The data from the vertical ionospheric sounding for 12 stations over the world were analyzed to find the relation between the values of foF2 for 02:00 LT and 14:00 LT of the same day. It is found that, in general, there exists a negative correlation between foF2(02) and foF2(14). The value of the correlation coefficient R(foF2) can be in some cases high enough and reach minus 0.7–0.8. The value...

The critical frequency of the F2-layer (foF2) is an important parameter in estimating the total electron content (TEC) of the ionosphere, which is necessary for predicting the ionospheric time delay in GPS applications. The foF2 data from Ahmedabad, which is in the equatorial anomaly region, are modelled using a multilayer neural network trained with back-propagation algorithm. The IRI-2001 mod...

This paper presents the application of Neural Networks for the spatial and temporal modeling of (critical frequency) foF2 data over Europe. foF2 is the most important parameter in describing the electron density profile of the ionosphere since it represents the critical point of maximum electron density in the profile and therefore can be used to drive empirical models of electron density which...

Earlier revealed morphological features of the foF2 and hmF2 long-term trends are interpreted in the scope of the geomagnetic control concept based on the contemporary F2-layer storm mechanisms. The F2-layer parameter trends strongly depend on the long-term varying geomagnetic activity whose effects cannot be removed from the trends using conventional indices of geomagnetic activity. Therefore,...

This paper deals with two problems, methods of foF2 trend determination and origin of trends in foF2, both being controversial in current literature. We found that various regression-based methods and artificial neural networkbased method of Yue et al. (2006) provided comparable results within uncertainties caused mainly by various ways of removing/suppressing the dominant solar cycle effect. T...

This paper presents the application of Neural Networks for the interpolation of (critical frequency) foF2 data over Cyprus in the presence of sporadic E layer which is a frequent phenomenon during summer months causing inevitable gaps in the foF2 data series. This ionospheric characteristic (foF2) constitutes the most important parameter in HF (High Frequency) communications since it is used to...

A short-term ionospheric forecasting empirical regional model (IFERM) has been developed to predict the state of the critical frequency of the F2 layer (foF2) under different geomagnetic conditions. IFERM is based on 13 short term ionospheric forecasting empirical local models (IFELM) developed to predict foF2 at 13 ionospheric observatories scattered around the European area. The forecasting p...

1 Institute of Statistics, National Central University, Chung-Li, Taiwan, ROC 2 Institute of Space Science, National Central University, Chung-Li, Taiwan, ROC 3 Center for Remote Sensing and Space Researches, National Central University, Chung-Li, Taiwan, ROC 4 Institute of Geophysics, National Central University, Chung-Li, Taiwan, ROC * Corresponding author address: Dr. Yuh-Ing Chen, Institute...

Solar cycle variations of the amplitudes of the 27day solar rotation period reflected in the geomagnetic activity index Ap, solar radio flux F10.7 cm and critical frequency foF2 for mid-latitude ionosonde station Moscow from the maximum of sunspot cycle 18 to the maximum of cycle 23 are examined. The analysis shows that there are distinct enhancements of the 27-day amplitudes for foF2 and Ap in...

[1] This study explores the saturation effects in the ionospheric foF2 due to sunspot number R, solar radio noise (10.7 cm) flux F10.7, and solar EUV fluxes. To locate the R, F10.7, or EUV value at which the foF2 values are saturated, a two-segmented regression model is built based on the data of the strictly rise period of the 21st solar cycle recorded by eight ionosonde stations scattering ro...