| DOI: | 10.1007/s10584-017-1944-x
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| Scopus记录号: | 2-s2.0-85015688111
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| 论文题名: | Using second-order approximation to incorporate GCM uncertainty in climate change impact assessments |
| 作者: | Eghdamirad S.; Johnson F.; Sharma A.
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| 刊名: | Climatic Change
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| ISSN: | 0165-0009
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| EISSN: | 1573-1480
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| 出版年: | 2017
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| 卷: | 142, 期:2018-01-02 | | 起始页码: | 37
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| 结束页码: | 52
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| 语种: | 英语
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| Scopus关键词: | Climate models
; Stream flow
; Climate change impact assessments
; Climate variables
; General circulation model
; Geo-potential heights
; Reference stations
; Second-order approximation
; Second-order expansion
; Statistical downscaling
; Climate change
; climate change
; climate effect
; downscaling
; general circulation model
; geopotential
; streamflow
; uncertainty analysis
; wind velocity
; Australia
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| 英文摘要: | This study presents a method to incorporate uncertainty of climate variables in climate change impact assessments, where the uncertainty being considered refers to the divergence of general circulation model (GCM) projections. The framework assesses how much bias occurs when the uncertainties of climate variables are ignored. The proposed method is based on the second-order expansion of Taylor series, called second-order approximation (SOA). SOA addresses the bias which occurs by assuming the expected value of a function is equal to the function of the expected value of the predictors. This assumption is not valid for nonlinear systems, such as in the case of the relationship of climate variables to streamflow. To investigate the value of SOA in the climate change context, statistical downscaling models for monthly streamflow were set up for six hydrologic reference stations in Australia which cover contrasting hydro-climate regions. It is shown that in all locations SOA makes the largest difference for low flows and changes the overall mean flow by 1–3%. Another advantage of the SOA approach is that the individual contribution of each climate variable to the total difference can be estimated. It is found that geopotential height and specific humidity cause more bias than wind speeds in the downscaling models considered here. © 2017, Springer Science+Business Media Dordrecht. |
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| 资源类型: | 期刊论文
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| 标识符: | http://119.78.100.158/handle/2HF3EXSE/84004
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| Appears in Collections: | 气候减缓与适应
气候变化事实与影响
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作者单位: | School of Civil and Environmental Engineering, The University of New South Wales, Kensington, NSW, Australia
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| Recommended Citation: | |
Eghdamirad S.,Johnson F.,Sharma A.. Using second-order approximation to incorporate GCM uncertainty in climate change impact assessments[J]. Climatic Change,2017-01-01,142(2018-01-02)
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