The CEMS-flood sub-seasonal and seasonal products are essentially the same across the two systems and similarly the same across EFAS and GloFAS. Below we introduce the available products and their main features.
River network summary map
The river network summary map layer shows the combined expected 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 in the seasonal (always calendar month , with the monthly average river discharge).
The forecasts can be navigated (or even animated if needed) with users can navigate between the different lead times by clicking on the chosen weeks (in sub-seasonal) and month (in seasonal) in the lead time controller (see Figure 1a bottom left corner) and . This way 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 forecast 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 expected anomaly category and by the uncertainty category.There There are altogether 7 anomaly categories and 3 uncertainty categories defined, based on the extremity level of the ensemble forecast members in the 99100-value percentile climatological distribution and the mean and standard deviation of these rank values (see Figure 1). The details of the computation methodology is described here: Placeholder CEMS-flood sub-seasonal and seasonal forecast anomaly and uncertainty computation methodology.
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 different categories and related colours are introduced in Figure 1 below.
Figure 1. Example snapshots of the sub-seasonal and seasonal river network summary maps with the reporting points, anim
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.
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