Field Line Resonances estimated using Machine Learning methods

This data set contains the machine learning input matrix (composed by 1D Fourier cross-spectra) + additional information, for the Classification algorithm implemented in Foldes et al. (Automatic Detection of Field Line Resonance Frequencies in the Earth’s Plasmasphere, 2023) for the pair of station Tartu-Birzai (TAR-BRZ).

Each file contains the following header at line 1. Columns are:

- P(f0)-P(f211): Cross-phase value per frequency bin

- YEAR

- DOY (Day Of Year)

- HOUR

- ToD_flag: "Umbra", "Penumbra", 'Light'

- L: McIllwain parameter

- stat_tag: "tarbrz"

- Kp

- Kp_w_05d: Kp index weighted on a 12hrs time window

- Kp_w_10d: Kp index weighted on a 24hrs time window

- Kp_w_15d: Kp index weighted on a 36hrs time window

- Kp_w_20d: Kp index weighted on a 2-day time window

- Kp_w_25d: Kp index weighted on a 2.5-day time window

- Kp_w_30d: Kp index weighted on a 3-day time window

- Kp_m_05d: Kp index max on a 12hrs time window

- Kp_m_10d: Kp index max on a 24hrs time window

- Kp_m_15d: Kp index max on a 36hrs time window

- Kp_m_20d: Kp index max on a 2-day time window

- Kp_m_25d: Kp index max on a 2.5-day time window

- Kp_m_30d: Kp index max on a 3-day time window

- DST

- DST_m_05d: DST index min on a 12hrs time window

- DST_m_10d: DST index min on a 24hrs time window

- DST_m_15d: DST index min on a 36hrs time window

- DST_m_20d: DST index min on a 2-day time window

- DST_m_25d: DST index min on a 2.5-day time window

- DST_m_30d: DST index min on a 3-day time window

- F107: F10.7 solar activity proxy

- EField: Earth Electric co-rotation field

- f(mHz): FLR frequency in mHz

- df(mHz): Uncertainty on the validated frequency

- class: 0 for "NoFreq", 1 for "Freq" and 2 for "PBL"