Abstract

The occurrence of post-sunset equatorial spread-F (ESF) could have detrimental effects on trans-ionospheric radio wave propagation used in modern communications systems. This problem calls for a simple but robust model that accurately predicts the occurrence of post-sunset ESF. Logistic regression was implemented to model the daily occurrence of post-sunset ESF as a function of the evening upward plasma drift (v). The use of logistic regression is formalized by y^=1/[1+exp(−z)], where y^ represents the probability of post-sunset ESF occurrence, and z is a linear function containing v. The value of v is derived from the vertical motion of the bottom side of the F-region in the evening equatorial ionosphere, which is observed by the ionosondes in Southeast Asia. Data points (938) of v and post-sunset ESF occurrence were collected in the equinox seasons from 2003 to 2016. The training set used 70% of the dataset to derive z and y^ and the remaining 30% was used to test the performance of y^. The expression z=−2.25+0.14v was obtained from the training set, and y^≥0.5 (v ≥ ~16.1 m/s) and y^<0.5 (v < ~16.1 m/s) represented the occurrence and non-occurrence of ESF, respectively, with an accuracy of ~0.8 and a true skill score (TSS) of ~0.6. Similarly, in the testing set, y^ shows an accuracy of ~0.8 and a TSS of ~0.6. Further analysis suggested that the performance of the z-function can be reliable in the daily F10.7 levels ranging from 60 to 140 solar flux units. The z-function implemented in the logistic regression (y^) found in this study is a novel technique to predict the post-sunset ESF occurrence. The performance consistency between the training set and the testing set concludes that the z-function and the y^ values of the proposed model could be a simple and robust mathematical model for daily nowcasting the occurrence or non-occurrence of post-sunset ESFs.

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