DOI: 10.1175/JCLI-D-14-00740.1
Scopus记录号: 2-s2.0-84934889341
论文题名: Monsoon-induced biases of climate models over the tropical Indian Ocean
作者: Li G. ; Xie S.-P. ; Du Y.
刊名: Journal of Climate
ISSN: 8948755
出版年: 2015
卷: 28, 期: 8 起始页码: 3058
结束页码: 3072
语种: 英语
Scopus关键词: Atmospheric temperature
; Atmospheric thermodynamics
; Climate change
; Errors
; Global warming
; Oceanography
; Surface waters
; Asian summer monsoons
; Climate prediction
; Coupled Model Intercomparison Project
; Interannual variability
; Intergovernmental panel on climate changes
; Multi-model ensemble
; Sea surface temperature (SST)
; Tropical Indian ocean
; Climate models
英文摘要: Long-standing biases of climate models limit the skills of climate prediction and projection. Overlooked are tropical Indian Ocean (IO) errors. Based on the phase 5 of the Coupled Model Intercomparison Project (CMIP5) multimodel ensemble, the present study identifies a common error pattern in climate models that resembles the IO dipole (IOD) mode of interannual variability in nature, with a strong equatorial easterly wind bias during boreal autumn accompanied by physically consistent biases in precipitation, sea surface temperature (SST), and subsurface ocean temperature. The analyses show that such IOD-like biases can be traced back to errors in the South Asian summer monsoon. A southwest summer monsoon that is too weak over the Arabian Sea generates a warm SST bias over the western equatorial IO. In boreal autumn, Bjerknes feedback helps amplify the error into an IOD-like bias pattern in wind, precipitation, SST, and subsurface ocean temperature. Such mean state biases result in an interannual IOD variability that is too strong. Most models project an IOD-like future change for the boreal autumn mean state in the global warming scenario, which would result in more frequent occurrences of extreme positive IOD events in the future with important consequences to Indonesia and East Africa. The Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) characterizes this future IOD-like projection in the mean state as robust based on consistency among models, but the authors' results cast doubts on this conclusion since models with larger IOD amplitude biases tend to produce stronger IOD-like projected changes in the future. © 2015 American Meteorological Society. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/50904
Appears in Collections: 气候变化事实与影响
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作者单位: State Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou, China; Key Laboratory of Meteorological Disaster of Ministry of Education, Nanjing University of Information Science and Technology, Nanjing, China; Scripps Institution of Oceanography, University of California, San Diego, La Jolla, CA, United States; Physical Oceanography Laboratory, Ocean University of China, Qingdao, China; State Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou, China
Recommended Citation:
Li G.,Xie S.-P.,Du Y.. Monsoon-induced biases of climate models over the tropical Indian Ocean[J]. Journal of Climate,2015-01-01,28(8)