Prediction of NmF2 in the polar ionosphere under disturbance conditions
A new prediction model of the ionospheric F2 layer peak electron density(NmF2)during geomagnetic disturbances for 1 hour is developed,using long-term ionospheric observation data from Zhongshan Station in Antarctica and Tromsø Station in Arctic.The machine learning model named PLPR is based on the time series prediction model Prophet,Long Short-Term Memory(LSTM)and polynomial regression.The predic-tions produced by PLPR can better reflect the daily variations of NmF2 at both stations than can those from other models,and the prediction accuracy at Zhongshan Station is better than that at Tromsø Station.Com-pared with the international reference ionosphere IRI-2016 model,as well as the single time series prediction model Prophet and LSTM,the PLPR model demonstrates superior performance.
polar region ionospheregeomagnetic disturbancesF2 layer peak electron density(NmF2)ionospheric parameter prediction
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