Snow depth is an important parameter for describing snowfall. High-precision snow depth products play an important role in weather forecasting, hydrology, and surface processes. Since April 2019, the National Satellite Meteorological Center has been releasing the passive microwave global snow depth/snow water equivalent product of the Fengyun-3D satellite (FY-3D) microwave radiometer on a global scale. Compared with the FY-3B algorithm, the operational snow depth algorithm of the FY-3D introduces an empirical correction of forest cover in the northeastern forest area. In order to verify the effect of this algorithm improvement and the accuracy of the operational products in the northeastern forest area, this paper uses the measured snow line data of the forest area in Yichun City, Heilongjiang Province, and the snow depth observation data of meteorological stations to validate the operational snow depth and snow water equivalent products of the FY-3D, and analyzes the verification results. The verification results show that the RMSE of the FY-3D snow depth product compared with the measured snow line data and the observation data of meteorological stations is 5 cm and 13.2 cm, respectively, and the RMSE of the snow water equivalent product of the FY-3D compared with the measured snow line data is 2.1 mm. The analysis shows that the uncertainty of the FY-3D snow depth product in forest areas is mainly due to the difficulty in removing the influence of forests on microwave radiation temperature through the semi-empirical algorithm. Although forest radiation correction can enhance the correlation between brightness temperature gradient and snow depth, the empirical nature of forest radiation correction increases the uncertainty of snow depth retrieval results. This work can serve as a reference for improving snow depth retrieval algorithms in forest areas based on domestic FY-3D brightness temperature data.

FY-3D/MWRI;Snow depth;Snow water equivalent;Product verification;Forest area