Understanding Earth's Ionospheric Cold Ion Outflow Using Machine Learning

报告人简介：Nicolas Doepke，he is a member of Elena Kronberg's Space Weather Research Group within the Magnetism Group at Ludwig-Maximilians-University (LMU) Munich's Department of Geophysics. His research interests lie in data science and machine learning modeling, specifically as applied to space weather dynamics and ionospheric processes.

报告简介：This study investigates cold ions (<70 eV) originating from Earth's high-latitude ionosphere and their subsequent entry into the magnetosphere, particularly directed towards the magnetotail. Observations from the Cluster spacecraft are utilized along with solar and solar wind data to develop machine learning models driven by solar and solar wind parameters. The results show a north-south asymmetry and highlight location as the most important predictor, followed by solar EUV irradiance, interplanetary magnetic field (IMF), solar wind dynamic pressure, and electric field. These findings help evaluate stellar wind-magnetospheric interactions influencing ion outflow at Earth-like exoplanets, emphasizing their role during active solar conditions at Earth.