6533b857fe1ef96bd12b39a7

RESEARCH PRODUCT

Neural network prediction of the AE index from the PC index

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Abstract It is shown that although the power spectra of the AE and PC data are quite similar they show differencies in structure function analysis. While the AE time series has a clear drop in the slope of the structure function (SF) after the first 2 hours, the slope of the SF of the PC data decreases gradually and at a little longer time scale. It is also shown by using 15-min averaged data, that both SFs are periodic with a clear diurnal variation. The PC time series seems to have a more pronounced periodicity, probably because it is measured at a single station at Thule. The AE index has been derived from the PC index for 7.5 minutes ahead by different methods. All these predictions gave normalized mean square errors (NMSE) of the order of 0.22–0.25 during wintertime. The corresponding correlation coefficient was 0.88 at the best. This shows that the AE time series can be derived quite accurately from the PC data, at least during wintertime, when the field-aligned current are the main source of the PC index.