Abstract
The Global Navigation Satellite System (GNSS) allows for the cost-effective estimation of the ionospheric total electron content (TEC). However, research on error characteristics of the derived TEC is scarce, which provides insights into the quality of the GNSS ionospheric observation. We investigate characteristics of errors in the derived TEC with data from ~260 GNSS dual-frequency receivers of the Crustal Movement Observation Network of China (CMONOC). The slant TEC is calculated from carrier phase measurements and the vertical TEC over China is fitted with a spatial resolution of 1° by 1° in latitude and longitude in four seasons of 2014. It is found that the errors of both the slant TEC and the derived TEC follow Laplace distribution rather than Gaussian distribution in all seasons. The errors of the slant TEC have sharper peaks than those of the derived TEC. The Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) of the slant TEC are typically 0.04 TECU and 0.2 TECU, while the MAE and RMSE of the fitting residuals for the derived TEC are typically 1 TECU and under 2 TECU, respectively. Both MAEs and RMSEs of the derived TEC have the largest value in spring and the smallest value in summer, while the seasonal dependence is only observed in RMSE of the slant TEC.
Highlights
In the last three decades, beacon signals transmitted from global navigation satellite systems (GNSS) have widely been utilized for ionosphere studies
VTECs are calculated from slant total electron content (TEC) and stored with grids according to their ionospheric piercing point (IPP) positions
We develop the Grid_TEC algorithm for deriving TEC with carrier phase observables from regional GNSS networks
Summary
In the last three decades, beacon signals transmitted from global navigation satellite systems (GNSS) have widely been utilized for ionosphere studies. The primary parameter obtained from the satellite beacon signals is the total electron content (TEC), derived from measurements of differential propagation delay and carrier phase between two frequencies, f 1 and f 2, transmitted from GNSS satellites and propagating through the dispersive ionosphere. To remove the instrumental biases, a mathematical model should be established to describe the relations among TEC, biases, and measurements, in which data characteristics and computer resources should be considered, and data fitting should be carried out This makes the TEC derivation a challenging task and efforts never cease to pursue goals, such as better accuracy and faster processing time.
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