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The ensemble consists of one unperturbed control member (CTRL) and 50 perturbed members that are similar to the control member but their initial states and model physics have been perturbed to explore the currently understood range of uncertainty in the observations and the model.  A set of medium range re-forecasts provide a basis for the medium range model climate medium range model climate (M-Climate).

The medium range 10 day and 15 day ensemble forecasts run with data analysed from the short cut off data analysis (SCDA).  

When averaged over many forecasts each of the perturbed members has lower skill than the control member though any individual forecast might show a higher skill.  There is a range of products to present the information from the ensemble in different ways and appropriate for different uses.  These include probabilities, clusters of alternative scenarios, and tropical cyclone and extra-tropical cyclone products.  Certain important products are based on, or directly show, anomalies relative to the M-climate, such as meteograms and the Extreme Forecast Index and Shift of Tails (EFI/SOT).    The ENS products and chart presentations show where and when weather may deviate from the average for the location and time of year, and if such an anomaly could be extreme.

Ensemble forecasts are run coupled to the Wave model (ECWAM) and the Dynamic Ocean model (NEMO) which includes modelling of sea ice (LIM2).  Atmosphere-ocean coupling occurs every hour.  This high-frequency coupling generally has a positive impact on the forecast development of synoptic-scale systems (e.g. tropical cyclones).

Definitive information on the ECMWF dissemination schedule and products can be found in the the Catalogue of ECMWF real-time products (ENS: Set iii).

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(Note: In older material there may be references to issues that have subsequently been addressed)

• Read an amplification of the above regarding medium-range ensembles and associated Charts and Products
• View the ECMWF eLearning module outline information on the Concept of Ensemble Predictions rational behind probabilistic weather forecasts.
• View the ECMWF eLearning module on the Ensemble Forecasting Introduction - Sources of Forecast Uncertainty.