DOI: 10.5194/hess-21-4103-2017
Scopus记录号: 2-s2.0-85027302431
论文题名: Skill of a global forecasting system in seasonal ensemble streamflow prediction
作者: Candogan Yossef N ; , Van Beek R ; , Weerts A ; , Winsemius H ; , Bierkens M ; F ; P
刊名: Hydrology and Earth System Sciences
ISSN: 10275606
出版年: 2017
卷: 21, 期: 8 起始页码: 4103
结束页码: 4114
语种: 英语
Scopus关键词: Forecasting
; Information services
; Stream flow
; Discharge observations
; Early Warning System
; European centre for medium-range weather forecasts
; European Commission
; Hydrological forecast
; Hydrological forecasting
; Hydrological modeling
; Streamflow prediction
; Weather forecasting
; benchmarking
; data set
; early warning system
; European Commission
; forecasting method
; hydrological modeling
; performance assessment
; prediction
; river discharge
; streamflow
英文摘要: In this study we assess the skill of seasonal streamflow forecasts with the global hydrological forecasting system Flood Early Warning 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 distributed global hydrological model PCR-GLOBWB (PCRaster Global Water Balance). 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 European Centre for Medium-range Weather Forecasts (ECMWF) and with probabilistic meteorological ensembles obtained following the ESP procedure. Here, the ESP ensembles, which contain no actual information on weather, serve as a benchmark to assess the additional skill that may be obtained using ECMWF seasonal forecasts. We use the Brier skill score (BSS) 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 potential skill that is achieved. The results suggest that the performance 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. © 2017 Author(s). Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/79087
Appears in Collections: 气候变化事实与影响
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作者单位: Faculty of Geosciences, Utrecht University, Utrecht, Netherlands; Department of Deltares, Delft, Netherlands; Department of Environmental Sciences, Wageningen University, Netherlands
Recommended Citation:
Candogan Yossef N,, Van Beek R,, Weerts A,et al. Skill of a global forecasting system in seasonal ensemble streamflow prediction[J]. Hydrology and Earth System Sciences,2017-01-01,21(8)