DOI: 10.1175/JCLI-D-13-00279.1
Scopus记录号: 2-s2.0-84892448406
论文题名: Statistical parameterization expressing ENSO variability and reversibility in response to CO2 concentration changes
作者: Ohba M. ; Tsutsui J. ; Nohara D.
刊名: Journal of Climate
ISSN: 8948755
出版年: 2014
卷: 27, 期: 1 起始页码: 398
结束页码: 410
语种: 英语
Scopus关键词: Climate change scenarios
; Concentration change
; ENSO
; Global-mean temperature
; Pre-industrial levels
; Statistical modeling
; Subsurface temperature
; Surface temperature changes
; Atmospheric composition
; Atmospheric movements
; Atmospheric pressure
; Atmospheric temperature
; Climate change
; Climate models
; Greenhouse gases
; Parameterization
; Surface properties
; Carbon dioxide
; air-sea interaction
; carbon dioxide
; carbon emission
; climate change
; climate modeling
; concentration (composition)
; El Nino-Southern Oscillation
; greenhouse gas
; parameterization
; sea surface temperature
; statistical analysis
; temperature gradient
; upper ocean
; Pacific Ocean
英文摘要: The degree of reversibility in the behavior of El Ni~no-Southern Oscillation (ENSO) in response to CO2 concentration changes is examined using the air-sea coupled Community Climate SystemModel, version 4. Themodel is run under simple and idealized climate change scenarios where atmospheric CO2 concentration is gradually increased to four times the preindustrial level and then gradually reduced at a similar rate along this trajectory. While the simulated ENSO amplitude is reduced when CO2 concentration increases, the amplitude is enhanced when CO2 decreases. This enhancement occurs with a relative El Niño-like warming of mean sea surface temperature. Most of the El Niño-like warming is attributed to a weakened cold water upwelling in the equatorial eastern Pacific. This weakened cooling is a result of a vertical ocean temperature gradient that is reduced in relation to a lag between subsurface temperature warming and surface temperature change. Fromthese findings, a statistical parameterization expressing ENSO variability is developed in terms of the global-mean surface temperature and the vertical gradient of the global-mean temperature in the upper ocean. Plugging this parameterization into a statistical model of ENSO and combining the latter with a statistical spatial pattern of the ENSO-related temperature anomaly enables the reconstruction of surface temperature variability over North America. This approach can be useful when one assesses future climate changes under various CO2 emission scenarios using very simple models whose outputs are limited to a small number of global-mean variables. © 2014 American Meteorological Society. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/51145
Appears in Collections: 气候变化事实与影响
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作者单位: Central Research Institute of Electric Power Industry, Abiko, Japan
Recommended Citation:
Ohba M.,Tsutsui J.,Nohara D.. Statistical parameterization expressing ENSO variability and reversibility in response to CO2 concentration changes[J]. Journal of Climate,2014-01-01,27(1)