This study targets the Brazilian Decimeter Array telescope. provide a unique TNS for detecting solar flare events in solar images obtained using radio astronomy techniques.
The solar flare is an intense, abrupt release of energy that occurs in the sun as the magnetic field changes due to the presence of flux or the movement of sunspots. Shijin Song, in Big Data in Astronomy, 2020 4.6 Solar flare detection Correlations of the number and intensity of flares with the number and size of sunspots have been observed. There are only few events per year with very large fluxes. At times of high solar activity, up to 10 events per day can occur. The number of flares is inversely proportional to their size. This is a consequence of the interplanetary magnetic field configuration. It has been observed that flares originating in the western hemisphere of the Sun are more likely to produce solar particles capable of reaching the Earth than flares in the eastern hemisphere. Impulsive soft X-ray events are usually of short duration (≤1h), whereas gradual soft-X-ray events last many hours and are called long duration events (LDE). Lately solar flare particle observations are classified according to the type of associated solar flare soft-X-ray emission into impulsive and gradual events. Solar flares are classified according to size. The increase of the electromagnetic radiation is particularly strong in the short wavelength region, around <2000 Å. Simultaneously shock waves and magnetic disturbances are generated which may affect the magnetosphere if the Earth lies within the zone of influence of a flare.
Sometimes the flux levels of particles and radiation are very high, several orders of magnitude higher than the galactic cosmic ray flux. The duration of a solar flare ranges from about 20 minutes to as much as 3 hours.įlares are accompanied with the emission of a broad spectrum of electromagnetic radiation, including X- and gamma ray emission, and relatively energetic particles, predominantly protons but also electrons, helium and small quantities of heavier nuclei. Initially they manifest themselves by a localized sudden brightening. They develop suddenly and rapidly, in minutes, and cover a relatively small region of the solar surface. Solar flares are sporadic local eruptions of the chromosphere. Grieder, in Cosmic Rays at Earth, 2001 6.4.2 Solar Flares Case analyses demonstrate that the deep learning-based solar flare forecasting model pays attention to areas with the magnetic polarity-inversion line or the strong magnetic field in magnetograms of active regions. The performance of the proposed forecasting model is comparable to that of the state-of-the-art flare forecasting models, even if the duration of the total magnetograms continuously spans 19.5 years. The performance of the deep learning forecasting model is not sensitive to the given forecasting periods (6, 12, 24, or 48 h). The testing results of the forecasting model indicate that the forecasting patterns can be automatically reached with the MDI data and they can also be applied to the HMI data furthermore, these forecasting patterns are robust to the noise in the observational data. Therefore, the prediction of solar flares is transformed into a two-category problem. The paper uses the CNN network structure to perform solar flare prediction, which means we process the input magnetic map through the CNN and predict whether flares will occur. In the current work, the deep learning method is applied to set up the solar flare forecasting model, in which forecasting patterns can be learned from line-of-sight magnetograms of solar active regions. For this reason, the conventional solar flare forecast is essentially based on the statistic relationship between solar flares and measures extracted from observational data. The triggering mechanism for these flares, however, remains unknown.
Solar flares originate from the release of the energy stored in the magnetic field of solar active regions. Linghe Kong, in Big Data in Astronomy, 2020 4.2.3 Deep learning