DOI: 10.1007/s00382-017-3979-0
Scopus记录号: 2-s2.0-85032347602
论文题名: Global-mean surface temperature variability: space–time perspective from rotated EOFs
作者: Chen X. ; Tung K.-K.
刊名: Climate Dynamics
ISSN: 9307575
出版年: 2018
卷: 51, 期: 2018-05-06 起始页码: 1719
结束页码: 1732
语种: 英语
英文关键词: AMO
; ENSO
; Global-mean temperature variability
; IPO
; PDO
; Rotated EOF
Scopus关键词: air-sea interaction
; Atlantic Multidecadal Oscillation
; atmospheric chemistry
; concentration (composition)
; El Nino-Southern Oscillation
; empirical orthogonal function analysis
; greenhouse gas
; Pacific Decadal Oscillation
; sea surface temperature
; surface temperature
; Pacific Ocean
; Pacific Ocean (Northeast)
; Pacific Ocean (Northwest)
英文摘要: The observed global-mean surface temperature (GST) has been warming in the presence of increasing atmospheric concentration of greenhouse gases, but its rise has not been monotonic. Attention has increasingly been focused on the prominent variations about the linear trend in GST, especially on interdecadal and multidecadal time scales. When the sea-surface temperature (SST) and the land- plus-ocean surface temperature (ST) are averaged globally to yield the global-mean SST (GSST) and the GST, respectively, spatial information is lost. Information on both space and time is needed to properly identify the modes of variability on interannual, decadal, interdecadal and multidecadal time scales contributing to the GSST and GST variability. Empirical Orthogonal Function (EOF) analysis is usually employed to extract the space–time modes of climate variability. Here we use the method of pair-wise rotation of the principal components (PCs) to extract the modes in these time-scale bands and obtain global spatial EOFs that correspond closely with regionally defined climate modes. Global averaging these clearly identified global modes allows us to reconstruct GSST and GST, and in the process identify their components. The results are: Pacific contributes to the global mean variation mostly on the interannual time scale through El Nino-Southern Oscillation (ENSO) and its teleconnections, while the Atlantic contributes strongly to the global mean on the multidecadal time scale through the interhemispheric mode called the Atlantic Multidecadal Oscillation (AMO). The Pacific Decadal Oscillation (PDO) has twice as large a variance as the AMO, but its contribution to GST is only 1/10 that of the AMO because of its compensating patterns of cold and warm SST in northwest and northeast Pacific. Its teleconnection pattern, the Pacific/North America (PNA) pattern over land, is also found to be self-cancelling when globally averaged because of its alternating warm and cold centers. The Interdecadal Pacific Oscillation (IPO) is not a separate mode of variability but contains AMO and PDO. It contributes little to the global mean, and what it contributes is mainly through its AMO component. A better definition of a Pacific low-frequency variability is through the IPO Tripole Index (TPI), using difference of averaged SST in different regions of the Pacific. It also has no contribution to the GSST and GST due to the PDO being its main component. © 2017, The Author(s). Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/109140
Appears in Collections: 影响、适应和脆弱性 气候变化事实与影响
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作者单位: Physical Oceanography Laboratory/CIMST, Ocean University of China, Qingdao, 266100, China; Qingdao National Laboratory of Marine Science and Technology, Qingdao, 266100, China; Department of Applied Mathematics, University of Washington, Seattle, WA, United States
Recommended Citation:
Chen X.,Tung K.-K.. Global-mean surface temperature variability: space–time perspective from rotated EOFs[J]. Climate Dynamics,2018-01-01,51(2018-05-06)