Abstract In this study, we examine the dynamical complexity transitions during HILDCAA events. HILDCAA preceded by an Interplanetary Coronal Mass Ejection (ICME) storm recovery phase, HILDCAA preceded by a Corotating Interaction Region (CIR) storm recovery phase, and non‐storm driven HILDCAA and geomagnetically quiet periods were investigated using the Auroral Electrojet index time series. Neural Network Entropy (NNetEn) was used to capture the dynamical complexity transitions during these sporadic events. The NNetEn was able to decipher the distinct dynamical features associated with the emergence of HILDCAA and the geomagnetically quiet periods. Our analysis revealed a high value of NNetEn during HILDCAA signifying that the complexity levels of the coupled solar wind‐magnetosphere‐ionosphere system for HILDCAA, driven by different interplanetary structures were high with no significance difference. Thus, indicating that during HILDCAA, the dynamical behavior of the underlying physical processes due to the energy deposition driven either by ICME, CIR or non‐storm HILDCAA remain the same. However, a deciphering feature of dynamical complexity between the geomagnetically quiet period and HILDCAA events was evident. It was noticed that as the HILDCAA emerges, the NNetEn depicts an increment in entropy value signifying that the complexity levels of the coupled solar wind‐magnetosphere‐ionosphere system increases, and as the dynamics transcend to its recovery state, a reduction in entropy was observed implying a decline in complexity levels. Low values of NNetEn revealing lower complexity levels are found to be associated with geomagnetically quiet periods.

Perturbations from thunderstorms can play a notable role in the dynamics of the ionosphere. In this work, ionospheric perturbation effects due to thunderstorms were extracted and studied. Thunderstorm-associated lightning activities and their locations were detected by the World-Wide Lightning Location Network (WWLLN). The mechanical components of ionospheric perturbations due to thunderstorms were extracted from the total electron content (TEC), which was measured at selected thunderstorm locations using the polynomial filtering method. Further analyses were conducted using wavelet analysis and Discrete Fourier Transform (DFT) to study the frequency modes and periodicities of TEC deviation. It was revealed that the highest magnitudes of TEC deviations could reach up to ~2.2 TECUs, with dominant modes of frequency in the range of ~0.2 mHz to ~1.2 mHz, falling within the gravity wave range and the second dominant mode in the acoustic range of >1 mHz to <7.5 mHz. Additionally, a 20–60 min time delay was observed between the sprite events, the other high-energy electrical discharges, and the time of occurrence at the highest peak of acoustic-gravity wave perturbations extracted from TEC deviations. The possible mechanism responsible for this phenomenon is further proposed and discussed.

A thunderstorm tracking algorithm is proposed to nowcast the possibility of lightning activity over an area of concern by using the total lightning data and neighborhood technique. The lightning radiation sources observed from the Beijing Lightning Network (BLNET) were used to obtain information about the thunderstorm cells, which are significantly valuable in real-time. The boundaries of thunderstorm cells were obtained through the neighborhood technique. After smoothing, these boundaries were used to track the movement of thunderstorms and then extrapolated to nowcast the lightning approaching in an area of concern. The algorithm can deliver creditable results prior to a thunderstorm arriving at the area of concern, with accuracies of 63%, 80%, and 91% for lead times of 30, 15, and 5 minutes, respectively. The realtime observations of total lightning appear to be significant for thunderstorm tracking and lightning nowcasting, as total lightning tracking could help to fill the observational gaps in radar reflectivity due to the attenuation by hills or other obstacles. The lightning data used in the algorithm performs well in tracking the active thunderstorm cells associated with lightning activities.

This paper examines the response of dynamical complexity in traveling ionospheric disturbances (TIDs) across Eastern Africa sector during major geomagnetic storms. Detrended total electron content derived from eight stations of Global Positioning System receivers across Eastern Africa was used to unveil the transient features of dynamical complexity response in TIDs. Neural network entropy (NNetEn) was applied to the detrended TEC time series data to capture the degree of dynamical complexity. The NNetEn track the distinct features associated with the occurrence of TIDs. The results show that as the signatures of TIDs begin to emerge, low values of NNetEn signifying reduction in the degree of dynamical complexity response were observed while high values of NNetEn were depicted as the signatures of TIDs subsides signifying increase in the dynamical complexity response. Reduction in dynamical complexity response associated with the occurrence of TIDs is more evident in the Southern Hemisphere compared to Northern Hemisphere. Furthermore, we found that the propagation of TIDs is more prominent at Equinoctial season compared to solstitial season. The latitudinal observation of NNetEn revealed higher degree of dynamical complexity response in ADIS and NEGE signifying that the development of TIDs is minimal in ADIS and NEGE. Finally, the reduction in dynamical complexity associated with the occurrence of TIDs were obvious during all the phases of geomagnetic storms. In particular, the dynamical complexity response at initial and recovery phases of geomagnetic storm depicts more TIDs features.

