## 3 Results
### Attribution Analysis of the Distribution of Carbon Fluxes  
It is crucial to analyze the correlation between the spatial and temporal variability of carbon fluxes and key variables to facilitate the study and prediction of carbon fluxes. For this purpose, we have identified the most significant factors that impact the variability of carbon fluxes, aiming to investigate their relationship with the spatial and temporal variability patterns of carbon fluxes. In this section, we have chosen FAPAR (fraction of absorbed photosynthetically active radiation), LAI, air temperature (TA), and latent heat flux (LE) for attribution analysis. Figures 7 and 8 calculate the regional averages of the four aforementioned predictors on a global scale and within seven climate zones over the years. In terms of global trends, both remote sensing variables, FAPAR and LAI, exhibit an upward trend over time, with a more notable increase especially after 2010. The global mean of FAPAR increases from 0.30 in 1999 to 0.34 in 2019, while LAI increases from 1.11 in 1999 to 1.24 in 2019. This upward trend aligns relatively consistently with the rising trend in global carbon fluxes. The results for different climate zones indicate that FAPAR and LAI have higher values in tropical and oceanic climate zones compared to other regions. Furthermore, both variables display varying magnitudes of increasing trends within each climate zone, with relatively larger increases in dry, subtropical, continental, and polar climate zones. These findings suggest that the rising FAPAR and LAI are important factors contributing to changes in carbon flux. The time series of temperature, globally and within each climate zone, also exhibit a certain upward trend, indicating a relationship between carbon flux changes and temperature increase. Among the climate zones, the greatest increase in temperature occurs in tropical and subtropical regions. Latent heat fluxes show a decreasing trend over time in the Mediterranean, continental, and polar climatic zones, while in other regions, they mainly demonstrate relatively large fluctuations. Overall, remote sensing variables and temperature changes over time are the primary factors influencing the temporal characteristics of carbon fluxes. Figure 6: Box plot of the distribution of carbon fluxes globally and within each climate zone, with data derived from the average spatial distribution of carbon fluxes from 1999 to June 2020. Figure 8: Time series of the global average and the regional average within each climate zone for FAPAR, LAI, air temperature, and latent heat fluxes. The variables are normalized for comparison. Figure 7: Time series of the global average and the regional average within each climate zone for the three carbon fluxes. The variables are normalized for comparison. The latitudinal average distribution of the three carbon fluxes and four predictors were calculated using the spatial distribution maps, which were obtained by averaging across all time points as depicted in Figure 9. Figure 10 shows the spatial distribution of three carbon fluxes and four predictors. The findings confirm the previous analysis, indicating that GPP and RECO exhibit the highest values at lower latitudes, while carbon sinks are primarily located in the southern hemisphere and the tropics. Specifically, GPP reaches its maximum value of 7.13 g C m\({}^{-2}\) d\({}^{-1}\) at 1.5\({}^{\circ}\) S, whereas RECO peaks at 6.30 g C m\({}^{-2}\) d\({}^{-1}\) at 5.0\({}^{\circ}\) S. Conversely, NEE exhibits the lowest value of \(-\)1.27 g C m\({}^{-2}\) d\({}^{-1}\) at 41.5\({}^{\circ}\) S. The distribution of the two remote sensing variables reveals that the carbon fluxes attain their peaks in regions that correspond to the peaks of FAPAR and LAI, with both FAPAR and LAI reaching their maximum values at 1\({}^{\circ}\) N. Overall, the latitudinal distribution of carbon fluxes aligns well with the remote sensing variables.