Search

Temporal oscillations in the IMF Bz associated with Alfvén waves occur frequently in solar wind, with a duration ranging from minutes to hours. Using Swarm observations, Fabry–Pérot interferometer measurements at Mohe station, and Thermosphere–Ionosphere–Electrodynamic General Circulation Model simulations, the perturbations of zonal (ΔUN) and meridional (ΔVN) winds due to temporal oscillations in the IMF Bz on 23–24 April 2023 are explored in the following work. ΔUN is strong westward with a speed of greater than 100 m/s at pre-midnight on 23–24 April. This phenomenon is primarily driven by the pressure gradient, offsetting by the ion drag and Coriolis force. On 23 April, ΔVN is weak northward at the pre-midnight and strong southward at a speed of ~200 m/s at pre-dawn. On 24 April, ΔVN is strong (weak) northward at pre-midnight (pre-dawn). It is mainly controlled by a balance between the pressure gradient, ion drag, and Coriolis force. [ABSTRACT FROM AUTHOR]

Space plasma turbulence plays a relevant role in several plasma environments, such as solar wind and the Earth's magnetosphere–ionosphere system, and is essential for describing their complex coupling. This interaction gives rise to various phenomena, including ionospheric irregularities and the amplification of magnetospheric and ionospheric currents. The structure and dynamics of these currents have relevant implications, for example, in studying ionospheric heating and the nature of electric and magnetic field fluctuations in the auroral and polar environments. In this study, we investigate the nature of small-scale fluctuations characterizing the ionospheric magnetic field in response to different geomagnetic conditions. We use high-resolution (50 Hz) magnetic data from the ESA's Swarm mission, collected during a series of high-latitude crossings, to probe the scaling features of magnetic field fluctuations in auroral and polar cap regions at spatial scales still poorly explored. Our findings reveal that magnetic field fluctuations in field-aligned currents (FACs) and polar cap regions across both hemispheres are characterized by different scaling properties, suggesting a distinct driver of turbulence. Furthermore, we find that geomagnetic activity significantly influences the nature of energy dissipation in FAC regions, leading to more localized filamentary structures toward smaller scales. [ABSTRACT FROM AUTHOR]

Atmospheric drag stands out as the predominant non-gravitational force acting on satellites in Low Earth Orbit (LEO), with altitudes below 2000 km. This drag exhibits a strong dependence on the thermospheric mass density (TMD), a parameter of vital significance in the realms of orbit determination, prediction, collision avoidance, and re-entry forecasting. A multitude of empirical TMD models have been developed, incorporating contemporary data sources, including TMD measurements obtained through onboard accelerometers on LEO satellites. This paper delves into three different TMD modelling techniques, specifically, Fourier series, spherical harmonics, and artificial neural networks (ANNs), during periods of geomagnetic quiescence. The TMD data utilised for modelling and evaluation are derived from three distinct LEO satellites: GOCE (at an altitude of approximately 250 km), CHAMP (around 400 km), and GRACE (around 500 km), spanning the years 2002 to 2013. The consistent utilisation of these TMD data sets allows for a clear performance assessment of the different modelling approaches. Subsequent research will shift its focus to TMD modelling during geomagnetic disturbances, while the present work can serve as a foundation for disentangling TMD variations stemming from geomagnetic activity. Furthermore, this study undertakes precise TMD modelling during geomagnetic quiescence using data obtained from the GRACE (at an altitude of approximately 500 km), CHAMP (around 400 km), and GOCE (roughly 250 km) satellites, covering the period from 2002 to 2013. It employs three distinct methods, namely Fourier analysis, spherical harmonics (SH) analysis, and the artificial neural network (ANN) technique, which are subsequently compared to identify the most suitable methodology for TMD modelling. Additionally, various combinations of time and coordinate representations are scrutinised within the context of TMD modelling. Our results show that the precision of low-order Fourier-based models can be enhanced by up to 10 % through the utilisation of geocentric solar magnetic coordinates. Both the Fourier- and SH-based models exhibit limitations in approximating the vertical gradient of TMD. Conversely, the ANN-based model possesses the capacity to capture vertical TMD variability without manifesting sensitivity to variations in time and coordinate inputs. [ABSTRACT FROM AUTHOR]