Evaluation and improvement of MODIS gross primary productivity in typical forest ecosystems of East Asia based on eddy covariance measurements

Gross primary productivity (GPP) is a major component of carbon exchange between the atmosphere and terrestrial ecosystems and a key component of the terrestrial carbon cycle. Because of the large spatial heterogeneity and temporal dynamics of ecosystems, it is a challenge to estimate GPP accurately at global or regional scales. The 8-day MODerate resolution Imaging Spectroradiometer (MODIS) GPP product provides a near real time estimate of global GPP. However, previous studies indicated that MODIS GPP has large uncertainties, partly caused by biases in parameterization and forcing data. In this study, MODIS GPP was validated using GPP derived from the eddy covariance flux measurements at five typical forest sites in East Asia. The validation indicated that MODIS GPP was seriously underestimated in these forest ecosystems of East Asia, especially at northern sites. With observed meteorological data, fraction of photosynthetically active radiation absorbed by the plant canopy (fPAR) calculated using smoothed MODIS leaf area index, and optimized maximum light use efficiency (ε _max) to force the MOD17 algorithm, the agreement between predicted GPP and tower-based GPP was significantly improved. The errors of MODIS GPP in these forest ecosystems of East Asia were mainly caused by uncertainties in ε _max, followed by those in fPAR and meteorological data. The separation of canopy into sunlit and shaded leaves, for which GPP is individually calculated, can improve GPP simulation significantly.