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This was also a case for the MISTRAL initiative (an EU project in which Italian partners and ECMWF have collaborated). In that project we have the "Italy flash flood use case", spearheaded by ECMWF, in which post-processing, of different types, is applied to the ECMWF ENSemble, and also a 2.2km Italy-centred limited area COSMO ensemble. The post-processed outputs are blended together, with lead-time-dependant weighting, to make the final product, which aims to give better probabilistic rainfall forecasts, in particular with a view to providing improved early warnings of flash flood risk (via the association with extreme short period rainfall). Users are encouraged to focus on the higher percentiles (or probabilities of exceeding high thresholds) in the MISTRAL products, to gauge the potential for localised extremes. However the plots below illustrate how the ensemble mean is handled in the raw model and post-processed output, with differences between the two (for a given system) indicating the nature of any bias-correction being applied on the model grid-scale.
| Model | DT 12UTC 26th | DT 00UTC 27th | DT 12UTC 27th | DT 00UTC 28th |
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| Model | 1. Raw ECMWF ENSemble | 2. Post-processed ENS (ecPoint) | 3. Raw COSMO Ens | 4. Post-Processed COSMO Ens | 5. Difference: 1 minus 3 |
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