An application of the weighted horizontal magnetic gradient to solar compact and eruptive events

Korsós, M. B.; Erdélyi, R.

doi:10.1016/j.asr.2017.05.023

Cited by 6 publications

(2 citation statements)

References 26 publications

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“…Komm & Hill (2009) observed that the vorticity and magnetic flux corresponding to the active regions of flares of different levels are quite different, with M-class flares related to large vorticity and X-class flares relevant to both large vorticity and large magnetic flux simultaneously. Korsós et al (2018) analyzed the evolution process of the active region before the flare eruption using SDO/HMI Debrecen data according to their proposed weighted horizontal magnetic gradient (WG M ) (Korsós et al 2015) in 2015. By studying two typical active regions, it was observed that the WG M and its time-series characteristics are strongly correlated with flare events.…”

Section: Magnetic Field Parametersmentioning

confidence: 99%

Research Progress on Solar Flare Forecast Methods Based on Data-driven Models

Han

et al. 2023

Res. Astron. Astrophys.

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Eruption of solar flares is a complex nonlinear process, and the rays and high energy particles generated by such eruption are detrimental to the reliability of space based or ground based systems. So far, there are not reliable physical models to accurately account for the flare outburst mechanism, but a lot of data driven models have been built to study the solar flare and forecast it. In the paper, the status of solar flare forecast is reviewed, with emphasis on the machine learning methods and data processing techniques used in the models. At first, the essential forecast factors strongly relevant to solar flare outbursts, such as classification information of the sunspots and evolution pattern of the magnetic field, are reviewed and analyzed. Subsequently, methods of resampling for data preprocessing are introduced to solve the problems of class imbalance in the solar flare samples. Afterwards, typical model structures adopted for flare forecasting are reviewed from the aspects of the single and fusion models, and the forecast performances of the different models are analyzed. Finally, we herein summarize the current research on solar flare forecasting and outline its development trends.

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Section: Magnetic Field Parametersmentioning

confidence: 99%

Research Progress on Solar Flare Forecast Methods Based on Data-driven Models

Han

et al. 2023

Res. Astron. Astrophys.

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“…Attie et al () studied the observed magnetic disturbances in AR 12673 during the first 3 days of September 2017. Solar flares and CMEs are known to be caused by a sudden release of magnetic energy stored in magnetic fields (e.g., see Korsos et al, , and references therein), and the occurrence of solar flares is closely associated with sheared magnetic fields (Wang et al, ). Yan et al () attempted to find the cause of solar flares and CMEs that occurred during the highly active period of early September 2017.…”

Section: Introductionmentioning

confidence: 99%

Forbush Decreases and Geomagnetic Storms During a Highly Disturbed Solar and Interplanetary Period, 4–10 September 2017

et al. 2019

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Features and peculiarities of the cosmic ray intensity (CRI) and the geomagnetic activity, along with several solar plasma and interplanetary magnetic field, during the period 4-10 September 2017 are studied. The period was characterized by strong solar activity: Several solar flares occurred; several halo coronal mass ejections (CMEs) were ejected in space. In the near-Earth interplanetary space, the CMEs driving shock(s) and sheath(s) were identified. At the Earth, strong Forbush decreases in CRI and geomagnetic storms were observed. Several large solar flares, one of them of very high X-ray importance (X9.3) and three halo CMEs were detected in the solar atmosphere. Two shock-associated interplanetary CMEs were observed during that interval in near-Earth space; the latter and faster one arrived even as the ejecta of the earlier one was still crossing. Variations in interplanetary plasma and field parameters during, before, and after the Forbush decreases and geomagnetic storms that occurred during the considered period were examined. A detailed time-lagged correlation analysis using data at three different temporal resolutions (hourly, 5-min, and 1-min) was also performed. Cross correlations of time series of CRI with geomagnetic activity during the period 4-10 September 2017 are computed. This cross-correlation analysis between CRI variability (defined as the difference of the CRI count rate between the current and the previous time step) and the Dst indicates a delay of Dst by 3-4 hr.

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