The Joint Calibration Model in probabilistic weather forecasting: some preliminary issues
| Autor: | Patrizia Agati, Daniela Giovanna Calò, Luisa Stracqualursi |
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| Jazyk: | angličtina |
| Rok vydání: | 2013 |
| Předmět: | |
| Zdroj: | Statistica, Vol 68, Iss 1, Pp 117-127 (2013) |
| Druh dokumentu: | article |
| ISSN: | 0390-590X 1973-2201 |
| DOI: | 10.6092/issn.1973-2201/3524 |
| 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). |
| Databáze: | Directory of Open Access Journals |
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