A method for f0F2 monitoring over Spain using the El Arenosillo digisonde current observations

Abstract

Ionosphere monitoring implies: observations, prediction and mapping of ionospheric parameters. A case with one available (El Arenosillo) ionosonde is considered. Some statistical methods for f0F2 short-term (1-24 h in advance) prediction are compared. The analysis of multi-dimensional regression for Df0F2 (relative deviation from running median) with Ap, F10.7 and previous Df0F2 observations has shown that inclusion of additional terms with Ap and F10.7 improves the prediction accuracy for lead time more than 15 h. For lead time 1-6 h a linear regression with earlier observed Df0F2 provides the f0F2 forecast with Relative Mean Deviation (RMD) 6-11%. This is acceptable from a practical point of view. A 24-h forecast can be done with RMD 10-11%. Multi-regressional methods provide better prediction accuracy than the usual 10-day running median or quasi-inertial method based on such median. Hourly f0F2 values may be used to calculate the effective index R12eff used as input to the ITU-R monthly median model. This allows the ITU-R model to "breathe" following hour-to-hour f0F2 variations. Then standard surfering methods may be applied for f0F2 mapping over the whole area. The f0F2 mapping accuracy based on the hourly R12eff index is shown to be 9-11% depending on solar activity level.

Keywords

• Ionospheric F2 layer
• short-term prediction methods
• ionospheric mapping