Journal of Space Weather and Space Climate (Jan 2024)

Statistical models of the variability of plasma in the topside ionosphere: 2. Performance assessment

  • Spogli Luca,
  • Jin Yaqi,
  • Urbář Jaroslav,
  • Wood Alan G.,
  • Donegan-Lawley Elizabeth E.,
  • Clausen Lasse B.N.,
  • Shahtahmassebi Golnaz,
  • Alfonsi Lucilla,
  • Rawlings James T.,
  • Cicone Antonio,
  • Kotova Daria,
  • Cesaroni Claudio,
  • Høeg Per,
  • Dorrian Gareth D.,
  • Nugent Luke D.,
  • Elvidge Sean,
  • Themens David R.,
  • Aragón María José Brazal,
  • Wojtkiewicz Pawel,
  • Miloch Wojciech J.

DOI
https://doi.org/10.1051/swsc/2024003
Journal volume & issue
Vol. 14
p. 4

Abstract

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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).

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