The paper proposes and illustrates an application of a recently developed methodology called Data Dependent Systems (DDS) to modeling and analysis of solar insolation data. Such an approach is shown to be capable of combining the advantages of deterministic as well as stochastic models. Major dynamic patterns are successfully reproduced by the models. The model characteristics reveal the relation of these patterns to direct and diffuse insolation as well as to constant and variable weather dynamics. The relation of the dynamic patterns with a physical model is developed to show that a more realistic estimate of the extinction coefficient is obtained from the DDS models.

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