with DST. As the number of magnetometer stations in the SuperMAG network increases over time, so does the spatial resolution of SME and SMR. Our statistical comparison between the established indices and their new SuperMAG counterparts finds that, for large excursions in geomagnetic activity, AE systematically underestimates SME for later cycles. The difference between distributions of recorded AE and SME values for a single solar maximum can be of the same order as changes in activity seen from one solar cycle to the next. We demonstrate that DST and SMR track each other but are subject to an approximate linear shift as a result of the procedure used to map stations to the magnetic equator. We explain the observed differences between AE and SME with the assistance of a simple model, based on the construction methodology of the electrojet indices. We show that in the case of AE and SME, it is not possible to simply translate between the two indices.

THE USE OF HORIZONTAL GEOMAGNETIC FIELD COMPONENTS FOR ESTIMATION OF GEOMAGNETICALLY INDUCED CURRENT OVER TURKEY DURING SPACE WEATHER EVENTS

In this study, the time derivatives of the horizontal geomagnetic field components were computed to estimate the geomagnetically induced current (GIC) over Turkey during space weather events and the results were compared with the geomagnetic activity indices. The interplanetary magnetic field (IMF) index, disturbance storm time (Dst) index, global geomagnetic activity indices (ap and Kp) were used as indicator of space weather events. The changes because of solar flares and coronal mass ejections in the space environment between the Sun and Earth are defined as space weather events. Such events’ effects on the Earth's magnetosphere are called geomagnetic storms. In this study, two different space weather events that occurred on 20-26 June 2015 and 06-10 September 2017 are analyzed. The data of the horizontal magnetic field components used in the analysis are obtained from İznik magnetic observatory (40.5⸰N, 29.7⸰E). During space weather event on 20-26 June 2015, the maximum (max.) value of time derivative of (dX/dt and dH/dt) X and H horizontal magnetic field components were calculated as 72,22 nT/min. and 74,40 nT/min., respectively, while during space weather event on 06-10 September 2017, the max. value of the time derivative of the X and H horizontal magnetic field components are calculated and the results are 36,90 nT/min. and 38,12 nT/min., respectively. Also, it was observed that the strength of the local geomagnetic disturbance and amplitude of dX/dt and dH/dt at the observatory station depend strongly on the characteristics of geomagnetic activity indices during the space weather events. The southward IMF Bz component induces larger amplitude of dX/dt and dH/dt. The results indicate that the possibility of GIC occurrence over Turkey is quite high. Therefore, we strongly believe that further research and experiment on GIC for Turkey is important.

Preliminary Analysis of Ionospheric Responses to Geomagnetic Storms Using the BDS GEO Satellites

The rapid development of Global Navigation Satellite System (GNSS) provides a reliable way to monitor the ionospheric response of geomagnetic storms. Compared with other types of satellites, the advantage of using the Beidou Navigation Satellite System (BDS) Geostationary Earth Orbit (GEO) satellites to monitor the ionosphere is that it has almost fixed Ionospheric Pierce Points (IPPs). When using the GEO satellites to monitor the ionosphere, the earth sites only need consider the ionospheric temporal change without considering the spatial change. In addition, the ionospheric delay directly calculated by the combined observations does not introduce model error and fitting error, and can obtain continuous and high-precision ionospheric delay series. According to the Disturbance Storm Time index (DST index) provided by World Data Center for Geomagnetism of Kyoto, three large geomagnetic storms occurred in 2015. This article uses the BDS dual-frequency observations to calculate the ionospheric VTEC sequences during the geomagnetic storms at the four sites KZN2, JFNG, SIN1, and CUT0, respectively; and the ionospheric responses during the three large geomagnetic storms in 2015 are preliminarily analysed. The results show that the ionospheric responses to geomagnetic storms are mainly positive and negative anomalies. Combining the results of each site during three geomagnetic storms, it is certain that different seasons have a decisive impact on the positive and negative ionospheric responses of geomagnetic storms.

