Estimation of Polar Cap Potential and the Role of PC Index

Polar cap potential has long been considered as an indicator for the amount of energy flowing in the magnetosphere-ionosphere system. Thus, the estimation of polar cap potential is important to understand the physical process of the magnetosphere. To estimate the polar cap potential in the Northern Hemisphere, merging electric field by Kan & Lee (1979) is adopted. Relationships between the PC index and calculated merging electric field ($E^*$) are examined during full-time and storm-time periods separately. For this purpose Dst, AL, and PC indices and solar wind data are utilized during the period from 1996-2003. From this linear relationship, polar cap potential (${\Phi}^*$) is estimated using the formula by Doyle & Burke (1983). The values are represented as $58.1{\pm}26.9$ kV for the full-time period and $123.7{\pm}84.1$ kV for a storm-time period separately. Considering that the average value of polar cap potential of Doyle & Burke (1983) is about 47 kV during moderately quiet intervals with the S3-2 measurements, these results are similar to such. The monthly averaged variation of Dst, AL, and PC indices are then compared. The Dst and AL indices show distinct characteristics with peaks during equinoctial season whereas the average PC index according to the month shows higher values in autumn than in spring. The monthly variations of the linear correlation coefficients between solar wind parameters and geomagnetic indices are also examined. The PC-AL linear correlation coefficient is highest, being 0.82 with peaks during the equinoctial season. As with the AL index, the PC index may also prove useful for predicting the intensity of an auroral substorm. Generally, the linear correlation coefficients are shown low in summer due to conductance differences and other factors. To assess the role of the PC index during the recovery phase of a storm, the relation between the cumulative PC index and the duration is examined. Although the correlation coefficient lowers with the storm size, it is clear that the average correlation coefficient is high. There is a tendency that duration of the recovery phase is longer as the PC index increases.