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Solar Physics

, Volume 254, Issue 1, pp 101–125 | Cite as

Statistical Assessment of Photospheric Magnetic Features in Imminent Solar Flare Predictions

  • Hui Song
  • Changyi Tan
  • Ju Jing
  • Haimin Wang
  • Vasyl Yurchyshyn
  • Valentyna Abramenko
Article

Abstract

In this study we use the ordinal logistic regression method to establish a prediction model, which estimates the probability for each solar active region to produce X-, M-, or C-class flares during the next 1-day time period. The three predictive parameters are (1) the total unsigned magnetic flux T flux, which is a measure of an active region’s size, (2) the length of the strong-gradient neutral line L gnl, which describes the global nonpotentiality of an active region, and (3) the total magnetic dissipation E diss, which is another proxy of an active region’s nonpotentiality. These parameters are all derived from SOHO MDI magnetograms. The ordinal response variable is the different level of solar flare magnitude. By analyzing 174 active regions, L gnl is proven to be the most powerful predictor, if only one predictor is chosen. Compared with the current prediction methods used by the Solar Monitor at the Solar Data Analysis Center (SDAC) and NOAA’s Space Weather Prediction Center (SWPC), the ordinal logistic model using L gnl, T flux, and E diss as predictors demonstrated its automatic functionality, simplicity, and fairly high prediction accuracy. To our knowledge, this is the first time the ordinal logistic regression model has been used in solar physics to predict solar flares.

Keywords

Sun: Activity Sun: Flares Sun: Magnetic fields Magnetic observables 

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Copyright information

© Springer Science+Business Media B.V. 2008

Authors and Affiliations

  • Hui Song
    • 1
  • Changyi Tan
    • 1
  • Ju Jing
    • 1
  • Haimin Wang
    • 1
  • Vasyl Yurchyshyn
    • 2
  • Valentyna Abramenko
    • 2
  1. 1.Space Weather Research Laboratory, Center for Solar-Terrestrial ResearchNew Jersey Institute of TechnologyNewarkUSA
  2. 2.Big Bear Solar ObservatoryNew Jersey Institute of TechnologyBig Bear CityUSA

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