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• Sources of forecast uncertainty: initial analysis and model error.
• Initial analysis uncertainty: sampled by use of Singular Vectors (SV) and Ensemble Data Assimilation (EDA).
• Model uncertainty: sampled by use of stochastic processes. In IFS this means Stochastically Perturbed Physical Tendencies (SPPT) and the spectral backscatter scheme (SKEB)
• Singular Vectors: a way of representing the fastest growing modes.
  
  
• Ensemble mean : this gives the average of all the ensemble members. Where the spread is high, small scale features can be smoothed out in the ensemble mean.
• Ensemble spread : this gives the standard deviation of the ensemble members and represents how different the members are from the ensemble mean.

Ensemble exercise tasks

This exercise comprises more tasks than the previous two.One of the difficulones.

Visualising ensemble exercises can be done in various ways. During this exercise, in order to understand the errors and uncertainties in the forecast, we will use a number of visualisation techniques.

Key questions

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Note that as only 6hrly wind gust data is available from the operational forecasts, we have supplemented the 3hrly fields using forecast data

Task ??. CDF/RMSE at different

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locations  <<< WHERE DOES THIS FIT???

Recap

TO DO: RMSE & CDF (concepts need explanation)

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• EDA+SV+SPPT+SKEB : Includes initial data and model uncertainty (experiment id : gbzl) <<< CHANGE THESE
• EDA+SV only                 : Includes only initial data uncertainty (experiment id: gc11)
• SPPT+SKEB only          : Includes model uncertainty only (run by participants, experiment id: oifs)

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