Mizrahi, E.

Total Electron Content (TEC) is an important characteristic of the ionosphere relevant to communications. Unpredictable variability of the ionospheric parameters due to various disturbances limits the efficiencies of communications, radar and navigation systems. Therefore forecasting and nowcasting of TEC are important in the planning and operation of Earth-space and satellite-to-satellite communication systems. Near-Earth space processes are complex being highly nonlinear and time varying with random variations in parameters where mathematical modeling is extremely difficult if not impossible. Therefore data driven models such as Neural Network (NN) based models are considered and found promising in modeling such processes. In this paper the NN based METU-NN model is introduced to forecast TEC values for the intervals ranging from 1 to 24 h in advance. Forecast and nowcast of TEC values are also considered based on TEC database. Day-to-day and hour to-hour variability of TEC are also estimated using statistical methods. Another statistical approach based on the clustering technique is developed and a preprocessing approach is demonstrated for the forecast of ionospheric critical frequency foF2.

The «prediction» and «forecast» of the critical frequency of the F 2 layer (f0 F2 ) is an important issue for frequency planning in short wave radio communications. In this context, «prediction» is used for the determination of monthly median values of f0 F2 for each hour, while «forecast» denotes the determination of hourly values. In a previous paper we proposed a «sliding window» technique for prediction combined with «feedback» for forecast (Bilge and Tulunay, 2000). In the present paper we obtain the variation of the feedback coefficient with R 12 and geographic latitude.

The deviations of hourly f 0 F 2 from monthly medians for 20 stations in Europe during the period 1958-1998 are studied. Spectral analysis is used to show that, both for original data (for each hour) and for the deviations from monthly medians, the deterministic components are the harmonics of 11 years (solar cycle), 1 year and its harmonics, 27 days and 12 h 50.49 m (2nd harmonic of lunar rotation period L 2 ) periodicities. Using histograms for one year samples, it is shown that the deviations from monthly medians are nearly zero mean (mean < 0.5) and approximately Gaussian (relative difference range between %10 to %20) and their standard deviations are larger for daylight hours (in the range 5-7). It is shown that the amplitude distribution of the positive and negative deviations is nearly symmetrical at night hours, but asymmetrical for day hours. The positive and negative deviations are then studied separately and it is observed that the positive deviations are nearly independent of R12 except for high latitudes, but negative deviations are modulated by R12 . The 90% confidence interval for negative deviations for each station and each hour is computed as a linear model in terms of R12. After correction for local time, it is shown that for all hours the confidence intervals increase with latitude but decrease above 60N. Long-term trend analysis showed that there is an increase in the amplitude of positive deviations from monthly means irrespective of the solar conditions. Using spectral analysis it is also shown that the seasonal dependency of negative deviations is more accentuated than the seasonal dependency of positive deviations especially at low latitudes. In certain stations, it is also observed that the 4th harmonic of 1 year corresponding to a periodicity of 3 months, which is missing in f 0 F 2 data, appears in the spectra of negative variations.