Rain backscatter corrupts Ku-band scatterometer wind retrieval by mixing with the signatures of the backscatter measurements (${\sigma }^{\circ }$) on the sea surface. The measurements are sensitive to rain clouds due to the short wavelength, and the rain-contaminated measurements in a WVC (Wind Vector Cell) deviate from the measurements that are simulated using the wind GMF (Geophysical Model Function). Therefore, QC (Quality Control) is essential to guarantee the retrieved winds' quality and consistency. The normalized MLE (Maximum Likelihood Estimator) residual ($R_{\text{n}}$​) is a QC indicator representing the distance between the measurements and the wind GMF; it works locally for one WVC. $J_{\text{OSS}}$ is another QC indicator. It is the speed component of the observation cost function, which is sensitive to spatial inconsistencies in the wind field. $R_{\text{n}}J$ is a combined indicator, and it takes both local information ($R_{\text{n}}$) and spatial consistency ($J_{\text{OSS}}$​) into account. This paper focuses on WindRAD on the FY-3E (Fengyun-3E) satellite, a dual-frequency (C and Ku band) rotating-fan-beam scatterometer. The $R_{\text{n}}$ and $R_{\text{n}}J$​ have been established and thoroughly investigated for Ku-band-only and combined C&Ku wind retrieval. A polynomial fit is applied to select the optimal $R_{\text{n}}$​ threshold. The C-band measurements are hardly influenced by rain, so the Ku-based $R_{\text{n}}$​ is proposed for the C&Ku wind retrieval instead of the total $R_{\text{n}}$​ from both C and Ku bands. In conclusion, the $R_{\text{n}}J$ gives the optimal QC result for the Ku-band-only and C&Ku wind retrieval. Adding the C-band into the retrieval suppresses the rain effect; therefore, a promising QC skill can be achieved with fewer rejected winds.