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• W44284827 abstract "The acknowledgement that hydro-meteorological forecasts may be uncertain, has resulted in an increasing useof probabilistic forecasting techniques in operational forecasting systems, often through the use of ensembleforecasting. Rather than providing a single value forecast, these ensemble forecasts provide a probability of afuture state, e.g. precipitation, water level or discharge. Although these probabilistic forecasts provide valuableinformation on the range of possible future states, the reliability, sharpness and resolution of these probabilityforecasts should be evaluated through a process of forecast verification.In this paper we present results of an extensive verification of forecasts made using two meteorological en-semble forecast products; the global scale ECMWF-EPS and the dynamically downscaled COSMO-LEPS.These are used to provide input forcing to the operational forecasting system of the Rhine basin, used byboth the German Federal Institute of Hydrology, and the Dutch Centre for Water Management for predictingwater levels and discharges at key forecasting locations. Ensemble flow forecasts are generated by forcing acalibrated hydrological model (HBV), using either of the two meteorological ensemble products. Verificationof a large set of hindcast runs shows that when compared to climatology, positive skill scores are found atall river gauges considered for lead times of up to 9 days. This shows that the medium-range flow forecastsobtained to be useful. However, the comparison between the low resolution ECMWF and the high resolutionCOSMO-LEPS model shows that the downscaled forecasts provide better representation of the variability. Higherskills are found across all catchment sizes, particularly for shorter lead time forecasts. The downscaling of the en-semble forecasts to a scale commensurate with the sub-basin scale in the hydrological model is thus recommended.Additionally we demonstrate the use of the probabilistic verification scores established for (i) the forecast-ing system developer, and (ii) the operational forecaster. On the one hand the developer aims to compare andimprove forecasts, and thus make decisions on data to be used in the system. Suitable measures are threshold basedbinary verification methods such as Reliability diagrams and the Brier score and multicategorical methods such asRank histogram and the Ranked Probability Score. For the forecaster, on the other hand, verification statistics thatcan help judge the forecast at hand and provide guidance on the decision to be taken. For this situation we discussthe use of the Reliability diagram and the Relative Operating Characteristic." @default.
• W44284827 created "2016-06-24" @default.
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• W44284827 date "2010-05-01" @default.
• W44284827 modified "2023-09-26" @default.
• W44284827 title "What we can learn from probabilistic verification scores in the context of hydrological ensemble forecasting" @default.
• W44284827 hasPublicationYear "2010" @default.
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