On the Relation between Source Region and In-situ Variability of Low $\delta B$ Solar Wind Streams

TL;DR

This study links in-situ low variability in the solar wind's magnetic field to its coronal source regions using Parker Solar Probe data, PFSS modeling, and magnetic connectivity analysis, revealing that low variability periods originate from stable source regions.

Contribution

It introduces a detailed analysis connecting low in-situ magnetic variability to source region stability, utilizing PFSS modeling and Parker Solar Probe observations for the first time.

Findings

Approximately half of low variability periods are linked to stable source regions.

Low $eta B / B$ periods between switchbacks show less source variability than switchback patches.

Results suggest a solar origin for low-variability periods, encouraging further diagnostic studies.

Abstract

Parker Solar Probe (PSP) observed a high speed stream near the Sun ($\sim 9.8 R_\odot$) in March 2025. As this stream was observed near the Sun, it allowed for an unparalleled opportunity to observe pristine, coronal hole wind with little evolution (expansion, stream interaction, etc) effects impacting its properties. Through an ensemble of magnetic connectivity analysis utilizing Potential Field Source Surface (PFSS) modeling and ballistic propagation, we make estimates of the footpoints, and corresponding source region parameters, associated with the stream. We then look at how the low variability regions (small gradient in the in-situ $B_r$) are related to the variability in the field strength at their source ($B_0$). We find that about half of these periods are associated with low source region variability. Lastly, we examine the low $\delta B / B$ periods between switchback patches and similarly find that they show statistically less variability in their associated $B_0$ value than their switchback patch counterparts. We believe that these results point to a solar source of these ``low-variability" periods, that warrants further investigation with composition diagnostics and more complex modeling techniques.