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    The effect of geomagnetic activity changes on the ionospheric critical frequencies (foF2) at magnetic conjugate points
    (Elsevier Sci Ltd, 2018) Timocin, Erdinc; Unal, Ibrahim; Tulunay, Yurdanur; Goker, Umit Deniz
    In this work, we investigate the possible effects of geomagnetic activity on the ionospheric critical frequencies (foF2) in geomagnetic conjugate points. For this purpose, hourly foF2 data measured for the year 1976 from the ionosonde stations Akita, St. John's and Resolute Bay in the Northern hemisphere and their corresponding magnetic conjugate ionosonde stations Brisbane, Halley Bay and Scott Base in the Southern hemisphere are examined. Planetary geomagnetic activity 3h-K-p indices are used as a geomagnetic activity indicator. foF2 data in the magnetic conjugate points (MCP) are investigated by using a superposed epoch analysis method. This analysis is done depending on the response of foF2 to geomagnetic activity variations in MCP based on geomagnetic stormy days around equinoxes (March 21, September 23) and solstices (June 21, December 21), and the results obtained from these MCP are compared. From these results, it is found that foF2 values in magnetic conjugate pairs give similar reactions to geomagnetic activity variations simultaneously, although this relationship differs according to the seasons and magnetic latitudes of the stations. (C) 2018 COSPAR. Published by Elsevier Ltd. All rights reserved.
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    Performance of IRI-based ionospheric critical frequency calculations with reference to forecasting
    (Amer Geophysical Union, 2011) Unal, Ibrahim; Senalp, Erdem Turker; Yesil, Ali; Tulunay, Ersin; Tulunay, Yurdanur
    Ionospheric critical frequency (foF2) is an important ionospheric parameter in telecommunication. Ionospheric processes are highly nonlinear and time varying. Thus, mathematical modeling based on physical principles is extremely difficult if not impossible. The authors forecast foF2 values by using neural networks and, in parallel, they calculate foF2 values based on the IRI model. The foF2 values were forecast 1 h in advance by using the Middle East Technical University Neural Network model (METU-NN) and the work was reported previously. Since then, the METU-NN has been improved. In this paper, 1 h in advance forecast foF2 values and the calculated foF2 values have been compared with the observed values considering the Slough (51.5 degrees N, 0.6 degrees W), Uppsala (59.8 degrees N, 17.6 degrees E), and Rome (41.8 degrees N, 12.5 degrees E) station foF2 data. The authors have considered the models alternative to each other. The performance results of the models are promising. The METU-NN foF2 forecast errors are smaller than the calculated foF2 errors. The models may be used in parallel employing the METU-NN as the primary source for the foF2 forecasting.