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An Adaptive Forecasting Method for Ionospheric Critical Frequency of F 2 Layer
Author(s) -
Wang Jian,
Feng Feng,
Ma Jianguo
Publication year - 2020
Publication title -
radio science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.371
H-Index - 84
eISSN - 1944-799X
pISSN - 0048-6604
DOI - 10.1029/2019rs007001
Subject(s) - predictability , earth's magnetic field , ionosphere , critical frequency , meteorology , mathematics , environmental science , statistics , geology , physics , geophysics , quantum mechanics , magnetic field
To achieve further improvements in quantitative predictability, a chaos‐based adaptive forecasting method for the critical frequency of the F 2 layer ( f o F 2 ) 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 f o F 2 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 f o F 2 values are presented to illustrate the applicability and suitability of the proposed method. Statistical results reveal that the f o F 2 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.