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Making Forecasts for Chaotic Physical Processes

Physical Review Letters, , , 2006


Status: Published

Citations:

Cite: [bibtex]


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Abstract: Making a prediction for a chaotic physical process involves specifying the probability associated with each possible outcome. Ensembles of solutions are frequently used to estimate this probability distribution. However, for a typical chaotic physical system H and model L of that system, no solution of L remains close to H for all time. We propose an alternative. This Letter shows how to inflate or systematically perturb the ensemble of solutions of L so that some ensemble member remains close to H for orders of magnitude longer than unperturbed solutions of L. This is true even when the perturbations are significantly smaller than the model error.



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