DOI: 10.1175/JCLI-D-14-00364.1
Scopus记录号: 2-s2.0-84925989663
论文题名: Climate model dependence and the ensemble dependence transformation of CMIP projections
作者: Abramowitz G. ; Bishop C.H.
刊名: Journal of Climate
ISSN: 8948755
出版年: 2015
卷: 28, 期: 6 起始页码: 2332
结束页码: 2348
语种: 英语
Scopus关键词: Error analysis
; Error statistics
; Societies and institutions
; Uncertainty analysis
; Coupled Model Intercomparison Project
; Ensembles
; Mean square difference
; Model errors
; Model evaluation/performance
; Model output statistics
; Surface air temperatures
; Temperature projection
; Climate models
; air temperature
; climate modeling
; ensemble forecasting
; error analysis
; precipitation (climatology)
; rainfall
英文摘要: Obtaining multiple estimates of future climate for a given emissions scenario is key to understanding the likelihood and uncertainty associated with climate-related impacts. This is typically done by collating model estimates from different research institutions internationally with the assumption that they constitute independent samples. Heuristically, however, several factors undermine this assumption: shared treatment of processes between models, shared observed data for evaluation, and even shared model code. Here, a "perfect model" approach is used to test whether a previously proposed ensemble dependence transformation (EDT) can improve twenty-first-century Coupled Model Intercomparison Project (CMIP) projections. In these tests, where twenty-first-centurymodel simulations are used as out-of-sample "observations," the mean-square difference between the transformed ensemble mean and "observations" is on average 30% less than for the untransformed ensemble mean. In addition, the variance of the transformed ensemble matches the variance of the ensemble mean about the "observations" much better than in the untransformed ensemble. Results show that the EDT has a significant effect on twenty-first-century projections of both surface air temperature and precipitation. It changes projected global average temperature increases by as much as 16% (0.2°C for B1 scenario), regional average temperatures by as much as 2.6°C (RCP8.5 scenario), and regional average annual rainfall by as much as 410mm (RCP6.0 scenario). In some regions, however, the effect is minimal. It is also found that the EDT causes changes to temperature projections that differ in sign for different emissions scenarios. This may be as much a function of the makeup of the ensembles as the nature of the forcing conditions. © 2015 American Meteorological Society. 资助项目: ARC, Australian Research Council
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/50510
Appears in Collections: 气候变化事实与影响
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作者单位: ARC Centre of Excellence for Climate System Science, Climate Change Research Centre, University of New South Wales, Sydney, NSW, Australia; Naval Research Laboratory, Monterey, CA, United States
Recommended Citation:
Abramowitz G.,Bishop C.H.. Climate model dependence and the ensemble dependence transformation of CMIP projections[J]. Journal of Climate,2015-01-01,28(6)