## 5 Conclusions  
This study evaluated the Noah-MP land surface model using single-point simulations against observations from 105 FLUXNET2015 sites across 12 typical vegetation types. The performance in simulating ET and GPP was assessed at half-hourly, monthly, and annual temporal scales. The main results were as follows:  
1. Noah-MP generally performed well in simulating ET and GPP fluxes, capturing their variability characteristics with relatively small biases compared to the observations. The ET simulations showed slightly better agreement with the observations than the GPP simulations.
2. Simulation performance varied significantly with temporal scales, systematically decreasing as the time scale lengthened. At the half-hourly scale, simulated ET and GPP showed high consistency with observations, indicating strong capability in capturing responses to short-term drivers. At the annual scale, cumulative errors increased substantially.
3. Noah-MP generally captured the characteristic diurnal, seasonal, and interannual variations of ET and GPP. Diurnal simulation biases were often largest around noon. Seasonally, simulation biases for both fluxes were smallest in winter. Inter-site simulation performance showed greater variability during the summer compared to the winter. The standard deviation across sites was smaller for ET than for GPP, suggesting less spread in the ET simulation performance.
4. Based on the evaluation metrics, the ET simulations performed relatively well for OSH, DBF, and MF, with the largest bias observed for WSA. The GPP simulationsperformed relatively well for WET, CSH, and SAV, with the largest bias occurring for EBF.
* Noah-MP exhibits a strong dependence on the climatic region. For ET, the model fails to capture the inter-annual variability in temperate and continental climates, indicating a fundamental weakness in simulating mid-latitude hydrology. For GPP, the model exhibits severe magnitude biases, particularly as overestimation in arid and temperate zones, while also failing to capture the temporal dynamics in arid and continental climates.  
The following supporting information can be downloaded at: [[https://www.mdpi.com/article/10.3390/land14071400/s1](https://www.mdpi.com/article/10.3390/land14071400/s1)]([https://www.mdpi.com/article/10.3390/land14071400/s1](https://www.mdpi.com/article/10.3390/land14071400/s1)).  
Methodology, B.P. and X.W.; Software, B.P.; Validation, B.P.; Formal analysis, B.P.; Investigation, X.W.; Resources, X.W.; Data curation, X.W.; Writing--original draft, B.P.; Writing--review & editing, X.C.; Visualization, B.P.; Supervision, X.C.; Project administration, X.C.; Funding acquisition, X.C. All authors have read and agreed to the published version of the manuscript.  
This work is supported by the National Key Research and Development Program of China (2023 YFF0805501) and the National Natural Science Foundation of China (42375165). We thank the technical support of the National Large Scientific and Technological Infrastructure \"Earth System Numerical Simulation Facility\" ([[https://cstr.on7/31134.02.EL](https://cstr.on7/31134.02.EL)]([https://cstr.on7/31134.02.EL](https://cstr.on7/31134.02.EL)) (accessed on 1 June 2025)).  
The data presented in this study are openly available in FLUXNET at [[https://fluxnet.org/data/fluxnet2015-dataset](https://fluxnet.org/data/fluxnet2015-dataset)]([https://fluxnet.org/data/fluxnet2015-dataset](https://fluxnet.org/data/fluxnet2015-dataset)) (accessed on 3 December 2024).  
The authors declare no conflicts of interest.