## 3 Results
### Effects of Viewing Zenith Angle in OCO-2 Glint Mode on SIF Observations
The consistency of tower GPP with the OCO-2 SIF on Glint and Nadir modes, the tower derived SIF and vegetation index, retrieved from the spectral measurements in the 2015 growing period of summer maize at the CN-YuC site, was further examined (Figure 2a). Maize photosynthesis began in the middle of June, with GPP rising rapidly, and ended in mid-October, with GPP close to zero (Figure 2a). Overall, the discontinuous OCO-2 SIF, tower derived SIF, NDVI, and VOG can reasonably capture seasonally photosynthetic dynamics. They all first increased and then decreased throughout the growing season of summer maize, consistent with the tower calculation of GPP. Compared with NDVI and VOG, the tower SIF especially captured better fluctuation details for the early (\"green-up\"), elongation, and later (senescence) phases (Figure 2a, Orange dotted box). In addition, Figure 2b further shows the relationship of the OCO-2 SIF values obtained from Glint and Nadir modes and the tower derived SIF. Compared with SIF\({}_{\text{glint}}\), SIF\({}_{\text{nadir}}\) tended to overestimate the field SIF, with the higher slope of 1.21. However, both SIF\({}_{\text{nadir}}\) and SIF\({}_{\text{glint}}\) showed a strong linear relationship with tower derived SIF. The R\({}^{2}\) values were consistently higher than 0.70. These analyses suggest again that it may be reasonable to combine data from Glint and Nadir observation modes to increase the number of available observations for further comparison of the GPP-SIF and GPP-LUE models. Comparison of Parameter Stability of the SIF and LUE Models across Multiple Temporal Aggregation Levels  
We optimized the key parameters (\(\varepsilon/SIF_{\text{yield}}\), \(\varepsilon_{\text{max}}\), \(\varepsilon_{\text{msu}}\), and \(\varepsilon_{\text{msh}}\)) of the SIF model, SL-LUE model, and TL-LUE model on mid-day, daily, and monthly timescales, respectively, to explore the stability of these parameters (Figure 3, Table 2). In general, the goodness of fit in these three models was better on the daily and monthly timescales than on the mid-day timescale, which is consistent with the results reported by [(37)] and [(1)]. Across all temporal aggregation levels, the TL-LUE model was better than the SIF model and the SL-LUE model at capturing and explaining the seasonal fluctuations of GPP. The corresponding R\({}^{2}\) were 0.70, 0.90, and 0.93 for the mid-day, daily, and monthly timescales, respectively, slightly higher than those of the SIF model by 4.3%, 7.8%, and 4.3%, and much higher than those of the SL-LUE model by 27.1%, 10%, and 14.0%. However, it is noteworthy that the posterior estimations of \(\varepsilon/SIF_{\text{yield}}\) in the SIF model and \(\varepsilon_{\text{max}}\) in the SL-LUE model was relatively convergent across all temporal aggregation levels (Table 2). The CV of \(\varepsilon/SIF_{\text{yield}}\) and \(\varepsilon_{\text{max}}\) were 6.1% and 4.1%, which were on average 13.5% (\(\pm 0.97\%\)) and 34.3% (\(\pm 1.28\%\)) lower than those of \(\varepsilon_{\text{msu}}\) and \(\varepsilon_{\text{msh}}\). These analyses indicate the existence of both a robust GPP-SIF linear relationship and a good  
Figure 2: The consistency of OCO-2 SIF in Glint and Nadir observation modes with the tower derived SIF: (**a**) Seasonal dynamics of tower gross primary production (GPP), normalized difference vegetation index (NDVI\({}_{\text{BRDF}}\)), Vogelmann red edge index (VOG\({}_{\text{BRDF}}\)), tower sun-induced chlorophyll infloresence (SIF), and OCO-2 SIF; (**b**) the relationship between OCO-2 SIF in Glint and Nadir modes and the tower SIF at the CN-YuC site over the 2015 growth period of summer maize. There are only six data points on Glint mode and seven data points on Nadir mode for both satellite overpassing and tower observing at the same time. The missing observations from 17 August 2015 to 1 September 2015 were due to an equipment failure.