In this work, the variations in the dynamical complexities in soil temperature variations were compared with that of air temperature using measured temperature parameters from different stations located in Nigeria. These parameters were also compared to the monthly averages of rainfall. The data sets were analysed using nonlinear time series analytical techniques. The results reveal that the annual trend of dynamical complexity follows a reverse trend of the rainfall peak period and the Lyapunov exponent for the un-detrended air temperature time series does not follow the same annual trend as that of the soil temperature. Also, dynamical properties of the two parameters are highly associated with correlation coefficients that are in some cases as high as 0.85 especially for the entropy measure for both air and soil. It was observed, however, that the degree of correlations between these parameters varies with time and location. An observed graduated response of Tsallis entropy computed for detrended soil temperature revealed a steady increase of the values of Tsallis entropy from north to south of Nigeria across the geographical belts. The observed variations have been associated with varying atmospheric factors and the changes in the properties of the soil with location. These factors might be influential in conjunction with other factors in the air-soil interface.

The complexities in the variations of soil temperature and thermal diffusion poses a physical problem that requires more understanding. The quest for a better understanding of the complexities of soil temperature variation has prompted the study of the q-statistics in the soil temperature variation with the view of understanding the underlying dynamics of the temperature variation and thermal diffusivity of the soil. In this work, the values of Tsallis stationary state q index known as q-stat were computed from soil temperature measured at different stations in Nigeria. The intrinsic variations of the soil temperature were derived from the soil temperature time series by detrending method to extract the influences of other types of variations from the atmosphere. The detrended soil temperature data sets were further analysed to fit the q-Gaussian model. Our results show that our datasets fit into the Tsallis Gaussian distributions with lower values of q-stat during rainy season and around the wet soil regions of Nigeria and the values of q-stat obtained for monthly data sets were mostly in the range 1.2≤q≤2.9 for all stations, with very few values q closer to 1.2 for a few stations in the wet season. The distributions obtained from the detrended soil temperature data were mostly found to belong to the class of asymmetric q-Gaussians. The ability of the soil temperature data sets to fit into q-Gaussians might be due and the non-extensive statistical nature of the system and (or) consequently due to the presence of superstatistics. The possible mechanisms responsible this behaviour was further discussed.

The equatorial Congo has been recognized as the most active lightning chimney region in the Globe. Although the perturbation of tropospheric thunderstorms on the lower ionosphere has been noticed in the middle latitudes through their transient lightning electric fields or convective gravity waves, the effects on equatorial ionosphere and the horizontal extent of this perturbation remains a mystery because of the difficulties in extracting the effects due to the sporadic nature of the equatorial ionosphere. Here we present observational results showing solid evidence of deviations in ionospheric total electron content (TEC) and its direction of propagation associated with thunderstorms using the method of polynomial filtering, by utilizing the TEC measured from equatorial Global Positioning System (GPS) Receiver stations along the West African region-Congo Basin. The TEC deviations due to the thunderstorms were found to be mostly propagated in a specific direction from the point of the event, with the highest absolute peak TEC at ~±1.5 TECUs. The internal dynamics of the equatorial ionosphere have been found to be suppressed by large thunderstorm effects during the daytime, with negligible impact at night.

Understanding the hidden dynamics of the atmosphere and its effect on radio wave propagation is paramount. Therefore proper characterization of atmospheric dynamics especially for its annual and seasonal variation is necessary. In this paper, atmospheric weather parameters (pressure, relative humidity and temperature), were used to obtain the radio refractivity at the surface N, level, at 100 m height, N,00 and the differential radio refractivity dN/dH. The extracted radio refractivity, parameters were characterized based on chaoticity and dynamical complexity, for Akure meteorological station (7 degrees 15'9.22 '' N, 5 degrees 11'35.23 '' E). The data analysis has been based on the Combined application of Largest Lyapunov Exponent and Tsallis Entropy (CLLETE). The data sets for the year 2011 and 2012 have been used for the computation. It was observed that the CLLETE parameters follow similar trend in most cases, and the Lyapunov exponent is generally positive indicating the presence of chaos for all radio refractivity data sets. It was further revealed that the pattern of the dynamical complexity variations in 2012 follow a similar trend from July to December for N-100 and dN/dH with the values of the dynamical complexity parameters computed for N-s having a huge departure from the other two heights with lower complexity values. However, the dynamical complexity parameters computed for N-s and N-100 a have similar a trend from the beginning of the year to June. The values of the Chaos and complexity parameters also show a similar variation in 2011 with N-s following the same trend between July and December. This indicates the dynamical response of radio refractivity to varying weather conditions. (C) 2018 COSPAR. Published by Elsevier Ltd. All rights reserved.

