The Delayed Time Response of Geomagnetic Activity to the Solar Wind

Abstract

We investigate the lagged correlation between a selection of geomagnetic indices and solar wind parameters for a complete solar cycle, from 2000 to 2011. We first discuss the mathematical assumptions required for such a correlation analysis. The solar wind parameters and geomagnetic indices have inherent timescales that smooth the variations of the correlation coefficients with time lag. Furthermore, the solar wind structure associated with corotating interaction regions and coronal mass ejections, and the compression regions ahead of them, strongly impacts the lagged correlation analysis results. This work shows that such bias must be taken into account in a correct interpretation of correlations. We then evidence that the magnetospheric response time to solar wind parameters involves multiple timescales. The simultaneous and quick response of the PC and AE indices to solar wind dynamic pressure with a delay of ~5 min suggests that magnetospheric compression by solar wind can trigger substorm activity. We find that the PC and AE indices respond to interplanetary magnetic field (IMF) BZ with a response time of respectively ~20 and ~35 min. The response of the SYM‐H index takes longer (~80 min) and is less sharp, SYM‐H being statistically significantly correlated to the IMF BZ observed up to more than ~10 h before. Our results suggest that the solar wind velocity's dominant impact on geomagnetic activity is caused by the compression regions at the interface of fast/slow solar wind regimes, which are very geo‐effective as they are associated with high solar wind pressure and strong interplanetary magnetic field.

Variation of Solar Wind Parameters Along With the Understanding of Energy Dynamics Within the Magnetospheric System During Geomagnetic Disturbances

“…The maximum correlation coefficient between the IMF-Bz and SYM-H is 0.9297 at time lag −170 min. This correlation coefficient value is quite different than that observed by Maggiolo et al (2017) where the coefficient value was 0.31 with time lag of 80 min. Such higher magnitude of correlation coefficient might have occurred due to the significant role played by IMF-Bz for the injection of energetic particles in this particular event, even though IMF-Bz is not sufficient condition for triggering of geomagnetic storm in most of the cases.…”

“…In contrast with the main phase, the length of recovery phase is normally long which can last as long as 3 days and is also longer than the duration of the interplanetary drivers igniting the storm itself (Yermolaev et al, 2012). Maggiolo et al (2017) where the coefficient value was 0.31 with time lag of 80 min. Figure 5 represents the energy dynamics of intense storm occurred on 30-31 May 2005.…”

Interplanetary Magnetic Field Control of Polar Ionospheric Equivalent Current System Modes

“…This allows us to also systematically test the hypothesis of Shore et al () that the dominant patterns of large‐scale variability in the ionospheric equivalent currents are describable as the historic disturbance‐polar systems. The delays in the effects of given IMF components on measurements or indices of the magnetosphere‐ionosphere system have been studied previously, for example, by Nishida and Maezawa (), Meng et al (), Baker et al (), Bargatze et al (), Browett et al (), and Maggiolo et al (). Our study is the first to systematically investigate the individual responses of the DP2, DPY, NBZ, and DP1 systems to IMF driving over the scale of a solar cycle.…”

On the Evaluation of Data Quality in the OMNI Interplanetary Magnetic Field Database

“…We analyze the cross‐correlation between the PC index (ground‐based polar cap magnetic index after Troshichev et al, ) and E KL SW driver computed using OMNI database. The idea behind such comparison is that the PC index, which has been constructed to characterize the intensity of twin‐vortices global magnetospheric convection, is known to show a prompt response and high correlation to the SW driver, particularly E KL (Maggiolo et al, ; Newell et al, ; Troshichev et al, ). Even more, the correlation between polar cap magnetic perturbations and E KL in the SW has been used in the procedure of PC index derivation to correct for seasonal and UT variations of effective ionospheric conductivity in the polar cap (see, e.g., Troshichev et al, ), so the PC is often considered as a possible ground‐based proxy for E KL parameter in the near‐Earth SW. To test PC capability as data quality estimator, we again compare its results with the data quality estimation based on Geotail‐OMNI comparison.…”