Fengyun-4A (FY-4A) and Fengyun-4B (FY-4B) are the first two geostationary satellites equipped with an infrared hyperspectral sounder known as the Geostationary Interferometric Infrared Sounder (GIIRS). This paper validates the FY-4A/4B GIIRS atmospheric temperature profile (ATP) products by comparing them with routine radiosonde data collected from 89 stations across China between February 2023 and January 2024. To mitigate the effects of balloon drift, a collocation strategy was implemented for each pressure level to identify the nearest temperature retrieval within 1800 s and 0.2° of the actual observation time and location of the radiosonde. This strategy enhances the agreement between radiosonde observations and satellite retrievals, particularly under clear-sky condition. Utilizing the per-level collocation strategy, we conducted a comprehensive evaluation of the GIIRS ATP products and analyzed how the evaluation results vary in relation to sensors (FY-4A/4B GIIRS), sky conditions (cloudy/clear), months, times (morning/evening), pressure levels, and regions. The results indicate that the FY-4A/4B GIIRS ATP products demonstrate a strong consistency with radiosonde observations, achieving high coefficients of determination (0.990–0.997), favorable biases (−0.92 to 0.06 K), and low RMSE (root-mean-square error) values (1.58–2.57 K). In comparison to cloudy conditions, the evaluation results are significantly improved and exhibit more pronounced variations across months and pressure levels under clear-sky conditions. The summer months demonstrate better performance than the winter months, and the retrievals in the evening are slightly better than those in the morning. Near the top of the atmospheric boundary layer (850 hPa) and the tropopause (200 hPa), the RMSE shows higher values and increased spatial heterogeneity compared to the mid-tropospheric level (500 hPa). FY-4B demonstrates significant superiority over FY-4A under clear-sky conditions; however, this trend does not persist under cloudy conditions due to the large negative biases associated with FY-4B, highlighting the need for further improvement in the retrieval method.

FY-3D MERSI/NDVI is a critical operational product used in many studies (ecosystem monitoring, climate change, agriculture drought, etc.), and it is essential to obtain a comprehensive assessment of this product's quality. In this paper, the first assessment results of global MERSI/NDVI for the period from May 2019 to December 2020 are reported using Terra MODIS/NDVI as the reference. Quantitative measures of APU (Accuracy, Precision and Uncertainty) are calculated and the variations associated with different factors (seasons, land cover types and NDVI values) are analyzed. Results indicate that generally the two products share a high similarity concerning the spatial pattern and temporal profiles features. The dynamic range of MERSI/NDVI is slightly narrower because it overestimates NDVI for barren land and underestimates NDVI for dense vegetation. Sensitivity analysis indicates that the overestimation is mainly attributed to overestimation of NIR reflectance, whereas the underestimation is mainly attributed to overestimation of red reflectance. Phonological features conveyed by the two NDVI products are consistent, but there are slightly noisier fluctuations in MERSI/NDVI time series probably caused by cloud contamination during growing season. Over the 20 months period checked in this study, the global mean of the Accuracy value ranges within −0.02—0, and the global mean of the Precision and Uncertainty values generally range within 0.06—0.08. With respect to the spatial pattern, APU values are the highest in forests, moderate in grassland/shrubland, and lowest in desert. Linear regression models with MODIS/NDVI as independent variables and MERSI/NDVI as dependent variables achieve high accuracies (R²: 0.91—0.95, RMSE: 0.048—0.068), confirming that it is feasible to build a compatible long-term NDVI dataset using both products. This study is the first cross-sensor comparison study using almost all of the global MERSI/NDVI data available since the operational application of the FY-3D satellite. Overall, the MERSI/NDVI data are of very high quality and can be effectively used for deriving vegetation phonological and greenness information. Its performance on the global scale will be monitored continually.