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• • is run four times daily:
    • base times 00 UTC and 12 UTC, 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 Km and vertical resolution of 137 model levels.  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) and 50 perturbed members that .  These are similar to the 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).

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When averaged over many forecasts each of the perturbed members has lower skill than the control member though .  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.  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 .  Particularly important are 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.

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