Temporal organization of magnetospheric fluctuations unveiled by recurrence patterns in the Dst index

Magnetic storms constitute the most remarkable large-scale phenomena of nonlinear magnetospheric dynamics. Studying the dynamical organization of macroscopic variability in terms of geomagnetic activity index data by means of complexity measures provides a promising approach for identifying the underlying processes and associated time scales. Here, we apply a suite of characteristics from recurrence quantification analysis (RQA) and recurrence network analysis (RNA) in order to unveil some key nonlinear features of the hourly Disturbance storm-time (Dst) index during periods with magnetic storms and such of normal variability. Our results demonstrate that recurrence-based measures can serve as excellent tracers for changes in the dynamical complexity along non-stationary records of geomagnetic activity. In particular, trapping time (characterizing the typical length of “laminar phases” in the observed dynamics) and recurrence network transitivity (associated with the number of the system’s effective dynamical degrees of freedom) allow for a very good discrimination between magnetic storm and quiescence phases. In general, some RQA and RNA characteristics distinguish between storm and non-storm times equally well or even better than other previously considered nonlinear characteristics like Hurst exponent or symbolic dynamics based entropy concepts. Our results point to future potentials of recurrence characteristics for unveiling temporal changes in the dynamical complexity of the magnetosphere. Geomagnetic activity indices trace the temporal variability of the Earth’s magnetic field across different spatial domains of the near-Earth environment. Among others, the Disturbance storm-time (Dst) index has been used in many previous studies as a diagnostic of the overall state of the magnetosphere. Here, we employ different techniques based upon the concept of recurrence plots to improve our understanding of the complex variability patterns exhibited by this index when the geomagnetic field undergoes a sequence of magnetic storm and quiescence periods triggered by non-stationary solar wind forcing. We demonstrate that recurrence characteristics provide unique tools for discriminating between the dynamical complexity properties of Dst during times with strong geomagnetic activity and quiescence phases. Thus, future applications of these measures to other geomagnetic activity indices with higher temporal resolution may potentially allow us to identify characteristic signatures of complexity variations preceding intense magnetic storms, which could open new perspectives for space weather short-term forecasting