The dual‐frequency global positioning system (GPS) data acquired from the UNAVCO over different places of Nepal were processed to examine the eclipse‐triggered consequences on total electron content (TEC) in response to the annular solar eclipse of 15th January 2010 and 21st June 2020. These occasions were exceptional since they occurred during solar minimum, additionally as in a magnetically quiet period. The eclipse phase coincided with the peak ionization‐time at the equatorial and low latitude regions. The solar eclipse of 21^st June 2020 was an annular solar eclipse with a magnitude of 0.994. Nepal has witnessed a partial eclipse, starting at ∼10:53 NST (05:08 UT), reached the maximum at ∼12:40 NST (6:55 UT), and ended at ∼14:24 NST (8:39 UT) with the total duration of 3 h and 31 min. The annular solar eclipse of 15th January 2010 had the magnitude of 0.919 and Nepal has witnessed a partial eclipse starting at ∼12:24 NST (6:39 UT), reached the maximum at ∼14:10 NST (8:25 UT), and ended at ∼15:40 NST (9:55 UT). The eclipse effect occurs as a trough‐like depression in the curve of TEC at all the GPS stations indicates the effect of sudden attenuation of solar extreme ultra‐violet irradiation on decayed electron content in the ionosphere over the region. Moreover, the extent of the exhaustion in ionospheric TEC was studied by comparing the eclipse day TEC with mean diurnal ionospheric TEC of five quietest days of the month to investigate the eclipse effect on the electron density of the ionosphere over the stations. The study additionally reveals that the measure of the decrease in vertical value of total electron content is proportional to the obscuration of the lunar disc, that is closely associated with the electron production via the photoionization process. Observing the values of TEC during the eclipse day and comparing it with other quiet days, our study showed an apparent variation during the time of the eclipse, which agrees with previous studies on ionospheric responses to the eclipse as well as theoretical assumptions.

A dominant process by which energy and momentum are transported from the magnetosphere to the ionosphere is known as field‐aligned current (FAC). It is enhanced during magnetic reconnection and explosive energy release at a substorm. In this paper, we studied FAC, interplanetary electric field component (E_y), interplanetary magnetic field component (B_z), and northward (x) and eastward (y) components of geomagnetic field during three events of supersubstorm occurred on 24 November 2001, 21 January 2005, and 24 August 2005. Large‐scale FAC, supposed to be produced during supersubstorm (SSS), has potentiality to cause blackout on Earth. We examined temporal variations of the x and y components of high‐latitude geomagnetic field during SSS, which is attributed to the FACs. We shall report the characteristics of high‐latitude northward and eastward components of geomagnetic field variation during the growth phase of SSS by the implementation of discrete wavelet transform (DWT) and cross‐correlation analysis. Among three examples of SSS events, the highest peak value of FAC was estimated to be ~19 μAm⁻². This is shore up with the prediction made by Parks (1991) and Stasiewicz et al. (1998) that the FACs may vary from a few tens to several hundred μAm⁻². Although this peak value of FACs for SSS event is much higher than the average FACs associated with regular substorms or magnetic storms, it is expedient and can be expect for SSS events which might be due to very high density solar wind plasma parcels (PPs) triggering the SSS events. In all events, during growth phase, the FAC increases to extremely high level and the geomagnetic northward component decreases to extremely low level. This represents a strong positive correlation between FAC and geomagnetic northward component. The DWT analysis accounts that the highest amplitude of the wavelet coefficients indicates singularities present in FAC during SSS event. But the amplitude of squared wavelet coefficient is found to be different from each other, which might be due to the solar wind PPs of different density triggering the SSS events. The cross‐correlation analysis suggests that the perturbation on geomagnetic northward component at high latitude during SSS strongly correlates with the fluctuation pattern of FAC density. Hence, the FAC is the primary sources for the eastward‐westward magnetic field perturbations at high latitude.

Streams of the particle ejected from the Sun and the extreme space weather conditions like storms, high‐speed streamers (HSSs), interplanetary coronal mass ejections (ICMEs), corotating interaction regions (CIRs), and interplanetary shocks (IS) termed as geomagnetic storms have massive influence in the climate and components of the Earth's upper atmosphere such as total electron content (TEC). The study of TEC helps to understand variations in ionospheric electron density during geomagnetic storms. Global ionospheric maps of TEC are a real‐time mapping of GPS observations produced by ground‐based stations. In this paper, we have analyzed three intense geomagnetic storms of the year 2015: during 16–21 March 2015 (the St. Patrick's Day storm), 21–24 June 2015, and 18–22 December 2015. We present the variations of IMF‐Bz, solar wind parameters (Vsw, Nsw, and Psw), and geomagnetic indices (AE and SYM‐H) and the variations 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 TEC throughout the globe using global ionospheric maps at a regular 2 hr interval of UT during the three intense geomagnetic storms. Moreover, we observed that heavily TEC‐influenced areas were found to be transposing through the equatorial plane starting from eastern sectors to the western sectors. The 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 traveling ionospheric disturbances (TID) and equatorial anomaly as seen in those areas. The equatorial and low‐latitude regions have been mainly affected by geomagnetic storms. All these results suggested that the acute disruption of global winds (surging toward the equator from higher latitudes) and electric fields commenced from magnetosphere‐ionosphere interaction causing the severe modification in the equatorial, low‐latitude region. We also checked the cross correlation of VTEC of LCK3 station and various other stations during the period of high solar and geomagnetic activities; the correlation gradually increased with the nearby stations by latitudes in most of the cases which was another intriguing result. Thus, these results suggested that 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 the magnetosphere‐ionosphere.

