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Forecast uncertainty category computation
In addition to the expected forecast anomaly computation for the whole ensemble, as one of 7 predefined categories, the forecast uncertainty is also represented in some of the sub-seasonal and seasonal products, namely on the new 'Seasonal outlook - River network' and 'Seasonal outlook - Basin summary' products. The forecast uncertainty is defined by the standard deviation (std) of the ensemble member ranks, which all can be from 1 to 100 (rank-std):
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If the ensemble member ranks cluster well, and the spread of the ranks is low, then the forecast uncertainty will be is low and conversely the confidence will be is high. One specific example is the even distribution with 51 values spread from 1 to 100 evenly, as ranks of 1, 3, 5,..., 47, 49, 50 (or 51), 52, 54,..., 96, 98 and 100. This distribution has a mean of very close to 50.5 and a standard deviation of very close to 29.0. Then another example can be the most uneven distribution of rank values of 1, 1, 1, ..., 1, 100, 100, 100,..., 100, with either 25 values of 1 and 26 values of 100 or vice versa. In this case the rank-mean is either 49.5 or 51.5 (depending on either 1 or 100 has 26 and not 25 values) and the standard deviation is in both case the same 49.5. Another specific example is when all values are the same, so there is no variability amongst the 51 ranks at all, in which case the rank-mean is the same value and the rank-std is 0.
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