On the Variation of Column Density Ratio Sigma O/N-2 in the Upper Atmosphere Using Principal Component Analysis in 2-Dimensional Images

The variability of the thermosphere on a daily basis is influenced by a variety of factors, including solar, geomagnetic, and meteorological drivers. The column density ratio of atomic oxygen to molecular nitrogen (Sigma O/N-2) is a useful parameter for quantifying this variability, and has been shown to closely correspond to F-region electron density, total electron content, and upper atmospheric transport. Despite the significance of the Sigma O/N-2, the relative contributions of these drivers to thermospheric variability are not well understood. In order to shed light on this issue, principal component analysis was performed in this study to distinguish and rank the various sources of variability in the Sigma O/N-2. The analysis was based on the Sigma O/N-2 data from the Global-scale Observations of the Limb and Disk mission from days 81-135 of 2020. The resulting two-dimensional eigen spatial patterns reveal the dominant variabilities during the specified period. The first six principal components are reported and associated with the major drivers through their spatial and temporal features. Geomagnetic storms, interhemispheric transport, atmospheric tides, and planetary waves were identified as the drivers of the first, second, third, and fifth components, respectively. The order of these components highlights that geomagnetic activity is the dominant source of daily variability in the Sigma O/N-2, followed by interhemispheric transport and meteorological drivers from the lower atmosphere. Plain Language Summary Day-to-day variability in the ionosphere and thermosphere is driven by changes in solar radiation, the solar wind, and by meteorological forcing from the lower atmosphere. The thermospheric Sigma O/N-2 responds to changes in thermospheric circulation and vertical transport, which are modified by the aforementioned drivers. We use principal component analysis, the same algorithm used in facial recognition technology, to identify the day-to-day variability of the thermospheric Sigma O/N-2 from NASA's Global-scale Observations of the Limb and Disk mission. With this powerful open-source tool, we identify the characteristic spatial variations of Sigma O/N-2. Our study reveals a strong response to a geomagnetic storm and a smaller response to a quasi 6-day atmospheric wave, demonstrating the relative importance of geomagnetic effects compared to planetary scale waves, present in components 1 and 5, respectively.