The joint calibration model in probabilistic weather forecasting: some preliminary issues
| Autor: | Patrizia Agati, Daniela Giovanna Calò, Luisa Stracqualursi |
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| Přispěvatelé: | P.Agati, D. G. Calò, L. Stracqualursi |
| Jazyk: | angličtina |
| Rok vydání: | 2008 |
| Předmět: | |
| Zdroj: | Statistica, Vol 68, Iss 1, Pp 117-127 (2013) |
| Popis: | Ensemble Prediction Systems play today a fundamental role in weather forecasting. They can represent and measure uncertainty, thereby allowing distributional forecasting as well as deterministic-style forecasts. In this context, we show how the Joint Calibration Model (Agati et al., 2007) – based on a modelization of the Probability Integral Transform distribution – can provide a solution to the problem of information combining in probabilistic forecasting of continuous variables. A case study is presented, where the potentialities of the method are explored and the accuracy of deterministic-style forecasts from JCM is compared with that from Bayesian Model Averaging (Raftery et al., 2005). Statistica; Vol 68, No 1 (2008); 117-127 |
| Databáze: | OpenAIRE |
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