Fine-grained Solar Flare Forecasting Based on the Hybrid Convolutional Neural Networks*

Improving the performance of solar flare forecasting is a hot topic in the solar physics research field. Deep learning has been considered a promising approach to perform solar flare forecasting in recent years. We first used the generative adversarial networks (GAN) technique augmenting sample data to balance samples with different flare classes. We then proposed a hybrid convolutional neural network (CNN) model (M) for forecasting flare eruption in a solar cycle. Based on this model, we further investigated the effects of the rising and declining phases for flare forecasting. Two CNN models, i.e., M rp and M dp, were presented to forecast solar flare eruptions in the rising phase and declining phase of solar cycle 24, respectively. A series of testing results proved the following. (1) Sample balance is critical for the stability of the CNN model. The augmented data generated by GAN effectively improved the stability of the forecast model. (2) For C-class, M-class, and X-class flare forecasting using Solar Dynamics Observatory line-of-sight magnetograms, the means of the true skill statistics (TSS) scores of M are 0.646, 0.653, and 0.762, which improved by 20.1%, 22.3%, and 38.0% compared with previous studies. (3) It is valuable to separately model the flare forecasts in the rising and declining phases of a solar cycle. Compared with model M, the means of the TSS scores for No-flare, C-class, M-class, and X-class flare forecasting of the M rp improved by 5.9%, 9.4%, 17.9%, and 13.1%, and those of the M dp improved by 1.5%, 2.6%, 11.5%, and 12.2%.

Microwave indicator of potential geoeffectiveness and magnetic flux-rope structure of a solar active region

We analyze the presence of a microwave neutral-line-associated source (NLS) in a super-active region NOAA 12673, which produced a number of geo-effective events in September 2017. To estimate the NLS position, we use data from the Siberian Radioheliograph in a range 4–8 GHz and from the Nobeyama Radioheliograph at 17 GHz. Calculation of the coronal magnetic field in a non-linear force-free approximation has revealed an extended structure consisting of interconnected magnetic flux ropes, located practically along the entire length of the main polarity separation line of the photospheric magnetic field. NLS is projected into the region of the strongest horizontal magnetic field, where the main energy of this structure is concentrated. During each X-class flare, the active region lost magnetic helicity and became a CME source.

Microwave indicator of potential geoeffectiveness and magnetic flux-rope structure of a solar active region

We analyze the presence of a microwave neutral-line-associated source (NLS) in a super-active region NOAA 12673, which produced a number of geo-effective events in September 2017. To estimate the NLS position, we use data from the Siberian Radioheliograph in a range 4–8 GHz and from the Nobeyama Radioheliograph at 17 GHz. Calculation of the coronal magnetic field in a non-linear force-free approximation has revealed an extended structure consisting of interconnected magnetic flux ropes, located practically along the entire length of the main polarity separation line of the photospheric magnetic field. NLS is projected into the region of the strongest horizontal magnetic field, where the main energy of this structure is concentrated. During each X-class flare, the active region lost magnetic helicity and became a CME source.