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The first table in the popup window ('Point information' provides metadata information of the station (Figure 2). These are the station ID and also an internal ID (Point ID), the station name (if available), country, basin and river names, and also coordinates (lat/lon) and upstream area in two flavours, the provided ones and the LISFLOOD river network equivalent. The provided coordinates and upstream area are from the users as those represent the real river gauge location. These are available only for the fixed points (sometimes provided upstream area is missing). For the basin-representative points, however, only the LISFLOOD coordinates and upstream area are available, as these points were defined solely on the simulated LISFLOOD river network. The fixed reporting points have a Point ID in the metadata table starting with 'SI', while the basin-representative points starting with 'SR'.
Hydrograph section
Next item in the popup window is the hydrograph, which graphically summarises the climatological, antecedent and forecast conditions (see Figure 2 and Figure 3).
The left half of the plot, left of the horizontal dotted line, which indicates the forecast start date, shows the past (see Figure 3a). The black dots (connected by black line) indicate the so-called water balance, the proxi observations, which are produced as a LISFLOOD simulation forced with either gridded meteorological observations in EFAS, or ERA5 meteorological reanalysis fields in GloFAS. These black dots show the simulated reality of the river discharge conditions, as close as the simulations can go at the actual periods (average river discharge over months in seasonal and weeks in sub-seasonal).
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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 forecast 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.
As Figure 3c describes, the seasonal hydrograph (it would not work for the sub-seasonal due to the much shorter weekly lead times) indicates a property of the model climatologies. The seasonal hydrograph is designed to have exactly 13 month as covered period which guarantees, the last month of the forecast (February in Figure 2 and 3) will feature as a month-7 forecast climatology and also as a month-1 forecast climatology in the past period as the oldest period plotted. This way, the hydrograph gives a visual impression of the drift in the river discharge forecasts. Drift in this context means, the month-7 reforecast-based climatology percentiles could occasionally be even very different to the month-1 reforecast-based percentiles and by this show a noticeable shift or drift in the forecast behaviour (i.e. values going lower or higher) from shorter to longer ranges (see Figure 3c for visual indication of this). In fact, for this comparison the left-most and right-most parts of the hydrograph need contrasting. In the example in Figure 2-3, the shaded climatological categories highlight that 'Extreme low' and 'Low' categories shift only very little, with the median being very stable. However, the higher percentiles (75th and 90th percentiles) are noticeably larger in the month-7 climatology, indicating a noticeable drift for larger values. While in the the month-1 average river discharge climatological distribution the 90th percentile is about 20 m3/s, so about 10% of the time the monthly mean can exceed this value, in the longer range month-7 reforecasts the same 90th percentile, the 10% of the time to exceed this value, increases to 25 m3/s. So, the forecast is more likely to show larger values in the longer ranges than in the short range.
Probability evolution table section
Finally, the last part of the reporting point popup window is the probability evolution table. This table shows all the 7 anomaly categories and the related probabilities for all the forecast lead time periods and from all the previous forecast runs that still verify in the most recent forecast horizon. For the sub-seasonal, this means 5 or 6 forecast lead time periods (depending on which day of the week the run date is, and thus how many calendar weeks the 46-day lead time can cover) and
Figure 2. Example snapshot of the reporting point pop-up window product (for a seasonal forecast).
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