Abstract
We investigate the drivers of 40–150 keV hourly electron flux at geostationary orbit (GOES 13) using autoregressive moving average transfer functions (ARMAX) multiple regression models which remove the confounding effect of diurnal cyclicity and allow assessment of each parameter independently. By taking logs of the variables, we create nonlinear models. While many factors show high correlation with flux in single variable analysis (substorms, ULF waves, solar wind velocity (V), pressure (P), number density (N) and electric field (E y ), IMF Bz, Kp, and SymH), ARMAX models show substorms are the dominant influence at 40–75 keV and over 20–12 MLT, with little difference seen between disturbed and quiet periods. The Ey influence is positive post‐midnight, negative post‐noon. Pressure shows a negative influence, strongest at 150 keV. ULF waves are a more modest influence than suggested by single variable correlation. Kp and SymH show little effect when other variables are included. Using path analysis, we calculate the summed direct and indirect influences through the driving of intermediate parameters. Pressure shows a summed direct and indirect influence nearly half that of the direct substorm effect. N, V, and B z , as indirect drivers, are equally influential. While simple correlation or neural networks can be used for flux prediction, neither can effectively identify drivers. Instead, consideration of physical influences, removing cycles that artificially inflate correlations, and controlling the effects of other parameters gives a clearer picture of which are most influential in this system.
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