Abstract
A nonlinear optimization algorithm coupled with a model of auroral current systems allows derivation of physical parameters from data and is the basis of a new inversion technique. We refer to this technique as automated forward modeling (AFM), with the variant used here being automated meridian modeling (AMM). AFM is applicable on scales from regional to global, yielding simple and easily understood output, and using only magnetic data with no assumptions about electrodynamic parameters. We have found the most useful output parameters to be the total current and the boundaries of the auroral electrojet on a meridian densely populated with magnetometers, as derived by AMM. Here, we describe application of AFM nonlinear optimization to magnetic data and then describe the use of AMM to study substorms with magnetic data from ground meridian chains as input. AMM inversion results are compared to optical data, results from other inversion methods, and field-aligned current data from AMPERE. AMM yields physical parameters meaningful in describing local electrodynamics and is suitable for ongoing monitoring of activity. The relation of AMM model parameters to equivalent currents is discussed, and the two are found to compare well if the field-aligned currents are far from the inversion meridian.
Highlights
The interpretation of ground magnetic data has long been realized as having an important role in understanding physical processes in near-Earth space
The role of initial parametrization or “an initial guess for parameter values” can be important. All of these factors play a role in the functional division of automated forward modeling (AFM) into global (AGM), regional (ARM), and meridian (AMM) approaches, which share a compute module but have different constraints, weighting, and initial condition requirements
Having outlined how AFM can be applied to inversion of magnetic data, we present its use in event studies where the automated meridian modeling (AMM) variant can be applied to inversion in single meridians
Summary
The interpretation of ground magnetic data has long been realized as having an important role in understanding physical processes in near-Earth space. Connors and Rostoker Earth, Planets and Space (2015) 67:155 physical quantities would be, for example, the current strength and latitudinal location of the auroral electrojets These are useful parameters to allow computation of a model, and they clearly correspond, at least at some level of approximation, to physical quantities, based on longstanding (Boström 1964) knowledge. We describe a new method of optimizing a simple forward model involving auroral zone currents, including field-aligned currents (FACs), for inversion of magnetic data alone, without the use of electrodynamic quantities such as conductivity. We proceed to discuss our method in detail and give examples in which the output parameters are useful in understanding auroral events
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