## 4 Discussion
### Influence of Background and Solar Zenith Angle on the Estimation of SIF Escape Probability  
We compared the simulation values of SIF escape probability (as'real' value) with the estimated values using SIT (Figure 4). The estimation accuracy of SIF escape probability is quite high with a non-reflecting background, both with dense forest (FVC = 0.8) and sparse forest (FVC = 0.3), which means that SIT can be directly used in the estimation of SIF escape probability for forest area with a non-reflecting background. However, in the presence of realistic background instead of the non-reflecting background, the estimation accuracy greatly decreased for each simulation setup, especially for the sparse scene (FVC = 0.3) and for a vegetation-covered background (Ref-3). This is because the reflecting background contaminates the \(NIR_{v}\) used to estimate the SIF escape probability. This result agrees with previous studies [12; 22] and the theoretical limit (i.e., black soil problem) of SIT [19; 20; 39].  
Recently, \(NIR_{v}\) (\(NIR_{v}=NIR_{T}\times\text{NDVI}\)) was proposed to replace \(NIR_{T}\) for the estimation of SIF escape probability using SIT [12; 14], where the use of NDVI is intended to reduce the contamination of soil reflectance on canopy reflectance. Our results confirmed the feasibility of \(NIR_{v}\) for specific simulation cases where the background was not totally covered by vegetation. However, the estimation accuracy of SIF escape probability was not improved with the use of NDVI for the simulation case where the background was mostly covered by vegetation (i.e., Ref-3). Considering the seasonal variation of understory LAI in sparse forests [31; 40], the use of NDVI for the estimation of SIF escape probability is still questionable in summer when the background is mostly covered by vegetation (i.e., high understory LAI value).  
With regards to the effect of the solar zenith angle on the estimation of SIF escape probability, Figure 4 shows that the accuracies of SIF escape probability estimated at a high solar zenith angle are higher than those estimated at a low solar zenith angle in most studied cases. This phenomenon may be due to the potential link between solar zenith angle and background reflectance. With the solar zenith angle increasing from 20\({}^{\circ}\) to 70\({}^{\circ}\), more incident photons will be absorbed by the tree crown, and fewer incident photons will be absorbed by the background, which then will weaken the impact of background reflectance on the estimation of SIF escape probability. The above phenomenon was further confirmed by Figure 5b where the estimation accuracy of total emitted SIF was clearly improved when using a constant value of SIF escape probability estimated at 70\({}^{\circ}\) (R\({}^{2}\) increased from 0.85 to 0.95). Conversely, the estimation accuracy of total emitted SIF slightly decreased (R\({}^{2}\) decreased from 0.85 to 0.81) when using a constant value of SIF escape probability estimated at 20\({}^{\circ}\) (Figure 5c). It is worth noting that these findings were based on the assumption that other input parameters remain constant when the solar zenith angle changes from 20\({}^{\circ}\) to 70\({}^{\circ}\) (i.e., over the season). In reality, it is not the case, because canopy structure and leaf optical properties change over the season [1; 31; 41]. Fortunately, Figure 2 shows that the impact of leaf optical properties (represented by Cab) on SIF escape probability is slight in the far-red region, which agrees with results obtained with the SCOPE model (Figure 4 in [22]).