Related papers: Toward Reliable Benchmarking of Solar Flare Foreca…

Whilst the most dynamic solar active regions (ARs) are known to flare frequently, predicting the occurrence of individual flares and their magnitude, is very much a developing field with strong potentials for machine learning applications.…

Prediction of the Solar Energetic Particle (SEP) events garner increasing interest as space missions extend beyond Earth's protective magnetosphere. These events, which are, in most cases, products of magnetic reconnection-driven processes…

We present a hybrid forecasting strategy that combines numerical modeling, statistical forecasting, and machine learning methods to predict enhanced bursts of solar activity. These bursts, referred to here as space weather seasons, occur on…

One prominent feature of solar cycle is its irregular variation in its cycle strength, making it challenging to predict the amplitude of the next cycle. Studies show that fluctuations and nonlinearity in generating poloidal field throughout…

The relationships between solar flare parameters (total importance, time duration, flare index, and flux) and sunspot activity (Rz) as well as those between geomagnetic activity (aa index) and the flare parameters can be well described by…

Predicting the severity of the solar eruptive phenomena like flares and Coronal Mass Ejections (CMEs) remains a great challenge despite concerted efforts for several decades. The advent of high quality vector magnetograms obtained from…

Solar flares are known to generate seismic waves in the Sun. We present a detailed analysis of seismic emission in sunspots accompanying M- and X-class solar flares. For this purpose, we have used high-resolution Dopplergrams and…

The prediction of solar flares is still a significant challenge in space weather research, with no techniques currently capable of producing reliable forecasts performing significantly above climatology. In this paper, we present a flare…

Solar flares - bursts of high-energy radiation responsible for severe space-weather effects - are a consequence of the occasional destabilization of magnetic fields rooted in active regions (ARs). The complexity of AR evolution is a barrier…

The Space-Weather ANalytics for Solar Flares (SWAN-SF) is a multivariate time series benchmark dataset recently created to serve the heliophysics community as a testbed for solar flare forecasting models. SWAN-SF contains 54 unique…

This paper develops a planetary model to predict the occurrence of intermediate range periodicity in solar activity, in particular the ~155 day Rieger periodicity in flare activity. It is shown that periodicity at half integer multiples of…

Solar flares, along with other sun-originated events such as Coronal Mass Ejections, fast solar wind streams, and solar energetic particles are among the most relevant events in Space Weather. Moreover, solar flares are the most energetic…

Solar Energetic Particle (SEP) events and their major subclass, Solar Proton Events (SPEs), can have unfavorable consequences on numerous aspects of life and technology, making them one of the most harmful effects of solar activity.…

The R-value is a measure of the strength of photospheric magnetic Polarity Inversion Lines (PILs) in Active Regions (ARs). This work investigates the possibility of a relation between R-value variations and the occurrence of X-class flares…

A phenomenological model is presented for the quantitative description of individual solar cycles' features, such as onset, intensity, evolution, in terms of the number of M and X-class solar flares. The main elements of the model are the…

We analyze the relationship between the flare X-ray peak flux, and characteristics of the Polarity Inversion Line (PIL) and Active Regions (AR), derived from line-of-sight (LOS) magnetograms. The PIL detection algorithm based on a…

Solar flares are observed and classified according to their intensity measured with the GOES X-ray Sensors. We show that the duration of a flare, as measured by the full width at half maximum (FWHM) in GOES is not related to the size of the…

In a recent work, Kilcik et al. (2017), have detected the temporal and periodic behavior of sunspot counts (SSC) in flaring (i.e. C, M, or X class flares), and non-flaring active regions for the last two solar cycles, covering the period:…

A hybrid two-stage machine learning architecture that addresses the problem of excessive false positives (false alarms) in solar flare prediction systems is investigated. The first stage is a convolutional neural network (CNN) model based…

The light curves of solar flares in the impulsive phase are complex in general, indicating that multiple physical processes are involved in. With the GOES (Geostationary Operational Environmental Satellite) observations, we find that there…