Dynamics of earth’s magnetopause during solar storms: insights from In-situ measurements of NASA’S MMS mission

Abstract

The Earth’s magnetosphere works as a protective shield against highly magnetized and energetic plasma originating from the Sun. This solar wind energy is transferred into the magnetosphere through various mechanisms, like magnetic diffusion, reconnection, and plasma instabilities. Our study focuses on the response of the magnetopause the outer boundary of the Earth’s magnetosphere, to varying solar wind conditions.To investigate this, we employed advanced analytical techniques such as Minimum Variance Analysis to get the magnetopause and to project the magnetic field components during boundary crossings. A semi-automated Python-based pipeline was developed to identify magnetopause crossings by detecting abrupt changes in magnetic field and energy spectra. Additionally, the empirical Shue98 model was used to estimate the shape of the magnetopause and standoff distance. Our results indicate significant compression of the magnetopause toward Earth during intense solar storm events, such as ”Mother’s Day Storm” of May 2024. During this event, the magnetopause was observed as close as 6.48 Earth radii (Re) from Earth’s center, compared to 11.08 Re on a typical quiet day, indicating a compression of over 3.5 Re compare to the standoff distance of magnetopause. These displacements were accompanied by notable variations in magnetic field, electron density, temperature, and velocity, as recorded by MMS spacecraft.Over a three-year period, we have identified 297 magnetopause crossings using the developed detection pipeline. For each crossing, we extracted corresponding plasma parameters, providing an opportunity to analyze the physical processes occurring near the magnetopause. The plasma data revealed a redistribution of plasma flux, with lower density and velocity near subsolar region, and higher values toward the dusk and dawn flanks of the magnetopause. Finally, we validated the detected magnetopause locations by comparing in situ data from theWind satellite with the predicted positions from the Shue98 model. The observed locations matched well within an error margin of ±1 Re, demonstrating the accuracy and reliability of our detection method.