Optimization of Model Parameters, Uncertainty Quantification and\n Experimental Designs for a Global Marine Biogeochemical Model

Methods for model parameter estimation, uncertainty quantification and\nexperimental design are summarized in this paper. They are based on the\ngeneralized least squares estimator and different approximations of its\ncovariance matrix using the first and second derivative of the model regarding\nits parameters. The methods have been applied to a model for phosphate and\ndissolved organic phosphorus concentrations in the global ocean. As a result,\nmodel parameters have been determined which considerably improved the\nconsistency of the model with measurement results. The uncertainties regarding\nthe estimated model parameters caused by uncertainties in the measurement\nresults have been quantified as well as the uncertainties associated with the\ncorresponding model output implied by the uncertainty in the model parameters.\nThis allows to better assess the model parameters as well as the model output.\nFurthermore, it has been determined to what extent new measurements can reduce\nthese uncertainties. For this, the information content of new measurements has\nbeen predicted depending on the measured process as well as the time and the\nlocation of the measurement. This is very useful for planning new measurements.\n