Common solar wind drivers behind magnetic storm\u2013magnetospheric substorm dependency

Jakob Runge,Georgios Balasis,Constantinos Papadimitriou,Reik V Donner,Ioannis A Daglis

doi:10.1038/s41598-018-35250-5

Abstract

The dynamical relationship between magnetic storms and magnetospheric substorms is one of the most controversial issues of contemporary space research. Here, we address this issue through a causal inference approach to two corresponding indices in conjunction with several relevant solar wind variables. We find that the vertical component of the interplanetary magnetic field is the strongest and common driver of both storms and substorms. Further, our results suggest, at least based on the analyzed indices, that there is no statistical evidence for a direct or indirect dependency between substorms and storms and their statistical association can be explained by the common solar drivers. Given the powerful statistical tests we performed (by simultaneously taking into account time series of indices and solar wind variables), a physical mechanism through which substorms directly or indirectly drive storms or vice versa is, therefore, unlikely.

Highlights

The identification of spurious associations and potentially causal relationships is key to an improved process-based understanding of various geoscientific processes
This multivariate measure for the influence of a subprocess X of a system on another subprocess Y is called information transfer to Y (ITY) and allows for more powerful tests on the absence or potential presence of a causal relationship, which is crucial for developing a better “mechanistic” understanding of the governing processes
DeMichelis et al.[13] found, on average, a net information flow from AL to SYM-H attaining its maximum at a typical time delay of about 1 h which is well resolved with our chosen time resolution

Summary

Introduction

The identification of spurious associations and potentially causal relationships is key to an improved process-based understanding of various geoscientific processes. DeMichelis et al suggested that information flow from AL to SYM-H dominates in the case of small geomagnetic disturbances, while the reverse situation is observed in presence of strong geomagnetic disturbances Bivariate measures such as mutual information (MI) or bivTE do not allow to exclude the very frequent influence of other variables as common drivers, rendering MI and bivTE associations spurious. We contrast bivariate measures with a directional, multivariate information-theoretic causality measure based on low-dimensionally estimated graphical models[17,18,19] This multivariate measure for the influence of a subprocess X of a system on another subprocess Y is called information transfer to Y (ITY) and allows for more powerful tests on the absence or potential presence of a causal relationship, which is crucial for developing a better “mechanistic” understanding of the governing processes. Our goal is to clarify whether substorm activity could causally drive storm dynamics or – on the contrary – whether solar wind variables can explain the statistical associations between storm and substorm activity

Objectives

Methods

Results

Discussion

Conclusion