DOI: 10.1002/2015MS000459
Scopus记录号: 2-s2.0-84959463858
论文题名: Quantifying contributions of model processes to the surface temperature bias in FGOALS-g2
作者: Liu B ; , Zhou T ; , Lu J
刊名: Journal of Advances in Modeling Earth Systems
ISSN: 19422466
出版年: 2015
卷: 7, 期: 4 起始页码: 1519
结束页码: 1533
语种: 英语
英文关键词: Atmospheric movements
; Climate models
; Heat flux
; Heat transfer
; Latent heat
; Oceanography
; Solar radiation
; Surface properties
; Atmospheric transport
; CFRAM
; Cloud radiative effects
; Model bias
; Nonradiative process
; Process-based
; Sensible and latent heat fluxes
; Surface latent heat fluxes
; Atmospheric temperature
; albedo
; atmospheric transport
; climate feedback
; climate modeling
; decomposition analysis
; land-sea interaction
; latent heat flux
; mixed layer
; quantitative analysis
; radiative transfer
; surface temperature
; water vapor
; Atlantic Ocean
; Atlantic Ocean (North)
; Pacific Ocean
; Pacific Ocean (North)
; Southern Ocean
英文摘要: To quantify the annual mean surface temperature bias due to various processes in Flexible Global Ocean-Atmosphere-Land-System model, Grid point version 2 (FGOALS-g2), the climate feedback-response analysis method (CFRAM) is used to isolate contributions from both radiative and nonradiative processes in the model by comparing the model simulation with ERA-Interim reanalysis. The observed surface temperature bias is decomposed into seven partial temperature biases associated with surface albedo, water vapor, cloud, both surface sensible and latent heat fluxes, land/ocean heat transport processes, and atmospheric transport processes. The global mean cold bias (-1.39 K) is mostly attributed to surface albedo and land/ocean heat transport processes while surface latent heat fluxes tend to weaken this bias. Cloud-induced bias is dominated by shortwave cloud radiative effect (SWCRE) over low-latitudes and longwave cloud radiative effect (LWCRE) over high latitudes. The mixed layer depth (MLD) bias is consistent with the bias due to ocean heat transport over North Pacific, North Atlantic, and the Southern Ocean. On global scale, contributions of radiative processes and nonradiative processes to the total observed cold bias are comparable, but tend to compensate each other over most regions except for the northern high latitudes. We suggest that the improvements in tropical clouds in the model may significantly decrease the global temperature bias through the interaction between clouds and circulation. © 2015. The Authors. Journal of Advances in Modeling Earth Systems published by Wiley Periodicals, Inc. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/75954
Appears in Collections: 影响、适应和脆弱性 气候变化与战略
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作者单位: State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China; University of Chinese Academy of Sciences, Beijing, China; Climate Change Research Center, Chinese Academy of Sciences, Beijing, China; Center for Ocean-Atmospheric Prediction Studies, Florida State University, Tallahassee, FL, United States
Recommended Citation:
Liu B,, Zhou T,, Lu J. Quantifying contributions of model processes to the surface temperature bias in FGOALS-g2[J]. Journal of Advances in Modeling Earth Systems,2015-01-01,7(4)