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In the forecast half, for each forecast period the equivalent climatology is plotted with that specific the appropriate lead time , from one climatological set. For the seasonal, where the climatology is static and produced only once for each month of the year, the climatology with the same month is displayed. For example, for an August 2024 seasonal forecast run, all reforecasts with August run dates (from 20 years) are taken and the climatological percentiles for month1 (August), month2 (September) ..., month7 (February) of those reforecasts are generated and shown on the hydrographs. For the sub-seasonal, on the other hand, the climatologies are produced dynamically for roughly every 4 days (fixed days as 1, 5, 9, 13, 17, 21, 25, 29 of the months). So, for the forecasts, the specific climatological set will be chosen which has the run date closest to the forecast run date. So, for example, for a sub-seasonal forecast of 14 December 2024, the climatology produced for 13 December will be chosen, which is the closest to the 14th from the available climate run dates of 1, 5, 9, 13, 17, 21, 25, 29 in of December. In the antecedent half the hydrographaddition, the week-1 forecast period (the first Mon-Sun period) will have the lead time of days3-9, week-2 is days10-16, week3 is days 17-23, week4 is days24-30, week5 is days31-37 and finally week6 is days 38-44.
In the antecedent half the hydrograph, the climatology with the shortest possible lead time will always be shown. For the seasonal, this will be month-1 for each of the 6 months. For the sub-seasonal, on the other hand, it is a bit more complicated and the climatology will be the shortest lead time that can covers the climatology with the shortest possible lead time will always be shown. For the seasonal, this will be the month-1 lead time, for each of the 6 months. For the sub-seasonal, on the other hand, it is a bit more complicated and the climatology will be the shortest lead time that can covers the actual Monday-Sunday calendar week periods from the most recent cliamate setperiod. In the above example of the sub-seasonal run on the 14th of December 2024, which was a Saturday run, the week-1 forecast period (the first Mon-Sun period) will have the lead time of days3-9, week-2 is days10-16, week3 is days 17-23, week4 is days24-30, week5 is days31-37 and finally week6 is days 38-44. Thus, the first water balance antecedent period will be the Monday-Sunday 6 water balance weekly periods will be 4-10 Nov, 11-17 Nov, 18-24 Nov, 25 Nov - 1 Dec, 2-8 Dec and 9-15 Dec, all Monday-Sunday calendar weeks. The last of these 9-15 Dec, the one before the week-1 forecast, which will be 9-15 December. So, at the time of the generation of the forecast for the 14 December, the water balance for this week will still not be known.
from 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, for each forecast period the equivalent climatology is plotted with that specific lead time.
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not be known by the time the forecast signal is generated and will only be adde a bit later retrospectively.
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Figure 4. Example snapshot of the reporting point pop-up window product's hydrograph, with different interpretation schemes (a-b-c).
The
Figure 4. Example snapshot of the reporting point pop-up window product's hydrograph, with different interpretation schemes (a-b-c).
The coloured background behind the forecast box-and-whiskers plot is the model climatology (see Figure 4b). The climatology is generated using reforecasts over a 20-year period. Further information on the climatologies and their generation is given on: Placeholder CEMS-flood sub-seasonal and seasonal forecast signal generation methodology. The forecast side of the climatology is always from 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, for each forecast period 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 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.
As Figure 4c highlights, the seasonal hydrograph indicates a property of the model climatologies, which is highlighted in Figure 4c. The seasonal hydrograph is designed to have exactly 13 (12+1) monthly periods, which guarantees that the last month of the forecast (February in Figure 4) will feature both as a month-7 forecast climatology and as a month-1 forecast climatology in the past period, as the oldest month plotted. This way, the comparison between the left-most and right-most background colouring of the hydrograph gives a visual impression of the drift in the river discharge forecasts. Drift in this context means, the month-7 climatology could occasionally be very different to the month-1 climatology. There can be a noticeable shift or drift in the forecast behaviour, represented by the change in the reforecast behaviour from shorter to longer ranges (see Figure 4c for visual indication of this).
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Unfortunately, this feature of contrasting the climatological behaviour at shorter and longer lead times, does not work for the sub-seasonal, as there is no 52+1 weeks available in the hydrograph (it would not be physically possible), which would be necessary to see the same week appearing as a week-1 climatology of the past period and as a week-6 climatology of the forecast.The past past half of the hydrograph (left from the forecast run date vertical dotted line) includes 6 lead time period, either the 6 calendar weeks before the first week of the forecast in the sub-seasonal, or 6 calendar months period before the first month of the forecast.
Probability evolution table
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