## 6 Ionospheric Total Electron Content and Disturbance Observations  
The ionosphere is a part of the Earth's upper atmosphere, located at an altitude from approximately 80 to 1500 km above the Earth's surface. The atoms and molecules within the ionosphere are primarily affected by solar radiation, which ionizes them, forming a weak plasma. This weak plasma influences the refraction and reflection of radio waves, thereby impacting the transmission of wireless signals. For instance, signals from GNSS can experience scattering and diffraction when passing through regions of plasma disturbance or irregularity, leading to fluctuations in signal amplitude and the carrier phase. These effects can cause significant errors in the calculation of position, velocity, and time (PVT) [109]. GNSS is one of the main methods for detecting and simulating parameters such as the total electron content and electron density in the ionosphere [110]. However, the uneven distribution of GNSS ground stations in areas such as oceans and land severely affects the accuracy and reliability of global ionospheric models in these regions. Furthermore, spaceborne GNSS-R has shown great potential in modeling the ionosphere in data-sparse regions [111]. At present, the monitoring of ionospheric total electron content (TEC) and plasma disturbances mainly relies on spaceborne GNSS-R standard data products [98]. In 2016, [PERSON] et al. [112] utilized data from the UK TDS-1 to discover that signal-to-noise ratio fluctuations mainly occur in open-ocean regions and areas of low wind speed within \(\pm 20^{\circ}\) of the magnetic equator. The impact of ionospheric scintillation on GNSS reflectometry is similar in both traditional and interferometric techniques. In 2018, [PERSON] et al. [113] focused on the ability of GNSS-R technology to describe ionospheric scintillation characteristics in high- and low-latitude regions. By analyzing GNSS-R ionospheric L1 data \begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Reference**} & **Satellite Data Used** & **Type of Data Used** & **Reference Surface/Data** & **Result (Accuracy)** \\ \hline
[48] & Spire & L0 & ICESat-2 &
\begin{tabular}{c} Compared with the monthly average ice freeboard measurement values of ICESat-2 L38, the GNSS-R retrieval results have a certain consistency with the overall trend of ICESat-2 measurement results. \\ \end{tabular} \\ \hline
[47] & Spire & L0 & \
\begin{tabular}{c} Interpolate from the DTU18 mean sea surface model \\ \end{tabular} &
\begin{tabular}{c} The comparison between the unsmooth 50 Hz retrieved surface height estimates and the model sea surface shows a good consistency, with an RMS difference of approximately 3.9 cm. \\ \end{tabular} \\ \hline
[54] & Spire & L0 & DEM &
\begin{tabular}{c} In Greenland and Antarctica, both the RMSE values retrieved by GC-R and the RMSE values of its reference surface model achieve meter-level accuracy. \\ \end{tabular} \\ \hline
[23] & TDS-1 & L0 & DTU13 MSS &
\begin{tabular}{c} The results show that the RMSD between the measured surface height and the reference one is 4.7 cm with 20 ms phase delay observations (\(\sim\)140 m along-track sampling distance and \(\sim\)400 m spatial resolution). \\ \end{tabular} \\ \hline
[21] & TDS-1 & L0 & DTU13 MSS &
\begin{tabular}{c} The group delay altimetry results show a much larger error comparing to the carrier-phase ones (0.88 m vs. 0.04 m). \\ \end{tabular} \\ \hline \hline \end{tabular}
\end{table} 
Table 5: The methods and accuracy of retrieving ice height (or ice sheet height) in the current published literature. from the Lemur-2 CubeSat payloads of Spire Global Inc. over the past few years, the performance of existing climatological ionospheric scintillation models was assessed, and weaknesses in the models were identified and improved. This provided more accurate data support for satellite communication, Global Navigation Satellite Systems, and Earth observation missions.