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This case was also relevant 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" (see here and here), 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 some of the plots below illustrate also 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. This plot focusses on a 6h accumulation period, 06-12UTC 28th, when most of the rainfall was diagnosed in the ECMWF model runs to be convective. In contrast Sections 3.2 and 3.3 above deal with a 24h accumulation period.

Model0. Observations (all the same)1.    Raw ECMWF ENSemble2.   PP-ENS (ecPoint)3.   Raw COSMO Ens4.   PP-COSMO Ens5.   Difference: 1 minus 36. 98th %ile ecPoint7. 98th %ile PP-COSMO8. 98th %ile blended
DT 12UTC 26th






DT 00UTC 27th

DT 12UTC 27th






DT 00UTC 28th

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