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The coloured background is the model climatology (see Figure 3b). This climatology is generated using reforecasts over a 20-year period. Further information on the climatologies and their generation is given here: Placeholder CEMS-flood sub-seasonal and seasonal forecast signal generation methodology for the sub-seasonal and Placeholder CEMS-flood seasonal forecast generation methodology for the seasonal. In the past half of the hydrograph, the climatology is always lead time 1, so first week (always as days 1-7) or first month (whichever month of the year it is), as that is the closest equivalent to the proxi-observation-based climatology. While in the forecast half, the climatologies are lead time dependent and for each forecast lead time the equivalent climatology is plotted with that specific lead time. From the climatology, the 5 anomaly categories are coloured, below the 10th the 'Extreme low' with red, above the 90th percentile the 'Extreme high' with blue, the 10th to 25th percentiles zone as 'Low' with orange, the 75th to 90th percentiles as 'High' with cyan and finally the remaining 25th to 75th percentile as 'Near normal' with grey. This 'Near normal' category is the extended one (see it being mentioned also with the river network summary map above), by merging the original 25-40, 40-60 and 60-75 percentile categories, including the narrower 'Near normal', the 'Bit low' and 'Bit high' categories.
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The basin summary map is the equivalent of the river network summary map on a averaged onto the larger basin scale. The basins are predefined, as described in Placeholder CEMS-flood sub-seasonal and seasonal basins and representative stations, with 204 basins in the EFAS domain and 944 basins globally in GloFAS.
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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. The basin Rank-mean/Rank-std values will be 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:
in the averaging.average Rank-mean is calculated as the arithmetic mean of the Rank-mean values of the river pixels in the basin, while the basin-average Rank-std is calculated again as the arithmetic mean of the Rank-std values at the pixels.
Figure 4. Example snapshot of the sub-seasonal and seasonal river network summary maps with the animation and river pixel colours explained.
At the predefined reporting point locations (either fixed or basin-representative) further detailed information is provided about the evolution of the forecast signal.
The river network summary map layer shows the combined forecast anomaly and uncertainty signal in a simplified way for each forecast lead time (Figure 1). The lead time is weekly (always Monday to Sunday, with the weekly average river discharge) in the sub-seasonal and monthly (always calendar month, with the monthly average river discharge).
The forecasts can be advanced (or even animated if needed) with the lead time controller (see Figure 1a bottom left corner) and the users can check the individual signal for each lead time, which currently is 5 or 6 weeks for the sub-seasonal (depending on which day of the week the run date is) and always 7 months for the seasonal.
The forecast signal is shown by colouring of all river pixels above a certain minimum catchment area (currently 50 km2 in EFAS and 250 km2 in GloFAS). Each of these river pixels are coloured by the dominant anomaly category and by the uncertainty category.
There are 7 anomaly categories and three uncertainty categories defined based on the extremity level of the ensemble forecast members in the 99-value percentile climatological distribution. The details of the computation methodology is described here: Placeholder CEMS-flood 
Figure 4. Example snapshot of the sub-seasonal and seasonal forecast anomaly and uncertainty computation methodology.On the river network summary map, however, only 5 anomaly categories are displayed, after combining the middle three into one larger 'Near normal' category, which allow the users to focus visually on the larger anomalies. Each of these categories are divided into three sub-categories by the uncertainty, as low, middle and high uncertainty, in total making it into 15 forecast signal categories. The inset figure in both Figure 1a and 1b shows the 15 categories and the corresponding colours on the maps .Figure 1a highlights some river sections with the explanation of the assigned colours and the corresponding anomaly and uncertainty levels. Each of the 5 anomaly categories have a distinct colour, where the 3 uncertainty categories is indicated by lighter colours as the uncertainty increases.
The river network summary map also contains the reporting points, which are labelled as example in Figure 1b. These are river locations, where detailed information is provided about the evolution of the forecast signal over the forecast horizon. There reporting points are either fixed points, which are also used in the medium-range flood products and the basin-representative points, which are selected locations, on a one point per basin basis. Further details about the basins and the representative points are available here: Placeholder CEMS-flood sub-seasonal and seasonal basins and representative stations.
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animation panel and river pixel colours explained.