9-13 July 2012
Africa/Johannesburg timezone
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Neural Network Based M(3000)F2 Global Model: An Option for the M(3000)F2 module within the IRI Global Model

Presented by Mr. Samuel Iyen Jeffrey ORONSAYE on 10 Jul 2012 from 11:00 to 11:20
Type: Oral Presentation
Session: Space Science
Track: Track D2 - Space Science

Abstract

We present a new updated version of M(3000)F2 global model. M(3000)F2 represent the propagation factor of the F2 region of the ionosphere. It is the highest frequency at which a radio wave can be received over a distance of 3000 km after reflection in the ionosphere. It is closely related to the peak height of F2 region (hmF2) of the ionosphere. This new version was developed using artificial neural network technique. It is an update to the existing International Reference Ionosphere (IRI) model which has been found to be inadequate in representing the diurnal variation of the equatorial ionosphere. In particular, the existing M(3000)F2-based hmF2 model is unable to reproduce the sharp post-sunset drop of M(3000)F2 parameter, which correspond to a sharp post-sunset peak in hmF2. Data from 135 ionospheric stations worldwide, including a good number of equatorial stations were used in this model. The ability of this new model to predict M(3000)F2 parameter especially in the equatorial region, which is known to be problematic for the existing IRI model is demonstrated in this work. The improvement in the prediction of M(3000)F2 parameter by this new version as compared to the IRI model is demonstrated in this paper. Keywords: Ionosphere, M(3000)F2, Neural Networks

Award

Yes

Level

MSc

Supervisor

Dr. Lee-Anne McKinnell, LMcKinnell@sansa.org.za, South African National Space Agency & Rhodes University, Grahamstown.

Paper

Yes

Place

Location: IT 4-3


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