Presentation #125.24 in the session General Topics: Solar — Poster Session.
Despite the fact that the Sun has been studied for centuries, its many properties and phenomena remain largely to be understood. One such phenomenon is the solar wind. The solar wind is a continuous stream of electrically charged particles (mainly protons and electrons), with speeds up to more than a million miles per hour, continually emitted by the sun and that permeates our solar system. The solar wind is important because it interacts with planetary magnetic fields or atmospheres. Understanding how the solar wind forms at the sun and gets accelerated, and how it evolves in interplanetary space, is important to understanding our space environment as well as the origin of the Sun’s other phenomena such as Coronal Mass Ejections (CMEs) and Solar Flares. In particular, the solar wind is observed to be faster and hotter than what traditional theories predict, and one of the major candidates that have been proposed to explain heating and acceleration of the wind is waves and turbulence. Here we perform an analysis of solar wind turbulence with Python by using data collected by NASA’s Wind spacecraft during a period of low solar activity. In this study, we compare the power spectral density slopes at different frequency ranges of the Alfvénic and non-Alfvénic (correlation between velocity and magnetic field) wind intervals. We find that the slope is similar in the low frequency range (10-4–10-1 Hz) for both the Alfvénic and non-Alfvénic wind, but the slope is significantly steeper in the higher frequency range for the Alfvenic solar wind. This suggests that the rate at which energy is cascaded from large to small scales is strongly affected by the type of fluctuations at the larger scales. As more analysis is performed, these conclusions can be subject to further discussion.