A Bayesian Hierarchical Approach to Ensemble Weather Forecasting

Cocchi, Daniela ; Di Narzo, Antonio Fabio (2008) A Bayesian Hierarchical Approach to Ensemble Weather Forecasting. Bologna, IT: Dipartimento di Scienze Statistiche "Paolo Fortunati", Alma Mater Studiorum Università di Bologna, p. 26. DOI 10.6092/unibo/amsacta/2462. In: Quaderni di Dipartimento. Serie Ricerche ISSN 1973-9346.
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In meteorology, the traditional approach to forecasting employs deterministic models mimicking atmospheric dynamics. Forecast uncertainty due to the partial knowledge of initial conditions is tackled by Ensemble Predictions Systems (EPS). Probabilistic forecasting is a relatively new approach which may properly account for all sources of uncertainty. In this work we propose a hierarchical Bayesian model which develops this idea and makes it possible to deal with an EPS with non-identifiable members using a suitable definition of the second level of the model. An application to Italian small-scale temperature data is shown.

Document type
Monograph (Working Paper)
Cocchi, Daniela
Di Narzo, Antonio Fabio
Ensemble Prediction System, hierarchical Bayesian model, predictive distribution, probabilistic forecast, verification rank histogram.
Deposit date
21 May 2008
Last modified
16 May 2011 12:08

Other metadata

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