Principles and Problems of Data Assimilation for High-Latitude Ionospheric Electrodynamics

Abstract:

Knowledge of the time-varying distributions of high-latitude ionospheric ionospheric electric fields and currents is needed for modeling the physics of the ionosphere and thermosphere. The patterns can also be used to investigate magnetospheric processes. The Assimilative Mapping of Ionospheric Electrodynamics (AMIE) procedure was developed to estimate the distributions of electrodynamic parameters from combinations of observations of ionospheric drifts, ground- and satellite-based magnetic perturbations, and quantities related to ionospheric electrical conductivities, together with prior information about climatology and covariance of the parameters. AMIE uses optimal estimation theory to build on previous statistical studies and on an earlier mapping procedure that used only ground magnetometer data. Many of the improvements made to AMIE have been the addition of new data sets and procedures for semi-automatically processing the data. Theoretical developments have included improvements to the organization of the data in realistic magnetic coordinates, and dynamic estimation of the covariance matrices based on the data available at any given time. More recently, it has been shown that most of the large-scale variability can be represented with a relatively small number of empirical orthogonal basis functions derived from statistical analysis of large data sets. A key remaining limitation of AMIE-type estimations is the limited knowledge of auroral ionospheric conductivities, including limited understanding of nonlinear conductivities when electric fields are very strong. Neutral winds have heretofore been neglected, but they can sometimes have significant effects on the electrodynamics.