## 3 Evaluations of Data Quality  
Before applying new instruments, it is essential to conduct quality assessments and bias analyses. Building upon the previous comparisons of the basic instrument characteristics of MWHS, MWTS, and ATMS, we have further analyzed and compared their simulated bias characteristics. In 2020, [PERSON] et al. released its first-generation Advanced Radiative Transfer Modeling System (ARMS), a system tailored specifically for Chinese satellite instruments. This model, based on the spectral response functions of China's meteorological satellite instruments, has designed a precise and rapid calculation scheme for atmospheric transmittance. It has also established a comprehensive atmospheric spectral dataset, enabling high-precision and rapid calculation of atmospheric transmittance across different channels of China's meteorological satellites [25]. This provides a crucial platform for our research on China's Fengyun satellite instruments. In this study, ERA5 data with a resolution of 0.25\({}^{\circ}\) were adopted as the background field. After temporally and spatially matching the satellite microwave data with the ERA5 data, they were input into ARMS for simulation. To minimize the impact of model errors and surface emissivity, the area for the simulation is the ocean under a clear sky. When removing the cloud, in order to eliminate the temporal resolution differences between microwave data and ERA5 data, a cloud detection method using the cloud liquid water path (CLWP) dual-channel physical algorithm based on microwave data was implemented [26]. ERA5, on the other hand, retained clear-sky pixels based on CLWP values less than 0.01 kg/m\({}^{2}\). The evaluation period covers a total of 10 days, from 12 October 2023 to 14 October 2023 and from 1 December 2023 to 7 December 2023. During the aforementioned time periods within the latitudes of 60\({}^{\circ}\)S and 60\({}^{\circ}\)N, the ERA5 data provided the necessary atmospheric and surface information for the ARMS simulations. The polarization settings of all MWHS channels on FY-3F are based on the aforementioned conclusions. The error statistics of equivalent channel observations and simulations are shown in Figures 3 and 4, where the x-axis represents the channel numbers of instruments. Figure 3a shows the mean bias comparison for MWHS equivalent channels. The difference between FY-3F MWHS and FY-3E MWHS is the largest at channel 15, reaching approximately 1.8 K. For the other channels, the differences between FY-3F MWHS and FY-3E MWHS are within 0.8 K. On average, the bias of FY-3E MWHS for each channel is \begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline \multicolumn{3}{c}{**MWTS Channel**} & \multicolumn{4}{c}{**Polarization**} & \multicolumn{4}{c}{**MWHS Channel**} & \multicolumn{3}{c}{**Polarization**} \\ \hline
**FY-3F** & **FY-3E** & **ATMS** & **FY-3F** & **FY-3E** & **ATMS** & **FY-3F** & **FY-3E** & **ATMS** & **FY-3F** & **FY-3E** & **ATMS** \\
**MWTS** & **MWTS** & **MWTS** & **MWTS** & **MWTS** & **MWTS** & **MWHS** & **MWHS** & **MWTS** & **MWTS** & **ATMS** \\ \hline
1 & 1 & 1 & Qh & Qh & Qv & 1 & 1 & 16 & Qv & Qh & Qv \\
2 & 2 & 2 & Qh & Qh & Qv & 2 & 2 & & & Qh & Qv & \\
3 & 3 & 3 & Qv & Qv & Qh & 3 & 3 & & Qh & Qv & \\
4 & 4 & 4 & Qv & Qv & Qv & Qh & 4 & 4 & & Qh & Qv & \\
5 & 5 & 5 & Qv & Qv & Qh & 5 & 5 & & Qh & Qv & \\
7 & 7 & 6 & Qv & Qv & Qh & 7 & 7 & & Qh & Qv & \\
8 & 8 & & Qv & Qv & & 8 & 8 & & Qh & Qv & \\
9 & 9 & 7 & Qv & Qv & Qh & 9 & 9 & & Qh & Qv & \\
10 & 10 & 8 & Qv & Qv & Qh & 10 & 10 & 17 & Qh & Qh & Qh \\
11 & 11 & 9 & Qv & Qv & Qh & 11 & 11 & 22 & Qh & Qv & Qh \\
12 & 12 & 10 & Qv & Qv & Qh & 12 & 12 & 21 & Qh & Qv & Qh \\
13 & 13 & 11 & Qv & Qv & Qh & 13 & 13 & 20 & Qh & Qv & Qh \\
14 & 14 & 12 & Qv & Qv & Qh & 14 & 14 & 19 & Qh & Qv & Qh \\
15 & 15 & 13 & Qv & Qv & Qh & 15 & 15 & 18 & Qh & Qv & Qh \\
16 & 16 & 14 & Qv & Qv & Qh & & & & & \\
17 & 17 & 15 & Qv & Qv & Qh & & & & & & \\ \hline \hline \end{tabular}
\end{table}