## 5 Conclusions  
We based this article on satellite greening data and meteorological datasets from 2001 to 2022 and used Theil-Sen media trend analysis and partial correlation analysis to study the spatiotemporal changes in NDVI\({}_{\text{max}}\), GPP\({}_{\text{max}}\), SM, and saturated VPD in the TP, as well as the response of the first two to the latter two. The results indicate that NDVI\({}_{\text{max}}\) and GPP\({}_{\text{max}}\) have similar spatial patterns, with NDVI\({}_{\text{max}}\) and GPP\({}_{\text{max}}\) showing an upward trend in most regions, accounting for approximately 65% of the area; SM and VPD exhibit different multiyear average spatial patterns, with SM showing a downward trend in 70% of the region, while VPD shows the opposite trend, with approximately 70% of the region showing an upward trend. Our findings indicate that both NDVI\({}_{\text{max}}\) and GPP\({}_{\text{max}}\) exhibit positive correlations with SM and negative correlations with VPD, attributable to the influence of driving factors. From the results of the partial correlation coefficient, it can be seen that the correlation between SM and VPD on peak vegetation growth is as important as precipitation and radiation. Furthermore, the results of the analysis of sensitivity intensity further support the importance of SM to the peak of vegetation growth.  
From the perspective of statistical vegetation types, the above correlation patterns were also observed in the four vegetation types of shrubs, alpine grasslands, alpine meadows, and sparse alpine vegetation. The most obvious manifestation was in the alpine meadows, which showed a dominant advantage over vegetation growth peaks in 60% of the areas. From the perspective of hydrothermal conditions, the above correlation pattern was only observed in areas with precipitation ranging from 200 to 800 mm and temperatures ranging from \(-10\)\({}^{\circ}\)C to \(10\)\({}^{\circ}\)C. When precipitation is too high, the peak vegetation values will be positively correlated with VPD, and conversely, they will be negatively correlated with SM. Overall, SM helps to promote the growth of vegetation peaks, while VPD mainly adversely affects vegetation peaks. Against the backdrop of global climate change, frequent drought events mean that the vegetation of the TP is facing a gradually worsening environment. Thisstudy contributes to a more comprehensive understanding of how vegetation phenology responds to future climate change.  
Conceptualization, X.W.; data curation, Z.Q.; methodology, Z.Q. and X.W.; writing--original draft, Z.Q. and L.T.; writing--review and editing, X.W., Y.Z., J.T., J.Y. and S.X. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the National Key R&D program of China (Grant No. 2023 YFF1303804), the National Natural Science Foundation of China (Grant No. 42271034), and the Youth Innovation Promotion Association of Chinese Academy of Sciences (Grant No. 2022051).  
The NDVI and GPP data were obtained from the NASA Earth-data Cloud website ([[https://appeeears.earthdatcloud.nasa.gov/](https://appeeears.earthdatcloud.nasa.gov/)]([https://appeeears.earthdatcloud.nasa.gov/](https://appeeears.earthdatcloud.nasa.gov/)), accessed on 12 December 2023). The climate data were obtained from the TerraClimate dataset ([[https://www.climatologylab.org/terraclimate.html](https://www.climatologylab.org/terraclimate.html)]([https://www.climatologylab.org/terraclimate.html](https://www.climatologylab.org/terraclimate.html)), accessed on 12 December 2023).  
The authors declare no conflicts of interest.