Accurate and reliable estimates of gross primary productivity (GPP) are required for monitoring the globalcarbon cycle at different spatial and temporal scales. Because GPP displays high spatial and temporal vari-ation, remote sensing plays a major role in producing gridded estimates of GPP across spatiotemporalscales. In this context, understanding the strengths and weaknesses of remote sensing-based models ofGPP and improving their performance is a key contemporary scientific activity. We used measurementsfrom 157 research sites (∼470 site-years) in the FLUXNET “La Thuile” data and compared the skills of11 different remote sensing models in capturing intra- and inter-annual variations in daily GPP in sevendifferent biomes. Results show that the models were able to capture significant intra-annual variationin GPP (Index of Agreement = 0.4–0.80) in all biomes. However, the models’ ability to track inter-annualvariation in daily GPP was significantly weaker (IoA < 0.45). We examined whether the inclusion of differ-ent mechanisms that are missing in the models could improve their predictive power. The mechanismsincluded the effect of sub-daily variation in environmental variables on daily GPP, factoring-in differentialrates of GPP conversion efficiency for direct and diffuse incident radiation, lagged effects of environmen-tal variables, better representation of soil-moisture dynamics, and allowing spatial variation in modelparameters. Our analyses suggest that the next generation remote sensing models need better represen-tation of soil-moisture, but other mechanisms that have been found to influence GPP in site-level studiesmay not have significant bearing on model performance at continental and global scales.

VERMA M.;  FRIEDL Mark A.;  LAW Beverly;  BONAL Damien;  KIELY Gerald;  BLACK A.;  WOHLFAHRT G.;  MOORS E.J.;  MONTAGNANI Leonardo;  MARCOLLA B.;  TOSCANO P;  VARLAGIN Andrej;  ROUPSARD Olivier;  CESCATTI Alessandro;  ARAIN Altaf M.;  D'ODORICO Petra; 

2018-01-16

ELSEVIER SCIENCE BV

JRC99997

0168-1923,   

http://www.sciencedirect.com/science/article/pii/S0168192315007108?via%3Dihub,    https://publications.jrc.ec.europa.eu/repository/handle/JRC99997,   

10.1016/j.agrformet.2015.09.005,