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ENS - Ensemble Forecasts

The ensemble forecast suite (ENS) forecasts provide  provides a range of possible future weather states in the medium range.  It runs daily from .  This allows investigation of the detail and uncertainty in the forecast during the first 10 days or 15 days.

The medium range ensemble (ENS):

• • is run four times daily:
    • base times 00 UTC and 12 UTC

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• • • , producing a 10 day forecast (T+0 to T+240) and also a 15 day forecast (T+0 to T+360).
    • base times 06UTC and 18UTC, producing a 6 day forecast (T+0 to T+144). Results from these runs are:
      • used in Early cut off analysis (SCDA) and Long window data analysis (LWDA).
      • disseminated T+0 to T+72.
  • has horizontal resolution of 9

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• • Km and vertical resolution of 137 model levels

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• • .  These values are the same as those of the High Resolution (HRES) in earlier IFS versions.
  • has land-atmosphere and ocean-atmosphere coupling.
  • has 50 ensemble members plus an unperturbed control member (CTRL).
  • the unperturbed control member (CTRL) corresponds to the High Resolution (HRES).
  • documentation gives details of medium range products and dissemination schedules

The ensemble consists of one unperturbed control member (CTRL.  The ensemble consists of one unperturbed member (the control) and 50 perturbed members that .  These are similar to the control control member but their differ only that initial states and model physics have been perturbed to explore .  This allows  exploration of 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 (or, for that matter, HRES), though control member.  Nevertheless any individual forecast might show a higher skill.   There is a  A range of ensemble products to present the information from the ensemble show information in different ways , and appropriate for different uses including .  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 ENS model climate (M-climate), such as .  Particularly important are meteograms and the Extreme Forecast Index and Shift of Tails (EFI/SOT).   From these one can infer, for example, whether conditions (temperature, rainfall, etc.) are likely to  The ENS products and chart presentations show where and when weather may deviate from the average for the location and time of year, and whether if such an anomaly could be extreme.  The ENS products and presentation in chart or diagram form are described later in the user guide.

Ensemble ENS 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 , such as tropical cyclones.The ENS runs are extended at lower resolution on Mondays and Thursdays from Day15 to Day46 based on 00UTC data time (the extended range forecasts(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).

Additional Sources of Information

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

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• 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.