Parameter optimization using algorithmic differentiation in a reduced-form model of the Atlantic thermohaline circulation

Optimizing some model parameters a reduced-form model of the Atlantic thermohaline circulation is fitted to data provided by a comprehensive climate model. Different techniques to compute stationary states of the reduced-form model are discussed. The fitting problem is formulated as weighted least-squares optimization problem with non-linear constraints that enforce a proper representation of the present climate. Possible formulations of the optimization problem are presented and compared with respect to their numerical treatment. The technique of algorithmic or automatic differentiation (AD) is used to provide gradient information that can be used in the optimization. The application of the AD software is described in detail and numerical results are given.

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