Research on ionospheric multisource data assimilation method

Multisource data assimilation is an important way which can be used for ionospheric weather nowcast and forecast. In this paper, parameterized ionospheric model(PIM) is chosen to be the background model as well as NeQuick model output is utilized to be the observations of the ground-based GNSS and COSMIC 2 occultation measurements. Error covariance matrix which spatial correlations are separable horizontally is given by a Gaussian in geophysical coordination. Kalman filter is used for ionospheric multisource data assimilation in China region. Assimilation results show that it can obtain a good estimation of total electron content (TEC) and ionospheric electron density (IDE) by ingesting the multisource data into the background model. The error of the TEC and IDE are significantly reduced after multisource data assimilation.