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- CEMS-Flood sub-seasonal products are produced every day, showing calendar week averaged river discharge anomalies up to 6 weeks divided into 5 main categories, from extreme low to extreme high compared with a forecast-range dependant climatology.
- CEMS-Flood seasonal products are produced every month, showing monthly averaged river discharge anomalies up to 7 months divided into 5 main categories, from extreme low to extreme high compared with a forecast-range dependant climatology.
- Both sub-seasonal and seasonal products are available for the EFAS and GloFAS systems based on the same methodology.
- Products are shown as maps over the full domain (river network and basin summary versions) with additional information available for reporting points, such as:
- Hydrographs: showing the antecedent conditions of the recent past and the forecast evolution of the future, together with the underlying model climatology to indicate the anomalies.
- Probability evolution tables: showing the forecast probabilities for the different anomaly categories at the different lead times from the most recent forecast runs.
- Map products are plotted for each lead time individually, with the possibility to navigate between them.
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The generation of the sub-seasonal and seasonal forecast signal relies on few major steps, illustrated by a flowchart in Figure 1. The forecast anomaly and uncertainty signals are derived by comparing the real time forecast (top left section in Figure 1) to the 99-value percentile climatology (bottom left section). The climatology is generated using reforecasts over a 20-year period, which provides range-dependent climate percentiles that change with the lead time. The climate generation is described in the bottom left corner of Figure 1.
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The CEMS-Flood sub-seasonal products cover calendar week periods (i.e. always Monday-Sunday), while the CEMS-Flood seasonal products are valid for whole calendar month periods. The forecast signal is derived from the relationship between the calendar weekly or monthly averaged river discharge and the climatological distribution of the historical weekly- or monthly-averaged values. While calendar month naturally allow consistency checks, the fixed-calendar weekly lead-times in the sub-seasonal were introduced to similarly allow users to directly compare forecasts from different forecast runs, as the verification periods will be fixed onto the calendar weeks, with different corresponding lead times from the forecast, depending on the day of the week the forecast did run.
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In order to display the information content of these 51 ensemble rank values, we use a simplified anomaly representation. For this, 7 anomaly categories were defined by the 10th, 25th, 40th, 60th, 75th and 90th percentiles, representing 7 categories from 'Extreme low' to 'Extreme high'; for the maps and hydrographs, the three middle category anomalies are combined in a single anomaly. In the forecasts, each of these 7 categories will have a probability value, depending on how many of the 51 ensemble members they contain. To simplify the
The overall expected anomaly category of the forecast (one of 5 categories, shown by colours in the river network and basin summary maps and in the hydrograph in the pop-up window; and one of 7 categories (with the middle 'Near normal' one extended into 3), highlighted in the probability evolution table in the pop-up window) is defined by the mean of the 51 ensemble member ranks (rank-mean), which represents a robust anomaly value without any random jumpiness. In addition, the uncertainty about these anomalies is also defined using the standard deviation of the 51 ensemble ranks (rank-std). Based on this rank standard deviation value, one of three uncertainty categories (low / medium / high) are assigned to the forecast.
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