In this paper, the Tsallis non-extensive q-statistics in ionospheric dynamics was investigated using the total electron content (TEC) obtained from two Global Positioning System (GPS) receiver stations. This investigation was carried out considering the geomagnetically quiet and storm periods. The micro density variation of the ionospheric total electron content was extracted from the TEC data by method of detrending. The detrended total electron content, which represent the variation in the internal dynamics of the system was further analyzed using for non-extensive statistical mechanics using the q-Gaussian methods. Our results reveals that for all the analyzed data sets the Tsallis Gaussian probability distribution ( q -Gaussian) with value q > 1 were obtained. It was observed that there is no distinct difference in pattern between the values of q q u i e t and q s t o r m . However the values of q varies with geophysical conditions and possibly with local dynamics for the two stations. Also observed are the asymmetric pattern of the q-Gaussian and a highly significant level of correlation for the q-index values obtained for the storm periods compared to the quiet periods between the two GPS receiver stations where the TEC was measured. The factors responsible for this variation can be mostly attributed to the varying mechanisms resulting in the self-reorganization of the system dynamics during the storm periods. The result shows the existence of long range correlation for both quiet and storm periods for the two stations.

In this study, the values of chaoticity and dynamical complexity parameters for some selected storm periods in the year 2011 and 2012 have been computed. This was done using detrended TEC data sets measured from Birnin-Kebbi, Torro and Enugu global positioning system (GPS) receiver stations in Nigeria. It was observed that the significance of difference (SD) values were mostly greater than 1.96 but surprisingly lower than 1.96 in September 29, 2011. The values of the computed SD were also found to be reduced in most cases just after the geomagnetic storm with immediate recovery a day after the main phase of the storm while the values of Lyapunov exponent and Tsallis entropy remains reduced due to the influence of geomagnetic storms. It was also observed that the value of Lyapunov exponent and Tsallis entropy reveals similar variation pattern during storm period in most cases. Also recorded surprisingly were lower values of these dynamical quantifiers during the solar flare event of August 8th and 9th of the year 2011. The possible mechanisms responsible for these observations were further discussed in this work. However, our observations show that the ionospheric effects of some other possible transient events other than geomagnetic storms can also be revealed by the variation of chaoticity and dynamical complexity.

A. B. Rabiu 1,2 , B. O. Ogunsua 1 , I. A. Fuwape 1 and J. A. Laoye 3 21 [1] {Space Physics Laboratory, Department of Physics, Federal University of Technology, 22 Akure, Ondo State, Nigeria} 23 [2]{Centre for Atmospheric Research, National Space Research and Development Agency, 24 Anyigba, Kogi State Nigeria} 25 [3] {Department of Physics, Olabisi Onabanjo University, Ago-Iwoye, Ogun State, Nigeria} 26 27 Correspondence to: B. O. Ogunsua (iobogunsua@futa.edu.ng) 28 29 30 31 Formatted: Indent: Left: 0" Formatted: Numbering: Continuous

