## 4 Results and Discussion  
### Validation MOD17A2H Based on In Situ  
The results of in situ and MOD17A2H GPP were compared in different land cover types. Figure 2 shows the time series of MOD17A2H and the in situ-based GPP over wetlands; their scatter plots are presented in Figure 3. As shown in Figure 2, missing data occurs frequently in the time series, especially in winter and early spring. This is attributed to the weak photosynthetic activity of vegetation and the lower data coverage during this period. Both MOD17A2H and in situ-based GPP show reasonable seasonal and annual variability over wetlands (Figure 2). However, the agreement between them is significantly different from site to site. The comparison results over wetlands can be divided into two groups according to the performance of MOD17A2H: (1) FI_Lom, US_Atq, GL_ZaF, and SJ_Adv; and (2) GL_NuF,  
Figure 3: Scatter plots of site-based GPP against MOD17A2H over different wetland sites (**a**-**g**) and the overall scatter plots by combining all wetland sites (**h**). Flux tower GPP means in situ GPP. The gray belt refers to the confidence interval of 95%. RU_Che and US_Ivo. MOD17A2H was found to underestimate in group (1) and overestimate in group (2). Nevertheless, the degree of underestimation varies significantly from site to site and is low for FI_tom and US_Atq, both in magnitude and temporal variation trend (Figure 2a,c), with RMSEs of 1.12 and 0.69 g C m\({}^{-2}\) d\({}^{-1}\) and R of 0.9 and 0.86, respectively (Figure 3a,c). For GL_ZaF and SJ_Adv, the agreement is worse, as the RMSEs are 2.01 and 1.79 g C m\({}^{-2}\) d\({}^{-1}\), respectively (Figure 3e,g), and the bias is very large, with values of \(-1.54\) and \(-1.21\), respectively. The large discrepancy between MOD17A2H and in situ GPP may be caused by their spatial scale mismatch. Furthermore, it should be noted that the data points (less than 50) over these two sites are very limited. For the second group, MOD17A2H is generally consistent with in situ measurements, with the RMSEs of 0.74, 1.22, and 1.0 g C m\({}^{-2}\) d\({}^{-1}\), and R of 0.86, 0.82, and 0.86 over GL_NuF, RU_Che, and US_Ivo, respectively. As indicated by Figure 3, the MOD17A2H performs well over wetlands when excluding the sites with limited data points (i.e., GL_ZaF and SJ_Adv). One interesting observation was that the latitudes of GL_ZaF and SJ_Adv are higher than 74\({}^{\circ}\) N while those of the other sites are lower than 74\({}^{\circ}\) N. In addition, the GL_NuF site where the best agreement between MOD17A2H and in situ occurs has the lowest latitude of all the wetland sites. Therefore, it can be inferred that the accuracy of MOD17A2H may be related to latitude, as it is higher over low latitudes but lower over high latitudes. When it comes to the overall performance of MOD17A2H over wetlands (Figure 3h), the overall RMSE and R are 1.17 g C m\({}^{-2}\) d\({}^{-1}\) and 0.76, respectively. MOD17A2H slightly underestimates GPP, with a bias of \(-0.19\). Based on the results above, MOD17A2H can be considered capable of revealing the spatial distribution characteristics and the temporal trend of GPP over wetlands in the Arctic. Figures 4 and 5 show the evaluation results of MOD17A2H over forest sites (i.e., FL_Sod and US_Prr). MOD17A2H underestimates GPP at FL_Sod but overestimates GPP at US_Prr. The extent of misestimation differs between the two sites and is weak for FL_Sod but strong for US_Prr. Over FL_Sod, MOD17A2H agrees well with in situ measurements (Figure 4a), with the RMSE of 1.33 g C m\({}^{-2}\) d\({}^{-1}\) and bias of \(-0.77\) (Figure 5a). However, for US_Prr, their agreement is worse (Figure 4b), with the RMSE of 2.05 g C m\({}^{-2}\) d\({}^{-1}\) and bias of 1.19 (Figure 5b). It is important to note that the extent of misestimating MOD17A2H varies from year to year. This is especially true over US_Prr, where the overestimation of MOD17A2H is more significant from 2012 to 2014 (Figure 4b).