Thermospheric Density Prediction Based on Electron Density Assimilation

Using the thermosphere ionosphere coupling model TIEGCM and the thermospheric and ionospheric observations, the assimilation and forecast experiments with simulated and measured data are carried out based on the ensemble Kalman filter method respectively. The results of the simulated assimilation experiments with different thermospheric ionospheric parameters show that the temperature is the key parameter to improve the thermospheric density. In the assimilation experiments, the temperature is taken as the parameter of state vector. The optimization results show that the root mean square error of relative deviation of atmospheric density predicted by the model is reduced from 38% to 27% in 48 hours, and the stabilization time of assimilation is at least 30 hours. However, it may need at least 30 hours to achieve the best assimilation results when only the temperature is estimated, and the e-folding time of neutral density is 34 hours. The accuracy of the neutral density prediction in the TIEGCM has been significantly improved, which indicates that it is feasible to improve the prediction accuracy of the neutral density of the thermosphere using ionospheric observations