DOI: 10.5194/hess-20-3277-2016
Scopus记录号: 2-s2.0-84982149294
论文题名: ENSO-conditioned weather resampling method for seasonal ensemble streamflow prediction
作者: Beckers J ; V ; L ; , Weerts A ; H ; , Tijdeman E ; , Welles E
刊名: Hydrology and Earth System Sciences
ISSN: 10275606
出版年: 2016
卷: 20, 期: 8 起始页码: 3277
结束页码: 3287
语种: 英语
Scopus关键词: Atmospheric pressure
; Forecasting
; Stochastic systems
; Stream flow
; Atmospheric climate
; Mode information
; Pacific Northwest
; Resampling method
; Seasonal forecasting
; Southern oscillation
; Streamflow prediction
; Streamflow regimes
; Climatology
; climate modeling
; El Nino-Southern Oscillation
; forecasting method
; hindcasting
; river basin
; sampling
; seasonality
; stochasticity
; streamflow
; weather station
; Columbia Basin
; Columbia River
; Pacific Northwest
; United States
英文摘要: Oceanic-atmospheric climate modes, such as El Niño-Southern Oscillation (ENSO), are known to affect the local streamflow regime in many rivers around the world. A new method is proposed to incorporate climate mode information into the well-known ensemble streamflow prediction (ESP) method for seasonal forecasting. The ESP is conditioned on an ENSO index in two steps. First, a number of original historical ESP traces are selected based on similarity between the index value in the historical year and the index value at the time of forecast. In the second step, additional ensemble traces are generated by a stochastic ENSO-conditioned weather resampler. These resampled traces compensate for the reduction of ensemble size in the first step and prevent degradation of skill at forecasting stations that are less affected by ENSO. The skill of the ENSO-conditioned ESP is evaluated over 50 years of seasonal hindcasts of streamflows at three test stations in the Columbia River basin in the US Pacific Northwest. An improvement in forecast skill of 5 to 10 % is found for two test stations. The streamflows at the third station are less affected by ENSO and no change in forecast skill is found here. © 2016 Author(s). Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/78762
Appears in Collections: 气候变化事实与影响
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作者单位: Deltares, Delft, Netherlands; Department of Environmental Sciences, Wageningen University, Wageningen, Netherlands; Department of Hydrology, University of Freiburg, Freiburg, Germany; Deltares USA Inc, Silver Spring, MD, United States
Recommended Citation:
Beckers J,V,L,et al. ENSO-conditioned weather resampling method for seasonal ensemble streamflow prediction[J]. Hydrology and Earth System Sciences,2016-01-01,20(8)