## 2 Materials and Methods
### Data  
(1) The Moderate Resolution Imaging Spectroradiometer (MODIS) products used in this study include the MCD15A2H Version 6 FPAR product (8-day temporal resolution, 500 m spatial resolution, available from 2001 to 2022), the MOD17A2H Version 6 GPP product (8-day temporal resolution, 500 m spatial resolution, available from 2001 to 2022), the MOD09A1 product (8-day composited global surface reflectance data, 500 m spatial resolution, available from 2001 to 2022), and the MCD12Q1 land cover classification  
Figure 1: The study area. product (IGBP classification scheme, focusing on evergreen coniferous forests, shrubs, grasslands, and permanent wetlands, with 8-day temporal resolution, 500 m spatial resolution, available from 2001 to 2022). (2) The ECMWF Analysis v5 (ERA5) dataset provides hourly meteorological data at a spatial resolution of approximately 9 km (0.1\({}^{\circ}\)\(\times\) 0.1\({}^{\circ}\)). This study utilizes three key ERA5-Land variables critical for meteorological analysis and climate research: 2 m dew point temperature (dewpoint_temperature_2m, K), 2 m air temperature (temperature_2m, K), and precipitation (precipitation, mm). The vapor pressure deficit (VPD) used in this study was calculated using dew point temperature and air temperature. To ensure data consistency, this study resampled the spatial resolution of ERA5-Land variables to 500 m and synthesized the temporal resolution into 8-day data for ease of calculation with MODIS. (3) The MOD16A2 evapotranspiration dataset, derived from MODIS (Moderate Resolution Imaging Spectroradiometer) satellite remote sensing data and processed using the Penman-Monteith equation, was selected for evapotranspiration analysis. This dataset provides global vegetation cover evapotranspiration data with an 8-day temporal resolution and 500 m spatial resolution, covering the period from 2001 to 2022. (4) The Leaf Area Index (LAI) data, obtained from the MOD15A2H Version 6.1 product of the Moderate Resolution Imaging Spectroradiometer (MODIS), has an 8-day temporal resolution and 500 m spatial resolution, covering the period from 2001 to 2022. (5) In this study, six stations were selected from the Qinghai-Tibet Plateau region of China for data accuracy validation, representing four major ecosystems: evergreen coniferous forests, alpine grasslands, wetlands, and shrubland (Table 1). The observed meteorological data used in this study were obtained from the Arou, Dashalong, and Guantan sites. These three stations were established as part of the Black River Integrated Remote Sensing Joint Experiment (Watershed Allied Telemetry Experimental Research, WATER). Data from the Haibei shrubland site, Haibei Wetland site, and Dangxiong site were freely obtained through the China FLUX website (China Flux Observation Research Union). \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Name** & **Altitude (m)** & **Longitude (\({}^{\circ}\))** & **Latitude (\({}^{\circ}\))** & **Time** & **Underlying Surface** \\ \hline Guantan & 2835 & 100.2863 E & 38.556 N & 2010–2011 & Evergreen coniferous forest \\ Dashalong & 3033 & 100.4643 E & 38.0473 N & 2015–2020 & Grassland \\ Arou & 3739 & 98.9406 E & 38.8399 N & 2014–2021 & Alpine grassland \\ Haibei-Shrub & 3250 & 101.31667 E & 37.61667 N & 2006–2010 & Shrublands \\ Haibei-Wetland & 3250 & 101.32240 E & 37.60991 N & 2004–2009 & Wetland \\ Dangxiong & 4313 & 91.06639 E & 30.49727 N & 2004–2010 & Alpine grassland \\ Ali & 4271 & 79.70 E & 33.38 N & 2010.9.6 - \\ Lijiang & 3560 & 100.23 E & 27.17 N & 2013–2025 & Alpine grassland \\ Maduo & 4410 & 97.32 E & 34.63 N & 2014.5.25–10.31 & Alpine grassland \\ Muztag & 3668 & 74.95 E & 38.66 N & 2016 & Alpine grassland \\ Mt. Everest & 4276 & 86.56 E & 28.21 N & 2016 & Shrublands \\ Shenzha & 4750 & 88.70 E & 30.95 N & 2017–2018 & Wetland \\ Naqu & 4598 & 92.01 E & 31.64 N & 2014–2018 & Alpine grassland \\ Zoige & 3460 & 102.87 E & 33.93 N & 2008–2009 & Wetland \\ Sanjiangyuan & 3960 & 100.55 E & 34.35 N & 2012–2016 & Alpine grassland \\ \hline \hline \end{tabular}
\end{table}