Abstract
Abstract This chapter is a short survey of the inverse modelling and parameter estimation methods currently used in the atmosphere and ocean sciences. The focus is on the estimation of model parameters. This can go as far as large parameter fields such as forcing fields that may drive or constrain a model. Future efficient data assimilation systems will probably incorporate these fields as part of control space. This overview of inverse modelling techniques describes regularization, information processing, Bayesian, and maximum entropy on the mean approaches, and estimation of the regularization parameters. Each concept introduced in this overview is illustrated using the concrete example of the inversion of the Chernobyl radionuclides source term with the help of a three-dimensional dispersion model.
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