2:15 PM - 2:30 PM
[PEM10-27] Electron Density Variations and the Short-wave Fadeout During X-Class Solar Flares in May 2024 Using PHITS
Keywords:Short-wave fadeout, Solar flare, Lower ionosphere, Simulation, Ionosonde
High-frequency (HF) radio communication is a crucial method of long-distance communication, particularly in disaster response and air traffic control, as it relies on ionospheric reflection. However, the rapid increase in X-ray flux during solar flares significantly enhances electron density in the lower ionosphere, potentially leading to the sudden disappearance of HF signals, which is known as the Short-wave fadeout (SWF). In May 2024, over ten X-class solar flares were observed, leading to widespread occurrences of the SWF worldwide. To assess these events and quantify their impact, it is essential to accurately estimate electron density fluctuations in the ionosphere.
In this study, we used the GAIA model (Jin et al., 2011) and the PHITS code (Sato et al., 2024) to evaluate electron density variations during solar flares. GAIA is a numerical simulation model capable of simulating electron density fluctuations throughout the global ionosphere in response to solar flares. However, it does not fully incorporate photochemical reactions in the lower ionosphere (below 100 km). To address this limitation, we used PHITS, a Monte Carlo-based particle transport and collision simulation code, for a more accurate modeling of electron density variations in the lower ionosphere due to X-ray emissions from solar flares.
The magnitude of the SWF can be inferred from the minimum frequency in the ionogram (fmin), since variations in fmin correspond to changes in electron density in the lower ionosphere. We compared simulated fmin values with observed fmin from 2010–2014 and May 2024. The best-fit linear regression analysis between simulated and observed fmin yielded a slope of 1.00, an intercept of 0.90 MHz, and a correlation coefficient of 0.77 for May 2024, whereas for 2010–2014, these values were 0.87, 0.36 MHz, and 0.88, respectively. Our results indicate that PHITS effectively reproduces electron density variations at the peak of solar flares.
In this presentation, we will discuss the differences in the magnitude of the SWF between 2010–2014 and May 2024 and provide a detailed validation of electron density variations estimated with PHITS.
In this study, we used the GAIA model (Jin et al., 2011) and the PHITS code (Sato et al., 2024) to evaluate electron density variations during solar flares. GAIA is a numerical simulation model capable of simulating electron density fluctuations throughout the global ionosphere in response to solar flares. However, it does not fully incorporate photochemical reactions in the lower ionosphere (below 100 km). To address this limitation, we used PHITS, a Monte Carlo-based particle transport and collision simulation code, for a more accurate modeling of electron density variations in the lower ionosphere due to X-ray emissions from solar flares.
The magnitude of the SWF can be inferred from the minimum frequency in the ionogram (fmin), since variations in fmin correspond to changes in electron density in the lower ionosphere. We compared simulated fmin values with observed fmin from 2010–2014 and May 2024. The best-fit linear regression analysis between simulated and observed fmin yielded a slope of 1.00, an intercept of 0.90 MHz, and a correlation coefficient of 0.77 for May 2024, whereas for 2010–2014, these values were 0.87, 0.36 MHz, and 0.88, respectively. Our results indicate that PHITS effectively reproduces electron density variations at the peak of solar flares.
In this presentation, we will discuss the differences in the magnitude of the SWF between 2010–2014 and May 2024 and provide a detailed validation of electron density variations estimated with PHITS.