Statistical analysis of the occurrence rate of geomagnetic storms during solar cycles 20–24

This study examines the occurrences rate of geomagnetic storms during the solar cycles (SCs) 20–24. It also investigates the solar sources at SCs 23 and 24. The Disturbed storm time (Dst) and Sunspot Number (SSN) data were used in the study. The study establishes that the magnitude of the rate of occurrences of geomagnetic storms is higher (lower) at the descending phases (minimum phases) of solar cycle. It as well reveals that severe and extreme geomagnetic storms (Dst < -250 nT) seldom occur at low solar activity but at very high solar activity and are mostly associated with coronal mass ejections (CMEs) when occurred. Storms caused by CME + CH-HSSW are more prominent during the descending phase than any other phase of the solar cycle. Solar minimum features more CH-HSSW- associated storms than any other phase. It was also revealed that all high intensity geomagnetic storms (strong, severe and extreme) are mostly associated with CMEs. However, CH-HSSW can occasionally generate strong storms during solar minimum. The results have proven that CMEs are the leading cause of geomagnetic storms at the ascending, maximum and the descending phases of the cycles 23 and 24 followed by CME + CH-HSSW. The results from this study indicate that the rate of occurrence of geomagnetic storms could be predicted in SC phases.     

Ionospheric storm due to solar Coronal mass ejection in September 2017 over the Brazilian and African longitudes

Coronal mass ejection (CME) occurs when there is an abrupt release of a large amount of solar plasma, and this cloud of plasma released by the Sun has an intrinsic magnetic field. In addition, CMEs often follow solar flares (SF). The CME cloud travels outward from the Sun to the interplanetary medium and eventually hits the Earth’s system. One of the most significant aspects of space weather is the ionospheric response due to SF or CME. The direction of the interplanetary magnetic field, solar wind speed, and the number of particles are relevant parameters of the CME when it hits the Earth’s system. A geomagnetic storm is most geo-efficient when the plasma cloud has an interplanetary magnetic field southward and it is accompanied by an increase in the solar wind speed and particle number density. We investigated the ionospheric response (F-region) in the Brazilian and African sectors during a geomagnetic storm event on September 07–10, 2017, using magnetometer and GPS-TEC networks data. Positive ionospheric disturbances are observed in the VTEC during the disturbed period (September 07–08, 2017) over the Brazilian and African sectors. Also, two latitudinal chains of GPS-TEC stations from the equatorial region to low latitudes in the East and West Brazilian sectors and another chain in the East African sector are used to investigate the storm time behavior of the equatorial ionization anomaly (EIA). We noted that the EIA was disturbed in the American and African sectors during the main phase of the geomagnetic storm. Also, the Brazilian sector was more disturbed than the African sector.     

Local empirical model of ionospheric variability

The paper presents an analysis of the ionospheric variability as a function of local time, month, and geomagnetic activity level. The 2003–2020 dataset of peak electron densities (NmF2) from the Irkutsk DPS-4 Digisonde (52.3°N, 104.3°E) was converted into the dataset of the NmF2 disturbances (ΔNmF2) representing the relative (percentage) deviations of the NmF2 from the 27-day running median. The ΔNmF2 dataset was used to calculate root mean square values of ΔNmF2 (σNmF2) by 27-day running averaging. These σNmF2 values were considered as a measure of ionospheric variability. The σNmF2 as function of local time, day of year, and year was the input for building the local empirical model of ionospheric variability based on the linear regression of σNmF2 on the 27-day average daily Ap-index of geomagnetic activity. The paper demonstrates the diurnal-seasonal variations in σNmF2 under low geomagnetic activity (linear regression intercept) as well as the rate of increase/decrease in σNmF2 with increasing Ap (linear regression slope). The obtained diurnal, seasonal, and geomagnetic activity behavior of σNmF2 is compared with previous studies of ionospheric variability.