Can an ensemble give anything more than Gaussian probabilities?
| Autor: | J. C. W. Denholm-Price |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2003 |
| Předmět: | |
| Zdroj: | Nonlinear Processes in Geophysics, Vol 10, Iss 6, Pp 469-475 (2003) |
| Druh dokumentu: | article |
| ISSN: | 1023-5809 1607-7946 |
| Popis: | Can a relatively small numerical weather prediction ensemble produce any more forecast information than can be reproduced by a Gaussian probability density function (PDF)? This question is examined using site-specific probability forecasts from the UK Met Office. These forecasts are based on the 51-member Ensemble Prediction System of the European Centre for Medium-range Weather Forecasts. Verification using Brier skill scores suggests that there can be statistically-significant skill in the ensemble forecast PDF compared with a Gaussian fit to the ensemble. The most significant increases in skill were achieved from bias-corrected, calibrated forecasts and for probability forecasts of thresholds that are located well inside the climatological limits at the examined sites. Forecast probabilities for more climatologically-extreme thresholds, where the verification more often lies within the tails or outside of the PDF, showed little difference in skill between the forecast PDF and the Gaussian forecast. |
| Databáze: | Directory of Open Access Journals |
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