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Magnetic storms are the most prominent global manifestations of out‐of‐equilibrium magnetospheric dynamics. Investigating the dynamical complexity exhibited by geomagnetic observables can provide valuable insights into relevant physical processes as well as temporal scales associated with this phenomenon. In this work, we utilize several innovative data analysis techniques enabling a quantitative nonlinear analysis of the nonstationary behavior of the disturbance storm time ( D  s  t ) index together with some of the main drivers of its temporal variability, the  V  B  South  electric field component, the vertical component of the interplanetary magnetic field,  B   z  , and the dynamic pressure of the solar wind,  P  dyn . Using recurrence quantification analysis and recurrence network analysis, we obtain several complementary complexity measures that serve as markers of different physical processes underlying quiet and storm time magnetospheric dynamics. Our approach discriminates the magnetospheric activity in response to external (solar wind) forcing from primarily internal variability and highlights the case‐specific nature of interdependencies between the  D  s  t  index and its potential drivers that need to be accounted for in future improved space weather forecasting models.

Recurrence‐Based Quantification of Dynamical Complexity in the Earth's Magnetosphere at Geospace Storm Timescales