English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

We develop forecast models of daily probability of major flares (M- andX-class) based on empirical relationships between photospheric magneticparameters and daily flaring rates from May 2010 to April 2018. In this study,we consider ten magnetic parameters characterizing size, distribution, andnon-potentiality of vector magnetic fields from Solar Dynamics Observatory(SDO)/Helioseismic and Magnetic Imager (HMI) and Geostationary OperationalEnvironmental Satellites (GOES) X-ray flare data. The magnetic parameters areclassified into three types: the total unsigned parameters, the total signedparameters, and the mean parameters. We divide the data into two setschronologically: 70% for training and 30% for testing. The empiricalrelationships between the parameters and flaring rates are used to predictflare occurrence probabilities for a given magnetic parameter value. Majorresults of this study are as follows. First, major flare occurrence rates arewell correlated with ten parameters having correlation coefficients above 0.85.Second, logarithmic values of flaring rates are well approximated by linearequations. Third, the total unsigned and signed parameters achieved betterperformance for predicting flares than the mean parameters in terms ofverification measures of probabilistic and converted binary forecasts. Weconclude that the total quantity of non-potentiality of magnetic fields iscrucial for flare forecasting among the magnetic parameters considered in thisstudy. When this model is applied for operational use, this model can be usedusing the data of 21:00 TAI with a slight underestimation of 2 - 6.3%.

Forecast of Daily Major Flare Probability Using Relationships between Vector Magnetic Properties and Flaring Rates