A new global F2 peak electron density model for theInternational Reference Ionosphere (IRI)E.O. Oyeyemia,b,c, L.A. McKinnellb,c,*aDepartment of Physics, University of Lagos, Akoka Yaba, Lagos, NigeriabHermanus Magnetic Observatory, PO Box 32, Hermanus, 7200, South AfricacDepartment of Physics and Electronics, Rhodes University, PO Box 94, Grahamstown, 6140, South AfricaReceived 15 October 2007; received in revised form 18 October 2007; accepted 18 October 2007AbstractA new neural network (NN) based global empirical model for the F2 peak electron density (NmF2) has been developed usingextended temporal and spatial geophysical relevant inputs. Measured ground based ionosonde data, from 84 global stations, spanningthe period 1995 to 2005 and, for a few stations from 1976 to 1986, obtained from various resources of the World Data Centre (WDC)archives (Space Physics Interactive Data Resource SPIDR, the Digital Ionogram Database, DIDBase, and IPS Radio and Space Ser-vices) have been used for training a NN. The training data set includes all periods of quiet and disturbed magnetic activity. A compre-hensive comparison for all conditions (e.g., magnetic storms, levels of solar activity, season, different regions of latitudes, etc.) betweenfoF2 value predictions using the NN based model and International Reference Ionosphere (IRI) model (including both the InternationalUnion of Radio Science (URSI) and International Radio Consultative Committee (CCIR) coefficients) with observed values was inves-tigated. The root-mean-square (RMS) error differences for a few selected stations are presented in this paper. The results of the foF2 NNmodel presented in this work successfully demonstrate that this new model can be used as a replacement option for the URSI and CCIRmaps within the IRI model for the purpose of F2 peak electron density predictions.? 2008 COSPAR. Published by Elsevier Ltd. All rights reserved.Keywords: foF2; Ionosphere; Neural networks1. IntroductionMany researchers (Jones and Obitts, 1970; Rush et al.,1983, 1984; Fox and McNamara, 1988; Bilitza, 2001; Ful-ler-Rowell et al., 2000) have made significant efforts bothat developing and improving the existing global modelsfor ionospheric parameter predictions. Recently, the needfor an improved global model for the ionospheric parame-ters, most especially the International Union of Radio Sci-ence(URSI)andInternationalRadioConsultativeCommittee (CCIR) foF2 model options of the IRI, hasreceived serious attention by the International ReferenceIonosphere (IRI) community. This is due to the fact thata large volume of data has accumulated since the existingmodels were developed and also, that there are more anal-ysis techniques. The CCIR and URSI coefficients are basedon the worldwide ionosonde data for epochs 1954 and 1964(Bradley, 1990; Zolesi and Cander, 2000). Also, the Rushet al. (1983, 1984) coefficients are based on data from July1975 to June 1976 and July 1978 to July 1979. Significantefforts have been made in recent times to improve theIRI model. Recently, due to the work of Fuller-Rowellet al. (2000), a storm-time correction model has been amajor development for the updating of the F2 peak elec-tron density incorporated into the IRI model. The F2 peakelectron density plays a major role in high frequency (HF)radio wave communications and navigations.0273-1177/$34.00 ? 2008 COSPAR. Published by Elsevier Ltd. All rights reserved.doi:10.1016/j.asr.2007.10.031*Corresponding author. Address: Hermanus Magnetic Observatory,PO Box 32, Hermanus, 7200, South Africa.E-mail addresses: e_oyeyemi@yahoo.co.uk (E.O. Oyeyemi), L.McKin-nell@ru.ac.za (L.A. McKinnell).www.elsevier.com/locate/asrAvailable online at www.sciencedirect.comAdvances in Space Research 42 (2008) 645–658
