| DOI: | 10.1002/jgrd.50493
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| 论文题名: | Boreal winter low-frequency variability in CMIP5 models |
| 作者: | Lee Y.-Y.; Black R.X.
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| 刊名: | Journal of Geophysical Research Atmospheres
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| ISSN: | 21698996
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| 出版年: | 2013
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| 卷: | 118, 期:13 | | 起始页码: | 6891
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| 结束页码: | 6904
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| 语种: | 英语
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| 英文关键词: | Boreal extratropical low-frequency variability
; Climatological stationary waves
; North Atlantic Oscillation
; Pacific-North American pattern
; Performance of GCMs in CMIP5
; Relation of low-frequency variability with climatological-mean flow
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| Scopus关键词: | Atmospheric pressure
; Climate models
; Cluster analysis
; Low frequency variability
; North Atlantic oscillations
; Pacific-North American pattern
; Performance of GCMs in CMIP5
; Stationary waves
; Computer simulation
; air temperature
; air-sea interaction
; boreal forest
; climatology
; data set
; frequency analysis
; magnitude
; North Atlantic Oscillation
; numerical model
; principal component analysis
; stratosphere
; Pacific Coast [North America]
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| 英文摘要: | This study assesses the capability of CMIP5 models in representing primary modes of boreal winter extratropical low-frequency variability. Rotated principal component analysis is applied to monthly mean output from historical simulations of 14 plus two variants models and National Centers for Environmental Prediction-National Center for Atmospheric Research reanalyses (NNR) to isolate the leading patterns of variability in 500 hPa height. For each model data set, North Atlantic Oscillation (NAO)-like and Pacific-North American (PNA)-like patterns are identified using pattern correlation analysis (against NNR patterns). The relative pattern correspondence among CMIP5 models and reanalyses is further quantified via cluster analyses of the rotated empirical orthogonal function, NAO-like, and PNA-like patterns, respectively. For both NAO and PNA, 18.8% of the model patterns lie within the same cluster as NNR. Composite structural differences among clusters chiefly consist of (a) spatial displacements of or (b) regional magnitude disparities in the primary anomaly features. While all models replicate the basic aspects of PNA, a small minority of models fails to replicate NAO pattern. Overall, the best performing model is the "GFDL-ESM2G." Interestingly, models having a well-resolved stratosphere generally perform more poorly than those without. Model biases in low-frequency mode structure have important consequences for the representation of associated regional anomalies in surface air temperature and storm track behavior. Those differences among clusters are linked to variations in dynamical structures and their relation to the climatological-mean flow. It is concluded that some state-of-the-art models have important deficiencies in representing low-frequency variability and some of these deficiencies are associated with the failure of models to adequately replicate the observed climatological stationary waves. Key Points Deficiencies of CMIP5 models in representing low frequency variability structure Biases in representing regional weather contribution Importance of replicating observed climatological stationary wave ©2013. American Geophysical Union. All Rights Reserved. |
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| 资源类型: | 期刊论文
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| 标识符: | http://119.78.100.158/handle/2HF3EXSE/63562
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| Appears in Collections: | 影响、适应和脆弱性
气候减缓与适应
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作者单位: | Earth and Atmospheric Sciences, Georgia Institute of Technology, 311 Ferst Dr., Atlanta, GA 30332, United States
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| Recommended Citation: | |
Lee Y.-Y.,Black R.X.. Boreal winter low-frequency variability in CMIP5 models[J]. Journal of Geophysical Research Atmospheres,2013-01-01,118(13)
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