DOI: 10.1175/JCLI-D-14-00361.1
Scopus记录号: 2-s2.0-84942025934
论文题名: Addressing interdependency in a multimodel ensemble by interpolation of model properties
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: 5150
结束页码: 5170
语种: 英语
Scopus关键词: Earth (planet)
; Earth system model
; Future climate projections
; Model intercomparisons
; Model performance
; Model properties
; Multi-model ensemble
; Multivariate distributions
; Sampling distribution
; Climate models
; climate modeling
; ensemble forecasting
; interpolation
; multivariate analysis
; performance assessment
英文摘要: The diverse set of Earth system models used to conduct the CMIP5 ensemble can partly sample the uncertainties in future climate projections. However, combining those projections is complicated by the fact that models developed by different groups share ideas and code and therefore biases. The authors propose a method for combining model results into single or multivariate distributions that are more robust to the inclusion of models with a large degree of interdependency. This study uses a multivariate metric of presentday climatology to assess both model performance and similarity in two recent model intercomparisons, CMIP3 and CMIP5. Model characteristics can be interpolated and then resampled in a space defined by independent climate properties.Aform of weighting can be applied by sampling more densely in the region of the space close to the projected observations, thus taking into account both model performance and interdependence. The choice of the sampling distribution's parameters is a subjective decision that should reflect the researcher's prior assumptions as to the acceptability of different model errors. © 2015 American Meteorological Society. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/50569
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.. Addressing interdependency in a multimodel ensemble by interpolation of model properties[J]. Journal of Climate,2015-01-01,28(13)