DOI: 10.1175/JCLI-D-14-00604.1
Scopus记录号: 2-s2.0-84944104232
论文题名: Estimating the anthropogenic sea surface temperature response using pattern scaling
作者: Bichet A. ; Kushner P.J. ; Mudryk L. ; Terray L. ; Fyfe J.C.
刊名: Journal of Climate
ISSN: 8948755
出版年: 2015
卷: 28, 期: 9 起始页码: 3751
结束页码: 3763
语种: 英语
Scopus关键词: Atmospheric temperature
; Climate change
; Climate models
; Estimation
; Forecasting
; Monte Carlo methods
; Ocean currents
; Sea ice
; Submarine geophysics
; Surface properties
; Surface waters
; Anthropogenic effects
; Climate prediction
; Coupled models
; Decadal variability
; Ensembles
; Sea surface temperature (SST)
; Oceanography
; air-sea interaction
; anthropogenic effect
; climate prediction
; decadal variation
; ensemble forecasting
; estimation method
; sea surface temperature
; temperature effect
; Arctic Ocean
; Indian Ocean
; Indian Ocean (Tropical)
英文摘要: This study seeks to derive the sea surface temperature (SST) response to anthropogenic forcing from observations over the last century, using simple methods inspired from pattern scaling. As in pattern scaling, the spatial response is assumed to scale with global-mean and annual-mean surface temperature. The long-term aim of this work is to generate anthropogenically forced SST and sea ice patterns for the recent past and near-term future, and use them to force atmosphere-land climate models for attribution and prediction purposes. The present work compares estimation methodologies and, within a Monte Carlo framework based on large initial condition ensembles of climate model simulations, examines the robustness of the patterns obtained. The different methods explored here yield a similar SST spatial response, mostly reflecting the observed SST linear trend map. The different methods nevertheless provide distinctive temporal evolution of the global-mean and annual-mean SST response, which in turn affects the temporal evolution of the global-mean and annual-mean air surface temperature simulated in corresponding prescribed SST simulations. The estimated SST spatial response consists mostly of a warming of the midlatitude coasts near the western boundary currents, the tropical Indian Ocean, and the Arctic Ocean. This pattern generally agrees with previously published observational and modeling studies. Based on Monte Carlo analysis of the large ensembles, it is found that between 36% and 56% of its spatial variance results from anthropogenic forcing. Overall, the work herein provides constraints on the uncertainty associated with the spatial variability of an anthropogenically forced component of climate change derived from observations, which can potentially be used for climate attribution and prediction. © 2015 American Meteorological Society. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/50660
Appears in Collections: 气候变化事实与影响
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作者单位: Department of Physics, University of Toronto, Toronto, ON, Canada; CERFACS/CNRS, URA1875, Toulouse, France; Canadian Centre for Climate Modelling and Analysis, Environment Canada, Victoria, BC, Canada
Recommended Citation:
Bichet A.,Kushner P.J.,Mudryk L.,et al. Estimating the anthropogenic sea surface temperature response using pattern scaling[J]. Journal of Climate,2015-01-01,28(9)