Identification of periodic density structures in Solar Orbiter data: Radial evolution

TL;DR

The paper addresses how quasi-periodic density structures (PDS) in the solar wind evolve radially from the inner heliosphere to near-Earth orbit. It employs a robust MTM plus wavelet framework on Solar Orbiter data (0.3–1 AU) to detect PDS in both frequency and time domains and to build a public catalog of events. The results show that PDS expand in slow solar wind and compress in fast wind at a rate of about 10%, consistent with a solar-origin formation mechanism involving magnetic reconnection in the corona. This large-scale statistical study provides new insight into the mesoscale structure of the solar wind and highlights opportunities for joint analysis with other missions to map PDS near the Sun.

Abstract

The quasi-Periodic density structures (PDSs) are quasiperiodic variations of solar wind density ranging from a few minutes to a few hours. They are trains of advected density structures with radial length scales LR in the 100-10,000 Mm range, thus belonging to the class of solar wind mesoscale structures. Even though PDS at L1 have been extensively studied both through statistical and event analysis, their investigation at distances closer to the Sun is limited. This study performs a statistical investigation of PDS at various distances from the Sun between 0.3 and 1 AU by exploiting Solar Orbiter data. We compiled and made publicly available an extensive list of PDSs following a well-established methodology that combines the Multitaper method as well as wavelet analysis to reveal the distribution of PDS radial length scales and how they vary with respect to the radial distance. Our results indicate that PDS advected with the ambient slow solar wind are expanded at a rate of approximately 10%, while PDS detected during fast solar wind segments show compression at a similar rate. These are consistent with the scenario in which PDSs are formed at the Sun by processes involving magnetic reconnection and interchange reconnection in the solar corona.

Figures (8)

• Figure 1: Distribution of the number of PDS events. From left to right: distributions for the entire sample, for the slow and fast solar wind, respectively. The distributions of the six-, twelve- and eighteen-hour interval are coloured with black, red and blue, respectively.
• Figure 2: De-trended probability of occurrence for PDS frequencies, where the distributions of the six-, twelve- and eighteen-hour interval are coloured with black, red and blue, respectively. From left to right: distributions for the entire sample, inner distances (R$<$0.86 AU) and near-L1 (R$>$0.86 AU), respectively. From top to bottom: distributions for the entire sample, slow (V$<$450 km/s) and fast (V$>$450 km/s) solar wind, respectively.
• Figure 3: Similar to figure \ref{['Fig2']} but for the PDS radial length scale (L$_R$). From top to bottom: distributions for the slow (V$<$450 km/s) and fast (V$>$450 km/s) solar wind, respectively. The light blue shaded rectangulars indicate the peaks of the distribution.
• Figure 4: Dependence of the PDS radial length scale during slow (left panel) and fast solar wind (right panel) on spacecraft radial distance for the 6-hour window. Grey dots correspond to the data and the solid black lines to the median of each R bin, respectively, while the grey shaded area is the inter-quartile range. The power law fit on the data is depicted with the solid red line, while the Root Mean Square Error (RMSE) is given on the top of each panel.
• Figure 5: Example of event detection using the continuous wavelet transform. Top panel: Time series of total ion density. Middle panel: Wavelet spectrum of the total ion density, where the horizontal white dashed lines correspond to the frequency range of interest (f$\pm0.15$ mHz) and the solid black line depict the cone of influence, where edge effects in the processing become important. Bottom panel: Average wavelet power in the f$\pm0.15$ mHz range. The horizontal red solid line corresponds to the 75th quantile of the power of the entire time period for the 6 hours window.