Plasma bubbles are regions of depleted plasma within the upper thermosphere/ionosphere that form during post-sunset hours near the magnetic equator. These structures tend to align with local geomagnetic field lines, extend upwards hundreds of kilometers along geomagnetic longitudes, and thousands of kilometers along geomagnetic latitudes. These large scale plasma density gradients can attenuate lower frequency radio waves, while small scale structures along the walls can interfere with centimeter scale wavelengths via Fresnel and Bragg scattering. Large scale statistical analysis of this phenomenon can further understanding of their occurrence and subsequent behavior. The current study utilizes Global-Scale Observations of the Limb and Disk (GOLD) 135.6 nm nightglow data from October 5, 2018 to September 30, 2022. GOLD has a unique perspective from geostationary orbit, allowing a constant and consistent view of nightglow and structures over the Americas and Atlantic. A plasma bubble detection method is developed and used to generate a database of plasma bubble occurrences. Occurrences are used to calculate plasma bubble drift speeds and separations. Clear seasonality in plasma bubble occurrence rate is evident. Overall occurrences peak during December solstice months and minimize during June solstice for longitudes seen by GOLD. Within GOLD’s field of view, higher occurrences are seen to the west during December solstice and east during June solstice. Plasma bubble drift speeds and separations show consistent distributions regardless of magnetic region, geographic region, season, or local time. This suggests plasma bubbles behave consistently and regularly once formed, at least on spatial scales seen by GOLD.

Divyam Goel

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Day-to-day variability in thermospheric composition is driven by solar, geomagnetic and meteorological drivers. The ratio of the column density of atomic oxygen and molecular nitrogen (O/N\textsubscript{2}) is a useful parameter for quantifying this variability that has been shown to exhibit close correspondence to F-region electron density, total electron content and upper atmospheric transport. Therefore, understanding the variability in O/N\textsubscript{2} gives an insight into the geophysical variability of other relevant ionospheric and thermospheric parameters. The relative contributions of these drivers for thermospheric variability is not well known. Here we report a new analysis of the variability in O/N\textsubscript{2} to identify the sources of variability in a 55-day time period. Principal Component Analysis (PCA) was performed on thermospheric O/N\textsubscript{2} column density ratio from days 81 to 135 of 2020 from NASA’s Global-scale Observations of the Limb and Disk (GOLD) mission. We find that geomagnetic activity is the major source of variability in O/N\textsubscript{2} column density ratio, followed by solar-driven transport and meteorological driving from the lower atmosphere. The first component (PC1) showed a strong correlation to Kp index and IMF, and geomagnetic storm effects are seen in the wavelet analysis of PC1’s weights. The fifth component (PC5) showed a strong quasi-6-day oscillation(Q6DO). The higher explained variance ratio of PC1 suggests a stronger effect of geomagnetic activity relative to meteorological forcing from planetary scale waves. The methodology of the present study also demonstrates how PCA can be used to isolate and rank different sources of variability in other IT parameters.
Prior investigations have attempted to characterize the longitudinal variability of the column number density ratio of atomic oxygen to molecular nitrogen (ΣO/N2) in the context of non-migrating tides. The retrieval of thermospheric ΣO/N2 from far ultra-violet (FUV) emissions assumes production is due to photoelectron impact excitation on O and N2. Consequently, efforts to characterize the tidal variability in O/N2 have been limited by ionospheric contamination from O+ radiative recombination at afternoon local times (LT) around the equatorial ionization anomaly. The retrieval of ΣO/N2 from FUV observations by the Ionospheric Connection Explorer (ICON) provides an opportunity to address this limitation. In this work, we derive modified ΣO/N2 datasets to delineate the response of thermospheric composition to non-migrating tides as a function of LT in the absence of ionospheric contamination. We assess estimates of the ionospheric contribution to 135.6 nm emission intensities based on either Global Ionospheric Specification (GIS) electron density, International Reference Ionosphere (IRI) model output, or observations from the Extreme Ultra-Violet imager (EUV) onboard ICON during March and September equinox conditions in 2020. Our approach accounts for any biases between the ionospheric and airglow datasets. We found that the ICON-FUV dataset, corrected for ionospheric contamination based on GIS, uncovered a previously obscured diurnal eastward wavenumber 2 tide in a longitudinal wavenumber 3 pattern at March equinox in 2020. This finding demonstrates not only the necessity of correcting for ionospheric contamination of the FUV signals but also the utility of using GIS for the correction.