DOI: 10.1007/s10584-017-2086-x
Scopus记录号: 2-s2.0-85031420860
论文题名: How reliable are GCM simulations for different atmospheric variables?
作者: Eghdamirad S. ; Johnson F. ; Sharma A.
刊名: Climatic Change
ISSN: 0165-0009
EISSN: 1573-1480
出版年: 2017
卷: 145, 期: 2018-01-02 起始页码: 237
结束页码: 248
语种: 英语
英文关键词: Climate change
; GCM
; Regional uncertainty
; Reliability
; Statistically downscaling
; VRS
Scopus关键词: Atmospheric humidity
; Climate models
; Reliability
; Uncertainty analysis
; Atmospheric variables
; Climate change impact assessments
; Climate variables
; Down-scaling
; General circulation model
; Geo-potential heights
; Initial conditions
; Regional uncertainty
; Climate change
; atmospheric dynamics
; climate change
; climate effect
; climate modeling
; climate prediction
; data set
; general circulation model
; geopotential
; height
; magnitude
; parameterization
; reliability analysis
; simulation
; uncertainty analysis
英文摘要: Considerable variability exists in simulations of the future climate. This variability is caused by differences in the parameterisations across general circulation models (GCMs), the initial conditions used and the different assumptions made as to how emissions will evolve in the future. As a result, there is considerable disagreement between available projections of climate variables, which can be used to quantify the uncertainty each variable exhibits. This leads to the question—which variables (or set of variables) are more reliable for use in climate change impact assessments. This research presents a framework to quantify the relative reliability amongst a range of upper air atmospheric variables. This is made possible by pooling simulations across multiple models, trajectories (scenarios) and initial conditions in a rank-transformed space. A metric named the variable reliability score (VRS) assesses the relative reliabilities across different atmospheric variables on a common scale. The VRS has been applied to calculate the total reliability as well as reliability from each source of uncertainty, namely model, scenarios and initial conditions. This comparison helps to decide if more models, scenarios or ensembles are required for uncertainty analysis of climate change impact assessment. The variables compared include geopotential height and its north-south difference, specific humidity, eastward wind and northward wind, all at the 500 and 850 hPa pressure levels. These variables were chosen based on availability of data and their documented use in previous climate change impact assessment studies worldwide. A regional assessment of VRS over 21 regions around the world shows that though the magnitude of VRS varies spatially, the ranked reliability of the variable rank remains relatively similar. On average, the lowest reliability is associated with geopotential height, whilst wind speeds and the north-south difference of geopotential height have higher reliability. © 2017, Springer Science+Business Media B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/83879
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: Research Center for the Disaster and Science Technology, Korea University, Seoul, South Korea; School of Civil and Environmental Engineering, University of New South Wales, Kensington, Sydney, NSW, Australia
Recommended Citation:
Eghdamirad S.,Johnson F.,Sharma A.. How reliable are GCM simulations for different atmospheric variables?[J]. Climatic Change,2017-01-01,145(2018-01-02)