In this study, we develop a three-dimensional ionospheric tomography with the ground-based global position system (GPS) total electron content observations. Because of the geometric limitation of GPS observation path, it is difficult to solve the ill-posed inverse problem for the ionospheric electron density. Different from methods given by pervious studies, we consider an algorithm combining the least-square method with a constraint condition, in which the gradient of electron density tends to be smooth in the horizontal direction and steep in the vicinity of the ionospheric F2 peak. This algorithm is designed to be independent of any ionospheric or plasmaspheric electron density models as the initial condition. An observation system simulation experiment method is applied to evaluate the performance of the GPS ionospheric tomography in detecting ionospheric electron density perturbation at the scale size of around 200 km in wavelength, such as the medium-scale traveling ionospheric disturbances.

The ionospheric plasma disturbances during a severe storm can affect human activities and systems, such as navigation and HF communication systems. Therefore, the forecast of ionospheric electron density is becoming an important topic recently. This study is conducted with the ionospheric assimilation model by assimilating the total electron content observations into the thermosphere‐ionosphere coupling model with different high‐latitude ionospheric convection models, Heelis and Weimer, and further to forecast the variations of ionospheric electron density during the 2015 St. Patrick's Day geomagnetic storm. The forecast capabilities of these two assimilation models are evaluated by the root‐mean‐square error values in different regions to discuss its latitudinal effects. Results show the better forecast in the electron density at the low‐latitude region during the storm main phase and the recovery phase. The well reproduced eastward electric field at the low‐latitude region by the assimilation model reveals that the electric fields may be an important factor to have the contributions on the accuracy of ionospheric forecast.

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