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Point Rainfall (from "ecPoint")
In April 2019 ECMWF introduced a new type of experimental product - "Point Rainfall" - into ecCharts, following several years of development work. The issue it aims to address is illustrated on Fig8.1.7-1.
Fig8.1.7-1: Radar-derived rainfall totals over part of Northern Ireland for the 12h period ending 00UTC 29 July 2018. Scale is in mm. Flash floods occurred in some locations. Figure based on data from netweather.tv (external website).
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Fig8.1.7-2 shows CDF examples for different sites on two different occasions for the full ensemble, illustrating both bias correction and the addition of sub-grid variability within ecPoint (notably for the first plot), but showing also that the point rainfall and raw model grid-scale distributions may sometimes be quite similar (second plot).
Fig8.1.7-2: Two CDF examples comparing raw grid-scale (red), post-processed bias-corrected grid-scale (green), and post-processed point rainfall (blue). The first plot is for a site in Spain in summer at day 2. The second plot is for a southern England site in autumn, at day 4. Note that for each case the areas to the left of the green and blue curves, that represent the mean gridbox rainfall over the ensemble, should be the same.
Output formats
Output from ecPoint can in principle be for pre-defined periods of time, or instances in time. For point rainfall we currently make available overlapping 12h periods up to day 10, namely T+0-T+12, T+6-T+18,... T+234-T+246. In future we plan also to make available equivalent products for 6 hour and 24 hour intervals.
Calibration
As with any post-processing system ecPoint has to be calibrated. For this it uses short-range Control run forecasts of 12h rainfall covering one year (the "training period"), which are individually compared with rainfall observations, for the same times, within the respective grid boxes. The full procedure is not described here, but involves segregation according to gridbox-weather-types, which each have different sub-grid variability structures and/or different bias corrections associated. The 12h point rainfall system introduced into operations in April 2019 incorporated 214 such types. The type definitions are currently based on the following parameters: convective rainfall fraction, total 12h precipitation forecast, 700hPa wind speed, CAPE, 24h clear-sky solar radiation.
Verification
1 year of global verification of 12h point rainfall products indicates that when compared to point observations, and relative to raw ensemble forecasts, the point rainfall forecasts are much more reliable, and have a much better discrimination ability. The net frequency of point observations of no (measurable) rain is much higher in reality than it is in raw ensemble gridbox forecasts, whereas the net frequency in point rainfall forecasts is almost perfect, as shown by the verification reliability metric. Meanwhile large totals, such as 50mm/12h, are much better delineated by the point rainfall; using the ROC area metric day 10 forecasts in the point rainfall are as good as day 1-2 forecasts from the raw ensemble for this threshold.
Some Uses of Point Rainfall
By giving, for example, non-zero probabilities for very large totals that had a zero probability in the raw ensemble output, the Point Rainfall can provide a useful new pointer to when flash floods are possible locally. Likewise if one wants a better idea of how likely it is that a given period remains dry, the point rainfall can usually provide better guidance; indeed in convective situations the point rainfall probabilities for dry should be much better. And where a certain criteria has to be met as the basis for a warning or alert, which might not always be a large total, again the point rainfall should overall provide customers with better guidance than the raw ensemble.
The ecCharts Products
Users can type "point" into the "Add Layers" filter box to find point rainfall layers. The first release of point rainfall products into ecCharts in April 2019 came with two new layer options for map display:
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For percentiles 4 colour-fill styles and one contouring style are available for the point rainfall. For probabilities there are 2 colour-fill styles and one contouring style. All 6 colour-fill styles are illustrated in legend format on Fig8.1.7-3 These styles have also been added as options for the raw ensemble ("total precipitation percentile" and "total precipitation probability") layers to facilitate direct comparison with the point rainfall; within ecCharts users need to scroll down through the "style" options to find them.
Fig8.1.7-3: Colour fill options for a user-defined percentile (first plot, amounts in mm), and a user defined threshold (second plot, probability in %)
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- Point rainfall charts are usually smoother than raw ensemble charts
- Point rainfall output usually broadens the raw ensemble distribution
- Values for high percentiles (e.g. 95+) are often much greater in the point rainfall
- The 50th percentile (median) is usually less in the point rainfall
- The percentile where point rainfall and raw ensemble are similar tends to be around 85%
- Probabilities of dry (or more strictly "no measurable rain") are usually greater in the point rainfall
- Outlier extreme rainfall values in say 1 or 2 raw ensemble members will usually be reduced down in the point rainfall
- Bias correction effects can very occasionally be very large - e.g. doubling or halving the rainfall
- It is more common for bias correction to reduce amounts than to increase amounts, but usually such changes are small in magnitude (e.g. up to ~20%)
- Point rainfall charts from successive forecasts, for a given valid time, tend to be less jumpy than equivalent raw ensemble charts
Fig8.1.7-4: 98th percentile of 12h rainfall from the raw ensemble (first plot) and point rainfall (second plot)
Fig8.1.7-5: Probabilities of >10mm from the raw ensemble (first plot) and point rainfall (second plot)
Extreme rainfall events
ecPoint can give a broad signal for the intensity of extreme rainfall events and be a useful and fairly detailed guide to their location. It generally improves on the probability of selected rainfall values derived from medium range ensemble alone. This is illustrated below for the extreme and damaging rainfall event near Valencia in late October 2024.
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- there is rather better run-to-run consistency in location.
- there is more consistency in probability levels.
- shows a steady increase in probability of high rainfall.
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Fig8.1.7-6: Sequence of medium range ensemble forecast probabilities for rainfall >150mm/12h for valid period 06-18UTC on 29th Oct 2024.
Fig8.1.7-7: Sequence of ecPoint forecast probabilities for rainfall >300mm/12h for valid period 06-18UTC on 29th Oct 2024
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- Utiel, 103mm precipitation during the period 06-18UTC 29 Oct 2024. Flooding was reported.
- Chiva, 348mm precipitation during the period 06-18UTC 29 Oct 2024. The max 24h rainfall in this extreme event seems to have been measured here.
- Valencia, 1mm precipitation during the period 06-18UTC 29 Oct 2024. Catastrophic flooding (mainly to the south of the marker).
Limitations
Users should be aware of some known limitations of point rainfall output, which are listed below:
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Future products may address items 3 and 4, and include a cdf comparison option.
Upgrades to ecPoint
From the 12UTC ensemble runs on Monday 23rd May 2022 onwards the post-processing algorithm differs in the following three ways:
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See https://confluence.ecmwf.int/display/FCST/ecPoint+output+improved for further information.
Additional Sources of Information
(Note: Some aspect of older material may now be out of date)
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