Researchers create a mathematical tool to measure the Sun’s atmosphere using spacecraft radio signals

An international team of scientists has developed a novel method to measure the speed and density of the solar wind using routine radio signals from spacecraft passing behind the Sun. By creating a universal mathematical formula that works across different radio frequencies, the researchers have unlocked a consistent way to study the Sun’s superheated, chaotic atmosphere, known as the corona. The research could help scientists better understand the powerful solar winds that constantly blow through our solar system. 

The team, including researchers from the Indian Institute of Technology (IIT) Indore, Vikram Sarabhai Space Centre (VSSC-ISRO), ISRO Telemetry Tracking and Command Network (ISTRAC), the University of Tokyo, Japan, and Kyoto Sangyo University, Japan, used an observational technique called radio occultation. When spacecraft like India’s Mars Orbiter Mission and Japan’s Venus Climate Orbiter, Akatsuki, move behind the Sun from Earth’s perspective, their communication radio beams must travel right through the solar corona to reach tracking stations on our planet. 

The corona, the outermost layer of the sun’s atmosphere, is a highly dynamic environment packed with magnetic fields and plasma, which is a superheated gas of charged particles like electrons. As the spacecraft’s radio waves push through this turbulent plasma, they experience a phenomenon known as Doppler spectral broadening. Essentially, the radio signal gets distorted, scattered, and stretched by the flowing particles.

By measuring how much the radio signal widened, the researchers could calculate how fast the solar wind was blowing across the signal’s path and how densely packed the electrons were in that region. To calculate the effect of solar atmosphere on the signals, the team relied on a physics concept called Kolmogorov turbulence, which describes how energy cascades from large, chaotic swirls of fluid or plasma down to much smaller scales. By assuming the Sun’s coronal plasma follows this specific mathematical turbulence pattern, the team built a model that directly translates distorted radio signals into measurements of wind speed and electron density.

While earlier studies used radio occultation to study the Sun, their mathematical tools were severely constrained by frequency. Previous formulas were tied to specific types of radio waves, meaning an equation designed for the radio frequency used by the Mars Orbiter Mission would not work accurately for the different frequency used by Akatsuki. This made it incredibly difficult to compare data across different space missions. This new research solves that problem by introducing a frequency-scaled relation. It provides a single, unified framework that automatically adjusts for the radio signal’s wavelength, allowing researchers to seamlessly compare data from any spacecraft, regardless of the telecommunication band used.

However, the researchers note that their generalised method relies on the assumptions that the solar corona is perfectly spherical, that the solar wind flows in a steady outward direction, and that the plasma strictly follows the Kolmogorov turbulence model. In reality, the Sun’s atmosphere is highly complex. In regions where the solar wind undergoes extreme, rapid acceleration near the Sun, or where turbulence is unpredictable, this simplified model becomes less accurate. Future models will need to account for these more complex, evolving turbulence patterns to improve measurement precision.

The continuous outflow of charged particles from the Sun carries massive amounts of energy and magnetic flux through interplanetary space, directly driving space weather. When severe solar storms hit Earth, they can damage satellites, disrupt GPS networks, and cause massive power grid failures. By maximising the scientific value of routine spacecraft radio signals, this new method allows for more frequent and consistent monitoring of the inner solar system. It provides a better understanding of how solar winds accelerate and behave, enabling earlier and more accurate predictions of extreme space weather events and helping safeguard our increasingly technology-dependent world.