We investigate the role of auroral particle precipitation in small-scale (below hundreds of meters) plasma structuring in the auroral ionosphere over the Arctic. To the scope, we together analyse data recorded by an Ionospheric Scintillation Monitor Receiver (ISMR) of Global Navigation Satellite System (GNSS) signals and by an All-Sky Camera located in Longyearbyen, Svalbard (Norway). We leverage on the raw GNSS samples provided at 50 Hz by the ISMR to evaluate amplitude and phase scintillation indices at 1 s time resolution and the Ionosphere-Free Linear Combination at 20 ms time resolution. The simultaneous use of the 1 s GNSS-based scintillation indices allows identifying the scale size of the irregularities involved in plasma structuring in the range of small (up to few hundreds of meters) and medium-scale size ranges (up to few kilometers) for GNSS frequencies and observational geometry. Additionally, they allow identifying the diffractive and refractive nature of the found fluctuations on the recorded GNSS signals. Six strong auroral events and their effects on plasma structuring are studied. Plasma structuring down to scales of hundreds of meters are seen when strong gradients in auroral emissions at 557.7 nm cross the line of sight between the GNSS satellite and receiver. Local magnetic field measurements confirm small-scale structuring processes coinciding with intensification of ionospheric currents. Since 557.7 nm emissions primarily originate from the ionospheric E-region, plasma instabilities from particle precipitation at E-region altitudes are considered to be responsible for the signatures of small-scale plasma structuring highlighted in the GNSS scintillation data.

Data assimilation (DA) techniques have recently gained traction in the ionospheric community, particularly at regional operational centers where more precise data are becoming prevalent. At centre stage is the argument over which technique or scheme merits realization. At 4DSpace, we have in-house developed and assessed the performance of two regional flavors of short-term forecast strong constraint four-dimensional (4D, space and time) variational (SC4DVar) DA schemes; the orthodox incremental (SC4DVar-Inc) and ensemble-based (SC4DEnVar) approach. SC4DVar-Inc is bottled-necked by expensive Tangent Linear Models (TLMs) and model Ad-joints (MAs), while SC4DEnVar design mitigates these limitations. Both schemes initialize from the same background (IRI-2016), and electron densities forward propagated (30-min) by a Gauss Markov filter- the densities take on a log-normal distribution to assert the mandatory ionosphere density positive definiteness. Preliminary assimilation is performed only with ubiquitous Global Navigation Satellite System observables from ground-based receivers, with a focus on moderately stable mid-latitudes, specifically the Japanese archipelago and neighboring areas. Using a simulation analysis, we find that under model space localization, 30 member Ensembles are sufficient for regional SC4DEnVar. Verification of reconstructions is with independent observations from ground-based ionosonde and satellite radio occultations: the performance of both schemes is fairly adequate during the quiet period when the background has a better estimation of the hmF2. SC4DVar-Inc is slightly better over areas densely populated with measurements, but SC4DEnVar estimates the overall 3D ionosphere picture better, particularly in remote areas and during severe conditions. These results warrant SC4DEnVar as a better candidate for precise short-time regional forecasts.

We develop a climatological model for the Northern Hemisphere based on a long-term dataset (2010-2021) of the rate of change of the total electron content (TEC) index (ROTI) maps from the International GNSS Service (IGS). The IGS ROTI maps are daily averaged in magnetic latitude and local time coordinates. To develop a climatological model, the ROTI maps are decomposed into a few base functions and coefficients using the empirical orthogonal function (EOF) method. The EOF method converges very quickly, and the first four EOFs reflect the majority (96%) of the total data variability. Furthermore, different EOF components can reflect different drivers of ionospheric irregularities. The first EOF reflects the averaged ROTI activity and the impact of the solar radiation and geomagnetic activity; the 2nd EOF reflects the impact of the interplanetary magnetic field (IMF) Bz and electric field; the 3rd and 4th EOFs reflect the dawn-dusk asymmetry around the auroral oval and polar cap, and they can be related to the IMF By. To build an empirical model, we fit the EOF coefficients using helio-geophysical indices from four different categories (solar activity; geomagnetic indices; IMF; the solar wind coupling function). The final EOF model is dependent on seven selected indices (F10.7P, Kp, Dst, Bt, By, Bz and Ekl). The statistical data-model comparisons show satisfactory results with a good correlation coefficient. However, the model cannot capture the significant expansion of the dayside ROTI activity during strong geomagnetic storms. Future effort is needed to provide corrections to the model for severe storms.

Auroral particle precipitation potentially plays a main role in ionospheric plasma structuring. The impact of auroral particle precipitation on plasma structuring is investigated using multi-point measurements from scintillation receivers and all sky cameras from Longyearbyen, Ny-Ålesund and Hornsund on Svalbard. This provides us with the unique possibility of studying the spatial and temporal dynamics of the aurora. Here we consider three case studies to investigate how plasma structuring is related to different auroral forms. We demonstrate that plasma structuring impacting the GNSS signals is largest at the edges of auroral forms. Here we studied two stable arcs, two dynamic auroral bands and a spiral. Specifically for arcs we find elevated phase scintillation indices at the pole-ward edge of the aurora. This is observed for auroral oxygen emissions (557.7 nm) at 150~km in the ionospheric E-region. This altitude is also used as the ionospheric piercing point for the GNSS signals as the observations remain the same regardless of different satellite elevations and azimuths. Further, there may be a time delay between the temporal evolution of aurora (f.e. commencement and fading of auroral activity) and observations of elevated phase scintillation indices. The time delay could be explained by the intense influx of particles, which increases the plasma density and causes recombination to carry on longer, which may lead to a persistence of structures - a ‘memory effect’. High values of phase scintillation indices can be observed even shortly after strong visible aurora and can then remain significant at low intensities of the aurora.