A multi-objective hierarchical calibration procedure for land surface/ecosystem models Land surface and ecosystem processes affect climate and weather in a range of time scales, from seconds to thousands of years. Land surface/ecosystem models (LSEMs) calculate the fluxes between the biosphere and the atmosphere and other ecosystem dynamics processes. In this study, we develop a calibration procedure, based on the theory of ecosystems hierarchy, to optimize all processes simulated by an LSEM. The procedure was implemented on Optis, a software for hierarchical multi-objective calibration of LSEMs. Optis is based on the multi-objective genetic algorithm, Non-dominated Sorted Genetic Algorithm-II (NSGA-II). The calibration was hierarchically performed from the fastest process (radiative fluxes) to the slowest process (carbon allocation), optimizing nine model outputs. The procedure demonstrated to be efficient, with the nine-objective model optimization reaching about 80% of the performance achieved by the mono-objective optimization. This calibration methodology allows a better global performance of the model, as all simulated variables are optimized.

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