Abstract
Predictors of magnetoionospheric disturbances occurring in phenomena in the Sun and in the solar wind and allowing one to forecast the probability of the occurrence of magnetoionospheric disturbances are described. In the study of the relation between ionospheric and magnetic storms, an empirical dependence of the beginning, intensity, and duration of ionospheric disturbances on magnetic ones is established. Methods of global representation of spatiotemporal variations in parameters of the F2 layer during disturbances with the use of both empirical and physical models are considered. The possibility of using a simplified single-ion model consisting of a system of two differential equations for NmF2 and hmF2 in short-term forecasting of maximum parameters of the F2 layer of the middle-latitude ionosphere is demonstrated. The input parameters of the model are the coordinates, solar and magnetic activity, as well as prediction of the beginning, type, and intensity of the disturbance. Correction in the forecast is performed by the drift velocity and recombination coefficient according to current observations. The materials accumulated by this model are compared with forecasts using the empirical model constructed in the Institute of Terrestrial Magnetism, Ionosphere, and Radiowave Propagation, Russian Academy of Sciences, by identifying regular disturbed variations. It is shown that the accuracies of these models are comparable. Based on statistical analysis of histograms of δ foF2, it is shown that the distribution law for the population of δ foF2 during disturbances is far from normal. A method of interpreting experimental probability density functions by the model with kurtosis and skewness constructed based on the Poisson random process both for data with an hourly resolution and by more frequent 5-min observations is proposed. The main stages of the further development of short-term ionospheric forecasting based on numerical theoretical models of the ionosphere are proposed.
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Sergeenko, N.P. A Short-Term Forecast for Parameters of the F2 Layer. Geomagn. Aeron. 62, 724–736 (2022). https://doi.org/10.1134/S0016793222060135
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DOI: https://doi.org/10.1134/S0016793222060135