The Assimilative Mapping of Ionospheric Electrodynamics (AMIE) model is an inversion technique that ingests data from a wide range of sources to produce a realistic representation of the high latitude electrodynamic state for a given time (Richmond and Kamide, 1988; Richmond, 1992). The data inputs typically include electric fields derived from ion velocities measured using radars and satellites, together with magnetic perturbations from ground- and space-based instruments. Using these data, the distribution of various electrodynamic parameters such as the electric potential and electric field can be derived through the electrodynamic equations. The AMIE code is run routinely at ASTRA on a 5-minute cadence, ingesting ground-based magnetometer, SuperDARN, and DMSP E-field data.
IDA4D (Bust et al., 2000; Bust et. al, 2004) is a procedure which combines model output with actual measurement data. The algorithm organizes the data into spatial maps of electron density via an objective analysis technique, based upon three dimensional variational (3DVAR) data assimilation (Daley and Barker, 2001; Daley, 1991). These spatial maps are projected forward in time through a simple electron density continuity equation model, combined with a Gauss-Markov Kalman filter where they are used to initialize the next analysis. IDA4D takes into account data, data error covariances, a background model and the background model error covariances.
IDA4D is able to ingest any available observation of electron density or electron content.