A Bayesian hierarchical approach to ensemble weather forecasting

A. F. Di Narzo and D. Cocchi

Journal of the Royal Statistical Society Series C, 2010, vol. 59, issue 3, 405-422

Abstract: Summary. In meteorology, the traditional approach to forecasting employs deterministic models mimicking atmospheric dynamics. Forecast uncertainty due to partial knowledge of the initial conditions is tackled by ensemble predictions systems. Probabilistic forecasting is a relatively new approach which may properly account for all sources of uncertainty. We propose a hierarchical Bayesian model which develops this idea and makes it possible to deal with ensemble predictions systems with non‐identifiable members by using a suitable definition of the second level of the model. An application to Italian small‐scale temperature data is shown.

Date: 2010
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https://doi.org/10.1111/j.1467-9876.2009.00700.x

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