# The Comparison of Electron Density between CSES In Situ and Ground-Based Observations in China
## 4 Comparing with Ionosonde Data
### Latitudinal Analysis  
According to the above data process illustrated at the beginning of Section 4, the comparison dataset between the Ne of the CSES and ionosonde data from CRIRP was constructed in March, June, September and December of 2019. Taking Lhasa station as an example, Figure 8 gives the time series of the two data, and the median value of relative change (calculated by Equation (1)) and correlation coefficient (obtained by Equation (3)) between the CSES and ionosonde Ne are also marked in each panel for different months. The variation patterns of the two datasets are almost consistent, and the peaks or troughs coincide with each other at times, for example, the similar trend seen in mid-September and the single peak in December. The correlation coefficients all exceed 0.4, and the value exceeds 0.7 in June. The value of the CSES Ne is lower than that of the ionosonde Ne with a ratio of 80-90%. In the same way as for the Lhasa station, the correlation coefficients between the CSES and ionosonde Ne for each station from CRIRP were calculated according to Equation (3) for March, June, September and December of 2019, which was summarized in Table 1. For a more intuitive representation, the differential correlation coefficients by \(1^{\circ}\times 1^{\circ}\) were obtained based on all of the data in Table 1; the contour lines with colors are shown in Figure 9, where the name of each station is used the abbreviation. It can be seen that the values at the low to mid-low latitudes are mostly higher than those at the middle latitude, which is more obvious in June, September and December. In general, the correlation between the two datasets in June and September is relatively better than that in other months, with the highest value in June for the CC, LZ, LS and CQ stations, and in September for the BJ, XA and KM stations. Figure 6: Ne scatters for CSES and ionosonde. Panels **(a–c)** are for Leshan, Tengchong and Puer stations, respectively. In each panel, the red line is the linear fitting line. Figure 7: Relative change of CSES Ne corresponding to ionosonde Ne. Panels **(a–c)** are for Leshan, Tengchong and Puer, respectively. In each panel, the \(Y\) axis represents empirical cumulative distribution function (cdf). Figure 8: Time series of Ne for CSES and Lhasa ionosonde in different months. In each panel, the red curve represents CSES Ne and the blue curve denotes Ne at the satellite altitude inferred by Lhasa ionosonde observations and IRI model. The two time series are displayed with a log scale. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Station** & **March** & **June** & **September** & **December** \\ \hline Manzhouli (MZL) & 0.5331 & 0.2192 & 0.1460 & \(-\)0.2932 \\ Changchun (CC) & 0.2410 & 0.5243 & 0.4167 & \(-\)0.0542 \\ Urumuchi (UC) & 0.3017 & 0.2121 & \(-\)0.0263 & \(-\)0.0101 \\ Beijing (BI) & 0.4895 & 0.2193 & 0.5864 & 0.1550 \\ Lanzhou (L2) & 0.4018 & 0.6445 & 0.5585 & 0.4069 \\ Xi’an (XA) & 0.3986 & 0.5119 & 0.6665 & 0.0989 \\ Lhasa (LS) & 0.4476 & 0.7124 & 0.5153 & 0.6356 \\ Chongqing (CQ) & 0.5444 & 0.7533 & 0.5366 & 0.3109 \\ Kunming (KM) & 0.3939 & 0.5786 & 0.7311 & 0.3447 \\ Haikou (HK) & 0.3552 & 0.5524 & 0.5228 & 0.6494 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Correlation coefficient between CSES and ionosonde Ne at different ionosonde stations. Figure 9: Contour map of correlation coefficient between CSES and ionosonde Ne in different months. Acronyms of station names are used in each panel. The median value of the relative change of the CSES Ne corresponding to the ionosonde observations (calculated by Equation (1)) for each station is summarized in Table 2. All of the data are negative, which means that the value of the CSES Ne is lower than that of the Ne at the satellite altitude inferred by ionosonde observations and the IRI model at different latitudes. The values are from \(-80\%\) to \(-95\%\).