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Øyvind Saetra
Jean-Raymond Bidlot


The potential benefits of using the ECMWF Ensemble Prediction System (EPS) for waves and marine surface winds are demonstrated using buoy and platform data as well as altimeter data.

For forecasting purposes, the spread of the different forecasts in the ensemble may indeed be regarded as a measure of the uncertainties in the deterministic predictions. In order to demonstrate this point, a new method is presented in which the ensemble spread is divided into different classes. An upper bound for the model errors is established by calculating the corresponding percentiles of the errors for each separate class. Using this upper bound for the model errors, a strong correlation between the ensemble spread and the deterministic forecast skill is shown.

The reliability of the probability forecasts as derived from the EPS for wind and waves is found to be good. However, the reliability diagrams indicate a small tendency for overconfidence in the wave probability forecasts for waves above 6 and 8 m. This is most pronounced in the Southern Hemisphere, whereas the reliability for the Northern Hemisphere is relatively good.

The impact of using of the wave EPS in decision making is studied by a cost–loss model for the relative economic value. For comparison, poor-man's ensembles (PMEs) are also created by adding normally distributed noise to the control forecasts. This study reveals that the real EPS performs better than both the PME and the control forecasts in terms of relative economic value. When more complex forecasting parameters are considered, such as the joint probability of wave height and period, benefits of using the EPS become even more pronounced.

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