*4.4. Uncertainty of GPP Modelling of the Desert Ecosystems and Its Implications for GPP Simulation in Arid Regions*

The current MOD17 model can effectively simulate GPP of main ecosystems in the arid region, however, there are still some difficulties in simulating GPP more accurately in the desert ecosystems. Model analyses indicate the importance of arid regions in the global carbon cycle, while the models suffer from a lack of data in water-limited regions [3,4]. The large errors of GPP simulation in desert ecosystems is caused by the uncertainty of remote sensing vegetation products in regions with large heterogeneity of landscape and low vegetation cover. Moreover, the uncertainty of flux tower observation in desert ecosystems makes it is difficult to estimate a relative 'true' value of GPP [58]. To improve GPP estimation in arid regions, several directions can be explored further in the future. For example, improving the estimation of MODIS FPAR and land cover classification products in arid regions using data-driven approaches [59] and improving model structures [60] could be better choices for improving GPP simulation in arid regions.

Meanwhile, since the biome-specific look up tables (BPLUT) are constant for a given biome at any time. Since the current BPLUT of the MOD17 cannot meet the needs of accurate definition of the parameters for all ecosystems [19,61], especially for the diverse and complex ecosystems in arid regions, further research needs to be done to update these BLUPT of the model. In addition to update the parameter of εmax, the water and temperature-limited parameters are also of great importance in GPP estimation, especially for the ecosystems in arid regions. As the development of eddy covariance technique, there are more than 900 EC flux sites in the world currently [62]. With the availability of these large number of flux datasets, it provided us the opportunity to retrieve the biome specific parameters for each vegetation type more reasonable, which may improve the accuracy of the current GPP simulation in the arid region.
