## 4 Discussion  
### Possible Reasons for the Underestimations of NEP  
More detailed analyses for the underestimations of NEP are provided here. The GPP and Re simulations from 2003-2017 and 2013-2016 using the measured dataset of solar radiation and meteorology [40] ([PERSON]'s group) exhibited good reproducibility, but a larger variation ranges more for Re estimates than the observations. This discrepancy  
Figure 13: Monthly sums of GPP calculated using EMGPP (GPP\({}_{\text{cal3}}\)) and GPP/SIF linear and non-linear relations (GPP\({}_{\text{cal31}}\) and GPP\({}_{\text{cal3}}\) n), observed GPP (GPP\({}_{\text{obs}}\)), and SIF from 2003–2017. might be due to the data processing of screening out extreme positive and negative Re values [41; 67; 69; 101]. It was slightly strange for the larger underestimations of NEPs from 2003-2017, compared to the overestimations of NEPs from 2013-2016 [40; 41]. It may be caused by the calculation of NEP = GPP \(-\) Re, positive and negative Re values during a day, and too many factors affect respiration processes, e.g., PAR, T, RH, E, etc. In addition, the measurements of PAR may be an important reason because GPP (as well as Re and NEP) is most sensitive to the changes in PAR [40], but the solar radiation sensors on the platform in the flux tower are very difficult to keep daily cleaning, maintenance, horizontal levels, and regular calibration from 2003-2017. For example, the PAR sensor was attenuated annually by about 3.6% [73]. In contrast, the NEP simulations from 2013-2016 provided reasonable overestimates as GPP and NEP simulations using the newly calibrated solar radiation sensors and making timely cleaning and maintenance [70]. The PAR common was performed between the measurements from the PAR sensors of the Qianyanzhou station and another set of solar radiation systems ([PERSON]'s group, described as PAR\({}_{\text{QYZ}}\), PAR\({}_{\text{B}}\), respectively) from May 2013 to December 2016. As shown in Figure 14, two PAR observations varied in similar patterns generally, but monthly PAR\({}_{\text{B}}\) values were a little larger than PAR\({}_{\text{QYZ}}\), indicating that the PAR sensor at the Qianyanzhou station requires calibration and timely maintenance. Additionally, it is suggested that the PAR sensor can also be timely calibrated using a new calibration method described in [102] for high-quality observations of solar radiation at this station. Regular and timely calibration and maintenance of solar radiation sensors on flux tower platforms in other locations worldwide are recommended. This will ensure accurate estimation of carbon exchange using reliable station measurement data and a variety of models. The empirical model of global solar radiation was developed using the hourly observed data (solar radiation and meteorology) from 2008-2011 at the Sodankyla station in the Antarctic and then applied to estimate global solar radiation from 2000-2018. Generally, reasonable performance was obtained [5]. A similar empirical model of Q was also developed using the hourly observed data from 2008-2011, and a little better performance from 2006-2016 was exhibited at the Dome C station in the Arctic [5]. These results indicated that the accurately observed solar radiation and strict routine maintenance of the solar sensors (e.g., Baseline Surface Radiation Network (BSRN) protocols) are very important to model development and, especially, model applications. Therefore, it is very necessary to conduct strict routine maintenance and timely calibration of the solar sensors and replace the broken solar sensors. Considering solar radiation (visible/PAR, Q, etc. ), it is the basic  
Figure 14: Monthly sums of PAR were measured using PAR sensors of Qianyanzhaou station and Bai’s group (PAR\({}_{\text{QYZ}}\) and PAR\({}_{\text{B}}\), respectively). and significant energy to the atmosphere, vegetation, hydrosphere, and land. Together with their interactions, reliable and long-term measurements of solar radiation are extremely important in China and the globe.