## 4 Discussion
### Data Reliability  
Under the assumption that the total global annual precipitation does not change significantly, we conclude that changes in precipitation frequency will affect the carbon sequestration capacity of vegetation. Precipitation frequency will directly affect vegetation leaves, such as washing away leaf dust and improving photosynthesis efficiency. In addition, changes in the frequency of precipitation also act directly on the toposil, creating complex interactions with it. Surface soil moisture is prone to evaporation, so changes in soil moisture are partly reflected in changes in precipitation frequency. Therefore, this study takes this as a starting point to discuss the sensitivity of GPP to precipitation frequency. Additionally, air temperature also causes vegetation GPP changes and vegetation growth [82; 83; 84], especially in cold regions. To address this point, the partial correlation between GPP and precipitation frequency was analyzed when mean temperature was controlled (Figure S9). The partial correlation coefficient was calculated using ppcor R package in R 4.3.2. It found that the spatial correlations of the marginal one were similar to those when annual mean temperature was controlled.  
In addition, for vegetation with short root systems, root soil moisture is mainly controlled by precipitation, while for vegetation with long root systems, such as forests, soil moisture in the root zone is not only affected by precipitation, but also by deep percolation, changes in soil water potential, soil structure, topographic factors, etc. The complexity of influencing factors prevents us from taking into account the impact of all environmental factors on sensitivity analysis. Merely using precipitation frequency as the input variable for the XGBoost model may restrict a comprehensive understanding of vegetation growth processes. However, this study mainly discusses the direct impact of precipitation frequency on vegetation GPP and ignores the influence of external factors on soil moisture and other factors on sensitivity analysis.  
Moreover, global land cover types were classed into six categories in GLASS-GLC, which could be insufficient to account for variations in the responses of different vegetation types. Vegetation roots have large spatial variability in the same land cover types, and there is limited flexibility and diversity of vegetation species communities. In the present paper, we only investigated sensitivity for different land cover types, which did not consider root conditions. Human impact also affects vegetation GPP changes. For example, irrigation mainly affects the GPP change of cropland. However, according to GLASS-GLC product, cropland accounted for only 8% (570,554 grids to 7,083,833 grids) of the global vegetation area in 2015, and more than 80% of the world's cropland relied on rainwater [85]. Therefore, in the grid analysis, the impact of human irrigation was ignored.  
Precipitation volume has large spatial variability, and there is not a consistent standard. According to the research and experiments, we artificially set 5 mm as the step size to divide different precipitation intensities. More sub-categories may be needed and suitable for areas with sparse precipitation. However, there is almost no vegetation distribution in arid areas. Therefore, this study did not consider more sub-categories, which would be involved in future research on arid regions.