Global comparison of light use efficiency models for simulating terrestrial vegetation gross primary production based on the LaThuile database
Yuan, Wenping | Cai, Wenwen | Xia, Jiangzhou | Chen, Jiquan | Liu, Shuguang | Dong, Wenjie | Merbold, Lutz | Law, Beverly | Arain, Altaf | Beringer, Jason | Bernhofer, Christian | Black, Andy | Blanken, Peter D. | Cescatti, Alessandro | Chen, Yang | Francois, Louis | Gianelle, Damiano | Janssens, Ivan A. | Jung, Martin | Kato, Tomomichi | Kiely, Gerard | Liu, Dan | Marcolla, Barbara | Montagnani, Leonardo | Raschi, A. | Roupsard, Olivier | Varlagin, Andrej | Wohlfahrt, Georg
Simulating gross primary productivity (GPP) of terrestrial ecosystems has been a major challenge in quantifying the global carbon cycle. Many different light use efficiency (LUE) models have been developed recently, but our understanding of the relative merits of different models remains limited. Using CO2 flux measurements from multiple eddy covariance sites, we here compared and assessed major algorithms and performance of seven LUE models (CASA, CFix, CFlux, EC-LUE, MODIS, VPM and VPRM). Comparison between simulated GPP and estimated GPP from flux measurements showed that model performance differed substantially among ecosystem types. In general, most models performed better in capturing the temporal changes and magnitude of GPP in deciduous broadleaf forests and mixed forests than in evergreen broadleaf forests and shrublands. Six of the seven LUE models significantly underestimated GPP during cloudy days because the impacts of diffuse radiation on light use efficiency were ignored in the models. CFlux and EC-LUE exhibited the lowest root mean square error among all models at 80% and 75% of the sites, respectively. Moreover, these two models showed better performance than others in simulating interannual variability of GPP. Two pairwise comparisons revealed that the seven models differed substantially in algorithms describing the environmental regulations, particularly water stress, on GPP. This analysis highlights the need to improve representation of the impacts of diffuse radiation and water stress in the LUE models.
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