DOI: 10.1175/JCLI-D-16-0537.1
Scopus记录号: 2-s2.0-85025699403
论文题名: Diagnosis of decadal predictability of Southern Ocean sea surface temperature in the GFDL CM2.1 Model
作者: Zhang L. ; Delworth T.L. ; Jia L.
刊名: Journal of Climate
ISSN: 8948755
出版年: 2017
卷: 30, 期: 16 起始页码: 6309
结束页码: 6328
语种: 英语
Scopus关键词: Atmospheric temperature
; Climate change
; Climate models
; Natural convection
; Spectrum analysis
; Surface properties
; Time series analysis
; Climate impacts
; Climate prediction
; Deep convection
; Deep ocean convection
; FORECAST model
; Internal variability
; Sea surface temperature (SST)
; Southern ocean
; Oceanography
英文摘要: The average predictability time (APT) method is used to identify the most predictable components of decadal sea surface temperature (SST) variations over the Southern Ocean (SO) in a 4000-yr unforced control run of the GFDL CM2.1 model. The most predictable component shows significant predictive skill for periods as long as 20 years. The physical pattern of this variability has a uniform sign of SST anomalies over the SO, with maximum values over the Amundsen-Bellingshausen-Weddell Seas. Spectral analysis of the associated APT time series shows a broad peak on time scales of 70-120 years. This most predictable pattern is closely related to the mature phase of a mode of internal variability in the SO that is associated with fluctuations of deep ocean convection. The second most predictable component of SO SST is characterized by a dipole structure, with SST anomalies of one sign over the Weddell Sea and SST anomalies of the opposite sign over the Amundsen-Bellingshausen Seas. This component has significant predictive skill for periods as long as 6 years. This dipole mode is associated with a transition between phases of the dominant pattern of SO internal variability. The long time scales associated with variations in SO deep convection provide the source of the predictive skill of SO SST on decadal scales. These analyses suggest that if the SO deep convection in a numerical forecast model could be adequately initialized, the future evolution of SO SST and its associated climate impacts are potentially predictable. © 2017 American Meteorological Society. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/48754
Appears in Collections: 气候减缓与适应 气候变化与战略
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作者单位: Atmospheric and Oceanic Science, Princeton University, Princeton, NJ, United States; NOAA, Geophysical Fluid Dynamics Laboratory, Princeton, NJ, United States
Recommended Citation:
Zhang L.,Delworth T.L.,Jia L.. Diagnosis of decadal predictability of Southern Ocean sea surface temperature in the GFDL CM2.1 Model[J]. Journal of Climate,2017-01-01,30(16)