globalchange  > 气候变化事实与影响
DOI: 10.1175/JCLI-D-12-00693.1
Scopus记录号: 2-s2.0-84892469882
论文题名:
Assimilation of time-averaged pseudoproxies for climate reconstruction
作者: Steiger N.J.; Hakim G.J.; Steig E.J.; Battisti D.S.; Roe G.H.
刊名: Journal of Climate
ISSN: 8948755
出版年: 2014
卷: 27, 期:1
起始页码: 426
结束页码: 441
语种: 英语
Scopus关键词: Climate field reconstruction ; Climate reconstruction ; Data assimilation ; Ensemble data assimilation ; General circulation model ; Global-mean temperature ; Paleoclimates ; Principal components analysis ; Atmospheric temperature ; Data processing ; Kalman filters ; Principal component analysis ; Surface properties ; Experiments ; data assimilation ; ensemble forecasting ; general circulation model ; Kalman filter ; paleoclimate ; principal component analysis ; reconstruction
英文摘要: The efficacy of a novel ensemble data assimilation (DA) technique is examined in the climate field reconstruction (CFR) of surface temperature. A minimalistic, computationally inexpensive DA technique is employed that requires only a static ensemble of climatologically plausible states. Pseudoproxy experiments are performed with both general circulation model (GCM) and Twentieth Century Reanalysis (20CR) data by reconstructing surface temperature fields from a sparse network of noisy pseudoproxies. TheDAapproach is compared to a conventional CFR approach based on principal component analysis (PCA) for experiments on global domains. DA outperforms PCA in reconstructing global-mean temperature in all experiments and is more consistent across experiments, with a range of time series correlations of 0.69-0.94 compared to 0.19- 0.87 for the PCA method. DA improvements are even more evident in spatial reconstruction skill, especially in sparsely sampled pseudoproxy regions and for 20CR experiments. It is hypothesized that DA improves spatial reconstructions because it relies on coherent, spatially local temperature patterns, which remain robust even when glacial states are used to reconstruct nonglacial states and vice versa. These local relationships, as utilized by DA, appear to be more robust than the orthogonal patterns of variability utilized by PCA. Comparing results for GCMand 20CR data indicates that pseudoproxy experiments that rely solely on GCM data may give a false impression of reconstruction skill. © 2014 American Meteorological Society.
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/51438
Appears in Collections:气候变化事实与影响

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作者单位: Department of Atmospheric Sciences, University of Washington, Seattle, WA, United States; Department of Earth and Space Sciences, University of Washington, Seattle, WA, United States

Recommended Citation:
Steiger N.J.,Hakim G.J.,Steig E.J.,et al. Assimilation of time-averaged pseudoproxies for climate reconstruction[J]. Journal of Climate,2014-01-01,27(1)
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