## 6 Conclusions  
In view of the limitations of the Biome-BGC model when applied to alpine regions, we have prescribed its phenological states based upon the remotely sensed phenology and calibrated its parameters to improve the modeling of GPP of alpine grasslands on the Tibetan Plateau (TP). Specifically, we first used the remotely sensed phenology to modify the original meteorological-based phenology module in the Biome-BGC to better prescribe the phenological states within the model, and then we combined the global sensitivity analysis method with the simulated annealing algorithm to calibrate the model parameters. Furthermore, we used the improved Biome-BGC model to simulate the GPP of alpine grasslands on the TP from 1982 to 2015. The results show that the improved Biome-BGC model effectively overcame the limitations in the original model and was capable of reproducing the magnitude and the temporal dynamics of GPP of alpine grasslands. At the same time, the simulated results indicate that the GPP of alpine grasslands on the TP exhibited a large spatial heterogeneity, which generally showed a decreasing trend from southeast to northwest and was consistent with the hydrothermal gradient of the TP. In addition, the mean annual GPP of alpine grasslands on the TP from 1982 to 2015 estimated by our study was 289.8 gC/m\({}^{2}\)/yr (305.8 TgC/yr), and GPP in most regions showed a significant increasing trend. However, it should be noted that although GPP exhibits an increasing trend over the past 34 years, the general trend in net carbon uptake is still unclear given the large uncertainty in soil respiration during the non-growing season. Therefore, in the case that more field-measured data such as soil temperature is available, we also need to consider the effects of frozensoil on alpine vegetation and further improve the soil respiration module of the Biome-BGC to obtain the carbon budget dynamics of alpine grassland ecosystem on the TP. **Supplementary Materials:** The following are available online at [[http://www.mdpi.com/2072-4292/11/11/1287/s1](http://www.mdpi.com/2072-4292/11/11/1287/s1)]([http://www.mdpi.com/2072-4292/11/11/1287/s1](http://www.mdpi.com/2072-4292/11/11/1287/s1)). A detailed description of the Morris method, Figure S1: Morris sensitivity indices of mean annual GPP to the input electrophysiological parameters; Figure S2: Sobol' sensitivity indices of mean annual GPP to the input electrophysiological parameters screened by the Morris method; Figure S3: Comparisons between GPP derived from EC measurements and GPP simulated by the version of V0, V1, and V2 for the validation year; Figure S4: Comparisons between NEE measured by EC technique and NEE simulated by the version of V0, V1, and V2 for the validation year; Figure S5: Comparisons between TER derived from EC measurements and TER simulated by the version of V0, V1, and V2 for the validation year. **Author Contributions:** [PERSON] and [PERSON] conceived and designed the method and the experiments, and led the manuscript writing; [PERSON] and [PERSON] conducted the experiments and analyzed the data; [PERSON], [PERSON], and [PERSON] provided help and suggestions in the experiments and its interpretation; [PERSON] and [PERSON] contributed to the writing and revision of the manuscript. **Funding:** This research was funded by the Strategic Priority Research Program of the Chinese Academy of Sciences: CAS Earth Big Data Science Project (No. XDA19030501), the Second Comprehensive Scientific Investigation of the Tibetan Plateau: Aerial Water Resources Monitoring on the Tibetan Plateau based on the Space-Air-Ground Integrated Network (No. 2019 QZKK0204), and the National Natural Science Foundation of China (Nos. 91547107, 41271426, and 41428103). **Acknowledgments:** The EC data used in this study is provided by the Chinese Flux Observation and Research Network, and the China Meteorological Forcing Dataset is developed by Data Assimilation and Modeling Center for Tibetan Multi-spheres, Institute of Tibetan Plateau Research, Chinese Academy of Sciences.