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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
https://doi.org/10.5194/hess-2016-521
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
Research article
24 Oct 2016
Review status
A revision of this discussion paper was accepted for the journal Hydrology and Earth System Sciences (HESS) and is expected to appear here in due course.
Skill of a global forecasting system in seasonal ensemble streamflow prediction
Naze Candogan Yossef1,2, Rens van Beek1, Albrecht Weerts2,3, Hessel Winsemius2, and Marc F. P. Bierkens1 1Faculty of Geosciences, Utrecht University, Utrecht, 3508 TC, The Netherlands
2Deltares, Delft, 2600 MH, The Netherlands
3Department of Environmental Sciences, Wageningen University, 6708 PB, The Netherlands
Abstract. In this study we assess the skill of seasonal streamflow forecasts with the global hydrological forecasting system FEWS-World which has been set up within the European Commission 7th Framework Programme project Global Water Scarcity Information Service (GLOWASIS). FEWS-World incorporates the global hydrological model PCR-GLOBWB. We produce ensemble forecasts of monthly discharges for 20 large rivers of the world, with lead times of up to 6 months, forcing the system with bias-corrected seasonal meteorological forecast ensembles from the ECMWF and with probabilistic meteorological ensembles obtained following the ESP procedure. Here, the skill from the ESP ensembles, which contain no actual information on weather, serves as a benchmark to assess the additional skill that may be obtained using ECMWF seasonal forecasts. We use the Brier Score to quantify the skill of the system in forecasting high and low flows, defined as discharges higher than the 75th and lower than the 25th percentiles for a given month respectively. We determine the theoretical skill by comparing the results against model simulations and the actual skill in comparison to discharge observations. We calculate the ratios of actual to theoretical skill in order to quantify the percentage of the theoretical skill that is achieved. The results suggest that the skill of ECMWF S3 forecasts is close to that of the ESP forecasts. While better meteorological forecasts could potentially lead to an improvement in hydrological forecasts, this cannot be achieved yet using the ECMWF S3 dataset.

Citation: Candogan Yossef, N., van Beek, R., Weerts, A., Winsemius, H., and Bierkens, M. F. P.: Skill of a global forecasting system in seasonal ensemble streamflow prediction, Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2016-521, in review, 2016.
Naze Candogan Yossef et al.
Naze Candogan Yossef et al.

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This paper presents a skill assessment of the global seasonal streamflow forecasting system FEWS-World. For 20 large basins of the world, forecasts using the ESP procedure are compared to forecasts using actual S3 seasonal meteorological forecast ensembles by ECMWF. The results are discussed in the context of prevailing hydroclimatic conditions per basin. The study concludes that in general, the skill of ECMWF S3 forecasts is close to that of the ESP forecasts.
This paper presents a skill assessment of the global seasonal streamflow forecasting system...
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