The development of a new auroral lower ionosphere model

This paper presents first results from the development of a new auroral latitude lower ionospheric model. The major difference between this new model and other models for the same region is that the technique of neural networks (NNs) was employed in the development. Data from the European Incoherent Scatter facility (EISCAT) combined with rocket measurements were used to provide a database of reliable lower ionosphere data from approximately 70 degrees geomagnetic. NN modelling requires a substantial database of reliable data with which the NN can learn the relationship between the input space and the output parameter. Combinations of various input parameters known to produce a response in the lower ionosphere were investigated as potential contributors to the input space. The final input space consisted of local magnetic time, riometer absorption, a local magnetic K index, the inverse Chapman function corresponding to the solar zenith angle, the 10.7 cm solar flux, and the pressure surface. The pressure surface is a representation of the seasonal variation and the altitude. The output was the electron density for the given set of input parameters at a particular pressure surface. Therefore, an average electron density profile describing the behaviour of the auroral lower ionosphere can be determined for a particular instance of the input space. A process of minimisation of mean squared errors was used to optimise the NNs. Predicted profiles are compared with actual data as well as existing ionospheric models. It will be shown that this model is capable of predicting realistic average electron density profiles for the high latitude lower ionosphere. In addition, the ability of this model to simulate the total absorption to within the resolution of a riometer will be demonstrated. It is the intention of the authors to provide this model in a suitable form for incorporation into the IRI model and therefore these results may be of interest to the IRI community.