DOI: 10.1175/JCLI-D-13-00629.1
Scopus记录号: 2-s2.0-84906879068
论文题名: Partitioning internal variability and model uncertainty components in a multimember multimodel ensemble of climate projections
作者: Hingray B. ; Saïd M.
刊名: Journal of Climate
ISSN: 8948755
出版年: 2014
卷: 27, 期: 17 起始页码: 6779
结束页码: 6798
语种: 英语
Scopus关键词: Catchments
; Space division multiple access
; Uncertainty analysis
; Climate simulation
; Global climate model
; Internal variability
; Model uncertainties
; Multi-model ensemble
; Noise free signals
; Statistical downscaling
; Total uncertainties
; Climate models
英文摘要: A simple and robust framework is proposed for the partitioning of the different components of internal variability and model uncertainty in an unbalanced multimember multimodel ensemble (MM2E) of climate projections obtained for a suite of statistical downscaling models (SDMs) and global climate models (GCMs). It is based on the quasi-ergodic assumption for transient climate simulations. Model uncertainty components are estimated from the noise-free signals of the different modeling chains using a two-way analysis of variance (ANOVA) framework. The residuals from the noise-free signals are used to estimate the large- and smallscale internal variability components associated with each considered GCM-SDM configuration. This framework makes it possible to take into account all members available from any climate ensemble of opportunity. Uncertainty is quantified as a function of lead time for projections of changes in temperature and precipitation produced for a mesoscale alpine catchment. Internal variability accounts for more than 80% of total uncertainty in the first decades. This proportion decreases to less than 10% at the end of the century for temperature but remains greater than 50% for precipitation. Small-scale internal variability is negligible for temperature; however, it is similar to the large-scale component for precipitation, whatever the projection lead time. SDM uncertainty is always greater than GCM uncertainty for precipitation. It is also greater for temperature in the middle of the century. The response-to-uncertainty ratio is very high for temperature. For precipitation, it is always less than one, indicating that even the sign of change is uncertain. © 2014 American Meteorological Society. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/51247
Appears in Collections: 气候变化事实与影响
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作者单位: CNRS, LTHE UMR 5564, Grenoble, France; Université Grenoble Alpes, LTHE UMR 5564, Grenoble, France; Agence Technique de l'Information sur l'Hospitalisation, Lyon, France
Recommended Citation:
Hingray B.,Saïd M.. Partitioning internal variability and model uncertainty components in a multimember multimodel ensemble of climate projections[J]. Journal of Climate,2014-01-01,27(17)