## 3 Results
### Effects of Viewing Zenith Angle in OCO-2 Glint Mode on SIF Observations
Comparison of Parameter Sensitivity of the SIF and LUE Models under Multiple Meteorological Conditions  
The sensitivity of environmental factors in the SIF and LUE models was further independently analyzed at mid-day, daily, and monthly timescales. The ECI well summarized the information contained in the three environmental variables (APAR, air temperature, VPD) (Figure 4) and provided an objective and simple criterion to describe the extent of meteorological conditions experienced by the vegetation and photosynthetic devices. Across all temporal aggregations, we found that ECIs higher than 0.8 occurred in the later growth phase of wheat, the early growth stage of maize, and over the whole growth phase of summer maize from early July to early October (Figure 4). The high ECI values of wheat were mainly due to high air temperature and VPD, with high VPD occurring at the beginning of the growing phase of summer maize. This might be due to the lack of sprinkler irrigation during this period with high temperature, leading to higher VPD values, because the irrigation in the CN-YuC site is mainly used during the growth period of wheat. The high ECI values of the maize were mostly due to exposure to an environment with high light and high air temperature. This could be explained by the precipitation being concentrated between June and August, thus keeping sufficient water vapor content in the air. Therefore, the corresponding VPD values were lower even though the temperature was high during this period. Figure 4: Seasonal dynamics of normalized meteorological conditions (scaled within 0–1), including normalized meteorological condition index (ECI), air temperature, VPD, and APAR at the (**a**) mid-day timescale, (**b**) daily timescale, and (**c**) monthly timescale. The solid grey lines refer to the threshold value of ECI values. The whole canopies are prone to experiencing exposure to excess light when the ECI is greater than 0.8 compared with when the ECI is lower. Figure 5 and Table 3 further show the fluctuations of parameters in the SIF and LUE models under a range of different meteorological conditions using 0.8 as a threshold value of ECI values to fit separately. Overall, the relationship remained linear without significant nonlinearity, though there is one point at which large ECI values deviated from the linear relationship on the mid-day timescale (the left panel of Figure 5a,d), which agrees with the results reported by [3]. However, all curves showed a slight change in the direction of their slopes with different values of air temperature, APAR, and VPD at individual timescales. For all three models, we noted that the posterior estimations of their parameters had the smallest \(CV\) values on the daily timescale, while larger fluctuations occurred on both the mid-day and monthly timescales. A detailed comparison is shown in Table 3. The values of \(\varepsilon/\mathit{SIF}_{\mathit{yield}}\) were relatively constant, with \(CV\) values ranging from 5.7% at the daily timescale to 22.5% at the monthly timescale, about one-half of the \(\varepsilon_{\mathrm{max}}\) CVs and one-quarter of the \(\varepsilon_{\mathrm{msu}}\) and \(\varepsilon_{\mathrm{msh}}\) CVs. These results thus enhance the confidence of using SIF to simulate ecosystem-scale GPP under varying meteorological conditions. Figure 5: The fluctuations in the parameters of the SIF model and the LUE models for a range of meteorological conditions, where 0.8 is the threshold value at which ECI values are fitted separately. The columns from left to right show the mid-day, daily, and monthly timescales, respectively. The rows from top to bottom indicate the SIF model (\(GPP=\varepsilon/\mathit{SIF}_{\mathrm{yield}}\times\mathit{SIF}\)), SL-LUE model (\(GPP=\varepsilon_{\mathrm{max}}\times APAR\times f(VPD)\times g(T_{\mathrm{a}})\)), and TL-LUE model (\(GPP=\varepsilon_{\mathrm{msu}}\times APAR_{\mathrm{su}}\times f(VPD)\times g (T_{\mathrm{a}})+\varepsilon_{\mathrm{msh}}\times APAR_{\mathrm{sh}}\times f( VPD)\times g(T_{\mathrm{a}})\)), respectively.