Equatorial predictions from a new neural network based global foF2 model

A new neural network (NN) based global empirical model for the foF2 parameter, which represents the peak ionospheric electron density, has been developed using extended temporal and spatial geophysical relevant inputs. It has been proposed that this new model be considered as a suitable replacement...

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Bibliographic Details
Published in:Advances in space research 2010-10, Vol.46 (8), p.1016-1023
Main Authors: McKinnell, L.A., Oyeyemi, E.O.
Format: Article
Language:English
Subjects:
Equatorial ionosphere
foF2
IRI
Modeling
Neural networks
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Summary:A new neural network (NN) based global empirical model for the foF2 parameter, which represents the peak ionospheric electron density, has been developed using extended temporal and spatial geophysical relevant inputs. It has been proposed that this new model be considered as a suitable replacement for the International Union of Radio Science (URSI) and International Radio Consultative Committee (CCIR) model options currently used within the International Reference Ionosphere (IRI) model for the purpose of F2 peak electron density predictions. The most recent version of the model has incorporated data from 135 global ionospheric stations including a number of equatorial stations. This paper concentrates on the ability of this new model to predict foF2 for the equatorial sector, an area that has been identified as problematic within the current IRI peak prediction setup. The improvement in the predictions of the foF2 parameter by the new model as compared to the URSI and CCIR model options of the IRI is demonstrated and the requirement for additional foF2 data from the equatorial zone for the purpose of global modeling of foF2 is highlighted in this paper.
ISSN:0273-1177
1879-1948
DOI:10.1016/j.asr.2010.06.003