globalchange  > 过去全球变化的重建
DOI: 10.1007/s00382-011-1135-9
Scopus记录号: 2-s2.0-84864387092
论文题名:
Multivariate and multiscale dependence in the global climate system revealed through complex networks
作者: Steinhaeuser K.; Ganguly A.R.; Chawla N.V.
刊名: Climate Dynamics
ISSN: 9307575
出版年: 2012
卷: 39, 期:3
起始页码: 889
结束页码: 895
语种: 英语
英文关键词: Complex networks ; Correlation ; Ocean meteorology ; Reanalysis data ; Teleconnections
英文摘要: A systematic characterization of multivariate dependence at multiple spatio-temporal scales is critical to understanding climate system dynamics and improving predictive ability from models and data. However, dependence structures in climate are complex due to nonlinear dynamical generating processes, long-range spatial and long-memory temporal relationships, as well as low-frequency variability. Here we utilize complex networks to explore dependence in climate data. Specifically, networks constructed from reanalysis-based atmospheric variables over oceans and partitioned with community detection methods demonstrate the potential to capture regional and global dependence structures within and among climate variables. Proximity-based dependence as well as long-range spatial relationships are examined along with their evolution over time, yielding new insights on ocean meteorology. The tools are implicitly validated by confirming conceptual understanding about aggregate correlations and teleconnections. Our results also suggest a close similarity of observed dependence patterns in relative humidity and horizontal wind speed over oceans. In addition, updraft velocity, which relates to convective activity over the oceans, exhibits short spatiotemporal decorrelation scales but long-range dependence over time. The multivariate and multi-scale dependence patterns broadly persist over multiple time windows. Our findings motivate further investigations of dependence structures among observations, reanalysis and model-simulated data to enhance process understanding, assess model reliability and improve regional climate predictions. © 2011 Springer-Verlag.
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/55216
Appears in Collections:过去全球变化的重建

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作者单位: Geographic Information Science and Tech. Group, Computational Sciences and Engineering Division, Oak Ridge National Laboratory, 1 Bethel Valley Rd, PO Box 2008, MS-6017, Oak Ridge, TN 37831, United States; Department of Computer Science and Engineering, Interdisciplinary Center for Network Science and Applications, University of Notre Dame, 384 Fitzpatrick Hall, Notre Dame, IN 46556, United States; Department of Civil and Environmental Engineering, University of Tennessee at Knoxville, 223 Perkins Hall, Knoxville, TN 37996, United States

Recommended Citation:
Steinhaeuser K.,Ganguly A.R.,Chawla N.V.. Multivariate and multiscale dependence in the global climate system revealed through complex networks[J]. Climate Dynamics,2012-01-01,39(3)
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