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The ‘expected to happen’ anomaly category (one of the seven categories) , included also the related uncertainty category (how uncertain the forecast is ; either low, medium or high) are indicated by cell colouring in the table below, having one coloured cell for each lead time and run date (all other cells are left blank). The colour is dependent on the anomaly, but also on the related forecast uncertainty category (how uncertain the forecast is; either low, medium or high). The expected category and the related uncertainty are defined by the ensemble member ranks in the 100-value climatology, based on the rank mean and rank standard deviation (of all the 51 ensemble members' ranks), respectively, as described in Placeholder CEMS-flood sub-seasonal and seasonal forecast anomaly and uncertainty computation methodology.
The used colours in the table are the same as in the river network and basin summary maps (see Figure 1), representing the 15 categories with 15 colours (5 anomaly categories combined with the 3 uncertainty sub-categories), explained above in the 'Product colouring' paragraph. The coloured cell will have the exact same colour that the corresponding pixel (that represents the reporting point location in the river network) has on the 'River network' map layer. In addition, the coloured cell's probability value is displayed bold to be more noticeable.
The coloured cell's probability is often the highest of the 7 categories as well, but not always, like in many forecasts in Figure 4. For example, the forecast for August shows a gradual progression from 'Bit low' anomaly with high uncertainty (lightest grey colour; grey group as the colour of the extended 'Near normal' category) to 'Extreme low' category with low uncertainty (darkest red colour). In addition, the probability value of the coloured cells is generally increasing as we go towards the shorter lead times. But again, this is not always the case, as sometimes the mean of the ensemble member ranks, that define the expected anomaly category, will not coincide with the most probable category.For For example, until the June forecast, the colours are the lightest of the three versions (light orange in the June forecast and light grey in earlier forecasts), which means the uncertainty is was high. While in the July forecast the uncertainty drops to medium level in the same 'Low' category (medium dark orange) and finally in the August forecast we arrive to the low uncertainty in the 'Extreme low' category (dark red). However, at the same time, in all of these forecasts the more likely of the 7 categories are constantly the 'Extreme low' category, with the probability values gradually increasing from 2X in February to 100% in the August forecast (all of the 51 ensemble members being in the 'Extreme low' category). The reason for the earlier forecast the categories shifting towards normal conditions is directly related to the increasing uncertainty with most or all of the categories having some ensemble members.
Out of the 7*3 possible category combinations, 5*3 are represented by colours, after the middle three anomaly categories ('Bit below', 'Normal' and 'Bit high') are merged into one 'Near normal' category. The choice of 5 anomaly categories for the colouring allows the users to focus on the larger anomalies, supplemented by the 3-level uncertainty representation.
The expected anomaly category and the uncertainty subcategory are represented by cell colouring in the table below, having one coloured cell for each lead time and run date. Out of the 7*3 possible category combinations, only 5*3 are represented by colours, after the middle three anomaly categories ('Bit below', 'Normal' and 'Bit high') are merged into one 'Near normal' category. Having only 5 anomaly categories for the colouring was a compromise, which allows the users to focus on the larger anomalies and at the same time retaining the 3-level uncertainty representation with reasonably distinguishable coloursreason for the earlier forecast the categories shifting towards normal conditions is directly related to the increasing uncertainty with most or all of the categories having some ensemble members.
Basin summary map
The basin summary map is the equivalent of the river network summary map averaged onto the larger basin scale. The basins are predefined, as described in in Placeholder CEMS-flood sub-seasonal and seasonal basins and representative stations, with 204 basins in the EFAS domain and 944 942 basins globally in GloFAS.
Figure 4 6 shows an example snapshot in the same area as Figure 1a above. One can compare, how the variable signal on the river network averages into the basin signal. The averaging is done from the river pixel information. A Rank-mean and a Rank-std value will be calculated for each basin and with those the exact same method is used (as for the river pixels on the river network summary map) to define the forecast anomaly category and the uncertainty category and thus the colour of the basin (see the inset figure with the colour legend in Figure 4). The colours used are the same as for the river network summary map, except there is a slight shift in transparency, in order to allow visibility for all river pixels, even for those with the same colour as the basin colour.
The basin Rank-mean and Rank-std values are determined using all the large enough river pixels in the basin. Currently, only pixels above 50km2 are used in EFAS and pixels above 250 km2 are used in GloFAS in the averaging. The basin Rank-mean/Rank-std values are calculated as an arithmetic average of the Rank-mean and Rank-std values of the individual river pixels, weighted by the square of the upstream area, as described below:
Figure 46. Example snapshot of the sub-seasonal and seasonal river network summary maps with the animation panel and river pixel colours explained.
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