Ensemble calibration and sensitivity study of a surface CO₂ flux scheme using an optimization algorithm

Because the in situ measurements are not dense enough to resolve CO2 exchange spatial variation on various scales, the variation has been mainly simulated by numerical ecosystem models. These models contain large uncertainties in estimating CO2 exchange owing to incorporating a number of empirical parameters on different scales.

This study applied a global optimization algorithm and ensemble approach to a surface CO2 flux scheme to (1) identify sensitive photosynthetic and respirational parameters, and (2) optimize the sensitive parameters in the modeling sense and improve the model skills. The photosynthetic and respirational parameters of corn (C4 species) and soybean (C3 species) in NCAR land surface model (LSM) are calibrated against observations from AmeriFlux site at Bondville, IL during 1999 and 2000 growing seasons.