## 3 Evaluation of Remote Sensing Products and GPP Simulations
FLUXCOM assimilated observations at the Dangx site into the product, but deviations still existed in the descriptions of the GPP characteristics at the Dangx site. The FLUXCOM \begin{table}
\begin{tabular}{c c c c c c c c c} \hline \hline \multirow{2}{*}{**Sites**} & \multicolumn{3}{c}{**PBIAS (\%)**} & \multicolumn{3}{c}{**RMSE**} & \multirow{2}{*}{**Corr**} & \multirow{2}{*}{**RSD**} \\  & & & & & **(gC\(\cdot\)m\({}^{-2}\cdot\)d\({}^{-1}\))** & & \\ \hline \multirow{4}{*}{Dangx} & & **CTL** & **NEW** & **CTL** & **NEW** & **CTL** & **NEW** \\ \cline{2-9}  & GPP & 20.9 & 16.6 & 0.321 & 0.261 & 0.922 & 0.952 & 1.100 & 1.121 \\  & NEE & \(-71.1\) & \(-87.8\) & 0.316 & 0.299 & 0.572 & 0.640 & 0.676 & 0.745 \\  & Re & 0.5 & 2.7 & 0.323 & 0.300 & 0.899 & 0.915 & 1.676 & 1.636 \\ Haibei & GPP & \(-6.9\) & \(-5.5\) & 1.227 & 1.127 & 0.863 & 0.882 & 0.780 & 0.892 \\  & NEE & \(-45.8\) & \(-40.7\) & 0.917 & 0.882 & 0.571 & 0.615 & 0.480 & 0.716 \\  & Re & \(-10.9\) & \(-8.6\) & 0.580 & 0.516 & 0.927 & 0.945 & 1.054 & 1.085 \\ Maqu & GPP & 18.2 & 11.3 & 1.401 & 1.028 & 0.903 & 0.956 & 0.946 & 1.087 \\  & NEE & \(-82.0\) & \(-79.7\) & 1.114 & 0.877 & 0.634 & 0.814 & 0.691 & 0.924 \\  & Re & 28.0 & 26.2 & 1.008 & 0.963 & 0.936 & 0.954 & 1.238 & 1.288 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Statistical results of the simulated GPP, NEE, and Re. product overestimated the length of the vegetation growing season, mostly due to an early start of the growing season. Compared to the FLUXCOM product, the start of the growing season of the GLASS product was closer to the observation, while the product seriously overestimated the observed GPP, especially in 2007, 2009, and 2010. The GPP provided by MODIS overestimated the GPP at Dangx and Haibei at the start of the growing season and the growing season at the Haibei site. At the Maqu site, the MODIS GPP generally coincided with the observed GPP. The simulated GPP from CLM5.0-DGVM displayed better performance and simulated the variation characteristics of GPP. As seen in Table 6, at the Dangx site, the average Bias values of the BGCDV_NEW experiment and the NIRv, GLASS, FLUXCOM, and MODIS products were 0.091 gC\(\cdot\)m\({}^{-2}\cdot\)d\({}^{-1}\), 0.840 gC\(\cdot\)m\({}^{-2}\cdot\)d\({}^{-1}\), 0.242 gC\(\cdot\)m\({}^{-2}\cdot\)d\({}^{-1}\), and 0.370 gC\(\cdot\)m\({}^{-2}\cdot\)d\({}^{-1}\), respectively. At the Haibei site, the GLASS product overestimated the observed GPP, while the seasonal variations generally coincided with observations. The FLUXCOM product underestimated GPP during the growing season and overestimated the observed GPP during the non-growing season. The bias between simulations from CLM5.0-DGVM and observations was smaller than that between the GLASS and FLUXCOM products. However, there was a valley value in the simulated GPP during the growing season, which did not exist in the observations. Compared to the NIRv, GLASS, FLUXCOM, and MODIS products, the RMSE of the simulated GPP from the BGCDV_NEW experiment decreased by 74%, 36%, 30%, and 39%, respectively. The GLASS product at Maqu generally coincided with observations, while the product overestimated GPP in 2011, 2014, and 2015. The years 2011, 2014, and 2015 were years with less precipitation, which led to lower GPP values. The MODIS GPP product had the best performance in simulating GPP at the Maqu site. Compared to the NIRv, GLASS, FLUXCOM, and MODIS products, the average Bias of the simulated GPP from the BGCDV_NEW experiment decreased by 2.02 gC\(\cdot\)m\({}^{-2}\cdot\)d\({}^{-1}\), 1.265 gC\(\cdot\)m\({}^{-2}\cdot\)d\({}^{-1}\), 0.143 gC\(\cdot\)m\({}^{-2}\cdot\)d\({}^{-1}\), and \(-\)0.159 gC\(\cdot\)m\({}^{-2}\cdot\)d\({}^{-1}\), respectively. Overall, the PBIAS values of the GPP simulations from the BGCDV_NEW experiment at Dangx, Haibei, and Maqu are within 20%, which is considered to be acceptable. In addition, the FLUXCOM and MODIS data are satisfactory at Maqu.