An Analysis of Unseasonal Equatorial Plasma Bubbles in July 2014

In the equatorial ionosphere, the Raleigh-Taylor (RT) plasma instability in the post sunset region is known to cause plasma depletions, known as equatorial plasma bubbles (EPBs). These EPBs can have adverse effects on satellite-reliant technologies by causing scintillations in the phase and amplitude of Global Navigation Satellite System (GNSS) signals. The effect of EPBs on satellite-reliant technologies highlights a need for reliable forecasting of EPBs in the low-latitude regions, which requires a solid understanding of their climatology and daily variability. The climatology of EPB occurrence is known to correlate with the angle between the magnetic field and solar terminator. This angle controls the longitudinal E-region conductivity gradient across the day-night terminator, which influences the strength of the pre-reversal enhancement in the upward plasma drift, a dominant term in the linear RT growth rate. This relationship is well established from ground-based GNSS and satellite-based studies. However, reliable forecasts have not been developed by space weather forecasting agencies due to the lack of understanding of EPB daily variability. During July, EPB occurrence is small in the South-East Asia longitude sector due to the relatively large angle between the magnetic field and solar terminator. As a result, the pre-reversal enhancement in the upward plasma drift is typically low during this period, creating less favourable conditions for EPB growth. However, despite the typically low pre-reversal enhancement strength, this analysis reveals that July 2014 is not devoid of EPB events above South-East Asia. These unseasonal EPB events during July 2014 are studied in the context of the prevalently low solar and geomagnetic activity conditions. Given the lack of solar and geomagnetic control, the influence of the lower atmosphere on EPB generation (e.g., via atmospheric gravity wave seeding) is explored. These events provide a unique opportunity to investigate the factors that affect the daily variability of EPBs, which will contribute towards the development of EPB prediction capabilities.