Solar wind data analysis aided by synthetic modeling: a better understanding of plasma-frame variations from temporal data
Norbert Magyar, Jaye Verniero, Adam Szabo, Jiyuan Zhang, Tom Van, Doorsselaere

TL;DR
This paper introduces a synthetic modeling toolkit to convert solar wind in-situ measurements from temporal to spatial frames, aiding the interpretation of plasma turbulence and anisotropy.
Contribution
The paper presents a novel synthetic modeling approach for better temporal-spatial conversion of solar wind data, improving analysis of plasma-frame variations.
Findings
The likelihood of parallel or perpendicular fluctuations depends on spectral anisotropy.
Synthetic data generation helps test analysis methods for solar wind measurements.
Application to Parker Solar Probe data demonstrates the toolkit's utility.
Abstract
In-situ measurements of the solar wind, a turbulent and anisotropic plasma flow originating at the Sun, are mostly carried out by single spacecraft, resulting in one-dimensional time series. The conversion of these measurements to the spatial frame of the plasma is a great challenge, but required for direct comparison of the measurements with MHD turbulence theories. Here we present a toolkit, based on the synthetic modeling of solar wind fluctuations as two-dimensional noise maps with adjustable spectral and power anisotropy, that can help with the temporal-spatial conversion of real data. Specifically, by following the spacecraft trajectory through a noise map (relative velocity and angle relative to some mean magnetic field) with properties tuned to mimic those of the solar wind, the likelihood that the temporal data fluctuations represent parallel or perpendicular fluctuations in…
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Taxonomy
TopicsSolar and Space Plasma Dynamics · Solar Radiation and Photovoltaics
