This page describes the way the anomaly and uncertainty of the ensemble forecasts in the sub-seasonal and seasonal products are determined using the climatology as reference. This includes also how the expected forecast anomaly category (one of the 7 predefined onesamongst 5 or 7 pre-defined categories) and the uncertainty category (of the 3 predefined ones of divided in 3 categories low/medium/high) of the ensemble forecasts are determined. This is a generic procedure, which is the same for both EFAS and GloFAS, as it is executed the same way for each river pixel, regardless of the resolution, and also the same for the sub-seasonal and seasonal products, as it works in the exact same way regardless of whether it is weekly mean values, as in the sub-seasonal, or monthly mean values, as in the seasonal.
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Based on the percentiles and the related 100 bins, there are seven anomaly categories defined, which will be used as anomaly categories can be defined (Table 1). These are also indicated by vertical lines separating them in Figure 1. The two most extreme categories are the bottom and top 10% of the climatological distribution (<10% as 'Extreme low' and 90%< as 'Extreme high'). Then the moderately low and high river discharge categories from 10-25% ('Low') and 75-90% ('High'). The smallest negative and positive anomalies are defined by 25-40% ('Bit low') and 60-75% ('Bit high'). Finally, the normal condition category is defined as 40-60%, so the middle 1/5th of the distribution, the area called 'Normal' in Figure 1. In addition, for some web products For simplification, the middle three categories of 'Bit low', 'Normal' and 'Bit high' are merged combined into one larger 'Near normal' category, covering the percentiles from 25th to 75th for graphical products (maps and hydrographs). This 'Near normal' category is also indicated in Figure 1 and Table 1.
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