The quest to find an index for proper characterization and description of the dynamical response of the ionosphere to external influences and its various internal irregularities has led to the study of the day-to-day variations of the chaoticity and dynamical complexity of the ionosphere. This study was conducted using Global Positioning System (GPS) total electron content (TEC) time series, measured in the year 2011, from five GPS receiver stations in Nigeria, which lies within the equatorial ionization anomaly region. The non-linear aspects of the TEC time series were obtained by detrending the data. The detrended TEC time series were subjected to various analyses to obtain the phase space reconstruction and to compute the chaotic quantifiers, which are Lyapunov exponents LE, correlation dimension, and Tsallis entropy, for the study of dynamical complexity. Considering all the days of the year, the daily/transient variations show no definite pattern for each month, but day-to-day values of Lyapunov exponents for the entire year show a wavelike semiannual variation pattern with lower values around March, April, September and October. This can be seen from the correlation dimension with values between 2.7 and 3.2, with lower values occurring mostly during storm periods, demonstrating a phase transition from higher dimension during the quiet periods to lower dimension during storms for most of the stations. The values of Tsallis entropy show a similar variation pattern to that of the Lyapunov exponent, with both quantifiers correlating within the range of 0.79 to 0.82. These results show that both quantifiers can be further used together as indices in the study of the variations of the dynamical complexity of the ionosphere. The presence of chaos and high variations in the dynamical complexity, even in quiet periods in the ionosphere, may be due to the internal dynamics and inherent irregularities of the ionosphere which exhibit non-linear properties. However, this inherent dynamics may be complicated by external factors like geomagnetic storms. This may be the main reason for the drop in the values of the Lyapunov exponent and Tsallis entropy during storms. The dynamical behaviour of the ionosphere throughout the year, as described by these quantifiers, was discussed in this work.

A. B. Rabiu 1,2 , B. O. Ogunsua 1 , I. A. Fuwape 1 and J. A. Laoye 3 3 [1] {Space Physics Laboratory, Department of Physics, Federal University of Technology, 4 Akure, Ondo State, Nigeria} 5 [2]{Centre for Atmospheric Research, National Space Research and Development Agency, 6 Anyigba, Kogi State Nigeria} 7 [3] {Department of Physics, Olabisi Onabanjo University, Ago-Iwoye, Ogun State, Nigeria} 8 9 Correspondence to: B. O. Ogunsua (iobogunsua@futa.edu.ng) 10 11 Abstract 12

The deterministic chaotic behavior and dynamical complexity of the space plasma dynamical system over Nigeria are analyzed in this study and characterized. The study was carried out using GPS (Global Positioning System) TEC (Total Electron Content) time series, measured in the year 2011 at three GPS receiver stations within Nigeria, which lies within the equatorial ionization anomaly region. The TEC time series for the five quietest and five most disturbed days of each month of the year were selected for the study. The nonlinear aspect of the TEC time series was obtained by detrending the data. The detrended TEC time series were subjected to various analyses for phase space reconstruction and to obtain the values of chaotic quantifiers like Lyapunov exponents, correlation dimension and also Tsallis entropy for the measurement of dynamical complexity. The observations made show positive Lyapunov exponents (LE) for both quiet and disturbed days, which indicates chaoticity, and for different days the chaoticity of the ionosphere exhibits no definite pattern for either quiet or disturbed days. However, values of LE were lower for the storm period compared with its nearest relative quiet periods for all the stations. The monthly averages of LE and entropy also show no definite pattern for the month of the year. The values of the correlation dimension computed range from 2.8 to 3.5, with the lowest values recorded at the storm period of October 2011. The surrogate data test shows a significance of difference greater than 2 for all the quantifiers. The entropy values remain relatively close, with slight changes in these values during storm periods. The values of Tsallis entropy show similar variation patterns to those of Lyapunov exponents, with a lot of agreement in their comparison, with all computed values of Lyapunov exponents correlating with values of Tsallis entropy within the range of 0.79 to 0.81. These results show that both quantifiers can be used together as indices in the study of the variation of the dynamical complexity of the ionosphere. The results also show a strong play between determinism and stochasticity. The behavior of the ionosphere during these storm and quiet periods for the seasons of the year are discussed based on the results obtained from the chaotic quantifiers.

The measurement of magnetic variations within the low frequency range of 0.1 to 40Hz requires a highly sensitive magnetometer. A magnetometer based on the induction coil principle was designed, simulated, and constructed in this research. The search coil was designed by winding 4,500 turns of insulated coil on PVC pipe with 3 silicon–Iron strips mounted on the PVC for higher magnetic susceptibility. The sensory method of the coil is based on the faraday’s law of electromagnetic induction. The output of the coil was amplified and filtered with a band pass electronic system designed to pass the desired frequency range of 0.1 to 40Hz. A simple calibration system using the Helmoltz coil pair was designed for the calibration of the sensor to determine the conversion factor of the output root mean square (r.m.s.) voltage with the external magnetic field (Hs), since the Helmoltz coil can generate very uniform magnetic field up to 25% or more of the covered area from the centre axis. The output voltage and applied magnetic field obtained as the calibration data were fitted into a linear graph`. A relatively high sensitivity of 299mv/µT was obtained.