In this paper, we present the variations of IMF-Bz, Solar wind Parameters (Vsw, Nsw, and Psw), and Geomagnetic Indices (AE and SYM-H), and the variation of Vertical Total Electron Content (VTEC) using simultaneous VTEC data from 12 GPS-TEC stations over the Indian, Australian, Brazilian and South African regions. We describe contrast in Total Electron Content (TEC) throughout the globe using global ionospheric maps at regular 2-hour interval of UT during the three intense geomagnetic storms. Moreover, we observed that heavily TEC influenced areas were found to be transposing through equatorial plane starting from eastern sectors to the western sectors. Indian Ocean, Atlantic Ocean and South Pacific Ocean sectors were affected flowingly. Global Ionospheric Maps evince that Indian and Brazilian sectors were affected heavily explaining the TID and Equatorial Anomaly as seen on those areas. The equatorial and low-latitude regions have been mainly affected by the geomagnetic storms. All these results suggested that the acute disruption of global winds (surging towards the equator from higher latitudes) and electric fields commenced from magnetosphere-ionosphere interaction cause the severe modification in the equatorial, low-latitude region. We checked the cross correlation during the period of high solar and geomagnetic activities; the correlation gradually increased with the near by stations by latitudes in most of the cases which was another intriguing result. the storms were affected globally which is why we believe that variation of TEC over various stations of the globe could turn out to be very helpful in predicting solar wind coupling with magnetosphere-ionospehere.

Ionospheric total electron content (TEC) variations prior and after to the great Gorkha Earthquake in Nepal (Mw = 7.8) on April 25, 2015, were analysed using measurements from widely distributed Global Positioning System (GPS) network. This study has been performed to understand the relationship between ionospheric TEC anomalies and earthquake occurrences. The analysis of vertical TEC (VTEC) time series from different GPS stations shows that the abnormal TEC variations appeared few days up to a few hours before the events. The results indicate that deviation in VTEC observed on the distant GPS station from the epicentre was found less relative to that of the stations near the epicentre, inferring that the variation in ionospheric VTEC nearly inversely relies upon the distance of GPS stations from the epicentre. Moreover, the pre-earthquake ionospheric anomalies were also observed in the geomagnetically conjugated region. In view of the solar-terrestrial environment, the pre-earthquake ionospheric anomalies could be associated with the Nepal earthquake. The VTEC anomaly was identified when it crosses the upper bound or lower bound. The outcomes additionally show that TEC variation was dominant in the vicinity of the earthquake epicentre. We also describe contrast in TEC throughout the globe using global ionospheric maps at regular 2-hour UT intervals, the day before, during and after the earthquake. In addition, we observed that areas heavily influenced by TEC were found to be transposed from eastern sectors to western sectors through the equatorial plane.

In this paper, we study the variations of the solar-wind parameters (solar wind velocity, plasma density, and IMF-Bz component) and the Earth’s disturbance storm-time index (Dst), in relation to cosmic ray flux measurements from 8 neutron monitor stations distributed over Canada, Russia, Finland, and Greenland, during 3 intense geomagnetic storms occurred during the 24th solar cycle (March 16-18, 2015, June 21-23, 2015, and September 7-9, 2017). The wavelet analysis of the Forbush decrease seen in the cosmic ray intensity reveals the clear evolution of the classical two-step process, and with a peak period of approximately 2.1 h. The correlation-delay analyses show a very strong correlation (~0.9) between the relative count rate changes cosmic ray intensity and the indices of solar wind velocity and Dst. We obtain similar time-delay responses to the solar wind velocity for all the cases (~4 hours), but large discrepancies are seen for the Dst index between the storms. We therefore recommend not using the Dst index for predicting Forbush decreases. Finally, we employ the resulting delay-times to parameterize the Forbush decreases in terms of solar wind, and we obtain a predictive model with R2 parameter of an approximate value of 0.8. Moreover, we observe a possible dependence on solar wind proton density which modulates the magnitude of Forbush decreases under similar solar wind velocity conditions. Our results verify the suitability of using solar wind parameters to predict Forbush decreases in the cosmic ray flux.

Invasion of solar wind particles inside earth’s magnetosphere induces the distortion of geomagnetic setting of earth. This geomagnetic disturbances be a consequence of energy discharge of solar plasma in different forms such as visible aurora in the polar region, joule heating, ring current energy; momentary fluctuation of earth’s magnetic field (SYM-H), intensification of magnetospheric current system; Field Aligned Current (FAC) and Polar Cap Potential (PCV) and many other phenomena. However, this event can cause some serious calamites, so having better understanding of it and able to be prepared in any severity of such situations is always in good accord. For this, we studied total of nine different intense geomagnetic storms from solar cycle 22, 23 and 24. Events included from solar cycle 22 and 24 were triggered by Stream Interaction Region (SIR) as well as SIR associated with complex structures which were a resultant of interactions between SIRs and Interplanetary Coronal Mass Ejections (ICMEs) respectively. The rest of the selected events which are all from solar cycle 23 were also the responses of solar structures like SIR and ICME along with sheath and magnetic cloud. To understand the impact of the solar wind particles on near earth space, magnetospheric and interplanetary parameters such as IMF-Bz, SYM-H, PCV and FAC are graphed along with total solar input energy and other energy sinks like auroral precipitation, joule heating, and ring current energy. To substantiate result, cross‐correlation technique is used along with pie chart and bar graphing which has helped in statistical investigation.