Carbon Cycle Data Assimilation System (CCDAS)

Carbon Cycle Data assimilation System (CCDAS)

Schematic of the CARBONES Carbon Cycle Data Assimilation System

A CCDAS has been built on the coupling of a prognostic model of the terrestrial carbon cycle to an optimization system so as to estimate some of the process parameters of the model with respect to various data sources (flux measurements, carbon inventory data, satellite products). The assimilation procedure consists in minimizing a misfit function that measures the mismatch between i) the model outputs, depending on the searched parameters, and the various observation streams, and ii) some a priori knowledge on these parameters and their optimized value. The assimilation framework requires that the model quantities (depending on the parameter to optimize) can be mapped to the various data sources, and that the error statistics (uncertainty) of each are known a priori. Given the uncertainties on the prior values of the parameters and on each observation source, a CCDAS allows deriving the uncertainties on the optimised model parameters. These uncertainties can finally be translated into uncertainty on the data assimilated and other model diagnostic. In CARBONES, as the model used is fully prognostic, we can therefore apply knowledge about the current terrestrial carbon cycle gained during the parameter optimization to predict its evolution into the future (with attached uncertainty on the predicted quantities).