Seasonal and Interhemispheric Effects on the Diurnal Evolution of EIA: Assessed by IGS TEC and IRI-2016 over Peruvian and Indian Sectors

Abstract

The global total electron content (TEC) map in 2013, retrieved from the International Global Navigation Satellite Systems (GNSS) Service (IGS), and the International Reference Ionosphere (IRI-2016) model are used to monitor the diurnal evolution of the equatorial ionization anomaly (EIA). The statistics are conducted during geomagnetic quiet periods in the Peruvian and Indian sectors, where the equatorial electrojet (EEJ) data and reliable TEC are available. The EEJ is used as a proxy to determine whether the EIA structure is fully developed. Most of the previous studies focused on the period in which the EIA is well developed, while the period before EIA emergence is usually neglected. To characterize dynamics accounting for the full development of EIA, we defined and statistically analyzed the onset, first emergence, and the peaks of the northern crest and southern crest based on the proposed crest-to-trough difference (CTD) profiles. These time points extracted from IGS TEC show typical annual cycles in the Indian sector which can be summarized as winter hemispheric priority, i.e., the development of EIA in the winter hemisphere is ahead of that in the summer hemisphere. However, these same time points show abnormal semiannual cycles in the Peruvian sector, that is, EIA develops earlier during two equinoxes/solstices in the northern/southern hemisphere. We suggest that the onset of EIA is a consequence of the equilibrium between sunlight ionization and ambipolar diffusion. However, the latter term is not considered in modeling the topside ionosphere in IRI-2016, which results in a poor capacity in IRI to describe the diurnal evolution of EIA. Meridional neutral wind’s modulation on the ambipolar diffusion can explain the annual cycle observed in the Indian sector, while the semiannual variation seen in the Peruvian sector might be due to additional competing effects induced by the F region height changes.

Interhemispheric Asymmetry of the Equatorial Ionization Anomaly (EIA) on the African Sector Over 3 Years (2014–2016): Effects of Thermospheric Meridional Winds

“…It constitutes one of the primary goals of the ICON satellite (Immel et al., 2018), which aims to explore the interconnection between the Earth weather and the space’s one. The transequatorial wind is a good candidate explaining the highest electron density in the Northern (Southern) Hemisphere during December solstice (June solstice); it blows from the summer hemisphere to the winter hemisphere, which pushes the plasma equatorward and poleward along the field line (referred to as pile‐up effects [Wan et al., 2022]) in the summer and winter hemispheres, respectively. These neutral wind effects contradict/favor the ambipolar diffusion in the summer/winter hemisphere; hence, the development of EIA crest in the summer/winter hemisphere is inhibited/promoted, resulting in that the time points of EIA’s development show clear winter hemispheric priority.…”

Pronounced Suppression and X‐Pattern Merging of Equatorial Ionization Anomalies After the 2022 Tonga Volcano Eruption

“…It is generally explained by the “fountain effect” in terms of drift and diffusion: an eastward daytime dynamo electric field around the magnetic equator lifts the ionospheric plasma to higher altitudes via upward E × B drifts; subsequently, increased gravitational and pressure gradient forces then lead to a poleward and downward plasma diffusion along magnetic field lines, causing concentrated density crests in the off‐equatorial region and a trough near the equator (e.g., Anderson, 1973 ; Balan & Bailey, 1995 ; Hanson & Moffett, 1966 ). EIA morphology and spatiotemporal characteristics, such as local time, longitude, altitude, interhemispheric asymmetry, and solar activity dependence, have been extensively studied using ionosonde observations (e.g., Jayachandran et al., 1997 ; Thomas, 1968 ), Global Navigation Satellite System Total Electron Content (GNSS TEC) data (e.g., Das et al., 2014 ; Wan et al., 2021 ; Zhao et al., 2009 ), radio occultation data (e.g., Huang et al., 2018 ; Lin et al., 2007 ; Luan et al., 2015 ; Tulasi Ram et al., 2009 ), satellite in‐situ measurements (e.g., Chen et al., 2016 ; Paul & Dasgupta, 2010 ; Xiong et al., 2013 ), remote sensing measurements (e.g., Basu et al., 2009 ; Cai et al., 2021 , 2020 ; Eastes et al., 2019 ; Kil et al., 2006 ), and numerical simulations (e.g., Dang et al., 2016 ; Lei et al., 2012 ; Su et al., 1997 ).…”

Investigation of the Physical Mechanisms of the Formation and Evolution of Equatorial Plasma Bubbles During a Moderate Storm on 17 September 2021

“…There have been a lot of studies on the north-south asymmetry of the EIA (e.g., Dang et al, 2016;Lin et al, 2007;L. Liu et al, 2007;Luan et al, 2015;Tulasi Ram et al, 2009;Wan et al, 2021;Xiong et al, 2013). Previous studies have shown that the north-south EIA asymmetry exhibits seasonal dependency.…”

“…In addition to these EPB characteristics, the north‐south asymmetry in the EIA shown in Figure 2 is also worth further discussion. There have been a lot of studies on the north‐south asymmetry of the EIA (e.g., Dang et al., 2016; Lin et al., 2007; L. Liu et al., 2007; Luan et al., 2015; Tulasi Ram et al., 2009; Wan et al., 2021; Xiong et al., 2013). Previous studies have shown that the north‐south EIA asymmetry exhibits seasonal dependency.…”