EGU2020-13298
https://doi.org/10.5194/egusphere-egu2020-13298
EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Solar flare forecasting model using 3D magnetic field data

Xin Huang
Xin Huang
  • National Astronomical Observatories, Chinese Academy of Sciences, China (xhuang@bao.ac.cn)

Solar flares originate from the release of the energy stored in the magnetic field of solar active regions. Generally, the photospheric magnetograms of active regions are used as the input of the solar flare forecasting model. However, solar flares are considered to occur in the low corona. Therefore, the role of 3D magnetic field of active regions in the solar flare forecast should be explored. We extrapolate the 3D magnetic field using the potential model for all the active regions during 2010 to 2017, and then the deep learning method is applied to extract the precursors of solar flares in the 3D magnetic field data. We find that the 3D magnetic field of active regions is helpful to build a deep learning based forecasting model.

How to cite: Huang, X.: Solar flare forecasting model using 3D magnetic field data, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13298, https://doi.org/10.5194/egusphere-egu2020-13298, 2020