## 4 Discussion
### Evaluation of LUE-GPP Model Performance under Different Weather Conditions  
The big-leaf LUE-GPP models performed differently under different weather conditions. Specifically, they overestimated \(GPP\) on sunny days (\(K_{\rm t}>0.7\)) and underestimated it on cloudy days (\(K_{\rm t}\leq 0.3\)). Based on the measured light-response curve, the light saturation point of kiwifruit leaves was 960 \(\upmu\)mol (photon) m\({}^{-2}\) s\({}^{-1}\) PPFD, which was approximately half of the midday summer irradiance observed in the field. Therefore, the intercepted solar radiation energy cannot be fully converted to photosynthetic chemical energy [54]. The simplified big-leaf LUE-GPP model considered the canopy as a whole with consistent properties; however, light intensity within the canopy leaves is often variable. The upper canopy leaves reach light saturation, whereas the lower ones do not receive sufficient sunlight for efficient photosynthesis due to shading. Thus, ignoring the photosynthetic difference under different light intensities may introduce estimation errors into the big-leaf LUE-GPP models [24; 55]. By contrast, the two-leaf LUE-GPP model considered the light distribution difference within the canopy and calculated the \(GPP\) of shaded and sunlit leaves separately, reporting consistent model performance under different weather conditions.  
As reported by [PERSON] and [PERSON] [26], changes in ecosystem \(PAR\) components due to weather conditions greatly affected ecosystem photosynthesis productivity. A parabolic relationship was found between \(K_{\rm t}\) and \(GPP\) (Figure 11). Therefore, although total sunlight radiation decreased with a decrease in \(K_{\rm t}\) (Figure 12), the photosynthetic rate might be higher in thin-cloudy conditions. In fact, daytime light intensity generally exceeds the light saturation point of most plants [54]. During thin-cloudy days, the reduced \(PAR_{\rm dir}\) may be higher than the maximum light-saturation point of sunlit leaves, but the enhanced \(PAR_{\rm diff}\) can better illuminate the lower canopy and increase the \(GPP\) of shaded leaves [55]; thus, the total \(GPP\) of the canopy is increased [25]. Although \(LUE\) may increase under low \(K_{\rm t}\) and high diffuse radiation, the total \(GPP\) will decrease when total radiation is decreased significantly, leading to a nonlinear relationship between \(K_{\rm t}\) and \(GPP\).  
Figure 11: The relationship between the clearness index (\(K_{\rm t}\)) and the gross primary productivity derived from EC measurement (\(GPP_{\rm EC}\)).  
Figure 12: The relationship between clearness index (\(K_{\rm t}\)) and photosynthetic active radiation (\(PAR\)), direct \(PAR\) (\(PAR_{\rm dir}\)), and diffuse \(PAR\) (\(PAR_{\rm diff}\)) in the humid region.  
Aside from the radiation distribution, ignoring the dynamic changes in _LUIE_ due to \(K_{\text{t}}\) may introduce some errors in estimating _GPP_[14; 18]. Field observation studies have reported that _LUIE_ increases with a decrease in \(K_{\text{t}}\)[10; 44]. The _LUIE_ values in the big-leaf and two-leaf models (sunlit and shaded leaves) are specified as constants, which explains the inconsistency in model performance under different weather conditions [9]. The constructed \(K_{\text{t}}\)-based dynamic _LUIE_ model with exponential form greatly improved the performance consistency of the traditional big-leaf LUE-GPP model under different weather conditions, achieving an overall high simulation accuracy. The accuracy and consistent performance under different weather conditions of the \(K_{\text{t}}\)-based two-leaf model were both improved compared to those of the traditional two-leaf LUE-GPP model. These results indicate that using a power or an exponential function to empirically fit the dynamic effect of \(K_{\text{t}}\) on _LUIE_ can improve model performance. Notably, the dynamic two-leaf LUE-GPP model based on an exponential function could weaken the estimated GPP of shaded leaves, which may be caused by the small parameter value.