## 3 Results
### Differences in Model Accuracy in Temporal Changes  
With the exception of the tropical evergreen broadleaf forest, the vegetation in the other biome types exhibited distinct phenological changes (Figure 6). Alongside the intra-annual variation of vegetation, most biome types (grass savanna, cropland, arctic tundra, temperate mixed forest, tallgrass prairie, and desert) demonstrated overestimation of FAPAR by each model during the off-peak vegetation growth period. The overestimation by FAPARMOD was more obvious, followed by FAPARLAI and FAPARFVC. At the peak of the vegetation growth period, all FAPAR models showed a reduction in overestimation, with some biome types (cropland and tallgrass prairie) beginning to be underestimated (Figure 6). The Dahra data from the grass savanna represented two years of observational data (2001 and 2002) collected at the same site. The improvement in the presented method over the two years exhibited a consistent pattern. Despite the notable disparity in FAPAR between 2001 and 2002, the accuracy of FAPARFVC was clearly higher than that of FAPARLAI and FAPARMOD in both years. Specifically, the MAPE decreased by 9.1% and 50.2% in 2001, and by 18.9% and 56.7% in 2002, respectively. Figure 5: Taylor diagrams of three FAPAR models across various biome types. The black concentric circles denote the standard deviation (SD); the angular position corresponds to the correlation coefficient (R). The purple concentric circles indicate the centered root mean squared error (CRMSE). Additionally, the yellow marker (labeled “Observation”) shows the position of observational data’s SD, R, and CRMSE values, while the yellow arc highlights simulated results sharing equivalent SD with the observational data. FAPARMOD, FAPARLAI, and FAPARFVC were the same in Figure 2.  
The accuracies of the estimated FAPAR during the peak vegetation growth period were higher than those during the off-peak vegetation growth period. The MAPE and MPE of FAPARMOD were 171.9% and 165.8% during the off-peak vegetation growth period, respectively, while those over the peak growth period were 34.3% and 29.7%, respectively. The former were 5.0 and 5.6 times higher than those for the latter. The MAPE and MPE of FAPARLI were 110.6% and 106.2% during the off-peak vegetation growth period, respectively, compared to 22.1% and 15.3% for the peak vegetation growth period, with the former being 5.0 and 6.9 times higher than the latter. The MAPE and MPE of FAPARFVCC were 76.1% and 42.2% during the off-peak vegetation growth period, respectively, compared to 22.2% and -7.0% for the peak growth period, with the former being 3.4 and 6.0 times more in terms of quantity than the latter (Table 3). Figure 6: Intra-annual variation in FAPAR estimation for different biome types. FAPAR was the same in Figure 1. FAPARMOD, FAPARLI, FAPARFVCC, and FVC were the same in Figure 2. Most biome types demonstrated overestimation of FAPAR by each model during the off-peak vegetation growth period. For FAPAR\({}_{\rm LAI}\) and FAPAR\({}_{\rm FVC}\) compared to FAPAR\({}_{\rm MOD}\), FAPAR\({}_{\rm FVC}\) showed clearly higher improvement in the overestimation of FAPAR during the off-peak growth period than during the peak growth period, whereas FAPAR\({}_{\rm LAI}\) showed a similar improvement over both periods. FAPAR\({}_{\rm FVC}\) reduced MAPE by 35.3% and 55.7% and MPE by 74.5% and 95.8% over both periods, respectively, while FAPAR\({}_{\rm LAI}\) reduced MAPE by 35.7% and 35.3% and MPE by 35.0% and 38.6% over both periods, respectively (Table 3 and Figure 6). Compared to FAPAR\({}_{\rm LAI}\), the improvements in accuracy and decrease in overestimation for FAPAR\({}_{\rm FVC}\) were clearer during the off-peak vegetation growth period than during the peak vegetation growth period; the accuracy of FAPAR\({}_{\rm FVC}\) did not change much during the peak vegetation growth period, but the overestimation condition was reduced clearly.