Predictability of Solar Flares Based on Satellite Observations and Magnetohydrodynamic Instability Models

Solar flares are catastrophic explosions in the solar corona and may potentially cause a severe space weather disaster which impacts various infrastructures. Some giant solar flares indeed caused the failures of our modern infrastructures, e.g., power grid, radio communication, satellite, and airplane operations. The historical records and the isotope analysis of tree rings and ice cores indicate that much larger flare events than we have observed so far might occur in the Sun. However, we do not yet completely understand what determines the occurrence and properties of solar flares and the subsequent processes of solar flares. Therefore, giant solar flares are the potential risk for modern society, and it is crucially important to improve our understanding and predictability of solar flares to mitigate the severe space weather impact.

Because solar flares are widely believed to be driven by the rapid release of magnetic energy stored in solar active regions around visible sunspots, the sophisticated observations of the solar surface and the solar corona can provide the precious information for predicting the occurrence of solar flares. In particular, the high-resolution observation of the photospheric magnetic field by Hinode and the Solar Dynamics Observatory (SDO) is important not only for the science research but also for the space weather prediction, and many efforts are taken to implement the magnetic field data for the prediction of solar flares and coronal mass ejections.

In this paper, we will report on the recent predictive studies that have been done in the Project for Solar-Terrestrial Environment Prediction (PSTEP), which is the nation-wide project for space weather and space climate in Japan. The key objective of the PSTEP is to build the synergy between scientific research and the space weather forecasting operation through the development of physics-based prediction models. As an activity for them, we developed a new flare-prediction model (called the kappa-scheme), which is capable of predicting where giant solar flares may occur and how large they may be from vector magnetic field data on the solar surface based on the new magnetohydrodynamic (MHD) instability model. Here, we demonstrate the kappa-scheme's ability to predict giant solar flares by analyzing the largest solar flares in the solar cycle 24. As the results, we show that the distribution of the magnetic twist flux density in the vicinity of the magnetic polarity inversion line (PIL) on the solar surface plays a crucial role in determining not only the sizes of solar flares but also when, where, and how solar flares may occur. The result indicates that the physics-based analysis of stability using the high-resolution observation of the magnetic field of the Sun is a powerful tool to predict imminent giant solar flares.