Large-scale estimation of terrestrial GPP for regions, continents, or the globe can improve our understanding of the feedbacks between the terrestrial biosphere and the atmosphere in the context of global change and facilitate climate policy-making. However, model based estimates of bio-geophysical variables are subject to uncertainty. This study evaluated five LUE models, i.e. MODIS-GPP, VPM, TG, GR and VI and simulated the spatial-temporal pattern of gross primary productivity in Northern China based on 17 site-year eddy covariance (EC) measurements from ChinaFlux database. The uncertainty of gross primary productivity in grassland ecosystem was also quantified.
Results/Conclusions
The results showed that the annual grassland GPP in Northern China during 2001-2012 was 206.3 g C m-2 a-1, increasing from the west to the east, with 46% relative uncertainty, with larger uncertainty occurring in regions with lower grassland GPP density. Temperature could contribute more to GPP uncertainty compared with other environmental controls. Our analysis provides an alternative and quantitative fashion that can be used in regional carbon cycle evaluation.