Predicting Lower Band Chorus With Autoregressive‐Moving Average Transfer Function (ARMAX) Models. Issue 7 (30th July 2019) - Simms, Laura E.; Engebretson, Mark J.; Rodger, Craig J.; Gjerloev, Jesper W.; Reeves, Geoffrey D.
Abstract: We model lower band chorus observations from the DEMETER satellite using daily and hourly autoregressive‐moving average transfer function (ARMAX) equations. ARMAX models can account for serial autocorrelation between observations that are measured close together in time and can be used to predict a response variable based on its past behavior without the need for recent data. Unstable distributions of radiation belt source electrons (tens of keV) and the substorm activity (SMEd from the SuperMAG array) that is thought to inject these electrons were both statistically significant explanatory variables in a daily ARMAX model describing chorus. Predictions from this model correlated well with observations in a hold‐out test data set (validation correlation of 0.675). Source electron flux was most influential when observations came from the same day or the day before the chorus measurement, with effects decaying rapidly over time. Substorms were more influential when they occurred on previous days, presumably due to their injecting source electrons from the plasma sheet. A daily ARMAX model with interplanetary magnetic field (IMF)| B |, IMF B z, and solar wind pressure as inputs instead of those given above was somewhat less predictive of chorus ( r =0.611). An hourly ARMAX model with only solar wind and IMF inputs was even less successful, with a validation correlation of 0.502. Key Points: Empirically based autoregressive‐moving average transfer function models predict daily‐averaged lower band chorus power well Validation correlation between chorus observations and predictions using source electron flux and substorm activity as inputs was 0.675 Source electron flux showed an immediate influence on chorus, while substorms were influential over many days