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"