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Can an ensemble give anything more than Gaussian probabilities?
School of Mathematics, Kingston University, Kingston upon Thames, KT1 2EE, UK
Abstract. 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.
Full Article (PDF, 133 KB)
Citation: Denholm-Price, J. C. W.: Can an ensemble give anything more than Gaussian probabilities?, Nonlin. Processes Geophys., 10, 469-475, 2003. Bibtex EndNote Reference Manager
