Statistical Models of the Variability of Plasma in the Topside Ionosphere:2. Performance assessment

Statistical models of the variability of plasma in the topside ionosphere based on the Swarm data have been developed in the “Swarm Variability of Ionospheric Plasma” (Swarm-VIP) project within the European Space Agency’s Swarm+4D-Ionosphere framework. The models can predict the electron density, its gradients for three horizontal spatial scales – 20, 50 and 100 km – along the North-South direction and the level of the density fluctuations. Despite being developed by leveraging on Swarm data, the models provide predictions that are independent of these data, having a global coverage, fed by various parameters and proxies of the helio-geophysical conditions. Those features make the Swarm-VIP models useful for various purposes, which include the possible support for already available ionospheric models and proxy of the effect of ionospheric irregularities of the medium scales that affect the signals emitted by Global Navigation Satellite Systems (GNSS). The formulation, optimisation and validation of the Swarm-VIP models are reported in Paper 1 (Wood et al. 2024. J Space Weather Space Clim. in press). This paper describes the performance assessment of the models, by addressing their capability to reproduce the known climatological variability of the modelled quantities, and the ionospheric weather as depicted by ground-based GNSS, as a proxy for the ionospheric effect on GNSS signals. Additionally, we demonstrate that, under certain conditions, the model can better reproduce the ionospheric variability than a physics-based model, namely the Thermosphere-Ionosphere-Electrodynamics General Circulation Model (TIE-GCM)

Statistical models of the variability of plasma in the topside ionosphere:1. Development and optimisation

This work presents statistical models of the variability of plasma in the topside ionosphere based on observations made by the European Space Agency’s (ESA) Swarm satellites. The models were developed in the “Swarm Variability of Ionospheric Plasma” (Swarm-VIP) project within the European Space Agency’s Swarm+4D-Ionosphere framework. The configuration of the Swarm satellites, their near-polar orbits and the data products developed, enable studies of the spatial variability of the ionosphere at multiple scale sizes. The statistical modelling technique of Generalised Linear Modelling (GLM) was used to create models of both the electron density and measures of the variability of the plasma structures at horizontal spatial scales between 20 km and 100 km. Despite being developed using the Swarm data, the models provide predictions that are independent of these data. Separate models were created for low, middle, auroral and polar latitudes. The models make predictions based on heliogeophysical variables, which act as proxies for the solar and geomagnetic processes. The first and most significant term in the majority of the models was a proxy for solar activity. The most common second term varied with the latitudinal region. This was the Solar Zenith Angle (SZA) in the polar region, a measure of latitude in the auroral region, solar time in the mid-latitude region and a measure of latitude in the equatorial region. Other, less significant terms in the models covered a range of proxies for the solar wind, geomagnetic activity and location. In this paper, the formulation, optimisation and evaluation of these models are discussed. The models show very little bias, with a mean error of zero to two decimal places in 14 out of 20 cases. The models capture some, but not all, of the trends present in the data, with Pearson correlation coefficients of up to 0.75 between the observations and the model predictions. The models also capture some, but not all, of the variability of the ionospheric plasma, as indicated by the precision, which ranged between 0.20 and 0.83. The addition of the thermospheric density as an explanatory variable in the models improved the precision in the polar and auroral regions. It is suggested that, if the thermosphere could be observed at a higher spatial resolution, then even more of the variability of the plasma structures could be captured by statistical models. The formulation and optimisation of the models are presented in this paper. The capability of the model in reproducing the expected climatological features of the topside ionosphere, in supporting GNSS-based ionospheric observations and the performance of the model against the Thermosphere-Ionosphere-Electrodynamics General Circulation Model (TIE-GCM), are provided in a companion paper (Spogli L et al. 2024. J Space Weather Space Clim https://doi.org/10.1051/swsc/2024003)