## 2 Materials and Methods
### Data Collection  
#### 2.2.1 In Situ Measurements  
To assess the precision of GPP estimation, in situ measurements within China were collected from the following three datasets (Table S1). The first data type is the global FLUXNET2015 dataset ([[https://fluxnet.org/data/fluxnet2015-dataset/](https://fluxnet.org/data/fluxnet2015-dataset/)]([https://fluxnet.org/data/fluxnet2015-dataset/](https://fluxnet.org/data/fluxnet2015-dataset/)), last access: 19 May 2022), which provides over 200 variables of CO\({}_{2}\), water, energy change, meteorological and biological measurements between the biosphere and the atmospheric processed at the site scale by the FLUXNET community. In this research, ten regional FLUXNET sites across China were employed to assess the effectiveness of the improved GPP estimation model, including five major terrestrial ecosystem vegetation types. The GPP value used in this study was GPP_NT_VUT_REF estimated from the nighttime partitioning method. In the FLUXNET 2015 dataset, quality flags varied from 0 to 1, representing the percentage of measured and high-quality gap-filled data. The daily values were aggregated for each variable into a monthly interval.  
The second data type is the dataset of primary production, respiration and net production in Chinese typical terrestrial ecosystems based on the literature integration [17]. This dataset covers measured GPP, ecosystem respiration, and net productivity for 57 distinct terrestrial ecosystems, including forests, grasslands, croplands and wetlands. In addition, biological and climatic information such as climatic zones, vegetation types, mean annual temperature and total annual precipitation are also included. The multi-year observed mean GPP at each site was used to validate the GPP estimation accuracy.  
Moreover, this study adopted the reference carbon cycle dataset for typical Chinese forests via collocated observations and data assimilation as the third type of validation data [18]. Utilizing data from the CERN long-term dynamic monitoring database, this dataset provides a long time series of baseline observational carbon cycle data for typical forest ecosystems in China over the past ten years, using assimilation-acquired sets of key carbon cycle process parameters and time-continuous data sets of carbon sequestration functional products, including vegetation, soil carbon pools, productivity, respiration and carbon sinks. Different from the second data type, this dataset contains some additional observations of forest ecosystems that were not available in the previous.  
The validation dataset comprised data from 71 sites, spanning different periods from 2000 to 2015 depending on the specific location. These sites represent a wide range of 11 major ecosystem types, as outlined in Table S1. The ecosystem types encompass deciduous needleleaf forest (DNF), evergreen needleleaf forest (ENF), deciduous broadleaf forest (DBF), evergreen broadleaf forest (EBF), mixed forest (MF), shrub (SHR), grassland (GRA), dryland (DRL), savanna (SAV), desert (DES), and wetland (WET).  
Figure 1: The geographic position of the study region. (**A**) Land cover map from the MCD12Q1 product and the locations of validation sites. (**B**) Elevation of the Qinghai–Tibet Plateau.