## 3 Results and Discussion
### Comparison with Previous Studies  
Table 3 shows the total NPP of China reported previously and in this study. Reported total NPP ranged from 1.44 to 4.64 Pg C yr\({}^{-1}\). The total NPP simulated by the CASA model ranged from 1.44 to 2.93 Pg C yr\({}^{-1}\); several estimates were lower, ranging from 1.44 to 1.95 Pg C yr\({}^{-1}\)[14; 15; 16]. The low total NPP output from the CASA model was possibly caused by the undervalue of maximum light use efficiency for some types of vegetation in China [64]. NPP simulated by the CASA model linearly changes with this parameter. [PERSON] [65] analyzed the estimates of total NPP in China's terrestrial ecosystems based on process-based models and remote sensing driven models in a meta-analysis,  
Figure 6: Trends of MAT and MAP in six geographical regions of China from 1961 to 2016. Grey bars are averages of regional precipitation (mm) in the periods of 1961–1980, 1981–2000, and 2001–2016, and the blue bars are the average precipitation of the regions between 1961 and 2016. The black lines are the average temperature (\({}^{\circ}\)C) in the periods of 1961–1980, 1981–2000, 2001–2016, and 1961–2016. Figure 7: NPP anomaly (departure from the average NPP from 1961 to 2016) in six geographical regions of China from 1961 to 2016.  
and the total NPP of these estimates averaged \(2.83\pm 0.83\) Pg C yr\({}^{-1}\). Additionally, large interannual variability of NPP exhibited in these estimates. Most of the estimates showed that total NPP peaked in 1990, and that valleys of NPP appeared in 1992 and 1997, similar to our results. The average total NPP of China in this study was \(3.10\pm 0.2\) Pg C yr\({}^{-1}\) during 1961-2016, higher than estimates of most previous studies. It should be kept in mind that the NPP estimated by the LPJ model is potential one, which is higher than actual NPP. The Eddy Covariance (EC) technique has been widely used to measure the carbon and water fluxes at the ecosystem scale [70; 71; 72], and EC observations have also been used to assess the ecosystem models. The simulated annual GPP was validated with the flux data during the period of 2003-2010 summarized by [PERSON] et al. [71]. As shown in Table 4 and Figure 8, the LPJ model performed well in simulating forest GPP, and the average error was 8.14% across 10 forest sites. At the DHS site located in Guangdong province, the vegetation type is subtropical evergreen broad-leaved forest, and the GPP here was overestimated by 42.91% compared with the observed value. In contrast, in the XSBN site of south Yunan, the vegetation is tropical rain forest, and the simulated GPP here was underestimated by 13.76%. The simulated GPP was obviously lower tower measurements at all cropland sites since cropland is not explicitly defined as a PFT, and was treated as grassland in the LPJ model. In China, intensive management, such as fertilizer application, the introduction of new varieties, and irrigation, enhance GPP. These mechanisms were not represented in the LPJ model. In grasslands and wetlands, the simulated GPP was overestimated. The mismatch of model spatial resolution and footprints of flux towers was one of the major reasons for the discrepancy between simulated and observed GPP. The spatial resolution in our simulations was \(0.5^{\circ}\times 0.5^{\circ}\), while the footprints of flux towers were just a few square kilometers. The human-induced land cover change and spatial heterogeneity of climate and soil within \(0.5^{\circ}\times 0.5^{\circ}\) grids were not considered in the current study, which would at least partially explain the departure of simulated GPP from observations. Overall, the LPJ model was able to capture GPP variations among different sites (Figure 6).