Simulating and Assimilating Ionospheric Observations with Multisources.

In this paper, using the International Reference Ionosphere model and the Global Core Plasma Model as the reference electron density field of the middle and bottom of ionosphere / the topside of the ionosphere and the plasmasphere respectively, ionospheric observational data from ground-based and spaceborne systems on Jan. 10th, 2008 were simulated. With the Nequick model as the initial field of the Kalman-filter(KF) algorithm, the global ionospheric density field was constructed by KF algorithm, and the subsequent works were processed.

• Various errors and influences in the inversion of the ionospheric data, especially easily overlooked errors, were analyzed,and corresponding improvement methods were proposed. From the statistics of vertical TEC and electron density deviations and RMSE( Root mean square of errpr ), after correcting the observed data, the assimilation results are significantly improved, which confirmed the effectiveness of the correction algorithm. These errors should be reduced before processing,and the time/grid correction can effectively and steadily improve the assimilation accuracy.

• The effects of constellation/system observations on the observation quality and spatial distribution configuration of the inversion of the ionospheric data were analyzed. The introduction of COSMIC occultation data can effectively fill the gaps in the ocean data and increase the ionospheric observational density and horizontal accuracy significantly.

• Finally, the characteristics of the Kalman filter assimilation algorithm and Abel inversion algorithm were compared, and it was showed that the Kalman filter assimilation algorithm has higher accuracy than the Abel-Retrieved method, especially in ionospheric peak altitude.

Recommended citation: Fu, N.; Guo, P.; Wu, M.; Huang, Y.; Hu, X.; Hong, Z. Simulating and Assimilating Ionospheric Observations with Multisources. Advances in Space Research 2019.