Assimilating GNSS TEC with an LETKF over Yunnan, China

A robust ionospheric model is indispensable for providing the atmospheric delay corrections global navigation satellite system (GNSS) and positioning forecasting space environment. The accuracy of models limited due to simplified structures. Complicated spatiotemporal variations in total electron content (TEC) biases between GNSS international reference ionosphere (IRI) suggest a strategy optimally combine IRI TEC high-precision modeling. In this paper, we propose novel data assimilation method, which local ensemble transform Kalman filter (LETKF), construct an over Yunnan southwestern China. We used LETKF method assimilate extracted from observations into IRI-2016 model. experimental results indicate that has more pronounced improvement effect on empirical during periods geomagnetic quiet than disturbance. On magnetic days, skill score (SKS) 0.60 root mean square error (RMSE) values before after are 5.08 TECU 2.02 TECU, respectively. correlation coefficient increases 0.94 0.99. storm SKS 0.42 RMSE 5.99 3.46 0.98 algorithm can be considered effective assimilation.