Forecasting the probability of a solar active region to flare is a challenging and pursued topic in the Space Weather field. The R value, developed by Schrijver (2007) is one of the most used descriptors of the photospheric magnetic field in active regions for flare forecasting applications. The R value method was calibrated on the magnetograms obtained from the Michelson Doppler Imager (MDI) instrument on board the Solar and Heliospheric Observatory (SOHO) between 1998 and 2006, during solar cycle 23. Since 2010, the Helioseismic and Magnetic Imager (HMI) on board the Solar Dynamics Observatory (SDO) satellite, is operative, collecting solar magnetograms with a spatial resolution 4 times higher than MDI, while the observation program of MDI was terminated on April 2011. We readjust the original R value algorithm to adapt it to the higher spatial resolution of HMI and we compare the statistical analysis of a sample of cycle 24th solar flares with the statistical analysis performed by Schrijver (2007). Furthermore, we propose a new parameter D, aimed to identify and count the number of magnetic polarity-inversion lines within the same active region, to better characterize magnetic active region morphology. The result of our statistical analysis show that both parameters are good descriptors of the behaviour of an AR and useful tools for flare forecasting, individually but especially if used together.

Giovannelli, L., Berrilli, F., Cicogna, D., Del Moro, D. (2019). Calibration of statistical solar flare forecast parameters for images from SDO/HMI space instrument. In Geographical research abstract. Volume 21, EGU General Assembly 2019. EGU.

Calibration of statistical solar flare forecast parameters for images from SDO/HMI space instrument

Giovannelli, Luca;Berrilli, Francesco;Del Moro, Dario
2019-01-01

Abstract

Forecasting the probability of a solar active region to flare is a challenging and pursued topic in the Space Weather field. The R value, developed by Schrijver (2007) is one of the most used descriptors of the photospheric magnetic field in active regions for flare forecasting applications. The R value method was calibrated on the magnetograms obtained from the Michelson Doppler Imager (MDI) instrument on board the Solar and Heliospheric Observatory (SOHO) between 1998 and 2006, during solar cycle 23. Since 2010, the Helioseismic and Magnetic Imager (HMI) on board the Solar Dynamics Observatory (SDO) satellite, is operative, collecting solar magnetograms with a spatial resolution 4 times higher than MDI, while the observation program of MDI was terminated on April 2011. We readjust the original R value algorithm to adapt it to the higher spatial resolution of HMI and we compare the statistical analysis of a sample of cycle 24th solar flares with the statistical analysis performed by Schrijver (2007). Furthermore, we propose a new parameter D, aimed to identify and count the number of magnetic polarity-inversion lines within the same active region, to better characterize magnetic active region morphology. The result of our statistical analysis show that both parameters are good descriptors of the behaviour of an AR and useful tools for flare forecasting, individually but especially if used together.
EGU General Assembly, 21.
2019
21.
Rilevanza internazionale
2019
Settore FIS/06 - FISICA PER IL SISTEMA TERRA E PER IL MEZZO CIRCUMTERRESTRE
English
https://meetingorganizer.copernicus.org/EGU2019/EGU2019-17832.pdf
Intervento a convegno
Giovannelli, L., Berrilli, F., Cicogna, D., Del Moro, D. (2019). Calibration of statistical solar flare forecast parameters for images from SDO/HMI space instrument. In Geographical research abstract. Volume 21, EGU General Assembly 2019. EGU.
Giovannelli, L; Berrilli, F; Cicogna, D; Del Moro, D
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2108/250715
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact