## 4 Discussion
### Performance of EMGPP  
Data quality plays a more vital role than data quantity in empirical model development and evaluation. For example, though the small observational datasets 8 and 18 were used in EMBE models for isoprene and monoterenes, respectively [27], the EMBE showed reasonable performance. Compare to EMBE development, more datasets were used in EMGPP development and the GPP simulations (\(-\)4 years) were acceptable by similar uncertainties with the observations (e.g., 20-50%) [26] and widely used models (e.g., RMSE). It is difficult to find hourly results of other models for more comparisons and evaluations of the EMGPP, which may be related to large uncertainties in GPP hourly simulations/processes. This study focuses on the simulation of GPP as a first step, the simulations of respiration and NEE (or the partitioning of GPP), as well as long-term variations in GPP, respiration and NEE since 2003 will be investigated in other studies. Accurate simulations of PAR and global solar radiation at high GLP loads (S/Q \(>\) 0.5) are still significant challenges [93] for GPP calculations, compared to GPP estimates at high with low S/Q levels. More studies in improving estimations of PAR and global solar radiation as well GPP in high S/Q situations are needed. It should be mentioned that once CO\({}_{2}\) is emitted into the atmosphere, it takes part in the attenuation, absorbing and scattering processes described/captured by GPP (corresponding to total CO\({}_{2}\)), photochemical and scattering terms (temperature, water vapor, S/Q factors), respectively, i.e., CO\({}_{2}\) interacts with other atmospheric substances and PAR that is attenuated by the absorption and scattering of GLPs. That means that CO\({}_{2}\)/GPP is not controlled by PAR only. This is another reason to study GPP in this study and respiration and NEE in other studies. [PERSON] et al. [26] reported a relative uncertainty of 20-50% for CO\({}_{2}\) flux measurements by eddy covariance, which depends on high or low CO\({}_{2}\) flux magnitudes. Annual amounts of net ecosystem CO\({}_{2}\) exchange with an error bound of 600 \(\pm\) 130 g C m\({}^{-2}\) year\({}^{-1}\) and \(300\pm 180\) g C m\({}^{-2}\) year\({}^{-1}\) in different forests [24]. The uncertainty in the annual estimation of NEE is 12-32%, as reported by [PERSON] et al. [25]. Comparisons between annual estimates using traditional ecological models and eddy covariance measurements are in agreement with 5%, 30% and 100% (for NEP) [22; 23; 24]. The RMSE values of the Breathing Earth System Simulator (BESS) and MODIS 8-day composite GPP products evaluated against flux tower observations are 2.58 (ranging from 1.37-3.86) g C m\({}^{-2}\) d\({}^{-1}\) and 2.86 (1.56-4.80) g C m\({}^{-2}\) d\({}^{-1}\), respectively [94]. All of the above results are beneficial and useful for understanding the uncertainties in measurements and model simulations. According to the calculations and evaluations of hourly, daily, monthly and annual GPP and the similar RMSE values for GPP simulations with the widely used models [76; 77; 78; 79], as well as the above uncertainties in CO\({}_{2}\) flux observations and model estimates, EMGPP can be used to simulate GPP in this coniferous forest. As a first step, the application of the EMBE model was suitable for GPP simulations at this site. Based on the previously successful development of EMBE in this forest to other typical forests in China [27], further development of EMGPP for other ecological systems in China, such as the grass ecosystem, is necessary and beneficial, [95; 96]. The EMGPP model performances for daily averages during 2013-2016 were similar to those for hourly averages and are not shown for the purpose of saving space. To thoroughly understand the absorbing and scattering processes, it is suggested to measure direct and/or diffuse solar radiation at sites in China and around the world. The 3-factor model provides a more thorough understanding of the processes than the 2-factor model.