# The Comparison of Electron Density between CSES In Situ and Ground-Based Observations in China
## 5 Discussion  
Figure 5 shows that the day-to-day variation can be found in the observations of both the CSES and ionosonde Ne, and the scaled ionograms of the ionosonde can also be affected by the phenomena of spread F, the stratification of the F2 layer, sporadic E layer (Es) and so on [37; 38; 39], which can induce differences between the CSES and ionosonde Ne. Meanwhile, the disturbances of the running mean with 15 days (shown by red and blue lines in Figure 5) are not frequent. The correlation coefficients of the running mean values between the two datasets were calculated according to Equation (3), and are listed in Table 3 for these three stations. The coefficients increase compared to the former analysis, with values up to 0.75, especially for the Leshan and Tengchong stations. Furthermore, the ionospheric disturbances can also be induced by solar activity, magnetic storms, and other space events [30]. In order to analyze the correlation on a geomagnetically quiet day, the coefficients between the CSES and ionosonde Ne were only calculated for the data in the days with 10.7 cm solar radio flux (\(F_{10.7}\)) < 160, \(\text{Kp}\leq 3\), \(\mid\!Dist\!\mid\!<\!\!\!30\) nT and \(AE\) < 500 nT, as shown in Table 3. Compared to the coefficient calculated by all data, the correlation between the CSES and ionosonde Ne is better on geomagneticly quiet days, which indicates that the consistency of the different observations for the ionosphere can be affected by geomagnetic events. It can be seen that the day-to-day variation and disturbance events could result in differences in the correlation analysis. In terms of time, the correlation coefficient in June and September is generally better than that in March and December. In Figure 5, the values of the CSES Ne in June and September of 2019 are all higher than those in March and December for three ionosonde stations. It seems that the CSES Ne in the month with a relative high value may exhibit good correlation with the ionosonde observations. In general, the signal-to-noise ratio (SNR) \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Station** & **March** & **June** & **September** & **December** \\ \hline Manzhouli (MZL) & \(-93.51\%\) & \(-90.35\%\) & \(-94.48\%\) & \(-94.22\%\) \\ Changchun (CC) & \(-85.52\%\) & \(-80.47\%\) & \(-84.62\%\) & \(-91.08\%\) \\ Urumuchi (UC) & \(-93.81\%\) & \(-88.35\%\) & \(-93.46\%\) & \(-94.29\%\) \\ Beijing (BJ) & \(-93.13\%\) & \(-87.11\%\) & \(-93.50\%\) & \(-94.10\%\) \\ Lanzhou (LZ) & \(-90.48\%\) & \(-85.00\%\) & \(-89.99\%\) & \(-93.45\%\) \\ Xi’an (XA) & \(-89.72\%\) & \(-84.45\%\) & \(-90.10\%\) & \(-92.86\%\) \\ Lhasa (LS) & \(-87.09\%\) & \(-82.18\%\) & \(-86.02\%\) & \(-91.17\%\) \\ Chongjing (CG) & \(-85.52\%\) & \(-80.47\%\) & \(-84.62\%\) & \(-91.08\%\) \\ Kunming (KM) & \(-88.72\%\) & \(-84.31\%\) & \(-89.52\%\) & \(-91.91\%\) \\ Haikou (HK) & \(-85.29\%\) & \(-81.85\%\) & \(-87.13\%\) & \(-93.21\%\) \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Median value for relative change of CSES Ne corresponding to ionosonde Ne at different stations. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Station** & **Raw Data** & **Running Mean** & **Geomagnetically Quiet Day** \\ \hline Leshan & 0.4858 & 0.7557 & 0.5785 \\ \hline Tengchong & 0.5973 & 0.7506 & 0.6334 \\ \hline Puer & 0.4944 & 0.6425 & 0.5431 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Correlation coefficient between CSES and ionosonde Ne for Leshan, Tengchong and Puer stations in different conditions. of the payload will be better under the conditions of the observation parameters with a relatively high value. In terms of latitude, the correlation between the CSES and ionosonde Ne is better at the low latitude than that at the middle latitude during the daytime. The spatial distributions of the monthly mean for the CSES Ne in March, June, September and December of 2019 are exhibited in Figure 10. The patterns of the CSES Ne in these four months all show the high values at low latitude and low values at middle latitude.