DOI: 10.1175/JCLI-D-14-00362.1
Scopus记录号: 2-s2.0-84942067342
论文题名: A representative democracy to reduce interdependency in a multimodel ensemble
作者: Sanderson B.M. ; Knutti R. ; Caldwell P.
刊名: Journal of Climate
ISSN: 8948755
出版年: 2015
卷: 28, 期: 13 起始页码: 5171
结束页码: 5194
语种: 英语
Scopus关键词: Earth (planet)
; Earth system model
; Future climate
; Impact study
; Multi-model ensemble
; Potential problems
; Random sample
; Temporal and spatial
; Validation data
; Climate models
; analytical method
; climate modeling
; ensemble forecasting
; spatiotemporal analysis
; uncertainty analysis
英文摘要: The collection of Earth system models available in the archive of phase 5 of CMIP (CMIP5) represents, at least to some degree, a sample of uncertainty of future climate evolution. The presence of duplicated code as well as shared forcing and validation data in the multiple models in the archive raises at least three potential problems: biases in the mean and variance, the overestimation of sample size, and the potential for spurious correlations to emerge in the archive because of model replication. Analytical evidence is presented to demonstrate that the distribution of models in the CMIP5 archive is not consistent with a random sample, and a weighting scheme is proposed to reduce some aspects of model codependency in the ensemble. A method is proposed for selecting diverse and skillful subsets of models in the archive, which could be used for impact studies in cases where physically consistent joint projections of multiple variables (and their temporal and spatial characteristics) are required. © 2015 American Meteorological Society. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/50536
Appears in Collections: 气候变化事实与影响
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作者单位: National Center for Atmospheric Research, Boulder, CO, United States; Institute for Atmospheric and Climate Science, ETH, Zurich, Switzerland; Lawrence Livermore National Laboratory, Livermore, CA, United States
Recommended Citation:
Sanderson B.M.,Knutti R.,Caldwell P.. A representative democracy to reduce interdependency in a multimodel ensemble[J]. Journal of Climate,2015-01-01,28(13)