The coupling process between solar wind-magnetosphere-ionosphere is an important physical 14 mechanism for the delineating concept of the magnetosphere-ionosphere system. In this work, we have studied the polar cap potential (PCV) and merging electric field (E_m) during three different supersubstorm (SSS) events. We have also studied the roles of polar cap index and auroral electrojet (AE) indices to observe polar cap activity during SSSs. To substantiate results, wavelet transform and cross-correlation techniques are used. We checked the cross correlation of PCV with AE, SYM-H, B_z, X, Y, and E_y individually. Positive good correlation of PCV with AE and SYM-H is obtained. Observing and obtaining these results, PCV shows the significant effects during geomagnetic activity (SSSs) generated by geoeffective solar wind parameters.

Polar cap potential (PCV) is an important parameter used for determining what kind of interaction takes place between solar wind and magnetosphere. Highly energetic particles from Sun driven by solar wind constantly bombard with Earth's magnetosphere–ionosphere system that results into a phenomenon like auroras, and major geomagnetic disturbances. Solar wind electron deposition determines the magnitude of field‐aligned current (FAC) and ultimately leads to PCV variation. Several studies found that increase in magnitude of IMF‐B_z causes an electric field of cross magnetosphere to increase, and it leads to increase in magnitude of ionospheric cross‐polar cap potential (PCV). Moreover, PCV was found to be a linear function of V_sw. In this research, we aim to study how field‐aligned current (FAC), for example, region 1 current and PCV, is related during different forms of geomagnetic disturbances. In all events, FAC and PCV are found to have corresponding fluctuations—especially at times of significant variation of IMF‐B_z (negative B_z interval) following the linearity of equation suggested by Moon in Moon (2012, https://doi.org/10.5140/JASS.2012.29.3.259). We found one‐to‐one correspondence between FAC and PCV. We did CWT analysis and found that FAC and PCV have more or less same spectral behaviors for each event considered. The cross‐correlation analysis shows a high and positive correlation between FAC and PCV at 0‐min time lag for all geomagnetic activity. The CWT analysis clearly supports the result of cross correlation between FAC and PCV. We found that FAC and V_sw, FAC‐B, and FAC and AE are also positively correlated with high‐correlation coefficient at lag 0 min for all geomagnetic storm. However, FAC‐B_z, FAC‐B_y, and FAC‐SYM (H) have varying correlation in different events. For a particular storm and substorm, the parameters B_z and B_y may not necessarily be varied with FAC in regular sequence but IMF (B) always show positive correlation with FAC for all geomagnetic activity. This paper presents a clear relation between FAC and PCV. This result will help to identify some of the outstanding issues in determining the causal mechanism of PCV variation, a crucial thing to understanding the coupling between the solar wind and M‐I system.

In this paper, we estimate the seismogenic energy during the Nepal Earthquake (25 April 2015) and studied the ground motion time-frequency characteristics in Kathmandu valley. The idea to analyze time-frequency characteristic of seismogenic energy signal is based on wavelet transform which we employed here. Wavelet transform has been used as a powerful signal analysis tools in various fields like compression, time-frequency analysis, earthquake parameter determination, climate studies, etc. This technique is particularly suitable for non-stationary signal. It is well recognized that the earthquake ground motion is a non-stationary random process. In order to characterize a non-stationary random process, it is required immeasurable samples in the mathematical sense. The wavelet transformation procedures that we follow here helps in random analyses of linear and non-linear structural systems, which are subjected to earthquake ground motion. The manners of seismic ground motion are characterized through wavelet coefficients associated to these signals. Both continuous wavelet transform (CWT) and discrete wavelet transform (DWT) techniques are applied to study ground motion in Kathmandu Valley in horizontal and vertical directions. These techniques help to point out the long-period ground motion with site response. We found that the long-period ground motions have enough power for structural damage. Comparing both the horizontal and the vertical motion, we observed that the most of the high amplitude signals are associated with the vertical motion: the high energy is released in that direction. It is found that the seismic energy is damped soon after the main event; however the period of damping is different. This can be seen on DWT curve where square wavelet coefficient is high at the time of aftershock and the value decrease with time. In other words, it is mostly associated with the arrival of Rayleigh waves. We concluded that long-period ground motions should be studied by earthquake engineers in order to avoid structural damage during the earthquake. Hence, by using wavelet technique we can specify the vulnerability of seismically active region and local topological features out there.