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BEGIN:VEVENT
DTSTAMP:20260523T210104Z
UID:https://www.mps.mpg.de/events/44717/7840847
DTSTART:20260212T100000Z
DTEND:20260212T110000Z
CLASS:PUBLIC
CREATED:20260205T194804Z
DESCRIPTION: Solar flares are the most energetic manifestations of solar ac
 tivity and can significantly affect Earth’s magnetosphere\, ionosphere\,
  and technological systems. Therefore\, anticipating these events remains 
 a fundamental challenge in heliophysics. Soft X-ray observations from the 
 GOES satellites have long been used to monitor and characterize solar flar
 es. Among the various forecasting approaches\, the Flare Anticipation Inde
 x (FAI)\, originally proposed by Hudson (2025)\, has established itself as
  a promising diagnostic tool for thermal activity preceding flares. The FA
 I is based on the detection of a Hot Onset Precursor Event (HOPE)\, charac
 terized by a gradual increase in plasma temperature\, and the emission mea
 sure before the impulsive phase of a flare. In this work\, we performed a 
 statistical validation of the FAI using a representative dataset of approx
 imately 8\,000 days between 1980 and 2025. Plasma temperatures and emissio
 n measurements were derived from GOES/XRS observations\, and FAI-based ale
 rts were generated using predefined thresholds correlated with GOES solar 
 flares within a 30-minute time interval from flare start to peak. A total 
 of 48\,344 flares of different classes were analyzed\, yielding varying de
 tection rates depending on the flare class. The parameter sets were chosen
  to minimize the number of false positives and increase the detection rate
  of large flares (M and X). The results suggest that the FAI is particular
 ly sensitive to medium and large solar flares and has potential for near r
 eal-time prediction\, while also highlighting the need to optimize the thr
 esholds to improve its predictive performance for each class.\nSpeaker: Pa
 ula González-Prieto 
LAST-MODIFIED:20260205T194929Z
LOCATION:https://uio.zoom.us/j/63138938090
ORGANIZER;CN=Valeriia Liakh:mailto:
SUMMARY:ESPOS: ESPOS: Can we anticipate solar flares? Statistical analysis 
 of the Flare Anticipation Index (FAI) (Paula González-Prieto)
URL;VALUE=URI:https://www.mps.mpg.de/events/44717/7840847
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