DOI: 10.5194/hess-20-685-2016
Scopus记录号: 2-s2.0-84958259422
论文题名: Technical Note: The impact of spatial scale in bias correction of climate model output for hydrologic impact studies
作者: Maurer E ; P ; , Ficklin D ; L ; , Wang W
刊名: Hydrology and Earth System Sciences
ISSN: 10275606
出版年: 2016
卷: 20, 期: 2 起始页码: 685
结束页码: 696
语种: 英语
Scopus关键词: Digital storage
; Mapping
; Meteorology
; Water resources
; Daily precipitations
; Hydrologic impacts
; Hydrology modeling
; Large-scale modeling
; Non-stationarities
; Provide guidances
; Statistical downscaling
; Western United States
; Climate models
; climate effect
; climate modeling
; downscaling
; hydrological modeling
; mapping method
; precipitation (climatology)
; streamflow
; water resource
; weather station
; United States
英文摘要: Statistical downscaling is a commonly used technique for translating large-scale climate model output to a scale appropriate for assessing impacts. To ensure downscaled meteorology can be used in climate impact studies, downscaling must correct biases in the large-scale signal. A simple and generally effective method for accommodating systematic biases in large-scale model output is quantile mapping, which has been applied to many variables and shown to reduce biases on average, even in the presence of non-stationarity. Quantile-mapping bias correction has been applied at spatial scales ranging from hundreds of kilometers to individual points, such as weather station locations. Since water resources and other models used to simulate climate impacts are sensitive to biases in input meteorology, there is a motivation to apply bias correction at a scale fine enough that the downscaled data closely resemble historically observed data, though past work has identified undesirable consequences to applying quantile mapping at too fine a scale. This study explores the role of the spatial scale at which the quantile-mapping bias correction is applied, in the context of estimating high and low daily streamflows across the western United States. We vary the spatial scale at which quantilemapping bias correction is performed from 2° (∼200 km) to 1/8° (∼12 km) within a statistical downscaling procedure, and use the downscaled daily precipitation and temperature to drive a hydrology model. We find that little additional benefit is obtained, and some skill is degraded, when using quantile mapping at scales finer than approximately 0.5° (∼50 km). This can provide guidance to those applying the quantile-mapping bias correction method for hydrologic impacts analysis. © 2016 Author(s). Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/78914
Appears in Collections: 气候变化事实与影响
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作者单位: Santa Clara University, Civil Engineering Department, Santa Clara, CA, United States; Indiana University, Department of Geography, Bloomington, IN, United States; California State University, Department of Science and Environmental Policy, Ames Research Center, Moffett Field, CA, United States
Recommended Citation:
Maurer E,P,, Ficklin D,et al. Technical Note: The impact of spatial scale in bias correction of climate model output for hydrologic impact studies[J]. Hydrology and Earth System Sciences,2016-01-01,20(2)