Tower-Based Validation and Improvement of MODIS Gross Primary Production in an Alpine Swamp Meadow on the Tibetan Plateau.

Alpine swamp meadow on the Tibetan Plateau is among the most sensitive areas to climate change. Accurate quantification of the GPP in alpine swamp meadow can benefit our understanding of the global carbon cycle. The 8-day MODerate resolution Imaging Spectroradiometer (MODIS) gross primary production (GPP) products (GPPαMOD) provide a pathway to estimate GPP in this remote ecosystem. However, the accuracy of the GPPαMOD estimation in this representative alpine swamp meadow is still unknown. Here five years GPPαMOD was validated using GPP derived from the eddy covariance flux measurements (GPPαEC) from 2009 to 2013. Our results indicated that the GPPαEC was strongly underestimated by GPPαMOD with a daily mean less than 40% of EC measurements. To reduce this error, the ground meteorological and vegetation leaf area index (LAI_G) measurements were used to revise the key inputs, the maximum light use efficiency (ε_max) and the fractional photosynthetically active radiation (FPARM) in the MOD17 algorithm. Using two approaches to determine the site-specific ε_max value, we suggested that the suitable ε_max was about 1.61 g C MJ^-1 for this alpine swamp meadow which was considerably larger than the default 0.68 g C MJ^-1 for grassland. The FPARM underestimated 22.2% of the actual FPAR (FPARG) simulated from the LAI_G during the whole study period. Model comparisons showed that the large inaccuracies of GPPαMOD were mainly caused by the underestimation of the ε_max and followed by that of the undervalued FPAR. However, the DAO meteorology data in the MOD17 algorithm did not exert a significant affection in the MODIS GPP underestimations. Therefore, site-specific optimized parameters inputs, especially the ε_max and FPARG, are necessary to improve the performance of the MOD17 algorithm in GPP estimation, in which the calibrated MOD17A2 algorithm (GPPαMODR3) could explain 91.6% of GPPαEC variance for the alpine swamp meadow. [ABSTRACT FROM AUTHOR]