We describe the peculiarity of two recurrent white light flares occurred on Sept. 06, 2017, in the super Active Region (SAR) NOAA 12673, with a time interval, between their peaks, of about 3 hours. These events of X2.2 and X9.3 GOES class are very important not only for their high level of emission and for the visible effects on the lower layers of the solar atmosphere, discernible as clear white light ribbons, but as well for the strong horizontal photospheric motions which seemed to drive them. In fact, we observed for several hours before the flare occurrence the displacement of a negative umbra located in the main delta spot of the Active Region. We measured velocities up to 0.6 km s −1 . The strong and persistent shear motion of the photospheric structures together with the high intensity of the magnetic flux involved by these events can be considered responsible for the new energy continuously supplied into the magnetic system.From the timing of the emissions at different wavelengths we were able to provide some constraints for the modeling of such events.

We describe a new tool developed for solar flare forecasting on the base of some sunspot group properties. Assuming that the flare frequency follows the Poisson statistics, this tool uses a database containing the morphological characteristics of the suspot groups daily observed by the Equatorial Spar of INAF − Catania Astrophysical Observatory since January 2002 up today. By means of a linear combination of the flare rates computed on the base of some properties of the sunspot groups, like area, number of pores and sunspots, Zurich class, relative importance between leading spot and density of the sunspot population, and type of penumbra of the main sunspot, we determine the probability percentages that a flare of a particular energy range may occur. Comparing our forecasts with the flares registered by GOES satellites in the 1−8 Å X−ray band during the subsequent 24 hrs we measured the performance of our method. We found that this method, which combines some morphological parameters and a statistical technique, has the best performances for the strongest events, which are more interesting for their implications in the Earth environment.

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