A model represents the way in which information about the world is captured in a form that can be manipulated for application to new situations. However, quantification of ‘model error’ presents formidable challenges. Various inverse problems in carbon cycle modelling are presented as illustrations of the issues. A ‘maximum-entropy’ representation of carbon cycle response is used to explore techniques for non-parametric estimation of carbon cycle uncertainty.
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