Construction and implementation of a near-real-time global ionospheric data assimilation and forecasting system

Ionospheric weather changes are becoming one of the most important contents of space weather forecasting. The establishment of a reliable and accurate ionospheric characteristic parameter nowcast and forecast system is of great value to space scientific research and military and civilian radio frequency systems. Based on the real-time ground-based GNSS data and ionosonde data from International GNSS Service (IGS) and Global Ionospheric Radio Observatory (GIRO), taking the International Reference Ionospheric(IRI) as the background model, adopting Gauss-Markov-band-limited Kalman filter assimilation algorithm, combining with ultra-large-scale matrix sparse storage and processing methods, a near-Real-Time Global Ionospheric Data Assimilation and Forecasting System (RT-GIDAM) is built on the cloud computing platform. The system has the ability of specification and prediction of global ionospheric total electron content (TEC) and electron density in near real time (with a delay of about 5 min), higher spatial and temporal resolution (5°×2.5°×15 min). The establishment of RT-GIDAM can provide data support for space physics research and related radiowave system applications.