An Adaptive Forecasting Method for Ionospheric Critical Frequency of F2 Layer.

To 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. Plain Language Summary: The critical frequency of F2 layer of ionosphere (foF2) is a very important characteristic parameter in various civil and military applications. To achieve further improvements in quantitative predictability, a chaos‐based adaptive forecasting method for foF2 is proposed for the development of an ionospheric forecasting technique for 1 hr ahead. This method has three advantages: simplified structure with easy implementation, high forecast accuracy with a small training dataset, and forecast without the requirement for any solar and geomagnetic indices. Comparisons between the measured and forecasting values of foF2 have shown the usability and appropriateness of the proposed method. Statistical results reveal that the foF2 calculated by the proposed model is consistent with the trend of the measurements whenever quiet and disturbed geomagnetic conditions. The average RMSE and RRMSE are 0.86 MHz and 17.36% using the past 27 days measured data during the year of 2008–2015. Moreover, the analysis results have proved the proposed method has the potential to forecasting any other ionospheric characteristic parameters and can achieve 1‐hr forecasting for global by combining spatial reconstruction technique. Key Points: Chaos and nonlinear dynamic theory have been applied to forecast foF2 short‐term variation valueThe forecasting procedure is achieved by chaotic space reconstruction and Volterra series adaptive filter techniqueThe proposed method has good accuracy in terms of forecasting values of foF2 with 27‐day training data [ABSTRACT FROM AUTHOR]