An Adaptive Forecasting Method for Ionospheric Critical Frequency of F2 Layer

Abstract

AbstractTo achieve further improvements in quantitative predictability, a chaos‐based adaptive forecasting method for the critical frequency of the F2 layer (foF2) is proposed for the development of an ionospheric forecasting technique for one hour ahead. This method has three new characteristics. (1) It is based on Volterra filters and it has a simplified structure with easy implementation. (2) Based only on past measured data, it can forecast foF2 values without the requirement for past or forecast values of any solar and geomagnetic indices. (3) It can achieve high forecast accuracy with a small training dataset of 27 days (one solar rotation period). Diurnal, seasonal, and annual comparisons of measured and forecasted foF2 values are presented to illustrate the applicability and suitability of the proposed method. Statistical results reveal that the foF2 values calculated using the proposed model are consistent with the trend of measurements irrespective of whether geomagnetic conditions are quiet or disturbed. The average RMSE and RRMSE values were 0.86 MHz and 17.36%, respectively, when using measured data from periods of past 27 days during 2008–2015. The proposed method has potential to forecast other ionospheric characteristic parameters, and that it could achieve satisfactory regional or global 1‐hr forecasting if combined with a spatial reconstruction technique.