Abstract. In this study, we use mutual information to characterise statistical dependencies of seed and relativistic electron fluxes in the Earth's radiation belts on ultra low frequency (ULF) wave power measured on the ground and at geostationary orbit . The benefit of mutual information, in comparison to measures such as the Pearson correlation, lies in the capacity to distinguish nonlinear dependencies from linear ones. After reviewing the property of mutual information and its relationship with the Pearson correlation for Gaussian bivariates of arbitrary correlation, we present a methodology to quantify and distinguish linear and nonlinear statistical dependencies that can be generalised to a wide range of solar wind drivers and magnetospheric responses. We present an application of the methodology by revisiting the case events studied by Rostoker et al. (1998). Our results corroborate the conclusions of Rostoker et al. (1998) that ULF wave power and relativistic electron fluxes are statistically dependent upon one another. However, we find that observed enhancements in relativistic electron fluxes correlate modestly, both linearly and nonlinearly, with the ULF power spectrum when compared with values found in previous studies (Simms et al., 2014), and with values found between seed electrons and ULF wave power for the same case events. Our results are indicative of the importance in incorporating data analysis tools that can quantify and distinguish between linear and nonlinear interdependencies of various solar wind drivers.
Responses of Earth's radiation belts to solar wind dynamic pressure variations in 2002 analyzed using multisatellite data and Kalman filtering
