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Selection of stations

GloFAS forecast skill assessment is conducted on all GloFAS web reporting points.

Background on GloFAS forecasting

The forecast quality of GloFAS river discharge forecasts (out to 30 day lead time) has been evaluated in order to provide additional information to users to aid decision-making. The forecast evaluation method is described in Harrigan et al. (2023) and summarised below with the results summarised in the "Forecast skill" layer on the GloFAS web map viewer: GloFAS forecast skill product.

Headline forecast skill score

The headline forecast skill score is the maximum lead time (in days), up to 30-days ahead, in which the Continuous Ranked Probability Skill Score (CRPSS) is greater than a value of 0.5, when compared to a persistence or climatology benchmark forecast using GloFAS historical river discharge reanalysis (also known as Forced simulation (sfo) within CEMS) as proxy observations. Forecast skill is calculated using river discharge reforecasts for a set of past dates, based on a configuration as close as possible to the operational setting. ECMWF-ENS medium and extended range reforecasts are used and are run twice per week for the past 20-years with 11 ensemble members.

Scores are shown on the GloFAS map viewer in the 'Forecast skill' layer under the 'Evaluation' menu (an example of the layer is shown here: GloFAS forecast skill product). For each GloFAS web reporting point, the maximum lead time the CRPSS is greater than 0.5 is given, with stations with purple circles having high skill for at longer lead times. The category "0", marked as light pink circles represents stations that have forecast skill lower than the 0.5 threshold for any lead time. Note: This does not mean that a station has no skill. Only when the CRPSS ≤ 0 is when the forecast has no skill when compared to a persistence or climatology benchmark forecast.

Method

Reforecasts

ECMWF-ENS medium and extended range reforecasts are generated every Monday and Thursday, for the same date in the past 20 years for 11 ensemble members out to a lead time of 30 days. For the GloFAS v4 forecast skill evaluation, reforecasts are from version 48r1 of the ECMWF Integrated Forecast System (IFS) implemented on 27 June 2023 with a horizontal resolution of ~9km for ensemble meteorological outputs. At the time of release of GloFAS v4 on 26 July 2023, reforecasts generated from ECMWF 48r1 for start dates across April to July 2023 were available. These were then forced through the GloFAS hydrological modelling chain to produce 20 years of river discharge reforecasts, twice weekly, for 11 ensemble members for start dates across April to July. Reforecasts from the ECMWF IFS 48r1 will continue to be generated operationally each Monday and Thursday for the corresponding dates in the last 20 years (i.e. 2003-2022). GloFAS v4 reforecasts will therefore only include start dates from part of the calendar year (i.e. April to July), and so results will not reflect forecast skill in other parts of the year. The forecast skill layer will be updated on a quarterly basis when newer reforecast data arrive, e.g. in September 2023, there will be reforecasts available from April to August, and so forth.

Benchmark forecasts

Following Pappenberger et al. (2015) and because GloFAS produces seamless forecasts across short, medium and extended lead times (day 1 to 30), two benchmarks are considered here, each calculated for all GloFAS diagnostic river points: persistence, typically used for short lead times where the forecast signal is dominated by serial correlation of river discharge, and climatology, typically used for longer lead times where the forecast signal is dominated by the seasonality of river discharge defined as follows:

persistence benchmark forecast defined as the single GloFAS daily river discharge of the day preceding the reforecast start date. The same river discharge value is used for all lead times.
climatology benchmark forecast based on a 44-year climatological sample (1979-2022) of moving 31-day windows of GloFAS river discharge reanalysis values, centred on the date being evaluated (+- 15 days). From each climatological sample, 11 fixed quantiles (Qn) at 10 % intervals were extracted (Q0, Q10, Q20, , Q80, Q90, Q100). The fixed quantile climate distribution used therefore varies by lead time, capturing the temporal variability in local river discharge climatology.

Proxy observations

Forecast skill is evaluated against GloFAS river discharge reanalysis, as a proxy to river discharge observations, for diagnostic points across the GloFAS domain. The advantages of using reanalysis instead of in situ river discharge observations is that the forecast skill can be determined independently from the hydrological model error and having a complete spatial and temporal coverage, so that forecast skill can be determined across the full GloFAS domain. Users must be aware that the key assumption with the proxy observation approach is that the GloFAS hydrological performance is reasonably good for the station of interest. If the hydrological model performance is poor, then particular care must be made in interpreting forecast skill scores.

Skill score

The ensemble forecast performance is evaluated using the Continuous Ranked Probability Score (CRPS) (Hersbach, 2000), one of the most widely used headline scores for probabilistic forecasts. The CRPS compares the continuous cumulative distribution of an ensemble forecast with the distribution of the observations . It has an optimum value of 0 and measures the error in the same units as the variable of interest (here river discharge in m³ s^-1). It collapses to the mean absolute error for deterministic forecasts (as is the case here for the single-valued persistence benchmark forecast). The CRPS is expressed as a skill score to calculate forecast skill, CRPSS, which measures the improvement over a benchmark forecast and is given in:

{CRPSS}={1-}\frac{{CRPS_{fc}}}{{CRPS_{bench}}}

A CRPSS value of 1 indicates a perfect forecast, CRPSS > 0 shows forecasts more skilful than the benchmark, CRPSS = 0 shows forecasts are only as accurate as the benchmark, and a CRPSS < 0 warns that forecasts are less skilful than the benchmark forecast. The headline GloFAS forecast skill score uses a CRPSS threshold of 0.5 in the summary layer in the GloFAS web map viewer, this can be interpreted as the GloFAS forecast is 50% more accurate than the benchmark forecast.

The CRPSS is calculated with GloFAS reforecasts against both persistence and climatology benchmark forecasts and verified against GloFAS river discharge reanalysis as proxy observations. CRPSS headline scores are then mapped on the GloFAS map viewer, and CRPSS and CRPS time-series plots are produced for each fixed reporting point station.

References

Alfieri, L., Pappenberger, F., Wetterhall, F., Haiden, T., Richardson, D., Salamon, P., 2014. Evaluation of ensemble streamflow predictions in Europe. Journal of Hydrology 517, 913–922.

Harrigan, S., Zsoter, E., Cloke, H., Salamon, P., and Prudhomme, C.: Daily ensemble river discharge reforecasts and real-time forecasts from the operational Global Flood Awareness System, Hydrol. Earth Syst. Sci., 27, 1–19, https://doi.org/10.5194/hess-27-1-2023, 2023.

Hersbach, H., 2000. Decomposition of the Continuous Ranked Probability Score for Ensemble Prediction Systems. Wea. Forecasting 15, 559–570.

Pappenberger, F., Ramos, M.H., Cloke, H.L., Wetterhall, F., Alfieri, L., Bogner, K., Mueller, A., Salamon, P., 2015. How do I know if my forecasts are better? Using benchmarks in hydrological ensemble prediction. Journal of Hydrology 522, 697–713.