On the relation of the AE and PC indices

It is shown that although the power spectra of the AE and PC data are quite similar, they appear different in the structure function (SF) analysis. Wh ile the AE time series has a clear drop in the slope of the SF after the fi rst 2 hours, the slope of the SF of the PC data only decreases gradually, a nd at a somewhat longer timescale. It is also shown by using 15-min average d data, that both SFs are periodic with a clear diurnal variation. The PC t ime series seems to have a more pronounced periodicity, probably because it is measured at a single station at Thule. The relation between the PC and AE indices has been analyzed in detail. The cross-correlation time between these data is shown to be 2-2.5 hours. It appears that the correlation func tion has two different scaling regions, one at the timescale within 2.5 hou rs and another between 2.5 and 12 hours. It also seems that a neural networ k prediction of the AE index from the PC: index is only possible for time s cales shorter than the cross-correlation time of these systems. The AE inde x has been derived from the PC index for 7.5 min ahead. These predictions g ave normalized mean square errors (NMSE) in the range 0.18-0.25 during wint ertime. The corresponding correlation coefficient was 0.91 at the best. Thi s shows that well within the cross-correlation time, the AE time series can be derived quite accurately from the PC data, at least during wintertime w hen the field-aligned currents are the main source of the PC index.