JP3D compression of solar data-cubes: Photospheric imaging and spectropolarimetry

Moro, D. Del; Giovannelli, Luca; Pietropaolo, E.; Berrilli, F.

doi:10.1007/s10686-016-9518-x

Cited by 7 publications

(2 citation statements)

References 16 publications

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“…Magnetograms from ground-based instruments (e.g. Cavallini et al 2002;Cavallini 2006;Scharmer et al 2008;Steward Puschmann et al 2012;Tadesse et al 2013;Del Moro et al 2017;Forte et al 2018Forte et al , 2020Giovannelli et al 2020) or on-board satellites (e.g. Scherrer et al 1995Scherrer et al , 2012Peter et al 2012;Berrilli et al 2015;Suematsu et al 2017) can be used to detect PILs.…”

Section: Flaring Harpsmentioning

confidence: 99%

Flare Forecasting Algorithms Based on High-Gradient Polarity Inversion Lines in Active Regions

Cicogna,

Berrilli,

Calchetti

et al. 2021

Preprint

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Solar flares emanate from solar active regions hosting complex and strong bipolar magnetic fluxes. Estimating the probability of an active region to flare and defining reliable precursors of intense flares is an extremely challenging task in the space weather field. In this work, we focus on two metrics as flare precursors, the unsigned flux R, tested on MDI/SOHO data and one of the most used parameters for flare forecasting applications, and a novel topological parameter D representing the complexity of a solar active region. More in detail, we propose an algorithm for the computation of the R value which exploits the higher spatial resolution of HMI maps. This algorithm leads to a differently computed R value, whose functionality is tested on a set of cycle 24th solar flares. Furthermore, we introduce a topological parameter based on the automatic recognition of magnetic polarity-inversion lines in identified active regions, and able to evaluate its magnetic topological complexity. We use both a heuristic approach and a supervised machine learning method to validate the effectiveness of these two descriptors to predict the occurrence of X-or M-class flares in a given solar active region during the following 24 hours period. Our feature ranking analysis shows that both parameters play a significant role in prediction performances. Moreover, the analysis demonstrates that the new topological parameter D is the only one, among 173 overall predictors, which is always present for all test subsets and is systematically ranked within the top-ten positions in all tests concerning the computation of the weighs with which each predictor impacts the flare forecasting.

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Section: Flaring Harpsmentioning

confidence: 99%

Flare Forecasting Algorithms Based on High-Gradient Polarity Inversion Lines in Active Regions

Cicogna,

Berrilli,

Calchetti

et al. 2021

Preprint

Self Cite

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“…Qualitatively, black and white regions corresponds to positive and negative

, respectively. More details and information about the dataset can be found in [ 48 , 49 , 50 , 51 ]. The dataset has been calibrated using the standard IBIS pipeline, as described in [ 52 ].…”

Section: Dataset and Methodsmentioning

confidence: 99%

Testing the Steady-State Fluctuation Relation in the Solar Photospheric Convection

Viavattene

Consolini

Giovannelli

et al. 2020

Entropy

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The turbulent thermal convection on the Sun is an example of an irreversible non-equilibrium phenomenon in a quasi-steady state characterized by a continuous entropy production rate. Here, the statistical features of a proxy of the local entropy production rate, in solar quiet regions at different timescales, are investigated and compared with the symmetry conjecture of the steady-state fluctuation theorem by Gallavotti and Cohen. Our results show that solar turbulent convection satisfies the symmetries predicted by the fluctuation relation of the Gallavotti and Cohen theorem at a local level.

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The Tor Vergata Synoptic Solar Telescope (TSST): A robotic, compact facility for solar full disk imaging

Giovannelli

Berrilli

Calchetti

et al. 2020

J. Space Weather Space Clim.

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By the continuous multi-line observation of the solar atmosphere, it is possible to infer the magnetic and dynamical status of the Sun. This activity is essential to identify the possible precursors of space weather events, such as flare or coronal mass ejections. We describe the design and assembly of TSST (Tor Vergata Synoptic Solar Telescope), a robotic synoptic telescope currently composed of two main full-disk instruments, a H telescope and a Potassium (KI D1) Magneto-Optical Filter (MOF)-based telescope operating at 769.9 nm. TSST is designed to be later upgraded with a second MOF channel. This paper describes the TSST concepts and presents the first light observation carried out in February 2020. We show that TSST is a low-cost robotic facility able to achieve the necessary data for the study of precursors of space weather events (using the magnetic and velocity maps by the MOF telescope) and fast flare detection (by the H telescope) to support Space Weather investigation and services.

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JP3D compression of solar data-cubes: Photospheric imaging and spectropolarimetry

Cited by 7 publications

References 16 publications

Flare Forecasting Algorithms Based on High-Gradient Polarity Inversion Lines in Active Regions

Flare Forecasting Algorithms Based on High-Gradient Polarity Inversion Lines in Active Regions

Testing the Steady-State Fluctuation Relation in the Solar Photospheric Convection

The Tor Vergata Synoptic Solar Telescope (TSST): A robotic, compact facility for solar full disk imaging

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