Statistical study of geomagnetic storm effects on the occurrence of ionospheric irregularities over equatorial/low-latitude region of Africa from 2001 to 2017

The effect of Coronal Mass Ejection (CME) and Corotating Interaction Region (CIR)-driven storms on the occurrence of ionospheric irregularities (OIIs) over the African equatorial and low-latitude region are studied statistically for the first time. In addition to the CME and CIRs’ catalogs, we have used the disturbance storm time (Dst) ≤ -30 nT and Kp ≥ 3 to identify the storm periods. The study was based on Global Navigation Satellite System (GNSS) total electron content (TEC) observation from three stations (nklg: 8.05°S, 81.05°E; mbar: 10.22°S, 102.36°E; and nazr: 0.25°S, 111.01°E, Geomagnetic) during 2001–2017. Based on the GNSS observations, the rate of change of total electron indices (ROTIROTI and ROTIave) have been used to observe the presence/absence of ionospheric irregularities. To examine the effect of the storms on the OIIs, ratio of ROTIave of the selected storm period to the quiet monthly mean of ROTIave, ROTIratio=ROTIobs/ROTI‾quiet, was applied. Based on our analysis, ROTIratio≥3.2, ROTIratio≤0.16 and 0.16<ROTIratio<3.2 were identified as threshold values indicating the enhancement (EN), suppression (SP), and no significant (NE) effect of the storms on the OIIs, respectively. Our results revealed that the SP in the OII during CME-and CIR-driven storms are more prevalent than the EN. During both CIR-and CME-driven storms, the percentage occurrence rate in EN observed over nklg was greater than mbar and nazr. Most of the SP effect of the storms, on the other hand, was predominantly observed over nazr and mbar stations. The occurrence rate of EN, SP and NE effect of both CME-and CIR-driven storms show dependence on the local time at which large decrease in Dst occurs. We also found that SP effect of both CIR-and CME-driven storm show a positive and linear correlation with sunspot number (SSN). While the EN effect of CIR-driven storm show a negative and linear relation with SSN, CME-driven storm effects show weak relation. The polarity and amplitude of different sources of disturbance electric field observed in the evening hours could play a dominant role in affecting the OIIs. The difference in the seasonal variation in the occurrence rate of EN, SP and NE effect of the storms observed over different stations were also discussed.

Effect of a magnetic pulse on orientation behavior in rainbow trout (Oncorhynchus mykiss)

Magnetoreception remains one of the most enigmatic of animal senses. Rainbow trout (Oncorhynchus mykiss) represent an ideal species to study this sense, as magnetoreception based upon microscopic particles of magnetite is suspected to play an important role in their orientation and navigation. Here we found that compared with controls, a magnetic pulse (a treatment commonly used to demonstrate magnetite-based magnetoreception) can induce orientation behavior in juvenile rainbow trout on a specific experimental day. Multiple circular-linear regression also indicated that this effect could at least be partially explained by daily variation in solar electromagnetic activity (i.e., sunspot count and disturbance storm time index). These results are consistent with magnetite-based magnetoreception in rainbow trout and suggest that 1) solar activity may impact magnetic orientation and 2) researchers should be cognizant of its potential consequences on studies of magnetoreception.

Study of nonlinear time series and wavelet power spectrum analysis using solar wind parameters and geomagnetic indices

ABSTRACT We investigate the time series of solar wind parameters (interplanetary magnetic field, Bz and solar wind speed, Vx) and geomagnetic indices (disturbance storm time, Dst and auroral electrojet, AE) using wavelet analysis and nonlinear dynamics time series techniques. The data were collected from the Flight Center Space Physics Data Facility (GSFC/SPDF) OMNIWEB interface between 2008 and 2017. Wavelet power spectrum (WPS) analysis assists in breaking down the time series of Bz, Vx, Dst and AE parameters into different scales. It was noted that there is a greater concentration of power between the 512 and 1024 months bands across the Bz, Vx, Dst and AE parameters. We also applied non-linear time series modelling methods to examine the Bz, Vx, Dst and AE parameters. We utilised both the time delay and embedded dimension in computing average mutual information (AMI) and false nearest neighbors (FNN), respectively. The Lyapunov exponent (LE) is used to express the complexity of the nonlinear dynamics based on embedding parameters. The Lyapunov exponents depict positive values which confirm that the complex solar wind parameters and the geomagnetic indices are deterministic chaotic systems. The results show noticeable chaotic characteristics in the Bz, Vx, Dst and AE parameters.