MODELING OF AURORAL ELECTROJET VARIATIONS DURING SOLAR MAXIMUM CONDITIONS

Abstract

Auroral electrojets (AEJs) represent critical current systems in the high-latitude ionosphere, directly influenced by solar wind–magnetosphere coupling. This study presents a quantitative model of AEJ variability during solar maximum conditions using a decade of data (2012–2022). Key solar wind drivers such as IMF Bz, dynamic pressure, and AE index were integrated into a neural network regression model to simulate electrojet intensities. Comparative analysis with satellite observations from AMPERE and SuperMAG data validated model performance. Results reveal peak intensification during substorms and high-speed stream impacts, with strong seasonal and magnetic local time dependencies. This work enhances understanding of auroral current dynamics and supports improved high-latitude space weather forecasting.