Learning from successful applications of methods originating in statistical mechanics or information theory in one scientific field (e.g. atmospheric physics or weather) can provide important insights or conceptual ideas for other areas (e.g. in the space sciences or beyond) or even stimulate new research questions and approaches. For instance, quantification and attribution of dynamical complexity in output time series of nonlinear dynamical systems is a key challenge across scientific disciplines. Especially in the field of space physics, an early and accurate detection of characteristic dissimilarity between normal and abnormal states (e.g. pre-storm activity vs. magnetic storms) has the potential to vastly improve space weather diagnosis and, consequently, the mitigation of space weather hazards.

The Swarm satellites of the European Space Agency (ESA) belong to a series of pioneering Earth Explorer research missions, providing a unique opportunity to simultaneously gain a better knowledge of the near-Earth electromagnetic environment and of its associated space weather effects. Information theory techniques have great potentials to identify previously unrecognized precursory structures and, thus, to contribute to a better understanding of the evolution of geomagnetic field perturbations along with extreme space weather phenomena like geospace magnetic storms. The associated nonlinear time series analysis methods like recurrence analysis, functional networks, and measures of statistical interdependence and causality can be used to disentangle the effects and response lag times of different solar wind drivers as well as characteristic observables of the near-Earth electromagnetic environment derived from spaceborne measurements that play important roles in the solar-terrestrial coupling. These approaches can provide a novel way to anticipating and predicting incipient transitions in the dynamical regime of geomagnetic field variations between quite-time and storm-time conditions.

In addition to improved space weather diagnosis and forecasting, we expect a better understanding of the relationship between magnetic storms and magnetospheric substorms by disentangling the manifold processes interlinking both types of geospace phenomena based also on findings recently published by members of our team. To achieve the aforementioned goals, the largely interdisciplinary international team (IT), combining expertise from both space physics and nonlinear physics communities, will thoroughly review and evaluate the applicability and efficiency of the novel data analysis tools to the Swarm multi-satellite mission at low-Earth orbit (LEO) in conjunction with relevant time series of solar wind variables and geomagnetic activity indices as well as long-term ground-based observations of the Earth’s magnetic field (SuperMAG network).

Other specific possible topics of investigation may include, but are not limited to: (i) Causes and effects of supersubstorms – Are they externally triggered, or only some of them? Why are they so intense? What are their local time and latitudinal locations? Can they affect power grids? (ii) The dayside superfountain caused by prompt penetrating electric fields during magnetic storms – It is well established that ionospheric ions are uplifted by E x B convection, however, a new question is: can the uplifted ions drag neutrals with them? If so, how much of a problem would this be for LEO satellites in terms of satellite drag? Ultimately, the results of the foreseen assignment will be available to the geomagnetism and space physics community for further incorporating data from the mission and newly gained process knowledge to existing space weather forecasting schemes, thus contributing to more accurate predictions of severe space weather phenomena.