PROBABILITAS LONTARAN MASSA KORONA BERDASARKAN PARAMETER MEDAN MAGNET UNIVARIAT

Rhorom Priyatikanto, Emanuel Sungging Mumpuni, Tiar Dani, Farahhati Mumtahana, Nana Suryana

Abstract

Forecasting of flare occurrence and coronal mass ejection (CME) are necessary since those energetic phenomena are able to effectively influence the space weather on Earth. In this study, we analyzed four magnetic parameters of active region: (1) mean gradient of horizontal magnetic field (meangbh), (2) mean helicity (meanjzh), (3) mean photospheric magnetic free energy (meanpot) and (4) mean gradient of total field (meangbt) and their potential usage for the input in CME prediction based on linear statistics. Obtained that among those four parameters, meangbt is the best parameter for the purpose mentioned. Active regions with meanbgt ≤ 96 Gauss/Mm probably produce flare with CME and the True Skill Score from this prediction is ~20%. Eventhough this achieved score is considerably low, it is proportionally comparable with respect to the other work.

 

Prediksi flare dan lontaran massa korona (coronal mass ejection, CME) perlu dilakukan mengingat kedua peristiwa energetik tersebut dapat mempengaruhi cuaca antariksa di Bumi secara efektif. Pada studi kali ini, kami menganalisis empat parameter magnetik daerah aktif: (1) rerata gradien medan horisontal (meangbh), (2) rerata arus puntir (meanjzh), (3) rerata gradien medan magnet total (meangbt), dan (4) rerata energi magnetik bebas fotosfer (meanpot) serta potensinya untuk sebagai input dalam prediksi CME berbasis statistik linier. Hasilnya, diantara keempat parameter tersebut, meangbt merupakan parameter terbaik untuk keperluan tersebut. Daerah aktif dengan meangbt ≤ 96 Gauss/Mm berpotensi menghasilkan flare yang disertai CME dan True Skill Score dari prediksi ini adalah ~20%. Meski masih tergolong rendah, skor yang didapatkan dapat disandingkan secara proporsional dengan pekerja oleh peneliti lain.

Keywords

lontaran massa korona, probabilitas statistik, parameter statistik, daerah aktif

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DOI: http://dx.doi.org/10.30536/j.jsd.2020.v17.a3007

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