DOI: 10.1175/JCLI-D-12-00622.1
Scopus记录号: 2-s2.0-84900462170
论文题名: Sensitivity of climate change detection and attribution to the characterization of internal climate variability
作者: Imbers J. ; Lopez A. ; Huntingford C. ; Allen M.
刊名: Journal of Climate
ISSN: 8948755
出版年: 2014
卷: 27, 期: 10 起始页码: 3477
结束页码: 3491
语种: 英语
Scopus关键词: Atmospheric temperature
; Characterization
; Greenhouse gases
; Anthropogenic emissions
; Autocorrelation structures
; Climate change detection
; Detection and attributions
; Global-mean temperature
; Intergovernmental panel on climate changes
; Internal climate variability
; Surface air temperatures
; Climate change
; air temperature
; anthropogenic source
; autocorrelation
; climate change
; climate variation
; detection method
; emission
; global climate
; greenhouse gas
; Intergovernmental Panel on Climate Change
; sensitivity analysis
; spatial variation
; stochasticity
英文摘要: The Intergovernmental Panel on Climate Change's (IPCC) "very likely" statement that anthropogenic emissions are affecting climate is based on a statistical detection and attribution methodology that strongly depends on the characterization of internal climate variability. In this paper, the authors test the robustness of this statement in the case of global mean surface air temperature, under different representations of such variability. The contributions of the different natural and anthropogenic forcings to the global mean surface air temperature response are computed using a box diffusion model. Representations of internal climate variability are explored using simple stochastic models that nevertheless span a representative range of plausible temporal autocorrelation structures, including the short-memory first-order autoregressive [AR(1)] process and the long-memory fractionally differencing process. The authors find that, independently of the representation chosen, the greenhouse gas signal remains statistically significant under the detection model employed in this paper. The results support the robustness of the IPCC detection and attribution statement for global mean temperature change under different characterizations of internal variability, but they also suggest that a wider variety of robustness tests, other than simple comparisons of residual variance, should be performed when dealing with other climate variables and/or different spatial scales. © 2014 American Meteorological Society. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/51294
Appears in Collections: 气候变化事实与影响
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作者单位: Oxford Center for Collaborative Applied Mathematics, Mathematical Institute, University of Oxford, Oxford, United Kingdom; Center for the Analysis of Time Series, London School of Economics, London, United Kingdom; Centre for Ecology and Hydrology, Wallingford, United Kingdom; Atmospheric, Oceanic and Planetary Physics, University of Oxford, Oxford, United Kingdom
Recommended Citation:
Imbers J.,Lopez A.,Huntingford C.,et al. Sensitivity of climate change detection and attribution to the characterization of internal climate variability[J]. Journal of Climate,2014-01-01,27(10)